GEO series

Predictive biomarkers and maternal immune alterations in postpartum preeclampsia reveal an immune-driven pathology

GSE262745 Homo sapiens (human) Single-cell RNA-seq 11 samples Submitted 2024/03/28 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 11 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: 11 samples: 11 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: Predictive biomarkers and initial analysis of maternal immune alterations in postpartum preeclampsia reveal an immune-driven pathologyFrontiers in immunology · 2024

Summary (written by the submitters)

Postpartum preeclampsia (PPPE) is an under-diagnosed condition, developing within 48 hours to 6 weeks following an uncomplicated pregnancy. The etiology of PPPE is still unknown, leaving patients vulnerable and making the identification and treatment of patients requiring postpartum care an unmet need. We aimed to understand the immune contribution to PPPE at the time of diagnosis, as well as uncover the predictive potential of perinatal biomarkers for the early postnatal identification of high-risk patients.

Read the full summary ↓

Placentas were collected at delivery from uncomplicated pregnancies (CTL) and PPPE patients for immunohistochemistry analysis. In this initial study, blood samples in PPPE patients were collected at the time of PPPE diagnosis (48h-25 days postpartum; mean 7.4 days) and compared to CTL blood samples taken 24h after delivery. Single-cell transcriptomics, flow cytometry, intracellular cytokine staining, and the circulating levels of inflammatory mediators were evaluated in the blood. Placental CD163+ cells and 1st trimester blood pressures can be valuable non-invasive and predictive biomarkers of PPPE with strong clinical application prospects. Furthermore, changes in immune cell populations, as well as cytokine production by CD14+, CD4+, and CD8+ cells, suggested a dampened response with an exhausted phenotype including decreased IL1b, IL12, and IFNg as well as elevated IL10. Understanding maternal immune changes at the time of diagnosis and prenatally within the placenta in our sizable cohort will serve as groundwork for pre-clinical and clinical research, as well as guiding clinical practice for example in the development of immune-targeted therapies, and early postnatal identification of patients who would benefit from more thorough follow-ups and risk education in the weeks following an uncomplicated pregnancy.

Published in

Predictive biomarkers and initial analysis of maternal immune alterations in postpartum preeclampsia reveal an immune-driven pathology

Couture C, Brien ME, Rechtzigel J et al. · Frontiers in immunology 2024 · PMID 38745664 · doi:10.3389/fimmu.2024.1380629

This dataset

Open GSE262745 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 GSE262745_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 PRJNA1093097 and SRA study SRP498493. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38745664) ↗

Study design

11 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 11 sample titles: 11 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

GSM8178020 PPPE.254 post
GSM8178021 PPPE.180 pp
GSM8178022 PPPE.183 post
GSM8178023 PPPE.192 pp
GSM8178024 PPPE.235 post
GSM8178025 PPPE.221 pp
GSM8178026 PPPE.223 pp
GSM8178027 PPPE.251 post
GSM8178028 PPPE.227 pp
GSM8178029 PPPE.243 post
GSM8178030 PPPE.255 pp

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