Most disease gene variants show minimal population differentiation despite incomplete coverage

Abstract

BackgroundUnderrepresentation of non-European populations in genomic databases creates challenges for ancestry-matched variant interpretation, particularly when population frequency data are incomplete. Current approaches either assume missing populations have reference allele fixation (naive zero-imputation) or restrict analyses to observed populations (missingness-aware), but the clinical impact of these methodological choices remains unquantified. MethodsWe compared naive and missingness-aware differentiation metrics across 72,915 variants in 17 African-relevant disease genes with documented selection or clinical significance, using 10-population data from the 1000 Genomes Project Phase 3. Genome-wide validation employed 1,102,375 chromosome 22 variants with complete 26-population coverage. Population differentiation was quantified as maximum absolute reference allele frequency difference (max--{Delta}p--). High-differentiation variants (max--{Delta}p-- [≥] 0.5) were compared between disease genes and chromosomal background using Fishers exact tests with bootstrap confidence intervals. ResultsMethods showed high overall correlation (Spearman{rho} = 0.9969) with only 0.71% disagreement (518/72,915 variants), concentrated among variants with incomplete population coverage. However, 350 variants (0.48%) exceeded the high-differentiation threshold, including well-characterized ancestry-informative markers under documented selection. Disease genes showed 4.75- fold depletion of highly differentiated variants relative to genome-wide background (Fishers exact test OR = 0.210, 95% CI [0.188, 0.233], p < 10-316), indicating that functional constraint limits frequency divergence except at sites under positive selection. Complete population coverage eliminated method disagreement (chromosome 22: Spearman{rho} = 1.0000, zero disagreements). ConclusionsAncestry-matched variant interpretation is not universally required but becomes critical for a small, clinically enriched subset (0.48%) showing substantial population differentiation. Functional constraint in disease genes concentrates extreme differentiation at specific adaptive sites rather than distributing it across functionally important regions. These findings provide empirical guidance for resource allocation in equitable variant interpretation frameworks.