Fibro-adipogenic Progenitor and Macrophage Remodeling of the Aging Skeletal Muscle Niche During Exercise-Induced Hypertrophy
Wang, J.; Jensen, J. B.; Kudahl, S.; Just, J.; Thybo, F. F.; Bjerre, M.; de Paoli, F. V.; Jessen, N.; Vissing, K.; Farup, J.
Show abstract
Fibro-adipogenic progenitors (FAPs) have emerged as central regulators of the skeletal muscle homeostasis and the muscle microenvironment. However, the role of FAPs in the context of exercise-induced muscle hypertrophy remains largely unexplored. Here, we utilized six weeks of blood flow restricted resistance exercise (BFRRE) to study cellular adaptations within the muscle microenvironment accompanying muscle hypertrophy in healthy older individuals. Using flow cytometry, we characterized global changes of key cell populations within the skeletal muscle microenvironment, including FAPs, muscle stem cells (MuSCs), and immune cells. BFRRE induced significant enlargement of both FAPs and MuSCs, consistent with cellular adaptation to exercise. Notably, exercise shifted the FAP pool toward an increased predominance of the CD90high FAP phenotype, without altering total FAP abundance. In addition to matrix and collagen-related genes, transcriptional analysis of genes associated with secretory proteins revealed enrichment of promyogenic factors in CD90high versus CD90low FAPs. Conditioned media experiments of freshly isolated FAPs demonstrated that CD90high FAPs promote myotube growth in vitro compared to CD90low counterparts, suggesting that this phenotypic shift may facilitate muscle hypertrophy. In parallel, BFRRE increased the proportion of pro-inflammatory (CD11c+) macrophages within the skeletal muscle niche, highlighting a dynamic immune response during adaptation. Finally, we show identified possible link between pro-inflammatory macrophages and FAPs, as TNF markedly reduced the proliferation of human primary FAPs ex vivo, suggesting that macrophage-derived signals may attenuate excessive FAP expansion during tissue remodelling. Together, these findings provide new insight into how the remodelling of the cellular niche may support muscle hypertrophy in response to exercise. The coordinated expansion and phenotypic remodeling of FAP and immune cell populations may represent an important mechanism through which exercise supports hypertrophy in older individuals.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Age-related changes in human skeletal muscle transcriptome and proteome are moreaffected by chronic inflammation and physical inactivity than primary aging 95%
- Delineating the relationship between immune system aging and myogenesis in muscle repair 94%
- Lipidomic Profiling Reveals an Age-Related Deficiency of Skeletal Muscle Proresolving Mediators that Contributes to Maladaptive Tissue Remodeling 94%
Similar papers in this journal
- Hallmarks of frailty and osteosarcopenia in prematurely aged PolgAD257A/D257A mice 94%
- Transcriptomic analysis of aging mouse sciatic nerve reveals early pathways leading to sarcopenia 93%
- Different outcomes of endurance and resistance exercise in skeletal muscles of Oculopharyngeal muscular dystrophy. 93%
Similar papers in this journal
- Disrupting the Feed-Forward Cycle of RyR1 Calcium Leak and Oxidative Stress Mitigates Doxorubicin-Induced Skeletal Myopathy 90%
- Unconventional myosin VI is involved in the regulation of muscle energy metabolism 90%
- Engineering of human myotubes toward a mature metabolic and contractile phenotype 90%
Similar papers in this journal
- Age and Sex-Specific Changes in Mitochondrial Quality Control in Skeletal and Cardiac Muscle 93%
- Endurance Exercise to Improve Physical Function in Adult and Older Mice: High Intensity Interval Training (HIIT) versus Voluntary Wheel Running (VWR) 91%
- Unveiling Frailty: Comprehensive and Sex-Specific Characterization in Prematurely Aging PolgA Mice 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.