Behavioural genetics

Behavioural genetics, also commonly referred to as behaviour genetics, is the field of study that examines the role of genetic and environmental influences on behaviour, with subspecialties focused on human behavioural genetics and animal behaviour genetics. Behavioural genetics is a field that uses genetic methodologies to understand the nature and origins of individual differences in behavior. Often associated with the "nature versus nurture" debate, behavioural genetics is highly interdisciplinary, involving contributions from biology, neuroscience, genetics, epigenetics, ethology, psychology, and statistics. Behavioural geneticists study the inheritance of behavioural traits. In humans, this information is often gathered through the use of genetic association studies or family studies including the twin study or adoption study. In animal studies, breeding, transgenesis, and gene knockout techniques are common. Psychiatric genetics, epigenetic research on behaviour, and genetic research in neuroscience are related subfields within behavioral genetics.

History

Selective breeding and the domestication of animals is perhaps the earliest evidence that humans considered the idea that individual differences in behavior could be due to natural causes.^[1] Plato and Aristotle each speculated on the basis and mechanisms of inheritance of behavioral characteristics. Plato, for example, argued in The Republic that selective breeding among the citizenry to encourage the development of some traits and discourage others, what today might be called eugenics, was to be encouraged in the pursuit of an ideal society. Behavioural genetic concepts also existed during the English renaissance, where William Shakespeare perhaps first coined the terms "nature" versus "nurture" in the The Tempest, where he wrote in Act IV, Scene I, that Caliban was "A devil, a born devil, on whose nature Nurture can never stick".^[2]

Galton in his later years

Modern-day behavioural genetics began with Sir Francis Galton, a nineteenth-century intellectual and cousin of Charles Darwin. Galton was a polymath who studied many things, including the heritability of human abilities and mental characteristics. His most well-known work involves a large pedigree study of social and intellectual achievement in the English upper-class. In 1869, 10 years after Darwin's Origin of the species, Galton published his results in Hereditary Genius.^[3] In this work, Galton found that the rate of "eminence" was highest among close relatives of eminent individuals, and decreased as the degree of relationship to eminent individuals decreased. While Galton could not rule out the role of environmental influences on eminence, a fact which he acknowledged, the study served to initiate an important debate about the relative roles of genes and environment on behavioral characteristics. Through his work, Galton also "introduced multivariate analysis and paved the way towards modern Bayesian statistics" that are used throughout the sciences—launching what has been dubbed the "Statistical Enlightenment".^[4]

The field of behavioural genetics, as founded by Galton, was utlimately undermined by another of Galton's intellectual contributions, the founding of the eugenics movement in 20th century society. The primary idea behind eugenics was to use selective breeding combined with our knowledge about the inheritance of behaviour to improve the human species. The eugenics movement was subsequently discredited by scientific corruption and genocidal actions in Nazi Germany. Behavioural genetics was thereby discredited through its association to eugenics.^[5]

In 1951, Calvin S. Hall in his seminal book chapter on behavioural genetics introduced the term "psychogenetics",^[6] which enjoyed some limited popularity in the 1960s and 1970s.^[7][8] However, it eventually disappeared from usage in favour of "behaviour genetics".

Publication trends in behavioural genetics since 1960. Adapted from source.^[9]

Years	Total Behavioural Genetic Articles	Articles in the journal Behavior Genetics
1960-1965	162	0
1966-1970	395	18
1971-1975	649	73
1976-1980	825	126
1981-1985	1,403	160
1986-1990	1,651	147
1991-1995	2,301	171
1996-2000	3,445	171
2001-2005	6,485	208
2006-2010	14,164	263
2011-2015	15,443	205

Behaviour genetics, per se, gained recognition as a research discipline with the publication in 1960 of the textbook Behavior Genetics by John L. Fuller and William Robert (Bob) Thompson (then Chair of the Department of Psychology at Queen's University, Canada).^[10] Nowadays, it is widely accepted that most behaviours in animals and humans are under some degree of genetic influence.^[11]

Underscoring the role of evolution in behavioural genetics, Theodosius Dobzhansky was elected the first president of the Behavior Genetics Association in 1972; the BGA bestows the Dobzhansky Award on researchers for their outstanding contributions to the field. In the early 1970s, Lee Ehrman, a doctoral student of Dobzhansky, wrote seminal papers describing the relationship between genotype frequency and mating success in Drosophila,^[12][13][14] lending impetus to the pursuit of genetic studies of behaviour in other animals. Studies on hygienic behaviour in honey bees were also carried out early in the history of the field.^[15][16] The social behaviour of honey bees has also been studied and recent work has focussed on the gene involved in the foraging behaviour of Drosophila; this essentially allowed for deriving a relationship between gene expression and behaviour, where the gene regulating foraging behaviour in Drosophila also regulated social behaviour in bees.^[17]

The table demonstrates how quickly the field of Behavioral Genetics has been expanding since the lull in behavioral genetic research after World War II, and after the first issue of the Behavior Genetics journal was published in February 1970. The table includes information adapted from Ayorech et al. (2016),^[9] and includes publications on behavior genetics in animals and humans, quantitative and molecular.

Methods

The primary goal of behavioural genetics is to investigate the nature and origins of individual differences in behaviour. Traditionally, different methods were used in human and animal experiments.

Animal studies

In animal research selection experiments have often been employed. For example, laboratory house mice have been bred for open-field behaviour,^[18] thermoregulatory nesting,^[19] and voluntary wheel-running behaviour.^[20] A range of methods in these designs are covered on those pages.

Twin and family studies

Marian and Vivian Brown, identical twins, photographed by Christopher Michel

Traditionally the most common research design used in behavioural genetic research are variations on family designs (also known as pedigree designs), including twin studies and adoption studies. Quantitative genetic modeling of individuals with known genetic relationships (e.g., parent-child, sibling, dizygotic and monozygotic twins) allows one to estimate to what extent genes and environment contribute to phenotypic differences among individuals. The basic intuition of the twin study is that monozygotic twins share 100% of their genome and dizygotic twins share 50% of their segregating genome. Thus, differences between the two members of a monozygotic twin pair can only be due to differences in their environment, whereas dizygotic twins will differ from one another due to environment as well as genes. Under this simplistic model, if dizygotic twins differ more than monozygotic twins it can only be attributable to genetic influences. An important assumption of the twin model is the equal environment assumption that monozygotic twins have the same shared environmental experiences as dizygotic twins. If, for example, monozygotic twins tend to have more similar experiences than dizygotic twins--and these experiences themselves are not genetically mediated through gene-environment correlation mechanisms--then monozygotic twins will tend to be more similar to one another than dizygotic twins for reasons that have nothing to do with genes.

Twin studies of monozygotic and dizygotic twins use a biometrical formulation to describe the influences on twin similarity and to infer heritability.^[21] The formulation rests on the basic observation that the variance in a phenotype is due to two sources, genes and environment. More formally, $Var(P) = g + (g \times \epsilon) + \epsilon$, where $P$ is the phenotype, $g$ is the effect of genes, $\epsilon$ is the effect of the environment, and $(g \times \epsilon)$ is a gene by environment interaction. The $g$ term can be expanded to include additive ($a^2$), dominance ($d^2$), and epistatic ($i^2$) genetic effects. Similarly, the environmental term $\epsilon$ can be expanded to include shared environment ($c^2$) and non-shared environment ($e^2$), which includes any measurement error. Dropping the gene by environment interaction for simplicity (typical in twin studies) and fully decomposing the $g$ and $\epsilon$ terms, we now have $Var(P) = (a^2 + d^2 + i^2) + (c^2 + e^2)$. Twin research then models the similarity in monozygotic twins and dizogotic twins using simplified forms of this decomposition, shown in the table.

Decomposing the genetic and environmental contributions to familial similarity.

Type of relationship	Full decomposition	Falconer's decomposition
Perfect similarity	$1.0 = a^2 + d^2 + i^2 + c^2 + e^2$	$1.0 = a^2 + c^2 + e^2$
Monozygotic twin correlation	$r_{MZ} = a^2 + d^2 + i^2 + c^2$	$a^2 + c^2$
Dizygotic twin correlation	$r_{DZ} = \frac{1}{2}a^2 + \frac{1}{4}d^2 + (k)i^2 + c^2$	$\frac{1}{2}a^2 + c^2$
Where $k$ is an unknown (probably very small) quantity.

The simplified Falconer formulation can then be used to derive estimates of $a^2$, $c^2$, and $e^2$. Rearranging and substituting the $r_{MZ}$ and $r_{DZ}$ equations one can obtain an estimate of the additive genetic variance, or heritability, $a^2 = 2(r_{MZ} - r_{DZ})$, the non-shared environmental effect $e^2 = 1- r_{MZ}$ and, finally, the shared environmental effect $c^2 = r_{MZ} - a^2$. The Falconer formulation is presented here to illustrate how the twin model works. Modern approaches use maximum likelihood to estimate the genetic and environmental variance components. ^[22]

Measured genetic variants

The Human Genome Project has allowed scientists to directly measure the sequence of human DNA nucleotides. Once measured, genetic variants can be tested for association with a behavioral phenotype, such as psychiatric disorder, cognitive ability, etc.

Candidate genes

One popular approach has been to test for association candidate genes with behavioural phenotypes, where the candidate gene is selected based on some a priori theory about biological mechanisms involved in the genesis of a behavioural trait or phenotype. In general, such studies have proven difficult to broadly replicate^[23][24] and there has been concern raised that the false positive rate in this type of research is high.^[25][26]

Genome-wide association studies

In genome-wide association studies, researchers test the relationship of millions of genetic polymorphisms with behavioural phenotypes across the genome. This approach to genetic association studies is largely atheoretical, and typically not guided by a particular biological hypothesis about phenotype etiology. Genetic association findings for behavioral traits and psychiatric disorders have been found to be highly polygenic (involving many small genetic effects).^{[27][28][29][30][31]}

SNP heritability and co-heritability

Recently, researchers have begun to use similarity between classically unrelated people at their measured single nucleotide polymorphisms (SNPs) to estimate genetic variation or covariation that is tagged by SNPs.^[32][33] To do this, researchers find the average genetic correlation across all SNPs between all individuals in a (typically large) sample, and use Haseman-Elston regression or restricted maximum likelihood to estimate the genetic variation that is tagged by SNPs. The proportion of phenotypic variation that is tagged by SNPs is called "SNP heritability." Intuitively, SNP heritability increases to the degree that phenotypic similarity is predicted by genetic similarity at measured SNPs, and is expected to be lower than the true narrow-sense heritability to the degree that measured SNPs fail to "tag" or predict (typically rare) causal variants. The value of this method is that it is an independent way to estimate heritability that does not require the same assumptions as those in twin and family studies, and that it gives insight into the allelic frequency spectrum of the causal variants underlying trait variation.

Quasi-experimental designs

Some behavioural genetic designs are useful not to understand genetic influences on behaviour, but to control for genetic influences to test environmentally-mediated influences on behaviour. Such behavioural genetic designs may be considered a subset of natural experiments,^[34] quasi-experiments that attempt to take advantage of naturally occurring situations that mimic true experiments by providing some 'control' over an independent variable. Natural experiments can be particularly useful when experiments are infeasible, due to practical or ethical limitations.

A general limitation of observational studies is that the relative influences of genes and environment are confounded. A simple demonstration of this fact is that measures of 'environmental' influence are heritable.^[35] Thus, observing a correlation between an environmental risk factor and a health outcome is not necessarily evidence for environmental influence on the health outcome. Similarly, in observational studies of parent-child behavioral transmission, for example, it is impossible to know if the transmission is due to genetic or environmental influences, due to the problem of passive gene-environment correlation.^[34] The simple observation that the children of parents who use drugs are more likely to use drugs as adults does not indicate why the children are more likely to use drugs when they grow up. It could be because the children are modeling their parents' behavior. Equally plausible, it could be that the children inherited drug-use-predisposing genes from their parent, which put them at increased risk for drug use as adults regardless of their parents' behavior. Adoption studies, which parse the relative effects of rearing environment and genetic inheritance, find a small to negligible effect of rearing environment on smoking, alcohol, and marijuana use in adopted children, ^[36] but a larger effect of rearing environment on harder drug use.^[37]

Other behavioural genetic designs include discordant twin studies,^[38] children of twins designs,^[39] and Mendelian randomization.^[40]

Broad conclusions from behavioral genetic research

There are many broad conclusions to be drawn from behavioural genetic research about the nature and origins of behaviour.^[41] Three major conclusions include: 1) all behavioural traits and disorders are influenced by genes; 2) environmental influences tend to make members of the same family more different, rather than more similar; and 3) the influence of genes tends to increase in relative importance as individuals age.

Genetic influences on behaviour are pervasive

It is clear from multiple lines of evidence that all researched behavioural traits and disorders are influenced by genes; that is, they are heritable. The single largest source of evidence comes from twin studies, where it is routinely observed that monozygotic (identical) twins are more similar to one another than are same-sex dizygotic (fraternal) twins.^[42][43]

The conclusion that genetic influences are pervasive has also been observed in research designs that do not depend on the assumptions of the twin method. Adoption studies show that adoptees are routinely more similar to their biological relatives than their adoptive relatives for a wide variety of traits and disorders. In the landmark Minnesota Study of Twins Reared Apart, monozygotic twins separated shortly after birth were reunited in adulthood. These reared-apart twins were as similar to one another as were twin reared together on a wide range of measures including general cognitive ability, personality, religious attitudes, vocational interests, and so on.^[44] Approaches using genome-wide genotyping have allowed researchers to measure genetic relatedness between individuals based on millions of genetic variants. Methods exist to test whether the extent of genetic similarity (aka, relatedness) between nominally unrelated individuals (individuals who are not close or even distant relatives) is associated with phenotypic similarity.^[33] Such methods do not rely on the same assumptions as twin or adoption studies, and routinely find evidence for heritability of behavioral traits and disorders.^[45][46][47]

Nature of environmental influence

Just as all researched human behavioral phenotypes are influenced by genes (i.e., are heritable), all such phenotypes are also influenced by the environment.^[48] The basic fact that monozygotic twins are genetically identical but are never perfectly concordant for psychiatric disorder or perfectly correlated for behavioral traits, indicates that the environment shapes human behavior.

The nature of this environmental influence, however, is such that it tends to make individuals in the same family more different from one another, not more similar to one another. That is, estimates of shared environmental effects ($c^2$) in human studies are small, negligible, or zero for the vast majority of behavioral traits and psychiatric disorders, whereas estimates of non-shared environmental effects ($e^2$) are moderate to large.^[48] From twin studies $c^2$ is typically estimated at 0 because the correlation ($r_{MZ}$) between monozygotic twins is at least twice the correlation ($r_{DZ}$) for dizygotic twins. When using the Falconer variance decomposition ($1.0 = a^2 + c^2 + e^2$) this difference between monozygotic and dizygotic twin similarity results in an estimated $c^2=0$. It is important to note that the Falconer decomposition is overly simple. It removes the possible influence of dominance and epistatic effects which, if present, will tend to make monozygotic twins more similar than dizygotic twins and mask the influence of shared environmental effects. This is a limitation of the twin design for estimating $c^2$. However, the general conclusion that shared environmental effects are negligible does not rest on twin studies alone. Adoption research also fails to find large ($c^2$) components; that is, adoptive parents and their adopted children tend to show much less resemblance to one another than the adopted child and his or her non-rearing biological parent. In studies of adoptive families with at least one biological child and one adopted child, the sibling resemblance also tends be nearly zero for the vast majority of measured traits. ^[49][48]

Similarity in twins and adoptees indicates a small role for shared environment in personality.

The figure provides an example from personality research, where twin and adoption studies converge on the conclusion of zero to small influences of shared environment on broad personality traits measured by the Multidimensional Personality Questionnaire including positive emotionality, negative emotionality, and constraint.^[50]

Given the fact that all researched behavioral traits and psychiatric disorders are heritable, biological siblings will always tend to be more similar to one another than will adopted siblings. However, for some traits, especially when measured during adolescence, adopted siblings do show some significant similarity (e.g., correlations of .20) to one another. Traits that have been demonstrated to have significant shared environmental influences include internalizing and externalizing psychopathology,^[51] substance use ^[52] and dependence, ^[37] and IQ.^[52]

Notable behavioural geneticists

Notable behavioural geneticists include Dorret Boomsma, Thomas Bouchard, Wim Crusio (the founding editor of the journal Genes, Brain and Behavior), John DeFries, Theodosius Dobzhansky, Lindon Eaves, David Fulker, Irving Gottesman, John K. Hewitt, Jerry Hirsch, Kenneth Kendler, John C. Loehlin, Nick Martin, Matt McGue, Gerald McClearn, Robert Plomin, Theodore Reich (a pioneer in psychiatric genetics), Hans van Abeelen, and Steven G. Vandenberg (the founding editor of the journal Behavior Genetics).

Journals

Behavioural geneticists are active in a variety of scientific disciplines including biology, medicine, pharmacology, psychiatry, and psychology; thus, behavioural-genetic research is published in a variety of scientific journals, including Nature, Nature Genetics, and Science. Journals that specifically publish research in behavioural genetics include Behavior Genetics, Genes, Brain and Behavior, Journal of Neurogenetics, Molecular Psychiatry, Psychiatric Genetics, and Twin Research and Human Genetics.

Societies

There exist several learned societies in the broader area of behavioural genetics:

• Behavior Genetics Association
• International Behavioural and Neural Genetics Society
• International Society of Psychiatric Genetics

See also

• Adoption study
• Behavioral epigenetics
• Behavioral neurogenetics
• Biocultural evolution
• Evolutionary psychology
• Genome-wide association study
• Human behavior genetics
• Molecular genetics
• Nature versus nurture
• Psychiatric genetics
• Quantitative genetics
• Twin study

References

1. Loehlin, JC (2009). "History of behavior genetics". In Kim, Y-K. Handbook of behavior genetics (PDF).
2. Vaughan, Virginia Mason; Vaughan, Alden T. (1999). The Tempest. The Arden Shakespeare, Third Series. The Arden Shakespeare. ISBN 978-1-903436-08-0.
3. Hereditary Genius: An Inquiry into Its Laws and Consequences. London: MacMillan and Co. 1869.
4. Stigler SM (July 2010). "Darwin, Galton and the Statistical Enlightenment". Journal of the Royal Statistical Society, Series A 173 (3): 469–482. doi:10.1111/j.1467-985X.2010.00643.x.
5. McGue, Matt; Gottesman, Irving I. (2015). "Behavior Genetics": 1–11. doi:10.1002/9781118625392.wbecp578.
6. Hall CS (1951). "The genetics of behavior". In Stevens SS. Handbook of Experimental Psychology. New York: John Wiley and Sons. pp. 304–329.
7. Grigorenko EL; Ravich-Shcherbo I (1997). "Russian psychogenetics". In Grigorenko EL. Psychology of Russia: Past, Present, Future. Commack, NY: Nova Science. pp. 83–124.
8. Broadhurst PL (July 1969). "Psychogenetics of emotionality in the rat". Annals of the New York Academy of Sciences 159 (3): 806–24. Bibcode:1969NYASA.159..806B. doi:10.1111/j.1749-6632.1969.tb12980.x. PMID 5260300.
9. Ayorech, Ziada; Selzam, Saskia; Smith-Woolley, Emily; Knopik, Valerie S.; Neiderhiser, Jenae M.; DeFries, John C.; Plomin, Robert (2016). "Publication Trends Over 55 Years of Behavioral Genetic Research". Behavior Genetics. doi:10.1007/s10519-016-9786-2. ISSN 0001-8244.
10. Fuller JL; Thompson WR (1960). Behavior Genetics. New York: John Wiley and Sons.
11. Plomin, Robert (1989). "Behavioral Genetics". Journal of Nervous and Mental Disease 177 (10): 645. doi:10.1097/00005053-198910000-00020.
12. Ehrman L (1966). "Mating success and genotype frequency in Drosophila". Animal Behaviour 14 (2): 332–9. doi:10.1016/S0003-3472(66)80093-3. PMID 5956600.
13. Ehrman L (February 1970). "Simulation of the mating advantage in mating of rare Drosophila males". Science 167 (3919): 905–6. Bibcode:1970Sci...167..905E. doi:10.1126/science.167.3919.905. PMID 5410860.
14. Ehrman L (February 1970). "The mating advantage of rare males in Drosophila". Proc. Natl. Acad. Sci. U.S.A. 65 (2): 345–8. Bibcode:1970PNAS...65..345E. doi:10.1073/pnas.65.2.345. PMC 282908. PMID 5263769.
15. Rothenbuhler WC (May 1964). "Behavior genetics of nest cleaning in honey bees. IV. Responses of F1 and backcross generations to disease-killed brood". Am. Zool. 4 (2): 111–123. doi:10.1093/icb/4.2.111. PMID 14172721.
16. Rothenbuhler WC (1958). "Genetics and breeding of the honey bee". Annual Review of Entomology 3: 161–180. doi:10.1146/annurev.en.03.010158.001113.
17. Christians JK (June 2005). "Behavioural genetics". BioEssays 27 (6): 664–666. doi:10.1002/bies.20247. PMID 15892115.
18. DeFries JC; Hegmann JP; Halcomb RA (1974). "Response to 20 generations of selection for open-field activity in mice". Behavior 11 (4): 481–485. doi:10.1016/s0091-6773(74)90800-1.
19. Lynch CB (1980). "Response to divergent selection for nesting behavior in Mus musculus". Genetics 96 (3): 757–765. PMC 1214374. PMID 7196362.
20. Swallow JG; Carter PA; Garland T, Jr. (1998). "Artificial selection for increased wheel-running behavior in house mice" (PDF). Behavior Genetics 28 (3): 227–237. doi:10.1023/A:1021479331779. PMID 9670598.
21. Jinks JL, Fulker DW (1970). "Comparison of the biometrical genetical, MAVA, and classical approaches to the analysis of the human behavior.". Psychological Bulletin 73: 311–349. doi:10.1037/h0029135.
22. Martin NG, Eaves LJ (1977). "The genetical analysis of covariance structure.". Heredity 38: 79–95. doi:10.1038/hdy.1977.9.
23. Farrel MS, Werge T, Sklar P, Owen MJ, Ophoff RA, O'Donovan MC, Corvin A, Cichon S, Sullivan PF (2015). "Evaluating historical candidate genes for schizophrenia". Molecular Psychiatry 20: 555–562. doi:10.1038/mp.2015.16.
24. Ioannidis JP, Ntzani EE, Trikalinos TA, Contopoulos-Ioannidis DG (2001). "Replication validity of genetic association studies". Nature Genetics 29: 306–309. doi:10.1038/ng749.
25. Colhoun, Helen M; McKeigue, Paul M; Smith, George Davey (2003). "Problems of reporting genetic associations with complex outcomes". The Lancet 361 (9360): 865–872. doi:10.1016/S0140-6736(03)12715-8. ISSN 0140-6736.
26. Duncan, Laramie E.; Keller, Matthew C. (2011). "A Critical Review of the First 10 Years of Candidate Gene-by-Environment Interaction Research in Psychiatry". American Journal of Psychiatry 168 (10): 1041–1049. doi:10.1176/appi.ajp.2011.11020191. ISSN 0002-953X.
27. Visscher PM, Brown MA, McCarthy MI, Yang J (2012). "Five years of GWAS discovery". American Journal of Human Genetics 90: 7–24. doi:10.1016/j.ajhg.2011.11.029.
28. Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014). "Biological insights from 108 schizophrenia-associated genetic loci". Nature 511: 421–427. doi:10.1038/nature13595.
29. Lee SH, DeCandia TR, Ripke S, Yang J, Schizophrenia Psychiatric Genome-Wide Association Study Consortium (PGC-SCZ), International Schizophrenia Consortium (ISC), Molecular Genetics of Schizophrenia Collaboration (MGS), Sullivan PF, Goddard ME, Keller MC, Visscher PM, Wray NR (2012). "Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs". Nature Genetics 44 (3): 247–250. doi:10.1038/ng.1108.
30. Sullivan PF, Daly MJ, ODonovan M (2012). "Genetic architectures of psychiatric disorders: the emerging picture and its implications". Nature Reviews Genetics 13: 537–551. doi:10.1038/nrg3240.
31. Genetics of Personality Consortium (2015). "Meta-analysis of genome-wide association studies for neuroticism, and the polygenic association with major depressive disorder". JAMA Psychiatry 72: 642–650. doi:10.1001/jamapsychiatry.2015.0554.
32. Yang, Jian; Benyamin, Beben; McEvoy, Brian P; Gordon, Scott; Henders, Anjali K; Nyholt, Dale R; Madden, Pamela A; Heath, Andrew C; Martin, Nicholas G; Montgomery, Grant W; Goddard, Michael E; Visscher, Peter M (2010). "Common SNPs explain a large proportion of the heritability for human height". Nature Genetics 42 (7): 565–569. doi:10.1038/ng.608. ISSN 1061-4036.
33. Yang, Jian; Lee, S. Hong; Goddard, Michael E.; Visscher, Peter M. (2011). "GCTA: A Tool for Genome-wide Complex Trait Analysis". The American Journal of Human Genetics 88 (1): 76–82. doi:10.1016/j.ajhg.2010.11.011. ISSN 0002-9297.
34. Rutter, Michael (2007). "Proceeding From Observed Correlation to Causal Inference: The Use of Natural Experiments". Perspectives on Psychological Science 2 (4): 377–395. doi:10.1111/j.1745-6916.2007.00050.x. ISSN 1745-6916.
35. Kendler, Kenneth S.; Baker, Jessica H. (2006). "Genetic influences on measures of the environment: a systematic review". Psychological Medicine 37 (05): 615. doi:10.1017/S0033291706009524. ISSN 0033-2917.
36. Keyes, Margaret; Legrand, Lisa N.; Iacono, William G.; McGue, Matt (2008). "Parental Smoking and Adolescent Problem Behavior: An Adoption Study of General and Specific Effects". American Journal of Psychiatry 165 (10): 1338–1344. doi:10.1176/appi.ajp.2008.08010125. ISSN 0002-953X.
37. Kendler, Kenneth S.; Sundquist, Kristina; Ohlsson, Henrik; Palmér, Karolina; Maes, Hermine; Winkleby, Marilyn A.; Sundquist, Jan (2012). "Genetic and Familial Environmental Influences on the Risk for Drug Abuse". Archives of General Psychiatry 69 (7). doi:10.1001/archgenpsychiatry.2011.2112. ISSN 0003-990X.
38. McGue, M.; Osler, M.; Christensen, K. (2010). "Causal Inference and Observational Research: The Utility of Twins". Perspectives on Psychological Science 5 (5): 546–556. doi:10.1177/1745691610383511. ISSN 1745-6916.
39. D'Onofrio, Brian M.; Turkheimer, Eric N.; Eaves, Lindon J.; Corey, Linda A.; Berg, Kare; Solaas, Marit H.; Emery, Robert E. (2003). "The role of the Children of Twins design in elucidating causal relations between parent characteristics and child outcomes". Journal of Child Psychology and Psychiatry 44 (8): 1130–1144. doi:10.1111/1469-7610.00196. ISSN 0021-9630.
40. Smith, G. D. (2004). "Mendelian randomization: prospects, potentials, and limitations". International Journal of Epidemiology 33 (1): 30–42. doi:10.1093/ije/dyh132. ISSN 1464-3685.
41. Plomin R, DeFries JC, Knopik VS, Neiderhiser JM (2016). "Top 10 replicated findings from Behavioral Genetics". Perspectives on Psychological Science 11 (1): 3–23. doi:10.1177/1745691615617439.
42. Polderman JC, Benyamin B, de Leeuw Christiaan A, Sullivan PF, van Bochoven A, Visscher PM, Posthuma D (2015). "Meta-analysis of the heritability of human traits based on fifty years of twin studies". Nature Genetics 47: 702–709. doi:10.1038/ng.3285.
43. Turkheimer E (2000). "Three Laws of Behavior Genetics and What They Mean" (PDF). Current Directions in Psychological Science 9: 160–164. doi:10.1111/1467-8721.00084.
44. Bouchard TJ Jr, Lykken DT, McGue M, Segal NL, Tellegen A (1990). "Sources of human psychological differences: the Minnesota Study of Twins Reared Apart". Science 250 (4978): 223–228. doi:10.1126/science.2218526.
45. de Moor, Marleen H. M.; van den Berg, Stéphanie M.; Verweij, Karin J. H.; Krueger, Robert F.; Luciano, Michelle; Arias Vasquez, Alejandro; Matteson, Lindsay K.; Derringer, Jaime; Esko, Tõnu; Amin, Najaf; Gordon, Scott D.; Hansell, Narelle K.; Hart, Amy B.; Seppälä, Ilkka; Huffman, Jennifer E.; Konte, Bettina; Lahti, Jari; Lee, Minyoung; Miller, Mike; Nutile, Teresa; Tanaka, Toshiko; Teumer, Alexander; Viktorin, Alexander; Wedenoja, Juho; Abecasis, Goncalo R.; Adkins, Daniel E.; Agrawal, Arpana; Allik, Jüri; Appel, Katja; Bigdeli, Timothy B.; Busonero, Fabio; Campbell, Harry; Costa, Paul T.; Davey Smith, George; Davies, Gail; de Wit, Harriet; Ding, Jun; Engelhardt, Barbara E.; Eriksson, Johan G.; Fedko, Iryna O.; Ferrucci, Luigi; Franke, Barbara; Giegling, Ina; Grucza, Richard; Hartmann, Annette M.; Heath, Andrew C.; Heinonen, Kati; Henders, Anjali K.; Homuth, Georg; Hottenga, Jouke-Jan; Iacono, William G.; Janzing, Joost; Jokela, Markus; Karlsson, Robert; Kemp, John P.; Kirkpatrick, Matthew G.; Latvala, Antti; Lehtimäki, Terho; Liewald, David C.; Madden, Pamela A. F.; Magri, Chiara; Magnusson, Patrik K. E.; Marten, Jonathan; Maschio, Andrea; Medland, Sarah E.; Mihailov, Evelin; Milaneschi, Yuri; Montgomery, Grant W.; Nauck, Matthias; Ouwens, Klaasjan G.; Palotie, Aarno; Pettersson, Erik; Polasek, Ozren; Qian, Yong; Pulkki-Råback, Laura; Raitakari, Olli T.; Realo, Anu; Rose, Richard J.; Ruggiero, Daniela; Schmidt, Carsten O.; Slutske, Wendy S.; Sorice, Rossella; Starr, John M.; St Pourcain, Beate; Sutin, Angelina R.; Timpson, Nicholas J.; Trochet, Holly; Vermeulen, Sita; Vuoksimaa, Eero; Widen, Elisabeth; Wouda, Jasper; Wright, Margaret J.; Zgaga, Lina; Porteous, David; Minelli, Alessandra; Palmer, Abraham A.; Rujescu, Dan; Ciullo, Marina; Hayward, Caroline; Rudan, Igor; Metspalu, Andres; Kaprio, Jaakko; Deary, Ian J.; Räikkönen, Katri; Wilson, James F.; Keltikangas-Järvinen, Liisa; Bierut, Laura J.; Hettema, John M.; Grabe, Hans J.; van Duijn, Cornelia M.; Evans, David M.; Schlessinger, David; Pedersen, Nancy L.; Terracciano, Antonio; McGue, Matt; Penninx, Brenda W. J. H.; Martin, Nicholas G.; Boomsma, Dorret I. (2015). "Meta-analysis of Genome-wide Association Studies for Neuroticism, and the Polygenic Association With Major Depressive Disorder". JAMA Psychiatry 72 (7): 642. doi:10.1001/jamapsychiatry.2015.0554. ISSN 2168-622X.
46. Lee, S Hong; DeCandia, Teresa R; Ripke, Stephan; Yang, Jian; Sullivan, Patrick F; Goddard, Michael E; Keller, Matthew C; Visscher, Peter M; Wray, Naomi R (2012). "Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs". Nature Genetics 44 (3): 247–250. doi:10.1038/ng.1108. ISSN 1061-4036.
47. Plomin, R.; Haworth, C. M. A.; Meaburn, E. L.; Price, T. S.; Davis, O. S. P. (2013). "Common DNA Markers Can Account for More Than Half of the Genetic Influence on Cognitive Abilities". Psychological Science 24 (4): 562–568. doi:10.1177/0956797612457952. ISSN 0956-7976.
48. Polderman, Tinca J C; Benyamin, Beben; de Leeuw, Christiaan A; Sullivan, Patrick F; van Bochoven, Arjen; Visscher, Peter M; Posthuma, Danielle (2015). "Meta-analysis of the heritability of human traits based on fifty years of twin studies". Nature Genetics 47 (7): 702–709. doi:10.1038/ng.3285. ISSN 1061-4036.
49. Plomin, R.; Daniels, D. (2011). "Why are children in the same family so different from one another?". International Journal of Epidemiology 40 (3): 563–582. doi:10.1093/ije/dyq148. ISSN 0300-5771.
50. Matteson, Lindsay K.; McGue, Matt; Iacono, William G. (2013). "Shared Environmental Influences on Personality: A Combined Twin and Adoption Approach". Behavior Genetics 43 (6): 491–504. doi:10.1007/s10519-013-9616-8. ISSN 0001-8244.
51. Burt, S. Alexandra (2009). "Rethinking environmental contributions to child and adolescent psychopathology: A meta-analysis of shared environmental influences.". Psychological Bulletin 135 (4): 608–637. doi:10.1037/a0015702. ISSN 1939-1455.
52. Buchanan, Jacob P.; McGue, Matt; Keyes, Margaret; Iacono, William G. (2009). "Are there Shared Environmental Influences on Adolescent behavior? Evidence from a Study of Adoptive Siblings". Behavior Genetics 39 (5): 532–540. doi:10.1007/s10519-009-9283-y. ISSN 0001-8244.

Further reading

• Plomin, R.; DeFries, J. C.; Knopik, V. S.; Neiderhiser, J. M. (2016). "Top 10 Replicated Findings From Behavioral Genetics". Perspectives on Psychological Science 11 (1): 3–23. doi:10.1177/1745691615617439. ISSN 1745-6916.
• Crusio, Wim E. (2015). "Key issues in contemporary behavioral genetics". Current Opinion in Behavioral Sciences 2: 89. doi:10.1016/j.cobeha.2014.10.002.
• Crusio, W. E.; Gerlai, R. T., eds. (1999). Handbook of Molecular-Genetic Techniques for Brain and Behavior Research. Techniques in the Behavioral and Neural Sciences 13. Elsevier. ISBN 978-0-444-50239-1.
• Crusio, Wim E.; Sluyter, Frans; Gerlai, Robert T.; Pietropaolo, Susanna, eds. (2013). Behavioral Genetics of the Mouse: Genetics of Behavioral Phenotypes. Cambridge Handbooks in Behavioral Genetics 1. Cambridge University Press. ISBN 978-1-107-03481-5.
• Flint, Jonathan; Greenspan, Ralph J.; Kendler, Kenneth S. (28 January 2010). How Genes Influence Behavior. Oxford University Press. ISBN 978-0-19-955990-9. Lay summary (20 November 2013).
• Johnson, Wendy; Turkheimer, E.; Gottesman, Irving; Bouchard, Thomas (2009). "Beyond Heritability: Twin Studies in Behavioral Research" (PDF). Current Directions in Psychological Science 18 (4): 217–220. doi:10.1111/j.1467-8721.2009.01639.x. PMC 2899491. PMID 20625474. Retrieved 21 November 2010.
• Johnson, Wendy; Penke, Lars; Spinath, Frank M. (2011). "Understanding Heritability: What it is and What it is Not" (PDF). European Journal of Personality 25 (4): 287–294. doi:10.1002/per.835. ISSN 0890-2070. Retrieved 15 December 2013.
• Maxson, Stephen C. (10 October 2012). "Chapter 1: Behavioral Genetics". In Weiner, Irving B.; Nelson, Randy J.; Mizumori, Sheri. Handbook of Psychology (PDF). Volume 3: Behavioral Neuroscience. John Wiley & Sons. ISBN 978-0-470-89059-2. Archived from the original on 2013. Retrieved 15 December 2013.
• Panofsky, Aaron (2014). Misbehaving Science. Controversy and the Development of Behavior Genetics. Chicago: University of Chicago Press. ISBN 978-0-226-05831-3.
• Plomin, Robert; DeFries, John C.; Knopik, Valerie S.; Jenae M. Neiderhiser (24 September 2012). Behavioral Genetics. Shaun Purcell (Appendix: Statistical Methods in Behaviorial Genetics). Worth Publishers. ISBN 978-1-4292-4215-8. Retrieved 4 September 2013. Lay summary (4 September 2013).
• Spinath, Frank M.; Johnson, Wendy (2011). "Chapter 10: Behavior Genetics". In Chamorro-Premuzic, Tomas; von Stumm, Sophie; Furnham, Adrian. The Wiley-Blackwell Handbook of Individual Differences. United Kingdom: Blackwell Publishing Ltd. doi:10.1002/9781444343120. ISBN 978-1-4443-3438-8. Lay summary (10 July 2013).

External links

• McGue, Matt (5 May 2014). "Introduction to Human Behavioral Genetics". Coursera. Retrieved 10 June 2014. Free Massively Open Online Course on human behaviour genetics
• Institute for Behavioral Genetics at the University of Colorado Boulder