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Record W4409866028 · doi:10.3389/fcimb.2025.1480293

Comparison of the gut microbiota in older people with and without sarcopenia: a systematic review and meta-analysis

2025· review· en· W4409866028 on OpenAlexaboutno aff
Xiangfeng He, Ling Wang, Nan Chen

Bibliographic record

VenueFrontiers in Cellular and Infection Microbiology · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsSarcopeniaMeta-analysisGut floraOlder peopleSystematic reviewMedicineGerontologyBiologyPsychologyMEDLINEImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Introduction: Sarcopenia, an age-related disorder marked by decreased skeletal muscle mass, strength, and function, is associated with negative health impacts in individuals and financial burdens on families and society. Studies have suggested that age-related alterations in gut microbiota may contribute to the development of sarcopenia in older people through the gut-muscle axis, thus modulation of gut microbiota may be a promising approach for sarcopenia treatment. However, the characteristic gut microbiota for sarcopenia has not been consistent across studies. Therefore, the aim of this study was to compare the diversity and compositional differences in the gut microbiota of older people with and without sarcopenia, and to identify gut microbiota biomarkers with therapeutic potential for sarcopenia. Methods: The PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, and Wanfang Database were searched studies about the gut microbiota characteristics in older people with sarcopenia. The quality of included articles was assessed by the Newcastle-Ottawa Scale (NOS). Weighted standardized mean differences (SMDs) and 95% confidence intervals (CIs) for α-diversity index were estimated using a random effects model. Qualitative synthesis was conducted for β-diversity and the correlation between gut microbiota and muscle parameters. The relative abundance of the gut microbiota was analyzed quantitatively and qualitatively, respectively. Results: Pooled estimates showed that α-diversity was significantly lower in older people with sarcopenia (SMD: -0.41, 95% CI: -0.57 to -0.26, I²: 71%, P < 0.00001). The findings of β-diversity varied across included studies. In addition, our study identified gut microbiota showing a potential and negative correlation with sarcopenia, such as Prevotella, Slackia, Agathobacter, Alloprevotella, Prevotella copri, Prevotellaceae sp., Bacteroides coprophilus, Mitsuokella multacida, Bacteroides massiliensis, Bacteroides coprocola Conversely, a potential and positive correlation was observed with opportunistic pathogens like Escherichia-Shigella, Eggerthella, Eggerthella lenta and Collinsella aerofaciens. Discussion: This study showed that α-diversity is decreased in sarcopenia, probably predominantly due to diminished richness rather than evenness. In addition, although findings of β-diversity varied across included studies, the overall trend toward a decrease in SCFAs-producing bacteria and an increase in conditionally pathogenic bacteria. This study provides new ideas for targeting the gut microbiota for the prevention and treatment of sarcopenia. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD42024573090, identifier CRD42024573090.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.023
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.026
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0230.031
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.312
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2025
Admission routes1
Has abstractyes

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