Researchers Use EMRs to Identify Subgroups of Type 2 Diabetes

Nov. 5, 2015
By analyzing electronic medical records (EMRs) and genotype data, researchers at the Icahn School of Medicine at Mount Sinai in New York City identified a subtype of patients with type 2 diabetes.

By analyzing electronic medical records (EMRs) and genotype data, researchers at the Icahn School of Medicine at Mount Sinai in New York City identified a subtype of patients with type 2 diabetes.

The research, published in Science Translational Medicine¸ details a complex network analysis of EMRs and for more than 11,000 patients and offers a glimpse of precision medicine in action, according to a statement from the Mount Sinai Health System, and points to the “possibility for more tailored diagnosis and treatment of type 2 diabetes in the future, but also reveals a novel approach that can be applied to virtually any disease.”

For the research, patients were grouped into three distinct subtypes based on EMR data, followed by genomic analysis pinpointing common genetic variants representative of each subtype. These subtypes were associated with different clinical characteristics. Patients were more likely to suffer diabetic nephropathy and retinopathy in subtype 1; cancer and cardiovascular disease in subtype 2; and neurological disease, allergies, and HIV infections in subtype 3. For each subtype, the researchers discovered unique genetic variants in hundreds of genes.

"This project demonstrates the very real promise of precision medicine to improve healthcare by tailoring diagnosis and treatment to each patient, as well as by learning from each patient," Joel Dudley, PhD, senior author on the paper and director of Biomedical Informatics at the Icahn School of Medicine at Mount Sinai, said in a statement. "It is absolutely encouraging that we were able to paint a much higher-resolution understanding for a common and complex disease that has long stymied the biomedical community with its heterogeneity. I look forward to seeing what we can accomplish for other patient populations."

Type 2 diabetes has quickly become a leading cause of death, and the World Health Organization estimates that 8 percent of the global adult population has the disease. The medical community has struggled to diagnose and treat type 2 diabetes because it presents with many different symptoms and a wide range of associated complications. It has long been thought that the disease, like cancer, could be treated more successfully if patients could be grouped into clinically distinct subtypes with more specific prognoses, according to the researchers’ report.

"Our approach demonstrates the potential to unlock clinically meaningful patient population subgroups from the wealth of information that is accumulating in electronic medical record systems. The unique genetic component of this study yielded high-priority variants for follow-up study in patients with type 2 diabetes,"  Ronald Tamler, M.D., co-author of the study and director of the Mount Sinai Clinical Diabetes Institute, within the Mount Sinai Health System. "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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