New genome analysis scores risk of serious common diseases

15 August 2018 (Last Updated August 15th, 2018 09:52)

A research team in the US has devised a new genome analysis approach that can identify large proportions of people who are at a higher risk of developing serious common diseases such as coronary artery disease.

New genome analysis scores risk of serious common diseases
Using ‘polygenic risk scoring’, researchers can identify people at high risk for common diseases. Credit: Lauren Solomon/Broad Communications.

A research team in the US has devised a new genome analysis approach that can identify large proportions of people who are at a higher risk of developing serious common diseases such as coronary artery disease.

The research has been carried out by the Broad Institute of MIT and Harvard in partnership with Massachusetts General Hospital (MGH) and Harvard Medical School.

According to the researchers, this polygenic risk scoring can predict greater chances of developing potentially fatal disorders well before the appearance of symptoms.

The scoring for disease risk leverages algorithms that were trained by the team using data obtained during large-scale genome-wide association studies.

“According to the researchers, this polygenic risk scoring can predict greater chances of developing potentially fatal disorders well before the appearance of symptoms.”

These studies were designed to identify genetic variants related to coronary artery disease, atrial fibrillation, type 2 diabetes, inflammatory bowel disease and breast cancer.

A computational algorithm was applied to each disease in order to integrate information from all the variants into a single polygenic risk score. This score can predict a person’s likelihood of developing these diseases depending on their genome.

The polygenic risk score algorithms were tested and validated on data from more than 400,000 individuals in the UK Biobank.

However, the genome analysis tests are primarily based on information from Europeans, and larger studies for additional ethnic groups are required to confirm their applications.

To test for other common diseases, the algorithms require further research for gathering genome-wide association data and validating the scores with reference biobanks.

Broad Institute Cardiovascular Disease Initiative director Sekar Kathiresan said: “We envision polygenic risk scores as a way to identify people at high or low risk for a disease, perhaps as early as birth, and then use that information to target interventions – either lifestyle modifications or treatments – to prevent disease.”