Inferring the nature of missing heritability in human traits

Abstract

Thousands of genes responsible for many diseases and other common traits in humans have been detected by Genome Wide Association Studies (GWAS) in the last decade. However, candidate causal variants found so far usually explain only a small fraction of the heritability estimated by family data, the rest remaining missing. The most common explanation for this observation is that the missing heritability corresponds to variants, either rare or common, with very small effect, which pass undetected due to a lack of statistical power. We carried out a meta-analysis using data from the NHGRI-EBI GWAS Catalog in order to explore the distribution of gene effects for a set of 59 complex traits, to investigate the factors related to new gene discovery and to quantify their contributions to heritability. With the data obtained we were able to predict the expected distribution of gene effects for 16 traits and diseases including cancer and immune disorders, the missing number of genes yet to be discovered, and the additive contribution of common variants to heritability. Our results indicate that, for most traits, the additive contribution of hundreds or thousands of genes is able to explain the familiar heritability. However, for some traits, the predicted heritability is lower than the familiar one, so that part of the missing heritability cannot be explained by the contribution of common variants with additive effects, and other phenomena (e.g. dominance or epistasis) should be invoked.\n\nAUTHOR SUMMARYThe heritability of biological traits refers to the fraction of the phenotypic (i.e. visible or diagnosable) variability that is explained by the underlying genetic variability. Despite the efforts made to find the genes responsible for complex traits and diseases, most of the heritability explained by the variants found explains only a small fraction of that measured by population and family studies. The remaining missing heritability is usually assumed to be due to the additive effect of undetected variants. Here we carried out a meta-analysis using records from a publicly available database of genome-wide studies on humans. With these data, we were able to investigate and make inferences on the nature of heritability and the factors associated to new gene discovery. Our results indicate that increasing population sample size, as well as its diversity, enhances the discovery of new genes, but these have lower and lower effects, contributing little to heritability. We were also able to predict the distribution of gene effects for many traits and the number of variants needed to fully explain the heritability. For some traits, the additive effects of single variants yet to be discovered cannot explain the heritability, suggesting that other sources of variation are involved.