| Backgrounds and Objectives:With the rapid development of economy and society,the living standard of human beings is improving day by day,and the trend of chronic diseases is becoming more and more serious.The trend of younger age of dyslipidemia has continuously,rapidly and significantly increased the risk of cardiovascular disease worldwide,posing a major challenge to public health systems.As a key developmental period,the transition period from adolescence to early adulthood is a period of great changes in lifestyle.During the transition period,the tendency of young people to adopt unhealthy behaviors will increase,which is conducive to the development of obesity and further leads to the formation of unhealthy behaviors affecting cardiovascular health.Therefore,the transitional age may be a critical period for cardiovascular health protection and prevention of cardiovascular diseases,and how to detect and effectively prevent dyslipidemia as early as possible has become an important topic.Skeletal muscle plays an important role in the physiological activities related to human metabolism and endocrine system.Skeletal muscle can not only secrete a large amount of actin,regulate energy demand,but also have an important impact on cardiovascular metabolism.A number of studies have shown that the combination of skeletal muscle mass and fat mass can be used to evaluate body composition,which may more accurately evaluate body obesity,and is an effective evaluation index for metabolic syndrome and cardiovascular disease.At the same time,fatty acids and amino acids in human body can regulate or act as signal molecules to participate in the process of metabolism and protein synthesis in vivo,and affect the synthesis of muscle protein and the change of muscle mass,thus affecting the lipid metabolism of human body.However,most of the previous studies used cross-sectional studies,and mainly focused on the middle-aged and elderly population,with less attention to the transitional youth.In this study,we investigated the role of skeletal muscle mass and body composition in the development of dyslipidemia in transitional-age youth by using a prospective study design based on the college cohort of"Northwest Natural Population Cohort in Ningxia Project",in order to provide theoretical basis for the development of dyslipidemia screening methods and prevention guidelines for specific populations,and to provide theoretical support for the prevention and treatment of dyslipidemia.Additionally,based on the nested case-control study design,the relationship between the change of organic acid content in the body and the change of skeletal muscle mass was discussed from the perspective of muscle protein synthesis induced by the change of organic acid content.The purpose of this study is to provide theoretical basis for the prevention of dyslipidemia in transitional youth and to provide population evidence for the mechanism of dyslipidemia.Methods:Part I:The research participants of this project are selected from a sub-cohort data in"Northwest Region Natural Population Cohort-Ningxia Project".In September 2018,all students of Grade 2018 were selected from a university in Ningxia to establish a college student cohort,and the follow-up was completed in July 2021,with an average follow-up time of 2.75 years and a follow-up rate of 94.40%.Collect the general demographic characteristics,behavior and lifestyle,health and nutrition status,body composition,biochemical indicators and other information of the study subjects at baseline and follow-up,and collect biological samples for future research and analysis.In this study,logistic regression was used to analyze the risk of dyslipidemia at different FMR quantiles,and the receiver operating characteristic（ROC）was used to determine the cutoff value applicable to the diagnosis of dyslipidemia.In the longitudinal analysis,the generalized estimating equation（GEE）was used to explore the relationship between skeletal muscle mass and its changes and the risk of dyslipidemia.Part II Based on the prospective study in Part I,a nested case-control study design was adopted.Patients with dyslipidemia found during follow-up were taken as case group,and healthy controls without dyslipidemia were matched with propensity score method.The organic acid metabolites were determined by gas chromatographic-mass spectrometry（GC-MS）at baseline and follow-up.SIMCA 14.1 multivariate statistical analysis software was used for preliminary analysis of metabolomics data.Metabo Analyst 5.0 online software was used to analyze the metabolic pathways involved in the screened potential biomarkers,and the role of ASMI,FMI,and FMR in the relationship between key metabolites and dyslipidemia was further analyzed using the intermediary effect model.Results:Part I:A total of 1660 subjects were included in this study,including 558 males and 1102 females,with an average age of（19.06±1.14）years.There were significant differences in smoking,drinking and physical activity intensity between male and female subjects（P<0.001）.Men had higher weight,height,BMI and WC,and the differences were statistically significant compared with women（P<0.001）.In terms of blood biochemical indexes,men had higher TC,TG,FBG and lower HDL-C,and the difference was statistically significant compared with women（P<0.05）.Among them,the prevalence rate of dyslipidemia was 18.3%in men and 11.0%in women.Male body composition has higher skeletal muscle mass（SMM）,ASM,ASMI,ASM%and soft lean mass（SLM）and lower FM,FMI and FMR levels than female body composition,and the difference is statistically significant（P<0.001）.Logistic regression analysis was used to explore the relationship between FMR and dyslipidemia.After adjusting for potential confounding factors,taking the first quantile of male FMR as reference,the OR（95%CI）values of the second to fifth quantiles of FMR for dyslipidemia in male transitional-age youth were（OR:1.57,95%CI:0.61–4.03）、（OR:2.22,95%CI:0.90–5.46）、（OR:3.29,95%CI:1.39–7.81）and（OR:7.56,95%CI:3.29–17.38）,respectively,the change trend is statistically significant(χtrend2=51.445,P<0.001).The OR（95%CI）values of the second to the fifth quantiles of FMR for dyslipidemia in female transitional-age youth were（OR:0.74,95%CI:0.34–1.60）、（OR:1.26,95%CI:0.63–2.52）、（OR:1.45,95%CI:0.74–2.88）and（OR:3.04,95%CI:1.63–5.67）,the change trend is statistically significant(χtrend2=63.248,P<0.001).ROC curve was used to explore the diagnostic value of FMR for dyslipidemia,hypercholesterolemia and hypertriglyceridemia.The results showed that the cut-off values of FMR for the diagnosis of dyslipidemia,hypercholesterolemia and hypertriglyceridemia were 0.2224,0.2251 and 0.3294,respectively,for male transitional-age youth.The cut-off point values of FMR diagnosis of dyslipidemia,hypercholesterolemia,and hypertriglyceridemia were 0.4809,0.4826,and 0.6865,respectively,for female transitional-age youth.During the follow-up period of this study,293 transitional-age youth had new dyslipidemia,with a cumulative incidence of 17.65%.After the follow-up,the body weight,BMI,WC,LDL-C,TG,FBG,SMM,FM,FMI and FMR of the study subjects increased to varying degrees,while TC,HDL-C,ASM,ASMI and ASM%decreased significantly（P<0.001）.The relationship between baseline ASMI,FMI,FMR and relative changes of ASMI,FMI,FMR and the risk of dyslipidemia was observed with the incidence of dyslipidemia as the dependent variable.According to the quintile method,the ASMI,FMI and FMR of different gender subjects were grouped.GEE regression analysis showed that higher ASMI,FMI and FMR at baseline were the risk factors for the occurrence dyslipidemia,while the increase of female relative ASMI by more than 10%after follow-up was a risk factor for the occurrence dyslipidemia.There was no statistically significant relationship between the changes of relative FMI and FMR of male and female subjects and the risk of dyslipidemia（P>0.05）.Part II:A total of 480 subjects were included in the Nest case-control study design,including 240 in the case group and 240 in the control group.After follow-up,the overall weight,BMI,waist circumference,LDL-C,TG,FMI and FMR of transitional-age youth increased（P<0.05）,while TC,HDL-C and ASMI decreased（P<0.05）.After follow-up,the comparison of general conditions between the control group and the case group showed that the body weight,BMI,waist circumference,LDL-C,TG,FMI and FMR of the study subjects in the case group were higher than those in the control group,while the TC and HDL-C levels in the case group were lower than those in the control group,and the differences were statistically significant（P<0.05）.After the human serum metabolites were detected by GS-MS detection platform,multivariate statistical analysis was performed using SIMCA 14.1 software.After OPLS-DA model and logistic regression analysis,7 key different metabolites were found between the case group and the control group,which were:glycerol monostearate,arachidonic acid,alpha-linolenic acid,trans-oleic acid,glycerol,leucine and ethanolamine.Metabolic pathway analysis by Metabo Analyst 5.0 software revealed three potential metabolic pathways associated with dyslipidemia in young people in transition,namelyα-linolenic acid metabolism,arachidonic acid metabolism and glyceride metabolism.The comparative analysis of the key difference metabolites between the case group and the control group at baseline and follow-up showed that the levels of glycerol monostearate,α-linolenic acid,（E）-2-butenedioic acid,L-leucine and ethanolamine in the serum of the study subjects at baseline were higher in the control group than in the case group,while the levels of arachidonic acid were lower in the control group than in the case group,with a statistically significant difference（P<0.05）.After follow-up,the contents of monostearate glycerol,1-monopalmitrin and glycerol in the case group were higher than those in the control group,while the contents ofα-linolenic acid,（E）-2-butenedioic acid,L-leucine and ethanolamine were lower than those in the control group,with a statistically significant difference（P<0.05）.Correlation analysis showed thatα-linolenic acid,elaidic acid,glycerol were negatively correlated with ASMI（P<0.05）,glycerol monostearate,（E）-2-butenedioic acid,glycerol,L-leucine,ethanolamine were positively correlated with FMI（P<0.05）,glycerol monostearate,（E）-2-butenedioic acid,elaidic acid,glycerol,L-leucine,ethanolamine were positively correlated with FMR（P<0.05）.After follow-up,elaidic acid and L-leucine were positively correlated with ASMI（P<0.05）.Glycerol monostearate and glycerol were positively correlated with FMI（P<0.05）.Arachidonic acid and ethanolamine were positively correlated with FMI（P<0.05）.Glycerol monostearate and glycerol were positively correlated with FMR（P<0.05）.Arachidonic acid was positively correlated with FMR（P<0.05）.Mediation effect analysis was carried out with the significant key differential metabolites of correlation analysis as independent variables,the results showed that the mediation effect of baseline ASMI,FMI and FMR on the relationship between key differential metabolites and dyslipidemia components were not significant（P>0.05）.After follow-up,ASMI showed a complete mediating effect on the relationship between elaidic acid and TG,HDL-C（P<0.05）,and a partial mediating effect on the relationship between elaidic acid and LDL-C,with the mediating effect accounting for 50.00%.After follow-up,ASMI showed a complete mediating effect on the relationship between L-leucine and TG,LDL-C（P<0.05）,and a partial mediating effect on the relationship between L-leucine and HDL-C,with the mediating effect accounting for 29.41%.After follow-up,FMI was a complete mediator between glycerol monostearate and TC,TG,LDL-C（P<0.05）,and a partial mediator between glycerol monostearate and HDL-C,wuth the mediating effect accounting for 18.42%;FMI completely mediated the relationship between glycerol and TC,TG,HDL-C,LDL-C（P<0.05）;FMI also showed a complete mediating effect on the relationship between ethanolamine and TG,LDL-C（P<0.05）,and a partial mediating effect on the relationship between ethanolamine and TC,HDL-C,with the mediating effect accounting for 61.96%and 18.26%,respectively.Meanwhile,after follow-up,FMR showed a complete mediating effect on the relationship between glycerol monostearate and TC,TG,LDL-C（P<0.05）,and a partial mediating effect in the relationship between glycerol monostearate and HDL-C（9.21%）;FMR also showed a complete mediating effect on the relationship between glycerol and TC,TG,HDL-C,LDL-C（P<0.05）.Conclusion:Baseline FMR has good diagnostic value for dyslipidemia,hypercholesterolemia,and hypertriglyceridemia in transitional-age youth.In contrast,higher baseline ASMI,FMI,and FMR levels were associated with a higher risk of dyslipidemia in transitional age youth over time.Meanwhile,the risk of dyslipidemia was higher when the relative ASMI increased by more than 10%in women.The results of metabolomics analysis suggested that metabolites such as glycerol monostearate,arachidonic acid,α-linolenic acid,trans-oleic acid,glycerol,leucine and ethanolamine may be potential candidate markers for identifying the risk of dyslipidemia in young people in transition period,and their metabolic pathways may be mainlyα-linolenic acid metabolism,arachidonic acid metabolism and glyceride metabolism.At the same time,after follow-up,ASMI may play a role on the relationship between linoleic acid,leucine and TG,HDL-C,LDL-C;FMI plays a role on the relationship between monostearate glycerol,glycerol,ethanolamine and TC,TG,HDL-C,LDL-C;FMR plays a role on the relationship between monostearate glycerol,glycerol and TC,TG,HDL-C,LDL-C.Therefore,the key differential organic acid metabolites in serum can promote the changes of ASMI,FMI and FMR levels,which leads to the occurrence of dyslipidemia and the changes of lipid components in transitional-age youth. |
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