Association of solute carrier family 30 A8 zinc transporter gene variations with gestational diabetes mellitus risk in a Chinese population

Abstract

BackgroundThe 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).MethodsThe 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.ResultsStatistically 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.ConclusionThe 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.

Genetic and inflammatory factors underlying gestational diabetes mellitus: a review

“…Incorporating genetic markers into risk prediction models holds excellent potential for early detection and treatment of GDM cases. By integrating genetic data with conventional risk factors like maternal age, body mass index, and family history of diabetes ( 41 ), clinicians can enhance the accuracy of risk assessment. This approach enables the implementation of targeted interventions, such as dietary modifications and careful monitoring, to mitigate the risks associated with GDM.…”

“…The SLC30A8 gene on chromosome 8q24.11 has garnered significant attention in the study of type 2 diabetes (T2D). Recent research has highlighted its relevance to GDM, as certain variations in the SLC30A8 gene may impact a mother’s ability to metabolize glucose during pregnancy ( 41 ). The placenta, a vital organ for fetal development, undergoes dynamic changes in gene expression throughout pregnancy.…”

“…Therefore, pregnant women with genetic variations in the IRS1 gene may struggle to maintain optimal sugar levels during pregnancy, heightening their risk of GDM ( 80 ). Alongside IRS1, the SLC30A8 gene also significantly influences GDM development through its role in zinc homeostasis regulation and insulin and beta cell function ( 41 ). Variations in both SLC30A8 and IRS1 genes can impair zinc transportation and subsequent insulin secretion in beta cells, increasing GDM risk.…”

“…SNPs are nucleotide variations occurring at single positions in the DNA sequence ( 91 ). Thanks to current genotyping technologies such as SNPscan™, TaqMan SNP genotyping, nucleic-acid-modifying enzymes, and PCR, we can now identify disease-related SNPs ( 41 , 52 , 92 ), including those linked to metabolic disorders such as obesity, TDM2 (Type 2 Diabetes Mellitus), cardiovascular disease, and GDM ( 93 , 94 ). These SNPs may be associated with a higher or lower risk of developing GDM in different populations worldwide ( 49 , 95 – 99 ).…”

Genetic Variants Affecting Insulin Signaling Pathways and Risk of Diabetes: A Comprehensive Systematic Review

“…It also works synergistically with Insulin secretin cells-1 or INS cells that in turn affect with the development of progression of diabetes mellitus type2 or insulin independent diabetes. It is also known as ZNT8 or ZnT-8 showing the role of zinc in this genetic expression [30].…”