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Circulating immune cells from early- and late-onset preeclampsia displays distinct profiles with differential impact on endothelial activation

GSE266488 Homo sapiens (human) Single-cell RNA-seq 48 samples Submitted 2024/09/24 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 48 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
48 samples: 48 samples, each with a distinct title — no replicated groupsGroups 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
Circulating Immune Cells from Early- and Late-onset Pre-eclampsia Displays Distinct Profiles with Differential Impact on Endothelial ActivationJournal of immunology (Baltimore, Md. : 1950) · 2024
Summary (written by the submitters)
Preeclampsia (PE) affects 5-8% of pregnancies and has detrimental effects on maternal-fetal health. PE is characterized by de novo hypertension after 20 weeks of gestation and end-organ damage. Systemic inflammatory imbalance has been associated with PE, but its contribution to the pathology is poorly understood. Our objective was to investigate maternal systemic immune changes in early-onset PE (EOPE) and late-onset PE (LOPE) vs uncomplicated pregnancies (CTRL), and their contribution to endothelial activation, hallmark of hypertension.
Read the full summary ↓
Blood samples were analyzed by flow cytometry, multiplex assay, intracellular cytokine staining (ICS), and single-cell RNA sequencing. We performed co-cultures between circulating immune cells and human umbilical veins endothelial cells (HUVECs) to assess endothelial activation. We found that EOPE had decreased Treg (4.64±0.33, p<0.05) and monocytes (33.92±3.08, p<0.01), whereas LOPE had decreased Treg (4.60±0.30, p<0.05) and Th2 cells (7.50±0.62, p<0.01) vs CTRL. Compared to CTRL, elevated cytokines/chemokines, and growth factors were observed in LOPE, whereas EOPE primarily showed decreased levels. Using ICS, we observed more monocytes producing IL-12, TNF, and IL-1 (all p<0.05) in LOPE vs CTRL. At the transcriptomic level, we found differentially expressed genes (DEGs) between EOPE and CTRL, predominantly related to upregulation of immune activation pathways. Lastly, EOPE peripheral blood mononuclear cells (PBMCs) induced heightened endothelial activation in vitro observed by increased ICAM-1 and ET-1 (p<0.05), whereas LOPE PBMCs required LPS stimulation. While significant proteomic changes are observed in the LOPE group, the EOPE displayed changes mostly at the transcriptomic levels and could induce endothelial activation in vitro.
Published in
Circulating Immune Cells from Early- and Late-onset Pre-eclampsia Displays Distinct Profiles with Differential Impact on Endothelial Activation
Bernier E, Couture C, Borchers A et al. · Journal of immunology (Baltimore, Md. : 1950) 2024 · PMID 39302114 · doi:10.4049/jimmunol.2400196
This dataset
Open GSE266488 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 GSE266488_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1107281 and SRA study SRP505485. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39302114) ↗
Study design
48 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 48 sample titles: 48 distinct titles with little repetition. 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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