Genetic subtypes of prediabetes, healthy lifestyle, and risk of type 2 diabetes: Prospective cohort study

Objectives: To cluster participants with prediabetes with five type 2 diabetes (T2D)-related partitioned polygenetic risk scores (pPRSs) and examine the risk of incident diabetes and the benefit of adherence to healthy lifestyle across clusters. Design: Prospective cohort study Setting: Hispanic Community Health Study/Study of Latinos (HCHS/SOL), US; UK Biobank (UKBB), UK. Participants: 7,227 US Hispanic/Latinos without diabetes from HCHS/SOL, including 3,677 participants with prediabetes. 400,149 non-Hispanic whites without diabetes from UKBB, including 16,284 participants with prediabetes. Main outcome measures: Prediabetes was defined by fasting plasma glucose (fasting glucose) between 100-125 mg/dL, 2-hour oral glucose tolerance test (OGTT 2h glucose) between 140-199 mg/dL, or hemoglobin A1c (HbA1c) between 5.7% and 6.5%. Diabetes was defined by fasting glucose levels [≥]126 mg/dL, 2h glucose after OGTT [≥]200 mg/dL, HbA1c [≥]6.5%, current use of anti-diabetic medications, or medical record. Five pPRSs representing various pathways related to T2D were calculated based on 94 T2D-related genetic variants. Health lifestyle score was assessed with five modifiable risk factors, including BMI, smoking, alcohol drinking, physical activity, and diet for T2D. Results: Using clustering on five pRPSs, six clusters of individuals with prediabetes with distinctive patterns of pPRSs and corresponding metabolic traits were identified in HCHS/SOL, with each cluster presenting disparate patterns of pPRSs and different patterns of metabolic traits. Except cluster 3 which was not detected, the other five clusters were conformed in participants with prediabetes in UKBB, with each cluster showing the similar patterns of pPRSs as their corresponding cluster in HCHS/SOL. At baseline, proportion of impaired glucose tolerance (IGT)/impaired fasting glucose (IFG) and glycemic traits in HCHS/SOL (fasting glucose, OGTT 2h glucose, and HbA1c) were not significantly different across six clusters (P=0.13, P=0.62, P=0.35, P=0.96, respectively). In UKBB, random glucose and HbA1c at baseline did not show significant difference across five clusters (P=0.43, P=0.71, respectively). Although baseline glycemic traits were similar across clusters, cluster 6, which featured a very low proinsulin score, exhibited elevated risk of incident T2D in both cohorts (risk ratio [RR]=1.39, 95% confidence interval [95% CI]=[1.10, 1.76] vs. cluster 1 in HCHS/SOL; Hazard ratio [HR]=1.29, 95% CI=[1.00, 1.69] vs. cluster 1 in UKBB; Combined RR/HR=1.34 [1.13, 1.60]). To explain the elevated risk of incident T2D in cluster 6, interactions between proinsulin score and other three pPRSs (Beta-cell score, Lipodystrophy-like score, Liver-lipid score) and sum score were detected (P for interaction=0.001, 0.04, 0.02 and 0.002, respectively). Cluster 5 showed an increased risk of incident T2D in UKBB (HR=1.35 [1.05, 1.75] vs. cluster 1) and in the combined analysis with HCHS/SOL (RR/HR=1.29 [1.08, 1.53]), although its risk of T2D was not significantly different from cluster 1 in HCHS/SOL (RR=1.23 [0.96, 1.57]). Inverse associations between the lifestyle score and risk of T2D were observed across different clusters, with a suggestively stronger association in Cluster 5 compared to Cluster 1, in both cohorts. Cluster 5 showed reduced risk of incident diabetes caused by healthy lifestyle score (RR=0.65 [0.47, 0.89], HR=0.71 [0.62, 0.81], respectively. Combined RR/HR=0.70 [0.62, 0.79]). Among individuals with a healthy lifestyle, those in Cluster 5 had a similar risk of T2D compared to those in Cluster 1 (combined RR/HR=1.03 [0.91-1.18]). Conclusions: This study identified genetic subtypes of prediabetes which may differ in risk of progression to T2D and in benefits from healthy lifestyle.