AUTHOR=Nie Lijie , Sun Yan , Li Ruiqi , Liang Qiulian , Deng Guocun , He Xinyu , Zeng Yifei , Zheng Hui , Xiao Xinhe , Ding Xiaodong , Huang Jian , Yu Xiangyuan 

TITLE=Genetic variants in HLA-DQA1/DQB1 genes modulate the risk of gestational diabetes mellitus in a southern Chinese population

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2025.1511561

DOI=10.3389/fendo.2025.1511561

ISSN=1664-2392

ABSTRACT=BackgroundGestational diabetes mellitus (GDM) is an endocrine disorder that occurs easily in women during pregnancy. HLA-DQA1/DQB1 genes play a crucial role in the regulation of the human immune and endocrine systems, potentially influencing the pathogenesis of GDM.ObjectiveTo explore the associations between single nucleotide polymorphisms (SNPs) in HLA-DQA1/DQB1 genes and the risk of GDM.MethodsSeven functional SNPs of HLA-DQA1/DQB1 genes were selected and genotyped in 523 GDM patients and 638 normal pregnant women. The odds ratio (OR) and its corresponding 95% confidence interval (CI) were utilized to assess the association between candidate SNPs and the risk of GDM. And then, false positive report probability (FPRP), multifactor dimensionality reduction (MDR) and haplotype analysis were employed to validate the statistically significant associations between studied SNPs and GDM risk.ResultsCompared to those with 0–1 risk genotypes, individuals with 2–7 unfavorable genotypes presented an increased risk of GDM (adjusted OR = 1.54, 95% CI=1.04-2.28, P=0.033). A dose- accumulation effect was detected between the number of unfavorable genotypes and GDM risk (Ptrend=0.024). Furthermore, stratified analysis revealed that the increased GDM risk was more likely to occur in individuals with higher blood pressure and TG, and lower HDL-c levels (P<0.05). Multifactor dimensionality reduction (MDR) analysis revealed that rs9274666 was the best single locus model, whereas the 7-loci model was the best multifactor interaction model for predicting GDM risk (χ²=134.28, P<0.0001). Finally, haplotype analysis revealed that the ACGAGTA and ACGGATA haplotypes were significantly associated with the increased GDM risk. HLA-DQA1/DQB1 SNPs can significantly alter individuals’ genetic susceptibility to GDM.ConclusionsThe genetic variations in the HLA-DQA1 and HLA-DQB1 genes may collectively contribute to the susceptibility to gestational diabetes mellitus. These findings suggest that these genetic markers could be useful for early prediction of GDM, and further validation in larger cohorts is warranted.