ArticleProceedings of the National Academy of Sciences of the United States of America2025
Participation bias in the estimation of heritability and genetic correlation.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Phenomic profiles and disease patterns of 1.9 million participants from Our Future Health.Nature medicine · 2026Article
- Separating direct, indirect, and parent-of-origin genetic effects in the human population.Cell genomics · 2026Article
- Inclusion bias affects common variant discovery and replication in a health-system linked biobank.American journal of human genetics · 2026Article
- Representation in genetic studies affects inference about genetic architecture.bioRxiv : the preprint server for biology · 2026Article
- Genetic underpinnings of chills from art and music.PLoS genetics · 2026Article
- Realizing the full potential of Our Future Health through data linkage and trans-biobank efforts.Nature genetics · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
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