  It is increasingly recognized that participation bias can pose problems for
genetic studies. Recently, to overcome the challenge that genetic information
of non-participants is unavailable, it is shown that by comparing the IBD
(identity by descent) shared and not-shared segments among the participants,
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, for phenotypes
whose mean differences between population and sample are known, we demonstrate
a way to do so by adopting a statistical framework that separates out the
genetic and non-genetic 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 8 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.
