New Paper from Faculty Examines Genome-wide Association Studies and Genetic Confounding

Department of Ecology and Evolution Assistant Professor Carl Veller recently published a paper in PLOS Biology. In the paper, Dr. Veller and co-author Dr. Graham Coop of the University of California-Davis present a general theoretical analysis of the influence of confounding in standard population-based and within-family genome-wide association studies (GWASs). Their research, which "details how different sources of confounding affect GWAS and whether family-based designs offer a solution", was featured in a PLOS Biology Primer for highlighting an important aspect of biology.

Dr. Carl Veller

Dr. Veller joined the E&E faculty in the fall of 2023. His is a population geneticist who uses mathematical modeling and computer simulations to understand the dynamics of gene frequency change in evolving populations. He is particularly interested in evolutionary consequences of the genetic shuffling that occurs with sexual reproduction.


A central aim of genome-wide association studies (GWASs) is to estimate direct genetic effects: the causal effects on an individual’s phenotype of the alleles that they carry. However, estimates of direct effects can be subject to genetic and environmental confounding and can also absorb the “indirect” genetic effects of relatives’ genotypes. Recently, an important development in controlling for these confounds has been the use of within-family GWASs, which, because of the randomness of mendelian segregation within pedigrees, are often interpreted as producing unbiased estimates of direct effects. Here, we present a general theoretical analysis of the influence of confounding in standard population-based and within-family GWASs. We show that, contrary to common interpretation, family-based estimates of direct effects can be biased by genetic confounding. In humans, such biases will often be small per-locus, but can be compounded when effect-size estimates are used in polygenic scores (PGSs). We illustrate the influence of genetic confounding on population- and family-based estimates of direct effects using models of assortative mating, population stratification, and stabilizing selection on GWAS traits. We further show how family-based estimates of indirect genetic effects, based on comparisons of parentally transmitted and untransmitted alleles, can suffer substantial genetic confounding. We conclude that, while family-based studies have placed GWAS estimation on a more rigorous footing, they carry subtle issues of interpretation that arise from confounding.