Abstract
Successful cognitive development between childhood and adulthood has important consequences for future mental and physical wellbeing, as well as occupational and financial success. Therefore, delineating the genetic influences underlying changes in cognitive abilities during this developmental period will provide important insights into the biological mechanisms that govern both typical and atypical maturation. Using data from the Philadelphia Neurodevelopmental Cohort (PNC), a large population-based sample of individuals aged 8 to 21 years old (n = 6634), we used an empirical relatedness matrix to establish the heritability of general and specific cognitive functions and determine if genetic factors influence cognitive maturation (i.e., Gene × Age interactions) between childhood and early adulthood. We found that neurocognitive measures across childhood and early adulthood were significantly heritable. Moreover, genetic variance on general cognitive ability, or g, increased significantly between childhood and early adulthood. Finally, we did not find evidence for decay in genetic correlation on neurocognition throughout childhood and adulthood, suggesting that the same genetic factors underlie cognition at different ages throughout this developmental period. Establishing significant Gene × Age interactions in neurocognitive functions across childhood and early adulthood is a necessary first step in identifying genes that influence cognitive development, rather than genes that influence cognition per se. Moreover, since aberrant cognitive development confers risk for several psychiatric disorders, further examination of these Gene × Age interactions may provide important insights into their etiology.
Similar content being viewed by others
References
Gur RC, Calkins ME, Satterthwaite TD, Ruparel K, Bilker WB, Moore TM, et al. Neurocognitive growth charting in psychosis spectrum youths. JAMA Psychiatry. 2014;71:366–74.
Paus T. Mapping brain maturation and cognitive development during adolescence. Trends Cogn Sci. 2005;9:60–8.
Deary IJ. Intelligence. Annu Rev Psychol. 2012;63:453–82.
Reichenberg A, Caspi A, Harrington H, Houts R, Keefe RS, Murray RM, et al. Static and dynamic cognitive deficits in childhood preceding adult schizophrenia: a 30-year study. Am J Psychiatry. 2010;167:160–9.
Mollon J, David AS, Zammit S, Lewis G, Reichenberg A. Course of cognitive development from infancy to early adulthood in the psychosis spectrum. JAMA Psychiatry. 2018;75:270–9.
Rakic P. Specification of cerebral cortical areas. Science. 1988;241:170.
Rakic P. Evolution of the neocortex: a perspective from developmental biology. Nat Rev Neurosci. 2009;10:724–35.
Kang HJ, Kawasawa YI, Cheng F, Zhu Y, Xu X, Li M, et al. Spatio-temporal transcriptome of the human brain. Nature. 2011;478:483–9.
Voineagu I, Wang X, Johnston P, Lowe JK, Tian Y, Horvath S, et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature. 2011;474:380.
Johnson MB, Kawasawa YI, Mason CE, Krsnik Ž, Coppola G, Bogdanović D, et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron. 2009;62:494–509.
Haworth CM, Wright MJ, Luciano M, Martin NG, de Geus EJ, van Beijsterveldt CE, et al. The heritability of general cognitive ability increases linearly from childhood to young adulthood. Mol Psychiatry. 2010;15:1112–20.
Fan J, Wu Y, Fossella JA, Posner MI. Assessing the heritability of attentional networks. BMC Neurosci. 2001;2:14.
Cornblatt BA, Risch NJ, Faris G, Friedman D, Erlenmeyer-Kimling L. The Continuous Performance Test, identical pairs version (CPT-IP): I. New findings about sustained attention in normal families. Psychiatry Res. 1988;26:223–38.
Myles-Worsley M, Coon H. Genetic and developmental factors in spontaneous selective attention: a study of normal twins. Psychiatry Res. 1997;71:163–74.
Robinson EB, Kirby A, Ruparel K, Yang J, McGrath L, Anttila V, et al. The genetic architecture of pediatric cognitive abilities in the Philadelphia Neurodevelopmental Cohort. Mol Psychiatry. 2015;20:454–8.
Ando J, Ono Y, Wright MJ. Genetic structure of spatial and verbal working memory. Behav Genet. 2001;31:615–24.
Kremen WS, Jacobsen KC, Xian H, Eisen SA, Eaves LJ, Tsuang MT, et al. Genetics of verbal working memory processes: a twin study of middle-aged men. Neuropsychology. 2007;21:569.
Vogler C, Gschwind L, Coynel D, Freytag V, Milnik A, Egli T, et al. Substantial SNP-based heritability estimates for working memory performance. Transl Psychiatry. 2014;4:e438.
Knowles EE, Mathias SR, McKay DR, Sprooten E, Blangero J, Almasy L, et al. Genome-wide analyses of working-memory ability: a review. Curr Behav Neurosci Rep. 2014;1:224–33.
Bearden CE, Karlsgodt KH, Bachman P, van Erp TG, Winkler AM, Glahn DC. Genetic architecture of declarative memory: implications for complex illnesses. Neuroscientist. 2012;18:516–32.
Knowles EE, Carless MA, de Almeida MA, Curran JE, McKay DR, Sprooten E, et al. Genome‐wide significant localization for working and spatial memory: Identifying genes for psychosis using models of cognition. Am J Med Genet Part B Neuropsychiatr Genet. 2014;165:84–95.
Swan GE, Reed T, Jack LM, Miller BL, Markee T, Wolf PA, et al. Differential genetic influence for components of memory in aging adult twins. Arch Neurol. 1999;56:1127–32.
McGue M, Bouchard TJ Jr, Iacono WG, Lykken DT. Behavioral genetics of cognitive ability: A life-span perspective. (eds Plomin R, McClearn GE), In Nature, nurture & psychology pp. 59–76 (Washington, DC, US: American Psychological Association, 1993).
Bergen SE, Gardner CO, Kendler KS. Age-related changes in heritability of behavioral phenotypes over adolescence and young adulthood: a meta-analysis. Twin Res Hum Genet. 2007;10:423–33.
Glahn DC, Kent JW Jr, Sprooten E, Diego VP, Winkler AM, Curran JE, et al. Genetic basis of neurocognitive decline and reduced white-matter integrity in normal human brain aging. Proc Natl Acad Sci USA. 2013;110:19006–11.
Bearden CE, Glahn DC. Cognitive Genomics: searching for the genetic roots of neuropsychological functioning. Neuropsychology. 2018;31:1003–19.
Tucker-Drob EM, Briley DA. Continuity of genetic and environmental influences on cognition across the life span: a meta-analysis of longitudinal twin and adoption studies. Psyc. Bull.2014;140:949
Trzaskowski M, Yang J, Visscher PM, Plomin R. DNA evidence for strong genetic stability and increasing heritability of intelligence from age 7 to 12. Mol Psychiatry. 2014;19:380–4.
Briley DA, Tucker-Drob EM. Explaining the increasing heritability of cognitive ability across development: a meta-analysis of longitudinal twin and adoption studies. Psychol Sci. 2013;24:1704–13.
Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet. 2011;88:76–82.
Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR, et al. Common SNPs explain a large proportion of the heritability for human height. Nat Genet. 2010;42:565–9.
Petrill SA, Lipton PA, Hewitt JK, Plomin R, Cherny SS, Corley R, et al. Genetic and environmental contributions to general cognitive ability through the first 16 years of life. Dev Psychol. 2004;40:805–12.
Blangero J. Statistical genetic approaches to human adaptability. Hum Biol. 1993;65:5.
Kent JW Jr, Goring HH, Charlesworth JC, Drigalenko E, Diego VP, Curran JE, et al. Genotypexage interaction in human transcriptional ageing. Mech Ageing Dev. 2012;133:581–90.
Calkins ME, Merikangas KR, Moore TM, Burstein M, Behr MA, Satterthwaite TD, et al. The Philadelphia Neurodevelopmental Cohort: constructing a deep phenotyping collaborative. J Child Psychol Psychiatry. 2015;56:1356–69.
Mailman MD, Feolo M, Jin Y, Kimura M, Tryka K, Bagoutdinov R, et al. The NCBI dbGaP database of genotypes and phenotypes. Nat Genet. 2007;39:1181–6.
Gur RC, Richard J, Calkins ME, Chiavacci R, Hansen JA, Bilker WB, et al. Age group and sex differences in performance on a computerized neurocognitive battery in children age 8–21. Neuropsychology. 2012;26:251–65.
Gur RC, Richard J, Hughett P, Calkins ME, Macy L, Bilker WB, et al. A cognitive neuroscience-based computerized battery for efficient measurement of individual differences: standardization and initial construct validation. J Neurosci Methods. 2010;187:254–62.
White IR, Royston P, Wood AM. Multiple imputation using chained equations: issues and guidance for practice. Stat Med. 2011;30:377–99.
Rubin DB. Multiple imputation after 18+years. J Am Stat Assoc. 1996;91:473–89.
Sterne JA, White IR, Carlin JB, Spratt M, Royston P, Kenward MG, et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ. 2009;338:b2393.
Buuren Sv, Groothuis-Oudshoorn K mice: Multivariate imputation by chained equations in R. J Stat Soft 2010;45:1–68.
Germine L, Robinson E, Smoller J, Calkins M, Moore T, Hakonarson H, et al. Association between polygenic risk for schizophrenia, neurocognition and social cognition across development. Transl Psychiatry. 2016;6:e924.
Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience. 2015;4:7.
Han L, Abney M. Using identity by descent estimation with dense genotype data to detect positive selection. Eur J Hum Genet. 2013;21:205–11.
R Development Core Team. R: A language and environment for statistical computing. (Vienna, Austria: R foundation for statistical computing; 2008).
Blangero J, Goring HH, Kent JW Jr., Williams JT, Peterson CP, Almasy, et al. Quantitative trait nucleotide analysis using Bayesian model selection. Hum Biol. 2005;77:541–59.
Speed D, Hemani G, Johnson MR, Balding DJ. Improved heritability estimation from genome-wide SNPs. Am J Hum Genet. 2012;91:1011–21.
Almasy L, Towne B, Peterson C, Blangero J Detecting genotype×age interaction. Genetic Epidemiology 2001;21(S1):S819–24.
Benjamini Y, Yekutieli D The control of the false discovery rate in multiple testing under dependency. Ann Stat 2001;29:1165–88.
Goldberg Hermo X, Lemos Giraldez S, Fananas Saura L. A systematic review of the complex organization of human cognitive domains and their heritability. Psicothema. 2014;26:1–9.
Beaujean AA. Heritability of cognitive abilities as measured by mental chronometric tasks: a meta-analysis. Intelligence. 2005;33:187–201.
Lenroot RK, Giedd JN. The changing impact of genes and environment on brain development during childhood and adolescence: initial findings from a neuroimaging study of pediatric twins. Dev Psychopathol. 2008;20:1161–75.
Blokland GAM, Mesholam-Gately RI, Toulopoulou T, Del Re EC, Lam M, DeLisi LE, et al. Heritability of neuropsychological measures in schizophrenia and nonpsychiatric populations: a systematic review and meta-analysis. Schizophr Bull. 2017;43:788–800.
Kendler KS, Turkheimer E, Ohlsson H, Sundquist J, Sundquist K. Family environment and the malleability of cognitive ability: a Swedish national home-reared and adopted-away cosibling control study. Proc Natl Acad Sci USA. 2015;112:4612–7.
Tucker-Drob EM, Rhemtulla M, Harden KP, Turkheimer E, Fask D. Emergence of a Gene x socioeconomic status interaction on infant mental ability between 10 months and 2 years. Psychol Sci. 2011;22:125–33.
Turkheimer E, Haley A, Waldron M, d’Onofrio B, Gottesman II. Socioeconomic status modifies heritability of IQ in young children. Psychol Sci. 2003;14:623–8.
Gur RC, Ragland JD, Moberg PJ, Turner TH, Bilker WB, Kohler C, et al. Computerized neurocognitive scanning: i. methodology and validation in healthy people. Neuropsychopharmacology. 2001;25:766–76.
Plomin R, DeFries JC, Loehlin JC. Genotype-environment interaction and correlation in the analysis of human behavior. Psychol Bull. 1977;84:309.
Kendler KS, Eaves LJ. Models for the joint effect of genotype and environment on liability to psychiatric illness. Am J Psychiatry. 1986;143:279–89.
Cheung AK, Harden KP, Tucker-Drob EM. From specialist to generalist: developmental transformations in the genetic structure of early child abilities. Dev Psychobiol. 2015;57:566–83.
Plomin R. Genetics and general cognitive ability. Nature. 1999;402(6761supp):C25.
Kovas Y, Voronin I, Kaydalov A, Malykh SB, Dale PS, Plomin R. Literacy and numeracy are more heritable than intelligence in primary school. Psychol Sci. 2013;24:2048–56.
Van Soelen IL, Brouwer RM, Van Leeuwen M, Kahn RS, Pol HEH, Boomsma DI. Heritability of verbal and performance intelligence in a pediatric longitudinal sample. Twin Res Human Genet. 2011;14:119–28.
Need AC, Goldstein DB. Next generation disparities in human genomics: concerns and remedies. Trends Genet. 2009;25:489–94.
Popejoy AB, Fullerton SM. Genomics is failing on diversity. Nature. 2016;538:161–4.
Acknowledgements
This research was supported by National Institute of Mental Health grants R01 MH107248 and MH107235.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Electronic supplementary material
Rights and permissions
About this article
Cite this article
Mollon, J., Knowles, E.E.M., Mathias, S.R. et al. Genetic influence on cognitive development between childhood and adulthood. Mol Psychiatry 26, 656–665 (2021). https://doi.org/10.1038/s41380-018-0277-0
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41380-018-0277-0
- Springer Nature Limited
This article is cited by
-
Cognitive performance from childhood to old age and intergenerational correlations in the multigenerational Young Finns Study
Journal of Neurology (2024)
-
Maternal cognitive function and neurodevelopmental outcomes of slum-dwelling children in Bangladesh
Current Psychology (2024)
-
Early predictors of neurodevelopment after perinatal arterial ischemic stroke: a systematic review and meta-analysis
Pediatric Research (2023)
-
KIBRA single nucleotide polymorphism is associated with hippocampal subfield volumes and cognition across development
Brain Structure and Function (2023)
-
Association between urinary iodine excretion, genetic disposition and fluid intelligence in children, adolescents and young adults: the DONALD study
European Journal of Nutrition (2023)