Role of Peptides in Skeletal Muscle Wasting: A Scoping Review
Petar Naumovski et al. J Cachexia Sarcopenia Muscle. 2025 Dec.
Abstract
Background: Systemic muscle wasting is a prevalent condition that predicts adverse health outcomes in aging and disease. Despite its clinical relevance, the development of predictive biomarkers and effective pharmacological therapies remains limited. Peptides have recently gained attention for their diverse bioactive functions, positioning them as promising biomarkers and therapeutic agents for muscle wasting.
Methods: This scoping review systematically identifies studies examining the direct association between well-defined peptides and clinical components of muscle wasting: muscle mass, strength and physical performance. The review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analysis for Scoping Reviews (PRISMA-ScR) guidelines. A comprehensive search of Embase, PubMed and Web of Science was conducted up to 31 October 2024, focusing on original human or animal studies. Studies involving congenital or inherited muscle disorders, inflammatory myopathies and neurodegenerative diseases, such as Parkinson's disease, were excluded. A snowball approach was used to synthesize the presumed cellular pathways of identified peptides.
Results: A total of 126 studies were included: 71 (56.3%) focused on a single muscle wasting component (48 on mass, 16 on strength and 7 on performance), 31 (24.6%) examined two, 16 (12.7%) analysed all three separately, and 8 (6.3%) assessed sarcopenia as a categorical variable. Eighty-seven distinct peptides linked to muscle wasting were identified, ranging from collagen tripeptide (3 amino acids) to insulin (51 amino acids). The most studied peptides are ghrelin (14.3%), brain natriuretic peptide (BNP, 11.1%), C-peptide (11.1%), insulin (10.3%) and Szeto-Schiller 31 (SS-31, 6.3%). Most (62.1%) influence one or more of four key muscle homeostasis pathways (PI3K/Akt/mTOR, ActR/SMAD, IKK/NF-κB and AMPK/PGC1α), which regulate atrophy (via FOXO, NF-κB, SMAD2/3, glucocorticoid receptor and GSK-3β) and hypertrophy (via androgen receptors, PGC-1α and S6K). Flaws in study design and reporting were prevalent, hindering clinical translation. Sex bias was evident, with females comprising 23.9% of participants in human interventional studies and only 9.1% and 12.4% of mice and rats in rodent studies, respectively. Clinical, pre-analytical and analytical reporting gaps were common: 56.6% documented diurnal timing, food intake and activity around peptide collection; none specified storage-to-analysis duration; and only 11.5% reported detection limits for peptide measurements.
Conclusion: This scoping review highlights the potential of peptides as biomarkers and intervention targets for muscle wasting. It connects the cellular receptors and signaling pathways linking peptides with skeletal muscle wasting. Improving clinical translation requires addressing study design limitations, incorporating more representative study populations and adhering to standardized reporting guidelines. The application of machine learning can support the identification of novel bioactive peptides.
Keywords: cachexia; muscle wasting; peptides; sarcopenia.
© 2025 The Author(s). Journal of Cachexia, Sarcopenia and Muscle published by Wiley Periodicals LLC.
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Conflict of interest statement
The authors declare no conflicts of interest.
Figures FIGURE 1
Preferred Reporting Items for Systematic Review and Meta‐Analysis (PRISMA) flow diagram for publication screening. FIGURE 2
General characteristics of the included studies. (A) Distribution of studies according to the countries in which the study was conducted. (B) Bar graph showing the exponential growth in the number of studies per year (fitted function in blue). (C) Donut chart illustrating the distribution of study design types. The inner circle shows the overall number of human, animal and mixed studies, whereas the outer circle shows the specific study design or animal order/genus for human and animal studies, respectively. FIGURE 3
Graphical summary of the population characteristics (A) Bar graph showing the distribution of population age across human studies (y‐axis: number of studies). (B) Bar graph showing the distribution of the population age across rat and mouse studies (y‐axis: number of studies). (C) Bar graph depicting the distribution of sexes across human studies and animal models. (D) Heat map illustrating the human population characteristics including various clinical conditions in which distinct skeletal muscle clinical endpoints were measured (Low values: blue, high values: red). Sarcopenia diagnosis was based on EWGSOP 1/2 or AWGS criteria. Separate outcome components used to diagnose sarcopenia are also included in the numbers. ASMM includes both measurements normalized and not normalized to height squared (ASMI). ASMM: appendicular skeletal muscle mass, CABG: coronary artery bypass graft, CF: cystic fibrosis, CHF: chronic heart failure: CKD: chronic kidney disease, COPD: chronic obstructive pulmonary disease, HGS: handgrip strength, NAFLD: non‐alcoholic fatty liver disease, SBS: short bowel syndrome, SPPB: short physical performance battery, T2DM: Type 2 diabetes mellitus, TUG: Time Up and Go. (E) Heat map illustrating the various preclinical population characteristics and species in which distinct skeletal muscle clinical endpoints were measured (low values: blue, high values: red). Mass endpoints include measurements both normalized and not normalized to body weight. When forelimb/hindlimb or 4‐limb grip strength was not specified in the study, measurements were considered as four‐limb grip strength. Stimulated strength was measured on either one or more of the individual muscles stated under muscle mass and/or the diaphragm. CKD: chronic kidney disease, D‐gal: D‐galactose, HFD; high‐fat diet, MI: myocardial infarction, NI: no intervention, OA: osteoarthritis, SCI: sciatic nerve injury, WT: wild type. FIGURE 4
Bar graph showing the proportion of studies in which important pre‐analytical and analytical operating modalities of peptide analysis were reported. FIGURE 5
Peptide‐mediated cellular pathways in skeletal muscle. This schematic provides a comprehensive overview of peptide‐regulated signalling pathways in skeletal muscle, summarizing current knowledge from the literature on how peptides influence muscle cell state and fate. The diagram is structured into three major sections: the myofibre, the adjacent extramuscular region, and distant regions, including the central nervous system and gut microbiota, which are highlighted in yellow light. Peptides are colour‐coded based on their overall effect, with green representing peptides associated with muscle hypertrophy, red indicating peptides linked to muscle atrophy, and grey denoting peptides with a neutral effect. Protein mediators are depicted in blue, small‐molecule mediators in light green, general homeostatic processes in light brown and general atrophy‐inducing processes in orange. Arrow‐tipped lines signify stimulation, whereas T‐shaped lines represent inhibition. Gene expression pathways that promote muscle hypertrophy are highlighted in green, whereas those driving muscle atrophy are marked in red. Certain intracellular factors are duplicated for clarity and are underlined to indicate their repeated appearance.
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