Identification And Functional Characterization Of Metabolites For Skeletal Muscle Mass In Early Postmenopausal Chinese Women

Background:Sarcopenia is characterized by age-related loss of skeletal muscle mass,strength,and physical performance,leading to a substantially increased risk of fractures,frailty,and mortality.Low skeletal muscle mass is a key component of the sarcopenia phenotypes.One of the most striking phenomena marking women’s aging process is menopause,typically accompanied by relatively rapid metabolism and endocrine changes,which were associated with decreased skeletal muscle mass in women.Previous metabolomics studies showed a close relationship between metabolites and sarcopenia,but are still rather limited.Previous studies on sarcopenia have mostly been conducted in the elderly population,and there is a lack of evidence from relatively young populations(especially in early postmenopausal women),making it difficult to capture disease-related early biomarkers.In addition,results from these previous studies were largely inconsistent in their significant findings,partially because different studies used different skeletal muscle indexes.Moreover,most of these previous studies did not provide an in-depth investigation into the potential mechanisms of the significant metabolites on skeletal muscle mass variation,resulting in a waste of relevant biological information.Objective:To address the questions and the gap in knowledge stated above,we performed untargeted serum metabolomics analysis,combined with whole genome sequencing and transcriptome sequencing technology and in vitro molecular experiments to identify serum metabolites associated with skeletal muscle mass variation in early postmenopausal Chinese women,and explore the potential mechanisms of significant metabolites on skeletal muscle mass variation.Methods:1.This study recruited 430 early postmenopausal Chinese women in Guangzhou,Guangdong,China.Basic information such as age,menopause time,height,and weight were collected.Dual-energy x-ray absorptiometry(DXA)was used to measure skeletal muscle mass.2.We investigated the proportion of low skeletal muscle mass in early menopausal women in Guangzhou,Guangdong,China.3.Based on liquid chromatography-mass spectrometry,the serum metabolic profiles of 430 early postmenopausal Chinese women were established through untargeted metabolomic information detection.4.We used partial least square(PLS)regression model and multiple linear regression model to identify serum metabolites associated with skeletal muscle mass variation.Metabolites with variable importance in projection(VIP)values greater than 1.5 in the PLS regression model and P value less than 0.05 in the multiple linear regression model were considered statistically significant.5.We performed a genome-wide association analysis of skeletal muscle mass indexes and significant metabolites based on whole-genome sequencing data of 412 early postmenopausal Chinese women.And,the causal effect of significant metabolite on skeletal muscle mass variation was inferred using one-sample Mendelian randomization(MR)analysis.6.The effects of significant metabolite on myoblast differentiation in vitro were observed from the phenotype,protein level,and transcript level by immunofluorescence technique,Western Blot technique,and Q-PCR technique,respectively.7.We performed transcriptomic sequencing of cells in the middle and end stages of myoblast differentiation and used bioinformatics analysis methods and in vitro molecular experiments to explore the potential mechanisms of significant metabolite on myoblast differentiation.Results:1.Untargeted metabolomic analysis results:(1)A total of 295 untargeted metabolic variables with known identities in the 430 early postmenopausal Chinese women,including 142 in positive ion mode and 153 in negative ion mode.(2)20.7%of early postmenopausal Chinese women have low skeletal muscle mass in Guangzhou,Guangdong,China.(3)In the present study,we identified 65 serum metabolites were associated with skeletal muscle mass variation using PLS and multiple linear regression models(VIP>1.5 and P<0.05),including 23 serum metabolites were associated with absolute skeletal muscle mass,21 metabolites were associated with body mass index-adjusted skeletal muscle mass,and 37 metabolites were associated with height2-adjusted skeletal muscle mass,and 26 metabolites were associated with body weight-adjusted skeletal muscle mass.The species and quantities of metabolites associated with different skeletal muscle mass indexes were quite different.(4)Enrichment analysis results showed that 20 skeletal muscle mass-associated serum metabolites were significantly enriched in eight metabolic pathways,five of which were related to fatty acid metabolism.(5)It is worth noting that stearic acid was negatively associated with all four skeletal muscle mass indexes(VIP>1.5 and P<0.05).And further one-sample MR analysis showed that stearic acid might be a risk factor for decreased skeletal muscle mass in early postmenopausal Chinese women.2.Experimental verification results:(1)In vitro experiments showed that stearic acid inhibited the length and diameter of myotubes at both the middle and end stages of myoblast differentiation.(2)Stearic acid inhibited the expression of myogenic factors(MyoD,MyoG,and MyHC)at the mRNA level during the differentiation of C2C12 myoblasts.(3)Stearic acid inhibited the expression of myogenic factors(MyoD,MyoG,and MyHC)at the protein level during the differentiation of C2C12 myoblasts.3.Transcriptomic bioinformatics analysis results:(1)Stearic acid affected 1329 genes significantly expressed at the mRNA level(fold change ≥2)of C2C12 myoblasts,382 genes were significantly expressed in both middle and end differentiation stages,109 were upregulated and 273 were down-regulated.(2)1329 significant genes were clustered into 6 modules,and the biological processes involved in each module were related to myoblast differentiation or function.For example,modules 1 and 2 were related to cell migration.(3)The further wound healing experiment showed that stearic acid significantly inhibited the migration of myoblasts.(4)Stearic acid inhibited the expression of myoblast migration and adhesion-related genes Actb,Ctnnbl,Egfr,Ptk2,and Rac1 at the mRNA level,or/and enhances the expression of Fyn at the mRNA level.Conclusions:1.Based on untargeted metabolomics,this study found that skeletal muscle mass variation was closely related to serum metabolic levels in early postmenopausal Chinese women.2.Elevated circulation stearic acid level is a risk factor for sarcopenia in early postmenopausal Chinese women.3.Stearic acid might affect skeletal muscle mass by inhibiting the release of myoblast factors(MyoD,MyoG,and MyHC)and regulating the migration,adhesion,fusion,and development of myoblasts.4.These findings provide new insights into our understanding of the causes and mechanisms of sarcopenia in early postmenopausal Chinese women and provide new potential targets for the prevention,diagnosis,and treatment of sarcopenia.