The total burden of rare, non-synonymous exome genetic variants is not associated with childhood or late-life cognitive ability

Proc Biol Sci. 2014 Feb 26;281(1781):20140117. doi: 10.1098/rspb.2014.0117. Print 2014 Apr 22.

Abstract

Human cognitive ability shows consistent, positive associations with fitness components across the life-course. Underlying genetic variation should therefore be depleted by selection, which is not observed. Genetic variation in general cognitive ability (intelligence) could be maintained by a mutation-selection balance, with rare variants contributing to its genetic architecture. This study examines the association between the total number of rare stop-gain/loss, splice and missense exonic variants and cognitive ability in childhood and old age in the same individuals. Exome array data were obtained in the Lothian Birth Cohorts of 1921 and 1936 (combined N = 1596). General cognitive ability was assessed at age 11 years and in late life (79 and 70 years, respectively) and was modelled against the total number of stop-gain/loss, splice, and missense exonic variants, with minor allele frequency less than or equal to 0.01, using linear regression adjusted for age and sex. In both cohorts and in both the childhood and late-life models, there were no significant associations between rare variant burden in the exome and cognitive ability that survived correction for multiple testing. Contrary to our a priori hypothesis, we observed no evidence for an association between the total number of rare exonic variants and either childhood cognitive ability or late-life cognitive ability.

Keywords: exome; fitness; general cognitive ability; genetic burden; intelligence; mutation–selection balance.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors
  • Aged
  • Child
  • Cohort Studies
  • Exome / genetics*
  • Gene Frequency
  • Genetic Fitness / genetics*
  • Genetic Variation / genetics*
  • Genetic Variation / physiology
  • Humans
  • Intelligence / genetics*
  • Linear Models
  • Mutation / genetics
  • Selection, Genetic
  • Sex Factors