A new study published in The Lancet clusters individuals with adult-onset diabetes and describes novel subgroups and outcomes associated with these data. Research led by Professor Leif Groop of the Lund University Diabetes Centre in Sweden and the Institute for Molecular Medicine Finland in Helsinki and colleagues groups individuals with adult-onset diabetes and describes associated novel subgroups and outcomes. The data encompassed by the study findings are critical, the scientists say, in defining the potential progression of diabetes.
The researchers noted that in addition to acquired risks, elevations in blood glucose can be caused by many genetic factors, leading to this heterogeneous clinical presentation and patient-specific disease progression. Groop and his team propose using this refined diabetes classification based on its heterogeneity to help better predict which individuals are most likely to develop complications and allow for a more personalized treatment approach. In their study, the researchers propose that diabetes should no longer be categorized as just two main types. Instead, they suggest that diabetes be classified into five distinct types.
The clusters analyzed in the Swedish study were based on six variables that included age at diagnosis, BMI, HbA1c, presence of antibodies (to glutamate decarboxylase), and assessment of beta-cell function and insulin resistance. These factors were then compared to patient records on the development of complications and medication interventions used, if any. Cox regression and logistic regression were used to compare time-to-medication intervention, reaching the treatment goal, risk of diabetic complications, and subsequent potential genetic associations.
Five clusters of patients with diabetes were identified in the study, and each had significantly different patient characteristics and risk of diabetic complications. Three of the clusters (clusters 1-3 below) were identified as severe:
• Cluster 1: severe autoimmune diabetes (currently known as type 1 diabetes), characterized by insulin deficiency and the presence of autoantibodies. This was identified in 6% to 15% of subjects.
• Cluster 2: severe insulin-deficient diabetes, characterized by younger age, insulin deficiency, and poor metabolic control, but no autoantibodies. This was identified in 9% to 20% of subjects.
• Cluster 3: severe insulin-resistant diabetes, characterized by severe insulin resistance and a significantly higher risk of kidney disease. This was identified in 11% to 17% of subjects.
• Cluster 4: mild obesity-related diabetes, most common in obese individuals. This affected 18% to 23% of subjects.
• Cluster 5: mild age-related diabetes, most common in elderly individuals. This was the most common form, affecting 39% to 47% of subjects.
Authors noted that patients categorized in cluster 3 had the most significant resistance to insulin and much higher risk of kidney complications, and patients in cluster 2 had the most significant risk of retinopathy. When clusters were compared, however, most had been prescribed similar diabetic interventions despite the unique challenges, complications, and negative outcomes.