# Association of Genetic Polymorphisms with Gestational Diabetes in a Kazakh Population: A Case–Control Study

## TL;DR

This study investigates genetic factors linked to gestational diabetes in a Kazakh population, finding that multiple genes may interact in small ways to influence risk.

## Contribution

The study explores gene–gene interactions in gestational diabetes among Kazakh women, revealing potential polygenic influences with modest effects.

## Key findings

- The MTNR1B rs10830963 SNP showed a protective effect in univariate analysis but not after adjustment.
- The TCF7L2 rs7903146 SNP was associated with increased GDM risk in the dominant model but not after correction.
- Gene–gene interactions involving IGF2BP2, MTNR1B, and PPARG were identified as statistically significant.

## Abstract

Background: Gestational diabetes mellitus (GDM) poses a growing public health challenge worldwide due to its increasing prevalence, associated pregnancy complications, and long-term metabolic risks for both mothers and offspring. Genetic factors are known to contribute to GDM susceptibility, yet little is known about their relevance in ethnic Kazakh population. The primary objective of this study was to evaluate associations between selected candidate SNPs involved in β-cell function and the risk of GDM in a Kazakh cohort. Secondary objectives included the assessment of potential gene–gene interactions. Methods: We conducted a case–control study among 365 pregnant Kazakh women. Of these, 217 were diagnosed with GDM, and 148 had normal glucose tolerance. Clinical and genealogical data were collected. Eight candidate SNPs that were previously associated with GDM or glucose metabolism were genotyped. Logistic regression was used to assess associations between SNPs and GDM risk. Gene–gene interactions were evaluated using multifactor dimensionality reduction (MDR). Results: In univariate analysis, MTNR1B rs10830963 demonstrated a statistically significant association under the additive model (OR 0.61, 95% CI 0.42–0.89), indicating a potential protective effect of the C allele. However, this association was not statistically significant after multivariable adjustment (adjusted OR 0.58, 95% CI 0.32–1.03) and correction for multiple testing. In the adjusted analysis, TCF7L2 rs7903146 showed a significant association under the dominant model (adjusted OR 2.29, 95% CI 1.01–5.46); however, this finding did not remain significant following FDR correction. MDR analysis showed that the best two-locus model included IGF2BP2 rs4402960 and CDKAL1 rs7754840 (CVC = 6/10; testing accuracy = 0.558; permutation p < 0.001). The most stable interaction was observed for the three-locus model comprising IGF2BP2 rs4402960, MTNR1B rs10830963, and PPARG rs1801282 (CVC = 9/10; testing accuracy = 0.576; permutation p < 0.001). Conclusions: The findings suggest that common variants in IGF2BP2, CDKAL1, MTNR1B, TCF7L2, PPARG, and GCK do not exert strong individual effects on GDM susceptibility in this cohort of ethnic Kazakh women. Instead, the results are more consistent with a modest polygenic architecture characterized by small effect sizes and possible weak gene–gene interactions. MDR analysis identified statistically significant interaction models; however, their limited predictive accuracy indicates that these findings should be interpreted as exploratory.