AI Article Synopsis

  • KCNJ11 gene is significant for insulin secretion and type 2 diabetes (T2D), but its impact varies across different populations.
  • The study found no KCNJ11 variants linked to T2D in Iranian adults; however, a meta-analysis revealed certain variants (rs5219 and rs5215) increase T2D risk in broader populations.
  • Findings emphasize the need for equal sample sizes in studies for accurate results, helping inform precision medicine strategies regarding T2D.

Article Abstract

Due to the central role in insulin secretion, the potassium inwardly-rectifying channel subfamily J member 11 (KCNJ11) gene is one of the essential genes for type 2 diabetes (T2D) predisposition. However, the relevance of this gene to T2D development is not consistent among diverse populations. In the current study, we aim to capture the possible association of common KCNJ11 variants across Iranian adults, followed by a meta-analysis. We found that the tested variants of KCNJ11 have not contributed to T2D incidence in Iranian adults, consistent with similar insulin secretion levels among individuals with different genotypes. The integration of our results with 72 eligible published case-control studies (41,372 cases and 47,570 controls) as a meta-analysis demonstrated rs5219 and rs5215 are significantly associated with the increased T2D susceptibility under different genetic models. Nevertheless, the stratified analysis according to ethnicity showed rs5219 is involved in the T2D risk among disparate populations, including American, East Asian, European, and Greater Middle Eastern, but not South Asian. Additionally, the meta-regression analysis demonstrated that the sample size of both case and control groups was significantly associated with the magnitude of pooled genetic effect size. The present study can expand our knowledge about the KCNJ11 common variant's contributions to T2D incidence, which is valuable for designing SNP-based panels for potential clinical applications in precision medicine. It also highlights the importance of similar sample sizes for avoiding high heterogeneity and conducting a more precise meta-analysis.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9715540PMC
http://dx.doi.org/10.1038/s41598-022-24931-xDOI Listing

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