Genetic Susceptibility, Mendelian randomization and Nomogram Model Construction of Gestational Diabetes Mellitus.

CONTEXT: Gestational diabetes mellitus (GDM) is a pregnancy complicated disease that poses a risk to maternal and infant health. However, the etiology of the disease has been not yet elucidated. OBJECTIVE: To detect the genetic susceptibility and construct a nomogram model with significantly associated polymorphisms and key clinical indicators for early prediction of gestational diabetes mellitus (GDM). METHODS: 11 functional single nucleotide polymorphisms (SNPs) screened by genome-wide association study (GWAS) were genotyped in 554 GDM cases and 641 healthy controls. Functional analysis of GDM positively associated SNPs, Multivariate mendelian randomization (MVMR) and a GDM early predictive nomogram model construction were performed. RESULT: rs1965211, rs3760675 and rs7814359 were significantly associated with genetic susceptibility to GDM after adjusting age and pre-pregnancy BMI (pre-BMI). It seems that GDM associated SNPs have effects on regulating target gene transcription factor binding, post transcriptional splicing, and translation product structure. Besides, rs3760675 can be expression quantitative trait locis (eQTLs) and increase the XAB2 mRNA expression level (P = 0.047). The MVMR analysis showed that the increase of clinical variables of BMI, HbA1c and FPG had significant causal effects on GDM (BMI-ORMVMR = 1.52, HbA1c-ORMVMR = 1.32, FPG-ORMVMR = 1.78), P <0.05. A nomogram model constructed with pre-BMI, FPG, HbA1c, and genotypes of rs1965211, rs3760675 and rs7814359 showed an area under the ROC curve of 0.824. CONCLUSION: Functional polymorphisms can change women's susceptibility to GDM and the predictive nomogram model based on genetic and environmental factors can effectively distinguish individuals with different GDM risks in early stages of pregnancy.

Genetic variants of ERBB4 gene and risk of gestational diabetes mellitus: a susceptibility and diagnostic nomogram study.

Introduction: Gestational 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. Methods: A 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. Results: Association 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 (P interaction = 0.01), FPG (P interaction < 0.001) and HbA1c (P interaction < 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. Discussion: ERBB4 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.

Systematically Evaluate The Effect Of Problem-Based Learning Method In The Teaching Of Epidemiology And Health Statistics In China.

OBJECTIVE: To systematically evaluate the application of problem-based learning teaching in medical institutions. Methods: The systematic review was conducted in China following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, and comprised search for relevant studies on July 31, 2020, of the China National Knowledge Infrastructure, Wanfang, China Biology Medicine disc, Web of Science, National Center for Biotechnology Information, Excerpta Medica Database and PubMed databases. Quality of the included studies was assessed as adequate, uncertain or inadequate based on the Cochrane Handbook for Systematic Reviews of Interventions. The teaching effects was evaluated using relative risk or standardised mean difference along with their corresponding 95% confidence intervals. RESULTS: There were 3,447 students the 20 studies analysed; 1,681(48.8%) in problem 24 based learning group A and 1,766(51.2%) in lecture-based learning group B. Group A showed improved students' test scores, learning interest, self-learning ability and collaboration skills (p<0.05). Conclusion: Problem-based learning teaching method showed advantages in terms of improvement in students' professional knowledge and key learning skills.

Systematic evaluation of the association between a missense variant in XRCC3 gene splicing site and the pathogenesis of ovarian cancer.

The effects and underlying mechanism of XRCC3 rs861539 on the risk of ovarian cancer (OC) are still unclear. Therefore, a meta-analysis of 10 studies containing 6,375 OC cases and 10,204 controls was performed for this topic. Compared with GG genotype, GA + AA genotypes could significantly decrease the OC risk, odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) were 0.89 (0.83-0.95) and P=0.001, and 0.88 (0.82-0.95) and P=0.001 under the dominant and heterozygous genetic models. Compared with G allele, rs861539 A could significantly reduce the OC risk, OR and its corresponding 95% CI was 0.94 (0.89-0.98) and P=0.007. By subgroup analysis in ethnicity, protective effects on OC risk in Caucasians were observed (the dominant model: OR = 0.88, 95% CI = 0.82-0.94, P<0.001; the heterozygous model: OR = 0.87, 95% CI = 0.81-0.94, P<0.001; the allelic model: OR = 0.93, 95% CI = 0.88-0.97, P=0.003; the homozygous model: OR = 0.89, 95% CI = 0.80-0.98, P=0.024). The authenticity of positive association findings was further confirmed by trial sequential analysis (TSA) and false-positive report probability (FPRP) analysis. The subsequent functional analysis revealed that rs861539 could regulate the post-transcriptional expression of XRCC3 by changing the activity of putative splice sites and types of splicing factors. rs861539 also may act as an expression Quantitative Trait Loci (eQTL) affecting the expression of genes such as XRCC3, MARK3, APOPT1, etc., and has an impact on the structure of XRCC3.

Association of ACE2 gene functional variants with gestational diabetes mellitus risk in a southern Chinese population.

Objective: To explore the relationship between angiotensin-converting enzyme 2 (ACE2) genetic variants and gestational diabetes mellitus (GDM) in a southern Chinese population. Methods: Potential functional variants (rs2106809, rs6632677, and rs2074192) of ACE2 were selected and genotyped in 566 GDM patients and 710 normal pregnaõncies in Guilin, China. The odds ratio (OR) and its corresponding 95% confidence interval (CI) were used to evaluate the association between genetic variant and GDM risk, and then the false positive report probability, multifactor dimensional reduction (MDR), and bioinformatics tools were used to confirm the significant association in the study. Results: After adjusting for age and prepregnancy body mass index, logistic regression analysis showed that ACE2 rs6632677 was significantly associated with a decreased risk of GDM (CC vs. GG: adjusted OR = 0.09, 95% CI: 0.01 - 0.71, P = .023; GC/CC vs. GG: adjusted OR = 0.68, 95% CI = 0.46 - 0.99, P = .048; and CC vs. GG/GC: adjusted OR = 0.09, 95% CI = 0.01 - 0.72, P = .024), whereas rs2074192 was associated with increased GDM risk (TT vs. CC/CT: adjusted OR = 1.38, 95% CI = 1.08 - 1.75, P = .009). Furthermore, we found that rs6632677 interacted with SBP (P interaction = .043) and FPG (P interaction = .021) and rs2074192 interacted with HDL-c (P interaction = .029) and LDL-c (P interaction = .035) to influence the GDM risk of the individual. In the MDR analysis, the rs6632677 was the best one-locus model, and the three-loci model was the best interaction model to predict GDM risk. In addition, functional analysis confirmed that rs2074192 may regulate the splicing process of ACE2 gene. Conclusion: ACE2 gene variants are significantly associated with the risk of GDM via gene-gene and gene-environment combinations. The rs2074192 C > T affects the splicing of the ACE2 gene, which may be a potential mechanism leading to the changed susceptibility of an individual female during pregnancy to GDM.

Association and functional analysis of angiotensin-converting enzyme 2 genetic variants with the pathogenesis of pre-eclampsia.

Objective: The aim of this study was to investigate the relationship between potential functional single-nucleotide polymorphisms (SNPs) of the angiotensin-converting enzyme 2 (ACE2) gene and the pathogenesis of pre-eclampsia (PE) in Guangxi, China. Materials and methods: A case-control study was conducted involving 327 PE cases and 591 age-matched, normal, singleton pregnant women. Potential functional ACE2 gene variants (rs2106809 A>G, rs6632677 G>C, and rs2074192 C>T) were selected and genotyped using kompetitive allele-specific PCR. The strength of the associations between the studied genetic variants and the risk of PE were evaluated using odds ratios (ORs) and corresponding 95% confidence intervals (CIs). Result: After adjusting for age and body mass index (BMI), unconditional logistic regression analysis showed that rs2106809 A>G was significantly associated with PE risk (AG vs. AA, OR = 1.43, 95% CI = 1.03-1.99, p = 0.034; AG/GG vs. AA, OR = 1.45, 95% CI = 1.06-1.99, p = 0.019), especially with severe PE (AG vs. AA, adjusted OR = 1.70, 95% CI = 1.10-2.61; AG/GG vs. AA, adjusted OR = 1.71, 95% CI = 1.14-2.57). Further stratified analysis showed that rs2106809 was even more pronounced in subjects in the pre-pregnancy BMI (pre-BMI) >23 kg/m2 (adjusted OR = 2.14, 95% CI = 1.32-3.45) and triglyceride (TG) >2.84 mmol/L subgroups (adjusted OR = 1.81, 95% CI = 1.09-3.01) under the dominant genetic model. We also found that rs2106809 interacted with pre-BMI (p interaction = 0.040), thereby affecting an individual's genetic susceptibility to PE. Multiple dimension reduction analysis demonstrated that rs2106809 made the best one-locus model, and the three-locus model was the best interaction model for predicting PE risk. Functional analysis suggested that rs2106809 A>G causes a change in the reliability of classifications of two putative splice sites in the ACE2 gene, potentially regulating the expression of functional genes (PIR, ACE2, and CLTRN) in multiple tissues and cell lines (p< 0.05). Conclusion: The ACE2 gene rs2106809 A>G variant is significantly associated with the risk of PE via individual locus effects and/or complex gene-gene and gene-environment interactions. Regulating the expression of functional genes such as PIR, ACE2, and CLTRN may be the molecular mechanism by which rs2106809 increases an individual's susceptibility to PE.