Burton, Mark A., Garratt, Emma S., Sharkh, Hanan Y., Hewitt, Matthew O., Antoun, Elie, Westbury, Leo D., Dennison, Elaine M., Harvey, Nicholas C., Cooper, Cyrus, Patel, Harnish P., Godfrey, Keith M. and Lillycrop, Karen A. (2026) Single-cell RNAseq identifies heterogeneity in myoblasts from older adults with differences related to muscle mass and function. JCSM Communications, 17 (1), [e70213]. (doi:10.1002/jcsm.70213).
Abstract
Background: ageing is associated with the loss of muscle mass and function, with consequences for metabolic health, frailty and independence in later life. The aim of this study was to investigate the transcriptional heterogeneity of human proliferating muscle satellite/stem cells (myoblasts) from older adults and how this heterogeneity may vary between healthy individuals and those with low muscle mass and function.
Methods: single-cell transcriptomic analysis was carried out on proliferating myoblasts isolated from vastus lateralis biopsies from 132 participants (34 male, 98 female) aged 72–83 years from the Hertfordshire Sarcopenia Study extension. Uniform Manifold Approximation and Projection (UMAP) clustering was applied to identify clusters of myoblasts with distinct transcriptional profiles, Gene Ontology analysis was used to identify pathways enriched among the clusters, and pseudotime trajectory analysis was used to identify inferred cell lineages. Differential gene expression within cell clusters, together with the proportions of cells within each cluster and lineage, were assessed with respect to participant appendicular lean-mass index (ALMi), grip strength, and gait speed.
Results: thirteen distinct cell clusters based on the transcriptional heterogeneity of the myoblasts were identified. Clusters 0–6 contained the majority (94.6%) of cells. Marker genes were enriched for cytoplasmic translation (Cluster 0, false discovery rate [FDR] = 7.21 × 10−63), muscle development (Cluster 1, FDR = 2.25 × 10−13), cell proliferation (Clusters 2, 4 and 6, all FDR ≤ 0.05), extracellular matrix organisation (Cluster 3, FDR = 1.92 × 10−45) and RNA processing (Cluster 5, FDR = 1.89 × 10−08). Individuals with the highest grip strength and ALMi had a greater proportion of Cluster 1 and Cluster 5 cells. Gene expression analysis (FDR ≤ 0.05) within the clusters identified 22 differentially expressed transcripts with respect to ALMi in Cluster 2 and 13 with respect to grip strength in Cluster 1. Inferred lineage analysis identified cells transitioning along five trajectories (L1–L5), including cells in L1, L3 and L4 progressing towards a stressed pre-senescent/senescent (L1) or fibrogenic (L3 and L4) state, with cells in these lineages being more likely to originate from individuals with low ALMi (χ2 p = 1.11 × 10−146) and grip strength (χ2 p = 1.31 × 10−269).
Conclusion: our findings demonstrate considerable transcriptional heterogeneity in skeletal muscle myoblasts from older adults. This heterogeneity includes myoblasts from individuals with low muscle mass and strength progressing towards a fibrogenic or stressed state.
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