Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence
Open accessAbstract
Danielle Posthuma and colleagues perform a large meta-analysis for intelligence and determine genetic overlap with several neuropsychiatric and metabolic traits. They find 15 new significant loci and implicate 40 new genes, most of which are predominantly expressed in the brain. Intelligence is associated with important economic and health-related life outcomes1. Despite intelligence having substantial heritability2 (0.54) and a confirmed polygenic nature, initial genetic studies were mostly underpowered3,4,5. Here we report a meta-analysis for intelligence of 78,308 individuals. We identify 336 associated SNPs (METAL P < 5 × 10−8) in 18 genomic loci, of which 15 are new. Around half of the SNPs are located inside a gene, implicating 22 genes, of which 11 are new findings. Gene-based analyses identified an additional 30 genes (MAGMA P < 2.73 × 10−6), of which all but one had not been implicated previously. We show that the identified genes are predominantly expressed in brain tissue, and pathway analysis indicates the involvement of genes regulating cell development (MAGMA competitive P = 3.5 × 10−6). Despite the well-known difference in twin-based heritability2 for intelligence in childhood (0.45) and adulthood (0.80), we show substantial genetic correlation (rg = 0.89, LD score regression P = 5.4 × 10−29). These findings provide new insight into the genetic architecture of intelligence.
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Genome-wide association studies to date suggest that hundreds to thousands of genes additively influence variation in intelligence, with the effect of any one gene being very small.
“Most genome-wide association studies (GWAS) to date have focused on intelligence or g [234–237], and suggest that hundreds to thousands of genes additively influence variation in intelligence, with the effect of any one gene being very small (typically in GWAS, a variant has r2 < 0.05% [238]).”
From The role of prefrontal cortex in cognitive control and executive function (2022) · cites this paper as [235]
The Abstract and letters section describe intelligence as polygenic, and the study identifies 52 associated genes through its SNP and gene-based analyses. Our copy does not establish that hundreds to thousands of genes influence intelligence, that their effects are additive, or that each gene’s effect is very small. The numerical variant-effect estimate is separately cited in the citing sentence. (LLM, conf=0.86)
Experimental — accuracy not yet measuredRecent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence.
“Recent genome-wide metaanalyses have identified 24 genomic loci linked to variation in intelligence 3-7”
From Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence (2018) · cites this paper as [5]
The Letters section reports that this genome-wide meta-analysis identified loci associated with intelligence, supporting the general point. It reports 18 independent significant loci, not 24; the cited paper alone therefore does not substantiate the sentence’s total across multiple studies. No page number is supplied in our copy. (LLM, conf=0.88)
Experimental — accuracy not yet measuredGWAS of educational attainment was conducted in a non-overlapping European subset of UKB (n = 188,435) who did not complete the intelligence measure.
“We conducted GWAS of educational attainment, an outcome with a high genetic correlation with intelligence 5 , in a non-overlapping European subset of the UKB sample (n = 188,435) who did not complete the intelligence measure.”
From Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence (2018) · cites this paper as [5]
The correlation of ASD PRS with higher educational attainment and IQ is opposite to what has been reported for PRS of other neurodevelopmental disorders.
“Surprisingly, multiple studies have found that PRS for ASD correlates with higher educational attainment and IQ in the population (Brainstorm Consortium et al., 2018), opposite to what has been reported for PRS of other neurodevelopmental disorders (Niemi et al., 2018; Sniekers et al., 2017).”
From Getting to the cores of autism (2019) · cites this paper as Sniekers et al., 2017
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Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625 · see citing works
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206 · see citing works
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072 · see citing works
Sudlow, C., Gallacher, J., Allen, N., Beral, V., Burton, P., Danesh, J., Downey, P., Elliott, P., Green, J., Landray, M., et al. (2015) · PLOS Medicine · doi:10.1371/journal.pmed.1001779 · Cited by 12,728 · see citing works
Genetics of Food Intake Self-Regulation in Childhood: Literature Review and Research Opportunities
Faith, M. S., Carnell, S., & Kral, T. V. E. (2013) · Human Heredity · doi:10.1159/000353879 · Cited by 7,628 · see citing works
Biological insights from 108 schizophrenia-associated genetic loci
Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014) · Nature · doi:10.1038/nature13595 · Cited by 7,577 · see citing works
Integrative analysis of 111 reference human epigenomes
Roadmap Epigenomics Consortium, Kundaje, A., Meuleman, W., Ernst, J., Bilenky, M., Yen, A., Heravi-Moussavi, A., Kheradpour, P., Zhang, Z., Wang, J., et al. (2015) · Nature · doi:10.1038/nature14248 · Cited by 6,368 · see citing works
A general framework for estimating the relative pathogenicity of human genetic variants
Kircher, M., Witten, D. M., Jain, P., O'Roak, B. J., Cooper, G. M., & Shendure, J. (2014) · Nature Genetics · doi:10.1038/ng.2892 · Cited by 6,183 · see citing works
The Reactome pathway Knowledgebase
Fabregat, A., Sidiropoulos, K., Garapati, P. V., Gillespie, M. E., Hausmann, K., Haw, R., Jassal, B., Jupe, S., Korninger, F., McKay, S., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1351 · Cited by 5,568 · see citing works
LD Score regression distinguishes confounding from polygenicity in genome-wide association studies
Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bulik-Sullivan, B. K., Loh, P.-R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., Daly, M. J., Price, A. L., & Neale, B. M. (2015) · Nature Genetics · doi:10.1038/ng.3211 · Cited by 5,559 · see citing works
METAL: fast and efficient meta-analysis of genomewide association scans
Willer, C. J., Li, Y., & Abecasis, G. R. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq340 · Cited by 5,205 · see citing works
The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans
The GTEx Consortium, Ardlie, K. G., Deluca, D. S., Segrè, A. V., Sullivan, T. J., Young, T. R., Gelfand, E. T., Trowbridge, C. A., Maller, J. B., Tukiainen, T., et al. (2015) · Science · doi:10.1126/science.1262110 · Cited by 5,062 · see citing works
Genetic studies of body mass index yield new insights for obesity biology
Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature · doi:10.1038/nature14177 · Cited by 4,534 · see citing works
Self-citationMAGMA: Generalized Gene-Set Analysis of GWAS Data
de Leeuw, C. A., Mooij, J. M., Heskes, T., & Posthuma, D. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004219 · Cited by 3,653 · see citing works
Self-citationAssociation analyses of 249,796 individuals reveal 18 new loci associated with body mass index
MAGIC, Speliotes, E. K., on behalf of Procardis Consortium, Willer, C. J., Berndt, S. I., Monda, K. L., Thorleifsson, G., Jackson, A. U., Allen, H. L., Lindgren, C. M., et al. (2010) · Nature Genetics · doi:10.1038/ng.686 · Cited by 2,912 · see citing works
Self-citationAnnotation of functional variation in personal genomes using RegulomeDB
Boyle, A. P., Hong, E. L., Hariharan, M., Cheng, Y., Schaub, M. A., Kasowski, M., Karczewski, K. J., Park, J., Hitz, B. C., Weng, S., et al. (2012) · Genome Research · doi:10.1101/gr.137323.112 · Cited by 2,722 · see citing works
LocusZoom: regional visualization of genome-wide association scan results
Pruim, R. J., Welch, R. P., Sanna, S., Teslovich, T. M., Chines, P. S., Gliedt, T. P., Boehnke, M., Abecasis, G. R., & Willer, C. J. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq419 · Cited by 2,707 · see citing works
A new multipoint method for genome-wide association studies by imputation of genotypes
Marchini, J., Howie, B., Myers, S., McVean, G., & Donnelly, P. (2007) · Nature Genetics · doi:10.1038/ng2088 · Cited by 2,609 · see citing works
ChromHMM: automating chromatin-state discovery and characterization
Ernst, J., & Kellis, M. (2012) · Nature Methods · doi:10.1038/nmeth.1906 · Cited by 2,489 · see citing works
Meta-analysis of the heritability of human traits based on fifty years of twin studies
Polderman, T. J. C., Benyamin, B., de Leeuw, C. A., Sullivan, P. F., van Bochoven, A., Visscher, P. M., & Posthuma, D. (2015) · Nature Genetics · doi:10.1038/ng.3285 · Cited by 2,467 · cited 5× · see citing works
“(2) UK Biobank touchscreen measure (UKB-ts; n = 36,257, non-overlapping with UKB-wb).”
BackgroundInfluentialthe GIANT Consortium (2009) · Nature Genetics · doi:10.1038/ng.287 · Cited by 1,720 · see citing works
Systematic identification of trans eQTLs as putative drivers of known disease associations
Westra, H.-J., Peters, M. J., Esko, T., Yaghootkar, H., Schurmann, C., Kettunen, J., Christiansen, M. W., Fairfax, B. P., Schramm, K., Powell, J. E., et al. (2013) · Nature Genetics · doi:10.1038/ng.2756 · Cited by 1,658 · see citing works
Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores
Vilhjálmsson, B. J., Yang, J., Finucane, H. K., Gusev, A., Lindström, S., Ripke, S., Genovese, G., Loh, P.-R., Bhatia, G., Do, R., et al. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.09.001 · Cited by 1,303 · see citing works
Self-citationGenome-wide association study identifies 74 loci associated with educational attainment
Okbay, A., Beauchamp, J. P., Fontana, M. A., Lee, J. J., Pers, T. H., Rietveld, C. A., Turley, P., Chen, G.-B., Emilsson, V., Meddens, S. F. W., et al. (2016) · Nature · doi:10.1038/nature17671 · Cited by 1,297 · see citing works
Self-citationThe neuroscience of human intelligence differences
Deary, I. J., Penke, L., & Johnson, W. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2793 · Cited by 1,038 · see citing works
FOXO3A genotype is strongly associated with human longevity
Willcox, B. J., Donlon, T. A., He, Q., Chen, R., Grove, J. S., Yano, K., Masaki, K. H., Willcox, D. C., Rodriguez, B., & Curb, J. D. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0801030105 · Cited by 983 · see citing works
Berndt, S. I., Gustafsson, S., Mägi, R., Ganna, A., Wheeler, E., Feitosa, M. F., Justice, A. E., Monda, K. L., Croteau-Chonka, D. C., Day, F. R., et al. (2013) · Nature Genetics · doi:10.1038/ng.2606 · Cited by 646 · see citing works
Self-citationGenome-wide association studies establish that human intelligence is highly heritable and polygenic
Davies, G., Tenesa, A., Payton, A., Yang, J., Harris, S. E., Liewald, D., Ke, X., Le Hellard, S., Christoforou, A., Luciano, M., et al. (2011) · Molecular Psychiatry · doi:10.1038/mp.2011.85 · Cited by 608 · see citing works
Self-citationAssociation of <i>FOXO3A</i> variation with human longevity confirmed in German centenarians
Flachsbart, F., Caliebe, A., Kleindorp, R., Blanché, H., von Eller-Eberstein, H., Nikolaus, S., Schreiber, S., & Nebel, A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0809594106 · Cited by 572 · see citing works
Genomic inflation factors under polygenic inheritance
Yang, J., Weedon, M. N., Purcell, S., Lettre, G., Estrada, K., Willer, C. J., Smith, A. V., Ingelsson, E., O’Connell, J. R., Mangino, M., et al. (2011) · European Journal of Human Genetics · doi:10.1038/ejhg.2011.39 · Cited by 560 · see citing works
Deary, I. J. (2012) · Annual Review of Psychology · doi:10.1146/annurev-psych-120710-100353 · Cited by 467 · see citing works
Disease variants alter transcription factor levels and methylation of their binding sites
Bonder, M. J., Luijk, R., Zhernakova, D. V., Moed, M., Deelen, P., Vermaat, M., van Iterson, M., van Dijk, F., van Galen, M., Bot, J. J., et al. (2016) · Nature Genetics · doi:10.1038/ng.3721 · Cited by 462 · see citing works
UK biobank data: come and get it
Allen, N. E., Sudlow, C., Peakman, T., Collins, R., & Biobank, O. B. O. U. (2014) · Science Translational Medicine · doi:10.1126/scitranslmed.3008601 · Cited by 399 · see citing works
Davies, G., Armstrong, N., Bis, J. C., Bressler, J., Chouraki, V, Giddaluru, S., Hofer, E., Ibrahim-Verbaas, C. A., Kirin, M., Lahti, J., et al. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.188 · Cited by 384 · see citing works
Self-citationComuzzie, A. G., Cole, S. A., Laston, S., Voruganti, V. S., Haack, K., Gibbs, R. A., & Butte, N. F. (2012) · PLoS ONE · doi:10.1371/journal.pone.0051954 · Cited by 383 · see citing works
Davies, G., Marioni, R. E., Liewald, D. C., Hill, W. D., Hagenaars, S. P., Harris, S. E., Ritchie, S. J., Luciano, M., Fawns-Ritchie, C., Lyall, D., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2016.45 · Cited by 373 · see citing works
Just one g: consistent results from three test batteries
Johnson, W., Bouchard, T. J., Krueger, R. F., McGue, M., & Gottesman, I. I. (2004) · Intelligence · doi:10.1016/s0160-2896(03)00062-x · Cited by 353 · see citing works
Self-citationWheeler, E., Huang, N., Bochukova, E. G., Keogh, J. M., Lindsay, S., Garg, S., Henning, E., Blackburn, H., Loos, R. J. F., Wareham, N. J., et al. (2013) · Nature Genetics · doi:10.1038/ng.2607 · Cited by 323 · see citing works
Most Reported Genetic Associations with General Intelligence Are Probably False Positives
Chabris, C., Hebert, B. M., Benjamin, D. J., Beauchamp, J., Cesarini, D., van der Loos, M., Johannesson, M., Magnusson, P., Lichtenstein, P., Atwood, C., et al. (2012) · Psychology Science · doi:10.1177/0956797611435528 · Cited by 301 · see citing works
Self-citationRietveld, C. A., Esko, T., Davies, G., Pers, T. H., Turley, P., Benyamin, B., Chabris, C. F., Emilsson, V., Johnson, A. D., Lee, J. J., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1404623111 · Cited by 258 · see citing works
Self-citationChildhood intelligence is heritable, highly polygenic and associated with FNBP1L
Benyamin, B., Pourcain, B., Davis, O. S. P., Davies, G., Hansell, N. K., Brion, M., Kirkpatrick, R. M., Cents, R. A. M., Franić, S., Miller, M. B., et al. (2013) · Molecular Psychiatry · doi:10.1038/mp.2012.184 · Cited by 258 · see citing works
Self-citationThe Epidemiology of Longevity and Exceptional Survival
Newman, A. B., & Murabito, J. M. (2013) · Epidemiologic Reviews · doi:10.1093/epirev/mxs013 · Cited by 128 · see citing works
CSE1L/CAS: Its role in proliferation and apoptosis
Behrens, P., Brinkmann, U., & Wellmann, A. (2003) · APOPTOSIS · doi:10.1023/a:1021644918117 · Cited by 112 · see citing works
The stability of g across different methods of estimation
Ree, M. J., & Earles, J. A. (1991) · Intelligence · doi:10.1016/0160-2896(91)90036-d · Cited by 93 · see citing works
2D Representation of Transcriptomes by t-SNE Exposes Relatedness between Human Tissues
Taskesen, E., & Reinders, M. J. T. (2016) · PLoS ONE · doi:10.1371/journal.pone.0149853 · Cited by 46 · see citing works
Self-citationEdwards, D. R. V., Naj, A. C., Monda, K. L., North, K. E., Neuhouser, M. L., Magvanjav, O., Kusimo, I., Vitolins, M. Z., Manson, J. E., O’Sullivan, M. J., et al. (2012) · Human Genetics · doi:10.1007/s00439-012-1246-3 · Cited by 45 · see citing works
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eQTLGen, Wray, N. R., 23andMe, the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Ripke, S., Mattheisen, M., Trzaskowski, M., Byrne, E. M., Abdellaoui, A., Adams, M. J., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0090-3 · Cited by 3,005 · see citing works
Self-citationIdentification of common genetic risk variants for autism spectrum disorder
Autism Spectrum Disorder Working Group of the Psychiatric Genomics Consortium, Grove, J., BUPGEN, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, 23andMe Research Team, Ripke, S., Als, T. D., Mattheisen, M., Walters, R. K., Won, H., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0344-8 · Cited by 2,421 · see citing works
23andMe Research Team, Lee, J. J., COGENT (Cognitive Genomics Consortium), Social Science Genetic Association Consortium, Wedow, R., Okbay, A., Kong, E., Maghzian, O., Zacher, M., Nguyen-Viet, T. A., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0147-3 · Cited by 2,470 · see citing works
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Analysis of shared heritability in common disorders of the brain
The Brainstorm Consortium, Anttila, V., Bulik-Sullivan, B., Finucane, H. K., Walters, R. K., Bras, J., Duncan, L., Escott-Price, V., Falcone, G. J., Gormley, P., et al. (2018) · Science · doi:10.1126/science.aap8757 · Cited by 1,924 · see citing works
Self-citationThe role of prefrontal cortex in cognitive control and executive function
Friedman, N. P., & Robbins, T. W. (2022) · Neuropsychopharmacology · doi:10.1038/s41386-021-01132-0 · Cited by 1,737 · see citing works
Genome-wide association study identifies 30 loci associated with bipolar disorder
eQTLGen Consortium, Stahl, E. A., BIOS Consortium, the Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Breen, G., Forstner, A. J., McQuillin, A., Ripke, S., Trubetskoy, V., Mattheisen, M., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0397-8 · Cited by 1,519 · see citing works
Self-citationSavage, J. E., Jansen, P. R., Stringer, S., Watanabe, K., Bryois, J., de Leeuw, C. A., Nagel, M., Awasthi, S., Barr, P. B., Coleman, J. R. I., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0152-6 · Cited by 1,443 · see citing works
Self-citationSanderson, E., Davey Smith, G., Windmeijer, F., & Bowden, J. (2019) · International Journal of Epidemiology · doi:10.1093/ije/dyy262 · Cited by 1,085 · see citing works
The genetic architecture of the human cerebral cortex
Grasby, K. L., Jahanshad, N., Painter, J. N., Colodro-Conde, L., Bralten, J., Hibar, D. P., Lind, P. A., Pizzagalli, F., Ching, C. R. K., McMahon, M. A. B., et al. (2020) · Science · doi:10.1126/science.aay6690 · Cited by 876 · see citing works
Self-citationComparative genetic architectures of schizophrenia in East Asian and European populations
Schizophrenia Working Group of the Psychiatric Genomics Consortium, Lam, M., Indonesia Schizophrenia Consortium, Genetic REsearch on schizophreniA neTwork-China and the Netherlands (GREAT-CN), Chen, C.-Y., Li, Z., Martin, A. R., Bryois, J., Ma, X., Gaspar, H., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0512-x · Cited by 655 · see citing works
Self-citationGenetic identification of brain cell types underlying schizophrenia
Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Skene, N. G., Bryois, J., Bakken, T. E., Breen, G., Crowley, J. J., Gaspar, H. A., Giusti-Rodriguez, P., Hodge, R. D., Miller, J. A., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0129-5 · Cited by 651 · see citing works
Self-citationA Single-Cell Transcriptomic Atlas of Human Neocortical Development during Mid-gestation
Polioudakis, D., de la Torre-Ubieta, L., Langerman, J., Elkins, A. G., Shi, X., Stein, J. L., Vuong, C. K., Nichterwitz, S., Gevorgian, M., Opland, C. K., et al. (2019) · Neuron · doi:10.1016/j.neuron.2019.06.011 · Cited by 513 · see citing works
The International League Against Epilepsy Consortium on Complex Epilepsies, Abou-Khalil, B., Auce, P., Avbersek, A., Bahlo, M., Balding, D. J., Bast, T., Baum, L., Becker, A. J., Becker, F., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-07524-z · Cited by 482 · see citing works
Rangaraju, S., Dammer, E. B., Raza, S. A., Rathakrishnan, P., Xiao, H., Gao, T., Duong, D. M., Pennington, M. W., Lah, J. J., Seyfried, N. T., et al. (2018) · Molecular Neurodegeneration · doi:10.1186/s13024-018-0254-8 · Cited by 430 · see citing works
Klimentidis, Y. C., Raichlen, D. A., Bea, J., Garcia, D. O., Wineinger, N. E., Mandarino, L. J., Alexander, G. E., Chen, Z., & Going, S. B. (2018) · International Journal of Obesity · doi:10.1038/s41366-018-0120-3 · Cited by 403 · see citing works
Modifiable pathways in Alzheimer’s disease: Mendelian randomisation analysis
Larsson, S. C., Traylor, M., Malik, R., Dichgans, M., Burgess, S., & Markus, H. S. (2017) · BMJ · doi:10.1136/bmj.j5375 · Cited by 382 · see citing works
Common genetic variants contribute to risk of rare severe neurodevelopmental disorders
Niemi, M. E. K., Martin, H. C., Rice, D. L., Gallone, G., Gordon, S., Kelemen, M., McAloney, K., McRae, J., Radford, E. J., Yu, S., et al. (2018) · Nature · doi:10.1038/s41586-018-0566-4 · Cited by 340 · see citing works
Hill, W. D., Marioni, R. E., Maghzian, O., Ritchie, S. J., Hagenaars, S. P., McIntosh, A. M., Gale, C. R., Davies, G., & Deary, I. J. (2019) · Molecular Psychiatry · doi:10.1038/s41380-017-0001-5 · Cited by 311 · see citing works
Tau Activation of Microglial cGAS–IFN Reduces MEF2C‐mediated Cognitive Resilience
Udeochu, J. C., Amin, S., Huang, Y., Fan, L., Torres, E. R. S., Carling, G. K., Liu, B., McGurran, H., Coronas-Samano, G., Kauwe, G., et al. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01315-6 · Cited by 289 · see citing works
Getting to the cores of autism
Iakoucheva, L. M., Muotri, A. R., & Sebat, J. (2019) · Cell · doi:10.1016/j.cell.2019.07.037 · Cited by 260 · see citing works
“, 2018), opposite to what has been reported for PRSs of other neurodevelopmental disorders (Niemi et al., 2018; Sniekers et al., 2017).”
ResultGenetic correlates of social stratification in Great Britain
Abdellaoui, A., Hugh-Jones, D., Yengo, L., Kemper, K. E., Nivard, M. G., Veul, L., Holtz, Y., Zietsch, B. P., Frayling, T. M., Wray, N. R., et al. (2019) · Nature Human Behaviour · doi:10.1038/s41562-019-0757-5 · Cited by 261 · see citing works
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Deary, I. J., Cox, S. R., & Hill, W. D. (2022) · Molecular Psychiatry · doi:10.1038/s41380-021-01027-y · Cited by 137 · see citing works
Walker, K. A., Chen, J., Shi, L., Yang, Y., Fornage, M., Zhou, L., Schlosser, P., Surapaneni, A., Grams, M. E., Duggan, M. R., et al. (2023) · Science Translational Medicine · doi:10.1126/scitranslmed.adf5681 · Cited by 148 · see citing works
Imprint of assortative mating on the human genome
Yengo, L., Robinson, M. R., Keller, M. C., Kemper, K. E., Yang, Y., Trzaskowski, M., Gratten, J., Turley, P., Cesarini, D., Benjamin, D. J., et al. (2018) · Nature Human Behaviour · doi:10.1038/s41562-018-0476-3 · Cited by 148 · see citing works
Self-citationGenetic and epigenetic regulation of human aging and longevity
Morris, B. J., Willcox, B. J., & Donlon, T. A. (2019) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2018.08.039 · Cited by 140 · see citing works
Davies, N. M., Hill, W. D., Anderson, E. L., Sanderson, E., Deary, I. J., & Davey Smith, G. (2019) · eLife · doi:10.7554/elife.43990 · Cited by 135 · see citing works
Social and non-social autism symptoms and trait domains are genetically dissociable
Warrier, V., Toro, R., Won, H., Leblond, C. S., Cliquet, F., Delorme, R., De Witte, W., Bralten, J., Chakrabarti, B., Børglum, A. D., et al. (2019) · Communications Biology · doi:10.1038/s42003-019-0558-4 · Cited by 94 · see citing works
Demontis, D., Walters, R. K., Rajagopal, V. M., Waldman, I. D., Grove, J., Als, T. D., Dalsgaard, S., Ribasés, M., Bybjerg-Grauholm, J., Bækvad-Hansen, M., et al. (2021) · Nature Communications · doi:10.1038/s41467-020-20443-2 · Cited by 50 · see citing works
A General Cognitive Ability Factor for the UK Biobank
Williams, C. M., Labouret, G., Wolfram, T., Peyre, H., & Ramus, F. (2023) · Behavior Genetics · doi:10.1007/s10519-022-10127-6 · Cited by 18 · see citing works
Genetic drivers of progression in Alzheimer’s disease are distinct from disease risk
Cohen, C. E., Fernandez, S., Yaman, U., Ehyaei, A. R., Kodosaki, E., Askarova, A., Porter, T., O’Brien, E., Study, A. I. B. A. L., Initiative, A. D. N., et al. (2026) · Alzheimer's Research & Therapy · doi:10.1186/s13195-026-02036-1 · Cited by 1 · see citing works
Genome-wide Analysis of Insomnia (N=1,331,010) Identifies Novel Loci and Functional Pathways
Jansen, P. R., Watanabe, K., Stringer, S., Skene, N., Bryois, J., Hammerschlag, A. R., de Leeuw, C. A., Benjamins, J., Muñoz-Manchado, A. B., Nagel, M., et al. (2018) · doi:10.1101/214973 · Cited by 860 · see citing works
Self-citation
- Authors
- Sniekers, S., Stringer, S., Watanabe, K., Jansen, P. R., Coleman, J. R. I., Krapohl, E., Taskesen, E., Hammerschlag, A. R., Okbay, A., Zabaneh, D., Amin, N., Breen, G., Cesarini, D., Chabris, C. F., Iacono, W. G., Ikram, M. A., Johannesson, M., Koellinger, P., Lee, J. J., Magnusson, P. K. E., McGue, M., Miller, M. B., Ollier, W. E. R., Payton, A., Pendleton, N., Plomin, R., Rietveld, C. A., Tiemeier, H., van Duijn, C. M., & Posthuma, D.
- Affiliations
- Amsterdam Neuroscience (NL)
- Erasmus MC (NL)
- King's College London (GB)
- New York University (US)
- Union College (US)
- University of Minnesota (US)
- Stockholm School of Economics (SE)
- Karolinska Institutet (SE)
- University of Manchester (GB)
- Manchester Academic Health Science Centre (GB)
- Erasmus University Rotterdam (NL)
- ORCID
- Stringer, Sven
- Watanabe, Kyoko
- Jansen, Philip R
- Coleman, Jonathan R I
- Krapohl, Eva
- Taskesen, Erdogan
- Hammerschlag, Anke R
- Okbay, Aysu
- Zabaneh, Delilah
- Amin, Najaf
- Breen, Gerome
- Cesarini, David
- Iacono, William G
- Ikram, M Arfan
- Johannesson, Magnus
- Koellinger, Philipp
- Lee, James J
- Magnusson, Patrik K E
- McGue, Matt
- Ollier, William E R
- Payton, Antony
- Pendleton, Neil
- Plomin, Robert
- Rietveld, Cornelius A
- Tiemeier, Henning
- Posthuma, Danielle
- Venue
- Nature Genetics
- Published
- 2017-05-22
- Volume
- 49
- Issue
- 7
- Pages
- 1107-1112
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC5665562
- OpenAlex
- W2940205897
- Semantic Scholar
- 2eaf0b9c66415e30a933ef121c6b80aec6b9c947
- Cited by
- 490
- References
- 46
- Citations by year
- 2026: 13 · 2025: 34 · 2024: 39 · 2023: 53 · 2022: 32 · 2021: 54 · 2020: 98 · 2019: 65 · 2018: 82 · 2017: 20
- FWCI
- 9.32
- Type
- journal article
- Language
- en
- Update notices
- erratum (2017-10-01)
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature Genetics (publishedVersion, other-oa)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (publishedVersion, cc-by)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
- VU Research Portal (publishedVersion, other-oa)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- e-space (Manchester Metropolitan University) (acceptedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- RePub (Erasmus University Rotterdam) (submittedVersion, other-oa)
- Figshare (submittedVersion)
- Research Portal (King's College London) (submittedVersion, other-oa)
- Research Explorer (The University of Manchester) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- Vrije Universiteit Amsterdam
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (480- 05-003, VICI 453-14-005, NWO VICI 453-14-005, 453-13-005, 453-14-005)
- Medical Research Council (MR/K002279/1, MR/M021475/1)
- Biotechnology and Biological Sciences Research Council (BB/F022441/1)
- National Institute on Alcohol Abuse and Alcoholism (R01AA009367, R37AA009367, R01AA011886)
- National Institute on Aging (T32AG000186)
- National Institute of Mental Health (R01MH066140, T32MH016880)
- National Institute on Drug Abuse (F31DA029377, R01DA013240, R01DA024417, R01DA005147, R01DA036216, R37DA005147)
- National Institute of Diabetes and Digestive and Kidney Diseases (U01DK066134)
- 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, polygenic risk, genetic loci, single nucleotide polymorphisms, brain gene expression, neuropsychiatric traits, metabolic phenotypes, genetic correlation, heritability, cell development, genetic architecture
- MeSH terms
- Adolescent, Adult, Aged, Brain, Child, Child, Preschool, Female, Humans, Infant, Intelligence, Male, Middle Aged, Nerve Tissue Proteins, Linkage Disequilibrium, Polymorphism, Single Nucleotide, White People, Genome-Wide Association Study, Young Adult
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