Multi-omics analysis of placental metabolomics and transcriptomics datasets reveals comprehensive insights into the pathophysiology of preeclampsia

Abstract

Preeclampsia, a life-threatening pregnancy complication, remains a major global health concern. Understanding the complex molecular mechanisms underlying this disorder is crucial for improving both diagnostics and therapeutic strategies. In this study, a multi-omics approach based on NMR metabolomics and RNA-seq transcriptomics analyses was conducted to analyze placental tissue samples obtained from patients with preeclampsia and healthy controls. Metabolomics data analysis results indicated alterations in several metabolite levels including lactate, myo-inositol, glutamate, glutamine, valine, leucine, isoleucine, creatinine, alanine, taurine, choline, phosphocholine, glycerophosphocholine, ethanolamine, and dihydroxyacetone. These alterations cause significant disruptions in the Krebs cycle, energy, lipid, and amino acid metabolisms. Concurrently, transcriptomics data analysis identified 10 upregulated and 37 downregulated genes (|log2FC= > 1 and padj < 0.05) in preeclampsia patients. Identified genes were linked to critical roles such as vasoconstriction, angiogenesis, inflammation, hormonal balance, oxidative stress, and collagen integrity. Multi-omics data analysis revealed the association of certain metabolites with several other genes. A gene interaction network formed by these genes resulted in a lower protein-protein interaction enrichment value (p-value < 1e-16) compared to the network formed with the differentially expressed genes (p-value = 0.0183) which suggests the importance of considering multiple omics levels for a comprehensive understanding of the disease.