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There are three subtypes of type 2 diabetes, discovered scientists. They analysed more than 11,000 patient records and located some genetic variants that were common among those traces, according to diabetes.

Hence, after studying 11,000 patients, scientists at the Icahn School of Medicine at Mount Sinai arrived at a complex network analysis of "electronic medical records (EMRs) and genotype data".

The patients were divided into three distinct subtypes, which took its reference from the EMR data, and then described with the help of genomic analysis that examined and located genetic variants that were common, and represented each subtype.

The scientists found that "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," according to ndtv.

In every subtype, scientists found distinguishing genetic variants in multiple 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 Joel Dudley, senior author on the paper and 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," Mr Dudley said.

"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, co-author of the study and Director of the Mount Sinai Clinical Diabetes Institute, within the Mount Sinai Health System.

"The unique genetic component of this study yielded high-priority variants for follow-up study in patients with type 2 diabetes," Dr Tamler said.

The study was published in Science Translational Medicine.