GEO series

Transcriptomic analysis of peripheral blood mononuclear cells reveals age specific differences at baseline and response to acute exercise

GSE293163 Homo sapiens (human) RNA-seq (gene expression) 30 samples Submitted 2025/05/01 Platform GPL34281

At a glance

RNA-seq (gene expression) · human · 30 samples

What it is: RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism: Homo sapiens (human)
Samples: 30 samples: 30 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: Transcriptomic analyses of peripheral blood mononuclear cells reveal age-specific basal and acute exercise responsiveness differences in humansAmerican journal of physiology. Endocrinology and metabolism · 2025

Summary (written by the submitters)

Aging is associated with alterations in immune cell function, contributing to age-related diseases and frailty. As key drivers of the immune response, we investigated the transcriptome of peripheral blood mononuclear cells (PBMCs) using RNA-sequencing before and after high-intensity single-leg knee-extension exercise in young (Young; n=7, 23±4 years) and older individuals (Old; n=8, 65±7 years).

Read the full summary ↓

Bioinformatic analyses revealed biological processes and pathways that were altered with aging and response to exercise. At baseline, 665 out of 19,762 genes differed in PBMCs with notable differences relating to pathways involved in DNA Damage/Telomere Stress Induced Senescence, NAD Signaling Pathway, and Oxidative Stress Induced Senescence. After exercise, 53 out of 13,695 genes were differentially expressed in the Young, while 1,026 out of 19,101 genes changed in the Old. In Young, the enriched processes and predicted pathways were linked to natural killer cells, while in Old, they focused on cell signaling immune responses. Lastly, 26 genes exhibited similar responses to exercise between groups, enriching the biological process of natural killer cell-mediated immunity regulation. Our findings indicate that PBMC gene expression is altered with aging and in response to acute exercise in older adults, with exercise having a more substantial modulating effect on the immune system response with aging. The underlying causes and functional consequences of the observed transcriptional differences require additional investigation.

Published in

Transcriptomic analyses of peripheral blood mononuclear cells reveal age-specific basal and acute exercise responsiveness differences in humans

Ruple BA, Carlini NA, Kofoed JS et al. · American journal of physiology. Endocrinology and metabolism 2025 · PMID 40695537 · doi:10.1152/ajpendo.00169.2025

This dataset

Open GSE293163 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 GSE293163_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1243092 and SRA study SRP573822. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40695537) ↗

Study design

30 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 30 sample titles: 30 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

GSM8877692 22719X31 01 Pre Young
GSM8877693 22719X32 01 Post Young
GSM8877694 22719X33 02 Pre Young
GSM8877695 22719X34 02 Post Young
GSM8877696 22719X35 03 Pre Young
GSM8877697 22719X36 03 Post Young
GSM8877698 22719X37 04 Pre Young
GSM8877699 22719X38 04 Post Young
GSM8877700 22719X39 05 Pre Young
GSM8877701 22719X40 05 Post Young
GSM8877702 22719X41 06 Pre Young
GSM8877703 22719X42 06 Post Young
GSM8877704 22719X43 08 Pre Old
GSM8877705 22719X44 08 Post Old
GSM8877706 22719X45 09 Pre Old
GSM8877707 22719X46 09 Post Old
GSM8877708 22719X47 10 Pre Old
GSM8877709 22719X48 10 Post Old
GSM8877710 22719X49 11 Pre Old
GSM8877711 22719X50 11 Post Old
GSM8877712 22719X51 12 Pre Old
GSM8877713 22719X52 12 Post Old
GSM8877714 22719X53 13 Pre Old
GSM8877715 22719X54 13 Post Old
GSM8877716 22719X55 14 Pre Old
GSM8877717 22719X56 14 Post Old
GSM8877718 22719X57 18 Pre Young
GSM8877719 22719X58 18 Post Young
GSM8877720 22719X59 19 Pre Old
GSM8877721 22719X60 19 Post Old

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.