scholarly articles nature vs nurture

Brain development and the nature versus nurture debate

Affiliation.

• 1 Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA. [email protected]
• PMID: 21489380
• DOI: 10.1016/B978-0-444-53884-0.00015-4

Over the past three decades, developmental neurobiologists have made tremendous progress in defining basic principles of brain development. This work has changed the way we think about how brains develop. Thirty years ago, the dominant model was strongly deterministic. The relationship between brain and behavioral development was viewed as unidirectional; that is, brain maturation enables behavioral development. The advent of modern neurobiological methods has provided overwhelming evidence that it is the interaction of genetic factors and the experience of the individual that guides and supports brain development. Brains do not develop normally in the absence of critical genetic signaling, and they do not develop normally in the absence of essential environmental input. The fundamental facts about brain development should be of critical importance to neuropsychologists trying to understand the relationship between brain and behavioral development. However, the underlying assumptions of most contemporary psychological models reflect largely outdated ideas about how the biological system develops and what it means for something to be innate. Thus, contemporary models of brain development challenge the foundational constructs of the nature versus nurture formulation in psychology. The key to understanding the origins and emergence of both the brain and behavior lies in understanding how inherited and environmental factors are engaged in the dynamic and interactive processes that define and guide development of the neurobehavioral system.

Copyright © 2011 Elsevier B.V. All rights reserved.

Publication types

• Research Support, N.I.H., Extramural
• Behavior / physiology*
• Body Patterning
• Brain / embryology*
• Brain / growth & development*
• Brain / physiology
• Environment*
• Inheritance Patterns
• Neural Stem Cells / physiology
• Neuronal Plasticity
• Signal Transduction

Grants and funding

• 1 R01 HD060595/HD/NICHD NIH HHS/United States
• R01-HD25077/HD/NICHD NIH HHS/United States

• Open supplemental data
• Reference Manager
• Simple TEXT file

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Original research article, nature vs. nurture: disentangling the influence of inheritance, incubation temperature, and post-natal care on offspring heart rate and metabolism in zebra finches.

• Centre d’Etudes Biologiques de Chizé, CNRS—La Rochelle Université, Villiers en Bois, France

A historic debate in biology is the question of nature vs. nurture. Although it is now known that most traits are a product of both heredity (“nature”) and the environment (“nurture”), these two driving forces of trait development are rarely examined together. In birds, one important aspect of the early developmental environment is egg incubation temperature. Small changes (<1°C) in incubation temperature can have large effects on a wide-array of offspring traits. One important trait is metabolism, because it is related to life-history traits and strategies, organismal performance, and energetic and behavioral strategies. Although it has been shown that embryonic and post-hatch metabolism are related to egg incubation temperature, little is known about how this may vary as a function of genetic differences or post-hatching environmental conditions. Here, we investigated this question in zebra finches ( Taeniopygia guttata ). We experimentally incubated eggs at two different temperatures: 37.5°C (control), which is optimal for this species and 36.3°C (low), which is suboptimal. We first measured embryonic heart rate as a proxy of embryonic metabolic rate. Then, at hatch, we cross-fostered nestlings to differentiate genetic and pre-hatching factors from post-hatching environmental conditions. When offspring were 30 days-old, we measured their resting metabolic rate (RMR; within the thermoneutral zone) and thermoregulatory metabolic rate (TMR; 12°C; birds must actively thermoregulate). We also measured RMR and TMR of all genetic and foster parents. We found that embryonic heart rate was greater in eggs incubated at the control temperature than those at the low temperature. Further, embryonic heart rate was positively related to genetic father RMR, suggesting that it is both heritable and affected by the pre-natal environment. In addition, we found that post-hatch metabolic rates were positively related to genetic parent metabolic rate, and interactively related to incubation temperature and foster mother metabolic rate. Altogether, this suggests that metabolism and the energetic cost of thermoregulation can be influenced by genetics, the pre-natal environment, and the post-natal environment. Our study sheds light on how environmental changes and parental care may affect avian physiology, as well as which traits may be susceptible to natural selection.

1 Introduction

Whole-organism metabolism is a fundamental aspect animal physiology, and thus understanding the drivers of individual variation in metabolism is crucial ( Burton et al., 2011 ; White and Kearney, 2013 ; Pettersen et al., 2018 ). Resting metabolic rate (RMR) represents an individual’s minimum energy requirements for self-maintenance ( Daan et al., 1990 ; Bryant, 1997 ), excluding physiological processes such as thermoregulation, digestion, and activity ( McNab, 1997 ). RMR is important for understanding basal metabolic rate, and is also related to individual life history traits and strategies, performance, energetic strategies, behavior, reproductive success, and survival ( Careau et al., 2008 ; Biro and Stamps, 2010 ; Williams et al., 2010 ; Careau and Garland, 2012 ; Rønning et al., 2016 ; Auer et al., 2018 ; Pettersen et al., 2018 ). While metabolic rate varies depending on current environmental conditions ( Broggi et al., 2004 ; Norin and Metcalfe, 2019 ), there is evidence that, across taxa, individual differences in metabolic rate are repeatable ( Nespolo and Franco, 2007 ; Careau et al., 2008 ; Broggi et al., 2009 ; Réveillon et al., 2019 ; Baškiera and Gvoždík, 2021 ; Dezetter et al., 2021 ) and heritable (reviewed in Pettersen et al., 2018 ). Further, conditions during early development and parental effects can also have lasting effects on individual metabolism ( Burton et al., 2011 ). For example, in oviparous species, maternal hormone deposition to eggs can affect offspring post-hatch metabolic rate ( Groothuis et al., 2005 ; Tobler et al., 2007 ; Nilsson et al., 2011 ). However, little is known about how different drivers (e.g., heritability and parental effects) may interact to influence metabolism ( Burton et al., 2011 ; White and Kearney, 2013 ; Pettersen et al., 2018 ; McFarlane et al., 2021 ). Understanding the sources of inter-individual variation in metabolism will shed light on how environmental changes, parental care decisions, and natural selection can shape this important aspect of physiology.

In birds, some of the most important sources of variation in offspring physiology arise from parental care decisions. Aside from important maternal effects during egg-laying (e.g., nutrient/hormone transfer to eggs; ( Groothuis et al., 2005 ; Tobler et al., 2007 ; Nilsson et al., 2011 ), two essential ways in which parents must ensure proper offspring development are through egg incubation and post-hatch nestling care. Incubation is necessary for eggs to hatch ( Deeming and Ferguson, 1991 ), but energetically costly and time consuming for parents ( Tinbergen and Williams, 2002 ; Nord and Williams, 2015 ). In turn, incubation investment varies among parents, due to factors such as ambient temperature, clutch size, parental experience, and individual quality ( Aldrich and Raveling, 1983 ; Haftorn and Reinertsen, 1985 ; Conway and Martin, 2000 ; Ardia and Clotfelter, 2007 ; Coe et al., 2015 ; Amininasab et al., 2016 ; Hope et al., 2020 ; Williams et al., 2021 ). This causes incubation temperatures to vary both among and within nests ( Boulton and Cassey, 2012 ; Coe et al., 2015 ; Hope et al., 2021 ). Importantly, small differences in temperature can have large effects on offspring physiology, such as metabolic rate, thermoregulation, glucocorticoid hormone levels, immune function, and telomere length ( Nord and Nilsson, 2011 ; DuRant et al., 2013 ; Hepp et al., 2015 ; Wada et al., 2015 ; Stier et al., 2020 ; Hope et al., 2021 ). Similarly, in altricial species, parental food provisioning is essential for the proper growth and development of offspring. However, parents vary in their nestling provisioning rates due to factors such as food availability, the sex of the parent, parental experience, ambient temperature, brood size, and predation risk ( Wright et al., 1998 ; Wiebe and Neufeld, 2003 ; Barba et al., 2009 ; Low et al., 2012 ; Ghalambor et al., 2013 ), with some evidence that provisioning behavior is repeatable and that some individuals are consistently “good” parents ( Schwagmeyer and Mock, 2003 ). As with incubation temperature, differences in provisioning can affect offspring morphology and physiology. For example, food limitation during nestling development is related to low body masses, slow growth rates, altered glucocorticoid hormone levels, higher metabolic rates, and lower survival ( Lepczyk and Karasov, 2000 ; Killpack and Karasov, 2012 ; Schmidt et al., 2012 ).

There is evidence that genetics, incubation temperature, and post-hatch parental care can influence both juvenile and adult avian metabolic rate. For example, avian RMR has been shown to be repeatable within individuals and heritable through adulthood ( Bech et al., 1999 ; Rønning et al., 2005 , 2007 ; Broggi et al., 2009 ; Nilsson et al., 2009 ). Further, studies have found that eggs incubated at lower temperatures have slower embryonic development and lower embryonic metabolic rates ( DuRant et al., 2011 ; Stier et al., 2020 ) but, after hatching, produce offspring that have higher RMR early in life compared to those incubated at a warmer temperature ( Nord and Nilsson, 2011 ; Wada et al., 2015 ). Moreover, environmental stressors during the post-hatch development, such as glucocorticoid exposure ( Spencer and Verhulst, 2008 ; Dupont et al., 2019 ), food restriction ( Moe et al., 2005 ; Criscuolo et al., 2008 ; Rønning et al., 2009 ; Careau et al., 2014 ), and sibling competition ( Burness et al., 2000 ; Verhulst et al., 2006 ), can have long-lasting effects on offspring RMR. Additionally, another important aspect of metabolism is thermoregulatory metabolic rate (TMR), which is the metabolic rate organisms express under challenging thermal conditions, and represents the metabolic cost associated with thermoregulation ( Broggi et al., 2004 ; Carleton and Rio, 2005 ; Nzama et al., 2010 ; DuRant et al., 2012 ; Dupont et al., 2019 ). Although less-often studied compared to RMR, there is also some evidence that avian TMR can be affected by incubation temperature and the post-hatch environment. For example, one study found that wood ducks ( Aix sponsa ) incubated at a lower temperature had higher TMR than those incubated at a warmer temperature ( DuRant et al., 2012 ). Further, one study found that house sparrows ( Passer domesticus ) with increased glucocorticoid exposure during post-hatch development had lower TMR than control nestlings ( Dupont et al., 2019 ). However, despite the evidence for the influence of genetics and pre- and post-hatch parental effects on both avian RMR and TMR, no study to date has investigated whether these different drivers may interact to affect metabolism.

In this study, we investigated whether genetics, incubation temperature, and/or post-hatch parental care interact to explain individual variation in avian RMR or TMR. To do this, we incubated zebra finch ( T. guttata ) eggs at two different temperatures: 37.5°C (control), which is optimal for this species and 36.3°C (low), which is suboptimal in this species, as shown in other studies ( Wada et al., 2015 ; Berntsen and Bech, 2016 ). During incubation, as a proxy of embryonic metabolic rate, we measured embryonic heart rate ( Sheldon et al., 2018 ). Then, at hatch, we cross-fostered nestlings to decouple genetic and pre-hatching factors from post-hatching environmental conditions. Lastly, we measured the RMR and TMR of all offspring at Day 30 (i.e., nutritional independence), and of all parents after reproduction had ended. Our main hypothesis was that offspring metabolism is shaped through a combination of inheritance, incubation conditions, and post-natal care. We tested the following predictions:

1) Embryonic heart rate and offspring metabolic rate on Day 30 are positively related to the metabolic rate of genetic parents (i.e., metabolic rate is heritable; Rønning et al., 2007 ; Nilsson et al., 2009 ).

2) Lower incubation temperatures lead to slower embryonic heart rates ( Rubin, 2019 ; Stier et al., 2020 ), but higher RMR ( Nord and Nilsson, 2011 ; Wada et al., 2015 ) and TMR ( DuRant et al., 2012 ) at Day 30.

3) We considered the relationship between foster parent and offspring metabolic rate to be representative of the overall influence of the post-hatch environment and predicted that offspring metabolic rate would also be related to the metabolic rate of foster parents.

Along with these predictions, we also tested for interactive effects among our incubation temperature treatment and parental metabolism, with the expectation that offspring metabolic rate and embryonic heart rate may have different relationships with parental metabolic rate, depending on the incubation temperature treatment.

2 Materials and Methods

2.1 general husbandry and breeding.

We used a breeding colony of zebra finches ( T. guttata ; N = 20 pairs; “parents”) housed at the CEBC (CNRS) for this study. We first housed the 40 birds together in an indoor aviary for 10 days and we formed pairs based on mating behaviors that we observed (e.g., singing, proximity, etc.). We then housed pairs in cages (47.5 × 38 × 51 cm) with external nest boxes (12 × 13 × 16 cm). Ambient temperature was kept at a constant 22°C and the photoperiod was set to a 14:10 day:night cycle, for all aspects of the study, including pair formation, reproduction, and nestling rearing. We provided birds with ∼10 g of alfalfa hay every day, and then ∼1 g of coconut fiber once the hay completely covered the bottom of the nest box. We misted pairs with water once per day until their first egg was laid, to stimulate reproduction. We provided birds with ad libitum food (Versele-Laga Prestige Tropical Finches seed mix), water supplemented with vitamins, cuttlefish bone, and grit. We also gave birds ∼2 g of chopped hard-boiled eggs (including the shells) every day from pair formation until nestling Day 30, along with endives and millet sprays once per week ( Olson et al., 2014 ). All procedures in this study were approved by the national ethics committee for animal experimentation under file number APAFIS#23727-2020011311559318.

2.2 Egg Incubation

We checked nest boxes daily at 10:00. Once an egg was found, we marked it with a unique ID using a small marker, weighed it, and placed it in an incubator (Brinsea © Ovation 28 Advance digital egg incubator) at one of two temperatures. We followed an incubation protocol similar to Wada et al. (2015) . The “control” incubator was set at a constant 37.5°C (± 0.1 [SD]), which is likely optimal for zebra finches. The “low” incubator was set at a constant 36.3°C (± 0.1 [SD]), which is within the natural range of zebra finch incubation temperatures, but there is evidence that it produces suboptimal offspring phenotypes in this species ( Wada et al., 2015 ). Both incubators were set at a humidity of 55%. We verified the temperature and humidity by placing iButton © (Hygrochron DS 1923, Maxim Integrated ™ ) temperature loggers inside of each incubator. We randomly assigned the incubation treatment to the first laid egg of each breeding pair, and then systematically alternated among temperature treatments for each subsequent egg for the entire length experiment. Multiple clutches from each breeding pair were used in this study, to attain a sufficient sample size. During artificial incubation, we gave parents fake clay eggs to incubate so that they stayed in the breeding phase. One day before the predicted hatching date (day 13 for “control” eggs and day 14 for “low” eggs), we transferred eggs to a hatcher that was set at a temperature of 37.5°C and 67% humidity.

2.3 Embryonic Heart Rate

Embryonic heart rate is correlated with embryonic oxygen consumption ( Du et al., 2010 ), and thus can be used as a proxy for energy expenditure during embryonic development. We measured embryonic heart rate by placing eggs in the Buddy digital egg monitor (Vetronic Services, Abbotskerswell, Devon, United Kingdom). We considered that a reading was reliable when the curve and heart rate outputs were relatively consistent for ∼10 s ( Sheldon et al., 2018 ). At each timepoint (see below), we took three repeated heart rate measures within 3 min of taking each egg (individually) out of the incubator and noted the time (seconds) that it took to take each measure. If any/all of the readings were unreliable (e.g., due to embryo movement; Sheldon et al., 2018 ), they were excluded from the analyses. All readings were taken in a room at a constant temperature of 22°C. If there was a consistent heart rate reading of “0”, we candled eggs and determined if they were infertile or had died during development.

We measured heart rates of embryos after 11, 12 and 13 days for incubation for “control” eggs and after 12, 13 and 14 days of incubation for “low” eggs. These three measures are hereafter referred to as “readings 1, 2 and 3”. We chose these days because the incubation period of “control” eggs is about 1 day shorter than that of and “low” eggs ( Table 1 ) and, thus, we chose to investigate differences in heart rate among embryos at the same stage of development (i.e., “developmental age”), instead of after the same number of days (i.e., “calendar age”). We validated that our embryonic heart rate results were not driven by differences in eggshell temperature, and that they were not affected by our choice of using “developmental age” instead of “calendar age” (see Supplementary Appendix S1 ). We placed eggs in the hatcher after the final heart rate readings.

TABLE 1 . Summary statistics of hatch success, incubation period, body mass, and metabolic rate.

2.4 Nestling Monitoring

We checked the hatcher for hatching multiple times each day and, at a minimum, once at 9:00 and once at 17:00. Once hatched, we weighed and marked nestlings by removing distinct patches of down feathers ( Adam et al., 2014 ). Then, we cross-fostered nestlings. We gave parents up to two nestlings, which were never from the same incubation treatment, and nestlings were never more than 1 day apart in age. We housed nestlings with their foster parents until independence (i.e., Day 30), and then we conducted the metabolism measurements. Afterward, we housed independent offspring in sex-specific communal cages for use in future studies. We banded nestlings on Day 10 and determined their sex using plumage characteristics on Day 30.

2.5 Metabolism

We quantified energy metabolism in both parents and offspring by measuring oxygen consumption rates using multichannel open-circuit respirometry (Sable Systems Int., Las Vegas, NV, United States; Brischoux et al., 2017 ). We measured offspring when they were 32 ± 2.9 (range: 28–39) days-old, and we measured parents after they had finished reproduction [75 ± 26 days after their last foster nestling reached Day 30 (for those that successfully raised at least one nestling); 102 ± 20 days since their last laid egg (all birds)]. We measured metabolism of each bird twice: once at 32°C (RMR; within the thermoneutral zone; Calder, 1964 ) and once at 12°C (TMR; when birds must actively thermoregulate; Dupont et al., 2019 ), to determine whether incubation temperature might affect energy expenditure during a thermal challenge. Measurements at different temperatures were conducted on consecutive days and the order was randomized among incubation temperature treatments. We weighed birds at ∼20:15 and began respirometry at ∼20:30. Up to 7 birds were measured each night, and the system measured oxygen consumption of each bird for 10 min and systematically alternated among chambers, with 15 min of baseline reading (empty chamber) each time a full cycle was completed. Birds were removed and weighed again at ∼8:30 the next morning. We did not analyze the first 3 h of data because this was the time when birds fasted ( Wada et al., 2015 ). Oxygen flow was set at ∼350 ml/min, and O 2 at 20.95%, which was recalibrated each night.

To calculate metabolic rate, we first chose the value of oxygen consumption for each 10 min run of each individual that was the lowest and most consistent, using the computer software ExpeData (Sable Systems). Then, we calculated metabolic rate using the Hoffman Equation for VO 2 (ml/h), and then corrected for body mass (ml/h/g). Lastly, we calculated the mean VO 2 of all runs of each individual to obtain the final VO 2 value (ml/h/g) for each individual.

2.6 Statistical Analyses

We conducted all statistical analyses using R v 3.5.1 ( R Core Team, 2018 ). We reduced models using stepwise backwards elimination of non-significant terms ( p > 0.10), starting with non-significant interactions. After eliminating the term with the highest p -value, we reran the model and continued this process until only significant ( p < 0.05) or marginally significant (0.05 < p < 0.10) terms remained in the model. Incubation temperature was always treated as a categorical variable. We ensured that all models met the assumptions of normal and homoscedastic residuals by investigating histograms of residuals, normal quantile plots, and fitted vs. residuals plots. We verified that models met the assumption of non-multicollinearity by investigating the variance inflation factors ( vif ). Further, all continuous independent variables that were used in interactions were scaled and centered to reduce multicollinearity. We used the package lme4 ( Bates et al., 2015 ) for mixed effects models and emmeans ( Lenth, 2018 ) for post-hoc tests, including slope comparisons for interactions. p -values were calculated using the Anova function using the car ( Fox and Weisberg, 2011 ) package. R 2 values for mixed effects models were calculated using the MuMln package ( Bartoń, 2018 ). Figures were created using the plyr ( Wickham, 2011 ) and ggplot2 ( Wickham, 2016 ) packages. Two male parents died for reasons unrelated to the experiment before parental metabolic rates were measured, and thus their RMR, TMR, and ΔMR were not able to be included in the analyses. Neither of these males was a genetic father to any offspring that lived until Day 30 in this study, and only one of these males was a foster father to a single individual that lived until Day 30.

First, to determine whether embryonic heart rate was related to incubation temperature and/or parent metabolism, we built one linear mixed effect model with heart rate as the dependent variable. The independent variables were incubation temperature, reading (1, 2 or 3), the time it took to take the measurement (seconds), the RMR of both the genetic mother and father, along with all two-way interactions with incubation temperature. Parent TMR was not included in this model because 1) we predicted only that parental RMR would be related with embryonic metabolism, measured when embryos were at warm temperatures (i.e., incubation) and 2) parent TMR and RMR were correlated ( r = 0.42; p < 0.01), and thus including them both in the model would increase multicollinearity. We also included whether the egg hatched or not as an independent variable, and egg mass as a covariate. Egg ID was included as a random effect to control for repeated measures.

Second, to determine whether offspring metabolism was related to incubation temperature and the temperature at which the measurement was taken, we built one linear mixed effects model. Offspring metabolism (VO 2, ml/h/g) was the dependent variable, and it was log-transformed to meet model assumptions. The independent variables were incubation temperature, the temperature of the measurement (12°C or 32°C), and their interaction. Sex and age were also included as covariates, as well as the interaction between incubation temperature and sex. Individual ID, genetic parent ID, and foster parent ID were included as random effects to account for repeated measures within individuals and among siblings.

Next, we determined whether offspring metabolism was related to parental metabolism. First, we calculated heritability ( h 2 ) as the slope of the regression between the mean value of genetic parent metabolism (either RMR or TMR) and offspring metabolism ( Åkesson et al., 2008 ; Wray and Visscher, 2008 ). Then, to examine relationships among all parents (genetic and foster; separated by sex), and to test whether there was an interactive effect of incubation temperature and parental metabolism, we built three linear models. For all models, the dependent variable was offspring metabolism (VO 2, ml/h/g) and the independent variables were incubation temperature, the metabolism of the genetic mother, genetic father, foster mother, and foster father, along with all two-way interactions with incubation temperature. The difference among the three models was that the first included only RMR data (both parents and offspring), the second included only TMR data, and the third used the difference between TMR and RMR (i.e., additional amount of energy expended during thermoregulation; hereafter ΔMR) for all individuals.

Lastly, to determine whether embryonic heart rate and offspring metabolism (at Day 30) were correlated within individuals, we built one linear mixed effect model. The dependent variable was embryonic heart rate, and only individuals that lived until the metabolic measurement (∼Day 30) were included in the model. The independent variables were incubation temperature, reading (1, 2 or 3), offspring RMR, and all two-way interactions with incubation temperature. Offspring TMR was not included in this model because 1) we predicted only that offspring RMR would be related with embryonic metabolism, measured when embryos were at warm temperatures (i.e., incubation) and 2) offspring TMR and RMR were correlated ( r = 0.73; p < 0.001), and thus including them both in the model would increase multicollinearity. We also included sex and its interaction with incubation temperature in this analysis because, contrary to the first analysis, we had data on the sex of all individuals (i.e., only individuals that lived until Day 30 were included). The time it took to take the measurement (seconds) and egg mass were also included as covariates. Egg ID, genetic parent ID, and foster parent ID were included as random effects to control for repeated measures among siblings.

3.1 Hatching Success, Incubation Period, and Body Mass

Summary statistics for hatching success, incubation period, and nestling body mass (Days 0 and 30) are reported in Table 1 . There were no differences in hatching success, body mass at Day 0, or body mass at Day 30 between incubation temperature treatment groups (all p > 0.25; simple linear models). However, eggs incubated at the lower temperature had a longer incubation period than those incubated at the control temperature ( p < 0.001).

3.2 Embryonic Heart Rate: Relationship With Incubation Temperature and Parental Metabolism

Embryonic heart rate was related to both incubation temperature and parent metabolic rate. We found that heart rate was greater in embryos from the control treatment compared to the low treatment ( p < 0.001; Table 2 ; Figure 1 ), and that heart rate increased throughout the course of incubation (reading: p < 0.001; Table 2 ). There was an interactive effect of incubation temperature and reading on heart rate ( p < 0.001; Table 2 ), and post-hoc tests revealed significant differences for all pairwise comparisons (all p < 0.001), except between the heart rate of control embryos on days 11 and 12 ( p > 0.99; Figure 1 ). Although embryonic heart rate was significantly related to mother RMR in the full model, it was not retained in the final model ( Table 2 ; Figure 2A ). However, embryonic heart rate was positively correlated with father RMR ( p = 0.0003; Table 2 ; Figure 2B ). There was also a relationship between whether or not the egg hatched and its heart rate ( p = 0.049; Table 2 ), where embryos with greater heart rates were more likely to hatch. Further, heart rate increased as egg mass increased ( p < 0.001; Table 2 ), and heart rate decreased with the time that it took to take the measurement ( p < 0.001; Table 2 ).

TABLE 2 . Full and reduced models investigating the relationship of embryonic heart rate with incubation temperature and parental metabolism.

FIGURE 1 . Zebra finch embryonic heart rate (beats per minute; bpm) at three different time points during development and incubated at two different temperatures (black = control; gray = low). To correct for different developmental rates, readings were taken on control eggs after (1) 11, (2) 12, and (3) 13 days of incubation, while readings were taken on low eggs after (1) 12, (2) 13, and (3) 14 days. Mean ± SE are shown.

FIGURE 2 . The relationships between egg heart rate (bpm) and (A) genetic mother RMR and (B) genetic father RMR. Eggs were incubated at two different temperatures (black = control; gray = low). All egg heart rate measurements are shown. Regression lines are included only for significant relationships.

3.3 Offspring Metabolic Rate: Relationship With Incubation Temperature and Parental Metabolism

Although we found no differences in metabolic rate among offspring incubated at different temperatures or between sexes ( Table 3 ), we found that offspring metabolism was related to the temperature at which the measurement was taken. As expected, metabolism was greater when the measurement was taken at 12°C (TMR) than at 32°C (RMR) ( p < 0.0001; Table 3 ; Figure 3 ).

TABLE 3 . Full and reduced models investigating the effects of incubation temperature and temperature of measurement on offspring metabolism at Day 30.

FIGURE 3 . Zebra finch metabolic rate (VO 2 ; ml/h/g) measured at two different temperatures (black = TMR: 12°C; gray = RMR: 32°C). Individuals were measured at Day 30 and had hatched from eggs incubated at two different temperatures (i.e., control or low).

The regression of mean genetic parent RMR with offspring RMR revealed that RMR was significantly heritable [ h 2 = 0.53 ± 0.22 (SE), p = 0.02]. When we examined the relationships of all parents (genetic and foster) as individual factors, we found that genetic mother RMR was positively related to offspring RMR ( p = 0.014; Table 4 ; Figure 4A ). However, offspring RMR was not related to any other parental RMR, and there were no interactive relationships with incubation temperature ( Table 4 ; Figure 4B–D ).

TABLE 4 . Full and reduced models investigating the relationship of offspring metabolism at Day 30 with interactions between incubation temperature and parental metabolism.

FIGURE 4 . Relationship between offspring RMR on Day 30 and the RMR of the (A) genetic mother, (B) genetic father, (C) foster mother, and (D) foster father. Offspring had been incubated at two different temperatures as eggs (black = control; gray = low). Regression lines are included only for significant relationships.

The regression of mean genetic parent TMR with offspring TMR revealed that the heritability of TMR was not statistically significant [ h 2 = 0.38 ± 0.28 (SE), p = 0.19]. However, when examining parents separately (i.e., all genetic and foster parents as separate independent variables), we found a trend that genetic father TMR was positively related to offspring TMR ( p = 0.093; Table 4 ). Further, there was an interactive effect of incubation temperature and foster mother TMR on offspring TMR ( p = 0.033; Table 4 ), where the TMR of offspring from the control group was not related to foster mother TMR (slope estimate: 0.022; confidence interval: −0.32 to 0.37) while the TMR of offspring from the low group was negatively related to the TMR of their foster mother (slope estimate: −0.56; confidence interval: −0.95 to −0.16). There were no relationships between offspring TMR and their genetic mother or foster father ( Table 4 ).

Similar to TMR, the heritability of ΔMR (i.e., TMR−RMR) was not statistically significant [ h 2 = 0.18 ± 0.27 (SE), p = 0.51]. However, when examining parents separately, although there was no relationship between genetic mother ΔMR and offspring ΔMR ( Table 4 ; Figure 5A ), we found that there was a significant positive relationship between genetic father ΔMR and offspring ΔMR ( p = 0.049; Table 4 ; Figure 5B ). There was also an interactive effect of incubation temperature and foster mother ΔMR on offspring ΔMR ( p = 0.025; Table 4 ; Figure 5C ). This relationship mimicked that of TMR: the ΔMR of offspring from the control group was not related to foster mother ΔMR (slope estimate: −0.12; confidence interval: −0.34 to 0.11; Figure 5C ) while the ΔMR of offspring from the low group was negatively related to the ΔMR of their foster mother (slope estimate: −0.55; confidence interval: −0.85 to −0.25; Figure 5C ). There was no relationship between offspring ΔMR and that of their foster father ( Table 4 ; Figure 5D ).

FIGURE 5 . Relationship between the difference in offspring TMR and RMR (ΔMR) on Day 30 and the ΔMR of the (A) genetic mother, (B) genetic father, (C) foster mother, and (D) foster father. Offspring had been incubated at two different temperatures as eggs (black = control; gray = low). Regression lines are included only for significant relationships.

3.4 Embryonic Heart Rate and Metabolic Rate: Relationship Within Individuals

Embryonic heart rate and offspring RMR were not correlated within individuals ( Table 5 ). Further, there were no significant interactive effects of incubation temperature and RMR. The only terms that remained in the model ( Table 5 ) were incubation temperature ( p < 0.001), reading ( p < 0.001), time to take the measurement ( p < 0.001), and incubation temperature x reading ( p < 0.001), as already found previously in Section 3.2.

TABLE 5 . Full and reduced models investigating the relationship between embryonic heart rate and Day 30 metabolism.

4 Discussion

Here, we manipulated the developmental environment of zebra finches to disentangle the impact of inheritance, incubation temperature, and post-hatch rearing conditions (i.e., cross-fostering) on the energy metabolism of embryos and offspring at nutritional independence (i.e., Day 30). We found that embryonic heart rate, a proxy of embryonic metabolism, was positively related to genetic father RMR and that embryos incubated at the higher incubation temperature had faster heart rates than those incubated at the lower temperature. Further, we found evidence that post-hatch offspring RMR is heritable and has a positive correlation with genetic mother RMR, although we found no relationship between offspring RMR and either foster parent RMR or incubation temperature. Lastly, we found that the metabolic cost of thermoregulation (i.e., TMR and ΔMR) had a lower heritability than RMR, but was positively related to genetic father TMR and ΔMR. Interestingly, foster mother TMR and ΔMR were negatively correlated with offspring TMR and ΔMR, respectively, but this relationship was only apparent when offspring were incubated at the lower temperature. This suggests that there are combined effects of the pre-natal environment and post-natal parental care on the metabolic cost of thermoregulation.

4.1 Effects of Incubation Temperature

As predicted, eggs that were incubated at the lower temperature had slower embryonic heart rates than those incubated at the higher temperature. Because embryonic heart rate should be an indicator of embryonic metabolism ( Du et al., 2010 ; Sheldon et al., 2018 ), this suggests that low incubation temperatures lead to a lower embryonic metabolic rate. Our results agree with two other studies that have investigated the relationship between incubation temperature and embryonic heart rate ( Rubin, 2019 ; Stier et al., 2020 ), and with one study that found that wood duck ( Aix sponsa ) eggs incubated at lower temperatures had lower daily embryonic oxygen consumption compared to those incubation at higher temperatures ( DuRant et al., 2011 ). This lower energy expenditure during embryonic development should be related to slower developmental rates ( Vedder et al., 2017 ; Sheldon and Griffith, 2018 ). Indeed, we found that eggs incubated at the lower temperature had a longer developmental duration (i.e., incubation period) than those incubated at the higher temperature ( Table 1 ). Importantly, we still found a difference in embryonic heart rate between incubation temperatures when we corrected for differences in eggshell temperature and differences in developmental rate (i.e., developmental age vs. calendar age; see Supplementary Material ). This suggests that incubation temperature alters physiology during development, more so than just a linear relationship with current temperature or developmental rate.

We predicted that offspring incubated at the low temperature would have greater post-hatch metabolic rates than those incubated at the control temperature because previous studies have found this effect of incubation temperature on both RMR ( Nord and Nilsson, 2011 ; Wada et al., 2015 ) and TMR ( DuRant et al., 2012 ) in birds. However, contrary to our predictions, offspring metabolic rate (RMR and TMR) was not affected by our incubation temperature treatments (control: 37.5°C; low: 36.3°C). This disagrees with some other avian studies. For example, Nord and Nilsson (2011) found that 14-day-old blue tits ( Cyanistes caeruleus ) incubated at a low temperature had higher RMR than those incubated at a warmer temperature and DuRant et al. (2012) found that 1-day-old wood ducks ( Aix sponsa ) incubated at a lower temperature had higher TMR than those incubated at a warmer temperature. To date, no study has investigated the effect of incubation temperature on zebra finch TMR, and two studies have examined the effects of incubation temperature on zebra finch RMR, with conflicting results. Supporting our findings, Berntsen and Bech (2021) found no difference in RMR among zebra finches that were incubated at 35.9°C and 37.9°C, measured at 15 and 45 days-old. In contrast, Wada et al. (2015) found that 25-day-old zebra finches incubated at 36.2°C had a higher RMR than those incubated at 37.4°C, although this effect was only found in females. In our study, we did not find an effect of sex on metabolic rate. In light of these conflicting results among species, it is possible that the effect of incubation temperature on metabolic rate is species-specific. For example, zebra finches may be a species that is more resistant to small changes in the embryonic thermal environment, and offspring develop similar physiological traits regardless of their developmental conditions. It is also possible that metabolic rate is more influenced by inheritance than by either the early developmental environment or sex, which could explain differences among zebra finch studies. Indeed, we found evidence that both RMR and TMR are heritable (see below). If our breeding parents displayed more genetic variation than those in the study of Wada et al. (2015) , this could have masked any effects of incubation temperature and could explain the difference in results of our two studies. It should also be noted that there was relatively low hatching success in our study, although it was within the range of hatching success found in other captive zebra finch studies (e.g., von Engelhardt et al., 2004 ; Von Engelhardt et al., 2006 ; Criscuolo et al., 2011 ; Winter et al., 2013 ). Nevertheless, we cannot exclude the possibility that there was a selective process during hatching, and that all offspring that succeeded to hatch had similar metabolic rates, regardless of incubation temperature.

4.2 Relationship With Genetic Parents

Embryonic heart rate was positively related to genetic father RMR, suggesting that there could be a genetic component to embryonic metabolism. Although there is evidence that embryonic heart rate and metabolism vary among different genetic lines in poultry ( Druyan, 2010 ), and that there are significant among-clutch differences in embryonic heart rate in wild zebra finches ( Sheldon et al., 2018 ), this is the first study to our knowledge that has explicitly investigated the relationship between parental and embryonic metabolism in birds. Although the correlation between genetic parent metabolism and embryonic heart rate could also be due to maternal effects during egg formation, such as egg yolk composition ( Ho et al., 2011 ), the relationship between embryonic heart rate and genetic mother RMR was not significant. In contrast, because the relationship with genetic father RMR was statistically significant, this suggests that maternal effects may not be as important as genetics for determining embryonic metabolism in zebra finches.

As predicted, we found evidence that offspring RMR was highly heritable ( h 2 = 0.53). This agrees with other studies that show that RMR is a heritable trait. For example, both Rønning et al. (2007) and Nilsson et al. (2009) measured RMR heritability by using restricted maximum likelihood to compare RMR among siblings and found evidence that RMR was heritable in zebra finches ( h 2 = 0.25) and blue tits ( h 2 = 0.59), respectively. Further, using methods similar to that of our study (i.e., parent-offspring regression), Bushuev et al. (2011) found evidence for heritability of RMR ( h 2 = 0.43) in pied flycatchers ( Ficedula hypoleuca ). Further in line with our results, Bushuev et al. (2011) found that offspring RMR was correlated with genetic parent RMR, but not foster parent RMR. The relationship between genetic parent and offspring RMR that we found in this study could also be due to non-genetic maternal effects, such as hormone deposition to the egg. Indeed, in contrast to what we found for embryonic heart rate, when we examined the RMR of the genetic mother and genetic father as separate factors, we only found a relationship between offspring RMR and genetic mother RMR, and not genetic father RMR. This suggests that pre-incubation maternal effects may play a large role in determining post-hatch offspring RMR. For example, zebra finch eggs with higher testosterone concentrations produce nestlings and adults with higher RMR ( Tobler et al., 2007 ; Nilsson et al., 2011 ). If the mothers with higher RMR in our study also deposited more testosterone into their eggs, this could partly explain the relationship that we found between parent and offspring RMR.

In comparison to RMR, the metabolic cost of thermoregulation (i.e., TMR and ΔMR) was less heritable. It may be expected that TMR would have a lower heritability than RMR because it may be more variable due to its dependence on the insulation capacity of plumage. For example, the body feathers of juvenile birds have different structural properties than those of adult birds ( Butler et al., 2008 ), which could mask relationships between the TMR of parents and young offspring. However, although the h 2 of TMR ( h 2 = 0.38) and ΔMR ( h 2 = 0.18) were not statistically significant, the h 2 of TMR was still within the range of those found for RMR (see above). Further, offspring TMR tended to be positively related to genetic father TMR, and offspring ΔMR was positively related to genetic father ΔMR. This is the first evidence that we are aware of for the heritability of TMR or ΔMR, and suggests that the metabolic expenditure associated with thermoregulation could be shaped by natural selection. However, in contrast to RMR, we found little evidence for non-genetic maternal effects because, when genetic mother and genetic father were tested as separate factors, genetic mother TMR and ΔMR were not related to that of their offspring. Thus, any non-genetic maternal effect that may have influenced RMR either did not translate into differences in thermoregulatory capacity, or was masked by other driving factors (e.g., post-hatch environment; see below).

4.3 Relationship With Foster Parents

Although there were no relationships between foster parent and offspring RMR, we found that foster mother TMR and ΔMR were negatively related to that of their foster offspring, but only for offspring in the low treatment. This suggests that the impact of foster mother metabolism, and thus post-hatch parental care, is not on RMR, but rather on the ability of offspring to increase their metabolic rate when faced with a thermal energetic challenge. Thus, the ability of parents to increase their metabolic rate in response to an energetic challenge may be important for effective post-hatch parental care. Because most studies focus on RMR, our results call for future studies to focus more on TMR.

Specifically, we found that the more energy that foster mothers expended on thermoregulation, the less energy that their foster offspring expended on thermoregulation. It is possible that this relationship can be explained by differences in nestling provisioning. For example, foster mothers with a high metabolic rate should also have a high investment in parental care ( Daan et al., 1990 ; Koteja, 2004 ; Sadowska et al., 2013 ), and provide a better developmental environment for their offspring (e.g., more food provisioning; Nilsson, 2002 ). In zebra finches, a greater food supply during nestling development, as opposed to food restriction, is related to lower offspring metabolic rate later in life ( Criscuolo et al., 2008 ; Careau et al., 2014 ). Thus, this could explain the negative relationship that we found between foster mother and offspring TMR and ΔMR. In our study, offspring growth rate between Day 0 and Day 30 was not correlated with foster mother TMR ( p = 0.9), and thus we did not find evidence to support the hypothesis that foster mother TMR is positively related to food provisioning and/or better parental care. However, we did not measure parental care behavior (i.e., provisioning rates) in this study, and thus future studies are needed to determine whether there is a relationship between parental TMR and nestling provisioning rates, along with offspring growth rates and metabolism.

It is important to note that the relationships between foster mother and offspring TMR and ΔMR were only present in offspring incubated at the low temperature, and not the control temperature. This suggests that the impact of post-hatch care (e.g., nestling provisioning) is dependent on the quality of pre-natal care (i.e., incubation temperature). It is possible that offspring incubated at the control temperature are more resistant to differences in their post-hatch environment than those incubated at the low temperature, although little is known about how incubation temperature may influence trait plasticity or canalization. Future research is needed to investigate how different thermal environments shape avian thermoregulatory ability across generations, especially in the context of acclimation and adaptation in response to climate change ( Nord and Giroud, 2020 ).

4.4 Relationship Between Heart Rate, Hatch Success, and Metabolic Rate Within Individuals

Embryonic heart rate is important because it can be used as a proxy for embryonic metabolic rate ( Du et al., 2010 ), and can also provide insights into developmental rate, hatchling phenotype, and the effects of environmental stressors (reviewed in Sheldon et al., 2018 ) . Contrary to what we expected, we did not find that embryonic heart rate was related to offspring RMR at Day 30. However, to our knowledge, this is the first study that has investigated whether there is a relationship between embryonic heart rate and offspring metabolism later in life. Our results suggest that individual metabolic rate can change throughout different stages of development, and that embryonic heart rate cannot be used to predict later-life metabolic rate in zebra finches. Indeed, studies that have found a positive relationship between heart rate and metabolic rate measured these two traits at the same developmental stage (i.e., embryonic; Du et al., 2010 ; Ide et al., 2017 ; Goodchild et al., 2020 ), and one study did not find a relationship between heart rate and metabolism even when measured at the same developmental stage (i.e., embryonic and hatching; Sartori et al., 2017 ). Similarly, one study on zebra finches found no relationship between embryonic heart rate and post-hatch growth rate or activity levels ( Sheldon and Griffith, 2018 ). Thus, it appears that embryonic heart rate may not be able to be extrapolated to phenotypic differences later in life.

However, when we investigated an endpoint closer to embryonic development—hatch success—we did find a relationship with embryonic heart rate. Eggs that hatched had greater embryonic heart rates than those that did not hatch, suggesting that heart rate may be an indicator of embryo quality or hatching probability. Although heart rate has been used in other studies to predict hatching date or to confirm embryonic mortality (reviewed in Sheldon et al., 2018 ), this is the first study to our knowledge that has explicitly linked the magnitude of embryonic heart rate to hatching probability. Because all individuals that hatch also have high heart rates as embryos, this could create a selective process for a particular metabolic functioning. It is possible that this could mask potential effects of the incubation treatment or parental care on offspring metabolic rate, and could also explain why we did not find some of the relationships that we had predicted (e.g., effect of incubation temperature on RMR, relationship with foster parent RMR).

5 Conclusion

In this study, we show that avian metabolic rate throughout development, from the embryo to nutritional independence, is related to parental inheritance, the pre-hatch environment (i.e., incubation temperature), and post-hatch conditions (i.e., foster parent). Revealing how these different factors are related to RMR and TMR sheds light on how metabolism and the energetic cost of thermoregulation can be shaped by environmental changes, parental care decisions, and natural selection. Although most studies to date focus on RMR, our study reveals important relationships with TMR, which could be particularly important in the context of climate change for understanding how the early thermal environment and parental care affect thermoregulatory ability, and the possibility that thermoregulatory ability can be shaped by natural selection. More work is needed to determine if the differences in RMR and TMR that we found in this study have effects on short- or long-term offspring fitness.

Data Availability Statement

The raw data supporting the conclusion of this article will be made available by the authors, without undue reservation.

Ethics Statement

The animal study was reviewed and approved by the Autorisation de Projet Utilisant des Animaux à des Fins Scientifiques under file number APAFIS#23727-2020011311559318.

Author Contributions

SH and FA contributed to the conception of the study. SH, OL and FA designed the study methods. SH and LS collected the data. SH performed the analyses and wrote the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.

This study is based on work funded by a Fyssen Foundation Post-doctoral Study Grant (to SH), the CPER ECONAT, the CNRS, and the Agence Nationale de la Recherche (ANR project URBASTRESS, ANR-16-CE02-0004-01, and ANR project VITIBIRD) (to FA).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

We thank Lucie Michel, Clémence Furic, and Elsa Daniaud for help with animal husbandry and experimental procedures and Sophie Dupont for help with respirometry. We also thank Stephen Ferguson and Ila Mishra for reviewing the manuscript and for their helpful comments.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fphys.2022.892154/full#supplementary-material

Adam I., Scharff C., Honarmand M. (2014). Who Is Who? Non-invasive Methods to Individually Sex and Mark Altricial Chicks. J. Vis. Exp. 87, 51429. doi:10.3791/51429

PubMed Abstract | CrossRef Full Text | Google Scholar

Åkesson M., Bensch S., Hasselquist D., Tarka M., Hansson B. (2008). Estimating Heritabilities and Genetic Correlations: Comparing the ‘Animal Model’ with Parent-Offspring Regression Using Data from a Natural Population. PLOS ONE 3, e1739. doi:10.1371/journal.pone.0001739

Aldrich T. W., Raveling D. G. (1983). Effects of Experience and Body Weight on Incubation Behavior of Canada Geese. Auk 100, 670–679. doi:10.1093/auk/100.3.670

CrossRef Full Text | Google Scholar

Amininasab S. M., Kingma S. A., Birker M., Hildenbrandt H., Komdeur J. (2016). The Effect of Ambient Temperature, Habitat Quality and Individual Age on Incubation Behaviour and Incubation Feeding in a Socially Monogamous Songbird. Behav. Ecol. Sociobiol. 70, 1591–1600. doi:10.1007/s00265-016-2167-2

Ardia D. R., Clotfelter E. D. (2007). Individual Quality and Age Affect Responses to an Energetic Constraint in a Cavity-Nesting Bird. Behav. Ecol. 18, 259–266. doi:10.1093/beheco/arl078

Auer S. K., Dick C. A., Metcalfe N. B., Reznick D. N. (2018). Metabolic Rate Evolves Rapidly and in Parallel with the Pace of Life History. Nat. Commun. 9, 14. doi:10.1038/s41467-017-02514-z

Barba E., Atiénzar F., Marín M., Monrós J. S., Gil‐Delgado J. A. (2009). Patterns of Nestling Provisioning by a Single‐prey Loader Bird, Great Tit Parus Major . Bird Study 56, 187–197. doi:10.1080/00063650902792049

Bartoń K. (2018). MuMIn: Multi-Model Inference . R package version 1.42.1. Available at: https://CRAN.R-project.org/package=MuMIn .

Google Scholar

Baškiera S., Gvoždík L. (2021). Repeatability and Heritability of Resting Metabolic Rate in a Long-Lived Amphibian. Comp. Biochem. Physiol. A: Mol. Integr. Physiol. 253, 110858. doi:10.1016/j.cbpa.2020.110858

Bates D., Mächler M., Bolker B., Walker S. (2015). Fitting Linear Mixed-Effects Models Usinglme4. J. Stat. Soft. 67, 1–48. doi:10.18637/jss.v067.i01

Bech C., Langseth I., Gabrielsen G. W. (1999). Repeatability of Basal Metabolism in Breeding Female Kittiwakes Rissatridactyla. Proc. R. Soc. Lond. B 266, 2161–2167. doi:10.1098/rspb.1999.0903

Berntsen H. H., Bech C. (2016). Incubation Temperature Influences Survival in a Small Passerine Bird. J. Avian Biol. 47, 141–145. doi:10.1111/jav.00688

Berntsen H. H., Bech C. (2021). Incubation Temperature and Physiological Aging in the Zebra Finch. PloS one 16, e0260037. doi:10.1371/journal.pone.0260037

Biro P. A., Stamps J. A. (2010). Do consistent Individual Differences in Metabolic Rate Promote Consistent Individual Differences in Behavior? Trends Ecol. Evol. 25, 653–659. doi:10.1016/j.tree.2010.08.003

Boulton R. L., Cassey P. (2012). How Avian Incubation Behaviour Influences Egg Surface Temperatures: Relationships with Egg Position, Development and Clutch Size. J. Avian Biol. 43, 289–296. doi:10.1111/j.1600-048X.2012.05657.x

Brischoux F., Meillère A., Dupoué A., Lourdais O., Angelier F. (2017). Traffic Noise Decreases Nestlings' Metabolic Rates in an Urban Exploiter. J. Avian Biol. 48, 905–909. doi:10.1111/jav.01139

Broggi J., Orell M., Hohtola E., Nilsson J.-Å. (2004). Metabolic Response to Temperature Variation in the Great Tit: an Interpopulation Comparison. J. Anim. Ecol. 73, 967–972. doi:10.1111/j.0021-8790.2004.00872.x

Broggi J., Hohtola E., Koivula K., Orell M., Nilsson J. k. (2009). Long-term Repeatability of winter Basal Metabolic Rate and Mass in a Wild Passerine. Funct. Ecol. 23, 768–773. doi:10.1111/j.1365-2435.2009.01561.x

Bryant D. M. (1997). Energy Expenditure in Wild Birds. Proc. Nutr. Soc. 56, 1025–1039. doi:10.1079/PNS19970107

Burness G. P., McClelland G. B., Wardrop S. L., Hochachka P. W. (2000). Effect of Brood Size Manipulation on Offspring Physiology: an experiment with Passerine Birds. J. Exp. Biol. 203, 3513–3520. doi:10.1242/jeb.203.22.3513

Burton T., Killen S. S., Armstrong J. D., Metcalfe N. B. (2011). What Causes Intraspecific Variation in Resting Metabolic Rate and what Are its Ecological Consequences? Proc. R. Soc. B. 278, 3465–3473. doi:10.1098/rspb.2011.1778

Bushuev A. V., Kerimov A. B., Ivankina E. V. (2011). Estimation of Heritability and Repeatability of Resting Metabolic Rate in Birds by the Example of Free-Living Pied Flycatchers Ficedula Hypoleuca (Aves: Passeriformes). Biol. Bull. Rev. 1, 26–46. doi:10.1134/s2079086411010026

Butler L. K., Rohwer S., Speidel M. G. (2008). Quantifying Structural Variation in Contour Feathers to Address Functional Variation and Life History Trade-Offs. J. Avian Biol. 39, 629–639. doi:10.1111/j.1600-048x.2008.04432.x

Calder W. A. (1964). Gaseous Metabolism and Water Relations of the Zebra Finch, Taeniopygia Castanotis. Physiol. Zoolog. 37, 400–413. doi:10.1086/physzool.37.4.30152758

Careau V., Garland T. (2012). Performance, Personality, and Energetics: Correlation, Causation, and Mechanism. Physiol. Biochem. Zool. 85, 543–571. doi:10.1086/666970

Careau V., Thomas D., Humphries M. M., Réale D. (2008). Energy Metabolism and Animal Personality. Oikos 117, 641–653. doi:10.1111/j.0030-1299.2008.16513.x

Careau V., Buttemer W. A., Buchanan K. L. (2014). Early-Developmental Stress, Repeatability, and Canalization in a Suite of Physiological and Behavioral Traits in Female Zebra Finches. Integr. Comp. Biol. 54, 539–554. doi:10.1093/icb/icu095

Carleton S. A., Rio C. M. d. (2005). The Effect of Cold-Induced Increased Metabolic Rate on the Rate of 13C and 15N Incorporation in House Sparrows ( Passer domesticus ). Oecologia 144, 226–232. doi:10.1007/s00442-005-0066-8

Coe B. H., Beck M. L., Chin S. Y., Jachowski C. M. B., Hopkins W. A. (2015). Local Variation in Weather Conditions Influences Incubation Behavior and Temperature in a Passerine Bird. J. Avian Biol. 46, 385–394. doi:10.1111/jav.00581

Conway C. J., Martin T. E. (2000). Effects of Ambient Temperature on Avian Incubation Behavior. Behav. Ecol. 11, 178–188. doi:10.1093/beheco/11.2.178

Criscuolo F., Monaghan P., Nasir L., Metcalfe N. B. (2008). Early Nutrition and Phenotypic Development: ‘catch-Up’ Growth Leads to Elevated Metabolic Rate in Adulthood. Proc. R. Soc. B. 275, 1565–1570. doi:10.1098/rspb.2008.0148

Criscuolo F., Monaghan P., Proust A., Škorpilová J., Laurie J., Metcalfe N. B. (2011). Costs of Compensation: Effect of Early Life Conditions and Reproduction on Flight Performance in Zebra Finches. Oecologia 167, 315–323. doi:10.1007/s00442-011-1986-0

Daan S., Masman D., Groenewold A. (1990). Avian Basal Metabolic Rates: Their Association with Body Composition and Energy Expenditure in Nature. Am. J. Physiol.-Regul. Integr. Comp. Physiol. 259, R333–R340. doi:10.1152/ajpregu.1990.259.2.R333

Deeming D. C., Ferguson M. W. J. (1991). “Physiological Effects of Incubation Temperature on Embryonic Development in Reptiles and Birds,” in Egg Incubation: Its Effects on Embryonic Development in Birds and Reptiles . Editors D. C. Deeming, and M. W. Ferguson (Cambridge: Cambridge University Press ), 147–172. doi:10.1017/cbo9780511585739.011

Dezetter M., Dupoué A., Le Galliard J.-F., Lourdais O. (2021). Additive Effects of Developmental Acclimation and Physiological Syndromes on Lifetime Metabolic and Water Loss Rates of a Dry‐skinned Ectotherm. Funct. Ecol. 36, 432–445. doi:10.1111/1365-2435.13951

Druyan S. (2010). The Effects of Genetic Line (Broilers vs. Layers) on Embryo Development. Poult. Sci. 89, 1457–1467. doi:10.3382/ps.2009-00304

Du W.-G., Ye H., Zhao B., Warner D. A., Shine R. (2010). Thermal Acclimation of Heart Rates in Reptilian Embryos. PLOS ONE 5, e15308. doi:10.1371/journal.pone.0015308

Dupont S. M., Grace J. K., Lourdais O., Brischoux F., Angelier F. (2019). Slowing Down the Metabolic Engine: Impact of Early-Life Corticosterone Exposure on Adult Metabolism in House Sparrows ( Passer domesticus ). J. Exp. Biol. 222, jeb211771. doi:10.1242/jeb.211771

DuRant S. E., Hopkins W. A., Hepp G. R. (2011). Embryonic Developmental Patterns and Energy Expenditure Are Affected by Incubation Temperature in Wood Ducks ( Aix sponsa ). Physiol. Biochem. Zool. 84, 451–457. doi:10.1086/661749

DuRant S. E., Hopkins W. A., Wilson A. F., Hepp G. R. (2012). Incubation Temperature Affects the Metabolic Cost of Thermoregulation in a Young Precocial Bird. Funct. Ecol. 26, 416–422. doi:10.1111/j.1365-2435.2011.01945.x

DuRant S. E., Hopkins W. A., Hepp G. R., Walters J. R. (2013). Ecological, Evolutionary, and Conservation Implications of Incubation Temperature-dependent Phenotypes in Birds. Biol. Rev. 88, 499–509. doi:10.1111/brv.12015

Fox J., Weisberg S. (2011). An {R} Companion to Applied Regression . 2nd ed. Thousand Oaks CA: Sage . Available at: http://socserv.socsci.mcmaster.ca/jfox/Books/Companion .

Ghalambor C. K., Peluc S. I., Martin T. E. (2013). Plasticity of Parental Care under the Risk of Predation: How Much Should Parents Reduce Care? Biol. Lett. 9, 20130154. doi:10.1098/rsbl.2013.0154

Goodchild C. G., Grisham K., Belden J. B., DuRant S. E. (2020). Effects of Sublethal Application of Deepwater Horizon Oil to Bird Eggs on Embryonic Heart and Metabolic Rate. Conserv. Biol. 34, 1262–1270. doi:10.1111/cobi.13539

Groothuis T. G. G., Müller W., Von Engelhardt N., Carere C., Eising C. (2005). Maternal Hormones as a Tool to Adjust Offspring Phenotype in Avian Species. Neurosci. Biobehav. Rev. 29, 329–352. doi:10.1016/j.neubiorev.2004.12.002

Haftorn S., Reinertsen R. E. (1985). The Effect of Temperature and Clutch Size on the Energetic Cost of Incubation in a Free-Living Blue Tit ( Parus caeruleus ). Auk 102, 470–478. doi:10.1093/auk/102.3.470

Hepp G. R., DuRant S. E., Hopkins W. A. (2015). “Influence of Incubation Temperature on Offspring Phenotype and Fitness in Birds,” in Nests, Eggs and Incubation: New Ideas about Avian Reproduction . Editors D. C. Deeming, and S. J. Reynolds (New York: Oxford University Press ), 171–178. doi:10.1086/49998810.1093/acprof:oso/9780198718666.003.0014

Ho D. H., Reed W. L., Burggren W. W. (2011). Egg Yolk Environment Differentially Influences Physiological and Morphological Development of Broiler and Layer Chicken Embryos. J. Exp. Biol. 214, 619–628. doi:10.1242/jeb.046714

Hope S. F., DuRant S. E., Angelier F., Hallagan J. J., Moore I. T., Parenteau C., et al. (2020). Prolactin Is Related to Incubation Constancy and Egg Temperature Following a Disturbance in a Precocial Bird. Gen. Comp. Endocrinol. 295, 113489. doi:10.1016/j.ygcen.2020.113489

Hope S. F., DuRant S. E., Hallagan J. J., Beck M. L., Kennamer R. A., Hopkins W. A. (2021). Incubation Temperature as a Constraint on Clutch Size Evolution. Funct. Ecol. 35, 909–919. doi:10.1111/1365-2435.13764

Ide S. T., Ide R., Mortola J. P. (2017). The Contribution of Heart Rate to the Oxygen Consumption of the Chicken Embryo during Cold- or Hypoxia-Hypometabolism. Comp. Biochem. Physiol. Part A: Mol. Integr. Physiol. 203, 49–58. doi:10.1016/j.cbpa.2016.08.026

Killpack T. L., Karasov W. H. (2012). Growth and Development of House Sparrows ( Passer domesticus ) in Response to Chronic Food Restriction throughout the Nestling Period. J. Exp. Biol. 215, 1806–1815. doi:10.1242/jeb.066316

Koteja P. (2004). The Evolution of Concepts on the Evolution of Endothermy in Birds and Mammals. Physiol. Biochem. Zool. 77, 1043–1050. doi:10.1086/423741

Lenth R. (2018). Emmeans: Estimated Marginal Means, Aka Least-Squares Means . R package version 1.3.0.

Lepczyk C. A., Karasov W. H. (2000). Effect of Ephemeral Food Restriction on Growth of House Sparrows. Auk 117, 164–174. doi:10.1093/auk/117.1.164

Low M., Makan T., Castro I. (2012). Food Availability and Offspring Demand Influence Sex-specific Patterns and Repeatability of Parental Provisioning. Behav. Ecol. 23, 25–34. doi:10.1093/beheco/arr145

McFarlane S. E., Ålund M., Sirkiä P. M., Qvarnström A. (2021). Low Heritability but Significant Early Environmental Effects on Resting Metabolic Rate in a Wild Passerine. Am. Nat. 198, 551–560. doi:10.1086/715842

McNab B. K. (1997). On the Utility of Uniformity in the Definition of Basal Rate of Metabolism. Physiol. Zoolog. 70, 718–720. doi:10.1086/515881

Moe B., Brunvoll S., Mork D., Brobakk T. E., Bech C. (2005). Does Food Shortage Delay Development of Homeothermy in European Shag Nestlings (Phalacrocorax Aristotelis)? J. Comp. Physiol. B 175, 21–30. doi:10.1007/s00360-004-0458-9

Nespolo R. F., Franco M. (2007). Whole-animal Metabolic Rate Is a Repeatable Trait: a Meta-Analysis. J. Exp. Biol. 210, 2000–2005. doi:10.1242/jeb.02780

Nilsson J.-Å., Åkesson M., Nilsson J. F. (2009). Heritability of Resting Metabolic Rate in a Wild Population of Blue Tits. J. Evol. Biol. 22, 1867–1874. doi:10.1111/j.1420-9101.2009.01798.x

Nilsson J. F., Tobler M., Nilsson J.-Å., Sandell M. I. (2011). Long-Lasting Consequences of Elevated Yolk Testosterone for Metabolism in the Zebra Finch. Physiol. Biochem. Zool. 84, 287–291. doi:10.1086/659006

Nilsson J. Å. (2002). Metabolic Consequences of Hard Work. Proc. R. Soc. Lond. B 269, 1735–1739. doi:10.1098/rspb.2002.2071

Nord A., Giroud S. (2020). Lifelong Effects of Thermal Challenges During Development in Birds and Mammals. Front. Physiol. 11, 419. Available at: https://www.frontiersin.org/article/10.3389/fphys.2020.00419 . (Accessed February 3, 2022). doi:10.3389/fphys.2020.00419

Nord A., Nilsson J.-Å. (2011). Incubation Temperature Affects Growth and Energy Metabolism in Blue Tit Nestlings. Am. Nat. 178, 639–651. doi:10.1086/662172

Nord A., Williams J. B. (2015). “The Energetic Costs of Incubation,” in Nests, Eggs & Incubation . Editors D. C. Deeming, and S. J. Reynolds (Oxford, UK: Oxford University Press ), 152–170. doi:10.1093/acprof:oso/9780198718666.003.0013

Norin T., Metcalfe N. B. (2019). Ecological and Evolutionary Consequences of Metabolic Rate Plasticity in Response to Environmental Change. Phil. Trans. R. Soc. B 374, 20180180. doi:10.1098/rstb.2018.0180

Nzama S. N., Downs C. T., Brown M. (2010). Seasonal Variation in the Metabolism-Temperature Relation of House Sparrows ( Passer domesticus ) in KwaZulu-Natal, South Africa. J. Therm. Biol. 35, 100–104. doi:10.1016/j.jtherbio.2009.12.002

Olson C. R., Wirthlin M., Lovell P. V., Mello C. V. (2014). Proper Care, Husbandry, and Breeding Guidelines for the Zebra Finch, Taeniopygia guttata . Cold Spring Harb Protoc. 2014, 1243–1248. doi:10.1101/pdb.prot084780

Pettersen A. K., Marshall D. J., White C. R. (2018). Understanding Variation in Metabolic Rate. J. Exp. Biol. 221, jeb166876. doi:10.1242/jeb.166876

R Core Team (2018). R: A Language and Environment for Statistical Computing . Vienna, Austria: R Foundation for Statistical Computing . Available at: https://www.r-project.org /.

Réveillon T., Rota T., Chauvet É., Lecerf A., Sentis A. (2019). Repeatable Inter‐individual Variation in the thermal Sensitivity of Metabolic Rate. Oikos 128, 1633–1640. doi:10.1111/oik.06392

Rønning B., Moe B., Bech C. (2005). Long-term Repeatability Makes Basal Metabolic Rate a Likely Heritable Trait in the Zebra Finch Taeniopygia guttata . J. Exp. Biol. 208, 4663–4669. doi:10.1242/jeb.01941

Rønning B., Jensen H., Moe B., Bech C. (2007). Basal Metabolic Rate: Heritability and Genetic Correlations with Morphological Traits in the Zebra Finch. J. Evol. Biol. 20, 1815–1822. doi:10.1111/j.1420-9101.2007.01384.x

Rønning B., Mortensen A. S., Moe B., Chastel O., Arukwe A., Bech C. (2009). Food Restriction in Young Japanese Quails: Effects on Growth, Metabolism,plasma Thyroid Hormones and mRNA Species in the Thyroid Hormone Signalling Pathway. J. Exp. Biol. 212, 3060–3067. doi:10.1242/jeb.029835

Rønning B., Broggi J., Bech C., Moe B., Ringsby T. H., Pärn H., et al. (2016). Is Basal Metabolic Rate Associated with Recruit Production and Survival in Free‐living House Sparrows? Funct. Ecol. 30, 1140–1148. doi:10.1111/1365-2435.12597

Rubin A. (2019). Effects of Periodic Cooling during Incubation on Lifelong Physiology in Zebra Finches. Mastery’s Thesis. Auburn, AL, USA: Auburn University .

Sadowska J., Gębczyński A. K., Konarzewski M. (2013). Basal Metabolic Rate Is Positively Correlated with Parental Investment in Laboratory Mice. Proc. R. Soc. B. 280, 20122576. doi:10.1098/rspb.2012.2576

Sartori M. R., Abe A. S., Crossley D. A., Taylor E. W. (2017). Rates of Oxygen Uptake Increase Independently of Changes in Heart Rate in Late Stages of Development and at Hatching in the green iguana, Iguana iguana . Comp. Biochem. Physiol. Part A: Mol. Integr. Physiol. 205, 28–34. doi:10.1016/j.cbpa.2016.12.020

Schmidt K. L., MacDougall-Shackleton E. A., Macdougall-Shackleton S. A. (2012). Developmental Stress Has Sex-specific Effects on Nestling Growth and Adult Metabolic Rates but No Effect on Adult Body Size or Body Composition in Song Sparrows. J. Exp. Biol. 215, 3207–3217. doi:10.1242/jeb.068965

Schwagmeyer P. L., Mock D. W. (2003). How Consistently Are Good Parents Good Parents? Repeatability of Parental Care in the House Sparrow, Passer domesticus . Ethology 109, 303–313. doi:10.1046/j.1439-0310.2003.00868.x

Sheldon E. L., Griffith S. C. (2018). Embryonic Heart Rate Predicts Prenatal Development Rate, but Is Not Related to post-natal Growth Rate or Activity Level in the Zebra Finch ( Taeniopygia guttata ). Ethology 124, 829–837. doi:10.1111/eth.12817

Sheldon E. L., McCowan L. S. C., McDiarmid C. S., Griffith S. C. (2018). Measuring the Embryonic Heart Rate of Wild Birds: An Opportunity to Take the Pulse on Early Development. Auk 135, 71–82. doi:10.1642/AUK-17-111.1

Spencer K. A., Verhulst S. (2008). Post-natal Exposure to Corticosterone Affects Standard Metabolic Rate in the Zebra Finch ( Taeniopygia guttata ). Gen. Comp. Endocrinol. 159, 250–256. doi:10.1016/j.ygcen.2008.09.007

Stier A., Metcalfe N. B., Monaghan P. (2020). Pace and Stability of Embryonic Development Affect Telomere Dynamics: an Experimental Study in a Precocial Bird Model. Proc. R. Soc. B. 287, 20201378. doi:10.1098/rspb.2020.1378

Tinbergen J., Williams J. (2002). “Energetics of Incubation,” in Avian Incubation Behaviour, Environment and Evolution . Editor D. Deeming (Oxford, UK: Oxford University Press ), 299–313.

Tobler M., Nilsson J.-Å., Nilsson J. F. (2007). Costly Steroids: Egg Testosterone Modulates Nestling Metabolic Rate in the Zebra Finch. Biol. Lett. 3, 408–410. doi:10.1098/rsbl.2007.0127

Vedder O., Kürten N., Bouwhuis S. (2017). Intraspecific Variation in and Environment-Dependent Resource Allocation to Embryonic Development Time in Common Terns. Physiol. Biochem. Zool. 90, 453–460. doi:10.1086/691690

Verhulst S., Holveck M.-J., Riebel K. (2006). Long-term Effects of Manipulated Natal Brood Size on Metabolic Rate in Zebra Finches. Biol. Lett. 2, 478–480. doi:10.1098/rsbl.2006.0496

von Engelhardt N., Dijkstra C., Daan S., Groothuis T. G. G. (2004). Effects of 17-β-Estradiol Treatment of Female Zebra Finches on Offspring Sex Ratio and Survival. Horm. Behav. 45, 306–313. doi:10.1016/j.yhbeh.2003.12.009

Von Engelhardt N., Carere C., Dijkstra C., G. G. Groothuis T. (2006). Sex-specific Effects of Yolk Testosterone on Survival, Begging and Growth of Zebra Finches. Proc. R. Soc. B. 273, 65–70. doi:10.1098/rspb.2005.3274

Wada H., Kriengwatana B., Allen N., Schmidt K. L., Soma K. K., MacDougall-Shackleton S. A. (2015). Transient and Permanent Effects of Suboptimal Incubation Temperatures on Growth, Metabolic Rate, Immune Function, and Adrenocortical Responses in Zebra Finches. J. Exp. Biol. 218, 2847–2855. doi:10.1242/jeb.114108

White C. R., Kearney M. R. (2013). Determinants of Inter-specific Variation in Basal Metabolic Rate. J. Comp. Physiol. B 183, 1–26. doi:10.1007/s00360-012-0676-5

Wickham H. (2011). The Split-Apply-Combine Strategy for Data Analysis. J. Stat. Softw. 40, 1–29. doi:10.18637/jss.v040.i01

Wickham H. (2016). ggplot2: Elegant Graphics for Data Analysis . New York: Springer-Verlag .

Wiebe K., Neufeld C. (2003). Correlates of Parental Care in Northern Flickers Colaptes Auratus: Do the Sexes Contribute Equally while Provisioning Young? Ardea -Wageningen- 91, 91–101.

Williams J. B., Miller R. A., Harper J. M., Wiersma P. (2010). Functional Linkages for the Pace of Life, Life-History, and Environment in Birds. Integr. Comp. Biol. 50, 855–868. doi:10.1093/icb/icq024

Williams D. P., Avery J. D., Gabrielson T. B., Brittingham M. C. (2021). Experimental Playback of Natural Gas Compressor Noise Reduces Incubation Time and Hatching success in Two Secondary Cavity-Nesting Bird Species. Ornithol. Appl. 123, duaa066. doi:10.1093/ornithapp/duaa066

Winter V., Elliott J. E., Letcher R. J., Williams T. D. (2013). Validation of an Egg-Injection Method for Embryotoxicity Studies in a Small, Model Songbird, the Zebra Finch ( Taeniopygia guttata ). Chemosphere 90, 125–131. doi:10.1016/j.chemosphere.2012.08.017

Wray N., Visscher P. (2008). Estimating Trait Heritability. Nat. Educ. 1, 29.

Wright J., Both C., Cotton P. A., Bryant D. (1998). Quality vs. Quantity: Energetic and Nutritional Trade-Offs in Parental Provisioning Strategies. J. Anim. Ecol. 67, 620–634. doi:10.1046/j.1365-2656.1998.00221.x

Keywords: incubation temperature, heritability, metabolic rate, thermoregulation, embryonic heart rate, cost of thermoregulation

Citation: Hope SF, Schmitt L, Lourdais O and Angelier F (2022) Nature vs. Nurture: Disentangling the Influence of Inheritance, Incubation Temperature, and Post-Natal Care on Offspring Heart Rate and Metabolism in Zebra Finches. Front. Physiol. 13:892154. doi: 10.3389/fphys.2022.892154

Received: 08 March 2022; Accepted: 19 April 2022; Published: 10 May 2022.

Reviewed by:

Copyright © 2022 Hope, Schmitt, Lourdais and Angelier. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Sydney F. Hope, [email protected]

† ORCID ID: Sydney F. Hope, orcid.org/0000-0002-3711-8593 Frédéric Angelier, orcid.org/0000-0003-2619-167X

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The Nature vs. Nurture Debate

Genetic and Environmental Influences and How They Interact

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Verywell / Joshua Seong

• Definitions
• Interaction
• Contemporary Views

Nature refers to how genetics influence an individual's personality, whereas nurture refers to how their environment (including relationships and experiences) impacts their development. Whether nature or nurture plays a bigger role in personality and development is one of the oldest philosophical debates within the field of psychology .

Learn how each is defined, along with why the issue of nature vs. nurture continues to arise. We also share a few examples of when arguments on this topic typically occur, how the two factors interact with each other, and contemporary views that exist in the debate of nature vs. nurture as it stands today.

Nature and Nurture Defined

To better understand the nature vs. nurture argument, it helps to know what each of these terms means.

• Nature refers largely to our genetics . It includes the genes we are born with and other hereditary factors that can impact how our personality is formed and influence the way that we develop from childhood through adulthood.
• Nurture encompasses the environmental factors that impact who we are. This includes our early childhood experiences, the way we were raised , our social relationships, and the surrounding culture.

A few biologically determined characteristics include genetic diseases, eye color, hair color, and skin color. Other characteristics are tied to environmental influences, such as how a person behaves, which can be influenced by parenting styles and learned experiences.

For example, one child might learn through observation and reinforcement to say please and thank you. Another child might learn to behave aggressively by observing older children engage in violent behavior on the playground.

The Debate of Nature vs. Nurture

The nature vs. nurture debate centers on the contributions of genetics and environmental factors to human development. Some philosophers, such as Plato and Descartes, suggested that certain factors are inborn or occur naturally regardless of environmental influences.

Advocates of this point of view believe that all of our characteristics and behaviors are the result of evolution. They contend that genetic traits are handed down from parents to their children and influence the individual differences that make each person unique.

Other well-known thinkers, such as John Locke, believed in what is known as tabula rasa which suggests that the mind begins as a blank slate . According to this notion, everything that we are is determined by our experiences.

Behaviorism is a good example of a theory rooted in this belief as behaviorists feel that all actions and behaviors are the results of conditioning. Theorists such as John B. Watson believed that people could be trained to do and become anything, regardless of their genetic background.

People with extreme views are called nativists and empiricists. Nativists take the position that all or most behaviors and characteristics are the result of inheritance. Empiricists take the position that all or most behaviors and characteristics result from learning.

Examples of Nature vs. Nurture

One example of when the argument of nature vs. nurture arises is when a person achieves a high level of academic success . Did they do so because they are genetically predisposed to elevated levels of intelligence, or is their success a result of an enriched environment?

The argument of nature vs. nurture can also be made when it comes to why a person behaves in a certain way. If a man abuses his wife and kids, for instance, is it because he was born with violent tendencies, or is violence something he learned by observing others in his life when growing up?

Nature vs. Nurture in Psychology

Throughout the history of psychology , the debate of nature vs. nurture has continued to stir up controversy. Eugenics, for example, was a movement heavily influenced by the nativist approach.

Psychologist Francis Galton coined the terms 'nature versus nurture' and 'eugenics' and believed that intelligence resulted from genetics. Galton also felt that intelligent individuals should be encouraged to marry and have many children, while less intelligent individuals should be discouraged from reproducing.

The value placed on nature vs. nurture can even vary between the different branches of psychology , with some branches taking a more one-sided approach. In biopsychology , for example, researchers conduct studies exploring how neurotransmitters influence behavior, emphasizing the role of nature.

In social psychology , on the other hand, researchers might conduct studies looking at how external factors such as peer pressure and social media influence behaviors, stressing the importance of nurture. Behaviorism is another branch that focuses on the impact of the environment on behavior.

Nature vs. Nurture in Child Development

Some psychological theories of child development place more emphasis on nature and others focus more on nurture. An example of a nativist theory involving child development is Chomsky's concept of a language acquisition device (LAD). According to this theory, all children are born with an instinctive mental capacity that allows them to both learn and produce language.

An example of an empiricist child development theory is Albert Bandura's social learning theory . This theory says that people learn by observing the behavior of others. In his famous Bobo doll experiment , Bandura demonstrated that children could learn aggressive behaviors simply by observing another person acting aggressively.

Nature vs. Nurture in Personality Development

There is also some argument as to whether nature or nurture plays a bigger role in the development of one's personality. The answer to this question varies depending on which personality development theory you use.

According to behavioral theories, our personality is a result of the interactions we have with our environment, while biological theories suggest that personality is largely inherited. Then there are psychodynamic theories of personality that emphasize the impact of both.

Nature vs. Nurture in Mental Illness Development

One could argue that either nature or nurture contributes to mental health development. Some causes of mental illness fall on the nature side of the debate, including changes to or imbalances with chemicals in the brain. Genetics can also contribute to mental illness development, increasing one's risk of a certain disorder or disease.

Mental disorders with some type of genetic component include autism , attention-deficit hyperactivity disorder (ADHD), bipolar disorder , major depression , and schizophrenia .

Other explanations for mental illness are environmental. This includes being exposed to environmental toxins, such as drugs or alcohol, while still in utero. Certain life experiences can also influence mental illness development, such as witnessing a traumatic event, leading to the development of post-traumatic stress disorder (PTSD).

Nature vs. Nurture in Mental Health Therapy

Different types of mental health treatment can also rely more heavily on either nature or nurture in their treatment approach. One of the goals of many types of therapy is to uncover any life experiences that may have contributed to mental illness development (nurture).

However, genetics (nature) can play a role in treatment as well. For instance, research indicates that a person's genetic makeup can impact how their body responds to antidepressants. Taking this into consideration is important for getting that person the help they need.

Interaction Between Nature and Nurture

Which is stronger: nature or nurture? Many researchers consider the interaction between heredity and environment—nature with nurture as opposed to nature versus nurture—to be the most important influencing factor of all.

For example, perfect pitch is the ability to detect the pitch of a musical tone without any reference. Researchers have found that this ability tends to run in families and might be tied to a single gene. However, they've also discovered that possessing the gene is not enough as musical training during early childhood is needed for this inherited ability to manifest itself.

Height is another example of a trait influenced by an interaction between nature and nurture. A child might inherit the genes for height. However, if they grow up in a deprived environment where proper nourishment isn't received, they might never attain the height they could have had if they'd grown up in a healthier environment.

A newer field of study that aims to learn more about the interaction between genes and environment is epigenetics . Epigenetics seeks to explain how environment can impact the way in which genes are expressed.

Some characteristics are biologically determined, such as eye color, hair color, and skin color. Other things, like life expectancy and height, have a strong biological component but are also influenced by environmental factors and lifestyle.

Contemporary Views of Nature vs. Nurture

Most experts recognize that neither nature nor nurture is stronger than the other. Instead, both factors play a critical role in who we are and who we become. Not only that but nature and nurture interact with each other in important ways all throughout our lifespan.

As a result, many in this field are interested in seeing how genes modulate environmental influences and vice versa. At the same time, this debate of nature vs. nurture still rages on in some areas, such as in the origins of homosexuality and influences on intelligence .

While a few people take the extreme nativist or radical empiricist approach, the reality is that there is not a simple way to disentangle the multitude of forces that exist in personality and human development. Instead, these influences include genetic factors, environmental factors, and how each intermingles with the other.

Schoneberger T. Three myths from the language acquisition literature . Anal Verbal Behav . 2010;26(1):107-31. doi:10.1007/bf03393086

National Institutes of Health. Common genetic factors found in 5 mental disorders .

Pain O, Hodgson K, Trubetskoy V, et al. Identifying the common genetic basis of antidepressant response . Biol Psychiatry Global Open Sci . 2022;2(2):115-126. doi:10.1016/j.bpsgos.2021.07.008

Moulton C. Perfect pitch reconsidered . Clin Med J . 2014;14(5):517-9 doi:10.7861/clinmedicine.14-5-517

Levitt M. Perceptions of nature, nurture and behaviour . Life Sci Soc Policy . 2013;9:13. doi:10.1186/2195-7819-9-13

Bandura A, Ross D, Ross, SA. Transmission of aggression through the imitation of aggressive models . J Abnorm Soc Psychol. 1961;63(3):575-582. doi:10.1037/h0045925

Chomsky N. Aspects of the Theory of Syntax .

Galton F. Inquiries into Human Faculty and Its Development .

Watson JB. Behaviorism .

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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A Close Look at Nature vs. Nurture

Psychology Professor shares her research for University’s Distinguished Scholar lecture

Posted in: Faculty Voices , Humanities and Social Sciences , Research , University

“If you’ve ever been around a crying infant, you may have concluded that the world of a newborn is one great ‘blooming, buzzing confusion’ …” So begins the lecture – and the nature vs. nurture debate – presented by this academic year’s University Distinguished Scholar, Psychology Professor Laura Lakusta.

For the past 15 years, Lakusta has focused on language and cognitive development, and most recently leadership, in research within one of oldest philosophical fields of psychology. 

“Is the world of a newborn really a big ‘booming, buzzing confusion’?” she asks referencing theorist William James. “O r do infants initially, and that is from birth, bring a rich knowledge base which may serve as a foundation and support subsequent learning?” 

In her lecture to the University community – presented virtually due to the state’s stay-at-home orders –  Lakusta explores the timeless theme while sharing her own extensive studies on inherited traits and learned behaviors. Research makes it increasingly clear that both nature and nurture play a role, she says.

The University’s Distinguished Scholar Award recognizes Montclair State faculty who have developed a distinguished record of scholarly or creative achievement, says University Provost and Vice President for Academic Affairs Willard Gingerich. “This award provided Laura with enhanced opportunities to implement two active, competitive research programs and the opportunity to share with the campus community her work exploring the domains of language and cognitive development, and a new line of research that explores the impact of nature and nurture in leadership development.”

As Lakusta explains in the presentation, “Nature and Nurture in Spatial Cognition and Beyond,” the nature and nurture theme is by no means solely of interest to the field of psychology, “but one that applies to a range of disciplines, including philosophy, cognitive science, linguistics, education, biology, genetics, et cetera, et cetera.” 

“The field is in agreement that it’s not an either/or question. It’s not, is it nature or is it nurture that contributes to development. But the question is how do they contribute? How can we understand how nature and nurture work together to drive development forward?”

Lakusta has published repeatedly – often with her students – in some of the most competitive journals in cognitive and developmental psychology, including the Proceedings of the National Academy of Sciences , and since 2008 she has presented more than 50 invited papers and conference posters.  

The studies of language and cognition – which have been supported with two different grants totaling about $900,000 from the National Science Foundation – test whether and how representations of spatial knowledge in children 6 months to 5 years can be influenced by environmental input. A portion of this work is a collaborative project with Barbara Landau, professor of Cognitive Science at Johns Hopkins University.

The main finding is that infants’ representations of events can support language learning. In the lab setting, for example, the researchers look at how infants and children interpret the world around them, and think about objects and actions. As explained in the lecture, this includes simple events, such as a duck moving out of a bowl or a leaf blowing into a box. 

“You may be surprised at how much infants actually do seem to know within just a few months of life or even just a year,” Lakusta says.

A new study of leadership development, in collaboration with Montclair State Psychology Professor Jennifer Bragger , explores the broad questions of whether children are predisposed to develop into certain types of leaders and how environmental context may influence leadership development. Specifically, Lakusta and Bragger are testing how children, adolescents and adults perceive the distinctions between different leadership types, and whether Theory of Mind development, humility and self-awareness play a role in leadership emergence.

“We’re looking at how people become servant leaders,” Lakusta says. “These are leaders that primarily lead by focusing on their followers. They lead by empowering their followers by guiding, by developing their followers. By doing this, by focusing on their followers, they’re actually able to attain goals.”

The research takes place in Montclair State’s Cognitive and Language Development Lab , where Lakusta leads teams of student researchers. The lab is among the University’s clinical labs in psychology that have received grant funding for research.

“The students really made it happen,” Lakusta says. “They do everything from reading and presenting empirical and theoretical research to coding and analyzing and interpreting data to assisting me with participant testing. They go out into the community on a Sunday afternoon to help recruit children at community fairs. They assist with IRB (Institutional Review Board). The research would not be possible without them.”

Story by Staff Writer Marilyn Joyce Lehren .

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• Published: 23 March 2018

The nature and nurture of education

• Pankaj Sah 1 ,
• Michael Fanselow 2 ,
• Gregory J. Quirk 3 ,
• John Hattie 4 ,
• Jason Mattingley   ORCID: orcid.org/0000-0003-0929-9216 1 &
• Tracey Tokuhama-Espinosa 5  

npj Science of Learning volume  3 , Article number:  6 ( 2018 ) Cite this article

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Learning is a life-long endeavour that continues from infancy to old age. We each navigate the learning process in different ways, yielding to our experiences and the circumstances in which we find ourselves. For many people, formal education takes place between the ages of 6–18, where we are educated based on core curricula that are delivered through a schooling system. Many countries have some form of compulsory education for children until they reach adulthood, but the route through the school system can vary greatly. In many first world countries, the choice is between public schools, generally funded by the state, and private schools which are funded through a combination of individual tuition fees, and religious or corporate institutions. School education is generally required by government mandate, and the cost of admission and tuition in public schools is borne by the state. In contrast, entry into a private school is often primarily dependent on socioeconomic status and some form of selection process—either formal testing or religious affiliation.

In many countries, studies have suggested that students attending private schools attain better educational outcomes, and long-term socioeconomic benefits. These data are then used by private schools to encourage attendance in this selective system. Private schools are generally expensive but may provide more individualized programs of study with better student–faculty ratios then those provided by public schools.

The choice parents make in selecting schools for their children, and the differences between public and private schools has been the subject of much debate, that is largely couched in social and economic terms. In a collection of manuscripts published in npj Science of Learning , two groups of researchers have approached this discussion from an interesting new direction—genetics. The Nature versus Nurture question has been greatly debated for many years, because it is not entirely clear which is the greatest influence on human development and behaviour. Although we are all born with a specific set of genes, with no control over our genetic allocation, we now know our life-style choices and different experiences though development and maturity also influence gene expression, and thus exert control over our behaviour via epigenetic modifications. Epigenetic mechanisms regulate the structure and activity of the genome in response to cellular and environmental cues, one such mechanism involves DNA methylation. Thus, biological processes are controlled by a combination of inherited genes and the life-long impact of epigenetic modifications that regulates their expression. Who we are is not simply a result of either nature or nurture but rather is shaped by a combination of these factors. Recent advances in genomic and epigenomic sequencing, have led to a growing interest in using this information to predict biological outcomes, and disease pathogenesis and help guide individuals in lifestyle choices and behaviour.

Two papers 1 , 2 published in npj Science of Learning have worked to address the question of 'Does an individual’s genetic makeup, and epigenetic modification, affect his or her educational attainment?'. Educational attainment is a measure of the highest level of education that an individual has completed at the end of full-time compulsory education. Educational attainment has been shown to strongly correlate with mental and physical health, as well as socioeconomic status, and is one of the strongest predictors of lifetime success, not only economically but also in terms of health and longevity.

In one study, 1 Smith–Woolley and colleagues looked at educational attainment in three groups of students in Britain that attended either: public schools, private schools or selective schools. The researchers found that as previously reported, students in private schools had higher levels of educational attainment than those in public schools. They then examined the genetic differences between students in these groups, and surprisingly, there were differences in genetic markers between them. Interestingly, when differences in genetics were accounted for, educational attainment differences between students attending the different schools disappeared.

In another study, 2 van Dongen and colleagues examine the DNA methylation status of genes in people with different levels of educational attainment. They found differential sites of DNA methylation at specific regions (loci) correlate with educational attainment and the methylation status of these sites are largely influenced by environmental factors such as smoking. These sites of differential methylation were found to be located in and near genes with neuronal, immune and developmental functions. Differential levels of DNA methylation in these regions could impact the expression of these genes during critical periods of childhood development. Together, the two studies point to the role of genetics and epigenetic changes in educational outcome. Two accompanying perspective pieces, one by Nick Martin 3 and the other by Sue Thompson, 4 provide a commentary on the implications of these studies from the genetic 3 and educational 4 viewpoint.

There is a growing interest in genomic and epigenomic sequencing of different populations, with the data generated being incorporated into many different databases. Large-scale projects like the ENCODE (Encyclopedia of DNA Elements) Consortium, which is an international collaboration of research groups funded by the National Human Genome Research Institute (NHGRI), and the British 100,000 genomes project, led by Genomics England, are leading the way in trying to understand how these factors influence biological processes. The two studies published in npj Science of Learning raise the question of the use of genomic data to help predict educational outcomes. Just as the management of our health is increasingly being found to be affected by genetic and epigenetic determinants, it may be that individuals progress through the education system based upon these factors as well.

Smith-Woolley, E. et al. Differences in exam performance between pupils attending selective and non-selective schools mirror the genetic differences between them. npj Sci. Learn. https://doi.org/10.1038/s41539-018-0019-8 (2018).

van Dongen, J. et al. DNA methylation signatures of educational attainment. npj Sci. Learn. https://doi.org/10.1038/s41539-018-0020-2 (2018).

Martin, N. Getting to the genetic and environmental roots of educational inequality. npj Sci. Learn. https://doi.org/10.1038/s41539-018-0021-1 (2018).

Thomson, S. Achievement at school and socioeconomic background—an educational perspective. npj Sci. Learn. https://doi.org/10.1038/s41539-018-0022-0 (2018).

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Pankaj Sah & Jason Mattingley

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Sah, P., Fanselow, M., Quirk, G.J. et al. The nature and nurture of education. npj Science Learn 3 , 6 (2018). https://doi.org/10.1038/s41539-018-0023-z

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2 Rethinking Nature and Nurture

As developmental psychologists stand at the threshold of a new era in understanding the biological bases for human growth and continue to address fundamental questions about parenting influences, it is time for a new appreciation of the coactivity of nature and nurture in development. Beginning at the moment of conception, hereditary potential unfolds in concert with the environment. The dynamic interplay between gene action and environmental processes continues throughout life. Although their influences are so often distinguished in ancient philosophy and modern science, the inseparability of nature and nurture has profound implications for how we study and understand human development. 1 In this chapter, we trace these implications drawing first on the literature on developmental behavioral genetics, then undertaking a discussion of molecular genetics. We close with a brief discussion of brain development, foreshadowing the focused attention that is given to this topic in Chapter 8 .

Nature and nurture are partners in how developing people interact with the surrounding environment. Nature and nurture are partners also in the transactions between the gene 2 and the variety of internal environments that surround it within the body (Greenough, 1991; Greenough and Black, 1992). The environment of the cell influences which of the tens of thousands of genes are expressed to affect cell characteristics. Hormones and growth factors in the cell can turn some genes on and turn others off. These substances can arise from the nucleus of the cell, its cytoplasm, or the surrounding cells or organs. The substances that influence gene expression arise also from the functioning of other genes within the cell (so-called regulator genes) and the products of earlier protein synthesis.

It is impossible to think of gene expression apart from the multiple environments in which it occurs. It is impossible to think of the manifestation of hereditary potential independently of the hierarchy of environments that shape its appearance. It is impossible to think of an organism that interacts with the environment without considering the genotypical uniqueness of that individual. It is impossible, in short, to consider nature apart from nurture.

Why, then, are these two forces of human development so persistently differentiated in efforts to understand human development? From ancient Platonic and Confucian philosophy to the present, the dichotomy between inherited capabilities and environmental incentives and pressures has guided human self-understanding in Western and Eastern thought. All contemporary scientists acknowledge the interaction of heredity and environment (see Elman et al., 1996, for a recent and sophisticated version of the interactionist view). Yet an emphasis on whether hereditary constraints or environmental incentives are the preeminent influence in human development can still be observed not only in scholarship in psychology but also, more significantly, in public discourse concerning the importance of parenting and early education, and in policy debates about early intervention programs, family support, delinquency and criminality, and other issues of child and family policy.

It is time to reconceptualize nature and nurture in a way that emphasizes their inseparability and complementarity, not their distinctiveness: it is not nature versus nurture, it is rather nature through nurture. If gene expression is inconceivable apart from the environment, then it is useless and potentially misleading to try to finely distinguish the relative importance of nature and nurture in the course of human development. Nature is inseparable from nurture, and the two should be understood in tandem. Moreover, by contrast with a traditional view that heredity imposes limitations and environments induce change in developmental pathways, research in developmental psychobiology shows that the coactivity of nature and nurture accounts for both stability and malleability in growth. This view is, indeed, one important way of integrating the science of early childhood development, and it is also reflected in recent scientific advances in some of the research fields that are currently generating greatest interest among developmental scientists: developmental behavioral genetics, molecular genetics, and brain development.

• DEVELOPMENTAL BEHAVIORAL GENETICS

In animal species, the importance of genetic influences on behavior can often be studied directly through selective breeding research. In humans, less intrusive procedures are necessary, and for the past several decades developmental behavioral genetics has provided a powerful means of understanding the strength of heritable influences on individual differences in human development, and the environmental contexts in which they are expressed (see Lemery and Goldsmith, 1999; Plomin et al., 1997a; and Rutter et al., 1999a, for overviews of this field). By taking advantage of naturally occurring variation in genotypes and environments, behavioral geneticists seek to partition behavioral variability into its genetic and environmental components and describe their interaction.

They have two primary research strategies for doing so. In adoption research, genetic contributions are estimated by comparing the characteristics of an adoptive child with those of the birth mother (to whom the child is genetically related, but they do not share an environment) and the adoptive mother (who shares the child's environment, but not genes). Sometimes biologically related and unrelated siblings are also studied. The second approach is twin research. Because identical (monozygotic) twins are genetically identical, comparing the similarity of their characteristics with those of fraternal (dyzygotic) twins, who on average share half their genes, is another way of estimating genetic contributions.

Twin and adoption research designs each have assumptions or limitations that can make the interpretation of findings difficult and sometimes controversial. In adoption research, for example, prenatal influences (e.g., teratogenic exposure) can also account for the resemblance of biological mothers to their offspring, and this can inflate estimates of genetic contributions. In addition, adoption designs assume that the selective placement by adoption agencies of children into the homes of parents who are like them (or their biological parents) does not occur. It is possible to estimate the potential biases introduced by selective placement or prenatal influences, but this is very difficult in most research designs. Twin studies also have certain assumptions: that identical twins do not share a more similar environment than do fraternal twins, and that the development of twin pairs is fairly representative of the growth of children in general. These assumptions, too, have been tested, with some researchers concluding that these assumptions are valid and others disagreeing.

Adoption and twin studies each provide means of estimating quantitatively the proportion of variance in human characteristics that is attributable to heredity and to the environment, and of examining how these influences interact in development. During the past decade, developmental behavioral genetics research has expanded considerably in sophistication and analytic methods, using variations on the basic adoption and twin research designs (sometimes combining these methods) and employing structural equations modeling and other quantitative model-fitting methods for estimating genetic and environmental contributions to behavioral variability. These efforts have yielded important new insights into the heritability of individual differences in cognitive abilities, extraversion, emotionality, self-control, and other characteristics and have shown how inherited propensities to childhood disorders like autism, schizophrenia, attention deficit hyperactivity disorder, and antisocial behavior need to be considered by practitioners (see reviews by Plomin et al., 1997b and Rutter et al., 1999b).

Even more important is how this research contributes to an appreciation of how nature and nurture influence development in concert. A recent study of the development of antisocial behavior in children by Ge, Conger, Cadoret, Neiderhiser, Yates, Troughton, and Stewart (1996) is exemplary. Using an adoption design, these researchers found that when biological parents had substance abuse problems or antisocial personality disorder, their adopted children were much more likely to be hostile and antisocial than were adoptees from untroubled biological parents. Children's inherited antisocial tendency may have been manifested as difficult temperaments, problems with emotional self-control, impulsivity, or other difficulties. It was not surprising, therefore, that children's antisocial tendency was also associated with greater harshness and less nurturance and involvement by their adoptive mothers and fathers. This illustrates how children's inherited characteristics can evoke complementary responses from their parents (called “gene-environment correlation”).

Parents and children in these adoptive families influenced each other. Children with greater hostility tended to evoke more severe disciplinary responses, but harsh discipline also tended to exacerbate children's antisocial behavior. Parents' treatment of their adoptive offspring was influenced not only by the child's demandingness, but also by influences that were found to be independent of the child's inherited characteristics, such as the quality of the parents' marital relationship (see Figure 2-1 ). Thus the development of antisocial behavior in children was influenced by heritable characteristics—which altered the childrearing climate of the home—and by family influences that arose independently of the child. Other studies offer a similar portrayal of the coactivity of nature and nurture in human development (see Cadoret et al., 1996; O'Connor et al., 1998; Pike et al., 1996; and Reiss, 1997).

Model of hereditary and environmental influences on children's antisocial behaviors. SOURCE: Adapted from Ge et al. (1996).

These studies have important practical implications. Since parenting and other environmental influences can moderate the development of inherited tendencies in children, efforts to assist parents and other caregivers to sensitively read a child's behavioral tendencies and to create a supportive context for the child are worthwhile. A good fit between environmental conditions and the child's characteristics is reflected, for example, in family routines that provide many opportunities for rambunctious play for highly active children, or in child care settings with quiet niches for shy children to take a break from intensive peer activity. Thoughtfully designed caregiving routines can incorporate helpful buffers against the development of behavior problems among children with inherited vulnerabilities by providing opportunities for choice, relational warmth, structured routine, and other assists. Interventions to assist children at risk for other psychological disorders must also be individualized and emphasize the creation of a good fit between inherited vulnerabilities and behavioral demands, especially for children at greater heritable risk for problems like antisocial behavior, depression, and attention deficit hyperactivity disorder.

Heritability

Twin and adoption research designs each permit behavioral geneticists to calculate a heritability statistic (h 2 ), which is an estimate of the proportion of variability in individual characteristics that is due to genetic differences. A heritability of .45, for example, indicates that 45 percent of the measured variability in a particular characteristic is due to genetic differences in the sample. There are comparable statistics that estimate environmental contributions to individual characteristics. Unfortunately, the distillation of many complex findings in behavioral genetics research to a single heritability figure has led to considerable misunderstanding of its meaning, especially when heritability estimates in the range of 30 to 70 percent are derived from studies of the genetic contributions to individual differences in intelligence, personality, and psychopathology. This misunderstanding derives, in part, from the traditional tendency to seek to distinguish the effects of nature and nurture in development. Thus it is important to appreciate several principles:

• Heritability estimates are proportions based on environmental as well as genetic diversity. As a proportion, heritability reflects the extent of environmental influences as well as genetic influences. On one hand, if the environment could be made the same for everyone, heritability would inevitably be large because individual differences would then be due entirely to genetic factors (Lemery and Goldsmith, 1999; Plomin et al., 1997b). On the other hand, if people are studied in environments with diverse influences on them (varying significantly in socioeconomic status, ethnicity, or culture, for example), environmental contributions are magnified and heritability is lower. In short, a heritability estimate is uninterpretable without an appreciation of the extent of the environmental variability that also influences behavior in a particular sample.
• Heritability estimates are sample- and context-specific. Heritability estimates reflect the environmental diversity of the sample under study, as well as their genetic diversity. Heritability estimates tend to be higher in samples with greater variability in relevant genetic influences and, conversely, lower in samples that are genetically homogeneous. Because research samples can vary in both their environmental and genetic diversity, a heritability estimate must always be understood as pertaining to observed differences between individuals in a particular sample at a particular time in a specific environment.
• Heritability estimates change with development. A characteristic that is highly heritable at one age may not be particularly heritable at another (Lemery and Goldsmith, 1999). There are many reasons for this, including the changes that occur in gene activation with human growth, changes in environmental influences with increasing age, and changes in the nature of a person's engagement with the environment over time. The heritability of variations in general cognitive ability tends to increase with age, for example, as does the heritability of certain behavioral difficulties, such as those associated with antisocial behavior (Goldsmith and Gottesman, 1996; Plomin et al., 1997b). Heritability estimates are thus not consistent over the course of development.
• Perhaps most important, heritability estimates describe what is in a particular population at a particular time, rather than what could be (Plomin et al., 1997b). Changes in either genetic influences or environmental influences are likely to alter the relative impact of heredity and environment on individual characteristics. Phenylketonuria is a highly heritable genetic disorder that leads to mental retardation. But with a combination of early detection and environmental interventions, retardation can be completely prevented (Birch et al., 1992). Thus contrary to the common belief that highly heritable characteristics are impervious to environmental modification, interventions that alter the relevant environment—such as educational opportunities, therapeutic support, improved nutrition—can significantly alter the development of that characteristic.

Moreover, it is important to remember that a heritability estimate describes influences on individual differences in a characteristic. Environmental influences can have a profound effect on that characteristic, however, even when heritability is high. During the past century, for example, there have been significant increases in average height owing to improved nutrition and medical care, even though individual differences in height are strongly influenced by heredity. This is because environmental changes (such as improved diet and medical care) have markedly increased average height from one generation to the next, while individual differences in height have remained highly heritable (i.e., smaller parents still have smaller children; see Figure 2-2 ). In a similar manner, other research (see Chapter 10 ) indicates that the socioeconomic status of adoptive homes has a powerful effect in elevating the IQ scores of adopted children, even though the heritability of individual differences in IQ remain high (see Maccoby, 1999; Schiff et al., 1982).

Illustration of the effect of environmental changes on group differences and genetic influence on individual differences over time. NOTE: Each line represents a family lineage, with P representing parents, and c representing off-spring.

High heritability therefore does not mean low malleability. Environmental interventions—which can include improved education, health care, nutrition, and caregiving—can significantly improve developmental outcomes for children, even though individual differences in those outcomes may be strongly influenced by genetic processes. Heritability does not imply constraints on change. It is instead more relevant to appreciating how developmental outcomes can be changed. In particular, heritability may be relevant to considering the kinds of interventions that might be most effective in relation to the genetically based characteristics of children.

Some developmental behavioral genetics researchers are dissatisfied, however, with the heritability estimate because it provides a quantitative but frequently misunderstood index of genetic influence that distracts attention from the ways that behavioral genetics research can contribute to a better understanding of risk and protective factors in development (e.g., Rutter, 1997; Rutter et al., 1999a; Wahlsten, 1990; Wahlsten and Gottlieb, 1997). An authoritative review of this field noted (Rutter, 1997:391):

It has gradually come to be accepted that the precise quantification of heritability has little value because it provides no unambiguous implications for theory, policy, or practice. . . . There is little to be gained by merely quantifying the relative importance of the contributions of genetic and environmental influences because any estimates will be specific to the population studied and will be subject to change if environmental circumstances alter.

Shared and Nonshared Environmental Effects

Research in developmental behavioral genetics has also elucidated features of environmental influence on individual differences. In particular, researchers have helpfully distinguished between shared and nonshared environmental influences. Shared environmental influences are those that make individuals similar in their common environment. Nonshared environmental influences are those that distinguish among individuals within the same environment. Within a family, for example, shared environmental influences make siblings alike independent of their genetic similarity, while nonshared environmental influences make siblings different independent of genetic factors. For instance, parental divorce is a source of shared environmental influence if siblings within the family are affected similarly by this event (e.g., because of moving to a new neighborhood, loss of contact with one parent). Parental divorce can also be a source of nonshared environmental influence if siblings are affected differently by the same event (e.g., older and younger children may interpret their parents' divorce differently). This example illustrates how the terms “shared” and “nonshared” refer not to events or people, but to the effects they have on different children within the family.

Both shared and nonshared environmental influences can be estimated from adoption and twin research designs, although in different ways and with different assumptions. Within each design, however, shared and nonshared environmental effects are inferred from the resemblances among genetically related family members and are rarely observed directly or experimentally manipulated. This has caused some scholars to criticize how shared and nonshared environmental influences are estimated (see, e.g., Baumrind, 1993; Rutter et al., 1999a) and to caution that direct measurement is necessary before firm conclusions can be drawn about shared and nonshared influences (e.g., Plomin et al., 1997b).

Like heritability estimates, the difference between shared and nonshared environmental influences is often misunderstood. Some studies have shown, for example, that within families the most important environmental influences are nonshared, making siblings different from each other (Plomin and Daniels, 1987; Rowe, 1994). Some commentators have interpreted this to mean that conventional portrayals of parenting influences (such as the view that parents who use reasoning and gentle sanctions raise responsible children, or that parents who read frequently inspire their offspring to do so) are no longer valid because the important parental influences are those that make siblings different rather than alike in their characteristics (e.g., Rowe, 1994; Scarr, 1992; see also Harris, 1995, 1998). But parenting influences have long been understood by developmental scientists as sources of differences between siblings for many reasons (Collins et al., 2000; Maccoby, 1999). Parents develop unique and special relationships with each of their offspring, their childrearing efforts are experienced differently by siblings because of each child's distinctive characteristics (e.g., temperament, personality, gender, age), and good parents take these characteristics into account in adapting their general childrearing practices to their specific encounters with each child (Grusec and Goodnow, 1994). Indeed, even when parents use the same child-rearing practices with different children, they evoke different reactions because of each child's temperament, age, and other characteristics. These influences contribute to why, as every parent knows, siblings develop unique and distinctive characteristics, and parental practices help to account for these differences.

The distinction between shared and nonshared family influences is important to refining an understanding of how family processes affect children. Most importantly, it emphasizes that parental practices and family events are unlikely to have uniform effects on offspring because of how children experience, understand, and respond in individualized ways. But the distinction between shared and nonshared influences does not radically change current views of the importance of parental influences in the context of genetic individuality (see Box 2-1 ). Moreover, until findings about the nature of shared and nonshared family influences are based on observational and experimental studies, strong conclusions from developmental behavioral genetics research about how parents influence their children in shared or nonshared ways must remain tentative. Furthermore, current research indicates that it is extremely difficult to identify objective features of the environment that are “shared” or “nonshared” between siblings, and that shared and nonshared effects may depend, in part, on the hereditary characteristics of the child (Rutter, in press; Rutter et al., in press; Turkheimer and Waldron, 2000). This form of gene-environment interaction is discussed in the next section.

Understanding—and Misunderstanding—Parenting Influences. Most parents are concerned about doing the right things for their children. In recent years, however, they have had reason to question whether what they do really matters. In public (more...)

Like the focus on the heritability estimate, a strong emphasis on the relative influence of shared and nonshared family influences risks missing the important conclusion of developmental behavioral genetics research: specifically, that the action is in the interaction between heredity and environment. The manner in which the family environment accommodates to and modifies a child's heritable characteristics shapes the development of those characteristics in a family environment that is also evolving over time.

• MOLECULAR GENETICS

Developmental behavioral genetics examines nature and nurture indirectly through the behavioral characteristics of genetically related and unrelated individuals. But it would be far more informative if researchers could identify specific, individual genes associated with distinctive human characteristics, examining their behavioral consequences in concert with particular environmental influences. That goal is slowly being realized because of advances in molecular genetics, a relatively new science that is based on significant technological advances in mapping the human genome and conceptual advances in studying the connections between genes and behavior.

Molecular genetics begins with the scientifically complex task of identifying DNA markers for specific genes and connecting genes and behavior through relative linkage studies and association strategies (for overviews of these procedures, consult Plomin et al., 1997a; Plomin and Rutter, 1998; Rutter et al., 1999a). There have been significant advances in molecular genetics during the past decade owing to advances in mapping the human genome and the development of less intrusive and expensive technologies for extracting and genotyping DNA from human biological samples. There is every reason for confidence that further advances in genetic mapping and in linkage and association studies will soon provide a strong foundation for the integration of molecular genetics into the behavioral research of psychologists.

For developmental psychologists of the future, therefore, molecular genetics offers the remarkable possibility of identifying the genetic markers associated with specific behavioral propensities in children and examining the manifestations of these propensities in relation to environmental factors, developmental changes, and the influence of other genes. Molecular genetics will also enable researchers to develop more powerful analytic methods and theoretical models for understanding the influence of heredity on behavioral development. Perhaps most important, molecular genetics will help developmental psychopathologists understand the genetic bases for childhood disorders, which will include a better appreciation of the continuities between typical variability in personality functioning and atypical deviation, improved detection of continuities in psychopathological risk across developmental transitions, and the potential of reconceptualizing clinical syndromes according to their genetic bases (Plomin and Rutter, 1998). There have already been promising discoveries, such as advances toward the identification of a susceptibility gene for autism and autistic-like characteristics, and research findings suggesting inherited propensities to attention deficit hyperactivity disorder through genes regulating neurotransmitter receptors (Rutter et al., 1999b). Furthermore, impending discoveries from molecular genetics studies will provide added evidence that: (a) hereditary influences are polygenic and multifactorial, involving the impact of multiple genes coacting with environmental influences to increase the likelihood of certain behavioral propensities; (b) genetic bases for developmental disorders reflect, in most cases, extreme variations on a continuum that includes normal variants of the same characteristics; and (c) genetic effects on behavior are probabilistic (rather than predetermined) because they increase the likelihood that certain characteristics will occur, but do not directly cause them (Plomin and Rutter, 1998).

Consistent with the more complex portrayal of nature and nurture emerging from molecular genetics is a new appreciation of the importance of gene-environment interaction. Gene-environment interaction indicates that genetic susceptibility may increase an individual's sensitivity to specific environmental influences. Such an interaction is especially important in understanding hereditary vulnerability to environmental stresses that might lead to psychopathology. Gene-environment interaction is demonstrated when researchers find, for example, that there is small to moderate risk for antisocial behavior in individuals who have either a genetic susceptibility for this disorder or grow up in a stressful environment, but for individuals with both genetic and environmental risk for antisocial behavior, the probability of pathology is sharply higher (Cadoret et al., 1995a, 1995b, 1996; Rutter et al., 1999b).

Comparative studies with animals can specify these gene-environment interactions more precisely. In one investigation, for example, rhesus monkeys with a specific genetic vulnerability affecting neuroendocrine functioning who grew up under adverse (peer-rearing) conditions consumed more alcohol in experimental conditions (Campbell et al., 1986a) than did monkeys without this vulnerability. However, monkeys raised under advantageous (mother-reared) conditions with the same genetic vulnerability consumed less alcohol than those without it, suggesting that a genetic risk factor under adversity was a protective factor in advantaged conditions. Other forms of gene-environment interaction were apparent with respect to dominance-related assertive behavior in this sample, showing that positive early rearing significantly buffered the detrimental social impact of specific genetic vulnerability in young rhesus monkeys (Bennett et al., 1998; Suomi, 2000). These studies underscore how significantly developmental outcomes depend on the interaction of heredity and environment, rather than the direct effects of either. They also indicate how the behavioral effects of genetic vulnerability can be altered in the context of positive or negative early rearing.

As this research shows, the identification of gene-environment interaction is important not only to understanding developmental psychopathology but also to its prevention, since it indicates how individuals with a genetic propensity to the development of a disorder may be buffered from its emergence if their environments are made more protective. A child with an inherited vulnerability to antisocial personality is much less likely to develop this disorder in supportive, nonstressful family, school, and community environments.

Typical research designs in developmental behavioral genetics lack power to detect these interactions and, in fact, they are often not measured at all (Lemery and Goldsmith, 1999), but molecular genetics research has the potential for identifying gene-environment interactions, as the susceptibility genes to personality characteristics become identified. Behavioral studies suggest the existence of many such gene-environment interactions, such as the heightened responsiveness of temperamentally fearful, inhibited young children to maternal discipline efforts (Kochanska, 1993, 1995, 1997), the stronger impact of mother-infant synchrony on the growth of self-control of temperamentally difficult children (Feldman et al., 1999), and other illustrations of what Belsky (1997) describes as children's differential susceptibility to rearing influences. As the field of molecular genetics matures, in other words, it will become possible to understand how the hereditary characteristics of children influence their responsiveness to parental incentives, their susceptibility to environmental stresses and demands, and their vulnerability (in concert with environmental risk) to psychopathology.

Psychology is thus at the dawn of a new era. Not only will molecular genetics enable scientists in the near future to better understand how the interaction of multiple genes influences behavioral characteristics, but it will also illuminate how gene action can augment vulnerability or resistance to environmental demands. This view of the multifactorial origins of behavior, reflected especially in gene-environment interaction, is another reflection of the essential integration of nature and nurture in behavioral development.

• BRAIN DEVELOPMENT

Brain development also reflects the coaction of nature and nurture. The traditional view of early brain development describes a process under tight genetic control, and to a great extent this portrayal is true. Important regulatory genes, such as the “homeobox” genes discovered in the fruit fly, control the timing of the expression of other genes and can direct the development of an entire segment of the insect's anatomy, such as an eye or a limb. Comparable genes have been shown to exist in mammals, including humans, which play similarly significant developmental roles. There is no question that there are genetically driven developmental processes that guide the basic organization of the body and the brain, and these processes influence the growth of single cells and entire systems.

But as the opening paragraphs of this chapter illustrate, gene expression always occurs within the context of the intracellular and extracellular environments within the body, and in the context of experience in the outside environment. These multilevel environmental influences are necessary to coordinate the complex behavioral and developmental processes that are influenced by heredity, as well as to provide catalysts to gene expression that enable behavior to become fine-tuned to the external settings in which the organism lives. When songbirds first hear their species' song, or when patterned light first hits the retina of the human eye, these experiences provoke a cascade of gene expression that commits neural development to certain growth patterns rather than others. This is because the genetically guided processes of neural development are designed to capture experience and to incorporate the effects of experience into the developing architecture of the nervous system. This is especially true of human brain development.

The purpose of a brain is to store, use, and create information. The amount, complexity, and contingency of the information required for humans is far greater than that of the fruit fly, and this is one reason why the strong regulatory influence of homeobox genes in the fruit fly provides a poor model for human brain development. A limited amount of information is required to enable a fruit fly to function successfully for a short life span, and much of the necessary information can be encoded genetically. By contrast, humans acquire information primarily from experience, including their systems for thinking, feeling, and communicating. Most of human knowledge cannot be anticipated in a species-typical genome (e.g., variations in culture, language, and technology), and thus brain development depends on genetically based avenues for incorporating experience into the developing brain. This developmental integration of nature and nurture enables humans to grow and adapt as a species in a manner unequalled by any other (fruit flies don't have books, movies, radio, or television from which to learn, and the only webs available to them are dangerous ones), permitting unparalleled flexibility in behavior and development. The incorporation of experience into the genetically driven plan for human brain development helps to account for many of the unique qualities of the species.

Developmental neurobiologists have begun to understand how experience becomes integrated into the developing architecture of the human brain (see Chapter 8 for further details). First, developmental processes of brain growth are based on the expectation that certain experiences will occur that will organize and structure essential behavioral systems. These developmental processes have been called “experience-expectant” because normal brain growth expects and relies on these forms of environmental exposure (Greenough and Black, 1992). Not surprisingly, the experiences that are incorporated into normative brain development are ubiquitous in early life: exposure to patterned light and auditory stimulation are two of the best studied, and there are likely to be others (such as acquiring physical coordination in gravity). Deprivation of these essential forms of environmental exposure can cause life-long detriments in behavioral functioning.

Second, throughout life, new experiences also help to trigger new brain growth and refine existing brain structures. This is, in fact, how learning, memories, and knowledge are acquired and retained throughout the life course. These developmental processes are called “experience-dependent” because they rely not on species-typical environmental exposures but instead on the idiosyncratic and sometimes unique life experiences that contribute to individual differences in brain growth (Greenough and Black, 1992). For example, there is evidence that brain functioning is changed in subtle ways if a person is a stringed instrument musician, which can alter neural areas governing the finger movements of each hand (Elbert et al., 1995). Experience-dependent brain development is thus a source of the human brain's special adaptability and lifelong plasticity (Nelson, 1999). Each person has a unique history of experience-dependent influences on brain growth.

Brain development therefore depends on an intimate integration of nature and nurture throughout the life course. Indeed, processes of brain development that were traditionally regarded as genetically hard-wired (such as visual capability) have now been discovered to depend on an exquisitely coordinated dance between experiential catalysts and the hereditary design for brain growth. Both nature and nurture are essential to the development of a brain of uniquely human capacities and potential. These developmental processes are discussed in further detail in Chapter 8 .

The integration of nature and nurture, revealed in the findings of behavioral genetics, molecular genetics, and brain development research, should significantly influence how human development is understood. Contrary to the traditional view that heredity imposes constraints and environments induce change in developmental pathways, research in developmental psychobiology shows that nature and nurture are each sources of stability and malleability in human growth. More importantly, their coaction provides the impetus for development, whether it is viewed from the perspective of “experience-expectant” brain growth or the interplay between of genes and environments. The developmental action is in the interaction of nature and nurture.

Although work in developmental psychobiology has contributed most significantly to a revised view of hereditary influences, it also causes us to regard the environment in a different way. Most importantly, we now appreciate that how children respond to environmental incentives is based, in part, on hereditary predispositions (gene-environment interaction), that the social environment adapts itself to a child's inherited characteristics (O'Connor et al., 1998), and that one of the most important ways of understanding environmental influences is how children are individually affected (the nonshared environment). Environmental influences are not just externally “out there”: a child's responses to the family, the neighborhood, and the culture hinge significantly on genetically based ways of feeling, interpreting, and responding to environmental events. For parents and practitioners, this underscores the importance of taking into account each child's individuality to create conditions of care that accord with the child's inherited attributes and which, for some children, provide buffers to modify the expression of heritable vulnerabilities. Indeed, the importance of the goodness of fit between the environment and heritable characteristics also shows why human relationships are so profoundly important in early development, since human partners who know a child well are the environmental influences that can most easily accommodate helpfully to a child's individuality.

The inextricable transaction between biology and experience also contributes to a better understanding of developmental disorders and the effects of early intervention. Hereditary vulnerabilities establish probabilistic, not deterministic, developmental pathways that evolve in concert with the experiential stressors, or buffers, in the family, the neighborhood, and the school. That is why early experiences of abuse, neglect, poverty, and family violence are of such concern. They are likely to enlist the genetic vulnerabilities of some children into a downward spiral of progressive dysfunction. By contrast, when children grow up in more supportive contexts, the hereditary vulnerabilities that some children experience may never be manifested in problematic behavior. Understanding the coaction of nature and nurture thus contributes to early prevention.

Early intervention, especially when it is well tailored to a child's individual characteristics, can be helpful in shifting the odds toward more optimal pathways of later growth, but because the nature-nurture interaction is dynamic over time, there are no guarantees. Each new developmental stage provokes new forms of gene-environment transactions that may alter, or maintain, previous pathways. This means that giving young children a good early start increases but does not guarantee later success, and that children who begin life at a disadvantage are not doomed to enduring difficulty. The interaction of nature and nurture underscores the importance of creating current conditions of care that respect inherited characteristics, recognizing that nature-nurture is a source of continuing potential change across the life course.

Finally, research in developmental psychobiology emphasizes the continuity that exists between typical and atypical variability in human characteristics. One of the important emerging insights of molecular genetics is that many psychological difficulties arise not from single-gene mutations, but instead from extreme variations on a biological continuum that includes normal variants of the same characteristics. There is, in other words, a very broad range of individual differences in which the boundaries between the normative and the atypical are matters of degree rather than quality. This means that, in studying the growth of typical children, researchers gain insight into the developmental dynamics of atypicality and that, conversely, efforts to understand the challenges of children with developmental disorders yield insights into normative growth.

These conclusions are consistent with the broader themes of this report and of the findings of research on early childhood development. Taken together, they indicate that despite a long historical tradition of dissociating the effects of nature and nurture on human character and development, their influences are, in the end, indissociable.

Although this chapter focuses primarily on genetic influences that contribute to individual differences among children, it is essential to remember that genetic influences also account for the characteristics that humans share as a species, such as upright walking and language. Indeed, the inseparability of nature and nurture is also reflected in the fact that both nature and nurture are required for children to acquire these and other attributes that all humans share.

Within the nucleus of every cell are chromosomes containing genes, which are segments of DNA. Genes direct the synthesis of proteins that are incorporated into the structure of the cell, regulate its biochemistry, and guide other genetic activity. Genes ultimately affect physical and behavioral characteristics through these influences on the cells within every living being. Although each cell contains genes that are identical to the genes of every other cell, not all genes function in the same way, and this accounts for why cells function differently from one another. Some genes act continuously, for example, while other genes in the same cells turn on temporarily, and others are never expressed. As one colorful description notes, if each gene is represented as a light bulb that is either activated or not, we would see a distinct twinkling of lights within each cell during its normal functioning (Leger, 1992). This is why organisms can have trillions of cells, all of which have the same DNA but many different forms and functions.

• Cite this Page National Research Council (US) and Institute of Medicine (US) Committee on Integrating the Science of Early Childhood Development; Shonkoff JP, Phillips DA, editors. From Neurons to Neighborhoods: The Science of Early Childhood Development. Washington (DC): National Academies Press (US); 2000. 2, Rethinking Nature and Nurture.
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Research Article

The Role of Nature and Nurture for Individual Differences in Primary Emotional Systems: Evidence from a Twin Study

Contributed equally to this work with: Christian Montag, Elisabeth Hahn

* E-mail: [email protected]

¶ ‡ These authors are shared first authors on this work.

Affiliation Institute of Psychology and Education, Ulm University, Ulm, Germany

Affiliation Department of Psychology, University of Saarbrücken, Saarbrücken, Germany

Affiliations Department of Psychology, University of Bonn, Bonn, Germany, Center for Economics and Neuroscience, University of Bonn, Bonn, Germany

Affiliation Department of Psychology, The University of North Carolina at Charlotte, Charlotte, North Carolina 28223, United States of America

Affiliation College of Veterinary Medicine, Washington State University, Washington 99164, United States of America

• Christian Montag, 
• Elisabeth Hahn, 
• Martin Reuter, 
• Frank M. Spinath, 
• Ken Davis, 
• Jaak Panksepp

• Published: March 21, 2016
• https://doi.org/10.1371/journal.pone.0151405
• Reader Comments

3 Jun 2016: Montag C, Hahn E, Reuter M, Spinath FM, Davis K, et al. (2016) Correction: The Role of Nature and Nurture for Individual Differences in Primary Emotional Systems: Evidence from a Twin Study. PLOS ONE 11(6): e0157200. https://doi.org/10.1371/journal.pone.0157200 View correction

The present study investigated for the first time the relative importance of genetics and environment on individual differences in primary emotionality as measured with the Affective Neuroscience Personality Scales (ANPS) by means of a twin-sibling study design. In N = 795 participants (n = 303 monozygotic twins, n = 172 dizygotic twins and n = 267 non-twin full siblings), moderate to strong influences of genetics on individual differences in these emotional systems are observed. Lowest heritability estimates are presented for the SEEKING system (33%) and highest for the PLAY system (69%). Further, multivariate genetic modeling was applied to the data showing that associations among the six ANPS scales were influences by both, a genetic as well as an environmental overlap between them. In sum, the study underlines the usefulness of the ANPS for biologically oriented personality psychology research.

Citation: Montag C, Hahn E, Reuter M, Spinath FM, Davis K, Panksepp J (2016) The Role of Nature and Nurture for Individual Differences in Primary Emotional Systems: Evidence from a Twin Study. PLoS ONE 11(3): e0151405. https://doi.org/10.1371/journal.pone.0151405

Editor: Daimei Sasayama, Shinshu University School of Medicine, JAPAN

Received: August 20, 2015; Accepted: February 26, 2016; Published: March 21, 2016

Copyright: © 2016 Montag et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Ethical restrictions prevent public sharing of data. Parties interested in obtaining the data may contact the authors.

Funding: CM is funded by a Heisenberg grant awarded to him by the German Research Foundation (DFG, MO 2363/3-1). Moreover, the present study is funded by the German Research Foundation (DFG, MO 2363/2-1), www.dfg.de .

Competing interests: The authors have declared that no competing interests exist.

Introduction

The study of primary emotional systems represents an important research endeavor to better understand psychological well-being and psychopathologies such as affective disorders in humans [ 1 ]. Specifically, it has been put forward that imbalances in these ancient emotional brain systems go along with psychopathologies, e. g. that a lack of PLAY behavior in childhood might be linked to Attention Deficit Hyperactivity Disorder (ADHD) later on or that an overactivation of the SADNESS (separation-distress, psychological-pain) system and the subsequence reduction of SEEKING urges are major cause for depression (for full discussion, see [ 2 , 3 ]). (Primary emotional systems are printed in capital letters, as a formal designation for primal emotional systems of mammalian brains, partly intended to distinguish them from the vernacular emotional terms commonly used in emotional and other psychological research. The need for scientifically clear designators for primary-process (i.e., evolved) brain emotional and motivational systems is essential, and the formal designators should help avoid mereological fallacies (part-whole confusions) which are abundant in neuropsychological discourse (see [ 4 ]). A major goal of Panksepp’s Affective Neuroscience perspective has been dedicated to elucidating how primal (i.e., evolved) neuropsychobiological emotional networks underlie core affective processes (using animal models to illuminate foundational human affects), and how their upward influence in the brain shape diverse higher-order psychological and behavioral processes. By applying techniques such as deep (subcortical) electrical stimulation of the mammalian brain and pharmacological challenges his group has provided evidence for seven distinct primary emotional systems (SEEKING, RAGE, FEAR, LUST, CARE, PANIC and PLAY) anchored in phylogenetically old brain areas which not only instigate instinctual emotional behaviors, but also influence and control the secondary processes of learning and memory and tertiary-process such as cognitive decision making [ 1 ]. These primal emotions are survival systems, which with various sensory and homeostatic (e.g., HUNGER and THIRST) affects constitute the primal value (reward and punishment) systems of the brain. These subcortical systems are foundational for higher mental processes in all animals since extensive damage to such systems compromise consciousness, and they are envisioned to guide the development of higher mental processes, including personality dimensions which, with maturation, gradually provide higher reciprocal-regulatory cortical control over lower affective processes.

The mammalian (especially human) prefrontal cortex and other neocortical regions can control emotional outbursts from subcortical areas (providing top-down behavioral and psychological regulation). But in extreme situations—such as in high danger—our brains often respond with stereotypic genetically-anchored affective response patterns (instigating bottom–up arousal of higher-order brain processes) such as strategies for fight, flight or freezing (e. g. [ 5 ]), which helped our ancestors to not only escape various hazardous situations but to develop cognitive skills to avoid them in the future (see also a new questionnaire measuring these distinct fear tendencies [ 6 ]). So different primary/basic emotions have different functions with respect to survival and reproductive behaviors. In the end a better understanding of the functioning and interplay of these emotional systems should facilitate development of new therapeutics to better treat a wide range of psychiatric disorders [ 2 , 3 ].

The seven primary emotional systems of Panksepp’s primary-process affective neuroscience can be divided into two larger groups of positive and negative emotions. The emotional systems belonging to the first group of positive emotions are called SEEKING, LUST, CARE and PLAY (in presumed evolutionary order), whereas the latter group representing negative emotions comprises RAGE (also labeled ANGER in discussions of human personality), FEAR (or “anxiety” in the vernacular), and PANIC (namely primary-process separation distress, or higher-order SADNESS, which we deemed a more clear and appropriate designator for human personality profiling). The SEEKING system energizes human beings and helps them not only to be energized with “enthusiasm” and “interest”, in explorative/investigative way in everyday life. The PLAY system has been best characterized not only by the instinctual nature of rough and tumble play in most mammals–a very bodily evolved form of play–best observed in all young mammals, including human childhood, with the brain mapping providing clarification of brain regions where Deep Brain Stimulation (DBS) evokes laughter-type play vocalizations in animal models [ 7 ]. The function of the PLAY system probably relates to learning about social structures/hierarchies (e.g., eventual social dominance), learning to cope with losing or being defeated, shaping social-appetitive motoric skills and from a psychological perspective, simply having fun (which may promote bodily and mental health). The LUST and CARE system are of high importance for reproductive success and social bonding and are deeply entwined. The PLAY system is probably evolutionary the youngest with LUST reproduction circuits evolving earlier than the genetic programs for CARE—nurturing other individuals especially one’s own offspring. The FEAR system has been already mentioned above and helps mammals to free themselves from danger. The RAGE/ANGER system facilitates acquiring and holding-on to resources, and can be activated by frustrations (that can arise from higher-order encoding of desires). Finally, the PANIC/SADNESS system reflects arousal of what has traditionally been called “separation distress” the chronic overactivity of which is associated with depression [ 2 , 3 , 8 ]. For cross-mammalian brain research purposes, this system has been formally designated the PANIC system, which is illustrated by typical panic behaviors and feeling (i.e., separation distress calls, commonly called “crying”) when children get lost and are out of sight of their parents or other caregivers.

Besides the importance of neuroscientific techniques, especially DBS, to study primary emotional systems, Davis et al. [ 9 ], published a self-report inventory called Affective Neuroscience Personality Scales (ANPS), updated and refined in Davis & Panksepp [ 10 ], aimed at measuring individual differences in these primary emotional systems. The publication of these scales represents an important addition to the toolbox of biologically/behaviorally oriented personality psychologists, because Panksepp’s primary emotional systems could be viewed as being among the evolutionary oldest contributors to human personality (influencing human personality bottom-up development as reflected by their neuroanatomical foundations in the “old-mammalian” and “reptilian” areas of Paul MacLean’s Triune Brain Concept; see also [ 11 ]). The ANPS contrasts to classic questionnaires reflecting the Five Factor Model of Personality (e. g. [ 12 ]) and may be more appropriate for guiding in the investigation of the biological underpinnings of individual differences in primary sources of temperament, namely one’s genetically controlled emotional strengths and weaknesses. For instance, Montag & Reuter [ 13 ] highlight the potential importance of these scales in the context of disentangling the molecular genetics of primary emotional systems and personality. As the Five Factor Model of Personality is based on a lexical (adjective-based) approach it does not help in hypothesizing about diverse neurobiological affect-engendering brain systems that are critical brain substrates underlying human personality. The usefulness of the ANPS for biologically-oriented personality psychology can be best explained by a small example. If animal models show that PLAY behavior in rodents is modulated by opioids (as it is, see [ 14 ]), the dynamics of brain opioid systems should also be of relevance for human ludic activities, because these ancient brain systems are highly conserved across species.

As postulated by Turkheimer [ 15 ] and newly confirmed within a meta-analysis [ 16 ], all human traits are heritable. For the Big Five personality traits, several studies in the past 50 years of research revealed a strong genetic basis for all five personality factors in the range of about 40–60% (e.g. [ 17 ]). In terms of environmental contributions, comparable amounts of personality variation can be explained by non-shared environmental experiences. This has also been underlined in a recent meta-analysis [ 18 ]. For the ANPS scales, Davis et al. [ 9 ] investigated the extent to which self-reports derived from the ANPS questionnaire were related to self-report measures of the Big Five personality traits, i.e. how closely core emotional systems were associated with basic personality traits. Each of the six ANPS scales was found to be closely related to at least one of the Big Five personality scales. The authors concluded that the six core emotional systems assessed by the ANPS scales constituted the roots of adult personality structures, and developmentally contributed to the construction of higher-order emotional traits. Given these findings and the theoretical concept behind the ANPS, one would postulate a strong genetic basis of all the basic emotional systems. With respect to associations among the ANPS scales, which can be depicted by a higher-order positive and negative system, one would further expect a common genetic basis underlying these emotional systems. Please note that LUST was intentionally dropped from the ANPS, because it overlaps greatly with homeostatic affects (e.g., peripheral hormonally-controlled core affects) and because of social reticence or lack of frankness in responding to questions concerning one’s sexuality. Also, such affective responses to one set of questions could potentially create spill-over problems for people responding to other trait questions frankly, but as discussed later, a Spirituality scale was added to evaluate therapeutically-important existential dimensions of existence.

To the best of our knowledge—there are currently no scientific-empirical studies showing the relative contribution of genetic influences on individual differences in these primal emotional foundations of human personality. Hence, the genetic and environmental etiology of individual differences in these traits as well as the etiology of associations among these systems remains poorly understood. Given this fact, the present study aimed to quantify for the first time, the relative influence of both nature and nurture on individual differences in primary emotional systems by means of identical (monozygotic) and fraternal (dizygotic) twin study. Univariate and multivariate genetic modeling was applied to investigate the extent of genetic sources on each emotional system and covariations among them to explore the structural nature of primary emotionality.

Participants

The sample was drawn from the Twin Study on Internet- and Online-Game Behavior (TwinGame), a study of adult twins and non-twin sibling pairs reared together. To realize the twin sample, we reverted to contact information from twins who had participated in previous voluntary German twin studies (e.g. SOEP twin study, ChronoS; for details see [ 19 ]. In addition, we invited twins and non-twin sibling pairs (with a maximum age difference of three years) via public announcements to participate in the study. Twins with previous contact information were contacted via telephone and invited to complete an online or paper-pencil version of our questionnaire addressing different areas, such as Internet consumption behavior, personality, health, subjective well-being, empathy and several attitudes. The resulting data set for the present study contained a total of 795 individuals (56% overall participation rate) including n = 303 monozygotic twins (149 complete pairs), n = 172 dizygotic twins (85 complete pairs), n = 267 non-twin siblings (122 complete pairs) and 53 individuals with unknown zygosity. Information on age and the gender distribution is presented in Table 1 .

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https://doi.org/10.1371/journal.pone.0151405.t001

All participants filled in the Affective Neuroscience Personality Scales (ANPS), as described in the next section. Zygosity was determined through self-reports assessing physical similarity (e.g., eye color, hair structure, skin color) as well as the frequency of twin confusion by different relatives, teachers, and peers across the life span (accuracies in the magnitude of 95%; for details, see [ 20 , 21 ]). The study was approved by the research ethics’ committee of the University of Bonn, Germany.

Questionnaire

We administered the German version of the ANPS (Reuter, Panksepp, Davis & Montag, test manual to be published at Hogrefe Publishers, soon) containing 110 items ranging from strongly agree to strongly disagree (four-point Likert scale) and reflecting a German translation of the ANPS as published by Davis et al. [ 9 ]. The ANPS measures individual differences in all mentioned primary emotional systems with the exception of LUST for the reasons mentioned above. To reiterate, the questionnaire contains one additional scale called Spirituality, which reflects no known primary emotional system, but is included due to its potential psychotherapeutic relevance, (e. g. in the treatment of alcohol addiction). In the present sample, internal consistencies of the German version of the ANPS were satisfying and ranged from .69 (SEEK) to .87 (FEAR) which was in line with the psychometric characteristics reported by Davis et a. [ 9 ]. All these parameters are summarized in Table 2 . Bivariate phenotypic correlations among the six ANPS scales are presented in Table 3 .

https://doi.org/10.1371/journal.pone.0151405.t002

https://doi.org/10.1371/journal.pone.0151405.t003

Statistical Analyses

First, ANPS scale scores were computed by taking the sum of the corresponding items (in part reverse coded) for each ANPS factor as described by Davis et al. [ 9 ]. Prior to behavior genetic modelling, age and sex effects as well as prerequisites for structural equation modelling were inspected for each scale. The perfect correlation for age and sex in same-sex twins can inflate twin similarities [ 22 , 23 ]. To address this potential confounding, raw scores of the ANPS scales were corrected for linear and quadratic sex and age effects as well as interaction effects between sex and age prior to behavior genetic analyses by using multiple regression analyses. Following standard practice, genetic analyses were based on residual scores. Further, we basically used the standard model for twins reared together to decompose the phenotypic variation into its genetic and environmental variance components. The standard twin design is based on several assumptions: First, the equal environment assumption (EEA) assumes that MZ twins share environmental influences to the same degree as DZ twins (e.g., Borkenau, Riemann, Angleitner, & Spinath, 2002). Second, no assortative mating is assumed. Third, there is no gene-environment correlation or interaction (Purcell, 2002). In general, different sources of variance can be considered to explain why individuals differ with respect to certain characteristics and behaviors. On the one hand, individuals can differ because of genetic differences between them or vice versa family members (e.g., twins, siblings) can be similar to each other because they share a certain amount of genetic similarity. The genetic variance indicated as overall heritability can be subdivided into additive genetic influences (commonly denoted as A ) and non-additive genetic influences, modeled as genetic dominance (commonly denoted as D ). On the other hand, resemblance between family members can be due to shared environmental experiences contributing to similarity while differences between family members can be explained by different environmental experiences that are specific to each individual and contribute to dissimilarity. Hence, the environmental variance comprises shared (commonly denoted as C ) and non-shared environmental influences (commonly denoted as E ). Non-shared environmental influences are usually modeled as residual variance that includes measurement error [ 24 ].

In the basic twin model, analyses are based on the comparison of the MZ and DZ twin similarities that is being traced back to the difference in the proportion of segregating genes shared between MZ twins and DZ twins. More specifically, different patterns of MZ and DZ resemblance suggest which influences should be expected to be important. For instance, higher MZ twin correlations than DZ twin correlations are indicative of genetic influences in general because of the higher genetic similarity of MZ twins. MZ twins share 100% of their additive genetic background, while DZ twins (and non-twin siblings) share on average only 50% of additive genetic influences. If the MZ twin correlation is more than twice the DZ twin correlation, there is also evidence of genetic effects due to dominance over additive genetic influences because MZ twins share 100% D influences, while for DZ twins, the dominance component should be about .25. Less than perfect MZ twin correlations (rMZ< 1) suggest non-shared environmental influences, not only developmental-learning but also post-natal epigenetic ones, contributing to this dissimilarity. Comparable high correlations for both MZ and DZ are indicative of shared environmental influences. In the twins reared together model, however, genetic dominance and shared environmental influences are confounded and cannot be estimated simultaneously [ 25 ]. Whether shared environment or genetic dominance can be expected in a particular model depends on the pattern of MZ and DZ twin similarities. In the present design, we included a third group of non-twin siblings. Just as DZ twins, non-twin siblings share on average half of their segregating genes (A) and 25% D influences. However, twin and non-twin siblings may differ concerning the impact of shared environment. DZ twins share the same prenatal environment, belong to the same cohort of children and because they are twins there could be something like a “specific twin environment”. Therefore, sources of variation unique to twins might be valid if DZ twins remain more alike than non-twin siblings after genetic effects are accounted for. To investigate twin specific environmental influences, we first specified different shared and non-shared environmental influences for twins (MZ and DZ twins) and non-twins siblings. After fitting this model, we equated twin and non-twin environmental influences and compared the fit statistics to determine the importance of twin-specific environmental influences.

MZ and DZ as well as non-twin sibling variance–covariance matrices were calculated as intra-class correlations (ICCs) and analyzed by fitting genetically informative structural equation models via maximum likelihood using OpenMx [ 26 ]. To test for the assumptions of mean and variance homogeneity in the CTD, first, a fully saturated model was tested against a saturated model where means and variances were equated within twin and sibling pairs and across the groups (i.e., MZ, DZ, siblings) for each of the ANPS scales. The same procedure was performed prior to multivariate modeling. We then fitted univariate genetic models for each ANPS scale separately including the test whether twins differ significantly from non-twin siblings as described above. To gain a first insight into possible underlying sources of covariance among the six ANPS scales, multivariate cholesky decompositions [ 27 , 28 ] were fit to the data. This approach can be used (a) to determine the importance of genetic and environmental influences on associations between variables independent of their influence on other variables and (b) to analyze the extent to which genetic as well as environmental influences on the variables overlap. Further, more restricted and more theoretically driven models, such as different independent and common pathway models, were fit to the data to test for a possible distinction between for example a positive and negative component of basic emotional systems. Within an independent pathway model [ 29 ], common genetic and environmental factors can be specified representing shared variance between all ANPS scales or alternately representing a positive and a negative component of emotionality. These common genetic and environmental factors influence the observed variables directly, without an intermediate higher order factor. In addition, scale specific factors are specified. Since the evidence for the existence of a clear distinction between a negative and positive emotional system is scare, additional common pathway models [ 30 ] were investigated. The first common pathway model assumes that the phenotypic covariance between all six scales can be explained by a single ‘phenotypic’ latent variable that can be decomposed into genetic and environmental factors. The second common pathway model specifies two phenotypic latent variables, one for SEEK, CARE and PLAY as positive component and one for FEAR, ANGER and SADNESS as negative component. Also, combined independent pathway and cholesky specifications were applied to the data (for similar implementations of these models, see [ 31 ]). Given that the cholesky decomposition model is fully parameterized, it can be used as a reference model to evaluate the fits of the more restricted models.

Overall model fit was evaluated by using the χ 2 -test as well as the Akaike’s information criterion (AIC; [ 32 ]). The lower the AIC, the better the fit of the model to the observed data. Due to the limited sample size and hence power considerations, we focus on the results for the full models (ADE and ACE models), instead of reduced models (e.g. AE model without shared environmental influences), given that the exclusion of any genetic or environmental effect may result in biased estimates of the remaining factors in the model, even if the removed factor was not significant [ 25 ]. With respect to multivariate model fitting, nested submodels were compared by hierarchic χ 2 -test. The χ 2 -statistic is computed by subtracting -2LL (log-likelihood) for the full model from that for a reduced model. We performed model fit comparisons for each multivariate submodel with respect to the full cholesky model as well as the respective full model within the specific type of multivariate model (e.g. within the group of independent pathway models). Given the complexity of the multivariate models, we also observed reduced models (e.g. dropping common or specific D influences) here.

Descriptive statistics for each dimension of the ANPS for the total sample as well as separately for each group are provided in Table 2 . Mean and variance differences among twin and sibling groups were inspected given that they can affect overall model fit [ 33 ]. For each ANPS factor the normal distribution could be assumed according to visual inspection, skewness and kurtosis statistics and the results of the Kolmogorov-Smirnov goodness-of-fit test (p-values between .13 and .95). Correlations between age and ANPS scales ranged between -.02 (for Spirituality) and .24 ( p < .01; for PLAY). For FEAR ( t (793) = 6.20; p < .01), CARE ( t (793) = 9.27; p < .01), ANGER ( t (793) = 3.41; p < .01), SADNESS ( t (793) = 9.67; p < .01) and Spirituality ( t (793) = 3.16; p < .01), females scored slightly to modestly higher than males. (For these ANPS scales, we also inspected twin and sibling resemblances for male and female pairs separately to see if the relative importance of genetic and environmental influences differs for male and female. For all scales, patterns of resemblances were comparable to those derived from to total twin and sibling groups indicating no meaningful gender differences with respect to the relative contribution of genetic and environmental influences. Therefore heritability was estimates based on the total sample.) After correction for age and sex, there were no statistically significant differences between group means and variances as determined by one-way ANOVAs and Levene’s tests for the residual scores of all ANPS dimensions. As can be seen in Table 3 , correlations ranged between .00 and .66 for twin 1 as well as .01 and .62 for twin 2 indicating a large overlap between specific ANPS scales. Table 4 shows twin and non-twin sibling ICCs as well as p-value differences for ICCs between DZ twins and non-twin siblings. As can be seen, MZ twin correlations exceeded those of the DZ twin and non-twin sibling pairs in all cases. For FEAR, ANGER, PLAY and SADNESS, MZ twin correlations were over double the DZ correlations suggesting genetic dominance influences to be especially important. Regarding SEEK CARE and Spirituality, twin correlations rather pointed to shared environmental influences. Apart from the pattern of twin similarities, relatively high resemblances within non-twin siblings rather indicated shared environmental influences for all ANPS dimension except SEEK and SADNESS. Moreover, sibling resemblances were significantly different from the corresponding DZ twin resemblance for CARE. As described above, both genetic dominance and shared environment cannot be estimated simultaneously. Because of these somewhat ambiguous patterns of similarities, we compared models including shared environment or genetic dominance (based on AIC) for all ANPS dimensions. Model fit statistics for the full and best-fitting models as well as parameter estimates are shown in Table 5 . Model fitting results showed good model fits for all univariate models compared to the saturated model.

https://doi.org/10.1371/journal.pone.0151405.t004

https://doi.org/10.1371/journal.pone.0151405.t005

First of all, models with different environmental estimates for twin and non-twin sibling pairs (i.e. assuming specific twin influences) did not fit the data significantly better than either of the models equating these influences. The final models for all ANPS scales favored equal environmental estimates across all groups. For ANGER and Spirituality an ACE model including additive genetic, shared and non-shared environmental influences yielded the best model fit while for the remaining dimensions an ADE model including additive and non-additive genetic as well as non-shared environmental influences fitted the data best. Fully standardized, heritability estimates (including additive and non-additive genetic influences) ranged from 33% for SEEK up to 69% for PLAY. Regarding FEAR, PLAY and SADNESS these genetic influences were in large part of a non-additive nature while SEEK and CARE showed only small proportions of non-additivity (between 3% for CARE and 68% for PLAY). With respect to the ACE models for ANGER and Spirituality, shared environmental influences were not significant and explained only 9%, respectively 5% of the variance. In comparison, non-shared environmental influences ranged between 31% (PLAY) and 67% (SEEK). Although internal consistencies for the ANPS scales were all no less than acceptable, any random measurement error affects estimates of genetic and environmental influences that typically lead to an underestimation of heritability [ 22 ]. Therefore, we further corrected heritability estimates (including additive and non-additive influences) for the corresponding reliabilities of the scales to get a more appropriate basis to compare them. (Heritability estimates from the model were standardized based on a variance of 1. To get estimates for the true variance corrected for measurement error, we used the following formula: h 2 corr = h 2 /α) After correction, lowest heritability estimates were found for ANGER (37%) and SEEK (48%), followed by SADNESS (56%), FEAR (60%), and Spirituality (64%). Highest estimates appeared for CARE and PLAY (82% and 88%).

The model fitting results for the multivariate genetic models are presented in Table 6 . All multivariate genetic models were tested compared to the multivariate saturated model and showed no significant differences in overall model fit statistics. The full cholesky decomposition model including specific and common additive and non-additive genetic as well as non-shared environmental influences for each of the six ANPS scales and among them provided a good fit to the data. Compared to this ‘baseline’ model, common pathway models (Model 13 and 14) with phenotypic latent factors (one or two factors) did not describe the data well. Within the independent pathway models (Model 4–12), the best fitting model (Model 9; see Fig 1 for an illustration) included an independent pathway specification for additive genetic influences and a cholesky decomposition for non-additive genetic influences as well as for non-shared environmental influences.

The best fitting model, with an independent pathway specification for additive genetic influences (A), and a cholesky decomposition for non-additive genetic influences (D) and non-shared environmental influences (E). For a better illustration, the model only shows A and E influences. D influences are not shown in the Figure, but were modeled the same way as E influences using a cholesky decomposition. For simplicity, the model is shown only for one member of a pair.

https://doi.org/10.1371/journal.pone.0151405.g001

https://doi.org/10.1371/journal.pone.0151405.t006

Table 7 provides standardized coefficients of additive genetic, non-additive genetic and non-shared environmental influences on the variance of each scale as well as the covariation among the scales based on the best fitting model. The results showed that the additive genetic variance (between 1% and 19%) in each ANPS scale was common to all six scales and that there was no specific additive genetic variance for a specific ANPS scale. With respect to non-additive genetic influences, genetic correlations between the scales were small to moderate and ranged between -.55 and .52. This means that only a part of the non-additive genetic variation was common to the specific scales. The same pattern can be seen for the non-shared environmental influences. Environmental correlations ranged between -.16 and .51.

https://doi.org/10.1371/journal.pone.0151405.t007

The present study aimed to investigate the influence of genetics and the environment on individual differences in ANPS-estimated primary emotional systems by means of a twin study. Our results show that every scale of the ANPS is influenced by genetics, but to varying degrees. The lowest heritability estimates are observed for the SEEK, ANGER and SADNESS system ranging between 31 and 40% (corrected 42 and 58%). Highest heritability estimates are observed for FEAR, CARE and PLAY going beyond .50. The genetic influence on individual differences in the PLAY system is especially pronounced (about .67; corrected .86). Thereby the results were comparable to findings of other twin studies using different personality inventories such as the Five Factor Model (see [ 17 ] for a review). Previous studies on the Big Five personality traits reported substantial genetic influences to a comparable degree. Moreover, for most of the Big Five personality traits, especially Neuroticism, Extraversion, Openness as well as Conscientiousness, there is substantial evidence for non-additive genetic influences [ 4 , 34 ]. Therefore, one explanation for the relation between PLAY and Extraversion and the connection of FEAR, ANGER and SADNESS with Neuroticism [ 9 ] could be that there is a genetic link including non-additivity between these constructs.

Moreover, a comparison of a variety of different multivariate genetic models provided first insights into genetic and environmental causes of phenotypic relations among the ANPS scales. The best fitting model showed an independent pathway specification for additive genetic influences and a cholesky composition for non-additive genetic as well as non-shared environmental influences. The finding of a single additive genetic component indicates that different primary emotional systems are not distinct at the level of additive genetic influences because all six scales loaded on one genetic factor. One explanation for this common genetic factor could be a similar set of genes. However, for non-additive genetic influences as well as non-shared environmental influences, correlations were small to moderate suggesting independent influences on specific emotional systems. So, although it can be assumed that genetic influences—mainly represented by a common genetic factor for all scales—are important, influences of non-shared environmental factors unique to each ANPS scale explain the remaining part of the variance. As the primary emotional systems could be seen as the basis of the Five Factor Model (e.g. PLAY underlying Extraversion or SEEK underlying Openness to Experience), similar non-environmental factors could play a role as observed in twin studies on the Five Factor Model. Such non-environmental variables being responsible for differences of the investigated persons of the same family could be “family composition, parental treatment, sibling interactions and extra-familial influences such as peers in addition to non-systematic factors. “([ 35 ]; p. 584)

Following from these findings the administration of the scales is of special value for molecular genetic studies (e. g. [ 36 , 37 , 38 ] These studies show that (an interaction of) dopaminergic genetic markers, but also an interaction of serotonergic and oxytocinergic markers are associated with individual differences in the primary emotional systems as measured with the ANPS), because a) an influence of genetics on individual differences of all primary emotional systems is demonstrated and b) the ANPS along with Panksepp’s cross species Affective Neuroscience approach to understanding primal emotions [ 1 ] now represents a genetically substantiated guide to test different brain transmitter systems and neuroanatomical structures (e. g. with MRI, [ 39 ]) in the context of each of the distinct primary emotional systems.

There are also limitations. Clearly, the questionnaire represents a cognitive approach to one’s own emotional experience; therefore it does not grasp emotional tendencies in a neuroscientifically direct way, e. g. as by directly observing human emotional behavioral and concurrent brain activities. This is put by Davis & Panksepp ([ 10 ], page 1952) as follows: “Although ANPS items attempt to address primary affects directly, since all self-report assessments must include cognitive reflection, we interpret the ANPS scales as tertiary (thought-mediated) approximations of the influence of the various primary emotional systems in people’s lives.”A second limitation concerns the sample size of the present twin study, which is relatively small. Previous studies have shown that some influences (e.g. shared environment) were often found to be non-significant due to small sample sizes and in consequence less power to detect them. In consideration of this issue, we decided to present the full model and not to exclude non-significant influences. However, compared to the classical twin approach, our sample was not limited just to twin data, which strengthens the assumption that the results are representative of the population. Third, there are some limitations that are inherent to most behavior genetic studies concerning different assumptions of the classical twin design (for an overview, see [ 21 ]). For example, the effect of gene-environment correlation and interaction could also be relevant in explaining individual differences in primary emotional systems, and hence should be considered in future research which requires information about specific environmental characteristics or specific genes.

In sum, the present study demonstrates that the ANPS is a new substantive empirical tool for biological oriented personality psychologists, which can advance the understanding of other major dimensions of human life. We anticipate the relevance of such understanding to eventually contribute to the study of imbalances of various primary emotional systems not only in various human addictions, but also a wide range of psychopathologies [ 40 , 41 ] especially various affective disorders (e.g. [ 2 , 3 , 8 ]).

Acknowledgments

The present study was funded by a grant awarded to CM by the German Research Foundation (DFG MO 2363/2-1). Moreover, the position of CM is funded by a Heisenberg grant awarded to him by the German Research Foundation (DFG MO 2363/3-1).

Author Contributions

Conceived and designed the experiments: CM EH MR FS. Performed the experiments: EH. Analyzed the data: EH. Wrote the paper: CM EH KD JP. Conceptualized the ANPS questionnaire, on which this study is based, so they provided additional advice of tremendous importance for the study: KD JP. Collected the data: EH.

• 1. Panksepp J. Affective Neuroscience. London: Oxford University Press; 1998.
• View Article
• Google Scholar
• PubMed/NCBI
• 11. MacLean P. The triune brain in evolution: Role in paleocerebral functions. New York, NY: Plenum Press; 1990.
• 17. Johnson AM, Vernon PA, Feiler AR. Behavioral genetic studies of personality: An introduction and review of the results of 50+ years of research. In: Boyle GJ, Matthews G, Saklofske DH editors. The SAGE Handbook of Personality Theory and Assessment: Volume 1 Personality Theories and Models. London: SAGE; 2008.
• 21. Oniszczenko W, Angleitner A, Strelau J, Angert T. The questionnaire of twins’ physical resemblance (Unpublished report). Warsaw, Poland: Department of Psychology, University of Warsaw; 1993.
• 22. Plomin R, DeFries JC, Knopik VS, Neiderhiser JM. Behavioral genetics (6th ed.). New York, NY: Worth Publishers; 2012.
• 24. Neale MC, Maes HH. Methodology for genetic studies of twins and families. Dordrecht, Netherlands: Kluwer Academics; 2004.
• 27. Neale MC, Maes HH. Methodology for genetic studies of twins and families. Dordrecht, Netherlands: Kluwer Academics; 2004.
• 33. Kline RB. Principles and practice of structural equation modeling (3rd ed.). Guilford Press; 2010.
• 40. Panksepp J (Ed.). A Textbook of Biological Psychiatry. New York, Wiley; 2004.

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UNIQUE The New Science of Human Individuality By David J. Linden

In the longstanding debate over whether “nature” or “nurture” determines how we turn out, the old saw goes like this: When your first baby is born, you are sure that what matters is nurture. When your second baby is born, you’re a firm believer in nature.

This adage is confirmed, somewhat, in how people answered a survey that David J. Linden cites in “Unique: The New Science of Human Individuality.” In the book Linden, a neuroscientist at Johns Hopkins University, sets out to look at everything that makes us distinctly ourselves: our height and weight, food preferences, personality styles, gender identity, racial identity, sexual orientation and intelligence. Are these qualities carried in our genes, or does the life we live — every experience, from the viruses we encounter to the books we read to what month we were born — play a bigger role in making us who we are?

Turns out we can be bad at guessing to what degree our traits are genetic — or what scientists call “heritable” — and to what degree they’re affected by environment. In an online survey from 2019, Linden tells us, Americans were generally good at intuiting the source of certain traits; they knew that height is strongly heritable, political beliefs are not heritable at all and musical talent is somewhere in between. But they also had some revealing blind spots. They assumed that the heritability of body mass index was 40 percent, for instance, when the consensus from the scientific literature is that it’s really more like 65 to 75 percent. “I imagine that many people want to believe that food consumption is more a matter of personal willpower than it really is,” Linden writes; they want to believe “that they (and others) have a greater degree of autonomy and personal agency than they really do.”

And the survey respondents who were most accurate? College-educated mothers of more than one child. In other words, the ones whose “it’s all nurture” attitude was likely attenuated by the birth of a second child with a different “nature.”

This is not to say that Linden is out to prove that genes define us; far from it. The main takeaway from “Unique” is that while there might be a genetic tendency to develop in a particular way, there’s a wide range of influences, beginning in fetal life, that help determine how and whether our genes are expressed. Some examples of the gene-environment interplay are well known, such as the single gene that causes a cognitive impairment known as PKU, which never reveals itself if a child eats the right diet. But most of the scientific understanding is still evolving as to just how experience interacts with and changes gene expression.

I feel the need to pause here to point out that Linden hates the phrase I’ve been using: “nature versus nurture.” He says it oversimplifies the question of how genetics and the environment influence each other over the course of development.

In ordinary English, “nurture” means how your parents raise you, he writes. “But, of course, that’s only one small part of the nonhereditary determination of traits.” He much prefers the word “experience,” which encompasses a broad range of factors, beginning in the womb and carrying through every memory, every meal, every scent, every romantic encounter, every illness from before birth to the moment of death. He admits that the phrase he prefers to “nature versus nurture” doesn’t roll as “trippingly off the tongue,” but he offers it as a better summary of how our individuality really emerges: through “heredity interacting with experience, filtered through the inherent randomness of development.”

There’s a lot of interesting stuff in “Unique,” including findings from decades’ worth of twin studies that gave scientists some of their first insights into how much of personality and behavior might be inherited and how much acquired. There are some great descriptions of investigations into genetics including, for instance, a Russian geneticist’s attempt, starting in the 1950s, to domesticate silver foxes by breeding them for tameness. Or we might find ourselves in the middle of a cool psych experiment, like one conducted at Berkeley in 2006 that ended up with a bunch of blindfolded college kids crawling through a grassy field trying to smell a trail of chocolate.

More notably, Linden marches into territory where too many other scientists fear to tread: the genetics of gender identity, sexual orientation and race. He manages, by and large, to avoid the worst land mines, acknowledging certain genetic differences among some populations but emphasizing that they don’t necessarily align with the social binaries of male/female, gay/straight, cis/trans or Black/white. Occasionally I did find myself cringing at some of the language, as in the chapter on gender, where I wish he had followed his own good advice — offered in a footnote in which he referred readers to the advocacy group InterACT — and steered clear of medicalized language to describe intersex people. But such missteps were rare.

I also wish he had worked harder to explain some of the complicated biological processes at the heart of his argument, especially epigenetics and neurogenetics. Too often he resorts to the crutch of apologizing in advance for prose riddled with “alphabet soup,” or for “bombarding you with a bunch of names for biomolecules,” before launching into a tangle of jargon. But apologizing in advance shouldn’t get him off the hook. It’s possible to convey even complicated biology in crisp, clear language without sacrificing accuracy. It’s just hard — especially for a scientist like Linden who clearly knows his subject inside out — and Lord knows it’s time-consuming. But it’s worth the effort.

Still, when it matters, Linden neither falters nor apologizes. At the end of his chapter on the genetics of race, he could not be clearer. “I can’t say this loudly enough,” he writes, making liberal use of italics: “ There is no evidence for significant average differences in intelligence-related genes between ‘races.’ Not between self-identified whites and Blacks in the United States, nor between any pair of self-defined racial groups. Not only that, there is no evidence for racial group differences in genes that have been linked to any behavioral or cognitive trait. Not aggression. Not A.D.H.D. Not extroversion. Not depression. Nada, niente , nichts , bupkis.”

That’s the kind of clarity we need more of in popular science books like this, especially ones that investigate both what makes us human and what makes us distinctly, immutably ourselves.

Robin Marantz Henig is a science writer and author of nine books, including “Pandora’s Baby” and “The Monk in the Garden.”

UNIQUE The New Science of Human Individuality By David J. Linden 336 pp. Basic Books. $30.

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Article Contents

Nature versus nurture, the exposome: a wild idea, the nature of nurture: refining the definition of the exposome.

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Gary W. Miller, Dean P. Jones, The Nature of Nurture: Refining the Definition of the Exposome, Toxicological Sciences , Volume 137, Issue 1, January 2014, Pages 1–2, https://doi.org/10.1093/toxsci/kft251

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We Need an Output of Environmental Exposures as Tangible as the Mutated Gene

Historical debates concerning human biology and behavior have frequently focused on contributions of nature, ie, the inherited characteristics with which we are born, and nurture, ie, life’s influences after birth. Indeed, the concept of nature vs nurture has guided our understanding of human biology for decades, if not centuries. A series of discoveries has greatly advanced the knowledge of our nature. Watson and Crick’s unraveling of the double helix revolutionized the understanding of our genetic makeup ( Watson and Crick, 1953 ). The polymerase chain reaction allowed amplification and manipulation of genes ( Saiki et al. , 1988 ). Identified links between specific genes and disease ( Saiki et al. , 1985 ) led to new diagnostic tools and treatments. These advances spurred the Human Genome Project with success in sequencing the entire human genome ( Lander et al. , 2001 ; Venter et al. , 2001 ). This epic undertaking of biomedical science and technology was completed with amazing speed and celebrated with great fanfare. But the limitation of genetics to predict disease rapidly became obvious; as noted by Dr Venter shortly after the completion of human genome sequence, “We simply do not have enough genes for this idea of biological determinism to be right ( McKie 2001 ).”

Genome-wide association studies (GWAS) have revealed genetic associations and networks that improve understanding of disease, but these still account for only a fraction of disease risk. With the majority of disease causation being nongenetic, the need for improved tools to quantify environmental contributions seems obvious. The simple distinction between genes and environment is blurred by knowledge that environmental exposures cause permanent genetic changes via mutagenesis and also have long-term impact on gene expression through epigenetic mechanisms. Importantly, epigenetic mechanisms are central to differentiation and development, impacting genome function before birth and throughout life.

The epigenome is highly reliant on nurture, ie, the nature and timing of environmental exposures and external forces. Randy Jirtle, a pioneer in epigenomics stated “The nature vs. nurture argument is rapidly proving to be irrelevant, because we’re finding that the 2 forces interact in highly specific ways that alter gene behavior ( Duke Health, 2006 ).” Although Dr Jirtle suggests the argument is becoming irrelevant, the reality is that biomedical research is overwhelmingly focused on the gene side of this debate. The tools and knowledge of our nature are far ahead of those for the environment. If we want to focus on the interaction between nature and nurture, we need better ways of cataloguing and integrating the complex exposures and forces that represent nurture. Such a framework is provided by the exposome.

In 2005, Dr Christopher Wild coined the term “exposome” and provided the basis for the concept ( Wild, 2005 ). In brief, Dr Wild suggested that the exposome “encompasses life-course environmental exposures (including lifestyle factors), from the prenatal period onwards.” Science and medicine have responded slowly to the concept ( Rappaport and Smith, 2010 ), perhaps because the original definition appeared confined to exposure assessment. A more appropriate position for the exposome is on par with the genome as a foundation for contemporary medicine and public health. This is not to diminish the importance of chemical exposures but rather to place those exposures within the broader context of diet, behavior, and other exogenous and endogenous agents ( Jones et al. , 2012 ). With systematic information on exposures, environment-wide association studies ( Patel et al. , 2010 ) could become much more powerful and complement GWAS and deep sequencing studies.

In our view, the exposome is even more expansive than what Dr Wild described 9 years ago. The exposome captures the essence of nurture; it is the summation and integration of external forces acting upon our genome throughout our lifespan ( Miller, 2014 ). What we eat, where we live, the air we breathe, our social interactions, our lifestyle choices such as smoking and exercise, and the inherent metabolic and cellular activity manipulate the biology encoded by our genome. This measurable quantity of the exposome represents a biological index of our nurture and is the context in which specific exposures have impact on health.

To date we have not seen much about the exposome in the pages of toxicology and biomedical science journals because the exposome was framed as a challenge to the field of exposure assessment. Although there is no doubt that exposure science will play an integral role, the exposome demands more. The exposome must explicitly include how our bodies respond to environment pressures, including epigenetic changes and mutations, as well as the complex chemistry resulting from the biochemical reactions that sustain our lives. This prompts a refined definition:

Exposome: The cumulative measure of environmental influences and associated biological responses throughout the lifespan, including exposures from the environment, diet, behavior, and endogenous processes

There are 3 distinct differences between our definition and that of Dr Wild. The first is the concept of the cumulative biological responses. This captures the ongoing adaptations and maladapations to external forces and chemicals and represents the body’s response to these challenges. The second is the inclusion of behavior. This is used in a very broad context to include personal and volitional actions and those that result from family, community, or social units. It goes beyond lifestyle to include the dynamic interaction with our surroundings, including relationships, interactions, and physical and emotional stressors. A third change is the addition of “endogenous processes.” Our bodies are complex biochemical reaction vessels with countless reactions occurring at any time. Glycolysis, oxidative respiration, microsomal p450s, and many other systems are generating new species and breaking down others. Even the microbes that constitute our microbiome play an important role and fall under the “endogenous processes.” The complex exposures are still at the heart of the definition, but the lingering damage; the DNA mutations or adducts, epigenetic alterations, and protein modifications are just as important as the chemicals themselves. In fact, they provide the evidence of an actual effect and may be more readily interrogated, eg, decades after exposure.

As toxicologists, we are especially interested in studying the impact of chemicals on biological systems. Research on the exposome is the epitome of such an endeavor. Although exposome research will likely be led by environmental health sciences (exposure science, environmental epidemiology, and toxicology), it will require the involvement from a wide range of disciplines. This is not a challenge restricted to those interested in the environment, it is a critical question open to all interested in biology . The revised definition makes this demonstrably clear.

A central challenge to exposome research is the need for an output from environmental exposure research that is as tangible as the mutated gene —something that epidemiologists and physicians can insert into existing frameworks of public health and medical models for disease prevention and management. With a broader definition, exposome research can begin to provide the tangible and quantifiable entities that medicine and public health desperately need. The success of the Human Genome Project exposed an imbalance in the nature-nurture interaction. Elucidating the exposome, ie, developing an integrated science of nurture, will help fulfill the promises of the Human Genome Project. Upon the publication of the first draft of the human genome, Francis Collins stated “What more powerful form of study of mankind could there be than to read our own instruction book? ( Collins 2000 )” The answer, of course, is to read the subsequent chapters that explain the interactions between our genes and our environment that determine health and disease.

Supported by NIEHS P30 ES 019776.

Collins F . 2000 . White House Press Briefing . Washington, DC . Available at www.genome.gov/10001356 .

Google Scholar

Google Preview

Duke Health . www.dukehealth.org/health+library/news/9583 . March 27, 2006.

Jones D. P. Park Y. Ziegler T. R . (2012) . Nutritional metabolomics: Progress in addressing complexity in diet and health . Annu. Rev. Nutr . 32 , 183 – 202 .

Lander E. S. Linton L. M. Birren B. Nusbaum C. Zody M. C. Baldwin J. Devon K. Dewar K. Doyle M. FitzHugh W. et al.  ; International Human Genome Sequencing Consortium . (2001) . Initial sequencing and analysis of the human genome . Nature 409 , 860 – 921 .

McKie R . (2001) . Revealed: The Secret of Human Behaviour. The Observer (London).

Miller G. W . (2014) . The Exposome: A Primer . Academic Press , Elsevier, Inc. Waltham, MA .

Patel C. J. Bhattacharya J. Butte A. J . (2010) . An Environment-Wide Association Study (EWAS) on type 2 diabetes mellitus . PLoS One 5 , e10746 .

Rappaport S. M. Smith M. T . (2010) . Epidemiology. Environment and disease risks . Science 330 , 460 – 461 .

Saiki R. K. Gelfand D. H. Stoffel S. Scharf S. J. Higuchi R. Horn G. T. Mullis K. B. Erlich H. A . (1988) . Primer-directed enzymatic amplification of DNA with a thermostable DNA polymerase . Science 239 , 487 – 491 .

Saiki R. K. Scharf S. Faloona F. Mullis K. B. Horn G. T. Erlich H. A. Arnheim N . (1985) . Enzymatic amplification of beta-globin genomic sequences and restriction site analysis for diagnosis of sickle cell anemia . Science 230 , 1350 – 1354 .

Venter J. C. Adams M. D. Myers E. W. Li P. W. Mural R. J. Sutton G. G. Smith H. O. Yandell M. Evans C. A. Holt R. A. et al.  (2001) . The sequence of the human genome . Science 291 , 1304 – 1351 .

Watson J. D. Crick F. H . (1953) . Molecular structure of nucleic acids; a structure for deoxyribose nucleic acid . Nature 171 , 737 – 738 .

Wild C. P . (2005) . Complementing the genome with an “exposome”: the outstanding challenge of environmental exposure measurement in molecular epidemiology . Cancer Epidemiol. Biomarkers Prev . 14 , 1847 – 1850 .

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Nature and Nurture in Personality

• Liisa Keltikangas-Järvinen , Ph.D. , and
• Markus Jokela , Ph.D.

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An interaction between individual and contextual factors is the central theme in development of personality. Molecular genetics offers the most valuable opportunity for increasing our understanding of the joint effect of nature and nurture. Sensitivity to environmental adversities and benefits may be conditional on genetic background, and the nature-nurture interactions may be of greater importance than direct gene-trait associations. In our recent series of studies, we have shown that different variants of serotonergic and dopaminergic genes may moderate the influence of environmental conditions on a range of psychological outcomes, at least on temperament, depression, and hostility. These studies suggest that, depending on their genotype, people may be differentially sensitive to the environmental conditions they encounter. In light of these results, it seems highly plausible that the effects of genes may become evident only when studied in the context of environmental factors.

It has recently been generally accepted that complex mental entities such as temperament and personality are the results of an interplay between genetic and environmental factors. The way to this balanced view emphasizing the joint effect of genes and environment has, however, not been easy in personality psychology. Environmentalism that attributes all human behaviors to an environment (“we are what we learn”) captivated developmental psychologists in the 1950s and dominated the research of personality over the two following decades. In the 1970s, there was still a debate about whether personality exists at all, and behavior was an indication of the environment only. During the last 15 years, a change toward a general acceptance of genetic factors in personality development has been so rapid that it is easily forgotten how “environmentalistic” the psychological explanations have been. Even in the 1960s, the major explanation for all personality traits and their associated clinical syndromes, such as autism or schizophrenia, was inappropriate or abnormal parenting.

Quantitative genetic research, i.e., animal behavior, family, twin, and adoption studies, demonstrated the importance of the genetic influence on personality ( 1 ). Most work to understand the roles of nature and nurture in human development has relied on molecular genetics and technologies for assessing brain metabolism.

Behavioral genetics has provided evidence of genetic influences on temperament and personality but, perhaps more importantly, has provided strong evidence for the significance of environmental influences. Early environmental information can considerably strengthen and even uncover associations between genes and traits. This has been initially demonstrated in animal studies that showed the contribution of rearing environment (types of maternal nurturance) and genetic background ( 5HTTLPR ) and their interaction to a development of temperament ( 2 ).

Given that, behavioral genetics suggests a focus on the joint effect of genes and environment and especially on the developmental interplay between nature and nurture over the course of a person's life. Genes may have a direct effect on the development of personality traits but, more important, they may moderate environmental effects on personality development and explain individual differences in vulnerability and resilience to environmental hazards. Vulnerability to environmental adversities and sensitivity to environmental benefits may be conditional, i.e., the same genotypes may be associated with different outcomes in different environments ( 3 , 4 ). This fact has been convincingly demonstrated, for instance, by Caspi et al. ( 5 ) in the Dunedin study and by Foley et al. ( 6 ) in the Virginia study, which showed a moderating effect of the MAO-A genotype in the relation between severe childhood maltreatment and later antisocial behavior.

BEHAVIORAL GENETICS IN PERSONALITY

Despite high initial expectancy, studies of behavioral genetics have not provided satisfactory results in personality psychology. The failure to identify the specific genetic underpinnings of behavior could be related to its multifactorial nature and the lack of biological validity of the personality concept and the important influence of the environmental factors on personality. A promising way to solve this problem is to look at the early biological roots of personality. Here, research has been concentrated on temperament, because an understanding of neuroregulatory systems underlying temperament may increase our knowledge of the interplay of nature and nurture in a development of normal personality and, in particular, may highlight mechanisms through which unfavorable and adverse environmental effects turn into personality disorders ( 7 ).

MONOAMINE TRANSMITTERS UNDERLIE TEMPERAMENT

Temperament consists of those components of personality that are heritable, developmentally stable, emotion based, or uninfluenced by sociocultural learning ( 8 ). Recent literature offers extensive evidence to show that interindividual differences in neuroregulatory systems, especially in the activities of the brain dopamine and serotonin systems, explain temperamental variability. This suggestion was originally made by Cloninger in his temperament and character theory ( 9 ). Cloninger conceptualizes personality as the combination of heritable, neurobiologically based temperament traits reflecting behavioral conditioning, and character traits reflecting both neurobiological and sociocultural mechanisms of semantic and self-aware learning. According to him, temperamental dimensions are related to heritable variation in responses to environmental stimuli and characterized by novelty seeking (NS) (a tendency toward exploratory activity and intense excitement in response to novel stimuli), harm avoidance (HA) (a tendency to respond intensely to aversive stimuli and to avoid punishment and novelty), and reward dependence (RD) (a tendency to respond intensely to reward and to learn to maintain rewarded behavior). NS is suggested to be linked with low basal dopaminergic activity, HA with high serotonergic activity, and RD with low basal noradrenergic activity ( 9 ). The extreme variants of these basic stimulus-response characteristics closely correspond to the traditional descriptions of personality disorders. This correspondence implies that the underlying structure of the normal adaptive traits is basically the same as that of the maladaptive personality traits.

The molecular genetics of temperament started in 1996 with two articles ( 10 , 11 ) that showed an association between NS and the dopamine 4 receptor (DRD4). This finding was shortly replicated in many studies ( 12 , 13 ), although some further studies questioned this association ( 14 , 15 ). These two first articles on NS were shortly followed by investigations linking HA with the allelic variation of the serotonergic genes, first with the serotonin transporter 5HTTLPR. This link was also replicated ( 16 , 17 ), even though the number of inconsistent findings was high ( 18 ).

In the 2000s, single gene effects as well as coeffects of several genes on temperament were increasingly documented, whereas studies using traditional personality traits were few in number. Gene × environment interactions in the development of temperament and personality have received less attention. The first molecular gene × environment interaction studies of human behavior were carried out by Berman and Noble ( 19 ) and Ozkaragoz and Noble ( 20 ), who showed that in adolescent boys, the minor alleles of the DRD2 gene interacted with familial alcoholism, resulting in high extraversion.

Later, it was demonstrated that the 5HTTLPR gene moderates parental influences on early temperament development. It has been shown that infants carrying the short allele of 5HTTLPR developed poorer behavioral self-regulation than their counterparts carrying only long alleles if they were insecurely attached to their caregivers but not when they were securely attached ( 21 ). Likewise, Fox et al. ( 22 ) showed that the short allele increased behavioral inhibition in children who had low parental support.

FINDINGS OF THE “CARDIOVASCULAR RISK IN YOUNG FINNS” SAMPLE

Our series of studies has capitalized on the population-based, longitudinal birth cohort study of the Cardiovascular Risk in Young Finns ( Table 1 ). In this study, a representative sample of 3,600 healthy subjects from six age cohorts (aged 3, 6, 9, 12, 15, and 18 years at the baseline) have been followed over 27 years since their childhood and monitored in eight study waves resulting in a huge reservoir of somatic, psychological, behavioral, and environmental predictors and somatic and psychological outcomes ( 23 ) ( Figure 1 ).

Table 1. Summary of the Studies

Figure 2. Main Genetic and Environmental Effects. Childhood Environment and Serotonergic and Dopaminergic Genes Have the Main Effects on Adulthood HA and NS, respectively.

This finding was repeated in the total Cardiovascular Risk in Young Finns sample and with a variant of another gene polymorphism related to dopaminergic transmission, i.e., DRD2 . In a highly hostile child-rearing environment, especially in terms of disciplinary style, the A1 allele carriers of the Taq1A variant of the DRD2 gene had higher scores for NS in adulthood than A2/A2 genotype carriers. When the childhood environment was emotionally positively tuned, the genotype had no effect on NS ( 27 ) ( Figure 3 ).

Figure 3. DRD2 and Childhood Environment Interact in Development of Adulthood NS.

In addition to emotional atmosphere, the DRD4 two- or five-repeat alleles interacted with childhood socioeconomic circumstances, residential setting, and parental alcohol use. In the carriers of this gene variant, high maternal education, high annual household income, and an urban residential setting in one's childhood increased the likelihood of scoring high on NS in adulthood. This was true after controlling for the effects of emotional relationships between the child and the mother. When maternal education and household income were low or the family resided in a rural setting, no differences between extreme high and extreme low NS groups were found ( 28 ). Further, in the presence of high paternal alcohol consumption, the two- or five-repeat alleles of the DRD4 were associated with a high level of NS, whereas no association was found in the presence of low alcohol consumption ( 29 ).

Somatic parameters modified an effect of the DRD4 polymorphism on NS, too. The two- or five-repeat alleles were associated with high NS in subjects with high levels of cholesterol but not in those with low cholesterol levels. This finding remained after adjustment for the apolipoprotein E polymorphism ( 30 ).

Second, we studied gene × environment interactions in the development of HA by using the T102C variant of the serotonin receptor 2A ( 5HTR2A ), and A218C and A799C haplotypes of the tryptophan hydroxylase 1 gene ( TPH1 ) as markers of the serotonin functioning. The T102C variant of the 5HT2RA polymorphism has been associated with the expression of the gene and with the binding potential of serotonin 2A receptors ( 31 ), and it has been considered as a candidate gene polymorphism for many psychiatric disorders, e.g., depression ( 32 ) and anxiety ( 33 ).

TPH1 is the rate-limiting enzyme for serotonin biosynthesis. It regulates serotonin levels and influences behaviors that are controlled by serotonin. Neurogenetic studies have mostly focused on A218C and A799C haplotypes of TPH1, and those polymorphisms have been shown to be associated with depression and suicidal behavior ( 34 ).

We showed that the T102C polymorphism of the HTR2A gene was directly associated with HA ( 24 ) and moderated the effect of childhood familial socioeconomic status (SES) on adulthood HA. The carriers of the T allele scored low on HA in adulthood if their familial SES was high in childhood or adolescence, whereas no association was observed among those with low familial childhood SES. This finding suggests that the T allele carriers may be more sensitive to environmental effects than the C/C carriers ( 24 ).

The joint effect of environment and genetic background was true with THP1 also. The A/A haplotypes of the TPH1 intron 7 A218A and A779C polymorphisms predicted a high level of adulthood HA in the presence of a hostile childhood environment as defined in terms of emotional rejection and inconsistent discipline, whereas no environmental effect was identified among C/C carriers ( 35 ) ( Figure 4 ).

Figure 4. TPH1 and Childhood Environment Interact in Development of Adulthood HA.

All the above gene × environment interactions effects on NS and HA were repeated at two or three different study phases of the Cardiovascular Risk in Young Finns study (samples highly overlapping but not identical) 4 or 5 years apart.

Our most recent unpublished finding suggests an interaction of childhood nurturing environment and the T102C polymorphism of 5HTR2A on social attachment, as measured with the attachment subscale of RD and related measures of adult attachment styles. T/T genotype carriers were found to benefit from a favorable maternal nurturance in childhood and adolescence by showing greater temperamental attachment in adulthood, whereas an unfavorable maternal nurturance in childhood induced a lower attachment security in adolescence among them. In C allele carriers, a quality of maternal nurturance was not associated with later social attachment.

Nature versus nurture in depression

Our findings have also suggested moderating roles for the DRD2 , TPH1 , and 5HTR2A in a development of depressive symptoms. We found a weak overall association between childhood negative life events and adulthood depressive symptoms. This association was stronger among those who carried the A/A genotype of the Taq1A polymorphism of DRD2 and weaker among those with other genotypes ( 36 ).

We also found that the T allele carriers of the T102C polymorphism of 5HT2RA who had experienced high maternal nurturance in childhood or adolescence expressed lower levels of depressive symptoms in adulthood, compared with their C/C genotype counterparts, suggesting that the T allele carriers were more able to benefit from the protective aspects of the environment ( 37 ). Further, we found that low social support predicted depressive symptoms more strongly in individuals carrying A alleles of the TPH1 than in those with other alleles ( 38 ).

Finally, the T102C polymorphism of the 5HT2RA was shown to moderate the effect of urban/rural living conditions on depressive symptoms. In T allele carriers, urban or suburban residency was associated with lower depressive symptoms, whereas living in remote rural areas predicted a high level of depressive symptoms in them. No correlation was observed among individuals carrying the C/C genotype ( 39 ).

Nature versus nurture in hostility

A nonsupportive and conflictual childhood family environment has been shown to contribute to development of hostility ( 40 ), whereas twin studies suggest that hostility also has a genetic component ( 41 ). Hostility and difficult temperament share the same elements ( 7 ), and hostility has been suggested to be mediated by the serotonergic system ( 42 ).

Given these previous findings, we studied the modifying effects of the 5HTR1A and 5HTR2A gene polymorphisms in the association between childhood maternal behavior (quality of nurturance) and adulthood hostility. Among the carriers of the T/T and T/C genotypes of 5HT2RA , nurturance predicted hostility, whereas no association among C/C carriers was observed (unpublished data).

In addition, the T102C polymorphism was also shown to moderate the association between childhood hyperactive temperament and adulthood hostility in men ( 43 ). T/T genotype carriers, who were rated as hyperactive in childhood by their mothers, expressed higher levels of hostility in adulthood. The same was not true among C allele carriers. A child's hyperactive temperament might create a hostility-prone environment, i.e., a child's own behavior contributes to an unfavorable parent-child relationship and the T/T gene variant selects the children who are most sensitive to this detrimental influence.

CONCLUSIONS

Together with other studies of gene-environment interactions, our series of studies suggest that depending on their genotype, people may be differentially sensitive to the environmental conditions they encounter. In addition, it seems that a certain genetic background may sensitize a person both to the positive and the negative aspects of the environment suggesting that a gene variant may not be acting solely as a “vulnerability factor” nor a pure “opportunity gene” that would be entirely good or bad for its carrier ( 44 ). For example, the allelic variance of the HTR2A gene was shown to be associated with both an ability to use positive aspects of the environment, when offered, and with a heightened vulnerability to negative aspects of the environment, this way affecting the overall responsivity to environmental conditions. In addition to current environmental effects, certain gene variants may influence the duration of early experiences. In light of these results it seems highly plausible that the effects of genes may become evident only when studied in the context of environmental factors, whereas ignoring environmental variability may lead to inconsistent replications of findings, as has often been observed for multifactorial traits.

It is known that any extreme temperamental bias may predispose a person to personality disorders ( 45 ). Genetic background not only delineates early temperament but also determines how malleable these dispositions are in response to the environment. In some individuals, high anxiousness (which is strongly correlated with HA) may be the result of genetics and insensitivity to environmental influences that would decrease anxiousness in more sensitive individuals. In others, high anxiousness may reflect a combination of high susceptibility and exposure to environmental influences increasing anxiousness. The study of gene-environment interactions helps us to understand the origins and consequences of temperament and personality traits that stem from these different developmental pathways.

Despite high consistency of the findings on the joint effect of genes and environment, one weakness needs to be recognized. This weakness limits our findings as well as most previous research. “Environment” usually refers to parental parameters that at least partly indicate a shared genetic background, too. Thus, the environment may be partly genetic. Nevertheless, adoption studies and other separation experiments indicate that both nature and nurture need to be considered carefully in assessing the development of temperament, personality, and their disorders. Neither genes nor environmental influences alone can be expected to explain the development of personality across the lifespan.

CME Disclosure

Liisa Keltikangas-Järvinen, Ph.D., and Markus Jokela, Ph.D., Department of Psychology, University of Helsinki, P.O. Box 9, FIN-00014 University of Helsinki, Finland

Dr. Keltikangas-Järvinen and Dr. Jokela report no competing interests.

1 Cloninger CR: Genetics of personality disorders, in Psychiatric Genetics . Edited by Nurnberger J, Wade B. New York, Cambridge University Press, in press Google Scholar

2 Ladd CO, Huot RL, Thrivikraman KV, Nemeroff CB, Meaney MJ, Plotsky PM: Long-term behavioral and neuroendocrine adaptations to adverse early experience. Prog Brain Res 2000 ; 122:81–103 Crossref ,  Google Scholar

3 Kendler KS: Twin studies of psychiatric illness: an update. Arch Gen Psychiatry 2001 ; 58:1005–1014 Crossref ,  Google Scholar

4 Rutter M, Silberg J: Gene-environment interplay in relation to emotional and behavioral disturbance. Annu Rev Psychol 2002 ; 53:463–490 Crossref ,  Google Scholar

5 Caspi A, McClay J, Moffitt TE, Mill J, Martin J, Craig IW, Taylor A, Poulton R: Role of genotype in the cycle of violence in maltreated children. Science 2002 ; 297:851–854 Crossref ,  Google Scholar

6 Foley DL, Eaves LJ, Wormley B, Silberg JL, Maes HH, Kuhn J, Riley B: Childhood adversity, monoamine oxidase a genotype, and risk for conduct disorder. Arch Gen Psychiatry 2004 ; 61:738–744 Crossref ,  Google Scholar

7 Plomin R, DeFries JC, McClearn GE, McGuffin P: Behavioral Genetics , 4th ed. New York, Worth Publishers, 2001 Google Scholar

8 Cloninger CR: Temperament and personality. Curr Opin Neurobiol 1994 ; 4:266–273 Crossref ,  Google Scholar

9 Cloninger CR, Svrakic DM, Przybeck TR: A psychobiological model of temperament and character. Arch Gen Psychiatry 1993 ; 50:975–990 Crossref ,  Google Scholar

10 Benjamin J, Li L, Patterson C, Greenberg BD, Murphy DL, Hamer DH: Population and familial association between the D4 dopamine receptor gene and measures of novelty seeking. Nat Genet 1996 ; 12:81–84 Crossref ,  Google Scholar

11 Ebstein RP, Novick O, Umansky R, Priel B, Osher Y, Blaine D, Bennett ER, Nemanov L, Katz M, Belmaker RH: Dopamine D4 receptor (D4DR) exon III polymorphism associated with the human personality trait of novelty seeking. Nat Genet 1996 ; 12:78–80 Crossref ,  Google Scholar

12 Noble EP, Ozkaragoz TZ, Ritchie TL, Zhang X, Belin TR, Sparkes RS: D2 and D4 dopamine receptor polymorphisms and personality. Am J Med Genet 1998 ; 81:257–267 Crossref ,  Google Scholar

13 Ono Y, Manki H, Yoshimura K, Muramatsu T, Mizushima H, Higuchi S, Yagi G, Kanba S, Asai M: Association between dopamine D4 receptor (D4DR) exon III polymorphism and novelty seeking in Japanese subjects. Am J Med Genet 1997 ; 74:501–503 Crossref ,  Google Scholar

14 Gelernter J, Kranzler H, Coccaro E, Siever L, New A, Mulgrew CL: D4 dopamine-receptor (DRD4) alleles and novelty seeking in substance-dependent, personality-disorder, and control subjects. Am J Hum Genet 1997 ; 61:1144–1152 Crossref ,  Google Scholar

15 Herbst JH, Zonderman AB, McCrae RR, Costa PT Jr: Do the dimensions of the temperament and character inventory map a simple genetic architecture? Evidence from molecular genetics and factor analysis. Am J Psychiatry 2000 ; 157:1285–1290 Crossref ,  Google Scholar

16 Rybakowski F, Slopien A, Dmitrzak-Weglarz M, Czerski P, Rajewski A, Hauser J: The 5-HT2A-1438 A/G and 5-HTTLPR polymorphisms and personality dimensions in adolescent anorexia nervosa: association study. Neuropsychobiology 2006 ; 53:33–39 Crossref ,  Google Scholar

17 Samochowiec J, Rybakowski F, Czerski P, Zakrzewska M, Stepien G, Pelka-Wysiecka J, Horodnicki J, Rybakowski JK, Hauser J: Polymorphisms in the dopamine, serotonin, and norepinephrine transporter genes and their relationship to temperamental dimensions measured by the Temperament and Character Inventory in healthy volunteers. Neuropsychobiology 2001 ; 43:248–253 Crossref ,  Google Scholar

18 Sen S, Burmeister M, Ghosh D: Meta-analysis of the association between a serotonin transporter promoter polymorphism (5-HTTLPR) and anxiety-related personality traits. Am J Med Genet B Neuropsychiatr Genet 2004 ; 127B:85–89 Crossref ,  Google Scholar

19 Berman SM, Noble EP: The D-2 dopamine receptor (DRD2) gene and family stress; interactive effects on cognitive functions in children. Behav Genet 1997 ; 27:33–43 Crossref ,  Google Scholar

20 Ozkaragoz T, Noble EP: Extraversion—interaction between D2 dopamine receptor polymorphisms and parental alcoholism. Alcohol 2000 ; 22:139–146 Crossref ,  Google Scholar

21 Kochanska G, Philibert RA, Barry RA: Interplay of genes and early mother-child relationship in the development of self-regulation from toddler to preschool age. J Child Psychol Psychiatry 2009 ; 50:1331–1338 Crossref ,  Google Scholar

22 Fox NA, Nichols KE, Henderson HA, Rubin K, Schmidt L, Hamer D, Ernst M, Pine DS: Evidence for a gene-environment interaction in predicting behavioral inhibition in middle childhood. Psychol Sci 2005 ; 16:921–926 Crossref ,  Google Scholar

23 Raitakari OT, Juonala M, Rönnemaa T, Keltikangas-Järvinen L, Räsänen L, Pietikäinen M, Hutri-Kähönen N, Taittonen L, Jokinen E, Marniemi J, Jula A, Telama R, Kähönen M, Lehtimäki T, Åkerblom HK, Viikari JS: Cohort profile: the cardiovascular risk in Young Finns Study. Int J Epidemiol 2008 ; 37:1220–1226 Crossref ,  Google Scholar

24 Jokela M, Lehtimäki T, Keltikangas-Järvinen L: The serotonin receptor 2A gene moderates the influence of parental socioeconomic status on adulthood harm avoidance. Behav Genet 2007 ; 37:567–574 Crossref ,  Google Scholar

25 Keltikangas-Järvinen L, Puttonen S, Kivimaki M, Rontu R, Lehtimaki T: Cloninger's temperament dimensions and epidermal growth factor A61G polymorphism in Finnish adults. Genes Brain Behav 2006 ; 5:11–18 Crossref ,  Google Scholar

26 Keltikangas-Järvinen L, Räikkönen K, Ekelund J, Peltonen L: Nature and nurture in novelty seeking. Mol Psychiatry 2004 ; 9:308–311 Crossref ,  Google Scholar

27 Keltikangas-Järvinen L, Pulkki-Råback L, Elovainio M, Raitakari OT, Viikari J, Lehtimäki T: DRD2 C32806T modifies the effect of child-rearing environment on adulthood novelty seeking. Am J Med Genet B Neuropsychiatr Genet 2009 ; 150B:389–394 Crossref ,  Google Scholar

28 Lahti J, Räikkönen K, Ekelund J, Peltonen L, Raitakari OT, Keltikangas-Järvinen L: Socio-demographic characteristics moderate the association between DRD4 and novelty seeking. Pers Individ Differences 2006 ; 40:533–543 Crossref ,  Google Scholar

29 Lahti J, Räikkönen K, Ekelund J, Peltonen L, Raitakari OT, Keltikangas-Järvinen L: Novelty seeking: interaction between parental alcohol use and dopamine D4 receptor gene exon III polymorphism over 17 years. Psychiatr Genet 2005 ; 15:133–139 Crossref ,  Google Scholar

30 Elovainio M, Kivimäki M, Puttonen S, Heponiemi T, Keltikangas-Järvinen L, Viikari J: Does the level of LDL cholesterol moderate a relationship between DRD4 and novelty seeking? Biol Psychol 2005 ; 68:79–86 Crossref ,  Google Scholar

31 Polesskaya OO, Sokolov BP: Differential expression of the “C” and “T” alleles of the 5-HT2A receptor gene in the temporal cortex of normal individuals and schizophrenics. J Neurosci Res 2002 ; 67:812–822 Crossref ,  Google Scholar

32 Du L, Bakish D, Lapierre YD, Ravindran AV, Hrdina PD: Association of polymorphism of serotonin 2A receptor gene with suicidal ideation in major depressive disorder. Am J Med Genet 2000 ; 96:56–60 Crossref ,  Google Scholar

33 Yoon HK, Yang JC, Lee HJ, Kim YK: The association between serotonin-related gene polymorphisms and panic disorder. J Anxiety Disord 2008 ; 22:1529–1534 Crossref ,  Google Scholar

34 Rujescu D, Giegling I, Sato T, Hartmann AM, Moller HJ: Genetic variations in tryptophan hydroxylase in suicidal behavior: analysis and meta-analysis. Biol Psychiatry 2003 ; 54:465–473 Crossref ,  Google Scholar

35 Keltikangas-Järvinen L, Puttonen S, Kivimaki M, Elovainio M, Rontu R, Lehtimaki T: Tryptophan hydroxylase 1 gene haplotypes modify the effect of a hostile childhood environment on adulthood harm avoidance. Genes Brain Behav 2007 ; 6:305–313 Crossref ,  Google Scholar

36 Elovainio M, Jokela M, Kivimäki M, Pulkki-Råback L, Lehtimäki T, Airla N, Keltikangas-Järvinen L: Genetic variants in the DRD2 gene moderate the relationship between stressful life events and depressive symptoms in adults: cardiovascular risk in young Finns study. Psychosom Med 2007 ; 69:391–395 Crossref ,  Google Scholar

37 Jokela M, Keltikangas-Järvinen L, Kivimäki M, Puttonen S, Elovainio M, Rontu R, Lehtimäki T: Serotonin receptor 2A gene and the influence of childhood maternal nurturance on adulthood depressive symptoms. Arch Gen Psychiatry 2007 ; 64:356–360 Crossref ,  Google Scholar

38 Jokela M, Räikkönen K, Lehtimäki T, Rontu R, Keltikangas-Järvinen L: Tryptophan hydroxylase 1 gene (TPH1) moderates the influence of social support on depressive symptoms in adults. J Affect Disord 2007 ; 100:191–197 Crossref ,  Google Scholar

39 Jokela M, Lehtimäki T, Keltikangas-Järvinen L: The influence of urban/rural residency on depressive symptoms is moderated by the serotonin receptor 2A gene. Am J Med Genet B Neuropsychiatr Genet 2007 ; 144B:918–922 Crossref ,  Google Scholar

40 Matthews KA, Woodall KL, Kenyon K, Jacob T: Negative family environment as a predictor of boys' future status on measures of hostile attitudes, interview behavior, and anger expression. Health Psychol 1996 ; 15:30–37 Crossref ,  Google Scholar

41 Rose RJ: Genetic and environmental variance in content dimensions of the MMPI. J Pers Soc Psychol 1988 ; 55:302–311 Crossref ,  Google Scholar

42 Staner L, Mendlewicz J: Heredity and role of serotonin in aggressive impulsive behavior. Encephale 1998 ; 24:355–364 Google Scholar

43 Keltikangas-Järvinen L, Puttonen S, Kivimäki M, Elovainio M, Pulkki-Råback L, Koivu M, Rontu R, Lehtimäki T: Serotonin receptor genes 5HT1A and 5HT2A modify the relation between childhood temperament and adulthood hostility. Genes Brain Behav 2008 ; 7:46–52 Google Scholar

44 Belsky J, Pluess M: Beyond diathesis stress: differential susceptibility to environmental influences. Psychol Bull 2009 ; 135:885–908 Crossref ,  Google Scholar

45 Cloninger CR: Feeling Good: The Science of Well Being . New York, Oxford University Press, 2004 Google Scholar

• The evolution of personality disorders: A review of proposals 30 January 2023 | Frontiers in Psychiatry, Vol. 14
• The relationship between temperament, polygenic score for intelligence and cognition: A population‐based study of middle‐aged adults 16 February 2022 | Genes, Brain and Behavior, Vol. 21, No. 4
• Psychiatry Investigation, Vol. 11, No. 4
• Journal of Theoretical Biology, Vol. 331

Taste depends on nature and nurture. Here are 7 ways you can learn to enjoy foods you don’t like

Research Scientist, Sensory, Flavour and Consumer Sciences, CSIRO

Principal Researcher, Public Health & Wellbeing Group, CSIRO

Disclosure statement

Astrid Poelman has worked on research funded by a variety of industry bodies, Australian government agencies and private companies.

Nicholas Archer does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

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You’re out for dinner with a bunch of friends, one of whom orders pizza with anchovies and olives to share, but you hate olives and anchovies! Do you pipe up with your preferred choice – Hawaiian – or stay quiet?

This scene plays out every day around the world. Some people ferociously defend their personal tastes. But many would rather expand their palate, and not have to rock the boat the next time someone in their friend group orders pizza.

Is it possible to train your tastebuds to enjoy foods you previously didn’t, like training a muscle at the gym?

What determines ‘taste’?

Taste is a complex system we evolved to help us navigate the environment. It helps us select foods with nutritional value and reject anything potentially harmful.

Foods are made up of different compounds, including nutrients (such as proteins, sugars and fats) and aromas that are detected by sensors in the mouth and nose. These sensors create the flavour of food . While taste is what the tastebuds on your tongue pick up, flavour is the combination of how something smells and tastes. Together with texture, appearance and sound, these senses collectively influence your food preferences.

Many factors influence food preferences, including age, genetics and environment. We each live in our own sensory world and no two people will have the same experience while eating .

Food preferences also change with age. Research has found young children have a natural preference for sweet and salty tastes and a dislike of bitter tastes. As they grow older their ability to like bitter foods grows.

Emerging evidence shows bacteria in saliva can also produce enzymes that influence the taste of foods. For instance, saliva has been shown to cause the release of sulphur aromas in cauliflower. The more sulphur that is produced , the less likely a kid is to enjoy the taste of cauliflower.

Read more: Blame it on mum and dad: how genes influence what we eat

Nature versus nurture

Both genetics and the environment play a crucial role in determining food preferences. Twin studies estimate genetics have a moderate influence on food preferences (between 32% and 54%, depending on the food type) in children , adolescents and adults .

However, since our cultural environment and the foods we’re exposed to also shape our preferences, these preferences are learned to a large degree.

A lot of this learning takes place during childhood, at home and other places we eat. This isn’t textbook learning. It’s learning by experiencing (eating), which typically leads to increased liking of the food – or by watching what others do (modelling), which can lead to both positive or negative associations.

Research has shown how environmental influences on food preferences change between childhood and adulthood. For children, the main factor is the home environment, which makes sense as kids are more likely to be influenced by foods prepared and eaten at home. Environmental factors influencing adults and adolescents are more varied.

The process of ‘acquiring’ taste

Coffee and beer are good examples of bitter foods people “acquire” a taste for as they grow up. The ability to overcome the dislike of these is largely due to:

the social context in which they’re consumed. For example, in many countries they may be associated with passage into adulthood.

the physiological effects of the compounds they contain – caffeine in coffee and alcohol in beer. Many people find these effects desirable.

But what about acquiring a taste for foods that don’t provide such desirable feelings, but which are good for you, such as kale or fatty fish? Is it possible to gain an acceptance for these?

Here are some strategies that can help you learn to enjoy foods you currently don’t:

eat, and keep eating. Only a small portion is needed to build a liking for a specific taste over time. It may take 10–15 attempts or more before you can say you “like” the food.

mask bitterness by eating it with other foods or ingredients that contain salt or sugar. For instance, you can pair bitter rocket with a sweet salad dressing.

eat it repeatedly in a positive context. That could mean eating it after playing your favourite sport or with people you like. Alternatively, you could eat it with foods you already enjoy; if it’s a specific vegetable, try pairing it with your favourite protein.

eat it when you’re hungry. In a hungry state you’ll be more willing to accept a taste you might not appreciate on a full stomach.

remind yourself why you want to enjoy this food. You may be changing your diet for health reasons, or because you’ve moved countries and are struggling with the local cuisine. Your reason will help motivate you.

start young (if possible). It’s easier for children to learn to like new foods as their tastes are less established.

remember: the more foods you like, the easier it’ll become to learn to like others.

A balanced and varied diet is essential for good health. Picky eating can become a problem if it leads to vitamin and mineral deficiencies – especially if you’re avoiding entire food groups, such as vegetables. At the same time, eating too many tasty but energy-dense foods can increase your risk of chronic disease, including obesity.

Understanding how your food preferences have formed, and how they can evolve, is a first step to getting on the path of healthier eating.

Read more: 9 tips to give yourself the best shot at sticking to new year's resolutions

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• Research article
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• Published: 12 December 2013

Perceptions of nature, nurture and behaviour

• Mairi Levitt 1  

Life Sciences, Society and Policy volume  9 , Article number:  13 ( 2013 ) Cite this article

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Trying to separate out nature and nurture as explanations for behaviour, as in classic genetic studies of twins and families, is now said to be both impossible and unproductive. In practice the nature-nurture model persists as a way of framing discussion on the causes of behaviour in genetic research papers, as well as in the media and lay debate. Social and environmental theories of crime have been dominant in criminology and in public policy while biological theories have been seen as outdated and discredited. Recently, research into genetic variations associated with aggressive and antisocial behaviour has received more attention in the media. This paper explores ideas on the role of nature and nurture in violent and antisocial behaviour through interviews and open-ended questionnaires among lay publics. There was general agreement that everybody’s behaviour is influenced to varying degrees by both genetic and environmental factors but deterministic accounts of causation, except in exceptional circumstances, were rejected. Only an emphasis on nature was seen as dangerous in its consequences, for society and for individuals themselves. Whereas academic researchers approach the debate from their disciplinary perspectives which may or may not engage with practical and policy issues, the key issue for the public was what sort of explanations of behaviour will lead to the best outcomes for all concerned.

Trying to separate out nature and nurture as explanations for behaviour, as in classic genetic studies of twins and families, is now said to be both impossible and unproductive. The nature-nurture debate is declared to be officially redundant by social scientists and scientists, ‘outdated, naive and unhelpful’ (Craddock, 2011 , p.637), ‘a false dichotomy’ (Traynor 2010 , p.196). Geneticists argue that nature and nurture interact to affect behaviour through complex and not yet fully understood ways, but, in practice, the debate continues 1 . Research papers by psychologists and geneticists still use the terms nature and nurture, or genes and environment, to consider their relative influences on, for example, temperament and personality, childhood obesity and toddler sleep patterns (McCrae et al., 2000 ; Anderson et al., 2007 ; Brescianini, 2011 ). These papers separate out and quantify the relative influences of nature/genes and nurture/environment. These papers might be taken to indicate how individuals acquire their personality traits or toddlers acquire their sleep patterns; part is innate or there at birth and part is acquired after birth due to environmental influences. The findings actually refer to technical heritability which is, ‘the proportion of phenotypic variation attributable to genetic differences between individuals’ (Keller, 2010 , p.57). In practice, as Keller illustrates, there is ‘slippage’ between heritability, meaning a trait being biologically transmissible, and technical heritability. This is not simply a mistake made by the media or ‘media hype’ but is, she argues, ‘almost impossible to avoid’ (ibid, p.71).

While researchers are aware of the complexity of gene-environment interaction, the ‘nature and nurture’ model persists as a simple way of framing discussion on the causes of behaviours. It is also a site of struggle between (and within) academic disciplines and, through influence on policy, has consequences for those whose behaviours are investigated. There is general agreement between social scientists and geneticists about the past abuses of genetics but disagreement over whether it will be possible for the new behavioural genetics to avoid discrimination and eugenic practices, and about the likely benefits that society will gain from this research (Parens et al. 2006 , xxi). In a special issue of the American Journal of Sociology ‘Exploring genetics and social structure’, Bearman considers the reasons why sociologists are concerned about genetic effects on behaviour; first they see it as legitimating existing societal arrangements, which assumes that ‘genetic’ is unchangeable. Second, if sociologists draw on genetic research it contaminates the sociological enterprise and, third, whatever claims are made to the contrary, it is a eugenicist project (Bearman, 2008 , vi). As we will see all these concerns were expressed by the publics in this study. Policy makers and publics are interested in explaining problem behaviour in order to change/control it, not in respecting disciplinary boundaries, and will expect the role of genetics to be considered alongside social factors. 2

Social and environmental theories of criminal behaviour have been dominant in criminology, and in public policy (Walsh, 2009 , p.7). Genetic disorders and mental illness have provided explanations for a small minority of offenders with specific conditions. A 2007 survey of American criminologists found that ‘criminologists of all ideological persuasions view alleged biosocial causes of crime (hormonal, genetic, and evolutionary factors and possibly low intelligence) as relatively unimportant’ compared with environmental causes (Cooper et al., 2010 ). Sociology textbooks have typically discussed biological theories of criminality only as discredited (Haralambos and Holborn, 2004 , Giddens, 2009 ). Biosocial theories are seen as attractive to ‘agents of social control’ and to be more likely to lead to abusive treatment of offenders. However, with increasing research and public interest in genetics more attention has been paid to biological aspects of crime and to genetic variations within the normal range. Research has focussed on violent and antisocial behaviours which are criminal or may be seen as a precursor to criminal behaviour, for example, antisocial behaviour in young people. Media reports have headlined ‘warrior genes’, ‘the aggressive gene’ and the ‘get out of jail free gene’, all referring to levels of monoamine oxidase A (MAOA) (Lea and Chambers, 2007 ; Levitt and Pieri, 2009 ) 3 . Think tanks and ethics groups have considered the ethics and practicalities of genetic testing for behavioural traits (Campbell and Ross, 2004 ; Dixon, 2005 Nuffield Council on Bioethics, 2002 ).

An attraction of research into genes and behaviour is the hope that identifying a genetic factor that is correlated with an increased incidence of, say, violent and antisocial behaviour, will point to a way of reducing such behaviour. Fotaki discusses the attraction of biological explanations of inequalities in health based on the assumption that genetic interventions ‘would succeed in addressing the causes of ill health that public health policies cannot.’ (Fotaki, 2011 , p.641). The danger is that biological explanations ‘are once more employed for political purposes to explain away the social roots of health inequalities.’ (ibid). Social scientists, and criminologists, have presented biological/genetic explanations of behaviour as dangerous in terms of their potential effect on the individuals or groups identified as genetically at risk. There are obvious dangers of discrimination against, and the stigmatisation of, already vulnerable groups who would be the first to be tested i.e. ‘problem’ families or minority ethnic groups. Discrimination could affect education, employment and family life. The effect of an individual being told s/he has a risk based on a genetic test has been much discussed in relation to health risks (Claassen et al., 2010 . While such information could be motivating, because it is personalised, it can also induce a fatalistic attitude that discourages the person from taking preventative measures. Claasen et al. conclude that it is important to identify those vulnerable to the fatalistic impact and to tailor health risk information (ibid p.194). Identifying risk for behaviour, rather than for disease, is likely to be more problematic because of the difficulty of finding preventative measures that are within the individuals’ own control.

..using DNA to assess risk, make a diagnosis or tailor treatments, may weaken beliefs in the efficacy of preventive behaviour and reinforce biological ways of reducing risk, resulting in a preference for medication as opposed to behavioural means to control or reduce risk (ibid, xiv).

Claasen et al.’s comment on genetic tests for health conditions could apply equally to parents given a behavioural risk for their young child from a genetic test, perhaps before any problem behaviour was evident. The test result could weaken parents’ belief that they could take action to prevent/reduce the risk of the behaviour developing in their child and pharmaceutical solutions, as posited by Caspi et al. might not be available (Caspi et al., 2002 , xvii). However, it is not necessarily the case that evidence of genetic or biological influence on behaviour leads to more punitive treatment. DeLisi et al. give the example of the use of findings from adolescent brain science in the case of Roper v. Simmons in the US which abolished the death penalty for adolescents. On the basis of the research it was stated that young people under the age of 18 ‘are more vulnerable or susceptible to negative influences and outside pressures including peer pressure’ (DeLisa et al., 2010 , p.25) When evidence on genetic traits associated with criminal behaviour has been allowed by courts, mainly in the US, it has so far more often been accepted as a mitigating rather than an aggravating factor in the offenders’ behaviour (Denno, 2009 , Farahany and Coleman, 2006 ).

Environmental explanations of behaviour can, of course, also be presented as deterministic, claiming a closed future for those experiencing poverty and disadvantage. However, it is biological explanations that have caused more concern not only because of the history of eugenics but also because they may be seen as more fundamental, being there from birth, and as harder to change. The public in surveys are reported to see the greatest role for genetic factors in physical features, a lesser role in health conditions and a smaller role still in human behaviour (Condit, 2010 , p.619).

Public perceptions

The model of nature/genes and nurture/environment is still used in behavioural genetics, as well as in popular culture, and has implications for public policy, including the treatment of offenders who claim that a genetic trait has influenced their criminal behaviour. The aim of this research was to explore ideas on the causes of behaviour, particularly violent and antisocial behaviour and examine how respondents use the nature/nurture model. This qualitative research looks at the ways in which lay publics in different age groups conceptualise the factors and influences that made them who they are and their explanations for the behaviour of other people; especially violent behaviour. It was hypothesised that the increased research and media emphasis on the role of genetic factors in health and behaviour might result in an increasing interest in ‘nature’, biology and genes as explanations for behaviour particularly among the young, but, when explaining their own behaviour people might prefer to see themselves as agents with control over their lives. By exploring explanations of behaviour with respondents from different generations, age differences should be apparent.

The views of 78 respondents from 3 generations were gathered by individual interview and questionnaires, using the same open ended questions and responses to two real-life criminal court case studies where environmental or genetic factors had been used by the defence team. Respondents were drawn from a group of retired people participating in an informal ‘senior learners’ programme at Lancaster University, a group of their mainly younger relatives and, in order to recruit more third generation respondents, a group of first year students taking a criminology module. The senior learners group had a programme of talks and discussions and could attend undergraduate lectures. They had, by definition, shown an interest in current issues in a range of fields. There were no educational or age requirements for the group but all the volunteers were retired from paid work and were aged from around 65 years to over 80 years.. They had had similar careers to those popular with social science students; social work, probation, teaching and administrative positions. The senior learners were asked to pass on questionnaires to younger relatives to investigate age differences in attitudes. The first 13 senior learners who responded were interviewed but as only 15 questionnaires were received from their relatives ethical approval was obtained to distribute the same questionnaire to Lancaster University students taking the criminology first year module. Most students were enrolled on social science degrees, including psychology and sociology, and age 18 or 19. While the sample of senior learners and relatives had only a few more women than men, 78 per cent of the students were female reflecting the gender balance on the module as a whole. This makes it difficult to comment on any gender differences in responses. No claims to generalisability are made for this exploratory study. Responses were coded and entered on SPSS and also analysed thematically using Atlas-ti.

The introduction to the interviews and questionnaire was ‘I am interested in your views and ideas on what makes us the people we are; what makes people behave the way they do? What is the influence of nature and nurture?’ The terms, nature and nurture were not used again until the final question. Although the terms were not defined all respondents readily used them with consistent meanings. They identified ‘nature’ with biology, ‘what you are born with’ and genes or DNA and nurture with all aspects of the environment including parenting, socio-economic conditions, the food you eat, culture and other people. Their understanding of environment was therefore similar to that used by genetic researchers; environment as everything that is external to the individual, although they tended to refer more to the social than the biological environment.

A general warm-up question asked whether, in their own family, there was anything they thought of as a ‘family trait’. Then respondents were asked; ‘Imagine a baby swapped at birth and brought up in a completely different family– which influences do you think would be most important – the influence of the birth parents or the influences of the new family- and why?’ 4 The rest of the interview schedule, and the subsequent questionnaire, consisted of open-ended questions.

Respondents were asked how they would explain different kinds of behaviour if they came across a child who is kind and considerate; a young person who displays antisocial and aggressive behaviour adult and an adult with criminal convictions for violence. This was to tap into any differences in general explanations of good and bad behaviour in young people and adults. A quotation about the child killers in the Bulger case being ‘unreformable’ was used to ascertain whether they saw some types of violent behavior, and the actors concerned, as immutable. In order to see how respondents conceptualized the influences of nature/biology/genes and environment/people/experiences in their own lives, respondents were asked to write down ‘what or who made you what you are today’ and any explanation of their responses. Comments were gathered on the introduction of an environmental factor (childhood neglect) by the defence in a violent attack by two young boys in England, and on a genetic factor (MAOA levels) introduced by the defence in an criminal court in Italy. Respondents were asked how they thought such evidence should be dealt with; whether it should affect the degree of blame and whether it should affect criminal responsibility. The final question asked if it mattered ‘for individuals or society’ whether nature or nurture was seen as most important in explaining problem behaviour. Those interviewed were asked if they had any further comments and there was a space for any additional comments on the questionnaire.

This paper focuses on the ways in which respondents employed nature/genes and nurture/environment in their responses as a whole and what other concepts they drew on when explaining behaviour.

Respondents’ explanations of what makes people behave the way they do are discussed through three themes.

Nurture is more influential than nature

Nature and nurture interact

Emphasising nature (but never nurture) can be dangerous

Theme 1: Nurture is more influential than nature

Whether asked about influences on a baby adopted at birth, on their own lives, on an aggressive child or a violent young person, almost all respondents emphasised nurture. Parents and family were seen as the most important influences for babies and young children, moving to peer group and other relationships and experiences for a young person. The explanation for the violent behaviour of an adult had more to do with the individual and the importance of nurture/environment in explaining behaviour weakened. The quotations below explaining behaviour in a child adopted at birth, a young person and an adult illustrate the widening of influences from infancy through childhood and the onus on adults to take responsibility for themselves.

[a child] The environment in which a child grows up in, particularly the influence and role of the parents shapes how a child will grow up and what sort of adult they will be (77 Student).

[a young person] I believe that upbringing shapes a person’s personality. Provisions of education, lifestyle opportunities and friendship groups all determine ….outlook. You can see evidence in young people at the school I teach at (20 Relative).

Once adult they have to take responsibility for themselves and address whatever has been in their background. An adult can’t turn round and say it’s not my fault (5 Senior Learner).

Participants also saw themselves as shaped by the people surrounding them, starting with their parents, or those who brought them up. Several mentioned the illness and/or death of a parent during their childhood and older respondents talked about separation due to the second world war. Students were especially likely to mention the influence of morals instilled in them by their parents, the core values and discipline that they were taught at home. Educational experiences were important to all. For the senior learners the school leaving age had been age 15, so whether or not they stayed on at school and took public examinations was crucial for their future, and, this decision depended largely on their parents and environment. For the student respondents who had come to university from school, life so far has been ‘kind of set-out’ (41 Student), in the sense that they had progressed through the education system to gain qualifications for university. For their peer group it was normal still to be in education or training at the age of 18.

The lasting effects of early influences were particularly striking among the senior learners, because they were much further removed in years from their childhood. Many related stories about parental influence and also about teachers who taught them at least 50 years ago and had affected them for better or worse. For example a senior learner recalled one of her teachers;

I hated primary school – the teacher in 3rd or 4th year juniors [for ages 9–11] I hated her she was not a nice woman….. I passed to go to the grammar school and it shocked her. She made a derogatory comment – may not have been directed at me but felt it was- about some who should have passed and didn’t and some passing who should not have done…… I always vowed I would never be like that when I was teaching….(11 Senior Learner).

Those who related negative influences presented themselves as active in response, not necessarily at the time but later in their lives. For example a student whose mother had died wrote that ‘it made me more independent’ and another student who was bullied at school wrote that ‘it made me stronger’. The adult had to deal with all the influences (negative or positive) and take control.

Theme 2: Nature and nurture interact

While respondents’ view of themselves and of a child adopted at birth assigned greater influence to environment this did not mean that they held a simplistic model of, for example 60:40 nurture to nature. In this one question when they were asked to choose one or other as the major influence, almost all chose nurture, as many social scientists might do. However, in open questions and comments more complex interactive models were expressed. Environment/nurture can affect genes/nature and vice versa. No one used the term epigenetics but responses referred to the possibility of environmental influences affecting gene expression, for example;

People with certain predispositions (e.g. to violence) are affected by society, and society affects how their genes are expressed (40 Student).

An older respondent reflects on personal experience of child rearing and asks whether nurture is influenced by nature;

I think the nature nurture debate is very interesting. In my family I can see where my children have their own natures that have developed despite being brought up in the same family with the same boundaries etc. However, as a parent did I alter how I nurture them to take into account their nature? (14 Senior Learner).

This quotation illustrates the inseparability of nature and nurture. The child is developing within the family and the parent is developing parenting strategies informed by previous experiences and by other influences including the reactions of the children.

It was obvious to respondents that both genetic and environmental factors impact on everyone (although the role of genes is not yet understood) and it will be harder for some than for others to behave well because of their genes and environment. These people may need different treatment or extra help if they have committed violent and aggressive crimes but that does not excuse their behaviour. Only in exceptional cases, like insanity, can a young person or adult be said to have no choice but to act in a particular way. It is important that people are seen as responsible while also giving them the help they need. In these two comments the treatment for environmental problems and ‘biology’ are similar; the individual can be helped to modify his/her behaviour.

No, [nature and nurture] both play a part, but they can’t be the explanation for everything. Some people grow up in broken homes and get treated appallingly- yet they seem to understand right + wrong and accept responsibility for their actions. There are too many excuses and we never solve any problems, just make them harder to resolve.......I think if you are sane and you know right from wrong you need to suffer the consequences if you’ve committed a crime, but I do appreciate you may need help psychologically if you have anger issues, for example. If we constantly find reasons to diminish blame from people who have committed heinous acts of crime more people will think they can get away with it and it will cause more harm than good (78 Student).

Some say you can’t fight your biology, but there are social factors that can stop bad behaviour like learned restraint (72 Student).

The desire to leave a space for individual agency may be linked to the finding that emphasising nature, but never nurture, could be dangerous. It is clear that as children grow up they can exercise more control over their environment, although some have more control and choices than others. On the other hand, whatever the individual is born with (genes and nature) is, or seems to be, less malleable which could lead to different criminal justice policies and different social perceptions of the criminal.

Theme 3: Emphasising nature (but never nurture) can be dangerous for society as a whole as well as for the criminal and victims

The question asked was whether it mattered ‘for individuals or society’ if either nature or nurture was seen as most important in explaining problem behavior. The two most popular answers were that both nature and nurture were needed to explain behaviour, or, that nurture was more important and that there were dangers in emphasising nature. No one in the sample regarded an emphasis on nurture as dangerous or detrimental to the individual or society. On the contrary, emphasising nurture was thought more likely to lead to non-punitive treatment of offenders. There would be attempts to alter future behaviour through improved education and parenting and spreading of knowledge in society about the impact nurture has on young people. Society as a whole would share the blame rather than the individual. As a student put it; ‘society as a whole [would be] open for criticism’ (55 S). An emphasis on nurture was therefore seen as more likely to lead to understanding of problem behaviours and effective treatment, however, the individuals were still to be held responsible for their behaviour.

In contrast there was a mistrust of nature/genetic explanations that again centred on the practical consequences for individuals. It would affect the way criminals were treated by others but could also change their view of themselves. Behaviour would be seen as unchangeable, out of the control of the individual or social action. As a consequence, individual accountability might be removed. The idea that individuals must normally be held responsible for their actions was constantly emphasised (Levitt, 2013 ).

It does [matter] because [if nurture is emphasised] people will care, parent and look after and raise people with more care. However if it’s proven it is nature, then people may lose the will to live (60 Student).

Several SLs referred to the examination at the end of primary education (the ‘eleven plus’) when explaining why they emphasised environment/nurture rather than nature, or, in this case, innate intelligence. The ‘eleven plus’ examination was used to decide which children would be offered a place at an academically selective grammar school and was based on the idea that intelligence, and future academic achievement, could be accurately measured and predicted at the age of 10 or 11.

‘The 11+ was a nature thing. I did the 11+ − it had an effect. Saying children not going to improve or change. Very embedded in the whole idea of nature – it can’t really be true’ (8 Senior Learner).

An emphasis on nature has practical detrimental consequences for individuals. Their status is fixed, for example as ‘not academic’ or ‘born evil’ and suggests, to them and to others, that their ‘nature’ is unchangeable or very difficult to change by individual or social action.

Yes, [it matters] hugely as position of blame is dependent on whether a person chose to do what they did .....nature suggests no control (35 Student).

Those who thought an emphasis on nature meant people were irredeemable either gave that as a reason not to emphasise nature or to suggest that in fact ‘defects’ of nature could be overcome, as in this comment by a student emphasising the power of education;

Yes it is very important because it helps to understand if people are reformable (nurture) or irredeemable (nature). I believe we are determined by our education and thus with the proper help we can change. In the case of people with major biological defects, education is still a way to get over these obstacles and society should be ready to help these people (38 Student).

It might be thought that offenders themselves would embrace a genetic explanation of their behaviour if this was interpreted, as the respondents feared, as meaning they were not responsible for their crimes. However, a small study of juvenile offenders in the Netherlands found that they gave social explanations of their crimes and most rejected the idea that biology might be a factor. They committed a crime for a specific purpose like to get money or to impress others or they gave environmental reasons such as a deprived background or peer pressure or explained their offences were due to psychological conditions brought on by the use of alcohol and soft drugs (Horstkötter et al., 2012 , p.291). Whether they gave goal directed or environmental reasons ‘most of them also state that they had a choice and that it was their choice to commit the crime’ (ibid p.292). As one young offender said in interview;

In the end the person makes the choice himself… The choices I have made also had a share in my past. But in the end I am the one who has made these choices (ibid).

• Genes and environment

Respondents were at ease with the language of nature and nurture which was only used in the introduction to the questionnaire or interview. They readily equated genes with nature and nurture with all sorts of environmental influences. There was an acknowledgement that our understanding of environmental factors is greater than our understanding of genetics but that that would change. Older respondents were more likely to be concerned about such a change.

They're going to be doing a lot more with genetics. Influences policy profoundly and people have to be very careful. It worries me that seen to be [more determining]. The complexities don’t get looked at. If you emphasise environment it is safer from a policy point of view because given that most people don’t know what they are talking about it is safer to see the person as redeemable than to come down on the side of genetics and write people off (3 Senior Learner).

This quotation is typical in its view that nature/genes are seen as determining even though the influences on behaviour are, in reality, complex. Like the studies quoted at the beginning of the article respondents often acknowledged the complexities as nature and nurture interact but separated them when explaining the causes of specific behaviours. Students were less likely to be fearful of genetic explanations of behaviour despite their academic interest in social science. However, the hypothesis that young people might be more likely to be interested in genetic explanations for behaviour was not shown in this small study. The senior learners were more likely to refer to reading on genes and display knowledge of genetics. Older respondents and their relatives more often echoed the sociologists’ concerns about behavioural genetics discussed by Bearman earlier (Bearman, 2008 ). For those who feared the practical consequences of genetic explanations, like the respondent quoted above, ‘it is safer’ to keep away from them.

Some respondents in all age groups were prepared for advances in genetics to change their understanding of behaviour and prepared for current views of genes/nature as more basic, fixed and unchanging to change too. One of the youngest relatives, in her 20s, emphasised our incomplete knowledge of genetic influences on behaviour as a reason for focussing on nurture ‘at present’;

It is very tricky as we cannot see genes and I am not sure that I totally trust the idea of blaming genes for violent behaviour- maybe the person has a gene for passive behaviour as well. …….In any case we can change nurture but at present we cannot change nature so let’s do one thing at a time (20 Relative).

As respondents in this small study grappled with explanations for their own and others’ behaviour they focussed on the practical consequences leading to a greater concern over explanations based on nature than the more familiar ones based on a complex web of environmental factors. Whereas academic researchers approach the debate from their disciplinary perspectives which may or may not engage with practical and policy issues, the key issue for the public was what sort of explanations of behaviour will lead to the best outcomes for all concerned.

1 Behavioural epigenetic research has indicated that life experiences can affect gene expression. While controversial the research suggests the possibility of further complications for the nature-nurture relationship as nurture may be said to shape nature (Buchen, 2010 Powledge, 2011 ). 2 Bearman op cit iv. The ESRC Cambridge Network Social Contexts of Pathways into Crime (SCoPiC) promoted multidisciplinary research into the causes of crime and included the E risk longitudinal twin study led by Terri Moffitt which investigated how genetic and environmental factors shape children's disruptive behaviour http://www.scopic.ac.uk Accessed 3 Sep 2013. 3 Violent and antisocial behaviour in this longitudinal study was correlated with a common genetic trait (low expression of MAOA) only where the person was severely maltreated in childhood. Behaviour was measured on 4 outcomes; diagnoses of conduct disorder, psychological tests of aggression and anti-social personality disorder and convictions for violent crime. Caspi et al. 2002 (supplementary material). 4 This initial warm-up question implied that the influences of nature and nurture could be separated and quantified as in common usage both in academic and popular discourses. As discussed respondents were able to express their views more fully (and with more complexity) in the subsequent open questions.

Anderson P, Butcher KF, Schanzenbach DW: Childhood obesity and disadvantage: is nature trumping nurture? NBER working paper No. 13479 . Cambridge MA: National Bureau of Economic Research; 2007. . Accessed 3 Sep 2013 http://www.nber.org/papers/w13479 . Accessed 3 Sep 2013

Book   Google Scholar  

Bearman P: Exploring genetics and social structure. American Journal of Sociology 2008, 114 (Suppl;S1):v-x. p.vi p.vi

Article   Google Scholar  

Brescianini S, Volzone A, Fagnani C, Patriarca V, Grimaldi V, Lanni R, Serino L, Mastroiacovo P, Stazi MA: Genetic and environmental factors shape infant sleep patterns: a study of 18-month-old twins. Pediatrics 2011, 127 (5):1296–1302. 10.1542/peds.2010-0858

Buchen L: In their nurture – can epigenetics underlie the enduring effects for a mother’s love. Nature 2010, 467: 146–148. 10.1038/467146a

Campbell E, Ross LF: Attitudes of healthcare professionals and parents regarding genetic testing for violent traits in childhood. Journal of Medical Ethics 2004, 30: 580–586. 10.1136/jme.2003.005389

Caspi A, et al .: Role of genotype in the cycle of violence in maltreated children. Science 2002, 2 (5582):851–854.

Claassen L, Henneman L, De Vet R, Knol D, Marteau T, Timmermans D: Fatalistic responses to different types of genetic risk information: Exploring the role of Self-Malleability. Psychology and Health 2010, 25 (2):183–196. 10.1080/08870440802460434

Condit CM: When do people deploy genetic determinism? A review pointing to te need for multi-Factorial theories of public utilization of scientific discourses. Sociology Compass 2010, 5 (7):618–635.

Cooper JA, Walsh A, Ellis L: Is criminology moving toward a paradigm shift? Evidence from a Survey of the American Society of Criminology Journal of Criminal Justice Education 2010, 21 (3):332–347.

Google Scholar  

Craddock N: Horses for courses: the need for pragmatism and realism as well as balance and caution. A commentary on Angel. Social Science and Medicine 2011, 73: 636–638. 10.1016/j.socscimed.2011.06.049

DeLisa M, Wright JP, Vaughn MG, Beaver KM: Nature and nurture by definition means both: a response to males. Journal of Adolescent Research 2010, 25 (1):24–30. p.25 p.25 10.1177/0743558409353063

Denno DW: Behavioral genetics evidence in criminal cases: 1994–2007. In The impact of behavioral sciences on criminal law . Edited by: Farahany NA. Oxford: Oxford University Press; 2009:317–354.

Chapter   Google Scholar  

Dixon M: Brave new choices: behavioural genetics and public policy . London: IPPR; 2005.

Farahany NA, Coleman JE Jr: Genetics and responsibility: to know the criminal from the Crime. Law and Contemporary Problems 2006, 69: 115–162.

Fotaki M: Agency versus structure or nature versus nurture: when the new twist on an old debate is not that new after all: a commentary on Angel. Social Science & Medicine 2011, 73 (5):639–642. 10.1016/j.socscimed.2011.06.044

Giddens A: Sociology . Cambridge: Polity Press; 2009.

Haralambos M, Holborn M: Sociology themes and perspectives . London: Collins Educational; 2004.

Horstkötter D, Berghmans R, de Ruiter C, Krumeich A, de Wert G: “We are also normal human beings, you know”. Views and attitudes of juvenile delinquents on antisocial behaviour, neurobiology and prevention. International Journal of Law and Psychiatry 2012, 35: 289–297. 10.1016/j.ijlp.2012.04.006

Keller EF: The mirage of a space between nature and nurture . Durham & London: Duke University Press; 2010.

Lea R, Chambers G: Monamine oxidase, addiction and the ‘warrior’ gene hypothesis. The New Zealand Medical Journal 2007, 120: 1250. Accessed 3 Sep 2013 http://journal.nzma.org.nz/journal/120–1250/2441/ .

Levitt M: Genes, environment and responsibility for violent behaviour: ‘Whatever genes one has it is preferable that you are prevented from going around stabbing people’. New Genetics and Society 2013, 32 (1):4–17. 10.1080/14636778.2012.699352

Levitt M, Pieri E: “It could just be an additional test couldn’t it?” Genetic testing for susceptibility to aggression and violence. New Genetics and Society 2009, 28 (2):189–200. 10.1080/14636770902901629

McCrae RR, Costa PT Jr, Ostendorf F, Angleitner A, Hřebíčková M, Avia MD, Sanz J, Sánchez-Bernardos ML, Kusdil ME, Woodfield R, Saunders PR, Smith PB: Nature over nurture: temperament, personality and life span development. Journal of Personality and Social Psychology 2000, 78 (1):173–86.

Nuffield Council on Bioethics: Genetics and human behaviour: the ethical context . London: Nuffield Council on Bioethics; 2002.

Parens E, Chapman ER, N. Press N (Eds): Wrestling with behavioural genetics. Science, ethics and public conversation . Baltimore: The John Hopkins Press; 2006.

Powledge TM: Behavioral Epigenetics: How nurture shapes nature. Biosciences 2011, 61: 588–592. 10.1525/bio.2011.61.8.4

Traynor BJ, Singleton AB: Nature versus nurture: death of a dogma, and the road ahead. Neuron 2010, 68: 196–200. 10.1016/j.neuron.2010.10.002

Walsh A: Biology and criminality. The biosocial synthesis . Oxon: Routledge; 2009.

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Acknowledgement

The support of the Economic and Social Research Council (ESRC) is gratefully acknowledged. This work was part of the Research Programme of the ESRC Genomics Network at Cesagen (ESRC Centre for Economic and Social Aspects of Genomics).

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Mairi Levitt

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Levitt, M. Perceptions of nature, nurture and behaviour. Life Sci Soc Policy 9 , 13 (2013). https://doi.org/10.1186/2195-7819-9-13

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Received : 18 September 2013

Accepted : 06 December 2013

Published : 12 December 2013

DOI : https://doi.org/10.1186/2195-7819-9-13

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