GEO series

Multi-omics Analysis Revealed Unique Features of Age-associated Type2 CD8 Memory T cells [CUT&Run]

GSE310773 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 23 samples Submitted 2026/02/11 Platform GPL24676

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 23 samples

What it is: ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism: Homo sapiens (human)
Samples: 23 samples: 23 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: Multi-Omics Analysis of Human Blood Cells Reveals Unique Features of Age-Associated Type 2 CD8 Memory T CellsAging cell · 2026

Summary (written by the submitters)

Aging impacts immune function, yet how and why various subsets of immune cells change during aging is still incompletely understood. Here, we analyzed peripheral blood mononuclear cells (PBMCs) from a cohort of healthy donors aged 20–82 years to uncover previously unrecognized age-dependent changes, using a 36-color spectral flow cytometry panel focused on T cells.

Read the full summary ↓

We found that CXCR3- memory CD8 T cells, which produce a Th2-like cytokine response, accumulate with age. Comprehensive multi-omics analysis revealed transcriptional and epigenetic signatures that support Th2-like function. Importantly, we also identified an age-dependent bias towards the production of Th2 cytokines after activation in naive CD8 T cells, along with transcriptional and epigenetic changes supporting this outcome. Moreover, health outcome association analysis demonstrated a pathogenic feature of CXCR3- CM accumulation. Together, our results suggest that age-dependent corruption of epigenetic programming may cause the aberrant emergence of this potentially pathogenic Th2-like immune population

Published in

Multi-Omics Analysis of Human Blood Cells Reveals Unique Features of Age-Associated Type 2 CD8 Memory T Cells

Matsui H, Cervantes M, Khalid MM et al. · Aging cell 2026 · PMID 41622514 · doi:10.1111/acel.70393

This dataset

Open GSE310773 in finder → Find more human ChIP / ATAC / CUT&Tag 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 GSE310773_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1367048 and SRA study SRP647308. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41622514) ↗

Study design

23 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 23 sample titles: 23 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

GSM9308642 Donor R29800, FACS sorted CD8+ CXCR3+ CM T cells, H3K4me3(Cut and Run)
GSM9308643 Donor R29796, FACS sorted CD8+ CXCR3+ CM T cells, H3K4me3(Cut and Run)
GSM9308644 Donor R29797, FACS sorted CD8+ CXCR3+ CM T cells, H3K4me3(Cut and Run)
GSM9308645 Donor R29800, FACS sorted CD8+ CXCR3- CM T cells, H3K4me3(Cut and Run)
GSM9308646 Donor R29796, FACS sorted CD8+ CXCR3- CM T cells, H3K4me3(Cut and Run)
GSM9308647 Donor R29797, FACS sorted CD8+ CXCR3- CM T cells, H3K4me3(Cut and Run)
GSM9308648 Donor R29800, FACS sorted CD8+ CD57+ EMRA T cells, H3K4me3(Cut and Run)
GSM9308649 Donor R29796, FACS sorted CD8+ CD57+ EMRA T cells, H3K4me3(Cut and Run)
GSM9308650 Donor R29797, FACS sorted CD8+ CD57+ EMRA T cells, H3K4me3(Cut and Run)
GSM9308651 Donor R29800, FACS sorted CD8+ CD28+/CD57+ EM T cells, H3K4me3(Cut and Run)
GSM9308652 Donor R29797, FACS sorted CD8+ CD28+/CD57+ EM T cells, H3K4me3(Cut and Run)
GSM9308653 Donor R29800, FACS sorted CD8+ CXCR3+ CM T cells, H3K27me3(Cut and Run)
GSM9308654 Donor R29796, FACS sorted CD8+ CXCR3+ CM T cells, H3K27me3(Cut and Run)
GSM9308655 Donor R29797, FACS sorted CD8+ CXCR3+ CM T cells, H3K27me3(Cut and Run)
GSM9308656 Donor R29800, FACS sorted CD8+ CXCR3- CM T cells, H3K27me3(Cut and Run)
GSM9308657 Donor R29796, FACS sorted CD8+ CXCR3- CM T cells, H3K27me3(Cut and Run)
GSM9308658 Donor R29797, FACS sorted CD8+ CXCR3- CM T cells, H3K27me3(Cut and Run)
GSM9308659 Donor R29800, FACS sorted CD8+ CD57+ EMRA T cells, H3K27me3(Cut and Run)
GSM9308660 Donor R29796, FACS sorted CD8+ CD57+ EMRA T cells, H3K27me3(Cut and Run)
GSM9308661 Donor R29797, FACS sorted CD8+ CD57+ EMRA T cells, H3K27me3(Cut and Run)
GSM9308662 Donor R29800, FACS sorted CD8+ CD28+/CD57+ EM T cells, H3K27me3(Cut and Run)
GSM9308663 Donor R29796, FACS sorted CD8+ CD28+/CD57+ EM T cells, H3K27me3(Cut and Run)
GSM9308664 Donor R29797, FACS sorted CD8+ CD28+/CD57+ EM T cells, H3K27me3(Cut and Run)

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