For the first time, scientists have used polygenic scoring to identify molecular drivers of cardiovascular disease and diabetes, which could be targeted to prevent or treat the chronic and costly conditions.
A team of researchers led by the Baker Institute’s Systems Genomics lab — in collaboration with Cambridge University, Harvard Medical School, and the Broad Institute — examined longitudinal data from more than 3000 healthy individuals.
Those with polygenic scores identifying a higher risk of coronary artery disease, type 2 diabetes, chronic kidney disease, and ischaemic stroke were found to have nonstandard levels of 49 plasma proteins.
The study results — — showed 28 of these plasma proteins were associated with those in the healthy sample group who went on to have a future heart attack or develop type 2 diabetes.
Lead researcher said 16 of these proteins were shown to play a causal role in disease development, and of these, 12 were identified as potential druggable targets, opening up avenues for novel therapies.
Dr Ritchie said the pioneering research demonstrated that polygenic scores designed to calculate a person’s individual risk of cardiometabolic disease could also be used to identify molecular mechanisms underlying the development of these same diseases.
“Cardiometabolic diseases such as heart disease and type 2 diabetes are frequently ‘polygenic’ in architecture, which means they comprise a large number of risk gene variants with small effects spread across the human genome,” he said.
“Polygenic scores aggregate these variations into a metric which represents an individual’s genetic predisposition to a specific cardiometabolic disease.
“Previous work from our research group, and others, has shown these scores can help predict someone’s individual risk of serious conditions such as coronary artery disease and stroke.
“But this study takes polygenic scoring one step further to show they can also be used to help us better understand disease biology.
“Our results demonstrate the potential for polygenic scores to uncover biological causes of disease and potential treatments to address them, which may have previously been missed.”
