Refining rare disease variant discovery in an isolated Andean community through imputation-enhanced IBD and kinship inference from whole exome sequencing data

Abstract

Rare genetic diseases pose significant diagnostic challenges, especially in geographically isolated populations where consanguinity, founder effects, and novel variants often influence disease patterns. Whole-exome sequencing (WES) is standard practice for rare disease diagnostics, but its limited coverage of noncoding regions limits inheritance-by-descent (IBD) and Runs of Homozygosity (RoH) inference. In this study, we tested an imputation-enhanced IBD and RoH detection method using WES data of 84 individuals from 51 families in Boyacá, Colombia—an Andean region with complex admixed American ancestry. By leveraging large, multi-ancestry reference panels to impute genotypes and increase variant distribution, we achieved improved detection of IBD and RoH regions, with KING showing the best results among the different tools that were tested. Imputation with the 1000 Genome reference panel underperformed compared to raw WES data, whereas large reference panels with diverse ancestry showed the best performance. By integrating these refined IBD results with pedigree information, we identified cryptic family relationships, clarified the role of consanguinity, and improved the prioritization of candidate variants. Our findings show that imputation-enhanced IBD analyses can bolster the utility of WES for rare disease studies, contributing to more accurate and timely genetic diagnoses. Keywords: Genotype imputation, Undiagnosed rare diseases, Kinship inference, Identity-by-descent, Consanguinity