Sarcopenia is among the most common musculoskeletal illnesses, yet its underlying biochemical mechanisms remain incompletely understood. In this study, we used Mendelian randomization (MR) to investigate the causal relationship between the genetically determined blood metabolites and sarcopenia, with the overall objective of identifying likely molecular pathways for sarcopenia. We used two-sample MR to investigate the effects of blood metabolites on sarcopenia-related traits. 452 metabolites were exposure, and three sarcopenia-related traits as the outcomes: hand-grip strength, appendicular lean mass, and walking pace. The inverse-variance weighted (IVW) causal estimates were determined. For sensitivity analysis, methods such as MR-Egger regression, the weighted median, the weighted mode, and the heterogeneity test were used. Additionally, for complementation, we performed replication, meta-analysis, and metabolic pathway analyses. Candidate biomarkers were defined by meeting one of the following criteria: (1) Significant metabolites are defined as Pivw<PBonferroni [1.11 × 10−4 (0.05/452)]; (2)Strong metabolites are defined as four MR methods P < 0.05; (3)Suggestive metabolites are defined as passing sensitivity analysis. Three metabolites (creatine, 1-arachidonoylglycerophosphocholine, and pentadecanoate [15:0]) with significant causality, three metabolites (glycine, 1-arachidonoylglycerophosphocholine, and epiandrosterone sulfate) with strong causality, and 25 metabolites (including leucylleucin, pyruvic acid, etc.) with suggestive causality were associated with sarcopenia-related traits. After further replication analyses and meta-analysis, these metabolites maintained substantial effects on sarcopenia-related traits. We additionally identified 14 important sarcopenia-related trait metabolic pathways. By combining metabolomics with genomics, these candidate metabolites and metabolic pathways identified in our study may provide new clues regarding the mechanisms underlying sarcopenia.

中文翻译：

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全代谢组孟德尔随机化评估血液代谢物与肌肉减少症相关特征之间的因果关系

肌肉减少症是最常见的肌肉骨骼疾病之一，但其潜在的生化机制仍不完全清楚。在这项研究中，我们使用孟德尔随机化（MR）来研究基因决定的血液代谢物与肌肉减少症之间的因果关系，总体目标是确定肌肉减少症的可能分子途径。我们使用两样本 MR 来研究血液代谢物对肌肉减少症相关特征的影响。暴露了 452 种代谢物，并以三种与肌肉减少症相关的特征作为结果：握力、四肢瘦肉质量和步行速度。确定了逆方差加权（IVW）因果估计。敏感性分析采用MR-Egger回归、加权中位数、加权众数、异质性检验等方法。此外，为了补充，我们进行了复制、荟萃分析和代谢途径分析。通过满足以下标准之一来定义候选生物标志物：(1)显着代谢物定义为Pivw＜PBonferroni[1.11×10−4(0.05/452)]；(2)强代谢物定义为四种MR方法P＜0。0.05；(3)建议代谢物定义为通过敏感性分析。3个具有显着因果关系的代谢物（肌酸、1-花生四烯酰甘油磷酸胆碱和十五烷酸[15:0]），3个具有强因果关系的代谢物（甘氨酸、1-花生四烯酰甘油磷酸胆碱和硫酸表雄酮），以及25个代谢物（包括亮氨酰亮氨酸、丙酮酸等）。 ）具有暗示因果关系与肌肉减少症相关特征相关。经过进一步的复制分析和荟萃分析，这些代谢物对肌肉减少症相关性状保持了实质性影响。我们还确定了 14 条重要的肌少症相关性状代谢途径。通过将代谢组学与基因组学相结合，我们的研究中确定的这些候选代谢物和代谢途径可能会提供有关肌肉减少症潜在机制的新线索。