Detection of distant familial relatedness in biobanks for identification of undiagnosed carriers of a Mendelian disease variant: application to Long QT syndrome

Abstract

Importance: The diagnosis and study of rare genetic disease is often limited to referral populations, leading to underdiagnosis and a biased assessment of penetrance and phenotype.

Objective: To develop a generalizable method of genotype inference based on distant relatedness and to deploy this to identify undiagnosed Type 5 Long QT Syndrome (LQT5) rare variant carriers in a non-referral population.

Participants: We identified 9 LQT5 probands and 3 first-degree relatives referred to a single Genetic Arrhythmia clinic, each carrying D76N (p.Asp76Asn), the most common variant implicated in LQT5. The non-referral population consisted of 69,879 ancestry-matched subjects in BioVU, a large biobank that links electronic health records to dense array data. Participants were enrolled from 2007-2022. Data analysis was performed in 2022.

Exposures: We developed and applied a novel approach to genotype inference (Distant Relatedness for Identification and Variant Evaluation, or DRIVE) to identify shared, identical-by-descent (IBD) large chromosomal segments in array data.

Main outcomes and measures: We sought to establish genetic relatedness among the probands and to use genomic segments underlying D76N to identify other potential carriers in BioVU. We then further studied the role of D76N in LQT5 pathogenesis.

Results: Genetic reconstruction of pedigrees and distant relatedness detection among clinic probands using DRIVE revealed shared recent common ancestry and identified a single long shared haplotype. Interrogation of the non-referral population in BioVU identified a further 23 subjects sharing this haplotype, and sequencing confirmed D76N carrier status in 22, all previously undiagnosed with LQT5. The QTc was prolonged in D76N carriers compared to BioVU controls, with 40% penetrance of QTc ≥ 480 msec. Among D76N carriers, a QTc polygenic score was additively associated with QTc prolongation.

Conclusions and relevance: Detection of IBD shared chromosomal segments around D76N enabled identification of distantly related and previously undiagnosed rare-variant carriers, demonstrated the contribution of polygenic risk to monogenic disease penetrance, and further established LQT5 as a primary arrhythmia disorder. Analysis of shared chromosomal regions spanning disease-causing mutations can identify undiagnosed cases of genetic diseases.

Figure 1.. A) The DRIVE tool for local IBD clustering.

This new tool identifies groups of people who share an IBD segment spanning a specific genomic region (in this study, the gene KCNE1). i. DRIVE first selects the pairwise IBD segments spanning the target gene/variant among clinic samples and biobank subjects. ii. DRIVE uses a random walk approach to cluster subjects who share the same haplotype. iii. DRIVE repeats the clustering steps for large and sparse clusters. iv. The inverse of the IBD segment lengths is used to represent genetic distance in a phylogenetic dendrogram. Sequence data can be integrated with the dendrogram to infer where in the family history of the genomic region the mutation event occurred (red star). B) Study subjects. Clinic D76N carriers comprise nine probands seen at the VUMC Genetic Arrhythmia Clinic and three related carriers identified through cascade screening. IBD-based genotype inference using the DRIVE tool was deployed in VUMC BioVU, which links the deidentified electronic health record to genomic data, to identify individuals who shared chromosomal segments at KCNE1 with the clinic carriers. Exome sequencing confirmed D76N carrier status in 22/23 biobank individuals identified via IBD, resulting in total of 34 D76N carriers at a single center. IBD = identical by descent, WES = exome sequencing, DRIVE = Distant relatedness for Identification and Variant Evaluation. 0000-0001-6824-7155

Figure 2.. D76N probands are distantly related.

Analysis of genome-wide IBD sharing in the clinic D76N carriers was used to reconstruct all known pedigrees of first-degree relatives and to identify previously unknown eighth to ninth degree relatedness among these pedigrees and three of the probands without close relatives. It is possible that more distant relatedness exists between the families that is beyond the limit of detection of existing tools (~9^th degree). The colored dashed lines indicate shared IBD segments (≥ 3 cM) spanning KCNE1, both those harboring D76N (orange) and not (blue). IBD = identical by descent

Figure 3.. IBD clustering revealed distantly related subjects in the biobank.

Local IBD sharing at KCNE1 was analyzed between the 12 clinic carriers and the 69,879 subjects in BioVU of European descent. This identified two clusters containing known carriers, with an additional 23 subjects sharing the same chromosomal segment at KCNE1. Of the 23 BioVU subjects, exome sequencing confirmed D76N in 22. In the connection plots for cluster A (A) and cluster B (B), individuals are represented by the segments along the periphery. Shared chromosomal segments at KCNE1 between individuals are indicated by the red and gray connectors. C) Illustration of the length and position of the shared segments spanning KCNE1 among members of cluster A (red), members of cluster B (purple), and in members of both cluster A and B (blue). D) The dendrograms for cluster A and cluster B represent generational distance between subjects based on the inverse of the length of the IBD segments underlying KCNE1 (labeled). All clinic subjects (“C” prefix) had D76N carriership determined by clinical-grade commercial testing.* indicates confirmation of D76N carriership by whole exome sequencing (WES), and the red star indicates the possible mutation event on the shared haplotype. The annotated branch length in the dendrograms for cluster A and cluster B represents the local familial distance between subjects, estimated as the inverse of the length of the IBD segments underlying KCNE1 (numeric label on each node). IBD = identical by descent

Figure 4.. The QTc and polygenic risk in D76N carriers compared to population controls.

A) ECGs meeting criteria detailed in eMethods were available for all clinic carriers, and for 13 of 22 biobank (BioVU) carriers. The ancestry-matched BioVU controls were selected as detailed in Methods. For both carriers and controls, if multiple ECGs were available for a subject, the maximum QTc was used. Male carrier QTcs were adjusted to female sex by adding 11.3 msec (derived from the difference between males and females in the control group when adjusted for age and PRS). The QTc was prolonged in carriers (465±6.2 msec, n=25) compared to female controls (429±22.9 msec, n= 2218; p-value=4.2x10⁻⁵). The boxplot shows the three quartiles (25%, 50%, and 75%) of the carriers. P-values indicate the result of the Welch unequal variances t-test between carriers and controls, with p-value<0.05 considered significant. B) Carriers have a longer QTc than controls with the same PRS. The PRS for the QTc was calculated for each carrier (clinic n=12, BioVU n=13) and for the ancestry-matched BioVU controls (n=3,436) with ECG data meeting criteria as detailed in eMethods. The predicted QTc as a function of PRS is shown for carriers (blue line) and non-carriers (gray line). C) Carriers with a prolonged QTc have a higher PRS than carriers with a normal QTc. The maximum QTc meeting inclusion criteria was used, and was adjusted for age and sex. The p-values indicates the result of Mann Whitney U test comparing carriers with maximum QTc <480, and ≥480 msec. P-value <0.05 was considered significant. PRS = polygenic risk score.