Introduction: There is growing evidence of research indicating that the gut microbiota is involved in the development of sarcopenia. Nevertheless, there exists a notable deficiency in comprehension concerning the connection between irregularities in the intestinal microbiome and metabolic processes in older individuals suffering from sarcopenia.Methods: To analyze fecal samples obtained from a cohort of 30 older patients diagnosed with sarcopenia as well as 30 older patients without sarcopenia, this study employed 16S rDNA sequencing and liquid chromatography-mass spectrometry (LC-MS)-based non-targeted metabolomics profiling techniques.Results: As a result, we found that 29 genera and 172 metabolites were significantly altered in the sarcopenic patients. Among them, Blautia, Lachnospiraceae_unclassified, and Subdoligranulum were the bacteria with a potential diagnostic value for sarcopenia diagnosis. Correlation analysis between clinical indices and these gut bacteria suggested that the IL-6 level was negatively correlated with Blautia. Function prediction analysis demonstrated that 17 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways differ significantly between sarcopenic and non-sarcopenic patients. The primary classes of metabolites identified in the study included lipids and lipid-like molecules, organic acids and derivatives, and organoheterocyclic compounds. KEGG enrichment analysis showed that purine metabolism, arginine and proline metabolism, alanine, aspartate, and glutamate metabolism, butanoate metabolism, and histidine metabolism may contribute to the development of sarcopenia. The correlation study on gut microbiota and metabolites found that Lachnospiraceae_unclassified was positively associated with seven metabolites that were more abundant in the non-sarcopenia group and negatively correlated with three metabolites that were more abundant in the sarcopenia group. In addition, Subdoligranulum was positively correlated with seven metabolites that were lacking in sarcopenia and negatively correlated with two metabolites that were enriching in sarcopenia. Moreover, Blautia was positively associated with xanthosine.Discussion: We conducted a study on the intestinal microbiota and metabolic profile of elderly individuals with sarcopenia, offering a comprehensive analysis of the overall ecosystem. Through this investigation, we were able to validate existing research on the gut–muscle axis and further investigate potential pathogenic processes and treatment options for sarcopenia.

Background: Various biomarkers associated with sarcopenia have been identified. However, there is a scarcity of studies exploring and validating biomarkers in individuals with age-related sarcopenia. Aims: This study aimed to investigate the proteome and identify potential biomarkers for age-related sarcopenia. Methods: Proteomic analysis and experimental validation were conducted using plasma from hospitalized older adults. Sarcopenia diagnosis was based on the Asian Working Group for Sarcopenia 2019 criteria. Data-independent acquisition-based proteomics was performed on plasma from 60 participants, with 30 diagnosed with sarcopenia and 30 without sarcopenia. Differentially expressed proteins (DEPs) were selected and evaluated by Receiver Operating Characteristic (ROC) analysis. Biomarker candidates were further quantitatively validated by enzyme-linked immunosorbent assay (ELISA) utilizing plasma from 6 participants with sarcopenia and 6 without sarcopenia. Results: A total of 39 DEPs were identified and 12 DEPs were selected for ROC analysis. 8 DEPs were included for ELISA validation based on their predictive performance. Paraoxonase-3 (PON3) consistently showed down-regulation in the sarcopenic group across both methodologies. Insulin-like growth factor-binding protein-2 (IGFBP2) showed inconsistency in the sarcopenic group, with up-regulation observed in proteomic analysis but down-regulation in ELISA. Discussion: Decline in PON3 may result in an overload of oxidative stress in skeletal muscles and contribute to sarcopenia. Protein modifications of IGFBP2 might exhibit during sarcopenia pathogenesis. Conclusions: Plasma proteins are implicated in sarcopenia pathogenesis. PON3 is highlighted as a potential biomarker for patients with age-related sarcopenia. Further studies are imperative to gain an in-depth understanding of PON3 and IGFBP2.