Diabetology & Metabolic Syndrome (Sep 2024)

Lipid metabolites and sarcopenia-related traits: a Mendelian randomization study

  • Jianping Liu,
  • Sufang Wang,
  • Yuan Shen,
  • Haicun Shi,
  • Lijian Han

DOI
https://doi.org/10.1186/s13098-024-01465-y
Journal volume & issue
Vol. 16, no. 1
pp. 1 – 9

Abstract

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Abstract Objective To explore the influence of lipid metabolism on the risk of sarcopenia. Methods Two-sample Mendelian randomization (MR) analysis was used to determine causality. A total of 179 lipid metabolism data points were used for exposure, and the data were obtained from a plasma lipid metabolite study of 7174 participants. The total muscle mass and total muscle strength, as well as the muscle strength and muscle mass of different sex groups, were selected as the relevant traits of sarcopenia. Data for outcomes were obtained from the UK Biobank, and sample sizes ranged from 135 468 to 450 243. Inverse-variance weighted (IVW), as the main method for evaluating the causal relationship between lipid metabolites and sarcopenia, uses the false discovery rate (FDR) for multiple comparisons and conducts heterogeneity, pleiotropy, and reverse causality tests. Results Twenty-seven lipid metabolites, mainly phosphatidylcholine, phosphatidylethanolamine, ceramide, triacylglycerol, sphingomyelin, and sterol ester, were found to be associated with the risk of sarcopenia. Ceramide (d40:1), ceramide (d40:2), and sterol ester are risk factors for decreased muscle mass and strength. There is a positive causal relationship between various phosphatidylcholine lipids and muscle mass and strength. Sphingomyelin (d42:2) is a protective factor for total muscle strength and female muscle strength. There are inconsistent effects between different lipid metabolites, triacylglycerol, and muscle strength and muscle mass. Conclusions There was a causal relationship between 27 lipid metabolites and sarcopenia traits, and targeting specific lipid metabolites may benefit sarcopenia diagnosis, disease assessment, and treatment.

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