Abstract

Pedigree-based analyses of intelligence have reported that genetic differences account for 50–80% of the phenotypic variation. For personality traits these effects are smaller, with 34–48% of the variance being explained by genetic differences. However, molecular genetic studies using unrelated individuals typically report a heritability estimate of around 30% for intelligence and between 0 and 15% for personality variables. Pedigree-based estimates and molecular genetic estimates may differ because current genotyping platforms are poor at tagging causal variants, variants with low minor allele frequency, copy number variants, and structural variants. Using ~20,000 individuals in the Generation Scotland family cohort genotyped for ~700,000 single-nucleotide polymorphisms (SNPs), we exploit the high levels of linkage disequilibrium (LD) found in members of the same family to quantify the total effect of genetic variants that are not tagged in GWAS of unrelated individuals. In our models, genetic variants in low LD with genotyped SNPs explain over half of the genetic variance in intelligence, education, and neuroticism. By capturing these additional genetic effects our models closely approximate the heritability estimates from twin studies for intelligence and education, but not for neuroticism and extraversion. We then replicated our finding using imputed molecular genetic data from unrelated individuals to show that ~50% of differences in intelligence, and ~40% of the differences in education, can be explained by genetic effects when a larger number of rare SNPs are included. From an evolutionary genetic perspective, a substantial contribution of rare genetic variants to individual differences in intelligence, and education is consistent with mutation-selection balance.

Highlights

  • We sought to identify reasons for the gap between pedigree-based and single-nucleotide polymorphisms (SNPs)-based estimates of heritability in samples of unrelated individuals, a difference that might be due to genetic variants in poor linkage disequilibrium (LD) with SNPs genotyped on current platforms

  • Using GREML-KIN we could account for the entire heritability of general intelligence and education, as estimated in twin and family studies, by adding the G and K estimates we derived directly from genome-wide molecular genetic data [63, 67]

  • Even though GREML-MS is expected to underestimate heritability for traits where the genetic architecture includes the contribution of copy number variants (CNVs), structural variants and very rare variants [64], we were able to recover the majority of this heritability following imputation to the Haplotype Reference Consortium

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Summary

Introduction

W. David Hill, Ruben C. Arslan and Charley Xia contributed equally to this work.Electronic supplementary material The online version of this article (https://doi.org/10.1038/s41380-017-0005-1) contains supplementary material, which is available to authorised users.Development Lentzeallee 94, 14195 Berlin, GermanyThe scores from different types of cognitive ability tests correlate positively and the variance that is shared between tests is termed general intelligence, general cognitive ability, or g [1]. General intelligence typically accounts for

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