Identification and Functional Characterization of Metabolites for Skeletal Muscle Mass in Early Postmenopausal Chinese Women.

Low skeletal muscle mass (SMM) is a crucial component of the sarcopenia phenotypes. In present study, we aim to identify the specific metabolites associated with SMM variation and their functional mechanisms of decreased SMM in early postmenopausal women. We performed an untargeted metabolomics analysis in 430 early postmenopausal women to identify specific metabolite associated with skeletal muscle mass indexes (SMIes). Then, the potential causal effect of specific metabolite on SMM variation was accessed by one sample Mendelian randomization (MR) analysis. Finally, in vitro experiments and transcriptomics bioinformatics analysis were conducted to explore the impact and potential functional mechanisms of specific metabolite on SMM variation. We detected 65 metabolites significantly associated with at least one SMI [variable importance in projection (VIP) > 1.5 by partial least squares regression and p-values < 0.05 in multiple linear regression analysis]. Remarkably, stearic acid (SA) was negatively associated with all SMIes, and subsequent MR analyses showed that increased serum SA level had a causal effect on decreased SMM (p-values < 0.05). Further in vitro experiments showed that SA could repress myoblast's differentiation at mRNA, protein, and phenotype levels. By combining transcriptome bioinformatics analysis, our study supports that SA may inhibit myoblasts differentiation and myotube development by regulating the migration, adhesion, and fusion of myoblasts. This metabolomics study revealed specific metabolic profiles associated with decreased SMM in postmenopausal women, firstly highlighted the importance of SA in regulating SMM variation, and illustrated its potential mechanism on decreased SMM.