Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

A combined analysis of genetically correlated traits identifies 107 loci associated with intelligence

W. D. Hill, G. Davies, A. M. McIntosh, C. R. Gale, I. J. Deary
doi: https://doi.org/10.1101/160291
W. D. Hill
Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK Department of Psychology, University of Edinburgh, Edinburgh, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
G. Davies
Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK Department of Psychology, University of Edinburgh, Edinburgh, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
A. M. McIntosh
Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK Division of Psychiatry, University of Edinburgh, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
C. R. Gale
Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK Department of Psychology, University of Edinburgh, Edinburgh, UK MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
I. J. Deary
Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK Department of Psychology, University of Edinburgh, Edinburgh, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Intelligence, or general cognitive function, is phenotypically and genetically correlated with many traits, including many physical and mental health variables. Both education and household income are strongly genetically correlated with intelligence, at rg =0.73 and rg =0.70 respectively. This allowed us to utilize a novel approach, Multi-Trait Analysis of Genome-wide association studies (MTAG; Turley et al. 2017), to combine two large genome-wide association studies (GWASs) of education and household income to increase power in the largest GWAS on intelligence so far (Sniekers et al. 2017). This study had four goals: firstly, to facilitate the discovery of new genetic loci associated with intelligence; secondly, to add to our understanding of the biology of intelligence differences; thirdly, to examine whether combining genetically correlated traits in this way produces results consistent with the primary phenotype of intelligence; and, finally, to test how well this new meta-analytic data sample on intelligence predict phenotypic intelligence variance in an independent sample. We apply MTAG to three large GWAS: Sniekers et al (2017) on intelligence, Okbay et al. (2016) on Educational attainment, and Hill et al. (2016) on household income. By combining these three samples our functional sample size increased from 78 308 participants to 147 194. We found 107 independent loci associated with intelligence, implicating 233 genes, using both SNP-based and gene-based GWAS. We find evidence that neurogenesis may explain some of the biological differences in intelligence as well as genes expressed in the synapse and those involved in the regulation of the nervous system. We show that the results of our combined analysis demonstrate the same pattern of genetic correlations as a single measure/the simple measure of intelligence, providing support for the meta-analysis of these genetically-related phenotypes. We find that our MTAG meta-analysis of intelligence shows similar genetic correlations to 26 other phenotypes when compared with a GWAS consisting solely of cognitive tests. Finally, using an independent sample of 6 844 individuals we were able to predict 7% of intelligence using SNP data alone.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
Back to top
PreviousNext
Posted July 07, 2017.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
A combined analysis of genetically correlated traits identifies 107 loci associated with intelligence
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
Share
A combined analysis of genetically correlated traits identifies 107 loci associated with intelligence
W. D. Hill, G. Davies, A. M. McIntosh, C. R. Gale, I. J. Deary
bioRxiv 160291; doi: https://doi.org/10.1101/160291
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
A combined analysis of genetically correlated traits identifies 107 loci associated with intelligence
W. D. Hill, G. Davies, A. M. McIntosh, C. R. Gale, I. J. Deary
bioRxiv 160291; doi: https://doi.org/10.1101/160291

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Genetics
Subject Areas
All Articles
  • Animal Behavior and Cognition (1545)
  • Biochemistry (2500)
  • Bioengineering (1757)
  • Bioinformatics (9729)
  • Biophysics (3929)
  • Cancer Biology (2990)
  • Cell Biology (4235)
  • Clinical Trials (135)
  • Developmental Biology (2653)
  • Ecology (4129)
  • Epidemiology (2033)
  • Evolutionary Biology (6933)
  • Genetics (5243)
  • Genomics (6532)
  • Immunology (2208)
  • Microbiology (7012)
  • Molecular Biology (2784)
  • Neuroscience (17412)
  • Paleontology (127)
  • Pathology (432)
  • Pharmacology and Toxicology (712)
  • Physiology (1068)
  • Plant Biology (2516)
  • Scientific Communication and Education (647)
  • Synthetic Biology (835)
  • Systems Biology (2699)
  • Zoology (439)