Detection of Distant Relatedness in Biobanks To Identify Undiagnosed Cases of Mendelian Disease As Applied to Long Qt Syndrome

Authors

Megan C Lancaster
Hung-Hsin Chen
M Benjamin Shoemaker
Matthew R Fleming
Teresa L Strickland
James T Baker
Grahame F Evans
Hannah G Polikowsky
David C Samuels
Chad D Huff
Dan M Roden
Jennifer E Below

Publication Date

8-29-2024

Journal

Nature Communications

Abstract

Rare genetic diseases are typically studied in referral populations, resulting in underdiagnosis and biased assessment of penetrance and phenotype. To address this, we develop a generalizable method of genotype inference based on distant relatedness and deploy this to identify undiagnosed Type 5 Long QT Syndrome (LQT5) rare variant carriers in a non-referral population. We identify 9 LQT5 families referred to a single specialty clinic, each carrying p.Asp76Asn, the most common LQT5 variant. We uncover recent common ancestry and a single shared haplotype among probands. Application to a non-referral population of 69,819 BioVU biobank subjects identifies 22 additional subjects sharing this haplotype, which we confirm to carry p.Asp76Asn. Referral and non-referral carriers have prolonged QT interval corrected for heart rate (QTc) compared to controls, and, among carriers, the QTc polygenic score is independently associated with QTc prolongation. Thus, our innovative analysis of shared chromosomal segments identifies undiagnosed cases of genetic disease and refines the understanding of LQT5 penetrance and phenotype.

Keywords

Humans, Long QT Syndrome, Female, Male, Biological Specimen Banks, Haplotypes, Adult, Penetrance, Middle Aged, Phenotype, Pedigree, Genetic Predisposition to Disease, Genotype, Electrocardiography

Comments

Supplementary Materials

PMID: 39209900