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Causal Relationship Between Circulating Metabolites and Sarcopenia-Related Traits: A Mendelian Randomization and
Weihui Qi1,2,3, Xinning Mao1, Zhenglin Mei1
1Department of Orthopaedics Hangzhou Traditional Chinese Medicine Hospital Affiliated to Zhejiang Chinese Medical University Hangzhou China.
This study reveals causal links between specific metabolites, like glycine, and sarcopenia (SP), a condition of age-related muscle loss. These findings highlight potential biomarkers for early detection and intervention strategies for sarcopenia.
Area of Science:
- Metabolomics
- Gerontology
- Genetics
Background:
- Sarcopenia (SP) is linked to metabolic factors, but causal relationships and pathways are unclear.
- Understanding these links is crucial for developing interventions for age-related muscle loss.
Purpose of the Study:
- To investigate causal associations between serum metabolites and sarcopenia using Mendelian randomization (MR).
- To identify biological signaling pathways involved in the metabolite-sarcopenia connection.
- To explore metabolite expression in an animal model of sarcopenia.
Main Methods:
- Bidirectional two-sample Mendelian randomization (MR) analysis of 1091 metabolite levels and 309 ratios with SP traits.
- Analysis of differential plasma metabolite expression and signaling pathways in an animal model.
- Bonferroni's correction and multiple contrast correction for statistical significance.
Main Results:
- Identified 11 robust causal associations between seven metabolite levels/ratios and SP traits.
- Validated a stable causal association between glycine levels and SP.
- Reverse MR analysis revealed 11 strong causal relationships between plasma metabolites and SP.
- Pathway analysis implicated glycine metabolism, insulin resistance, and cAMP signaling.
Conclusions:
- Glycine metabolism is strongly associated with sarcopenia, supported by MR and animal model data.
- Identified metabolites and pathways can serve as biomarkers for sarcopenia screening and prevention.
- These findings offer potential targets for future mechanism exploration and drug development.
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