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Genomics-Based Approach to Predicting Drug Side Effects

In addition to pointing toward potential drug targets, genomic data can also provide researchers with an inkling of what the possible side effects of drugs targeting certain genes might be, writes Francis Collins at the NIH Director's Blog.

Because people with type 2 diabetes are at an increased risk of cardiovascular disease, the US Food and Drug Administration has instructed drug developers to ensure that their drugs aimed at treating diabetes don't have an adverse effect on the cardiovascular system. Researchers from University of Cambridge and GlaxoSmithKline reported in Science Translational Medicine recently that they'd used a 'Big Data' approach to gauge a drug's possible side effect early in the development process.

Building on a previous study, the researchers examined 121 variants housed in six genes — genes that encode potential drug targets that had been licensed by or were in development by GlaxoSmithKline to treat diabetes or obesity — and their relationship with a number of metabolic traits. From this, they found that a low-frequency missense variant in the glucagon-like peptide-1 receptor (GLP1R) gene was associated with lower fasting glucose and type 2 diabetes risk. GLP1R, they noted, is the target of GLP1R agonists.

Then by sifting through genomic and clinical data from some 60,000 people with heart disease and 160,000 healthy controls, the researchers found that this minor allele was associated with protection against heart disease. That, in turn, indicates that GLP1R agonists are unlikely to increase the risk of a cardiovascular problem, they say.

"The new study outlines a genomic approach that makes use of several research cohorts of more than 50,000 participants. The hope is that this teaming of genomic and clinical Big Data will help to streamline the drug development process, helping to avoid late-stage failures attributable to lack of efficacy or adverse safety profiles," Collins adds. "That's critical considering that just 1 in 10 drug candidates entering human clinical trials successfully goes on to receive FDA approval."