Diabetes Genetic Clusters and Clinical Outcomes in the Chronic Renal Insufficiency Cohort.

KEY POINTS: Type 2 diabetes partitioned polygenic scores capture metabolic profiles for obesity, β-cell with positive proinsulin, and lipodystrophy clusters in CKD. The type 2 diabetes obesity genetic cluster was associated with higher risk of overall mortality among individuals with CKD.

BACKGROUND

Type 2 diabetes (T2D) exhibits biologic and pathophysiologic heterogeneity, which may contribute to variations in diabetes-related complications, particularly in high-risk populations such as individuals with CKD. Prior research has explored T2D mechanisms using partitioned polygenic scores (pPGS), derived from distinct clusters of variants according to their associations with cardiometabolic traits. In this study, we investigated whether cluster-specific pPGS are associated with cardiovascular outcomes and CKD progression in individuals with CKD.

METHODS

We used genome-wide genotype data from the Chronic Renal Insufficiency Cohort (CRIC) to calculate both a total polygenic score for T2D and pPGS for T2D clusters. We examined their associations with cardiometabolic traits and conducted time-to-event analysis to assess their association with mortality (overall and cardiovascular), incident cardiovascular outcomes (myocardial infarction, stroke, heart failure, atrial fibrillation [AFIB], peripheral artery disease, and a composite of major cardiovascular events), and CKD progression.

RESULTS

Among 3577 CRIC participants (mean age 58 years, 45% were women, 49% had T2D), the total polygenic score was significantly associated with higher hemoglobin A1c (P = 4.8×10−21) among nondiabetic participants. Cluster-specific pPGS in CRIC captured distinct cardiometabolic profiles corresponding to T2D mechanistic subtypes, particularly the obesity cluster, the β-cell dysfunction with positive proinsulin cluster, and the lipodystrophy cluster. The obesity cluster pPGS was significantly associated with incident AFIB (P = 2.89×10−4) and overall mortality (P = 4.29×10−4), but the association with AFIB was attenuated when accounting for competing risk of death (P = 0.002). The β-cell dysfunction with negative proinsulin cluster was inversely associated with CKD progression (P = 2.48×10−5).

CONCLUSIONS

Our findings suggest that T2D driven by insulin resistance and obesity contributes to a higher risk of overall death in individuals with CKD and explain in part the higher risk of AFIB. These results highlight the importance of considering T2D heterogeneity when assessing cardiovascular risk in this population.