Rare genetic variants associated with cardiometabolic diseases discovered

Analysis of recently released exome sequence data has identified an association between rare genetic variants and cardiometabolic diseases, such as diabetes and heart failure.

Published in Nature Genetics, the study carried out by researchers at the Broad Institute, Cambridge, Massachusetts focused on the contribution of rare genetic variants to 83 cardiometabolic diseases and traits. Of the diseases studied, the findings identified 57 associations between the genetic variants and cardiometabolic diseases. Significantly, the findings confirmed 42 previously known associations as well as highlighting 15 novel links.

'Our findings may help both geneticists and clinicians better understand the relative risk conferred by disease-causing variants,' claimed Sean Jurgens, co-first author of the study and a scholar with the Cardiovascular Disease Initiative at the Broad Institute.

The data analysed as part of the study, gathered from around 200,000 people, was released by the UK Biobank, a comprehensive database of genetic and health information assembled from 500,000 people. For this study, researchers focused on sequence data from only the protein coding region of the genome, known as the exome.

The team at the Broad Institute narrowed their attention to genetic variants which functionally disable a gene, commonly referred to as 'loss of function' variants. Through this approach, the research team could pinpoint genes that have a more prominent role in the development of disease. Importantly, analysis of the whole dataset found that between 1-2.4 percent of participants possessed rare genetic variants which may lead to cardiometabolic disorders.

To improve the validity of their findings, the researchers assessed whether the results from the UK Biobank data were replicated in an alternative dataset. Through a collaboration with the Geisinger health system, the researchers analysed exome sequencing data from nearly 175,000 participants in the USA, collected during the MyCode cohort study. The team tested 14 of the novel associations they had initially discovered against the new dataset and found that 13 were replicated within the MyCode cohort participants. The consistency of the results across the two separate cohort studies indicates that their novel findings were not specific to the data gathered by the UK Biobank.

New risk variants were identified in the study, some of them in genes which already have more common known variants associated with an increased risk of disease. For example, variants on the GIGYF1 gene have already been associated with type II diabetes risk and this study uncovered some other rarer variants on this genes that were also associated with increase type II diabetes risk.

The discovery of such a high rate of rare disease-associated variants could have implications for screening.