Is the Child Father of the Man[1].PDF Obligatoriu

DEVELOPMENTAL SCIENCE REVIEW

Is the child ‘father of the Man’? Evaluating the stability of geneticinfluences across development

Angelica Ronald

Centre for Brain and Cognitive Development, Department of Psychological Sciences, Birkbeck, UK

Abstract

This selective review considers findings in genetic research that have shed light on how genes operate across development. We willaddress the question of whether the child is ‘father of the Man’ from a genetic perspective. In other words, do the same geneticinfluences affect the same traits across development? Using a ‘taster menu’ approach and prioritizing newer findings on cognitiveand behavioral traits, examples from the following genetic disciplines will be discussed: (a) developmental quantitative genetics(such as longitudinal twin studies), (b) neurodevelopmental genetic syndromes with known genetic causes (such as Williamssyndrome), (c) developmental candidate gene studies (such as those that link infant and adult populations), (d) developmentalgenome-wide association studies (GWAS), and (e) DNA resequencing. Evidence presented here suggests that there isconsiderable genetic stability of cognitive and behavioral traits across development, but there is also evidence for genetic change.Quantitative genetic studies have a long history of assessing genetic continuity and change across development. It is now time forthe newer, more technology-enabled fields such as GWAS and DNA resequencing also to take on board the dynamic nature ofhuman behavior.

Introduction

The quotation referred to in the title of this paper, ‘TheChild is father of the Man’, from a poem by WilliamWordsworth (1770–1850), is interpreted by somescholars to say that our early life shapes whom webecome as adults. We now know that early life isinfluenced by both our genes and our environmentalexperiences. In this selective review, evidence for thestability of genetic influences on early and later devel-opment will be considered. To what extent is the child‘father of the Man’ in terms of genetic influences? It isimportant to note that the review focuses on common,complex cognitive and behavioral traits, on which it isbelieved that genetic influences act probabilisticallyrather than deterministically. In other words, to whatextent do the same (probabilistically acting) genesinfluence similar kinds of individual differences in infancy,childhood, adolescence and adulthood? Without denyingthe importance of environmental influences, they areoutside the scope of this review, and the reader isdirected elsewhere for informative reviews on the pro-cesses that could underlie gene–environment interac-tion, including epigenetics and gene expression(Gottlieb, 2007; Kan, Ploeger, Raijmakers, Dolan & vander Maas, 2010; Plomin & Schalkwyk, 2007; Rutter,2007; Westermann, Mareschal, Johnson, Sirois, Sprat-ling & Thomas, 2007).

Why is this question important? First, it has been oflong-standing interest to understand what causes indi-vidual differences in human behavior. Development iscentral to human behavior and as such exploring thecauses of age-to-age change as well as continuity is anintrinsic part of understanding individual differences.Second, prevention is now a key priority in medicalresearch (Sahakian, Malloch & Kennard, 2010). It iscritical to know not just which genes are associated witha complex disease or disorder, but which genes areassociated with the pre-disease, at-risk, prodromal state.Pre-disease, at-risk states are better targets for preventionthan the disease once it has started. In this vein, infantsat risk of (nonsyndromic) autism spectrum conditionsare now the focus of much research, for example(Elsabbagh & Johnson, 2010; Noland, Steven Reznick,Stone, Walden & Sheridan, 2010; Young, Merin, Rogers& Ozonoff, 2009). An understanding of how geneticinfluences operate across developmental time wouldconstitute an important knowledge base from which todevelop preventative strategies for heritable but notgenetically predetermined cognitive or behaviourally de-fined disorders.

Using a ‘taster menu’ approach, that is, picking par-ticular examples from the field and prioritizing newerfindings, examples from the following genetic disciplineswill be discussed: (a) developmental quantitative genetics,(b) neurodevelopmental genetic syndromes with a known

Address for correspondence: Angelica Ronald, Centre for Brain and Cognitive Development, Department of Psychological Sciences, Birkbeck,London WC1E 7XH, UK; e-mail: [email protected]

� 2011 Blackwell Publishing Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA.

Developmental Science 14:6 (2011), pp 1471–1478 DOI: 10.1111/j.1467-7687.2011.01114.x

genetic cause, (c) developmental candidate gene studies,(d) developmental genome-wide association studies, and(e) DNA resequencing. The review focuses on findingsthat relate to genetic influences on the development ofcognitive and behavioral traits.

Developmental quantitative genetics

Quantitative genetics is the investigation of genetic andenvironmental influences on complex traits and disorders(Plomin, DeFries, McClearn & McGuffin, 2008). Theclassic twin design is one of the main methods employedin quantitative genetics; it involves the comparison of thewithin-pair similarity of identical (or monozygotic) andfraternal (or dizygotic) twins. The twin design is equallyinformative about environmental influences as aboutgenetics, but here we will focus on the genetic findingsfrom twin studies.

The twin design is a particularly useful tool forstudying development. Longitudinal studies of identicaland fraternal twins studied at multiple ages can beinformative about genetic continuity – the degree towhich genetic influences on a trait or disease are stableacross ages – as well as about two types of geneticchange, genetic innovation – the degree to which newgenetic influences are present at later ages – and geneticattenuation – the degree to which genetic influencespresent at earlier ages decline in influence at later ages(Kendler, Gardner, Annas, Neale, Eaves & Lichtenstein,2008).

The basis of a longitudinal twin analysis is to comparethe degree to which one twin’s trait score at the earlierage correlates with their co-twin’s trait score at the laterage (called a cross-age cross-twin correlation), separatelyfor identical and fraternal twins. If identical twins show agreater cross-age cross-twin correlation than fraternaltwins, this suggests that the same genetic influences areoperating on the trait across development. The modelcan also estimate if there are different genetic effects onthe trait at different ages. A cross-age genetic correlation(rg) is a direct estimate derived from twin models of thedegree of shared genetic influences across ages. Thisgenetic correlation can vary from 0, indicating thatcompletely different genetic influences play a role at twoages, to 1, indicating complete overlap in genetic influ-ences at two ages.

In terms of cognitive development, a recent examplecomes from a study of 8700 twin pairs who were assessedfrom age 2 to age 10 years on their cognitive abilities.Across this 8-year age range spanning early to middlechildhood, the authors found considerable stability ingenetic influences (cross-age rg = 0.57) but also signifi-cant change (Davis, Haworth & Plomin, 2009). A secondrecent twin study of cognitive development employedtwo complementary twin cohorts who were assessed atdifferent ages on verbal abilities (Hoekstra, Bartels, vanLeeuwen & Boomsma, 2009). They showed that verbal

abilities have a similar genetic architecture in childhood(9-year-olds) and late adolescence (18-year-olds), that is,the degree of genetic overlap between different subdo-mains of verbal ability was similar across the two ages.This careful matching of independent twin samples,while not providing a direct estimate of the degree towhich the same genetic influences are operating at thetwo ages (because cross-age rg cannot be estimated fromtwo independent samples), allowed the authors to makeconclusions about similarity in the genetic architecture ofdiverse verbal abilities across ages, without the costly andtime-consuming effort of following up the same cohortacross a 9-year interval.

In research on behavioral development, twin studieshave been conducted from childhood to adulthood. Forexample, a large twin study of parent- and self-reportedfears, a common form of anxiety, was conducted on asample assessed from age 8 years to age 20 years. Theyfound modest evidence for genetic stability and consid-erable evidence for both genetic innovation and geneticattenuation from age 8 to age 20. The authors concludedthat their results mostly supported ‘the ‘‘developmentallydynamic’’ hypothesis [which] predicts that genetic effectson fear-proneness will vary over time’ (Kendler et al.,2008, p. 2; emphasis added).

In contrast, a longitudinal twin study of self-ratedprosocial behavior in adolescence reported considerablegenetic stability (albeit across a much briefer develop-mental gap than the above study of fears). The sampleranged in age between 13 and 17 years old (at the firstassessment) and was assessed again 17 months later. Theauthors reported significant genetic continuity on pro-social behaviors across the two waves of data collectionwith a high genetic correlation (rg = 0.64) (Gregory,Light-Hausermann, Rijsdijk & Eley, 2009).

Turning to the first years of life, Gagne and Goldsmith(2011) recently assessed anger and later inhibitory con-trol in twins at 12 and 36 months old. They reported thatindividual differences in anger showed considerablegenetic stability from ages 12 to 36 months old(rg = 0.52), and anger at 12 months old also showedgenetic overlap with later parent-rated inhibitory controlat 36 months of age (rg = )0.26) (Gagne & Goldsmith,2011). However, their findings were specific to parentreport measures: they did not replicate these findingswith their lab-based assessments of anger and inhibitorycontrol. It is relevant to note that different measurementmethods, such as actigraph versus parent-rated assess-ments of activity (Saudino, 2009) or parent- versus tea-cher- versus self-reports of psychopathology, for example(Ronald, Happ� & Plomin, 2008; Stevenson, Asherson,Hay, Levy, Swanson, Thapar & Willcutt, 2005), haveboth been shown to pick up on slightly different geneticinfluences and, as such, measurement method alwaysneeds to be taken into account when assessing findingsregarding genetic influences on development.

Longitudinal twin studies can also explore geneticstability and change on the comorbidity between two

1472 Angelica Ronald

� 2011 Blackwell Publishing Ltd.

traits or disorders across development. Recent examplesof this are studies on the longitudinal etiological rela-tionship between autistic traits and anxiety-relatedbehaviors (Hallett, Ronald, Rijsdijk & Happ�, 2010) andthe longitudinal etiological relationship between autistictraits, and intelligence and verbal ability (Dworzynski,Ronald, Hayiou-Thomas,, McEwen, Happ�, Bolton &Plomin, 2008; Hoekstra, Happ�, Baron-Cohen & Ron-ald, 2010). As such, these studies demonstrate to whatdegree the same genetic influences on one trait or dis-order at an earlier age are also involved in a related traitor disorder at a later age.

In sum, evidence from developmental quantitativegenetics suggests that the answer to the question in thetitle of this paper, ‘Is the child "father of the Man''?’, is apartial yes. The above examples demonstrate thatcognitive and behavioral development show significantgenetic influences that are stable across development.The answer is only a ‘partial yes’ because it is notablethat all the studies discussed above also reported a degreeof change in genetic influence. One limitation worthy ofnote is that longitudinal twin studies that span bothchildhood and adulthood are relatively rare due to theextensive research effort and time that they inevitablyrequire (several decades of research and funding).

Neurodevelopmental genetic syndromes

The study of neurodevelopmental genetic syndromeswith a known genetic cause has been realized to be apowerful tool for understanding how genetic influencesoperate across development (e.g. Paterson, Brown,Gsodl, Johnson & Karmiloff-Smith, 1999) (in addition,of course, to the important goal of understanding theseconditions in their own right). Because the genetic causeof the condition is known, the developmental phenotypecan be associated with a specific change in the genome.Furthermore, because individuals with these conditionscan be diagnosed and studied prospectively from infancyonwards, this provides greater scope to study develop-ment than in multifactorial conditions where diagnosisonly occurs at a later age, and as such the infancy ⁄ earlychildhood developmental window is often missed orpoorly understood. Developmentalists have placedemphasis on the need to understand genetic effects onthe developing infant brain, which is very different fromthe adult brain in terms of degree of specialization andlocalization (Karmiloff-Smith, 2007).

Williams syndrome will be discussed here as anexample of how a known genetic developmental syn-drome can inform us about genetic influences acrossdevelopment. Williams syndrome involves a knowngenetic microdeletion on the long arm of chromosome 7affecting as many as 28 genes and occurs in 1 in 15,000live births. The Williams syndrome phenotype involves aspecific physical, behavioral and cognitive profile (Don-nai & Karmiloff-Smith, 2000). Behavioral features

include a strong preference for faces and inappropriatefriendliness to strangers. Notable cognitive features in-clude an IQ of approximately 60 with higher verbalcompared to visuo-spatial abilities and serious numericaldifficulties. Individuals with Williams syndrome havesome atypical visuo-spatial abilities such as difficultieswith visual search in toddlerhood (Scerif, Cornish, Wil-ding, Driver & Karmiloff-Smith, 2004), impairmentswith identifying spatial relationships between landmarksin older childhood (Farran, Blades, Boucher & Tranter,2010) and difficulties with multiple object tracking inchildhood and adulthood (O’Hearn, Hoffman & Lan-dau, 2010).

An example of research on Williams syndrome thathas considered how the phenotype varies across thewhole of development is work on number processing.Studies have demonstrated that individuals with Wil-liams syndrome show atypical large number processingboth in infancy, as measured using an experimentalobservational task to test small versus large numberdiscrimination (Van Herwegen, Ansari, Xu & Karmiloff-Smith, 2008), and numerical impairments in later child-hood and early adulthood as assessed using arithmeticassessments (Udwin, Davies & Howlin, 1996).

A second example of how the Williams syndromephenotype has been investigated across development is astudy on the personality and behavior profile of Williamssyndrome individuals (Gosch & Pankau, 1997). Indi-viduals with Williams syndrome have a distinctive profileof personality characteristics. Gosch and Pankau’s(1997) study included three groups of individuals withWilliams syndrome: under 10-year-olds, 10–20-year-olds,and over 20-year-olds. While some personality measures,such as over-friendliness, showed a lower mean score inthe adolescent and adult Williams syndrome groupscompared to the under 10-year-old group (that is, scoresbecame closer to general population averages), scoreswere still higher than population means. Overall theauthors concluded that the characteristic personalityprofile of individuals with Williams syndrome was stablefrom childhood to adulthood.

In answer to the question in the title of this paper, ‘Isthe child "father of the Man''?’, findings from research onWilliams syndrome suggest that the answer is yes to theextent that there appears to be relative consistency in thephenotype profile across the lifespan in this neurodevel-opmental syndrome with a known genetic cause.Although known genetic syndromes are a different ge-netic 'model' to that of multiple probabilistically actinggenes on common traits, they are informative about theeffects of variation in the genome on development.However, there is the consideration of to what degreefindings from specific neurodevelopmental genetic syn-dromes with a known genetic cause generalize tounderstanding the genetic influences on cognitive andbehavioral traits in the general population. On a prac-tical level, samples tend to be small and heterogeneous,they only directly inform us about the specific area of the

Genetics and development 1473


genome in which the mutation has occurred, and devel-opmental fluctuation in environmental influences is notusually included within the study designs, although cross-cultural studies have been conducted (see Zitzer-Com-fort, Doyle, Masataka, Korenberg & Bellugi, 2007, for anexample). In the next section, candidate gene studies ofinfant and adult samples demonstrate how typicallydeveloping samples can be used to test the degree ofgenetic continuity across the lifespan.

Developmental candidate gene associationstudies

Candidate gene studies involve testing for an associationbetween a trait or disease of interest and a known can-didate gene. The known candidate gene might be selectedbecause it is ‘biologically plausible’ in that it codes for aprotein that is hypothesized to have a role in the phe-notype’s causal pathway, or selected on the basis ofgenomic position (e.g. from linkage studies).

Candidate genes that play a role in the dopamine andserotonin neurotransmitter pathways have been selectedas biologically plausible for many cognitive and behav-ioral traits (Hirschhorn, Lohmueller, Byrne & Hirsch-horn, 2002). These candidate gene studies can inform usabout genetic influences on development becauseassociations between phenotypic variation and specificgenetic variation can be explored at different ages. Toillustrate this, some recent studies are highlighted thathave tested whether genes that play a role in the dopa-mine and serotonin neurotransmitter pathways areassociated with similar behavioral phenotypes in infancyas well as later life.

Genetic variation in a region of a gene that encodestryptophan hydroxylase isoform 2 (TPH2) is thought tomodify gene expression in such a way as to alter sero-tonin concentrations in neurons in the brain. In adults,variation in this gene region has been associated withattention regulation and cognitive control (e.g. Strobel,Dreisbach, Muller, Goschke, Brocke & Lesch, 2007). In arecent study, the same genetic variation (a greater num-ber of T alleles) that is associated with poorer perfor-mance on attentional tasks in adults was associated witha higher number of missing attention shifts in 7-month-old infants in an experimental paradigm that tested forefficiency of attentional shifts (Leppanen, Peltola, Puura,Mantymaa, Mononen & Lehtimaki, 2011). These studiesappear to suggest that the same genetic variation influ-ences attentional processes in infancy and adulthood.

The monoamine oxidase A (MAOA) gene codes for acatabolic enzyme that is involved in regulating the deg-radation of serotonin and dopamine and as such isconsidered another biologically plausible candidate genefor cognitive and behavioral traits. Variation in theMAOA gene has been associated with impulsivity andaggressive behavior in adults (e.g. Brunner, Nelen,Breakefield, Ropers & van Oost, 1993). In a recent study,

6-month-old infants were assessed for their self-regula-tion in the lab by observing the degree to which theyoriented away from a threatening event (the presentationof a large toy chimpanzee). The authors concluded fromthis first study of MAOA in infancy that a commonfunctional MAOA variable number tandem repeat(MAOA-uVNTR) was associated with variation in self-regulatory behavior (the more active genotype, 4 ⁄ 4, wasassociated with higher regulation), although the associ-ation was only found in girls and not boys (Zhang, Chen,Way, Yoshikawa, Deng, Ke, Yu, Chen, He, Chi & Lu,2011).

A third example is a recent study of dopamine systemgenes in infancy. The catechol-O-methyltransferase(COMT) gene codes for an enzyme which is involved inthe metabolic degradation of dopamine. The COMTVal158 Met polymorphism has been associated with effi-ciency of function in prefrontal cortex in school-agechildren (Diamond, Briand, Fossella & Gehlbach, 2004)and adults (Mier, Kirsch & Meyer-Lindenberg, 2009).One of the key findings in a recent study of infants wasthat variation in the COMT Val158 Met polymorphismwas associated with degree of distractibility on the‘Freeze-Frame’ task, a task specifically designed to assessattention and frontal cortex functioning, in 9-month-oldinfants (Holmboe, Nemoda, Fearon, Csibra, Sasvari-Szekely & Johnson, 2010) (although variants in othercandidate genes, such as the DRD4 48-bp VNTR, didnot show an association with performance on this task).Thus several recent studies suggest that there is somecontinuity in the genotype–phenotype associations foundin infancy, childhood and adulthood.

Finally, two studies from a Dutch longitudinal sampleassessed from childhood through to adolescence testedwhether several serotonin and dopamine system-relatedgenes, including TPH2 and genes encoding serotonintransporters, were associated with longitudinal measuresof attention problems, and anxiety and depression,respectively (Middeldorp, Slof-Op't Landt, Medland, vanBeijsterveldt, Bartels, Willemsen, Hottenga, de Geus,Suchiman, Dolan, Neale, Slagboom & Boomsma, 2010;van Beijsterveldt, Middeldorp, Slof-Op't Landt, Bartels,Hottenga, Suchiman, Slagboom & Boomsma, 2011).Perhaps surprisingly, however, these longitudinal behav-ioral traits did not show an association with the selectedcandidate genes.

The answer to the question ‘is the child "father of theMan''?’ appears to be yes to some extent from theexample candidate gene association findings on dopa-mine and serotonin system genes mentioned above.There is some evidence for the same genotype–phenotypeassociations emerging from infancy, childhood andadulthood. These candidate gene association studies areperhaps the most direct, if restricted, examples of geneticstability across development because they take one ge-netic variant and one phenotype and test for theirassociation at two age ranges, e.g. in infancy and adult-hood. They are by default limited to the phenotype, the



age groups, and the restricted amount of genetic varia-tion on which they focus. These studies ignore the rest ofthe genome, environmental variation and other pheno-types. It has been argued, in the field of attentionalprocesses for example, that research needs to be carriedout on ‘gene · environment · time interactions acrossdomains’ (Scerif, 2010, p. 811, emphasis added; see alsoPosner, Rothbart & Sheese, 2007). This is an admirablealbeit ambitious goal. Candidate gene association studiesoffer a starting place for investigating main effects onbiologically plausible genetic associations.

The most pertinent limitation to candidate gene stud-ies is that the significant findings have proved difficult toreplicate. The reason for this could be that the gene effectsizes were smaller than predicted and so studies wereunderpowered to replicate them, but there are otherpossible reasons (Hirschhorn et al., 2002; Plomin, inpress). As reviewed in the next sections, GWAS andDNA resequencing offer more comprehensive and sys-tematic methods for finding replicable genetic associa-tions across development.

Developmental genome-wide associationstudies

‘Genome-wide’ association studies (GWAS) involvesimultaneously testing for associations between hundredsof thousands of common variants, that is, variants withminor allele frequencies greater than 1%, spread acrossthe entire genome (in contrast to looking at a single‘candidate’ gene) with a trait or disorder. This design hasbeen made possible by the arrival of microarrays (Plomin& Schalkwyk, 2007). GWAS are more systematic thancandidate gene studies because if a microarray with goodcoverage of the genome is used, most of the commonvariation in the genome will be measured.

GWAS of individual phenotypes have struggled to findgenetic variants associated with cognitive and behavioralphenotypes, a phenomenon named the ‘missing herita-bility’ problem in the GWAS field at large (Manolio,Collins, Cox, Goldstein, Hindorff, Hunter et al., 2009).An exemplar comes from GWAS of ADHD. ADHD isone of the most highly heritable behaviorally defineddisorders, yet a recent and well-designed study, and fur-ther meta-analysis, reported no genome-wide significantgenetic associations (Neale, Medland, Ripke, Anney,Asherson, Buitelaar et al., 2010a; Neale, Medland, Ripke,Asherson, Franke, Lesch et al., 2010b).

Could the success of GWAS be improved by incor-porating findings from quantitative genetics? An exam-ple of how findings from quantitative genetics have fedinto the design of GWAS comes from research on autistictraits. Twin studies have shown that social autistic traitsand restricted repetitive behaviors and interests (RRBIs,also called non-social autistic traits) are both types ofautistic symptoms that show high heritability but appearto have largely distinct genetic and environmental influ-

ences in middle childhood (Happ� & Ronald, 2008;Ronald, Happ�, Bolton, Butcher, Price, Wheelwright,Baron-Cohen & Plomin, 2006; Ronald, Happ� & Plomin,2005). On the basis of this finding of a lack of geneticoverlap between social and RRBI autistic traits, the firstGWA study of autistic traits was conducted separatelyfor social and non-social autistic traits (Ronald, Butcher,Docherty, Davis, Schalkwyk, Craig & Plomin, 2010).

However, quantitative genetic research findingsregarding genetic stability and change do not appear tohave fed into GWA study designs. At the time of writing,and based on searches in Pubmed and http://www.ge-nome.gov/gwastudies/, there appeared to be no GWASon cognitive or behavioral development that employed alongitudinal repeated measures phenotype. This isdespite many developmental twin studies reportingevidence for some genetic change across development, asdemonstrated in the Developmental quantitative geneticssection above. A prescient study 6 years ago took fivesingle nucleotide polymorphisms (SNPs) that had beenidentified as associated with cognitive ability at age 7 andcombined them into an SNP set composite to test forassociation with cognitive ability in earlier childhood(Harlaar, Butcher, Meaburn, Sham, Craig & Plomin,2005). However, to the author’s knowledge, no full-scaleGWAS of cognitive or behavioral traits have tested suchdevelopmental hypotheses.

In research on health-related phenotypes, GWAS havebegun to incorporate longitudinal data; for example,there has been a longitudinal GWA study of cardiovas-cular disease risk factors (Smith, Chen, Kahonen, Kett-unen, Lehtimaki, Peltonen et al., 2010). The authors’conclusions are also relevant to the field of cognitive andbehavioral traits: ‘longitudinal studies may be a useful toolto better capture time-dependent variation that couldultimately be [more] predictive of future outcomes’ (Smithet al., 2010, p. 6; emphasis added).

Is the reason for the lack of significant associations inmany GWAS of cognitive or behavioral traits due totheir reliance on cross-sectional data that do notcapture all the ‘time-dependent’ genetic variation? Thisremains a possibility, although clearly it is unlikely to bethe only reason (see Manolio et al., 2009, and Plomin,in press, for a discussion of other potential reasons forthe lack of significant findings). With regard to theADHD GWAS mentioned above (Neale et al., 2010a;Neale et al., 2010b), the ADHD diagnosis is thought tobe moderately stable. A developmental quantitative ge-netic twin study reported genetic correlations betweenADHD traits of between 0.32 and 0.62 from age 2 toage 8. These results on ADHD traits suggest consid-erable genetic stability but also some genetic changeacross childhood (Kuntsi, Rijsdijk, Ronald, Asherson &Plomin, 2005) which could be taken into account infuture GWAS of ADHD traits. Future GWAS of cog-nitive or behavioral traits and disorders could benefitfrom assessing whether the trait being studied showsgenetic change across ages, as Smith et al. described, ‘to



better capture time-dependent [genetic] variation’ (2010,p. 6; emphasis added).

In answer to the question ‘Is the child "father ofthe Man''?’, developmental GWAS of cognitive andbehavioral traits have not yet attempted to answer this.The GWAS field is struggling with the problem ofmissing heritability and the focus at present is onobtaining larger samples to detect small genetic effects(Manolio et al., 2009). Here we highlight another con-sideration for the design of GWAS, which is the potentialvalue of longitudinal data for phenotypes that areinfluenced by partly different sets of genes across devel-opment. Capturing more of the genetic variation actingacross development might not help with the small effectsize issue but it would help to provide a more accuratemeasure of the genetic variation that influences a traitacross ages. A suggested rule of thumb for designingGWAS that will capture maximum cross-age geneticvariation could be that if the genetic correlation betweenany two ages is greater than 0.5, researchers can justifyusing data from a single age because they know that aconsiderable amount of genetic variation is the sameacross the two ages. If the genetic correlation is less than0.5, researchers should endeavor to capture the geneticvariation present at both ages in their design, for exam-ple, by conducting a GWA study separately for each age,or by using structural equation models to incorporate thelongitudinal data in the analysis. In time, it is predictedthat the value of formally modeling development inGWAS will be recognized (e.g. Das, Li, Wang, Tong, Fu,Li, Xu, Ahn, Mauger, Li & Wu, 2011).

DNA resequencing

DNA resequencing involves identifying the entiresequence of DNA code in an individual’s genome. Thecost of DNA resequencing has fallen dramatically inrecent years and the technical ability has improved,which allows resequencing of vast quantities of DNA tobe carried out accurately and in great depth. Thesedevelopments have led to speculation that it will not belong before many individuals’ DNA sequence data arecollected routinely (Collins, 2010). Plomin (in press)predicted that there will be two ways in which thissequencing revolution will affect developmentalists.First, it will democratize the whole genome so that it isnot just genes themselves that are the focus (coding genesmake up less than 2% of the genome, and as reviewedabove, candidate genes narrow the focus even further tojust a handful of genes). DNA sequence data provideinformation about the entire genome, which includes rarevariants, mutations, and non-coding genes. Second, whensequence data do become available there will be no needfor DNA to be collected more than once or for geno-typing to be conducted. This should revolutionize thefield of genetic influences on development and allow us

to answer the question of this paper, ‘Is the child "fatherof the Man''?’ in terms of genetic influences with muchgreater certainty.

Conclusions

This review paper addressed the question posed at thestart of this paper, namely in terms of genetic influences,‘Is the child "father of the Man''?’ or phrased differently,to what extent do the same genes influence individual dif-ferences on the same traits in infancy, childhood, adoles-cence, and adulthood? Evidence from developmentalquantitative genetic and developmental candidate genestudies both support the notion that to some extent thesame genes influence early and later cognitive andbehavioral traits (from infancy to adulthood), althoughwe note that developmental quantitative genetic studiesalso report some evidence for changes in genetic influ-ence and that not all candidate gene associations repli-cate across ages. Research on known genetic syndromessuch as Williams syndrome shows that individuals with aknown genetic mutation display a phenotype associatedwith this mutation that is relatively stable across life frominfancy to adulthood. It is now time for the newer, moretechnology-enabled fields such as GWAS and DNAresequencing to take on board the dynamic nature ofhuman behavior and thereby further our understandingof the degree of genetic stability across development.

Key points

• Genetic influences can be stable across ages (‘geneticcontinuity’) or new genetic influences can occur at oneage and not another (‘genetic change’, which can in-volve either genetic innovation or genetic attenuation).

• Longitudinal twin studies of cognitive and behavioraltraits tend to report both genetic stability and changeacross development, although twin studies spanningthe entirety of human development (infancy to adult-hood) are rare.

• Candidate gene association studies offer a startingplace for investigating main effects on biologicallyplausible genetic associations across development (forexample, dopamine and serotonin system genes havebeen associated with apparently similar infant andadult phenotypes), but newer technologies (genome-wide association studies and DNA resequencing) nowprovide a far more systematic approach to exploregenetic associations.

• Genetic syndromes with known etiology can be studiedfrom infancy to adulthood, although the informa-tiveness of these studies to genetics is to some extentlimited to the region of the genetic mutation. Researchon Williams syndrome is an example that supports theargument for relative genetic stability across devel-opment and is a good example of the leverage offered



by known genetic syndromes for studying genotype–phenotype mapping across development.

• No genome-wide association study on cognitive orbehavioral traits has yet employed longitudinal phe-notypic data.

• Knowledge of how genes operate across developmentwill have important practical consequences in inform-ing, for example, the development of preventativestrategies for heritable conditions, as well as impactingbasic science by contributing to our understanding ofthe causes of individual differences in behavior.

Acknowledgements

Thanks to Miss Sarah Hawley, Professor Mark Johnson,Professor Annette Karmiloff-Smith, Dr Emma Mea-burn, Professor Robert Plomin, Dr Elise Robinson, MissAline Scherff and Mr Mark Taylor for their helpfulcomments on earlier versions of this manuscript.

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Received: 4 August 2011Accepted: 25 August 2011



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