Using genomic data in an EHR, researchers from the Icahn School of Medicine at Mount Sinai in New York identified a subtype of patients with type 2 diabetes.
Researchers analyzed the EHRs and genotype data of more than 11,000 patients. The patients were grouped into subtypes associated with different clinical characteristics based on EHR data. Researchers found unique genetic variants in hundreds of genes for each of the three subtypes.
Those in subtype 1 were more likely to suffer diabetic nephropathy and retinopathy. Those in subtype 2 were more likely to experience cancer and cardiovascular disease, and those in subtype 3 had higher risk of neurological disease, allergies and HIV infections.
"Our approach demonstrates the potential to unlock clinically meaningful patient population subgroups from the wealth of information that is accumulating in [EHRs]," said Ronald Tamer, MD, co-author of the study and director of the Mount Sinai Clinical Diabetes Institute. "The team's results suggest an attractive alternative to the kind of large-scale, narrow phenotype studies that have produced limited success in explaining common, complex disease."
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