Association and function analysis of genetic variants and the risk of gestational diabetes mellitus in a southern Chinese population

Front Endocrinol (Lausanne). 2024 Dec 24:15:1476222. doi: 10.3389/fendo.2024.1476222. eCollection 2024.

Abstract

Background: Gestational diabetes mellitus (GDM) is a complex metabolic disease that has short-term and long-term adverse effects on mothers and infants. However, the specific pathogenic mechanism has not been elucidated.

Objective: The aim of this study was to confirm the associations between candidate genetic variants (rs4134819, rs720918, rs2034410, rs11109509, and rs12524768) and GDM risk and prediction in a southern Chinese population.

Methods: Candidate variants were genotyped in 538 GDM cases and 626 healthy controls. The odds ratio (OR) and its corresponding 95% confidence interval (CI) were calculated to assess the associations between genotypes and GDM risk. Then, the false-positive report probability (FPRP) analysis was adopted to confirm the significant associations, and bioinformatics tools were used to explore the potential biological function of studied variants. Finally, risk factors of genetic variants and clinical indicators identified by logistics regression were used to construct a nomogram model for GDM prediction.

Results: It was shown that the XAB2 gene rs4134819 was significantly associated with GDM susceptibility (CT vs. CC: adjusted OR = 1.38, 95% CI: 1.01-1.87, p = 0.044; CT/TT vs. CC: crude OR = 1.42, 95% CI: 1.08-1.86, p = 0.013). Functional analysis suggested that rs4134819 can alter the specific transcription factors (CPE bind and GATE-1) binding to the promoter of the XAB2 gene, regulating the transcription of XAB2. The nomogram established with factors such as age, FPG, HbA1c, 1hPG, 2hPG, TG, and rs4134819 showed a good discriminated and calibrated ability with an area under the curve (AUC) = 0.931 and a Hosmer-Lemeshow test p-value > 0.05.

Conclusion: The variant rs4134819 can significantly alter the susceptibility of the Chinese population to GDM possibly by regulating the transcription of functional genes. The nomogram prediction model constructed with genetic variants and clinical factors can help distinguish high-risk GDM individuals.

Keywords: association; genetic variants; gestational diabetes mellitus; nomogram model; prediction.

MeSH terms

  • Adult
  • Asian People* / genetics
  • Case-Control Studies
  • China / epidemiology
  • Diabetes, Gestational* / epidemiology
  • Diabetes, Gestational* / genetics
  • East Asian People
  • Female
  • Genetic Predisposition to Disease*
  • Genotype
  • Humans
  • Nomograms
  • Polymorphism, Single Nucleotide*
  • Pregnancy
  • Risk Factors

Associated data

  • Dryad/10.5061/dryad.rv15dv4j7

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was supported by the Guangxi Natural Science Foundation(2024JJH140351), the Guangxi Science and Technology Base and Talent Special Project (AD24010027), Guilin Science Research and Technology Development Plan Project (20230135-2-1), self-funded research project of the Health Committee of Guangxi (Z-C20241580) and the Fujian Provincial Health Technology Project (2020CXA017).