Alternate approach to genome wide association studies can identify new heritable mutations

11 May 2016

Heart arrhythmia study from MIT demonstrates new technique that can identify previously uncertain genetic variants that cause the condition.

Genome wide association studies aim to identify the common genetic variants shared by patients with the same condition. Progress towards this goal has always difficult due to lack of patients, and therefore data. Without a lot of data, finding a statistically significant variant has always been a problem.

New work by an MIT team focuses on targets which are categorised as sub-threshold i.e linked to the disease, yet without the statistical evidence to prove it.

The team looked at 60 genetic markers with a proven association with heart arrhythmia. Comparing the properties of the epigenomic markers with a computer algorithm found they were mostly situated in regions of the genome known as enhancers, which affect how specific genes are activated. Next, the team looked at sub-threshold variants – weakly linked to heart arrhythmia – filtering them by the same common properties; identifying 60 more markers which could be linked to the disease.

By analysing and predicting which genes these enhancers were modifying, the team were able to experiment in switching those genes off in mice and zebra fish. Many of the genes they identified were proven to have an effect on the heart.

The team believe that their ap proach could easily be adapted to other conditions to identify previously unknown genetic variants without needing ever larger genome wide association studies.

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