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Dual specificity phosphate 1 (DUSP1) has a key non-invasive predictive marker in preeclampsia

GSE262147 Homo sapiens (human) RNA-seq (gene expression) 53 samples Submitted 2024/03/26 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 53 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
53 samples: 16 conditions, mostly in duplicateGroups 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
Dual specificity phosphatase 1 as a non-invasive circulating biomarker candidate in preeclampsiaFrontiers in endocrinology · 2025
Summary (written by the submitters)
Preeclampsia (PE) is a multisystem pregnancy complication constituting a major cause of maternal and fetal morbidity and mortality. Factors pointing to a placental origin are the development of the pathology only during pregnancy, and its disappearance in the post-partum period. Our study identified a specific signature of PE including five Gene Ontology clusters including "angiogenesis and differentiation", "cell cycle”, "cell adhesion", "inflammatory response" and "cellular metabolism".
Read the full summary ↓
Interestingly, we identified DUSP1 as a biomarker of interest in PE. Pregnant women with PE have a higher concentration of DUSP1 in serum in the first trimester of pregnancy compared to healthy donors. Interesting, at a distance from childbirth DUSP1 finds a rate like the control group showing the predictive interest of DUSP1 as a predictive biomarker of PE
Published in
Dual specificity phosphatase 1 as a non-invasive circulating biomarker candidate in preeclampsia
Andrieu J, Donet A, Cocallemen JF et al. · Frontiers in endocrinology 2025 · PMID 41019346 · doi:10.3389/fendo.2025.1576240
This dataset
Open GSE262147 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 GSE262147_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 PRJNA1090471 and SRA study SRP497023. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41019346) ↗
Study design
16 conditions, mostly in duplicate
PE_02_V ×2 PE_04_V ×2 PE_07_V ×2 PE_08_V ×2 PE_09_V ×2 PE_23_V ×2 PE_24_V ×2 PE_25_V ×2 +29 more

Supports a between-group comparison across 32 samples.

How we read this: 16 replicated groups read from 53 sample titles; they account for 32 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

+ 13 more — browse all 53 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.