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

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.

Authors

Institutions

Publication Details

Journal
Human Molecular Genetics
Published
2025-08-15
DOI
https://doi.org/10.1093/hmg/ddaf132
Primary Topic
Genomics and Rare Diseases
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Rodrigo Cabrera, Dora Janeth Fonseca, Carlos Martín Restrepo, Adrien Morel et al.
Human Molecular Genetics
Genomics and Rare Diseases
article

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

Rodrigo Cabrera, Dora Janeth Fonseca, Carlos Martín Restrepo, Adrien Morel, Andrea Casas‐Vargas, Cristian Camilo Gaviria-Sabogal, Nora Contreras Bravo, I. Bernal, William Usaquén, Yasmín Sánchez‐Gómez
article en

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.

Human Molecular GeneticsVol. 34(20)
University of Boyaca (CO), Universidad Nacional de Colombia (CO), Universidad del Rosario (CO)
Universidad Nacional de Colombia, Universidad del Rosario
Openalex Percentile: Top 77%
Genomics and Rare Diseases
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.