Researchers at the Icahn School of Medicine at Mount Sinai, New York, have identified three subtypes of patients with type 2 diabetes, which could lead to more customised diagnosis and treatment.
Mount Sinai scientists evaluated the electronic medical records (EMRs) of roughly 2,500 people with type 2 diabetes. The genetic information, health and symptoms of the patients were all assessed, with subtypes based on patterns of clinical characteristics and disease comorbidities.
Joel Dudley, lead author and director of biomedical informatics at the Icahn School of Medicine at Mount Sinai Hospital, said the findings displayed “statistically meaningful differences between patients.”
Using genetic association analysis, three groups of people with type 2 diabetes were identified, each with a different set of problems associated with the disease. More than 300 single nucleotide polymorphisms (SNPs) – these are variations in population based DNA sequences – were identified as being specific to each subtype.
Patients were more likely to be obese, have kidney disease and diabetic retinopathy in subtype 1. In subtype 2, patients had a greater prevalence of both cancer and heart disease, but were less likely to be obese; and in subtype 3, patients had a greater likelihood of heart disease, but also an increased propensity for mental illness and allergies.
Dudley added: “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. 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.”
Dudley and his team believes these distinctions call for “tailored treatment regimens rather than one-size-fits-all approach” for type 2 diabetes, and that more research is required to confirm these findings in other groups of patients.
This study was published in Science Translational Medicine.

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