Poster Presentation ESA-SRB 2023 in conjunction with ENSA

Integrative transcriptomic analysis of miRNA-mRNA network in late-onset preeclampsia placentae (#405)

Luhao Han 1 , Olivia Holland 1 , Fabricio Da Silva Costa 2 3 , Anthony Perkins 4
  1. School of Pharmacy and Medical Sciences, Griffith University, Gold Coast, Queensland, Australia
  2. Maternal Fetal Medicine Unit, Gold Coast University Hospital, Gold Coast , Queensland, Australia
  3. School of Medicine and Dentistry, Griffith University, Gold Coast, Queensland, Australia
  4. School of Health, University of the Sunshine Coast, Sunshine Coast, Queensland, Australia

Preeclampsia is a heterogeneous disorder of pregnancy with two main subtypes, early-onset and late-onset, suggesting potentially different underlying molecular mechanisms. Late-onset preeclampsia is more prevalent (approximately 70% of cases) and remains challenging to predict and manage. This study aimed to identify dysregulated genes, miRNAs and their interaction in term placentae from late-onset preeclampsia by utilizing in silico analysis.

 

Differential expressed genes (DEGs) and miRNAs (DEMs) were identified from subsets of public datasets GSE75010 (cases = 26, controls = 28) and GSE103542 (cases = 5, controls = 8) from Gene Expression Omnibus datasets. Differential expression and pathway analyses were performed using the R packages “limma” and “clusterProfiler”. A protein-protein interaction (PPI) network was generated via the STRING database. Target genes of DEMs were predicted with the R package “multiMiR”. DEGs that overlapped with the target genes of DEMs were defined as DEM-target DEGs for constructing a miRNA-mRNA network by Cytoscape software.

 

We identified 216 DEGs (96 upregulated, 120 downregulated) and 20 DEMs (10 upregulated, 10 downregulated) with |logFC| > 2 and p < 0.05. The PPI network of 216 DEGs was constructed to select hub genes according to the Maximal Clique Centrality (MCC) score using CytoHubba in Cytoscape. The top ten genes with the highest MCC score were FN1, SEPRINE1, FLT1, TIMP3, ENG, EPAS1, PGF, LEP, SCARB1, and TIMP2. miRNA-mRNA regulatory networks implicated miR-548c-3p/u, miR-3065-5p, miR-3921, miR-34c-5p, and miR-3163 interaction with multiple DEGs.

 

This study uncovered the top ten hub genes and ten DEG-related miRNAs associated with placental dysfunction in late-onset preeclampsia. In particular, miR-34-5p may play an important role in late-onset preeclampsia pathogenesis by regulating several hub genes such as SERPINE1, FLT1, LDHA, and ADAM12. These findings will be further validated in our local placental biobank (case = 26) to confirm their relevance in late-onset preeclampsia.