DOI: 10.5061/dryad.rv15dv4j7
title: Data from: Association and function analysis of genetic variants and the risk of gestational diabetes mellitus in a southern Chinese population

description: This dataset include 538 gestational diabetes mellitus (GDM) patients and
 626 healthy pregnancies’ baseline information obtained from unique
 questionnaires and medical records, and the genetic loci were genotyped by
 the Sequenom MassARRAY platform. The clinical indicators and genetic
 variants that are statistically associated with GDM were used to construct
 a nomogram model. The nomogram model is formulated as a standard of
 scoring based on the regression coefficient (β) of indicators. Each level
 of the indicators will be given a specific score and the scores of each
 factor are added up to get the total point, which can be used to predict
 the probability of GDM occurrence.  Subjects’ baseline data
 involve systolic blood pressure (SBP, mmHg), diastolic blood pressure
 (DBP, mmHg), fasting plasma glucose (FPG, mmol/L), oral glucose tolerance
 test 1h plasma glucose (1hPG, mmol/L), oral glucose tolerance test 2h
 plasma glucose (2hPG, mmol/L), glycated hemoglobin (HbA1c, %),
 triglyceride (TG, mmol/L), total cholesterol (TC, mmol/L), high-density
 lipoprotein cholesterol (HDL-c, mmol/L), low-density lipoprotein
 cholesterol (LDL-c, mmol/L). The data of genetic polymorphism include
 rs4134819 C&gt;T, rs720918 A&gt;G, rs2034410 T&gt;C,
 rs11109509 A&gt;G, and rs12524768 G&gt;A and their corresponding
 dominant and recessive genetic model.
description: # Data from: Association and function analysis of genetic variants and the
 risk of Gestational Diabetes Mellitus in a southern Chinese population ##
 Descriptions The meaning of the different assignments in the dataset: *
 Group: 1=GDM; 0=Control group * Sample ID: Identification number of the
 test sample * Variants and genotypes assignment 1\)rs4134819 C&gt;T: 1=CC
 genotype; 2=CT genotype;3=TT genotype 2\)rs720918 A&gt;G: 1=AA genotype;
 2=AG genotype;3=GG genotype 3\)rs2034410 T&gt;C: 1=TT genotype; 2=TC
 genotype;3=CC genotype 4\) rs11109509 A&gt;G: 1=AA genotype; 2=AG
 genotype;3=GG genotype 5\) rs12524768 G&gt;A : 1=GG genotype; 2=GA
 genotype;3=AA genotype 6\)rs4134819 Dominant model(CT/TT vs.CC): 1=CC
 genotype; 4=CT/TT genotypes 7\) rs720918 Dominant model(AG/GG vs. AA):
 1=AA genotype; 4=AG/GG genotypes 8\) rs2034410 Dominant model(TC /CC
 vs.TT): 1=TT genotype; 4=TC /CC genotypes 9\) rs11109509 Dominant
 model(AG/GG vs. AA): 1=AA genotype; 4=AG/GG genotypes 10\) rs12524768
 Dominant model(GA/AA vs. GG): 1=GG genotype; 4=GA/AA genotypes 11\)
 rs4134819 Recessive model(TT vs. CC/CT): 3=TT genotype; 5=CC/CT genotypes
 12\) rs720918 Recessive model (GG vs. AA/AG): 3=GG genotype; 5=AA/AG
 genotypes 13\) rs2034410 Recessive model(CC vs. TT/TC): 3=CC genotype;
 5=TT/TC genotypes 14\) rs11109509 Recessive model (GG vs. AA/AG): 3=GG
 genotype; 5=AA/AG genotypes 15\) rs12524768 Recessive model(AA vs. GG/GA):
 3=AA genotype; 5=GG/GA genotypes * Variables for stratification analysis
 1\) SBP_M (Mean SBP value:110.03 mmHg,1="≤110.03 mmHg"；2=
 “＞110.03mmHg” ); 2\) DBP_M (Mean DBP value:69.44 mmHg,1="≤69.44
 mmHg"；2= “＞69.44 mmHg ); 3\) FPG_M (Mean FPG value:4.78
 mmol/L,1="≤4.78 mmol/L"；2= “＞4.78 mmol/L ); 4\) 1hPG_M (Mean
 1hPG value:8.24 mmol/L,1="≤8.24 mmol/L"；2= “＞8.24 mmol/L”);
 5\)2hPG_M (Mean 2hPG value:7.10 mmol/L,1="≤7.10 mmol/L"；2=
 “＞7.10 mmol/L” ); 6\)HbA1c_M (Mean HbA1c(%)
 value:5.20%,1="≤5.20%"；2= “＞5.20%”); 7\)TG_M (Mean TG value:2.53
 mmol/L,1="≤2.53 mmol/L"；2= “＞2.53 mmol/L”); * NA: missing value