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

GSE271628 Homo sapiens (human) RNA-seq (gene expression) 11 samples Submitted 2024/12/10 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 11 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
11 samples: 7 × Placental tissue, Preeclampsia vs 4 × Placental tissue, ControlGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Multi-omics analysis of placental metabolomics and transcriptomics datasets reveals comprehensive insights into the pathophysiology of preeclampsiaJournal of pharmaceutical and biomedical analysis · 2025
Summary (written by the submitters)
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.
Read the full summary ↓
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.
Published in
Multi-omics analysis of placental metabolomics and transcriptomics datasets reveals comprehensive insights into the pathophysiology of preeclampsia
Mumcu A, Sarıdoğan E, Düz SA et al. · Journal of pharmaceutical and biomedical analysis 2025 · PMID 39883963 · doi:10.1016/j.jpba.2025.116701
This dataset
Open GSE271628 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE271628_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1132524 and SRA study SRP518291. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39883963) ↗
Study design
7 × Placental tissue, Preeclampsia vs 4 × Placental tissue, Control

Supports a between-group comparison across 11 samples.

How we read this: 2 replicated groups read from 11 sample titles; they account for 11 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
Datasets on a similar topic

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