Authors
Shuang Song, Stefania Benonisdottir, Jun S Liu, Augustine Kong
Published in
Proceedings of the National Academy of Sciences of the United States of America. Volume 122. Issue 25. Pages e2425530122. Jun 24, 2025. Epub Jun 20, 2025.
Abstract
It is increasingly recognized that participation bias can pose problems for genetic studies. Recently, to overcome the challenge that genetic information of nonparticipants is unavailable, it is shown that by comparing the IBD (identity by descent) shared and not-shared segments between participating relative pairs, one can estimate the genetic component underlying participation. That, however, does not directly address how to adjust estimates of heritability and genetic correlation for phenotypes correlated with participation. Here, we demonstrate a way to do so by adopting a statistical framework that separates the genetic and nongenetic correlations between participation and these phenotypes. Crucially, our method avoids making the assumption that the effect of the genetic component underlying participation is manifested entirely through these other phenotypes. Applying the method to 12 UK Biobank phenotypes, we found eight that have significant genetic correlations with participation, including body mass index, educational attainment, and smoking status. For most of these phenotypes, without adjustments, estimates of heritability and the absolute value of genetic correlation would have underestimation biases.
PMID:
40540605
Bibliographic data and abstract were imported from PubMed on 21 Jun 2025.
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