The Bioinformatics Study On Novel Candidate Genes In The Comorbidity Of Preeclampsia And Gestational Diabetes Mellitus

Objective: At present,there are more than 200,000 pregnant women suffering from gestational diabetes in China each year,with an incidence between 5% and 20%,accompanied by a variety of pregnancy complications,of which preeclampsia is the main reason for the increase in maternal mortality.Its etiology and pathogenesis have not yet been fully elucidated.Research on the complications of preeclampsia and gestational diabetes focuses on cohort studies and clinical genotyping experiments.There is no related research on constructing comorbid gene interaction networks,screening co-occurring disease genes,or mining common pathogenesis and biological processes.In this study,text mining was performed on the titles and abstracts of relevant literatures,and the important pathogenic genes of gestational diabetes/preeclampsia comorbidities were screened out,the gene interaction network constructed and the biological processes involved reveal the potential pathogenic mechanism of gestational diabetes/preeclampsia comorbidities and used for disease prevention and control and clinical research.Methods: This study retrieved the literature related to preeclampsia and gestational diabetes in Pubmed,and used the ANDSystem tool(Associative Network Discovery System)to perform word segmentation and semantic analysis,and screened out the related genes of comorbidities.The study dug out the relationship between them,and built the gene interaction network of the two diseases.The DAVID database conducted the gene ontology biological process enrichment analysis on candidate genes,found out the physiological processes that these genes participate in,and explored the potential pathogenic mechanisms of comorbidities.The use of Endeavor,Topp Gene,Coexpedia and other bio-informatics tools prioritized these candidate genes from different perspectives.Finally,the important candidate genes of gestational diabetes/preeclampsia comorbidities were determined according to the results of gene priority,and their kinetic studies and literature verification were carried out to confirm their roles in the pathogenesis of comorbidities.Results: This study constructed a gene interaction network for preeclampsia,gestational diabetes,and gestational diabetes/preeclampsia comorbidities.The key nodes were VCAM1,KDR and TNF,which have the best connectivity with other genes.131 co-occurring genes of the two diseases were screened as candidate gene sets for subsequent processing.The top ten pathological biological processes of comorbidities mainly include angiogenesis,aging,positive regulation of angiogenesis,positive regulation of cell proliferation,and positive regulation of protein phosphorylation et al.According to the priority ranking results of candidate genes,the important candidate genes for comorbidities were selected as PLG,VCAM1,TGFβ1,INSR,VEGFA,ANXA2,AGT,TNF,HLA-C and KDR.The research trends of important candidate genes all showed a positive correlation trend,and researchers were more active in the research situation of important candidate genes.In the literature verification part,there was no research to confirm the regulatory effect of important candidate genes on gestational diabetes/preeclampsia comorbidities,but most of them have been confirmed to be related to gestational diabetes or preeclampsia,AGT,HLA-C and KDR only Participated in some related biological processes,but it has not been confirmed that they had an impact on the disease.Conclusion: We have established a gene interaction network between preeclampsia and gestational diabetes,screened out candidate genes for co-occurrence of the two diseases,and unearthed the important physiological processes involved in candidate genes,reflecting the molecular genetics of the two diseases during pregnancy.The potential connection of the diseases would help to further reveal the pathogenesis of comorbidities and preeclampsia.Comparing the role of candidate genes in the genetic mechanism of comorbidities,the selected important candidate genes could be used in clinical planned genotyping experiments and maternal-fetal cohort studies.