Search

ObjectiveTo explore the correlation between skeletal muscle mass and metabolic syndrome （MS） disease risk among middle-aged and elderly community residents in Urumqi， and to provide a theoretical basis for understanding the relationship between skeletal muscle mass and MS among middle-aged and elderly community residents in China.MethodsA total of 1 438 community residents ≥ 50 years old were selected as the research subjects from July 2018 to January 2019 in Urumqi. They were selected from a multi-ethnic natural population cohort in Xinjiang. Data were collected through questionnaires， physical examination， bioelectrical impedance analysis （BIA）， laboratory tests， etc. Skeletal muscle mass was evaluated using the limb skeletal muscle mass index （SMI） corrected for body weight； MS was defined as it at least includes three of the following： abdominal obesity， hypertension， hyperglycemia， high triglycerides and low high-density lipoprotein cholesterol. SMI was divided into four quantile arrays of Q1‒Q4. Trend χ2 test was applied to explore whether there was a correlation between SMI changes and MS. A multivariate logistic regression model was used to analyze whether there is a difference in the risk of MS between the higher SMI group （Q2， Q3， Q4） and the reference group Q1.ResultA total of 560 MS patients were detected in this study， with a prevalence rate of 38.94%. Among them， the prevalence rate of MS was 39.16% in males and 38.80% in females. The increase in male SMI grading level is not correlated with the prevalence of MS （trend P>0.05）； After adjusting for confounding factors （model 4）， the increase in SMI was still not related to the prevalence of MS （Ptrend=0.995）. There was no statistical difference in the risk of MS between the lowest quartile group Q1 and the highest quartile group Q4 （OR=1.01， 95%CI： 0.69‒1.78）. The prevalence of MS in women gradually decreased with the increase of SMI grading level （Ptrend

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 2-sample MR to investigate the effects of blood metabolites on sarcopenia-related traits. 452 metabolites were exposure, and 3 sarcopenia-related traits as the outcomes: handgrip 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 p IVW <  p Bonferroni [1.11 × 10−4 (.05/452)]; (2) strong metabolites are defined as 4 MR methods p  < .05; and (3) suggestive metabolites are defined as passing sensitivity analysis. Three metabolites (creatine, 1-arachidonoylglycerophosphocholine, and pentadecanoate [15:0]) with significant causality, 3 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. [ABSTRACT FROM AUTHOR]

Background: Observational studies have shown that micronutrients can affect the occurrence of frailty. However, it is not clear whether there is a causal relationship between the two. This study aimed to explore the causal relationship between circulating micronutrient levels and frailty risk using a two-sample Mendelian randomization (TSMR) approach., Methods: We gathered and screened instrumental variables (IVs) for six circulating micronutrients, including vitamin B 12 , vitamin B 6 , folate, vitamin C, vitamin D, and vitamin E, from published genome-wide association studies (GWAS) and the IEU OpenGWAS open database. Summary statistics for frailty were obtained from a GWAS meta-analysis, including the UK Biobank and TwinGene ( N = 175,226). We performed two independent TSMR analyses and a meta-analysis based on the two independent MR estimates to assess the causal relationship between circulating micronutrientn and frailty., Results: Our study found, no causal relationship between genetically predicted vitamin D ( β  = -0.059, p = 0.35), vitamin B 6 ( β  = 0.006, p = 0.80), vitamin E ( β  = -0.011, p = 0.79), vitamin C ( β  = -0.044, p = 0.06), vitamin B 12 ( β  = -0.027, p = 0.37), and folate ( β  = 0.029, p = 0.17), with frailty., Conclusion: This study showed that these six micronutrients did not reduce the risk of developing frailty. However, we think it is necessary further to investigate the relationship and mechanisms between micronutrients and frailty using methods such as randomized controlled trials., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Kuribanjiang, Min, Yan, Chen, Aiheti, Wupuer, Wang, Peng, Li, Li, Dong, Fan, Yang and Zhao.)