| Summary: | IntroductionGestational diabetes (GDM) is one of the common complications of female pregnancy, which seriously affects the health of mothers and their offspring. So far, the etiology has not been fully clarified.MethodsA case-control study was conducted to clarify the relationship between Erb-b2 receptor tyrosine kinase 4 (ERBB4) functional tag genetic variants (rs1595064, rs1595065, rs1595066 and rs6719645) and the risk of GDM. Associations between variants and GDM risk were evaluated with the odds ratios (ORs) and their corresponding 95% confidence intervals (CIs). Subsequently, the false-positive reporting probability (FPRP), multi-factor dimension reduction (MDR) and bioinformatics analysis were adopted to confirm the significant associations. A nomogram model was constructed to predict the risk of GDM.ResultsAssociation analysis demonstrated that rs1595066 TT genotype performed a protective effect on GDM risk among all subjects (TT vs. CC: adjusted OR = 0.60, 95% CI = 0.38 - 0.94, P = 0.026; TT vs. CC/CT: adjusted OR = 0.61, 95% CI = 0.40 - 0.95, P = 0.027). Meanwhile, stratified analysis showed that rs1595066 TT can also reduce the GDM risk in age > 30.09 years old, pre-pregnancy BMI > 22.23 Kg/m2, SBP ≤ 110.08 mmHg, etc subgroups. Interactions between rs1595066 and DBP (Pinteraction = 0.01), FPG (Pinteraction < 0.001) and HbA1c (Pinteraction < 0.001) were detected. The FPRP analysis confirmed that association between rs1595066 and GDM risk in subjects of FPG < 4.79 mmol/L (P = 0.199) is true. The MDR analysis showed that rs1595066 was the best single locus model while the 4-loci model was the best multiple factors model to predict GDM risk. Functional prediction revealed that rs1595066 may disturb the stability of miRNA-mRNA binding. The predictive nomogram model has a well consistence and acceptable discriminative ability with a diagnosed AUC of 0.813.DiscussionERBB4 variants can change an individual’s susceptibility to GDM via the interaction of gene-gene, gene-environment and changes in the regulatory effects of miRNAs on ERBB4 expression.
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