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Biological annotation of genetic loci associated with intelligence in a meta-analysis of 87,740 individuals

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Coleman, Jonathan R. I., Bryois, Julien, Gaspar, Héléna A., Jansen, Philip R., Savage, Jeanne E., Skene, Nathan, Plomin, Robert, Muñoz-Manchado, Ana B. +6 more·2019·Molecular Psychiatry

Published version of a preprint

Abstract

Variance in IQ is associated with a wide range of health outcomes, and 1% of the population are affected by intellectual disability. Despite a century of research, the fundamental neural underpinnings of intelligence remain unclear. We integrate results from genome-wide association studies (GWAS) of intelligence with brain tissue and single cell gene expression data to identify tissues and cell types associated with intelligence. GWAS data for IQ (N = 78,308) were meta-analyzed with a study comparing 1247 individuals with mean IQ ~170 to 8185 controls. Genes associated with intelligence implicate pyramidal neurons of the somatosensory cortex and CA1 region of the hippocampus, and midbrain embryonic GABAergic neurons. Tissue-specific analyses find the most significant enrichment for frontal cortex brain expressed genes. These results suggest specific neuronal cell types and genes may be involved in intelligence and provide new hypotheses for neuroscience experiments using model systems.

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  1. [1]Okbay A Beauchamp JP Fontana MA Lee JJ Pers TH Rietveld CA Genome-wide association study identifies 74 loci associated with educational attainment Nature 2016 533 539 542 27225129 PMC4883595
  2. [2]Lo M-T Hinds DA Tung JY Franz C Fan C-C Wang Y Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders Nat Genet 2016 [Internet] 10.1038/ng.3736 PMC5278898 27918536 · DOI
  3. [3]Sullivan PF Agrawal A Bulik C Andreassen OA Borglum A Breen G Psychiatric Genomics: An Update and an Agenda bioRxiv 2017 115600 [Internet] [cited 2017]; Available from: http://biorxiv.org/content/early/2017/03/10/115600 PMC5756100 28969442
  4. [4]Sniekers S Stringer S Watanabe K Jansen PR Coleman JRI Krapohl E Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence Nat Genet 2017 [Internet] [cited 2017] 10.1038/ng.3869 PMC5665562 28530673 · DOI · Paper page
  5. [6]Benyamin B Pourcain B Davis OS Davies G Hansell NK Brion M-J Childhood intelligence is heritable, highly polygenic and associated with FNBP1L Mol Psychiatry 2013 19 253 258 23358156 PMC3935975
  6. [7]Deary IJ Intelligence Annu Rev Psychol 2012 63 453 482 21943169
  7. [8]Wray NR Allele frequencies and the r2 measure of linkage disequilibrium: impact on design and interpretation of association studies Twin Res Hum Genet 2005 8 87 94 15901470
  8. [9]Carlson CS Eberle MA Rieder MJ Yi Q Kruglyak L Nickerson DA Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium Am J Hum Genet 2004 74 106 120 14681826 PMC1181897
  9. [10]Hormozdiari F Zhu A Kichaev G Ju CJ-T Segrè AV Joo JWJ Widespread Allelic Heterogeneity in Complex Traits Am J Hum Genet 2017 100 789 802 28475861 PMC5420356
  10. [11]Zhu Z Zhang F Hu H Bakshi A Robinson MR Powell JE Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets Nat Genet 2016 48 481 487 27019110
  11. [12]Boyle EA Li YI Pritchard JK An Expanded View of Complex Traits: From Polygenic to Omnigenic Cell 2017 169 1177 1186 28622505 PMC5536862
  12. [13]Shi H Kichaev G Pasaniuc B Contrasting the Genetic Architecture of 30 Complex Traits from Summary Association Data Am J Hum Genet 2016 99 139 153 27346688 PMC5005444
  13. [14]Loh P-R Bhatia G Gusev A Finucane HK Bulik-Sullivan BK Pollack SJ Contrasting genetic architectures of schizophrenia and other complex diseases using fast variance-components analysis Nat Genet 2015 47 1385 1392 26523775 PMC4666835
  14. [15]Breen G Li Q Roth BL O’Donnell P Didriksen M Dolmetsch R Translating genome-wide association findings into new therapeutics for psychiatry Nat Neurosci 2016 19 1392 1396 27786187 PMC5676453
  15. [17]Zabaneh D Krapohl E Gaspar HA Curtis C Lee SH Patel H A genome-wide association study for extremely high intelligence Mol Psychiatry 2017 [Internet] [cited 2017] 10.1038/mp.2017.121 PMC5987166 29731509 · DOI · Paper page
  16. [18]Consortium GTEx Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans Science 2015 348 648 660 25954001 PMC4547484
  17. [19]Deary IJ Penke L Johnson W The neuroscience of human intelligence differences Nat Rev Neurosci 2010 11 201 211 20145623
  18. [20]Willer CJ Li Y Abecasis GR METAL: fast and efficient meta-analysis of genomewide association scans Bioinformatics 2010 26 2190 2191 20616382 PMC2922887
  19. [21]Purcell S Cherny SS Sham PC Genetic Power Calculator: design of linkage and association genetic mapping studies of complex traits Bioinformatics 2003 19 149 150 12499305
  20. [22]Peloso GM Rader DJ Gabriel S Kathiresan S Daly MJ Neale BM Phenotypic extremes in rare variant study designs Eur J Hum Genet 2016 24 924 930 26350511 PMC4867440
  21. [24]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 25722852 PMC4342193
  22. [25]Watanabe K Taskesen E van Bochoven A Posthuma D FUMA: Functional mapping and annotation of genetic associations bioRxiv 2017 110023 [Internet] [cited 2017]; Available from: http://biorxiv.org/content/early/2017/02/20/110023.abstract PMC5705698 29184056
  23. [26]Bulik-Sullivan BK Loh P-R Finucane HK Ripke S Yang J Schizophrenia Working Group of the Psychiatric Genomics Consortium LD Score regression distinguishes confounding from polygenicity in genome-wide association studies Nat Genet 2015 47 291 295 25642630 PMC4495769
  24. [27]Finucane HK Bulik-Sullivan B Gusev A Trynka G Reshef Y Loh P-R Partitioning heritability by functional annotation using genome-wide association summary statistics Nat Genet 2015 47 1228 1235 26414678 PMC4626285
  25. [29]Vernot B Tucci S Kelso J Schraiber JG Wolf AB Gittelman RM Excavating Neandertal and Denisovan DNA from the genomes of Melanesian individuals Science 2016 352 235 239 26989198 PMC6743480
  26. [30]Buenrostro JD Giresi PG Zaba LC Chang HY Greenleaf WJ Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position Nat Methods 2013 10 1213 1218 24097267 PMC3959825
  27. [31]Sudmant PH Rausch T Gardner EJ Handsaker RE Abyzov A Huddleston J An integrated map of structural variation in 2,504 human genomes Nature 2015 526 75 81 26432246 PMC4617611
  28. [32]de Leeuw CA Mooij JM Heskes T Posthuma D MAGMA: generalized gene-set analysis of GWAS data PLoS Comput Biol 2015 11 e1004219 25885710 PMC4401657
  29. [33]de Leeuw CA Neale BM Heskes T Posthuma D The statistical properties of gene-set analysis Nature Reviews Genetics 2016 17 353 364 27070863
  30. [35]Barbeira A Shah KP Torres JM Wheeler HE Torstenson ES Edwards T MetaXcan: Summary Statistics Based Gene-Level Association Method Infers Accurate PrediXcan Results bioRxiv 2016 045260 [Internet] [cited 2017]; Available from: http://biorxiv.org/content/early/2016/03/23/045260.full-text.pdf+html
  31. [36]Koscielny G An P Carvalho-Silva D Cham JA Fumis L Gasparyan R Open Targets: a platform for therapeutic target identification and validation Nucleic Acids Res 2016 [Internet] 10.1093/nar/gkw1055 PMC5210543 27899665 · DOI
  32. [37]Liberzon A Birger C Thorvaldsdóttir H Ghandi M Mesirov JP Tamayo P The Molecular Signatures Database (MSigDB) hallmark gene set collection Cell Syst 2015 1 417 425 26771021 PMC4707969
  33. [38]Bayés A van de Lagemaat LN Collins MO Croning MDR Whittle IR Choudhary JS Characterization of the proteome, diseases and evolution of the human postsynaptic density Nat Neurosci 2011 14 19 21 21170055 PMC3040565
  34. [41]Hill WD Davies G Harris SE Hagenaars SP neuroCHARGE Cognitive Working group Liewald DC Molecular genetic aetiology of general cognitive function is enriched in evolutionarily conserved regions Transl Psychiatry 2016 6 e980 27959336 PMC5290340
  35. [42]Zeisel A Muñoz-Manchado AB Codeluppi S Lönnerberg P La Manno G Juréus A Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq Science 2015 347 1138 1142 25700174
  36. [43]Pardiñas AF Holmans P Pocklington AJ Escott-Price V Ripke S Carrera N Common schizophrenia alleles are enriched in mutation-intolerant genes and maintained by background selection bioRxiv 2016 068593 [Internet] [cited 2016]; Available from: http://biorxiv.org/content/early/2016/08/09/068593 PMC5918692 29483656
  37. [44]Brawand D Soumillon M Necsulea A Julien P Csárdi G Harrigan P The evolution of gene expression levels in mammalian organs Nature 2011 478 343 348 22012392
  38. [48]Carss KJ Stevens E Foley AR Cirak S Riemersma M Torelli S Mutations in GDP-mannose pyrophosphorylase B cause congenital and limb-girdle muscular dystrophies associated with hypoglycosylation of α-dystroglycan Am J Hum Genet 2013 93 29 41 23768512 PMC3710768
  39. [49]Jensen BS Willer T Saade DN Cox MO Mozaffar T Scavina M GMPPB-Associated Dystroglycanopathy: Emerging Common Variants with Phenotype Correlation Hum Mutat 2015 36 1159 1163 26310427 PMC4843780
  40. [50]Rodríguez Cruz PM Belaya K Basiri K Sedghi M Farrugia ME Holton JL Clinical features of the myasthenic syndrome arising from mutations in GMPPB J Neurol Neurosurg Psychiatry 2016 87 802 809 27147698 PMC6047737
  41. [51]Belaya K Rodríguez Cruz PM Liu WW Maxwell S McGowan S Farrugia ME Mutations in GMPPB cause congenital myasthenic syndrome and bridge myasthenic disorders with dystroglycanopathies Brain 2015 138 2493 2504 26133662 PMC4547052
  42. [52]Cabrera-Serrano M Ghaoui R Ravenscroft G Johnsen RD Davis MR Corbett A Expanding the phenotype of GMPPB mutations Brain 2015 138 836 844 25681410
  43. [53]Wright KM Lyon KA Leung H Leahy DJ Ma L Ginty DD Dystroglycan organizes axon guidance cue localization and axonal pathfinding Neuron 2012 76 931 944 23217742 PMC3526105
  44. [54]Roberts JA The genetics of mental deficiency Eugen Rev 1952 44 71 83 21260618 PMC2973323
  45. [55]McGue M Gottesman II Classical and Molecular Genetic Research on General Cognitive Ability Hastings Cent Rep 2015 45 S25 S31 26413945
  46. [56]Vissers LELM Gilissen C Veltman JA Genetic studies in intellectual disability and related disorders Nat Rev Genet 2016 17 9 18 26503795
  47. [57]Network and Pathway Analysis Subgroup of Psychiatric Genomics Consortium Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways Nat Neurosci 2015 18 199 209 25599223 PMC4378867

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Authors
Coleman, J. R. I., Bryois, J., Gaspar, H. A., Jansen, P. R., Savage, J. E., Skene, N., Plomin, R., Muñoz-Manchado, A. B., Linnarsson, S., Crawford, G., Hjerling-Leffler, J., Sullivan, P. F., Posthuma, D., & Breen, G.
Affiliations
  • King's College London (GB)
  • Karolinska Institutet (SE)
  • Erasmus MC (NL)
  • Vrije Universiteit Amsterdam (NL)
  • Duke University (US)
  • University of North Carolina at Chapel Hill (US)
Corresponding author
Breen, Gerome
Venue
Molecular Psychiatry
Published
2018-03-08
Volume
24
Issue
2
Pages
182-197
ISSN
  • 1359-4184 (ISSN-L)
  • 1476-5578
OpenAlex
W2792859845
Cited by
66
References
9
Citations by year
2026: 2 · 2025: 7 · 2024: 8 · 2023: 6 · 2022: 10 · 2021: 8 · 2020: 14 · 2019: 7 · 2018: 3 · 2017: 1
FWCI
1.12
Type
journal article
Language
en
Open access
Locations
  • Molecular Psychiatry (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • Pure Amsterdam UMC (publishedVersion, other-oa)
  • EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • RODIN (Universidad de Cádiz) (acceptedVersion, cc-by-nc-nd)
  • Data Archiving and Networked Services (DANS) (submittedVersion)
  • EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
  • UCL Discovery (University College London) (submittedVersion)
  • Research Portal (King's College London) (submittedVersion, other-oa)
  • Amsterdam UMC (VU Amsterdam) - Institutional Repository (submittedVersion)
  • VU Research Portal (submittedVersion, other-oa)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
Funders
  • National Science Foundation
  • John Templeton Foundation
  • Eli Lilly and Company
  • Pfizer
  • South London and Maudsley NHS Foundation Trust
  • Maudsley Charity (TR130505)
  • National Institute for Health and Care Research
  • King's College London
  • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
  • Vrije Universiteit Amsterdam
  • Nederlandse Organisatie voor Wetenschappelijk Onderzoek (480- 05-003, VICI 453-14-005, NWO VICI 453-14-005, 453-14-005)
  • H. Lundbeck A/S
  • Medical Research Council (MR/M021475/1)
  • National Institute of Mental Health (U01MH109528, U01MH109536)
  • National Human Genome Research Institute
  • FP7 Ideas: European Research Council (295366)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
Keywords
intelligence, IQ, genetic loci, brain tissue expression, single-cell gene expression, pyramidal neurons, somatosensory cortex, hippocampal CA1, frontal cortex, intellectual disability
MeSH terms
Data Analysis, Brain, Cognition, Female, Frontal Lobe, Humans, Intelligence, Male, Temporal Lobe, Cohort Studies, Gene Expression, Pyramidal Cells, Genetic Predisposition to Disease, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Genetic Loci

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