Alleviating misclassified germline variants in underrepresented populations: A strategy using popmax

Abstract

Purpose: Germline variant interpretation often depends on population-matched control cohorts. This is not feasible for population groups that are underrepresented in current population reference databases.

Methods: We classify germline variants with population-matched controls for 2 ancestrally diverse cohorts of patients: 132 early-onset or familial colorectal carcinoma patients from Singapore and 100 early-onset colorectal carcinoma patients from the United States. The effects of using a population-mismatched control cohort are simulated by swapping the control cohorts used for each patient cohort, with or without the popmax computational strategy.

Results: Population-matched classifications revealed a combined 62 pathogenic or likely pathogenic (P/LP) variants in 34 genes across both cohorts. Using a population-mismatched control cohort resulted in misclassification of non-P/LP variants as P/LP, driven by the absence of ancestry-specific rare variants in the control cohort. Popmax was more effective in alleviating misclassifications for the Singapore cohort than the US cohort.

Conclusion: Underrepresented population groups can suffer from higher rates of false-positive P/LP results. Popmax can partially alleviate these misclassifications, but its efficacy still depends on the degree with which the population groups are represented in the control cohort.

Keywords: Colorectal carcinoma; Germline variants; Popmax; Underrepresented populations; Variant misclassification.