A new study from the University of Pittsburgh reveals that women who develop type 2 diabetes after gestational diabetes can be categorized into three distinct “clusters,” each characterized by a unique molecular driver. These findings, published in Diabetes/Metabolism Research and Reviews, could help guide precision-medicine strategies to prevent or treat type 2 diabetes in this high-risk population.
Lead author Saifer Khan, Ph.D., a researcher at the Vascular Medicine Institute at Pitt and the VA Medical Center in Pittsburgh, explained that while many pathways are implicated in type 2 diabetes, identifying cause-and-effect relationships has been challenging. “By examining this very high-risk group, we were able to focus on the early stages of disease progression and simplify the underlying mechanisms,” Khan said.
The study focused on 225 women who had a history of gestational diabetes and went on to develop type 2 diabetes within 12 years of delivery. The cohort was selected from The Study of Women, Infant Feeding, and Type 2 Diabetes After Gestational Diabetes (The SWIFT Study). The researchers employed computational modeling and machine learning techniques to analyze metabolomic, proteomic, and genomic data, alongside clinical measures such as triglycerides, insulin, and glucose levels.
The study revealed three distinct clusters of women based on the primary molecular drivers of their type 2 diabetes:
Pancreatic Beta-Cell Dysfunction: A group of participants whose diabetes was largely driven by impaired pancreatic beta-cell function.
Insulin Resistance: A second group where insulin resistance was the key factor.
Mixed Mechanism: A third group, comprising about 50% of participants, where both pancreatic dysfunction and insulin resistance contributed to the disease.
This research builds on earlier findings published in Science Advances, which identified molecular mechanisms involved in the progression from gestational diabetes to type 2 diabetes.
Looking ahead, the researchers aim to develop methods for easily determining which cluster a woman belongs to, allowing for targeted interventions that could prevent the progression to type 2 diabetes. This approach could enable earlier, more effective treatments for women at high risk.
Additional contributors to the study include Zhang Xiangyu, Ph.D., and Babak Razani, M.D., Ph.D., from the University of Pittsburgh and the VA Medical Center; Juile Van and Michael B. Wheeler, Ph.D., from the University of Toronto; Stacey Alexeeff, Ph.D., from Kaiser Permanente Northern California; and Erica P. Gunderson, Ph.D., M.P.H., from Kaiser Permanente Northern California and Kaiser Permanente Bernard J. Tyson School of Medicine.
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