Distance relationship in biobanks exploited to identify undiagnosed genetic diseases

Innovative analysis of shared segments within the genome – an indication of distant “relatedness” – has identified undiagnosed cases of long QT syndrome, a rare condition that can lead to abnormal heart rhythms, fainting and cardiac death sudden.

The results, reported in the journal Natural communicationsillustrate the feasibility of the new approach developed by researchers at Vanderbilt University Medical Center to detect undiagnosed carriers of genetic variants responsible for rare diseases.

“Rare genetic diseases are typically studied in reference populations – people who have been referred to specialist clinics for assessment – ​​but this approach often overestimates the true population impact, which would be better assessed in large, non-referenced populations. such as biobanks,” said Jennifer (Piper) Below, Ph.D., professor of medicine in the Division of Genetic Medicine and senior corresponding author of the new study.

Since most biobanks recruit participants from the same region, there are often significant undocumented relationships between participants, resulting in shared genomic segments due to common ancestry – “identical by descent” segments. ”, explained below.

“Identical segments by descent give us the opportunity to group related people together to find rare variants present in a common ancestor,” she said.

To do this, researchers have developed a genetic inference method called DRIVE (Distant Relatedness for Identification and Variant Evaluation). The studies were led by co-first authors Megan Lancaster, MD, Ph.D., clinical fellow in the Division of Cardiovascular Medicine, and Hung-Hsin Chen, Ph.D., postdoctoral fellow in the Division of Genetics. Medicine. Dan Roden, MD, Sam L. Clark, MD, Ph.D. President and Senior Vice President for Personalized Medicine, is co-senior author.

To test DRIVE, researchers focused on a rare variant of the KCNE1 gene that causes long QT syndrome type 5 (LQT5). The KCNE1 gene codes for a protein that modifies potassium currents.

An international consortium of 26 centers had identified 89 probands (affected individuals who are the first subjects of a genetic study) with possible LQT5, 140 additional parent carriers, and 19 cases of another syndrome attributed to KCNE1 variants.

Of 35 candidates with the most common KCNE1 variant (p.Asp76Asn), nine (26%) were evaluated by the VUMC Genetic Arrhythmia Clinic. None of the probands were known to be related. Three relatives of the applicants were also found to carry the variant.

“This enrichment of a rare variant at VUMC compared to other centers in the consortium suggests that these local candidates may be distantly related and that we could use this relatedness to identify additional carriers in BioVU,” Below said. BioVU is VUMC’s DNA biobank linked to de-identified electronic health records.

The team first estimated the genome-wide relatedness of the 12 clinically identified p.Asp76Asn carriers and constructed the lineage pedigrees. They found eighth- to ninth-degree relatedness among these pedigrees (for reference, fourth cousins ​​– great-grandchildren of first cousins ​​– are ninth-degree relatives), supporting the hypothesis of a local common ancestor with the p.Asp76Asn variant.

Next, the researchers identified shared genomic regions spanning the KCNE1 gene and applied DRIVE to 69,819 BioVU subjects. They identified 22 BioVU subjects with the shared region, confirmed the p.Asp76Asn variant by DNA sequencing, and evaluated electrocardiograms and medical records for LQT5 features.

Reference and non-reference variant carriers have a prolonged QT interval compared to controls.

“In this study, we used DRIVE to rapidly identify 22 carriers of a previously described disease-causing gene variant,” Below said. “DRIVE could also be used to identify unknown causal genetic variants, by grouping individuals with identical segments by descent and assessing disease enrichment within groups.

“We are excited about the potential of DRIVE to identify undiagnosed cases of genetic diseases.”