“Hidden Heritability due to Heterogeneity across 7 Populations”, 2017 (; similar):
Meta-analyses of genome-wide association studies, which dominate genetic discovery, are based on data from diverse historical time periods and populations. Genetic scores derived from genome-wide association studies explain only a fraction of the heritability estimates obtained from whole-genome studies on single populations, known as the hidden heritability puzzle.
Using 7 sampling populations (n = 35,062), we test whether hidden heritability is attributed to heterogeneity across sampling populations and time, showing that estimates are:
substantially smaller across populations compared with within populations. We show that the hidden heritability varies substantially: from 0% for height to 20% for body mass index, 37% for education, 40% for age at first birth, and up to 75% for number of children. [ie. fertility is highly non-stationary!]
Simulations demonstrate that our results are more likely to reflect heterogeneity in phenotypic measurement or gene-environment interactions than genetic heterogeneity.
These findings have substantial implications for genetic discovery, suggesting that large homogenous datasets are required for behavioral phenotypes and that gene-environment interaction may be a central challenge for genetic discovery.