Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Novel genetic loci underlying human intracranial volume identified through genome-wide association

Abstract

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five previously unknown loci for intracranial volume and confirmed two known signals. Four of the loci were also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρgenetic = 0.748), which indicates a similar genetic background and allowed us to identify four additional loci through meta-analysis (Ncombined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, and Parkinson's disease, and were enriched near genes involved in growth pathways, including PI3K-AKT signaling. These findings identify the biological underpinnings of intracranial volume and their link to physiological and pathological traits.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Purchase on Springer Link

Instant access to full article PDF

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Common genetic variants associated with intracranial volume.
Figure 2: Regional association and functional annotation of previously unknown genome-wide significant loci.
Figure 3: Meta-analysis of intracranial volume and child head circumference.
Figure 4: Enrichment analyses of common variants associated with intracranial volume.
Figure 5: Temporal trends of intracranial volume loci during pre- and postnatal brain development.

Similar content being viewed by others

References

  1. Bartley, A.J., Jones, D.W. & Weinberger, D.R. Genetic variability of human brain size and cortical gyral patterns. Brain 120, 257–269 (1997).

    Article  PubMed  Google Scholar 

  2. Davis, P.J.M. & Wright, E.A. A new method for measuring cranial cavity volume and its application to the assessment of cerebral atrophy at autopsy. Neuropathol. Appl. Neurobiol. 3, 341–358 (1977).

    Article  Google Scholar 

  3. Sgouros, S., Goldin, J.H., Hockley, A.D., Wake, M.J. & Natarajan, K. Intracranial volume change in childhood. J. Neurosurg. 91, 610–616 (1999).

    Article  CAS  PubMed  Google Scholar 

  4. Buckner, R.L. et al. A unified approach for morphometric and functional data analysis in young, old and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume. Neuroimage 23, 724–738 (2004).

    Article  PubMed  Google Scholar 

  5. Farias, S.T. et al. Maximal brain size remains an important predictor of cognition in old age, independent of current brain pathology. Neurobiol. Aging 33, 1758–1768 (2012).

    Article  PubMed  Google Scholar 

  6. Ikram, M.A. et al. Common variants at 6q22 and 17q21 are associated with intracranial volume. Nat. Genet. 44, 539–544 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Stein, J.L. et al. Identification of common variants associated with human hippocampal and intracranial volumes. Nat. Genet. 44, 552–561 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Hibar, D.P. et al. Common genetic variants influence human subcortical brain structures. Nature 520, 224–229 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Paus, T. et al. KCTD8 gene and brain growth in adverse intrauterine environment: a genome-wide association study. Cereb. Cortex 22, 2634–2642 (2012).

    Article  PubMed  Google Scholar 

  10. Psaty, B.M. et al. Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium: design of prospective meta-analyses of genome-wide association studies from 5 cohorts. Circ Cardiovasc Genet 2, 73–80 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Thompson, P.M. et al. The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data. Brain Imaging Behav. 8, 153–182 (2014).

    PubMed  PubMed Central  Google Scholar 

  12. Bulik-Sullivan, B.K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Wood, A.R. et al. Defining the role of common variation in the genomic and biological architecture of adult human height. Nat. Genet. 46, 1173–1186 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Stefansson, H. et al. A common inversion under selection in Europeans. Nat. Genet. 37, 129–137 (2005).

    Article  CAS  PubMed  Google Scholar 

  15. Spillantini, M.G. & Goedert, M. Tau pathology and neurodegeneration. Lancet Neurol. 12, 609–622 (2013).

    Article  CAS  PubMed  Google Scholar 

  16. Desikan, R.S. et al. Genetic overlap between Alzheimer's disease and Parkinson's disease at the MAPT locus. Mol. Psychiatry 20, 1588–1595 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Kirchhoff, M., Bisgaard, A.M., Duno, M., Hansen, F.J. & Schwartz, M. A 17q21.31 microduplication, reciprocal to the newly described 17q21.31 microdeletion, in a girl with severe psychomotor developmental delay and dysmorphic craniofacial features. Eur. J. Med. Genet. 50, 256–263 (2007).

    Article  PubMed  Google Scholar 

  18. Koolen, D.A. et al. Mutations in the chromatin modifier gene KANSL1 cause the 17q21.31 microdeletion syndrome. Nat. Genet. 44, 639–641 (2012).

    Article  CAS  PubMed  Google Scholar 

  19. Estrada, K. et al. Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture. Nat. Genet. 44, 491–501 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Kemp, J.P. et al. Phenotypic dissection of bone mineral density reveals skeletal site specificity and facilitates the identification of novel loci in the genetic regulation of bone mass attainment. PLoS Genet. 10, e1004423 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Broer, L. et al. GWAS of longevity in CHARGE consortium confirms APOE and FOXO3 candidacy. J. Gerontol. A Biol. Sci. Med. Sci. 70, 110–118 (2015).

    Article  CAS  PubMed  Google Scholar 

  22. Kaplan, R.C. et al. A genome-wide association study identifies novel loci associated with circulating IGF-I and IGFBP-3. Hum. Mol. Genet. 20, 1241–1251 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Paik, J.H. et al. FoxOs cooperatively regulate diverse pathways governing neural stem cell homeostasis. Cell Stem Cell 5, 540–553 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Renault, V.M. et al. FoxO3 regulates neural stem cell homeostasis. Cell Stem Cell 5, 527–539 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Rzehak, P. et al. Associations of IGF-1 gene variants and milk protein intake with IGF-I concentrations in infants at age 6 months: results from a randomized clinical trial. Growth Horm. IGF Res. 23, 149–158 (2013).

    Article  CAS  PubMed  Google Scholar 

  26. Taal, H.R. et al. Common variants at 12q15 and 12q24 are associated with infant head circumference. Nat. Genet. 44, 532–538 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Lynch, S.A. et al. The 12q14 microdeletion syndrome: six new cases confirming the role of HMGA2 in growth. Eur. J. Hum. Genet. 19, 534–539 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Sweet, T., Yen, W., Khalili, K. & Amini, S. Evidence for involvement of NFBP in processing of ribosomal RNA. J. Cell. Physiol. 214, 381–388 (2008).

    Article  CAS  PubMed  Google Scholar 

  29. Verhaaren, B.F. et al. Multi-ethnic genome-wide association study of cerebral white matter hyperintensities on MRI. Circgenetics. 114, 000858 (2015).

    Google Scholar 

  30. Balestrini, A., Cosentino, C., Errico, A., Garner, E. & Costanzo, V. GEMC1 is a TopBP1-interacting protein required for chromosomal DNA replication. Nat. Cell Biol. 12, 484–491 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Chan, Y. et al. Genome-wide analysis of body proportion classifies height-associated variants by mechanism of action and implicates genes important for skeletal development. Am. J. Hum. Genet. 96, 695–708 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Fukumoto, A. et al. Head circumference and body growth in autism spectrum disorders. Brain Dev. 33, 569–575 (2011).

    Article  PubMed  Google Scholar 

  33. Stern, Y. Cognitive reserve in ageing and Alzheimer's disease. Lancet Neurol. 11, 1006–1012 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Quesada, A., Lee, B.Y. & Micevych, P.E. PI3 kinase/Akt activation mediates estrogen and IGF-1 nigral DA neuronal neuroprotection against a unilateral rat model of Parkinson's disease. Dev. Neurobiol. 68, 632–644 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Hevner, R.F. Brain overgrowth in disorders of RTK-PI3K-AKT signaling: a mosaic of malformations. Semin. Perinatol. 39, 36–43 (2015).

    Article  PubMed  Google Scholar 

  36. Rivière, J.-B. et al. De novo germline and postzygotic mutations in AKT3, PIK3R2 and PIK3CA cause a spectrum of related megalencephaly syndromes. Nat. Genet. 44, 934–940 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. Boland, E. et al. Mapping of deletion and translocation breakpoints in 1q44 implicates the serine/threonine kinase AKT3 in postnatal microcephaly and agenesis of the corpus callosum. Am. J. Hum. Genet. 81, 292–303 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Wang, D., Zeesman, S., Tarnopolsky, M.A. & Nowaczyk, M.J. Duplication of AKT3 as a cause of macrocephaly in duplication 1q43q44. Am. J. Med. Genet. A. 161A, 2016–2019 (2013).

    Article  PubMed  CAS  Google Scholar 

  39. Pawlikowska, L. et al. Association of common genetic variation in the insulin/IGF1 signaling pathway with human longevity. Aging Cell 8, 460–472 (2009).

    Article  CAS  PubMed  Google Scholar 

  40. Davies, G. et al. Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N = 53,949). Mol. Psychiatry 20, 183–192 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. de Moor, M.H.M. et al. Meta-analysis of genome-wide association studies for neuroticism, and the polygenic association with major depressive disorder. JAMA Psychiatry 72, 642–650 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  42. van den Berg, S.M. et al. Meta-analysis of genome-wide association studies for extraversion: findings from the Genetics of Personality Consortium. Behav. Genet. 46, 170–182 (2016).

    Article  PubMed  Google Scholar 

  43. Nalls, M.A. et al. Large-scale meta-analysis of genome-wide association data identifies six new risk loci for Parkinson's disease. Nat. Genet. 46, 989–993 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Cross-Disorder Group of the Psychiatric Genomics Consortium. Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet 381, 1371–1379 (2013).

  45. Benyamin, B. et al. Childhood intelligence is heritable, highly polygenic and associated with FNBP1L. Mol. Psychiatry 19, 253–258 (2014).

    Article  CAS  PubMed  Google Scholar 

  46. Kundaje, A. et al. Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Willer, C.J., Li, Y. & Abecasis, G.R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Chauhan, G. et al. Association of Alzheimer's disease GWAS loci with MRI markers of brain aging. Neurobiol. Aging 36, 1765.e7–1765.e16 (2015).

    Article  CAS  Google Scholar 

  49. Finucane, H.K. et al. Partitioning heritability by functional category using GWAS summary statistics. Nat. Genet. 47, 1228–1235 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Horikoshi, M. et al. New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism. Nat. Genet. 45, 76–82 (2013).

    Article  CAS  PubMed  Google Scholar 

  51. van der Valk, R.J.P. et al. A novel common variant in DCST2 is associated with length in early life and height in adulthood. Hum. Mol. Genet. 24, 1155–1168 (2015).

    Article  CAS  PubMed  Google Scholar 

  52. Lambert, J.-C. et al. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease. Nat. Genet. 45, 1452–1458 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Li, M.X., Gui, H.S., Kwan, J.S. & Sham, P.C. GATES: a rapid and powerful gene-based association test using extended Simes procedure. Am. J. Hum. Genet. 88, 283–293 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Segrè, A.V., Groop, L., Mootha, V.K., Daly, M.J. & Altshuler, D. Common inherited variation in mitochondrial genes is not enriched for associations with type 2 diabetes or related glycemic traits. PLoS Genet. 6, e1001058 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  55. Li, M.X., Kwan, J.S. & Sham, P.C. HYST: a hybrid set-based test for genome-wide association studies, with application to protein-protein interaction-based association analysis. Am. J. Hum. Genet. 91, 478–488 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

CHARGE: Infrastructure for the CHARGE Consortium is supported in part by the National Heart, Lung and Blood Institute grant HL105756 and for the neuroCHARGE phenotype working group through the National Institute on Aging grant AG033193.

ENIGMA: ENIGMA was supported in part by a Consortium grant (U54 EB020403 to PMT) from the NIH Institutes contributing to the Big Data to Knowledge (BD2K) Initiative, including the NIBIB and NCI.

Age, Gene/Environment Susceptibility-Reykjavik Study (AGES-Reykjavik): This study has been funded by NIH contracts N01-AG-1-2100 and 271201200022C, the NIA Intramural Research Program, Hjartavernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament). The study was approved by the Icelandic National Bioethics Committee, VSN: 00-063. The researchers are indebted to the participants for their willingness to participate in the study.

Alzheimer's Disease Neuroimaging Initiative (ADNI): Data collection and sharing for this project was funded by the ADNI (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the Alzheimer's Association; Alzheimer's Drug Discovery Foundation; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; GE Healthcare; Innogenetics, N.V.; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. The Canadian Institutes of Health Research provides funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (http://www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory of Neuro Imaging at the University of Southern California.

ANM: AddNeuroMed was funded through the EU FP6 programme. HS: Academy of Finland, Research Council for Health, 258081, UEFBrain, University of Eastern Finland, VTR funding Kuopio University Hospital.

Atherosclerosis Risk In Communities Study (ARIC): The Atherosclerosis Risk in Communities study was performed as a collaborative study supported by National Heart, Lung, and Blood Institute (NHLBI) contracts (HHSN268201100005C, HSN268201100006C, HSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C), R01HL70825, R01HL087641, R01HL59367, and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health (NIH) contract HHSN268200625226C. Infrastructure was partly supported by grant no. UL1RR025005, a component of the NIH and NIH Roadmap for Medical Research. This project was also supported by NIH R01 grant NS087541 to M.F.

Austrian Stroke Prevention Study Family (ASPS-Fam): The ASPS-Fam is funded by the Austrian Science Fund (FWF) project I904, the Medical University of Graz and the Steiermärkische Krankenanstalten Gesellschaft.

BETULA: This sample collection was supported by a Wallenberg Scholar grant from the Knut and Alice Wallenberg (KAW) foundation and a grant from Torsten and Ragnar Söderbergs Foundation to Lars Nyberg. S.l.H. was supported by a grant from HelseVest RHF (grant 911554).

Bipolar Family Study (BFS): The Bipolar Family Study wishes to thank the Scottish Mental Health Research Network for research assistant support, the Brain Research Imaging Centre Edinburgh, a center in the Scottish Funding Council Scottish Imaging Network–A Platform for Scientific Excellence (SINAPSE) Collaboration, for image acquisition and the Wellcome Trust Clinical Research Facility for genotyping. Genotyping was supported by the National Alliance for Research on Schizophrenia and Depression (NARSAD) Independent Investigator Award (to A.M.M.), and data collection was supported by the Health Foundation Clinician Scientist Fellowship. The research leading to these results also receives funding from the European Community's Seventh Framework Programme (FP7/2007– 2013) under grant agreements #602450 (IMAGEMEND) and ongoing support from the Wellcome Trust (Ref 104036/Z/14/Z).

Brain Imaging Genetics (BIG): This work makes use of the BIG database, first established in Nijmegen, The Netherlands, in 2007. This resource is now part of Cognomics (http://www.cognomics.nl), a joint initiative by researchers of the Donders Centre for Cognitive Neuroimaging, the Human Genetics and Cognitive Neuroscience Departments of the Radboud University Medical Center and the Max Planck Institute for Psycholinguistics in Nijmegen. The Board of the Cognomics Initiative consists of B. Franke, S. Fisher, G. Fernandez, P. Hagoort, H. Brunner, J. Buitelaar, H. van Bokhoven and D. Norris. The Cognomics Initiative has received supported from the participating departments and centers and from external grants, that is, the Biobanking and Biomolecular Resources Research Infrastructure (Netherlands) (BBMRI-NL), the Hersenstichting Nederland, and the Netherlands Organization for Scientific Research (NWO). The research leading to these results also receives funding from the NWO Gravitation grant 'Language in Interaction', the European Community's Seventh Framework Programme (FP7/2007– 2013) under grant agreements no 602450 (IMAGEMEND), no 278948 (TACTICS), and no 602805 (Aggressotype), as well as from the European Community's Horizon 2020 programme under grant agreement no 643051 (MiND) and from ERC-2010-AdG 268800-NEUROSCHEMA. In addition, the work was supported by a grant for the ENIGMA Consortium (grant number U54 EB020403) from the BD2K Initiative of a cross-NIH partnership. We wish to thank all persons who kindly participated in the BIG research.

Brain Genomics Superstruct Project (GSP): Data were provided in part by the Brain Genomics Superstruct Project of Harvard University and the Massachusetts General Hospital, with support from the Center for Brain Science Neuroinformatics Research Group, the Athinoula A. Martinos Center for Biomedical Imaging, and the Center for Human Genetic Research. 20 individual investigators at Harvard and MGH generously contributed data to GSP. This work is supported by NIMH grants K99 MH101367 (P.H.L.), R01-MH079799 (J.W.S.), K24MH094614 (J.W.S.) and K01MH099232 (A.J.H.).

Brainscale and NTR-Adults: We would like to thank all twin participants from the Netherlands Twin Register. The NTR-adult and Brainscale studies were supported by the Netherlands Organization for Scientific Research NWO [MW904-61-193 (E.d.G. and D.B.), MaGW-nr: 400-07-080 (D. V't E.), MagW 480-04-004 (D.B.), (51.02.060 (H.H.), 668.772 (D.B. and H.H.); NWO/SPI 56-464-14192 (D.B.), the European Research Council (ERC-230374) (D.B.), High Potential Grant Utrecht University (H.H.), NWO Brain and Cognition 433-09-220 (H.H.) and the Neuroscience Campus Amsterdam.

Cardiovascular Health Study (CHS): This research was supported by NHLBI contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086; and NHLBI grants U01HL080295, R01HL087652, R01HL105756, R01HL103612, R01HL120393, and R01HL130114 with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through R01AG023629, R01AG15928, R01AG20098, R01AG027002, R01AG05133, and R01AG027058 from the National Institute on Aging (NIA). A full list of principal CHS investigators and institutions can be found at http://CHS-NHLBI.org. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR000124, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

CHAP: This research was funded by grants from the National Institute of Health (AG011101 and AG030146) and the International Alzheimer's Association (NIRP-14-302587). DNA samples were collected during clinical evaluations and population interviews, and analyzed at the Broad Institute.

Epidemiology of Dementia in Singapore (EDIS): The Singapore Malay Eye Study (SiMES) and the Singapore Chinese Eye. Study (SCES) are funded by National Medical Research Council (grants 0796/2003, IRG07nov013, IRG09nov014, STaR/0003/2008 and CG/SERI/2010) and Biomedical Research Council (grants 09/1/35/19/616), Singapore. The Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore provided services for genotyping. The Epidemiology of Dementia in Singapore study is supported by the National Medical Research Council, Singapore (NMRC/CG/NUHS/2010, grant no. R-184-006-184-511). M.K.I. received additional funding from the Singapore Ministry of Health's National Medical Research Council (NMRC/CSA/038/2013).

EPIGEN: Work from the London Cohort was supported by research grants from the Wellcome Trust (grant 084730 to S.M.S.), University College London (UCL)/University College London Hospitals (UCLH) NIHR Biomedical Research Centre/Specialist Biomedical Research Centres (CBRC/SBRC) (grant 114 to S.M.S.), the European Union Marie Curie Reintegration (to M. Matarin and S.M.S.), the UK NIHR (08-08-SCC), the Comprehensive Local Research Network (CLRN) Flexibility and Sustainability Funding (FSF) (grant CEL1300 to S.M.S.), The Big Lottery Fund, the Wolfson Trust and the Epilepsy Society. This work was undertaken at UCLH/UCL, which received a proportion of funding from the UK Department of Health's NIHR Biomedical Research Centres funding scheme. Work from the Royal College of Surgeons in Ireland was supported by research grants from the Science Foundation Ireland (Research Frontiers Programme award 08/RFP/GEN1538) and Brainwave–the Irish Epilepsy Association. M. Matarin is funded by Epilepsy Research UK (grant F1206).

Erasmus Rucphen Family study (ERF) The ERF study as a part of EUROSPAN (European Special Populations Research Network) was supported by European Commission FP6 STRP grant number 018947 (LSHG-CT-2006-01947) and also received funding from the European Community's Seventh Framework Programme (FP7/2007-2013)/grant agreement HEALTH-F4-2007-201413 by the European Commission under the programme “Quality of Life and Management of the Living Resources” of 5th Framework Programme (no. QLG2-CT-2002-01254). High-throughput analysis of the ERF data was supported by joint grant from Netherlands Organization for Scientific Research and the Russian Foundation for Basic Research (NWO-RFBR 047.017.043). We are grateful to all study participants and their relatives, general practitioners and neurologists for their contributions and to P. Veraart for her help in genealogy, J. Vergeer for the supervision of the laboratory work and P. Snijders for his help in data collection. N. Amin is supported by the Netherlands Brain Foundation (project number F2013(1)-28). The ERF study genome-wide array data and phenotype data (age and gender) is archived in European Genome-Phenome Database (EGA). The study is archived in the DAC named Erasmus Rucphen Family Study with the accession code: EGAS00001001134. Researchers who wish to use other phenotypic data of the Erasmus Rucphen Family Study must seek approval from the management team of the Erasmus Rucphen Family study. They are advised to contact Cornelia van Duijn (c.vanduijn@erasmusmc.nl).

Framingham Heart Study (FHS): This work was supported by the dedication of the Framingham Study participants, the National Heart, Lung and Blood Institute's Framingham Heart Study (Contract No. HHSN268201500001I), and by grants from the National Institute of Health (AG008122, AG054076, AG049607, AG033193, AG010129, NS017950, and U01AG49505).

Generation R: The Generation R Study is conducted by the Erasmus Medical Centre in close collaboration with the Municipal Health Service Rotterdam area, and the Stichting Trombosedienst & Artsenlaboratorium Rijnmond (STAR), Rotterdam. We gratefully acknowledge the contribution of general practitioners, hospitals, midwives and pharmacies in Rotterdam. Additional support for neuroimaging came from ZonMw TOP 40-00812-98-11021.

GeneSTAR: GeneSTAR was supported by grants from the National Institute of Neurological Disorders and Stroke (R01NS062059), the National Heart, Lung, and Blood Institute (U01 HL72518, HL097698) and the National Institutes of Health/National Center for Research Resources (M01-RR000052) to the Johns Hopkins General Clinical Research Center. We would like to thank the participants and families of GeneSTAR and our dedicated staff for all their sacrifices.

GIG: The GIG (Genomic Imaging Göttingen) sample was established at the Center for Translational Research in Systems Neuroscience and Psychiatry at Göttingen University. We thank M. Keil, E. Diekhof, T. Melcher and I. Henseler for assistance in MRI data acquisition, and E. Binder and H. Mohr for their valuable help with genotyping. We are grateful to all persons who kindly participated in the GIG study.

GOBS: We acknowledge the ultimate source of our data, the Mexican American community of San Antonio and surrounding areas. Financial support for this study was provided by grants from the National Institute of Mental Health MH0708143 (D.C. Glahn), MH078111 (J. Blangero) and MH083824 (D.C. Glahn and J. Blangero). Theoretical development of SOLAR is supported by MH59490 (J. Blangero). This investigation was conducted, in part, in facilities constructed with support from Research Facilities Improvement Program grant numbers C06 RR13556 and C06 RR017515 from the National Center for Research Resources, NIH. Some of this work was performed at Texas Biomedical Research Institute, where J. Blangero began this investigator-initiated competitively publicly funded work.

HUBIN: This study was financed by the Swedish Research Council (K2007-62X-15077-04-1, K2008-62P-20597-01-3. K2010-62X-15078-07-2, K2012-61X-15078-09-3), the regional agreement on medical training and clinical research between Stockholm County Council and the Karolinska Institutet, the Knut and Alice Wallenberg Foundation, and the HUBIN project. Genotyping was performed by the SNP&SEQ Technology Platform in Uppsala. The platform is part of Science for Life Laboratory at Uppsala University and supported as a national infrastructure by the Swedish Research Council.

IMAGEN: IMAGEN was supported by the European Union-funded FP6 Integrated Project IMAGEN (Reinforcement-related behavior in normal brain function and psychopathology) (LSHM-CT- 2007-037286), the FP7 projects IMAGEMEND (602450) and MATRICS (603016), and the Innovative Medicine Initiative Project EU-AIMS (115300-2), the Medical Research Council Programme Grant “Developmental pathways into adolescent substance abuse” (93558), as well as the NIHR-biomedical Research Center “Mental Health”. Further support was provided by the Swedish Research Council FORMAS, and the German Federal Ministry for Education and Research BMBF (eMED SysAlc 01ZX1311A; Forschungsnetz AERIAL; 1EV0711) and the US National Institutes of Health (Axon, Testosterone and Mental Health during Adolescence; MH085772-01A1), and grants from the French MILDECA and from the Fondation pour la Recherche Médicale.

IMpACT: This study was funded by a grant from the Brain & Cognition Excellence Program of the Netherlands Organization for Scientific Research (NWO, grant 433-09-229) and in part by the Netherlands Brain Foundation (grant number, 15F07[2]27). B. Franke is supported by a Vici grant from the Netherlands Organization for Scientific Research (NWO; grant no 016.130.669). The research leading to these results also receives funding from the European Community's Seventh Framework Programme (FP7/2007– 2013) under grant agreements no 602450 (IMAGEMEND), no 278948 (TACTICS), and no 602805 (Aggressotype) as well as from the European Community's Horizon 2020 programme under grant agreement no 643051 (MiND). In addition, the work was supported by a grant for the ENIGMA Consortium (grant number U54 EB020403) from the BD2K Initiative of a cross-NIH partnership.

LBC1936: We thank the LBC1936 participants and the members of the LBC1936 research team who collected and collated the phenotypic and genotypic data. This work was undertaken as part of the Cross Council and University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE; http://www.ccace.ed.ac.uk). This work was supported by a Research into Ageing programme grant (to I.J.D.) and the Age UK-funded Disconnected Mind project (http://www.disconnectedmind.ed.ac.uk; to I.J.D. and J.M.W.), with additional funding from the UK Medical Research Council (MRC; to I.J.D., J.M.W. and M.E.B.). J.M.W. is supported by the Scottish Funding Council through the SINAPSE Collaboration (http://www.sinapse.ac.uk). M.V.M. is supported by the Row Fogo Charitable Trust. CCACE (MRC MR/K026992/1) is funded by the UK Biotechnology and Biological Sciences Research Council (BBSRC) and the UK MRC. Genotyping was supported by a grant from the BBSRC (BB/F019394/1).The image acquisition and analysis was performed at the Brain Research Imaging Centre, University of Edinburgh (http://www.bric.ed.ac.uk).

Leiden Longevity Study (LLS): The Leiden Longevity Study was supported by a grant from the Innovation-Oriented Research Program on Genomics (SenterNovem IGE05007) and the Netherlands Consortium for Healthy Ageing (grant number 050-060-810).

Mind Clinical Imaging Consortium (MCIC): Data used in the preparation of this work were obtained from the Mind Clinical Imaging Consortium database through the Mind Research Network (http://www.mrn.org). The MCIC project was supported by the Department of Energy under Award Number DE-FG02-08ER64581. MCIC is the result of efforts of co-investigators from University of Iowa, University of Minnesota, University of New Mexico, and Massachusetts General Hospital.

MooDS: The establishment of the MooDS sample was funded by the German Federal Ministry of Education and Research (BMBF) through the Integrated Genome Research Network (IG) MooDS (Systematic Investigation of the Molecular Causes of Major Mood Disorders and Schizophrenia; grant 01GS08144 to M.M. Nöthen and S. Cichon, grant 01GS08147 to J. Rietschel and A. Meyer-Lindenberg and grant 01GS08148 to A. Heinz), under the auspices of the National Genome Research Network plus (NGFNplus), and through the Integrated Network IntegraMent (Integrated Understanding of Causes and Mechanisms in Mental Disorders), under the auspices of the e:Med Programme (grant 01ZX1314A to M.M. Nöthen, grant 01ZX1314C to H. Walter, grant 01ZX1314G to M. Rietschel).

MPIP: The MPIP Munich Morphometry Sample comprises images acquired as part of the Munich Antidepressant Response Signature Study and the Recurrent Unipolar Depression (RUD) Case-Control study performed at the MPIP, and control subjects acquired at the Ludwig-Maximilians-University, Munich, Department of Psychiatry. We thank E. Meisenzahl and D. Rujescu for providing MRI and genetic data for inclusion into the MPIP Munich Morphometry sample. We wish to acknowledge A. Olynyik and radiographers R. Schirmer, E. Schreiter, R. Borschke and I. Eidner for image acquisition and data preparation. We thank D.P. Auer for local study management in the initial phase of the RUD study. We are grateful to GlaxoSmithKline for providing the genotypes of the Recurrent Unipolar Depression Case-Control Sample. We thank the staff of the Center of Applied Genotyping (CAGT) for generating the genotypes of the MARS cohort. The study is supported by a grant of the Exzellenz-Stiftung of the Max Planck Society. This work has also been funded by the Federal Ministry of Education and Research (BMBF) in the framework of the National Genome Research Network (NGFN), FKZ 01GS0481.

NCNG: this sample collection was supported by grants from the Bergen Research Foundation and the University of Bergen, the Dr. Einar Martens Fund, the K.G. Jebsen Foundation, the Research Council of Norway, to S.L.H., V.M.S. and T.E.

NESDA: Funding was obtained from the Netherlands Organization for Scientific Research (Geestkracht program grant 10-000-1002); the Center for Medical Systems Biology (CSMB, NWO Genomics), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL), VU University's Institutes for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam, University Medical Center Groningen, Leiden University Medical Center, National Institutes of Health (NIH, R01D0042157-01A, MH081802, Grand Opportunity grants 1RC2 MH089951 and 1RC2 MH089995). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health. Computing was supported by BiG Grid, the Dutch e-Science Grid, which is financially supported by NWO.

NeuroIMAGE: The NeuroIMAGE project was supported by NIH Grant R01MH62873 (to S.V. Faraone), NWO Large Investment Grant 1750102007010 (to J. Buitelaar), and by grants from Radboud University Nijmegen Medical Center, University Medical Center Groningen and Accare, and VU University Amsterdam. The work contributing to this result also receives support from the European Community's Seventh Framework Programme (FP7/2007– 2013) under grant agreements no 602450 (IMAGEMEND), no 278948 (TACTICS) and no 602805 (Aggressotype) as well as from the European Community's Horizon 2020 programme under grant agreement n0 643051 (MiND). In addition, the work was supported by a grant for the ENIGMA Consortium (grant number U54 EB020403) from the BD2K Initiative of a cross-NIH partnership.

NIMH-IRP: Supported in part by the NIMH Intramural Research Program (ZIAMH002810; Z01MH002792; Z01MH002790).

North American Brain Expression Consortium (NABEC): This research was supported by the Intramural Research Program of the NIH, National Institute on Aging.

Older Australian Twins Study (OATS): We would like to acknowledge and thank the OATS participants, their supporters and respective Research Teams. This work was supported by a number of sources. OATS is supported by the NHMRC/Australian Research Council Strategic Award 401162 and NHMRC Project Grant 1045325 to P. Sachdev and colleagues. OATS was facilitated through access to the Australian Twin Registry, a national research resource supported by the NHMRC Enabling Grant 310667, administered by the University of Melbourne. DNA was extracted by Genetic Repositories Australia, an Enabling Facility supported by the NHMRC Grant 401184. OATS genotyping was partly funded by a Commonwealth Scientific and Industrial Research Organisation Flagship Collaboration Fund Grant. Henry Brodaty is supported by the Australian Government funded Dementia Collaborative Research Centre (DCRC), UNSW. Nicola Armstrong was supported by the NHMRC Project Grant 525453 and Karen Mather is supported by an Alzheimer's Australia Dementia Research Foundation Postdoctoral Fellowship and the NHMRC Capacity Building Grant 568940.

Osaka: This study was supported, in part, by research grants from the Japanese Ministry of Health, Labor and Welfare; the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) KAKENHI and Scientific Research on Innovative Areas (Comprehensive Brain Science Network); and the Brain Sciences Project of the Center for Novel Science Initiatives (CNSI), the National Institutes of Natural Sciences (NINS), and the Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS) from Japan Agency for Medical Research and development, AMED.

PAFIP: The PAFIP study was supported by Instituto de Salud Carlos III, FIS00/3095, 01/3129, PI020499, PI060507, PI10/00183, PI14/00639, the SENY Fundació Research Grant CI 2005-0308007, and the Fundación Marqués de Valdecilla API07/011. PAFIP wish to acknowledge WTCCC2 (Wellcome Trust Case Control Consortium 2) for DNA Genotyping, Valdecilla Biobank for providing the biological samples and associated data included in this study and Idival Neuroimaging Unit for its help in the technical execution of this work. D. Tordesillas-Gutiérrez is funded by a contract from the Carlos III Health Institute (CA12/00312).

PROSPER: The PROSPER study was supported by an investigator-initiated grant obtained from Bristol-Myers Squibb. J.W. Jukema is an Established Clinical Investigator of the Netherlands Heart Foundation (grant 2001 D 032). Support for genotyping was provided by the seventh framework program of the European commission (grant 223004) and by the Netherlands Genomics Initiative (Netherlands Consortium for Healthy Aging grant 050-060-810).

QTIM: D.P.H., N.J., C.R.K.C. and P.M.T. are supported, in part, by NIH grants R01 NS080655, R01AG040060, R01 EB008432, R01 MH097268, U01 AG024904, R01 MH085667, R01 MH089722, P41 EB015922, and R01 MH094343. R.K.W. is supported by National Science Foundation (BCS-1229450). J.L.S. was supported by the NIMH (K99MH102357) and Autism Speaks. G.Z. is supported by a Future Fellowship (FT0991634) from the Australian Research Council. S.E.M. and G.W.M. are supported by a National Health and Medical Research Council (NHMRC), Australia, Fellowships (1103623, 619667). The QTIM study is supported by grants from NIH (R01 HD050735) and the NHMRC (389875, 486682, 1009064). We thank the twins and siblings for their participation, M. Grace and A. Eldridge for twin recruitment, A. Al Najjar and other radiographers for scanning, K. McAloney and D. Park for research support, and A. Henders and staff for DNA sample processing and preparation.

ROS and MAP: The clinical, genomic, and neuroimaging data for the Religious Orders Study and the Rush Memory and Aging Project was funded by NIH grants P30AG10161, RF1AG15819, R01AG17917, R01AG30146, R01AG40039, and the Translational Genomics Research Institute.

Rotterdam Study: The generation and management of GWAS genotype data for the Rotterdam Study are supported by the Netherlands Organisation of Scientific Research NWO Investments (nr. 175.010.2005.011, 911-03-012). This study is funded by the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO) project nr. 050-060-810. The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. This research is supported by the Dutch Technology Foundation STW, which is part of the NWO, and which is partly funded by the Ministry of Economic Affairs. This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No 678543). Further support was obtained through the Joint Programme - Neurodegenerative Disease Research working group on High-Dimensional Research in Alzheimer's Disease (ZonMW grant number 733051031). MAI is supported by ZonMW grant number 916.13.054. H.H.H.A. is supported by the Van Leersum Grant of the Royal Netherlands Academy of Arts and Sciences.

Saguenay Youth Study (SYS): The Saguenay Youth Study project is funded by the Canadian Institutes of Health Research (T.P., Z.P.), Heart and Stroke Foundation of Quebec (Z.P.), and the Canadian Foundation for Innovation (Z.P.). T.P. is supported by the Tanenbaum Chair in Population Neuroscience at the Rotman Research Institute, University of Toronto.

SHIP and TREND: The SHIP data sets are part of the Community Medicine Research net (CMR) of the University of Greifswald, which is funded by the German Federal Ministry of Education and Research and the German Ministry of Cultural Affairs, as well as by the Social Ministry of the Federal State of Mecklenburg–West Pomerania (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), and the network 'Greifswald Approach to Individualized Medicine (GANI_MED)' funded by the Federal Ministry of Education and Research (grant 03IS2061A). Genome-wide data and MRI scans were supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthcare, Erlangen, Germany, and the Federal State of Mecklenburg–West Pomerania. The University of Greifswald is a member of t the Caché Campus Program of the InterSystems GmbH.

Sydney Memory and Ageing Study (Sydney MAS): We would like to thank the Sydney MAS participants, their supporters and respective research teams. Sydney MAS was supported by the Australian National Health and Medical Research Council (NHMRC) Program Grants 350833 and 568969 to P. Sachdev, H. Brodaty and G. Andrews. DNA was extracted by Genetic Repositories Australia, an Enabling Facility supported by the NHMRC Grant 401184. H. Brodaty is supported by the Australian Government funded Dementia Collaborative Research Centre (DCRC), UNSW. N. Armstrong was supported by the NHMRC Project Grant 525453 and K. Mather is supported by an Alzheimer's Australia Dementia Research Foundation Postdoctoral Fellowship. Both S. Reppermund and K. Mather are supported by the NHMRC Capacity Building Grant 568940.

Tasmanian Study of Gait and Cognition (TASCOG): The Tasmanian Study of Gait and Cognition is supported by project grants from the National Health and Medical Research Council of Australia (NHMRC; 403000,491109, and 606543) and a grant from the Wicking Dementia Education and Research Centre, Hobart. V.S. is supported by a cofunded NHMRC Career Development Fellowship (1061457) and a Heart Foundation Future Leader Fellowship (ID 100089).

Three-City Dijon Study: The Three-City Study is conducted under a partnership agreement among the Institut National de la Santé et de la Recherche Médicale (INSERM), the Victor Segalen–Bordeaux II University, and Sanofi-Aventis. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The Three-City Study is also supported by the Caisse Nationale Maladie des Travailleurs Salariés, Direction Générale de la Santé, Mutuelle Générale de l'Education Nationale (MGEN), Institut de la Longévité, Conseils Régionaux of Aquitaine and Bourgogne, Fondation de France, and Ministry of Research–INSERM Programme “Cohortes et collections de données biologiques.” Christophe Tzourio and Stéphanie Debette are supported by a grant from the Fondation Leducq.

TOP: The study was supported by the Research Council of Norway (#213837, #223273, #229129), South-East Norway Health Authority (#2013-123) and KG Jebsen Foundation. The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement no 602450 (IMAGEMEND).

UCLA_NL_BP: Data collection and genotyping was made possible with (NIH/NIMH) R01 MH090553 to R.A.O.th-East Norway Health Authority (#2013-123) and KG Jebsen Foundation.

UMCU: UMCU acknowledgment data: This work was supported by 917.46.370 (H.H.) and 908-02-123 (H.H.) from the Netherlands Organization for Health Research and Development ZonMW.

WHICAP: This study was supported by a grant from the NIH (5R01AG037212).

CHARGE consortium: See ref. 40 for the general cognitive function GWAS, and ref. 29 for the white matter lesion GWAS.

Early Growth Genetics (EGG) consortium: Data on head circumference, birth weight, and birth length have been contributed by the EGG Consortium and was downloaded from http://www.egg-consortium.org.

Genetic Investigation of ANthropometric Traits (GIANT) consortium: See ref. 13.

Genetics of Personality Consortium: See ref. 41 for the neuroticism GWAS and ref. 42 for the extraversion GWAS.

IGAP: We thank the International Genomics of Alzheimer's Project (IGAP) for providing summary results data for these analyses. The investigators within IGAP contributed to the design and implementation of IGAP and/or provided data but did not participate in analysis or writing of this report. IGAP was made possible by the generous participation of the control subjects, the patients, and their families. The i–Select chips was funded by the French National Foundation on Alzheimer's disease and related disorders. EADI was supported by the LABEX (laboratory of excellence program investment for the future) DISTALZ grant, Inserm, Institut Pasteur de Lille, Université de Lille 2 and the Lille University Hospital. GERAD was supported by the Medical Research Council (Grant no 503480), Alzheimer's Research UK (Grant no 503176), the Wellcome Trust (Grant no 082604/2/07/Z) and German Federal Ministry of Education and Research (BMBF): Competence Network Dementia (CND) grant no 01GI0102, 01GI0711, 01GI0420. CHARGE was partly supported by the NIH/NIA grant R01 AG033193 and the NIA AG081220 and AGES contract N01–AG–12100, the NHLBI grant R01 HL105756, the Icelandic Heart Association, and the Erasmus Medical Center and Erasmus University. ADGC was supported by the NIH/NIA grants: U01 AG032984, U24 AG021886, U01 AG016976, and the Alzheimer's Association grant ADGC–10–196728.

International Parkinson's Disease Genomics Consortium (IPDGC): See ref. 43.

Psychiatric Genomics Consortium: See ref. 44.

Social Science Genetic Association Consortium (SSGAC): See ref. 45 for the childhood cognitive function GWAS.

Author information

Authors and Affiliations

Authors

Contributions

Conceived of the study and drafted the manuscript: H.H.H.A., D.P.H., V.C., J.L.S., M.E.R., S.T., A.A., P.N, V.G., G.S., M.F., B.F., S.D., S.E.M., M.A.I., P.M.T. Performed statistical analyses: H.H.H.A., D.P.H., V.C., J.L.S., M.E.R., S.T., A.A., Sy.D., A.H.B., N.J., K.W., Lu.A., N.A., M.A., B.S.A., N.J.A., La.A., A.B., M.B., J.C.B., L.M.E.B., S.H.B., M.M.B., Ja.B., O.C., M.M.C., Ga.C., Q.C., C.R.K.C., G.C., Nh.D., St.E., Ti.G., Su.G., A.L.G., C.U.G., Ol.G., M.E.G., T.G., Jo.H., U.K.H., S.H., E.H., M.H., D.J., T.J., N.K., D.K., S.K., M.K., B.K., P.H.L., J.L., D.C.M.L., L.M.L., M.L., Ch.M., Su.M., An.M., Ma.M., M.M., Be.M., D.R.M., R.M., Y.M., R.L.M., K.N., L.M.O., J.O., Ma.P., I.P., L.P., S.P., B.P., K.B.R., A.R., J.S.R., S.L.R., R.R., Na.R., N.A.R., T.R., C.L.S., Li.S., An.J.S., L.S., J.S., A.V.S., E.S., L.T.S., Al.T., Ro.T., Di.T., R.T., D.T., Dh.V., J.V., S.J.V., D.vdM., M.M.J.V., K.R.V., D.vR., Es.W., L.T.W., A.M.W., G.W., C.W., Th.W., L.R.Y., J.Y., M.P.Z., A.M.D., I.O.F., B.M., T.E.N., J.A.T., B.X., Sa.A., A.M.B., A.dB., A.J.H., A.C.N., P.G.S., C.D.W., S.M.B., R.M.B., G.D., J.G., O.G., R.K., C.M., M.A.N., D.V., B.N.V., T.W., E.J.R. Acquired data: P.N., Su.S., K.A.A., T.A., M.P.B., Ir.F., R.F.G., D.H., K.A.M., Em.S., B.G.W., A.Z., I.A., N.T.A., L.A., D.A., P.A., O.A.A., S.A., A.A.A., M.E.B., D.M.B., J.T.B., D.A.B., J.B., H.v.a.B., D.I.B., H.B., H.G.B., R.L.B., J.K.B., K.B.B., W.C., V.D.C., D.M.C., G.L.C., C-Y.C., C.C., S.C., M.R.C., A.C., B.C., J.E.C., M.C., G.E.D., E.J.C.D., P.L.D., G.I.D., N.D., Ch.D., A.DeS., A.D., Sr.D., W.C.D., R.D., T.D.D., S.E., T.E., D.A.E., G.F., L.F., S.E.F., D.A.F., I.F., T.M.F., P.T.F., C.F., Ma.F., D.C.G., R.L.G., H.H.H.G., H.J.G., R.C.G., S.G., N.K.H., J.H., C.A.H., R.H., K.H., An.H., S.L.e.H., D.G.H., D.J.H., B.H., P.J.H., W.H., A.H., F.H., G.H., N.H., J-J.H., H.E.H., M.I., M.K.I., C.R.J., R.J., E.G.J., J.J., R.S.K., I.K., D.S.K., P.K., J.B.K., L.J.L., S.M.L., H.L., X.L., D.L.L., W.L., O.L.L., S.L., O.M., J.M., V.S.M., A.M.M., F.J.M., K.L.M., P.M., I.M., A.M., S.M., G.W.M., D.W.M., T.H.M., T.W.M., M.N., W.J.N., M.M.N., L.N., K.O., R.L.O., R.A.O., M.P., T.P., Z.P., B.W.J.P., G.P., S.G.P., B.M.P., S.R., Ma.R., J.L.R., N.R., J.I.R., M.R., R.L.S., P.S.S., A.J.S., He.S., P.R.S., S.S., A.S., S.M.S., C.S., J.W.S., H.S., V.S., V.M.S., D.J.S., J.E.S., A.T., H.T., A.W.T., B.T., J.T., C.T., A.G.U., M.C.V., M.vdB., A.V., N.J.A.V., C.M.V., N.E.M.V., M.V., D.J.V., M.W.V., H.V., H.W., J.M.W., T.H.W., M.E.W., D.R.W., M.W.W., W.W., E.W., T.Y.W., C.B.W., R.H.Z., A.B.Z., I.J.D., C.D., R.S., N.G.M., A.J.M.D., M.J.W., V.G., G.S., M.F., B.F., S.D., S.E.M., M.A.I., P.M.T., A.Sim., Sa.A., A.M.B., A.dB., A.J.H., A.C.N., P.G.S., C.D.W., S.M.B., R.M.B., G.D., J.G., O.G., R.K., C.M., M.A.N., D.V., B.N.V., T.W., E.J.R. All authors critically reviewed the manuscript for important intellectual content.

Corresponding authors

Correspondence to M Arfan Ikram or Paul M Thompson.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Quantile-quantile plot of intracranial volume genome-wide association study meta-analysis.

All observed –log10(p-values) from the intracranial volume GWAS plotted against the expected –log10(p-values) of a normal distribution.

Supplementary Figure 2 Comparison of enrichment by chromosome between intracranial volume and other complex traits.

Enrichment of association by chromosome for intracranial volume compared with other complex traits. The –log10(p-values) that were larger than 10 (only for the height GWAS) were set to 10.

Supplementary Figure 3 Enrichment of association by functional class for intracranial volume compared with other complex traits.

The –log10(p-values) that were larger than 10 (only for the height GWAS) were set to 10.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–3 (PDF 411 kb)

Supplementary Methods Checklist

(PDF 429 kb)

Supplementary Table 1

Information on sampling and demographics of study populations. (XLSX 16 kb)

Supplementary Table 2

Information on genotyping and quality control. (XLSX 14 kb)

Supplementary Table 3

Information on image acquisition and processing. (XLSX 24 kb)

Supplementary Table 4

Functional annotation of genome-wide significant variants associated with intracranial volume and all variants in LD (> 0.8). (XLSX 40 kb)

Supplementary Table 5

Phenotypic correlation between intracranial volume and height. (XLSX 8 kb)

Supplementary Table 6

Genome-wide significant variants associated with intracranial volume with and without adjustment for height. (XLSX 9 kb)

Supplementary Table 7

The association between a polygenic score constructed from the 697 variants identified for height by the GIANT consortium and intracranial volume, with and without adjustment for height. (XLSX 92 kb)

Supplementary Table 8

Genome-wide significant variants associated with height and their association with intracranial volume. (XLSX 9 kb)

Supplementary Table 9

Novel genome-wide significant variants after meta-analysis of intracranial volume and child head circumference. (XLSX 8 kb)

Supplementary Table 10

Pathway analysis of intracranial volume using the KGG software. (XLSX 95 kb)

Supplementary Table 11

Pathway analysis of intracranial volume using the MAGENTA software. (XLSX 404 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Adams, H., Hibar, D., Chouraki, V. et al. Novel genetic loci underlying human intracranial volume identified through genome-wide association. Nat Neurosci 19, 1569–1582 (2016). https://doi.org/10.1038/nn.4398

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nn.4398

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing