Differential gene expression and network-based analyses of the placental transcriptome reveal distinct potential biomarkers for gestational diabetes mellitus

AIMS: Gestational diabetes mellitus (GDM) is a common complication during pregnancy affecting the mother and fetus. With the problems encountered with the oral glucose tolerance test (OGTT), we aim to identify potential early biomarkers of GDM. METHODS: A cross-sectional study was conducted among 80 pregnant women. Blood samples were collected every trimester, and total RNA was isolated. After quality control and library preparation, next-generation sequencing was performed. Differential expression analysis was done. Enriched Gene Ontology: Biological Processes (GO: BP) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were identified. Gene co-expression networks were constructed. Protein-protein Interaction (PPI) networks were then built from modules significantly correlated with Hemoglobin A1c. Genes with the highest degree of interaction were identified as hub genes. RESULTS: IGKV2D-28 and PTPRG were consistently differentially expressed among the three comparisons. Top enriched GO: BP terms and KEGG pathways are linked to immune responses. Orange (r = 0.59, p = 0.02) and purple modules (r = 0.41, p = 0.02) of the GDM cohorts in the first and second trimesters, respectively, significantly correlated with Hemoglobin A1c. HDAC8 of the orange module and MPO and CRISP3 of the purple module were identified as hub genes. CONCLUSIONS: In this study, potential biomarkers of GDM were identified, namely, IGKV2D-28, PTPRG, HDAC8, MPO, and CRISP3.