A Novel Genetic Inference Method for Detecting Rare Disease Variants

Undiagnosed cases of Long QT syndrome have been found, thanks to an inventive examination of shared genomic sequences, which is a sign of distant “relatedness” and can cause irregular heart rhythms, fainting, and sudden cardiac death.

The results, which were published in the journal Nature Communications, demonstrate the viability of a novel strategy created by Vanderbilt University Medical Center researchers to identify carriers of rare disease-causing genetic variations who have not yet been diagnosed.

Rare genetic diseases are usually studied in referral populations people who have been referred to specialty clinics for evaluation but this approach often overestimates the true population impact, which would be better assessed in large non-referral populations, such as biobanks.”

Jennifer (Piper) Below, Professor and Senior Corresponding Author, Division of Genetic Medicine, Vanderbilt University

The majority of biobank participants are drawn from the same geographic area, and there is frequently a high degree of unrecorded relatedness between the individuals. This leads to genetic segments that are shared because of a shared ancestor or “identical-by-descent” segments, as described below.

“Identical-by-descent segments give us an opportunity to cluster related people to find rare variants that were present in a common ancestor,” she said.

The researchers created DRIVE (Distant Relatedness for Identification and Variant Evaluation), a genetic inference technique, to do this. Co-first authors Hung-Hsin Chen, PhD, a Postdoctoral Fellow in the Division of Genetic Medicine, and Megan Lancaster, MD, PhD, a Clinical Fellow in the Division of Cardiovascular Medicine, oversaw the investigations.

A Co-Senior Author is Dan Roden, MD, the Sam L. Clark, MD, PhD Chair and Senior Vice President for Personalized Medicine.

The researchers concentrated on an uncommon variation in the KCNE1 gene that underlies Type 5 diabetes to test DRIVE.

An international partnership including 26 facilities has discovered 19 cases of a different syndrome linked to mutations in KCNE1, 140 additional carrier relatives, and 89 probands (affected persons who are the initial participants of a genetic investigation) with potential LQT5.

Nine (26%) of the 35 probands with the most prevalent KCNE1 mutation (p.Asp76Asn) were examined by the VUMC Genetic Arrhythmia Clinic. It was unknown if any of the probands were related. It was also discovered that three of the probands' relatives carried the variation.

This enrichment of a rare variant at VUMC relative to other centers in the consortium suggested that these local probands may be distantly related and that we could use that relatedness to identify additional carriers in BioVU.”

Jennifer Piper Below, Professor and Senior Corresponding Author, Division of Genetic Medicine, Vanderbilt University

VUMC's DNA biobank, known as BioVU, is connected to de-identified electronic health records.

First, the group created lineage pedigrees and evaluated the genome-wide relatedness of the 12 clinically identified p.Asp76Asn carriers. The theory of a local common ancestor with the p.Asp76Asn variant was supported by the eighth to ninth degree relatedness they discovered among these pedigrees (for example, fourth cousins, who are the great-grandchildren of first cousins, are ninth degree relatives).

After that, the researchers used DRIVE on 69,819 BioVU participants after finding shared genetic areas spanning the KCNE1 gene. By using DNA sequencing to confirm the p.Asp76Asn mutation, they were able to identify 22 BioVU individuals who shared the same location. Additionally, they examined electrocardiograms and medical records for signs of LQT5.

Comparing referral and non-referral carriers of the variation to controls, the QT interval is longer.

In this study, we used DRIVE to rapidly pinpoint 22 carriers of a previously described pathogenic gene variant, DRIVE could also be used to identify unknown causal gene variants, by clustering individuals with shared identical-by-descent segments and assessing the enrichment of disease within clusters. We are excited about the potential of DRIVE to identify undiagnosed cases of genetic disease.”

Jennifer (Piper) Below, Professor and Senior Corresponding Author, Division of Genetic Medicine, Vanderbilt University