Cognitive Genomics: Recent Advances and Current Challenges
- 104 Downloads
Purpose of Review
We review recent progress in uncovering the complex genetic architecture of cognition, arising primarily from genome-wide association studies (GWAS). We explore the genetic correlations between cognitive performance and neuropsychiatric disorders, the genetic and environmental factors associated with age-related cognitive decline, and speculate about the future role of genomics in the understanding of cognitive processes.
Improvements in genomic methods, and the increasing availability of large datasets via consortia cooperation, have led to a greater understanding of the role played by common and rare variants in the genomics of cognition, the highly polygenic basis of cognitive function and dysfunction, and the multiple biological processes involved.
Recent research has aided in our understanding of the complex biological nature of genomics of cognition. Further development of data banks and techniques to analyze this data hold significant promise for understanding cognitive ability, and for treating cognitively related disability.
KeywordsCognition Genomics Schizophrenia Aging GWAS Rare variants
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they have no conflicts of interest.
Human and Animal Rights and Informed Consent
This article does not contain any studies with human or animal subjects performed by any of the authors.
Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance
- 3.Plomin R, DeFries JC, McClearn GE, McGuffin P. Behavioral genetics. 4th ed. New York: Worth Publishers; 2001.Google Scholar
- 7.•• Lee JJ, Wedow R, Okbay A, Kong E, Maghzian O, Zacher M, et al. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat Genet. 2018;50(8):1112–21. https://doi.org/10.1038/s41588-018-0147-3 This study is the largest GWAS study to date on educational attainment using both public and commerically available data and highlights the role of genes involved in the prenatal brain as well post natal development. CrossRefPubMedPubMedCentralGoogle Scholar
- 8.• Lam M, Hill WD, Trampush JW, Yu J, Knowles E, Davies G, et al. Pleiotropic meta-analysis of cognition, education, and schizophrenia differentiates roles of early neurodevelopmental and adult synaptic pathways. bioRxiv. 2019;105:334. https://doi.org/10.1101/519967 This paper examines the pleiotropic nature of GWAS findings on intelligence and psychiatric disorders. CrossRefGoogle Scholar
- 13.De Schryver M, Hughes S, Rosseel Y, De Houwer J. Unreliable yet still replicable: a comment on LeBel and Paunonen (2011). Front Psychol. 2016;6(2039). https://doi.org/10.3389/fpsyg.2015.02039.
- 15.Fawns-Ritchie C, Deary IJ. Reliability and validity of the UK Biobank cognitive tests. medRxiv. 2019;19002204. https://doi.org/10.1101/19002204.
- 17.Sniekers S, Stringer S, Watanabe K, Jansen PR, Coleman JRI, Krapohl E, et al. Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence. Nat Genet. 2017;49(7):1107–12. https://doi.org/10.1038/ng.3869.CrossRefPubMedPubMedCentralGoogle Scholar
- 18.Trampush JW, Yang ML, Yu J, Knowles E, Davies G, Liewald DC, et al. GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium. Mol Psychiatry. 2017;22(3):336–45. https://doi.org/10.1038/mp.2016.244.CrossRefPubMedPubMedCentralGoogle Scholar
- 19.Davies G, Armstrong N, Bis JC, Bressler J, Chouraki V, Giddaluru S, et al. Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N=53949). Mol Psychiatry. 2015;20(2):183–92. https://doi.org/10.1038/mp.2014.188.CrossRefPubMedPubMedCentralGoogle Scholar
- 20.Sudlow C, Gallacher J, Allen N, Beral V, Burton P, Danesh J, et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 2015;12(3):e1001779. https://doi.org/10.1371/journal.pmed.1001779.CrossRefPubMedPubMedCentralGoogle Scholar
- 23.•• Davies G, Lam M, Harris SE, Trampush JW, Luciano M, Hill WD, et al. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function. Nat Commun. 2018;9(1):2098. https://doi.org/10.1038/s41467-018-04362-x This study demonstrates the power of sample size to GWAS findings by the addition of the UK Biobank data. It confirms previous findings and identifies new loci associated with neuronial communication. CrossRefPubMedPubMedCentralGoogle Scholar
- 24.•• Savage JE, Jansen PR, Stringer S, Watanabe K, Bryois J, de Leeuw CA, et al. Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence. Nat Genet. 2018;50(7):912–9. https://doi.org/10.1038/s41588-018-0152-6 Again using the UK Biobank and other data, this study had identified the largest number of association snps for IQ to date, and reports a bio-informatic analysis of these findings. CrossRefPubMedPubMedCentralGoogle Scholar
- 27.• Hill WD, Marioni RE, Maghzian O, Ritchie SJ, Hagenaars SP, AM MI, et al. A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence. Mol Psychiatry. 2018. https://doi.org/10.1038/s41380-017-0001-5 Hill et al. demonstrate the additive effects of multi-trait anlaysis and its utility to generate further findings. CrossRefGoogle Scholar
- 34.• Huguet G, Schramm C, Douard E, Jiang L, Labbe A, Tihy F, et al. Measuring and estimating the effect sizes of copy number variants on general intelligence in community-based samples. JAMA Psychiatry. 2018;75(5):447–57. https://doi.org/10.1001/jamapsychiatry.2018.0039 This study presents a framework for examining the effects of copy number variants on general cognition. CrossRefPubMedPubMedCentralGoogle Scholar
- 35.• Stefansson H, Meyer-Lindenberg A, Steinberg S, Magnusdottir B, Morgen K, Arnarsdottir S, et al. CNVs conferring risk of autism or schizophrenia affect cognition in controls. Nature. 2013;505:361. https://doi.org/10.1038/nature12818 The study of population isolates can highlight the role of CNVs in cognition. CrossRefPubMedGoogle Scholar
- 38.Kendall KM, Bracher-Smith M, Fitzpatrick H, Lynham A, Rees E, Escott-Price V, et al. Cognitive performance and functional outcomes of carriers of pathogenic copy number variants: analysis of the UK Biobank. Br J Psychiatry. 2019;214(5):297–304. https://doi.org/10.1192/bjp.2018.301.CrossRefPubMedPubMedCentralGoogle Scholar
- 39.Warland A, Kendall KM, Rees E, Kirov G, Caseras X. Schizophrenia-associated genomic copy number variants and subcortical brain volumes in the UK Biobank. Mol Psychiatry. 2019:1–9. https://doi.org/10.1038/s41380-019-0355-y.
- 40.•• Ganna A, Genovese G, Howrigan DP, Byrnes A, Kurki MI, Zekavat SM et al. Ultra-rare disruptive and damaging mutations influence educational attainment in the general population. Nat Neurosci. 2016;19:1563. doi: https://doi.org/10.1038/nn.4404 Important paper highlighting the role of rare mutations in intelligence using EA as a proxy measure.
- 41.• Hill WD, Arslan RC, Xia C, Luciano M, Amador C, Navarro P, et al. Genomic analysis of family data reveals additional genetic effects on intelligence and personality. Mol Psychiatry. 2018;23(12):2347–62. https://doi.org/10.1038/s41380-017-0005-1 This study shows how using family based data can resolve some of the missing hertiability in cognition. CrossRefPubMedPubMedCentralGoogle Scholar
- 44.Xia C, Amador C, Huffman J, Trochet H, Campbell A, Porteous D, et al. Pedigree- and SNP-associated genetics and recent environment are the major contributors to anthropometric and cardiometabolic trait variation. PLoS Genet. 2016;12(2):e1005804. https://doi.org/10.1371/journal.pgen.1005804.CrossRefPubMedPubMedCentralGoogle Scholar
- 45.Shafee R, Nanda P, Padmanabhan JL, Tandon N, Alliey-Rodriguez N, Kalapurakkel S, et al. Polygenic risk for schizophrenia and measured domains of cognition in individuals with psychosis and controls. Transl Psychiatry. 2018;8(1):78. https://doi.org/10.1038/s41398-018-0124-8.CrossRefPubMedPubMedCentralGoogle Scholar
- 46.• Hasan A, Afzal M. Gene and environment interplay in cognition: Evidence from twin and molecular studies, future directions and suggestions for effective candidate gene x environment (cGxE) research. Mult Scler Relat Disord. 2019;33:121–30. https://doi.org/10.1016/j.msard.2019.05.005 This article reviews the interplay between the enviroment and cognition and explores the need to examine these effects in future studies. CrossRefPubMedGoogle Scholar
- 47.Cheesman R, Hunjan A, Coleman JRI, Ahmadzadeh Y, Plomin R, McAdams TA, et al. Comparison of adopted and non-adopted individuals reveals gene-environment interplay for education in the UK Biobank. bioRxiv. 2019:707695. https://doi.org/10.1101/707695.
- 49.Selzam S, Ritchie SJ, Pingault J-B, Reynolds CA, O’Reilly PF, Plomin R. Comparing within- and between-family polygenic score prediction. bioRxiv. 2019:605006. https://doi.org/10.1101/605006.
- 52.Blokland GAM, Del Re EC, Mesholam-Gately RI, Jovicich J, Trampush JW, Keshavan MS, et al. The Genetics of Endophenotypes of Neurofunction to Understand Schizophrenia (GENUS) consortium: a collaborative cognitive and neuroimaging genetics project. Schizophr Res. 2018;195:306–17. https://doi.org/10.1016/j.schres.2017.09.024.CrossRefPubMedGoogle Scholar
- 53.Lencz T, Knowles E, Davies G, Guha S, Liewald DC, Starr JM, et al. Molecular genetic evidence for overlap between general cognitive ability and risk for schizophrenia: a report from the Cognitive Genomics consorTium (COGENT). Mol Psychiatry. 2014;19(2):168–74. https://doi.org/10.1038/mp.2013.166.CrossRefPubMedGoogle Scholar
- 55.Hagenaars SP, Harris SE, Davies G, Hill WD, Liewald DC, Ritchie SJ, et al. Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank (N=112 151) and 24 GWAS consortia. Mol Psychiatry. 2016;21(11):1624–32. https://doi.org/10.1038/mp.2015.225.CrossRefPubMedPubMedCentralGoogle Scholar
- 56.Fanous AH, Zhou B, Aggen SH, Bergen SE, Amdur RL, Duan J, et al. Genome-wide association study of clinical dimensions of schizophrenia: polygenic effect on disorganized symptoms. Am J Psychiatry. 2012;169(12):1309–17. https://doi.org/10.1176/appi.ajp.2012.12020218.CrossRefPubMedPubMedCentralGoogle Scholar
- 57.•• Richards AL, Pardiñas AF, Frizzati A, Tansey KE, Lynham AJ, Holmans P, et al. The Relationship Between Polygenic Risk Scores and Cognition in Schizophrenia. Schizophr Bull. 2019. https://doi.org/10.1093/schbul/sbz061 This study provides a current estimate of the genetic correlation between cognitive function and schizophrenia susceptibility.
- 59.World Health O. World report on ageing and health. Geneva: World Health Organization; 2015.Google Scholar
- 60.Andrews SJ, Das D, Cherbuin N, Anstey KJ, Easteal S. Association of genetic risk factors with cognitive decline: the PATH through life project. Neurobiol Aging. 2016;41:150–8. https://doi.org/10.1016/j.neurobiolaging.2016.02.016.CrossRefPubMedGoogle Scholar
- 62.•• Cabeza R, Albert M, Belleville S, FIM C, Duarte A, Grady CL, et al. Maintenance, reserve and compensation: the cognitive neuroscience of healthy ageing. Nat Rev Neurosci. 2018;19(11):701–10. https://doi.org/10.1038/s41583-018-0068-2 This article presents a clear theortitical model to explain the factors involved in cognitive decline. CrossRefPubMedPubMedCentralGoogle Scholar
- 63.Stern Y, Arenaza-Urquijo EM, Bartrés-Faz D, Belleville S, Cantilon M, Chetelat G, et al. Whitepaper: defining and investigating cognitive reserve, brain reserve, and brain maintenance. Alzheimers Dement. 2018. https://doi.org/10.1016/j.jalz.2018.07.219.
- 64.• Ritchie SJ, Hill WD, Marioni RE, Davies G, Hagenaars SP, Harris SE, et al. Polygenic predictors of age-related decline in cognitive ability. Mol Psychiatry. 2019. https://doi.org/10.1038/s41380-019-0372-x This study explores the use of PGS in understanding the genetics of cognitive decline and highlights the need for further work.
- 66.Plassman BL, Williams JW Jr, Burke JR, Holsinger T, Benjamin S. Systematic review: factors associated with risk for and possible prevention of cognitive decline in later life. Ann Intern Med. 2010;153(3):182–93. https://doi.org/10.7326/0003-4819-153-3-201008030-00258.CrossRefPubMedGoogle Scholar
- 67.•• Boldrini M, Fulmore CA, Tartt AN, Simeon LR, Pavlova I, Poposka V, et al. Human hippocampal neurogenesis persists throughout aging. Cell Stem Cell. 2018;22(4):589–99.e5. https://doi.org/10.1016/j.stem.2018.03.015 This research explores new frontiers in the understanding of cognitive variance in aging and proposes novel concepts involving neurogenesis. CrossRefPubMedPubMedCentralGoogle Scholar
- 68.Van Hout CV, Tachmazidou I, Backman JD, Hoffman JX, Ye B, Pandey AK, et al. Whole exome sequencing and characterization of coding variation in 49,960 individuals in the UK Biobank. bioRxiv. 2019;572347. https://doi.org/10.1101/572347.
- 76.Wray NR, Ripke S, Mattheisen M, Trzaskowski M, Byrne EM, Abdellaoui A, et al. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat Genet. 2018;50(5):668–81. https://doi.org/10.1038/s41588-018-0090-3.CrossRefPubMedPubMedCentralGoogle Scholar
- 77.Pardiñas AF, Holmans P, Pocklington AJ, Escott-Price V, Ripke S, Carrera N, et al. Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection. Nat Genet. 2018;50(3):381–9. https://doi.org/10.1038/s41588-018-0059-2.CrossRefPubMedPubMedCentralGoogle Scholar