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Genetic influence on cognitive development between childhood and adulthood

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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.

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References

  1. 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.

    Article  PubMed  Google Scholar 

  2. Paus T. Mapping brain maturation and cognitive development during adolescence. Trends Cogn Sci. 2005;9:60–8.

    Article  PubMed  Google Scholar 

  3. Deary IJ. Intelligence. Annu Rev Psychol. 2012;63:453–82.

    Article  PubMed  Google Scholar 

  4. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  5. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Rakic P. Specification of cerebral cortical areas. Science. 1988;241:170.

    Article  CAS  PubMed  Google Scholar 

  7. Rakic P. Evolution of the neocortex: a perspective from developmental biology. Nat Rev Neurosci. 2009;10:724–35.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. 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.

    Article  CAS  PubMed  Google Scholar 

  12. Fan J, Wu Y, Fossella JA, Posner MI. Assessing the heritability of attentional networks. BMC Neurosci. 2001;2:14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. 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.

    Article  CAS  PubMed  Google Scholar 

  14. Myles-Worsley M, Coon H. Genetic and developmental factors in spontaneous selective attention: a study of normal twins. Psychiatry Res. 1997;71:163–74.

    Article  CAS  PubMed  Google Scholar 

  15. 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.

    Article  CAS  PubMed  Google Scholar 

  16. Ando J, Ono Y, Wright MJ. Genetic structure of spatial and verbal working memory. Behav Genet. 2001;31:615–24.

    Article  CAS  PubMed  Google Scholar 

  17. 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.

    Article  PubMed  Google Scholar 

  18. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. 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.

    Article  PubMed  CAS  Google Scholar 

  21. 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.

    Article  Google Scholar 

  22. 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.

    Article  CAS  PubMed  Google Scholar 

  23. 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).

  24. 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.

    Article  PubMed  Google Scholar 

  25. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Bearden CE, Glahn DC. Cognitive Genomics: searching for the genetic roots of neuropsychological functioning. Neuropsychology. 2018;31:1003–19.

    Article  Google Scholar 

  27. 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

    Article  Google Scholar 

  28. 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.

    Article  CAS  PubMed  Google Scholar 

  29. 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.

    Article  PubMed  Google Scholar 

  30. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Blangero J. Statistical genetic approaches to human adaptability. Hum Biol. 1993;65:5.

    Google Scholar 

  34. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  36. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  38. 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.

    Article  PubMed  Google Scholar 

  39. White IR, Royston P, Wood AM. Multiple imputation using chained equations: issues and guidance for practice. Stat Med. 2011;30:377–99.

    Article  PubMed  Google Scholar 

  40. Rubin DB. Multiple imputation after 18+years. J Am Stat Assoc. 1996;91:473–89.

    Article  Google Scholar 

  41. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Buuren Sv, Groothuis-Oudshoorn K mice: Multivariate imputation by chained equations in R. J Stat Soft 2010;45:1–68.

  43. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. 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.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  45. 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.

    Article  CAS  PubMed  Google Scholar 

  46. R Development Core Team. R: A language and environment for statistical computing. (Vienna, Austria: R foundation for statistical computing; 2008).

  47. 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.

    Article  PubMed  Google Scholar 

  48. Speed D, Hemani G, Johnson MR, Balding DJ. Improved heritability estimation from genome-wide SNPs. Am J Hum Genet. 2012;91:1011–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Almasy L, Towne B, Peterson C, Blangero J Detecting genotype×age interaction. Genetic Epidemiology 2001;21(S1):S819–24.

  50. Benjamini Y, Yekutieli D The control of the false discovery rate in multiple testing under dependency. Ann Stat 2001;29:1165–88.

  51. 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.

    PubMed  Google Scholar 

  52. Beaujean AA. Heritability of cognitive abilities as measured by mental chronometric tasks: a meta-analysis. Intelligence. 2005;33:187–201.

    Article  Google Scholar 

  53. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  54. 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.

    Article  PubMed  Google Scholar 

  55. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. 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.

    Article  PubMed  Google Scholar 

  57. 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.

    Article  PubMed  Google Scholar 

  58. 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.

    Article  CAS  PubMed  Google Scholar 

  59. Plomin R, DeFries JC, Loehlin JC. Genotype-environment interaction and correlation in the analysis of human behavior. Psychol Bull. 1977;84:309.

    Article  CAS  PubMed  Google Scholar 

  60. 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.

    Article  CAS  PubMed  Google Scholar 

  61. 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.

    Article  PubMed  Google Scholar 

  62. Plomin R. Genetics and general cognitive ability. Nature. 1999;402(6761supp):C25.

    Article  CAS  PubMed  Google Scholar 

  63. 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.

    Article  PubMed  Google Scholar 

  64. 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.

    Article  Google Scholar 

  65. Need AC, Goldstein DB. Next generation disparities in human genomics: concerns and remedies. Trends Genet. 2009;25:489–94.

    Article  CAS  PubMed  Google Scholar 

  66. Popejoy AB, Fullerton SM. Genomics is failing on diversity. Nature. 2016;538:161–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This research was supported by National Institute of Mental Health grants R01 MH107248 and MH107235.

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Correspondence to Josephine Mollon.

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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

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