Raw data for the association of genetic variants of ErbB4 gene and gestational diabetes mellitus
Data files
Oct 30, 2023 version files 112.61 KB
Abstract
Gestational diabetes (GDM) is one of the common complications of female pregnancy, which seriously affects the health of patients and their offspring. So far, the etiology has not yet been fully clarified. To clarify the relationship of Erb-b2 receptor tyrosine kinase 4 (ErbB4) genetic variants and GDM risk in a Chinese population, ErbB4 variants (rs1595064, rs1595065, rs1595066 and rs6719645) were selected and genotyped in 554 GDM cases and 641 healthy controls. The associations between variants and GDM risk were evaluated with the odds ratios (ORs) and their corresponding 95% confidence intervals (CIs). 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. Association analysis demonstrated that the rs1595066 genotype performed a protective effect on GDM risk among whole subjects. Meanwhile, stratified analysis showed that rs1595066 was significantly associated with GDM risk in various subgroups, such as age>30.09 years old, pre-pregnancy BMI>22.23 Kg/m2 ,SBP≤110.08 mmHg, etc. Further, 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 of rs1595066 and GDM risk in subjects of FPG≤4.79 mmol/L (P=0.199) is true at a prior probability of 0.1. The MDR analysis suggested that rs1595066 was the best single locus model, while the 4-loci model was considered the best multiple factors model to predict GDM risk. Functional prediction revealed that rs1595066 may disturb the microRNA binding sites to influence the stability of miRNA-mRNA binding. The predictive nomogram model has a good consistency and acceptable discriminative ability with a diagnosed AUC of 0.813.ErbB4 rs1595066 was significantly associated with GDM risk and underlying mechanism causing GDM may be the interaction of gene-gene, gene-environment and the changes in the regulatory effects of miRNAs on ERBB4 expression. The nomogram model has a good prospect for GDM prediction.
1. Sample ID: Identification number of test sample
2. Group: 1=GDM; 0=Control group
3. Age: Age in years of participants
4. Pre-BMI: Prepregnancy body mass index
5. Variants and genotypes assignment
- rs1595064 G > C: 1=GG genotype; 2=GC genotype;3=CC genotype
- rs1595065 A > G: 1=AA genotype; 2=AG genotype;3=GG genotype
- rs1595066 C > T: 1=CC genotype; 2=CT genotype;3=TT genotype
- rs6719645 C > T: 1=CC genotype; 2=CT genotype;3=TT genotype
- rs1595066 Dominant model(CT/TT vs. CC): 1=CC genotype;4=CT/TT genotypes
- rs1595066 Recessive model(TT vs.CC/CT): 5=CC/CT genotype;3=TT genotype;
6. Variables for stratification analysis
- Age_M (Mean age:30.09 years, 1="≤30.09"；2= “＞30.09”);
- Pre-BMI_M (Mean pre-BMI:22.23 kg/m2,1="≤22.23"；2= “＞22.23” );
- SBP_M (Mean SBP:110.08 mmHg,1="≤110.08"；2= “＞110.08” );
- DBP_M (Mean DBP:69.53 mmHg,1="≤69.53"；2= “＞69.53” );
- FPG_M (Mean FPG:4.79 mmol/L,1="≤4.79"；2= “＞4.79” );
- 1hPG_M (Mean OGTT 1h:8.26 mmol/L,1="≤8.26"；2= “＞8.26”);
- 2hPG_M (Mean OGTT 2h:7.11 mmol/L,1="≤7.11"；2= “＞7.11” );
- HbA1c_M (Mean HbA1c(%):5.20 mmol/L,1="≤5.20"；2= “＞5.20” );
- TG_M (Mean TG:2.54 mmol/L,1="≤2.54"；2= “＞2.54”);
7. Abbreviations：
- GDM: gestational diabetes mellitus;
- Pre-BMI(Kg/m2): Prepregnancy body mass index;
- FPG(mmol/L): fasting plasma glucose;
- 1hPG(mmol/L): oral glucose tolerance test 1h plasma glucose
- 2hPG(mmol/L): oral glucose tolerance test 2h plasma glucose
- HbA1c(%): glycated hemoglobin
- SBP(mmHg): Systolic blood pressure;
- DBP(mmHg): Diastolic blood pressure;
- TG(mmol/L): triglyceride;
- TC(mmol/L): total cholesterol;
- HDL-c(mmol/L): high-density lipoprotein cholesterol;
- LDL-c(mmol/L): low-density lipoprotein cholesterol.
8. NA: missing value
- Li, Ruiqi et al. (2023), Genetic variants of ERBB4 gene and risk of gestational diabetes mellitus: a susceptibility and diagnostic nomogram study, Frontiers in Endocrinology, Journal-article, https://doi.org/10.3389/fendo.2023.1283539
- Yu, Xiang-Yuan; Liang, Qiulian; Wang, Yukun; Li, Ruiqi (2023), Raw data for the association of genetic variants of ErbB4 gene and gestational diabetes mellitus, , Dataset, https://doi.org/10.5061/dryad.qz612jmnr