Research News

According to new research from Cleveland Clinic data scientists led by Daniel Rotroff, PhD, there is a previously unrecognized genetic subtype of patients with type 2 diabetes (T2D) at high risk for cardiovascular disease who may benefit from intensive glycemia treatment. The findings, published in Diabetes Care, offer new insights into personalized care for patients with T2D.

For nearly two decades, findings from the ACCORD (Action to Control Cardiovascular Risk in Diabetes) clinical trial have informed guidelines for treating T2D. The trial enrolled more than 10,000 T2D patients with cardiovascular disease or who were at high risk for developing cardiovascular disease, and investigated whether moderate or intensive treatment to lower blood glucose levels was more effective in preventing or delaying related events, including myocardial infarction, stroke and even death.

Surprisingly, the intensive treatment arm of the trial was terminated early because the researchers saw a significant increase in cardiovascular-related and overall mortality.

“Ultimately, researchers from the ACCORD trial concluded that moderate treatment is optimal for older patients with established cardiovascular disease or those who are at high risk for developing cardiovascular disease,” said Kevin Pantalone, DO, an endocrinologist and Director of Diabetes Initiatives in the Endocrinology & Metabolism Institute and co-author on the study. “This has been the recommendation by the premiere T2D guidelines since completion of the ACCORD trial and other studies, and remains the standard-of-care approach in clinical practice.”

The new findings from Dr. Rotroff’s team reveal that the risks of intensive treatment may not be universal, however, and suggest that a specific subgroup of patients may actually benefit from more aggressive treatment.

Taking a second look: An overlooked subgroup of the intensive treatment group

Here, Dr. Rotroff and his team took another look at the data from the ACCORD clinical trial. “On the whole, participants from the intensive treatment group did experience significantly more adverse events,” said Dr. Rotroff, who is assistant staff in Lerner Research Institute’s Department of Quantitative Health Sciences. “But there was heterogeneity within the intensive treatment group, which signaled to us that a one-size-fits-all approach may not be appropriate.”

The researchers used a first-of-its-kind algorithm to categorize patients from the intensive treatment arm into four groups. Groupings were determined based on glycated hemoglobin A1C (HbA1C) levels at various time points throughout the trial, where HbA1C is an indicator of blood glucose level.

They found that one of the patient groups had more than 50 percent fewer cardiovascular events than patients from the standard treatment group. After analyzing patient genomes, the researchers developed a machine learning-based algorithm to predict who is likely to benefit from intensive glycemia treatment.

“In addition to developing our algorithm, we also found genetic variants—including ones related to the MAS1 gene—that may provide insight into why some patients have such difficulty reaching their optimal blood glucose even when taking medication,” said Dr. Rotroff. “Additional research will be necessary, but we are optimistic that this genetic algorithm could help clinicians identify which patients are optimal candidates for more aggressive glycemia treatment.” 

Arshiya Mariam, a bioinformatics technician in Dr. Rotroff’s lab, was first author on the study, which was supported in part by the Clinical and Translational Science Collaborative of Cleveland, which is funded by the National Center for Advancing Translational Sciences (part of the National Institutes of Health).