Researchers Identify 3 Subtypes of Type 2 Diabetes

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By reviewing health records, researchers found 3 distinct subgroups of type 2 diabetes.
By reviewing health records, researchers found 3 distinct subgroups of type 2 diabetes.

(HealthDay News) — Researchers say they have identified 3 distinct subgroups of type 2 diabetes by reviewing the health records of more than 11 000 patients. 

The study findings were published in Science Translational Medicine.

The researchers started with electronic health data from 11 210 patients at Mount Sinai, of whom 2551 had been diagnosed with type 2 diabetes. The data included a full blood panel and a genetic analysis. The research team then created a map on which patients were grouped based on the numbers from their blood tests.

Each of the subgroups faces unique health problems related to type 2 diabetes, and shares common genetic traits that can explain those challenges, senior author Joel Dudley, PhD, told HealthDay. Dudley is director of biomedical informatics and an assistant professor of genetics and genomic sciences at the Mount Sinai School of Medicine in New York City. 

"Not only did the clinical data tell us those were meaningful groups, but the genetics pointed toward potential biological factors that explain these differences in clinical characteristics."

The 3 subtypes identified by the data analysis included a cluster made up of the youngest and most obese patients, who were more likely to suffer kidney disease and blindness, and a group at highest risk for cancer and cardiovascular disease (CVD). 

The other cluster tended to suffer from many different health problems, including CVD, mental illness, allergy, and HIV infection. 

Based on these groupings, a doctor could recommend more aggressive cancer monitoring in some patients, while prescribing heart-healthy medications and lifestyle changes for others, Dudley said.

Reference

  1. Li L, Cheng W-Y, Glicksberg BS, et al. Identification of type 2 diabetes subgroups through topological analysis of patient similarity. Sci Transl Med. 2015;doi:10.1126/scitranslmed.aaa9364.
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