AUTHOR=Chen Jie-ling , Dai Hui-fang , Kan Xin-chen , Wu Jie , Chen Hong-Wu 

TITLE=The integrated bioinformatic analysis identifies immune microenvironment-related potential biomarkers for patients with gestational diabetes mellitus

JOURNAL=Frontiers in Immunology

VOLUME=15

YEAR=2024

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2024.1296855

DOI=10.3389/fimmu.2024.1296855

ISSN=1664-3224

ABSTRACT=<sec><title>Background</title><p>Gestational diabetes mellitus (GDM), a transient disease, may lead to short- or long-term adverse influences on maternal and fetal health. Therefore, its potential functions, mechanisms and related molecular biomarkers must be comprehended for the control, diagnosis and treatment of GDM.</p></sec><sec><title>Methods</title><p>The differentially expressed genes (DEGs) were identified using GSE49524 and GSE87295 associated with GDM from the Gene Expression Omnibus database, followed by function enrichment analysis, protein-protein interactions network construction, hub DEGs mining, diagnostic value evaluation and immune infiltration analysis. Finally, hub DEGs, the strongest related to immune infiltration, were screened as immune-related biomarkers.</p></sec><sec><title>Results</title><p>A hundred and seven DEGs were identified between patients with GDM and healthy individuals. Six hub genes with high diagnostic values, including <italic>ALDH1A1</italic>, <italic>BMP4</italic>, <italic>EFNB2</italic>, <italic>MME</italic>, <italic>PLAUR</italic> and <italic>SLIT2</italic>, were identified. Among these, two immune-related genes (<italic>PLAUR</italic> and <italic>SLIT2</italic>) with the highest absolute correlation coefficient were considered immune-related biomarkers in GDM.</p></sec><sec><title>Conclusion</title><p>Our study provides a comprehensive analysis of GDM, which would provide a foundation for the development of diagnosis and treatment of GDM.</p></sec>