Abstract
Background
Single nucleotide polymorphism–based heritability is a fundamental quantity in the
genetic analysis of complex traits. For case-control phenotypes, for which the continuous
distribution of risk in the population is unobserved, observed-scale heritability
estimates must be transformed to the more interpretable liability scale. This article
describes how the field standard approach incorrectly performs the liability correction
in that it does not appropriately account for variation in the proportion of cases
across the cohorts comprising the meta-analysis. We propose a simple solution that
incorporates cohort-specific ascertainment using the summation of effective sample
sizes across cohorts. This solution is applied at the stage of single nucleotide polymorphism–based
heritability estimation and does not require generating updated meta-analytic genome-wide
association study summary statistics.
Methods
We began by performing a series of simulations to examine the ability of the standard
approach and our proposed approach to recapture liability-scale heritability in the
population. We went on to examine the differences in estimates obtained from these
2 approaches for real data for 12 major case-control genome-wide association studies
of psychiatric and neurologic traits.
Results
We found that the field standard approach for performing the liability conversion
can downwardly bias estimates by as much as approximately 50% in simulation and approximately
30% in real data.
Conclusions
Prior estimates of liability-scale heritability for genome-wide association study
meta-analysis may be drastically underestimated. To this end, we strongly recommend
using our proposed approach of using the sum of effective sample sizes across contributing
cohorts to obtain unbiased estimates.
Keywords
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Article Info
Publication History
Published online: June 07, 2022
Accepted:
May 21,
2022
Received in revised form:
May 2,
2022
Received:
September 27,
2021
Publication stage
In Press Journal Pre-ProofIdentification
Copyright
© 2022 Society of Biological Psychiatry.
