# Cluster-specific genetic associations of CDKAL1, CDKN2A, CDKN2B, HHEX, KCNQ1, MTNR1B, PAX4, SLC30A8, TCF7L2, and UBE2E2 variants in new onset type 2 diabetes

## TL;DR

This study finds that certain genetic variants are linked to specific subtypes of type 2 diabetes, suggesting genetic differences in how the disease manifests.

## Contribution

The study identifies cluster-specific genetic associations in T2D, revealing genetic heterogeneity among subtypes.

## Key findings

- Eight SNPs showed significant associations with T2D clusters, particularly in SIDD and MOD subgroups.
- Genetic heterogeneity was observed in TCF7L2, KCNQ1, and CDKAL1 across T2D clusters.
- Findings suggest potential for precision therapy strategies based on genetic profiles.

## Abstract

Type 2 diabetes (T2D) is a heterogeneous metabolic disorder. Recent cluster-based classifications offer insights into distinct pathophysiological subtypes. The objective of the study is to investigate the association of genetic variants in T2D-related genes with defined T2D clusters. We analyzed 678 single nucleotide polymorphisms (SNPs) from ten genes (CDKAL1, CDKN2A, CDKN2B, HHEX, KCNQ1, MTNR1B, PAX4, SLC30A8, TCF7L2, and UBE2E2) in 471 T2D patients classified into four clusters: Severe Insulin-Deficient Diabetes (SIDD), Mild Obesity-related Diabetes (MOD), Mild Age-related Diabetes (MARD), and Metabolic Syndrome-related Diabetes (MSD). Genotyping was performed using the Axiom PDMRAv2 array. Following Hardy–Weinberg Equilibrium filtering, 376 SNPs were analysed. The association between T2D clusters and SNPs was assessed by multinomial logistic regression. Nineteen SNPs showed significant differences in genotypic frequencies among clusters (p < 0.05). Eight SNPs (rs61875103 in TCF7L2; rs12576156, rs2283220, rs2074197, and rs163165 KCNQ1; rs4710943, rs9368248, and rs6456379 in CDKAL1) significantly associated with cluster assignment. Cluster-specific effects were most notable in SIDD and MOD subgroups. Our findings support genetic heterogeneity of TCF7L2, KCNQ1, and CDKAL1 in T2D clusters and underscore the potential for genetically informed precision therapy strategies.