Gut Dysbiosis and Muscle Aging: Searching for Novel Targets against Sarcopenia
Open accessAbstract
Advanced age is characterized by several changes, one of which is the impairment of the homeostasis of intestinal microbiota. These alterations critically influence host health and have been associated with morbidity and mortality in older adults. “Inflammaging,” an age-related chronic inflammatory process, is a common trait of several conditions, including sarcopenia. Interestingly, imbalanced intestinal microbial community has been suggested to contribute to inflammaging. Changes in gut microbiota accompanying sarcopenia may be attenuated by supplementation with pre- and probiotics. Although muscle aging has been increasingly recognized as a biomarker of aging, the pathophysiology of sarcopenia is to date only partially appreciated. Due to its development in the context of the age-related inflammatory milieu, several studies favor the hypothesis of a tight connection between sarcopenia and inflammaging. However, conclusive evidence describing the signaling pathways involved has not yet been produced. Here, we review the current knowledge of the changes in intestinal microbiota that occur in advanced age with a special emphasis on findings supporting the idea of a modulation of muscle physiology through alterations in gut microbial composition and activity.
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Dysbiosis seems more severe in conditions with increasing prevalence with ageing, such as obesity and type 2 diabetes.
“Dysbiosis seems to be more severe in conditions in which prevalence increases with ageing, such as obesity and type 2 diabetes73.”
From Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty (2018) · cites this paper as [73]
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Flagged first, then by citations
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- Authors
- Picca, A., Fanelli, F., Calvani, R., Mulè, G., Pesce, V., Sisto, A., Pantanelli, C., Bernabei, R., Landi, F., & Marzetti, E.
- Affiliations
- Università Cattolica del Sacro Cuore (IT)
- Institute of Sciences of Food Production (IT)
- University of Bari Aldo Moro (IT)
- Corresponding author
- Calvani, Riccardo
- ORCID
- Venue
- Mediators of Inflammation
- Publisher
- Wiley
- Published
- 2018
- Volume
- 2018
- Pages
- 1-15
- ISSN
- 0962-9351 (ISSN-L)
- 1466-1861
- PMC
- PMC5893006
- OpenAlex
- W2786077795
- Cited by
- 181
- References
- 196
- Citations by year
- 2026: 23 · 2025: 14 · 2024: 27 · 2023: 31 · 2022: 25 · 2021: 22 · 2020: 18 · 2019: 15 · 2018: 6
- FWCI
- 2.01
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Mediators of Inflammation (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- PubliCatt (Università Cattolica del Sacro Cuore) (submittedVersion, other-oa)
- CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro) (submittedVersion, cc-by-nc-nd)
- Funders
- Centro Studi Achille e Linda Lorenzon (D3.2 2013, D3.2 2015, 115621)
- Catholic University of the Sacred Heart (D3.2 2013, D3.2 2015, 115621)
- Innovative Medicine Initiative-Joint Undertaking (D3.2 2013, D3.2 2015, 115621)
- Fondazione Roma (D3.2 2013, D3.2 2015, 115621)
- Topics
- Health Sciences › Medicine › Physiology › Nutrition and Health in Aging
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Muscle Physiology and Disorders
- Keywords
- gut dysbiosis, muscle aging, sarcopenia, inflammaging, gut microbiota, aging, prebiotics, probiotics, chronic inflammation, older adults, muscle physiology
- MeSH terms
- Gastrointestinal Microbiome, Aging, Animals, Humans, Intestines, Muscles, Sarcopenia, Dysbiosis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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