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Preterm birth skews the developmental trajectory of myeloid-derived suppressor cells in the first 48 hours of life: single-cell transcriptomics and inferred intercellular communication

GSE326288 Homo sapiens (human) Single-cell RNA-seq 19 samples Submitted 2026/05/18 Platform GPL34284
At a glance

Single-cell RNA-seq · human · 19 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
19 samples: 7 × PT vs 6 × FT vs 6 × HAGroups 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.
Summary (written by the submitters)
Background: Prematurity is a leading cause of neonatal and childhood mortality, with infections driving early deaths. Innate immunity provides frontline defense after birth and is shaped in part by myeloid-derived suppressor cells (MDSCs). The role of MDSCs in regulation of neonatal immunity, especially in the context of prematurity, remains elusive.
Read the full summary ↓
We sought to understand the transcriptional landscape of neonatal immune myeloid regulators, specifically differences between preterm and full-term neonates. Insight into specific cellular networks could help understand how to skew preterm MDSCs’ development towards classical immunotolerant and anti-microbial mechanisms. Methods: This cross-sectional study used single-cell RNA sequencing to characterize the neonatal MDSC transcriptional landscape, developmental trajectories, and predicted signaling networks within 48 hours after birth. Peripheral blood mononuclear cells were isolated from 7 preterm neonates (<36 weeks gestational age), 6 full-term neonates (>37 weeks), and 6 healthy adult (21-45 years old, control). Primary exposure was premature birth and neonatal intensive care hospitalization from a single-center, academic tertiary care hospital between 2023 – 2024. Results: Among ~339,000 cells, preterm neonates exhibited enrichment of polymorphonuclear MDSCs (10.6%±5.3%) vs full-term (2.6%±1.3%) and adults (0.4%±1.3%). Trajectory analysis identified a prematurity-associated differentiation branch characterized by inflammatory signaling, mitochondrial stress, and heightened protein-translation programs, distinct from a conserved, tolerogenic MDSC trajectory present across ages. Cell-communication modeling showed intensified outgoing and incoming signaling via ADGRE, RESISTIN, TGF-β, ANNEXIN, and ICAM networks. Antigen presentation signatures suggested preserved MHC-I output and diminished MHC-II interactions in neonates, with increased MHC-I input to preterm polymorphonuclear MDSCs. Conclusions: Prematurity is associated with early divergence of MDSC maturation toward an inflammatory and metabolically stressed PMN-MDSC state with altered immune communication. These findings identify cellular mechanisms that may contribute to the heightened tissue damage and infection susceptibility of preterm neonates and highlight MDSC signaling as a potential target for early-life immunomodulatory interventions.
This dataset
Open GSE326288 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 GSE326288_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 PRJNA1445076 and SRA study SRP687659. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
7 × PT vs 6 × FT vs 6 × HA

Supports a between-group comparison across 19 samples.

How we read this: 3 replicated groups read from 19 sample titles; they account for 19 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
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