Metabolic gene polymorphisms and type 2 diabetes mellitus risk: a systematic review and meta‑analyses - Indarto, Dono; Susilawati, Tri N.; Suselo, Yuliana H.; Rejeki, Purwo S.; Feng, Yuxi; Wibowo, Yohanes Cakrapradipta; Mahanani, Melani R. (Experimental and Therapeutic Medicine, 2026)
The present systematic review and meta‑analysis aimed to explore the associations between four diabetic‑related genes [dipeptidyl peptidase‑4 (DPP4), glucagon‑like peptide‑1 receptor (GLP1R), protein tyrosine phosphatase non‑receptor type 1 (PTPN1) and CD36] and the risk of type 2 diabetes mellitus (T2DM) across different body weight categories. A comprehensive search for all available evidence was conducted on the associations between these four genes and T2DM, up to March 31, 2024, and 11 meta‑analyses were performed on genetic polymorphisms that had been examined in >2 studies. A total of 36 studies were identified, investigating the association between the four genes of interest and T2DM risk. Notably, the 11 meta‑analyses on polymorphisms in GLP1R, PTPN1 and CD36 did not reveal any significant associations between the specific genetic variants and T2DM risk. Specifically, the meta‑analysis on the CD36 rs1761667 polymorphism showed no significant association with T2DM, either in the overall population or when stratified by body weight category. The funnel plots and results from the Egger's test indicated some variation. Furthermore, while the leave‑one‑out analyses of the GLP1R and PTPN1 polymorphisms showed some differences compared with the overall estimates, these may be a part of a broader sensitivity analysis, rather than definitive evidence of an impact. Despite the extensive systematic review and meta‑analysis of data from multiple studies, the evidence for an influence of various polymorphisms in key metabolic genes on T2DM risk was not statistically significant. Future research should focus on larger and more diverse populations, potentially examining additional genetic variants and their interactions with other risk factors to improve the understanding of the complex nature of T2DM.