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Multi-omics analysis reveals sex-specific etiology of human muscle weakness following musculoskeletal injury

GSE324033 Homo sapiens (human) Single-nucleus RNA-seq 15 samples Submitted 2026/05/15 Platform GPL24676
At a glance

Single-nucleus RNA-seq · human · 15 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). 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
15 samples: 8 × ACLR, vs 7 × Non-injured,Groups 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 reveals sex-specific etiology of human muscle weakness following musculoskeletal injuryBMC medicine · 2026
Summary (written by the submitters)
Background: Musculoskeletal injuries comprise a growing source of disability worldwide, and the recovery of muscle strength following injury is a critical determinant of patient reported outcomes. Females experience exacerbated muscle atrophy, poorer outcomes, and higher re-injury rates, necessitating a comprehensive interrogation of sex-specific skeletal muscle differences.
Read the full summary ↓
Our purpose in the current study was to perform an unbiased transcriptomic profiling of muscle samples to identify putative sex-specific molecular targets to enhance recovery in patients who underwent anterior cruciate ligament reconstruction (ACLR). Methods: We performed cellular phenotyping, bulk and single nucleus RNA-sequencing on muscle biopsy samples obtained from thirty-six participants (18M, 18F). Muscle samples were obtained from the ACLR and contralateral limb with follow-up tissue collection of the injured limb also occurring at seven days and four months post-ACLR. Transcriptomic analyses illuminated putative molecular mechanisms through which sex influences muscle recovery following acute injury. Results: Females exhibited greater muscle atrophy relative to males at 4 months post-ACLR compared to the uninjured limb. Bulk and single nucleus paired-limb transcriptomic analyses revealed the emergence of sex-specific myonuclear signaling cascades that demonstrate impaired reactive oxygen species scavenging in females. Females exhibited attenuated SOD2 expression that was associated with increased indices of oxidative stress and protein damage. Within females, angiogenesis signaling was also impaired and associated with capillary rarefaction after reconstructive surgery. Conclusions: These findings reveal inherent sex-based differences in muscle pathology that likely necessitate unique clinical treatments following musculoskeletal injury.
Published in
Multi-omics analysis reveals sex-specific etiology of human muscle weakness following musculoskeletal injury
Keeble AR, Owen AM, Thomas NT et al. · BMC medicine 2026 · PMID 41882639 · doi:10.1186/s12916-026-04818-8
This dataset
Open GSE324033 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 GSE324033_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 PRJNA1433036 and SRA study SRP681384. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41882639) ↗
Study design
8 × ACLR, vs 7 × Non-injured,

Supports a between-group comparison across 15 samples.

How we read this: 2 replicated groups read from 15 sample titles; they account for 15 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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