After carefully analyzing the electronic health records (EHRs) of 11,000 patients, investigators at the Icahn School of Medicine at Mount Sinai have discovered three potential new subtypes of type 2 diabetes.
The discovery, led by Joel Dudley, PhD, Director of Biomedical Informatics at the Icahn School of Medicine, highlights the power of new technology and the promise of precision medicine, as the Mount Sinai Health System ushers in the use of Big Data in discovering, treating, and preventing disease. The results of the study were published in Science Translational Medicine in October, 2015.
“There has been a lot of talk about ‘precision medicine,’ but not a lot of people actually doing it,” says Dr. Dudley. “Our research puts Mount Sinai in the forefront of this effort and provides a concrete example of what precision medicine looks like: redefining patient populations and disease with data.”
In his recent blog post, Francis S. Collins, MD, PhD, Director of the National Institutes of Health (NIH), noted Mount Sinai’s findings, writing that “researchers demonstrated the tremendous potential of using EHRs, combined with genome-wide analysis, to learn more about a common, chronic disease—type 2 diabetes.”
Dr. Collins wrote that Mount Sinai’s approach was “similar to building a social network with connections forged not on friendships but medical information. When the resulting network was color-coded to reveal participants with type 2 diabetes, an interesting pattern emerged. Instead of being located in one large clump on this ‘map,’ the points indicating people with type 2 diabetes were actually grouped into several smaller, distinct clusters, suggesting the disease may have subtypes.”
According to Dr. Dudley, some doctors had noticed the unique characteristics in patients with diabetes, but this was the first time these groupings were proven to be significant. More than 29 million people in the United States have diabetes.
“Experienced clinicians have always suspected that not all people with type 2 diabetes are the same,” says Ronald Tamler, MD, PhD, Director of the Mount Sinai Clinical Diabetes Institute, and a co-author of the study. “These new findings will eventually help us recommend a tailored regimen for treatment and complication prevention for a given diabetes subtype.”
Over two years, the researchers analyzed vast troves of patient data in the Icahn School of Medicine at Mount Sinai’s racially and socioeconomically diverse BioMe™ Biobank Program. They located 2,551 patients with type 2 diabetes and found that people with the disease naturally grouped into three subtypes: those most at risk for developing diabetic nephropathy and retinopathy; cancer and cardiovascular disease; or neurological disease, allergies, and HIV infections. For each subtype, the researchers discovered unique genetic variants in hundreds of genes.
In their next phase of study, the researchers plan to evaluate whether the genetic variants they have identified are able to reliably predict the complications a person with type 2 diabetes is most likely to experience.
Their hope is that ultimately, diabetic patients will receive highly individualized treatment plans that are far more effective than today’s reliance on a “one-size-fits-all” approach.