Gestational diabetes mellitus (GDM) poses a significant global health concern, impacting both maternal and fetal well-being. Early detection and treatment are imperative to mitigate adverse outcomes during pregnancy. This review delves into the pivotal role of insulin function and the influence of genetic variants, including SLC30A8, CDKAL1, TCF7L2, IRS1, and GCK, in GDM development. These genetic variations affect beta-cell function and insulin activity in crucial tissues, such as muscle, disrupting glucose regulation during pregnancy. We propose a hypothesis that this variation may disrupt zinc transport, consequently impairing insulin production and secretion, thereby contributing to GDM onset. Furthermore, we discussed the involvement of inflammatory pathways, such as TNF-alpha and IL-6, in predisposing individuals to GDM. Genetic modulation of these pathways may exacerbate glucose metabolism dysregulation observed in GDM patients. We also discussed how GDM affects cardiovascular disease (CVD) through a direct correlation between pregnancy and cardiometabolic function, increasing atherosclerosis, decreased vascular function, dyslipidemia, and hypertension in women with GDM history. However, further research is imperative to unravel the intricate interplay between inflammatory pathways, genetics, and GDM. This understanding is pivotal for devising targeted gene therapies and pharmacological interventions to rectify genetic variations in SLC30A8, CDKAL1, TCF7L2, IRS1, GCK, and other pertinent genes. Ultimately, this review offers insights into the pathophysiological mechanisms of GDM, providing a foundation for developing strategies to mitigate its impact.

Background: The solute carrier family 30 A8 zinc transporter (SLC30A8) plays a crucial role in insulin secretion. This study aimed to investigate the impact of SLC30A8 gene polymorphisms on gestational diabetes mellitus (GDM).Methods: The research objective was to select 500 patients with GDM and 502 control subjects. Rs13266634 and rs2466293 were genotyped using the SNPscan™ genotyping assay. Statistical tests, such as the chi-square test, t-test, logistic regression, ANOVA, and meta-analysis, were conducted to determine the differences in genotypes, alleles, and their associations with GDM risk.Results: Statistically significant differences were observed in age, pregestational BMI, SBP, DBP, and parity between individuals with GDM and healthy subjects (P < 0.05). After adjusting for these factors, rs2466293 remained significantly associated with an increased risk of GDM in overall subjects (GG+AG vs. AA: OR = 1.310; 95% CI: 1.005-1.707; P = 0.046, GG vs. AA: OR = 1.523; 95% CI: 1.010-2.298; P = 0.045 and G vs. A: OR = 1.249; 95% CI: 1.029-1.516; P = 0.024). Rs13266634 was still found to be significantly associated with a decreased risk of GDM in individuals aged ≥ 30 years (TT vs. CT+CC: OR = 0.615; 95% CI: 0.392-0.966; P = 0.035, TT vs. CC: OR = 0.503; 95% CI: 0.294-0.861; P = 0.012 and T vs. C: OR =0.723; 95% CI: 0.557-0.937; P = 0.014). Additionally, the haplotype CG was found to be associated with a higher risk of GDM (P < 0.05). Furthermore, pregnant women with the CC or CT genotype of rs13266634 exhibited significantly higher mean blood glucose levels than those with the TT genotype (P < 0.05). Our findings were further validated by the results of a meta-analysis.Conclusion: The SLC30A8 rs2466293 polymorphism was found to be associated with an increased risk of GDM, while rs13266634 was associated with a decreased risk of GDM in individuals aged ≥ 30 years. These findings provide a theoretical basis for GDM testing.

Background:CDK5 regulatory subunit associated protein 1 like 1 (CDKAL1) is a major pathogenesis-related protein for type 2 diabetes mellitus (T2DM). Recently, some studies have investigated the association of CDKAL1 susceptibility variants, including rs4712523, rs4712524, and rs9460546 with T2DM. However, the results were inconsistent. This study aimed to evaluate the association of CDKAL1 variants and T2DM patients.Methods: A comprehensive meta-analysis was performed to assess the association between CDKAL1 SNPs and T2DM among dominant, recessive, additive, and allele models.Results: We investigated these three CDKAL1 variants to identify T2DM risk. Our findings were as follows: rs4712523 was associated with an increased risk of T2DM for the allele model (G vs A: OR = 1.172; 95% CI: 1.103–1.244; p < 0.001) and dominant model (GG + AG vs AA: OR = 1.464; 95% CI: 1.073–1.996; p = 0.016); rs4712524 was significantly associated with an increased risk of T2DM for the allele model (G vs A: OR = 1.146; 95% CI: 1.056–1.245; p = 0.001), additive model (GG vs AA: OR = 1.455; 95% CI: 1.265–1.673; p < 0.001) recessive model (GG vs AA + AG: OR = 1.343; 95% CI: 1.187–1.518; p < 0.001) and dominant model (GG + AG vs AA: OR = 1.221; 95% CI: 1.155–1.292; p < 0.001); and rs9460546 was associated with an increased risk of T2DM for the allele model (G vs T: OR = 1.215; 95% CI: 1.167–1.264; p = 0.023). The same results were found in the East Asian subgroup for the allele model.Conclusions: Our findings suggest that CDKAL1 polymorphisms (rs4712523, rs4712524, and rs9460546) are significantly associated with T2DM.

Gestational diabetes mellitus (GDM) has seen a significant rise and has become a growing concern worldwide, especially in Asian populations. Genetic factors, such as variations in the CDKAL1 gene, have been linked to its development. However, existing research on this connection is limited and inconclusive, highlighting the need for further investigation. This study aims to explore the association between CDKAL1 gene polymorphisms and GDM risk in a Chinese population using a comprehensive case-control study and meta-analysis. The SNPscan™ genotyping assay was used to genotype rs7754840 and rs7756992, in 502 control participants and 500 GDM patients. ANOVA, T-test, chi-square test, logistic regression, and other statistical tests were used to determine the differences in genotypes and alleles and their associations to the risk of GDM. Additionally, a meta-analysis of existing studies on CDKAL1 polymorphisms and GDM was performed to provide a broader context and resolve inconsistencies in the literature. The GDM group had a significantly older average mean age and higher blood pressure, and fasting plasma glucose levels than the control group (P < 0.05). CDKAL1 rs7754840 showed significant associations under codominant homozygous model (CC vs. GG: OR = 1.748; 95% CI: 1.178–2.593; P = 0.006). After adjusting, these results indicated an association between CDKAL1 rs7754840 and increased risk of GDM in the codominant model (OR = 1.715; 95% CI: 1.133–2.595; P = 0.011). However, further analysis revealed no significant associations under all genetic models for CDKAL1 rs7756992. The study found that individuals under 30 with the rs7754840 CC genotype had higher fasting glucose and postprandial glucose levels (P < 0.05) compared to those with the GG genotype. Figure 3 A demonstrated a modest association between the CDKAL1 and GDM susceptibility (OR 1.16, 95% CI 1.104–1.29, P = 0.0258). Individuals with the CDKAL1 rs7754840 polymorphism was associated to an increased risk of GDM, whereas rs7756992 did not show significant association with GDM risk. These results provide a theoretical foundation for GDM testing to mitigate its associated complications by enhancing our ability to predict, prevent and manage GDM. Ultimately improving outcomes for both mothers and their children. This research contributes to the growing evidence of genetic predisposition to GDM and highlights the importance of CDKAL1 as a potential genetic marker for GDM risk assessment.

Background: Insulin-like growth factor-1 (IGF-1) has been demonstrated to increase fatty acid β oxidation during fasting, and play an important role in regulating lipid metabolism and type 2 diabetes mellitus (T2DM). The rs35767 (T > C) polymorphism, a functional SNP was found in IGF-1 promoter, which may directly affect IGF-1 expression. However, the inconsistent findings showed on the IGF-1 rs35767 polymorphism and T2DM risk.Methods: We performed a comprehensive meta-analysis to estimate the association between the IGF-1 rs35767 and T2DM risk among four genetic models (the allele, additive, recessive and dominant models).Results: A total 49,587 T2DM cases and 97,906 NDM controls were included in the allele model, a total 2256 T2DM cases and 2228 NDM controls were included in the other three genetic models (the additive; recessive and dominant models). In overall analysis, the IGF-1 rs35767 was shown to be significantly associated with increased T2DM risk for the allele model (T vs. C: OR = 1.251, 95% CI: 1.082–1.447, p = 0.002), additive model (homozygote comparisons: TT vs. CC: OR = 2.433, 95% CI: 1.095–5.405, p = 0.029; heterozygote comparisons: TC vs. CC: OR = 1.623, 95% CI: 1.055–2.495, p = 0.027) and dominant model (TT + CT vs. CC: OR = 1.934, 95% CI: 1.148–3.257, p = 0.013) with random effects model. After omitting Gouda’s study could reduce the heterogeneity, especially in the recessive model (TT vs. CC + CT: I² = 38.7%, p = 0.163), the fixed effects model for recessive effect of the T allele (TT vs. CC + CT) produce results that were of borderline statistical significance (OR = 1.206, 95% CI: 1.004–1.448, p = 0.045). And increasing the risk of T2DM in Uyghur population of subgroup for the allele model.Conclusion: The initial analyses that included all studies showed statistically significant associations between the rs35767 SNP and type 2 diabetes, but after removing the Gouda et al. study produced results that were mostly not statistically significant. Therefore, there is not enough evidence from the results of the meta-analysis to indicate that the rs35767 SNP has a statistically significant association with type 2 diabetes.