GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium
Open accessAbstract
The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P<5 × 10−8). Gene-based analysis identified an additional three Bonferroni-corrected significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e.=0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness.
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Most of the inflation (λGC = 1.92) could be explained by polygenic signal.
“indicated that most of the inflation (λ GC = 1.92) could be explained by polygenic signal 6”
From Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence (2018) · cites this paper as [6]
In Results, under “GWAS of general cognitive function,” the paper says polygenicity accounted for most of the increase in the mean χ² statistic. But it reports λGC = 1.12, not 1.92. (LLM, conf=0.92)
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 [6]
The Results (GWAS of general cognitive function; page unavailable) report two genome-wide-significant loci, supporting the claim that a meta-analysis identified loci associated with cognitive performance. The Abstract reports that 24 is the number of cohorts studied, not the number of loci identified; it also reports three additional loci from gene-based analysis. This source therefore does not support the count of 24 genomic loci. (LLM, conf=0.90)
Experimental — accuracy not yet measuredIn healthy individuals, studies that have focused on global abilities have found robust genomic correlates of global cognitive performance defined with both intelligence and neurocognitive tests.
“in healthy individuals, studies that have focused on global abilities have found robust genomic correlates of global cognitive performance defined with both intelligence and neurocognitive tests. 68”
From Domains of cognition and their assessment (2019) · cites this paper as [68]
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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
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-citationDomains of cognition and their assessment
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Self-citationThe new genetics of intelligence
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Self-citationLandslide recognition : identification, movement and courses
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Genome-wide analysis identifies molecular systems and 149 genetic loci associated with income
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Self-citationTaylor, M. J., Martin, J., Lu, Y., Brikell, I., Lundström, S., Larsson, H., & Lichtenstein, P. (2019) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2018.3652 · Cited by 174 · see citing works
Resource profile and user guide of the Polygenic Index Repository
Becker, J., Burik, C. A. P., Goldman, G., Wang, N., Jayashankar, H., Bennett, M., Belsky, D. W., Linnér, R. K., Ahlskog, R., Kleinman, A., et al. (2021) · Nature Human Behaviour · doi:10.1038/s41562-021-01119-3 · Cited by 171 · see citing works
Genomic prediction of cognitive traits in childhood and adolescence
Allegrini, A. G., Selzam, S., Rimfeld, K., von Stumm, S., Pingault, J., & Plomin, R. J. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0394-4 · Cited by 171 · see citing works
Large and fast human pyramidal neurons associate with intelligence
Goriounova, N. A., Heyer, D. B., Wilbers, R., Verhoog, M. B., Giugliano, M., Verbist, C., Obermayer, J., Kerkhofs, A., Smeding, H. M. M., Verberne, M., et al. (2018) · eLife · doi:10.7554/elife.41714 · Cited by 162 · see citing works
Genome-wide association study identifies 48 common genetic variants associated with handedness
Cuéllar-Partida, G., Tung, J. Y., Eriksson, N., Albrecht, E., Alıev, F., Andreassen, O. A., Barroso, I., Beckmann, J. S., Boks, M. P., Boomsma, D. I., et al. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-00956-y · Cited by 161 · see citing works
Self-citationGill, D., Efstathiadou, A., Cawood, K., Tzoulaki, I., & Dehghan, A. (2019) · International Journal of Epidemiology · doi:10.1093/ije/dyz200 · Cited by 151 · see citing works
Zhao, B., Zhang, J., Ibrahim, J. G., Luo, T., Santelli, R., Li, Y., Li, T., Shan, Y., Zhu, Z., Zhou, F., et al. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0569-z · Cited by 141 · see citing works
Are specific learning disorders truly specific, and are they disorders?
Peters, L., & Ansari, D. (2019) · Trends in Neuroscience and Education · doi:10.1016/j.tine.2019.100115 · Cited by 151 · see citing works
Genetic variation, brain, and intelligence differences
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Self-citationGenes, Cells and Brain Areas of Intelligence
Goriounova, N. A., & Mansvelder, H. D. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2019.00044 · Cited by 141 · see citing works
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Self-citationThalamic Reticular Dysfunction as a Circuit Endophenotype in Neurodevelopmental Disorders
Krol, A., Wimmer, R. D., Halassa, M. M., & Feng, G. (2018) · Neuron · doi:10.1016/j.neuron.2018.03.021 · Cited by 117 · see citing works
Lam, M., Hill, W. D., Trampush, J. W., Yu, J., Knowles, E., Davies, G., Stahl, E. A., Huckins, L. M., Liewald, D. C. M., Djurovic, S., et al. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.06.012 · Cited by 113 · see citing works
Self-citationGenomics and psychological resilience: a research agenda
Choi, K. W., Stein, M. B., Dunn, E. C., Koenen, K. C., & Smoller, J. W. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0457-6 · Cited by 102 · see citing works
Wu, Z., Phyo, A. Z. Z., Alharbi, T., Woods, R. L., & Ryan, J. L. (2020) · Journal of Alzheimer s Disease Reports · doi:10.3233/adr-200232 · Cited by 100 · see citing works
Polygenic risk score increases schizophrenia liability through cognition-relevant pathways
Toulopoulou, T., Zhang, X., Cherny, S. S., Dickinson, D., Berman, K. F., Straub, R. E., Sham, P. C., & Weinberger, D. R. (2018) · Brain · doi:10.1093/brain/awy279 · Cited by 98 · see citing works
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Uhl, G. R., & Martinez, M. J. (2019) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.14002 · Cited by 90 · see citing works
Genetic Markers of ADHD-Related Variations in Intracranial Volume
Klein, M., Walters, R. K., Demontis, D., Stein, J. L., Hibar, D. P., Adams, H. H. H., Bralten, J., Mota, N. R., Schachar, R. J., Sonuga-Barke, E. J. S., et al. (2019) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2018.18020149 · Cited by 89 · see citing works
Twin studies to GWAS: there and back again
Friedman, N. P., Banich, M. T., & Keller, M. C. (2021) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2021.06.007 · Cited by 83 · see citing works
Self-citationWang, Y., Ye, C., Kong, L., Zheng, J., Xu, M., Xu, Y., Li, M., Zhao, Z., Lu, J., Chen, Y., et al. (2022) · Hypertension · doi:10.1161/hypertensionaha.122.20286 · Cited by 83 · see citing works
Yang, Z., Zhou, D., Li, H., Cai, X. M., Liu, W., Wang, L., Chang, H., Li, M., & Xiao, X. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0592-0 · Cited by 82 · see citing works
Recent Advances in the Genetics of Schizophrenia
Avramopoulos, D. (2018) · Complex Psychiatry · doi:10.1159/000488679 · Cited by 80 · see citing works
Self-citationHarris, S. E., Cox, S. R., Bell, S., Marioni, R. E., Prins, B. P., Pattie, A., Corley, J., Maniega, S. M., Hernández, M. D. C. V., Morris, Z., et al. (2020) · Nature Communications · doi:10.1038/s41467-019-14161-7 · Cited by 78 · see citing works
Self-citationGurney, M. E., Nugent, R. A., Mo, X., Sindac, J. A., Hagen, T. J., Fox, D. N. A., O’Donnell, J. M., Zhang, C., Xu, Y., Zhang, H., et al. (2019) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.9b00193 · Cited by 78 · see citing works
Xu, Q., Guo, L., Cheng, J., Wang, M., Geng, Z., Zhu, W., Zhang, B., Liao, W., Qiu, S., Zhang, H., et al. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0627-6 · Cited by 76 · see citing works
Shafee, R., Nanda, P., Padmanabhan, J. L., Tandon, N., Alliey‐Rodriguez, N., Kalapurakkel, S. S., Weiner, D. J., Gur, R. E., Keefe, R. S. E., Hill, S. K., et al. (2018) · Translational Psychiatry · doi:10.1038/s41398-018-0124-8 · Cited by 69 · see citing works
Wang, W., Corominas, R., & Lin, G. N. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00258 · Cited by 70 · see citing works
New considerations for hiPSC-based models of neuropsychiatric disorders
Hoffman, G. E., Schrode, N., Flaherty, E. K., & Brennand, K. (2018) · Molecular Psychiatry · doi:10.1038/s41380-018-0029-1 · Cited by 65 · see citing works
The Neurodevelopmental Hypothesis of Huntington’s Disease
van der Plas, E. A. A., Schultz, J. L., & Nopoulos, P. (2020) · Journal of Huntington s Disease · doi:10.3233/jhd-200394 · Cited by 65 · see citing works
Martschenko, D. O., Trejo, S., & Domingue, B. W. (2019) · AERA Open · doi:10.1177/2332858418810516 · Cited by 64 · see citing works
Genetic Overlap between General Cognitive Function and Schizophrenia: A Review of Cognitive GWASs
Ohi, K., Sumiyoshi, C., Fujino, H., Yasuda, Y., Yamamori, H., Fujimoto, M., Shiino, T., Sumiyoshi, T., & Hashimoto, R. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19123822 · Cited by 62 · see citing works
Efstathiadou, A., Gill, D., McGrane, F., Quinn, T. J., & Dawson, J. (2019) · Journal of the American Heart Association · doi:10.1161/jaha.119.012738 · Cited by 62 · see citing works
Comes, A. L., Senner, F., Budde, M., Adorjan, K., Anderson‐Schmidt, H., Andlauer, T. F. M., Gade, K., Heilbronner, M., Heilbronner, U., Kalman, J. L., et al. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0547-x · Cited by 78 · see citing works
Effects of polygenic risk for Alzheimer’s disease on rate of cognitive decline in normal aging
Kauppi, K., Rönnlund, M., Adolfsson, A. N., Pudas, S., & Adolfsson, R. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-00934-y · Cited by 57 · see citing works
Effect of Trinucleotide Repeats in the Huntington's Gene on Intelligence
Lee, J. K., Conrad, A. L., Epping, E. A., Mathews, K. D., Magnotta, V. A., Dawson, J. D., & Nopoulos, P. (2018) · EBioMedicine · doi:10.1016/j.ebiom.2018.03.031 · Cited by 55 · see citing works
Rosoff, D. B., Kaminsky, Z. A., McIntosh, A. M., Smith, G. D., & Lohoff, F. W. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-01047-2 · Cited by 59 · see citing works
Hu, Y., Zhang, Y., Zhang, H., Gao, S., Wang, L., Wang, T., Han, Z., Sun, B., & Liu, G. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01695-4 · Cited by 47 · see citing works
Ohi, K., Sumiyoshi, C., Fujino, H., Yasuda, Y., Yamamori, H., Fujimoto, M., Sumiyoshi, T., & Hashimoto, R. (2017) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2017.00293 · Cited by 48 · see citing works
Mallet, J., Strat, Y. L., Dubertret, C., & Gorwood, P. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9020341 · Cited by 42 · see citing works
Multivariate genome-wide analysis of education, socioeconomic status and brain phenome
Wendt, F. R., Pathak, G. A., Lencz, T., Krystal, J. H., Gelernter, J. E., & Polimanti, R. A. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-00980-y · Cited by 49 · see citing works
Self-citationOhi, K., Shimada, T., Nemoto, K., Kataoka, Y., Yasuyama, T., Kimura, K., Okubo, H., Uehara, T., & Kawasaki, Y. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.08.008 · Cited by 46 · see citing works
Li, H., Qu, N., Hui, L., Cai, X. M., Zhang, C., Zhong, B., Zhang, S.-F., Chen, J., Xia, B., Wang, L., et al. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-0777-y · Cited by 44 · see citing works
Thalamuthu, A., Mills, N. T., Berger, K., Minnerup, H., Grotegerd, D., Dannlowski, U., Meinert, S. L., Opel, N., Repple, J., Gruber, M., et al. (2021) · Molecular Psychiatry · doi:10.1038/s41380-021-01379-5 · Cited by 44 · see citing works
Self-citationEndophenotypes in Schizophrenia: Digging Deeper to Identify Genetic Mechanisms
Greenwood, T. A., Shutes‐David, A., & Tsuang, D. W. (2019) · Journal of Psychiatry and Brain Science · doi:10.20900/jpbs.20190005 · Cited by 44 · see citing works
Hervé, M., Bergon, A., Guisquet, A. L., Leman, S., Consoloni, J.-L., Fernandez, N., Lefebvre, M., El‐Hage, W., Belzeaux-R, R., Belzung, C., et al. (2017) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2017.00248 · Cited by 40 · see citing works
Wang, X., Cheng, W., Zhu, J. L., Yin, H., Chang, S., Yue, W., & Yu, H. (2019) · Journal of Affective Disorders · doi:10.1016/j.jad.2019.11.116 · Cited by 39 · see citing works
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Klaus, K., Butler, K., Curtis, F., Bridle, C., & Pennington, K. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.01.021 · Cited by 39 · see citing works
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Low-frequency variation in TP53 has large effects on head circumference and intracranial volume
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Genetic insights into the causal relationship between physical activity and cognitive functioning
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Dimensional and transdiagnostic phenotypes in psychiatric genome-wide association studies
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Self-citationXavier, R. M., Dungan, J. R., Keefe, R. S. E., & Vorderstrasse, A. A. (2018) · Schizophrenia Research Cognition · doi:10.1016/j.scog.2018.01.001 · Cited by 29 · see citing works
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Cognitive genomics: Searching for the genetic roots of neuropsychological functioning.
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Self-citationGenetic Association of Phosphodiesterases With Human Cognitive Performance
Gurney, M. E. (2019) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2019.00022 · Cited by 25 · see citing works
Shin, J., Ma, S., Hofer, E., Patel, Y., Vosberg, D. E., Tilley, S., Roshchupkin, G. V., Sousa, A. M. M., Jian, X., Gottesman, R., et al. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa035 · Cited by 25 · see citing works
Self-citationIdentifying nootropic drug targets via large-scale cognitive GWAS and transcriptomics
Lam, M., Chen, C., Ge, T., Xia, Y., Hill, D. W., Trampush, J. W., Yu, J., Knowles, E., Davies, G., Stahl, E. A., et al. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-021-01023-4 · Cited by 23 · see citing works
Self-citationOatman, S. R., Reddy, J. S., Quicksall, Z., Carrasquillo, M. M., Wang, X., Liu, C., Yamazaki, Y., Nguyen, T., Malphrus, K. G., Heckman, M. G., et al. (2023) · Molecular Neurodegeneration · doi:10.1186/s13024-022-00592-2 · Cited by 25 · see citing works
Gut microbiota and cognitive performance: A bidirectional two-sample Mendelian randomization
Wang, Q., Song, Y.-X., Wu, X., Luo, Y.-G., Miao, R., Yu, X.-M., Guo, X., Wu, D.-Z., Bao, R., Mi, W., et al. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.02.083 · Cited by 24 · see citing works
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Thomas, T., Koomar, T., Casten, L. G., Tener, A. J., Bahl, E., & Michaelson, J. J. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-01982-2 · Cited by 24 · see citing works
Metabolic Profiling of Cognitive Aging in Midlife
Huo, Z., Rana, B. K., Elman, J. A., Dong, R., Engelman, C. D., Johnson, S. C., Lyons, M. J., Franz, C. E., Kremen, W. S., & Zhao, J. (2020) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2020.555850 · Cited by 20 · see citing works
Longitudinal change in memory performance as a strong endophenotype for Alzheimer's disease
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Cohort profile: Genetic data in the German Socio-Economic Panel Innovation Sample (SOEP-G)
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Self-citationIntelligence decline across major depressive disorder, bipolar disorder, and schizophrenia
Ohi, K., Takai, K., Sugiyama, S., Kitagawa, H., Kataoka, Y., Soda, M., Kitaichi, K., Kawasaki, Y., Ito, M., & Shioiri, T. (2021) · CNS Spectrums · doi:10.1017/s1092852921000298 · Cited by 19 · see citing works
Habtewold, T. D., Liemburg, E. J., Islam, M. A., de Zwarte, S. M. C., Boezen, H. M., Luykx, J. J., Rutten, B. P. F., van Winkel, R., van Amelsvoort, T., Bartels‐Velthuis, A. A., et al. (2020) · Schizophrenia Research · doi:10.1016/j.schres.2020.05.020 · Cited by 20 · see citing works
Jian, X., Sofer, T., Tarraf, W., Bressler, J., Faul, J. D., Zhao, W., Ratliff, S. M., Lamar, M., Launer, L. J., Laurie, C. C., et al. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-00930-2 · Cited by 20 · see citing works
Lutz, M. W., Casanova, R., Saldana, S. J., Kuchibhatla, M. N., Plassman, B. L., & Hayden, K. M. (2019) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2018.10.028 · Cited by 19 · see citing works
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Liang, J., Cai, H., Liang, G., Liu, Z., Fang, L., Zhu, B., Liu, B., & Zhang, H. (2021) · Acta Diabetologica · doi:10.1007/s00592-020-01647-w · Cited by 18 · see citing works
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Multivariate Pattern Analysis of Genotype–Phenotype Relationships in Schizophrenia
Zheutlin, A. B., Chekroud, A. M., Polimanti, R. A., Gelernter, J. E., Sabb, F. W., Bilder, R. M., Freimer, N. B., London, E. D., Hultman, C. M., & Cannon, T. D. (2018) · Schizophrenia Bulletin · doi:10.1093/schbul/sby005 · Cited by 16 · see citing works
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Establishing the Brief Assessment of Cognition - Short form
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- Authors
- Trampush, J. W., Yang, M. L. Z., Yu, J., Knowles, E., Davies, G., Liewald, D. C., Starr, J. M., Djurovic, S., Melle, I., Sundet, K., Christoforou, A., Reinvang, I., DeRosse, P., Lundervold, A. J., Steen, V. M., Espeseth, T., Räikkönen, K., Widen, E., Palotie, A., Eriksson, J. G., Giegling, I., Konte, B., Roussos, P., Giakoumaki, S., Burdick, K. E., Payton, A., Ollier, W., Horan, M., Chiba-Falek, O., Attix, D. K., Need, A. C., Cirulli, E. T., Voineskos, A. N., Stefanis, N. C., Avramopoulos, D., Hatzimanolis, A., Arking, D. E., Smyrnis, N., Bilder, R. M., Freimer, N. A., Cannon, T. D., London, E., Poldrack, R. A., Sabb, F. W., Congdon, E., Conley, E. D., Scult, M. A., Dickinson, D., Straub, R. E., Donohoe, G., Morris, D., Corvin, A., Gill, M., Hariri, A. R., Weinberger, D. R., Pendleton, N., Bitsios, P., Rujescu, D., Lahti, J., Le Hellard, S., Keller, M. C., Andreassen, O. A., Deary, I. J., Glahn, D. C., Malhotra, A. K., & Lencz, T.
- Affiliations
- Zucker Hillside Hospital (US)
- Institute of Mental Health (SG)
- Feinstein Institute for Medical Research (US)
- Yale University (US)
- University of Edinburgh (GB)
- Alzheimer Scotland (GB)
- Oslo University Hospital (NO)
- Haukeland University Hospital (NO)
- University of Oslo (NO)
- University of Bergen (NO)
- University of Helsinki (FI)
- Martin Luther University Halle-Wittenberg (DE)
- New York/New Jersey VA Health Care Network (US)
- University of Crete (GR)
- Manchester Academic Health Science Centre (GB)
- University of Manchester (GB)
- Duke University (US)
- Imperial College London (GB)
- Centre for Addiction and Mental Health (CA)
- National and Kapodistrian University of Athens (GR)
- Johns Hopkins University (US)
- University of California, Los Angeles (US)
- Stanford University (US)
- University of Oregon (US)
- 23andMe (United States) (US)
- National Institutes of Health (US)
- Ollscoil na Gaillimhe – University of Galway (IE)
- Trinity College Dublin (IE)
- University of Colorado Boulder (US)
- Corresponding author
- Lencz, T
- ORCID
- Trampush, J W
- Yu, J
- Davies, G
- Liewald, D C
- Starr, J M
- Djurovic, S
- Sundet, K
- DeRosse, P
- Lundervold, A J
- Espeseth, T
- Räikkönen, K
- Palotie, A
- Eriksson, J G
- Giegling, I
- Konte, B
- Roussos, P
- Giakoumaki, S
- Burdick, K E
- Payton, A
- Ollier, W
- Attix, D K
- Need, A C
- Cirulli, E T
- Voineskos, A N
- Stefanis, N C
- Avramopoulos, D
- Arking, D E
- Smyrnis, N
- Bilder, R M
- Cannon, T D
- Poldrack, R A
- Sabb, F W
- Congdon, E
- Scult, M A
- Dickinson, D
- Straub, R E
- Donohoe, G
- Morris, D
- Corvin, A
- Gill, M
- Hariri, A R
- Weinberger, D R
- Pendleton, N
- Rujescu, D
- Lahti, J
- Keller, M C
- Andreassen, O A
- Deary, I J
- Glahn, D C
- Malhotra, A K
- Lencz, T
- Venue
- Molecular Psychiatry
- Published
- 2017-01-17
- Volume
- 22
- Issue
- 3
- Pages
- 336-345
- ISSN
- 1359-4184 (ISSN-L)
- 1476-5578
- PMC
- PMC5322272
- OpenAlex
- W2575342665
- Cited by
- 271
- References
- 76
- Citations by year
- 2026: 13 · 2025: 22 · 2024: 33 · 2023: 30 · 2022: 21 · 2021: 25 · 2020: 37 · 2019: 40 · 2018: 33 · 2017: 16
- FWCI
- 22.87
- Type
- journal article
- Language
- en
- Update notices
- erratum (2017-09-12)
- Open access
- hybrid
- doi.org
- Locations
- Molecular Psychiatry (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- ARAN (University of Galway Research Repository) (Ollscoil na Gaillimhe – University of Galway) (acceptedVersion, cc-by-nc-nd)
- Työväentutkimus Vuosikirja (submittedVersion, cc-by)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- Arrow@dit (Dublin Institute of Technology) (submittedVersion, cc-by-nc-sa)
- Arrow@dit (Dublin Institute of Technology) (submittedVersion)
- ARAN (University of Galway Research Repository) (Ollscoil na Gaillimhe – University of Galway) (submittedVersion, cc-by-nc-nd)
- NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
- eScholarship (California Digital Library) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- Research Explorer (The University of Manchester) (submittedVersion, other-oa)
- University of Galway Research Repository (submittedVersion, cc-by-nc)
- Spiral (Imperial College London) (submittedVersion)
- Trinity's Access to Research Output (TARA) (Trinity College Dublin) (submittedVersion)
- STM:n Hallinnonalan avoin julkaisuarkisto (Julkari) (submittedVersion)
- Research Repository UCD (University College Dublin) (cc-by-nc)
- WOS
- Funders
- National Science Foundation
- Ellison Medical Foundation (AG‐NS‐0441‐08)
- Helsingin Yliopisto
- Finska Läkaresällskapet
- Centre for Addiction and Mental Health Foundation
- Folkhälsanin Tutkimussäätiö
- University of Edinburgh (MR/K026992/1, LBC1936)
- Science Foundation Ireland (12/IP/1359, 08/IN.1/B1916, 12/IP/1670)
- Academy of Finland
- Novo Nordisk
- Helse Vest
- Signe ja Ane Gyllenbergin Säätiö
- Emil Aaltosen Säätiö
- Samfundet Folkhälsan
- Universitetet i Bergen
- Norges Forskningsråd (154313/V50, 177458, 177458/V50)
- Bergens Forskningsstiftelse
- Centre for Cognitive Ageing and Cognitive Epidemiology (MR/K026992/1)
- National Institutes of Health (n01hc085082-026, n01hc085081-021, 5u01da024417-02, n01hc085079-024, 1ul1rr033176-01, n01hc085083-027, n01hc085080-026, UL1TR000124, n01hc65226-6-0-0, LBC1936, n01hc085086-022, n01hc25195-41-0-1, n01hc55222-0-0-0, n02hl64278-6-0-0, n01hc075150-004, AG049789)
- Directorate for Biological Sciences
- Canadian Institutes of Health Research (15431_3)
- Medical Research Council (MR/K026992/1, LBC1936)
- Biotechnology and Biological Sciences Research Council (BB/F022441/1, MR/K026992/1, BB/F019394/1, F019394/1, LBC1936)
- National Institute on Aging (R01AG023629, R01AG049789)
- National Heart, Lung, and Blood Institute (N01-HC-85081, N01-HC-65226, N01HC-85083, N01‐HC25195, N01HC85082, N01HC‐75150, HHSN268201500001I, N01 HC85086, HHSN 268200800007C, N01HC85080, N02- HL-64278, N01 HC55222, HHSN268201200036C, U01HL080295, N01-HC85079)
- National Institute of Mental Health (RC2MH089983, PL1MH083271, R01MH100141, R01MH092515, K23MH077807, R01MH085018, R01MH080912, MH080912, RC2MH089924, MH080173, K01MH085812, RL1MH083269, P50MH080173, MH085812, K01MH098126, MH077807, R01MH079800)
- National Institute on Drug Abuse (U01-DA024417, RL1DA024853, R01DA033369)
- National Institute of Neurological Disorders and Stroke (PL1NS062410)
- National Institute of Dental and Craniofacial Research (UL1DE019580)
- National Center for Research Resources (UL1-RR-033176)
- National Center for Advancing Translational Sciences
- 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
- general intelligence, cognitive performance, genetic loci, single nucleotide polymorphisms, polygenic risk score, educational attainment, CENPO, SNP heritability, smoking behavior, openness to experience, personality traits, mental illness
- MeSH terms
- Adult, Alleles, Cognition, Female, Gene Frequency, Humans, Male, Middle Aged, Genetic Variation, Neurocognitive Disorders, Genetic Predisposition to Disease, Multifactorial Inheritance, Polymorphism, Single Nucleotide, White People, Genome-Wide Association Study, Genetic Loci, Genetic Association Studies
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