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Single-cell map of the healthy human immune system across the lifespan reveals unique infant immune signatures

GSE233321 Homo sapiens (human) Single-cell RNA-seq 118 samples Submitted 2026/05/07 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 118 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
118 samples: 99 distinct titles, 4 of them repeatedGroups 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
Single-cell map of the healthy human immune system across the lifespan reveals unique infant immune signaturesNature communications · 2026
Summary (written by the submitters)
The human immune system undergoes dynamic remodeling from infancy through old age. We profiled PBMCs from 167 healthy individuals (ages 2 months to 105 years): infants (n=36), children (n=26), adolescents (n=20), young adults (n=24), middle‑aged (n=16), older adults (n=33) and oldest old (n=12) using scRNA‑seq and snATAC‑seq (n=23). MAIT and γδ T cells showed a “rise and fall” pattern, rising in childhood, peaking in young adulthood, and declining with age.
Read the full summary ↓
Conventional CD8⁺ T cells were most profoundly altered with age, with decreasing naïve and increasing GZMK⁺ and TEMRA cells. The oldest old had increased TEMRA, adaptive NK, and KLRF1⁺ γδ T cells. Infants showed increased CD16⁺ monocytes and pDCs, constitutive interferon‑stimulated gene expression, and expanded SOX4⁺ naïve T cells. Inflammatory and stress‑response pathways increased with age, while interferon pathways declined. This map provides insights into human immune system dynamics across the lifespan, emphasizing unique features of the infant immune system.
Published in
Single-cell map of the healthy human immune system across the lifespan reveals unique infant immune signatures
Nehar-Belaid D, Thibodeau A, Eroglu A et al. · Nature communications 2026 · PMID 42297833 · doi:10.1038/s41467-026-73729-2
This dataset
Open GSE233321 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 GSE233321_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 PRJNA975864. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42297833) ↗
Study design
99 distinct titles, 4 of them repeated
PBMC, Infants and children, Infant ×9 PBMC, Young and middleage adults, Young ×6 PBMC, Older adults, Olde ×5 PBMC, Adolescents, Ado ×3

How we read this: Read from 118 sample titles: 99 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

+ 78 more — browse all 118 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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