NEW YORK, Oct. 30 (UPI) -- Researchers at Mount Sinai Hospital have identified three subtypes of type 2 diabetes after analyzing more than 11,000 patient records and identifying common genetic variants among them.
The approach taken in analyzing the records has researchers suggesting a similar approach can be applied to other diseases when searching for ways to make treatment better tailored to specific patients.
"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," said Dr. Ronald Tamler, director of the Mount Sinai Clinical Diabetes Institute, in a press release. "The unique genetic component of this study yielded high-priority variants for follow-up study in patients with type 2 diabetes. 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."
Utilizing electronic medical records at Mount Sinai Medical Center, the researchers reviewed the records of more than 11,000 patients, classifying them by genotype and then genomic analysis pinpointing common genetic variants representative of each subtype.
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The researchers found subtype 1 followed the classic symptoms of type 2 diabetes -- obesity, high blood sugar, kidney disease, and eye disease -- while subtype 2 was more likely to play a role in cancer and cardiovascular disease and subtype 3 was marked by neurological disease, allergies and HIV infections. The researchers also found unique genetic variants in each subtype for 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," said Dr. Joel Dudley, Director of Biomedical Informatics at the Icahn School of Medicine at Mount Sinai. "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."
The study is published in Science Translational Medicine.
