A Mendelian randomization study to examine the causal associations of circulating micronutrient levels with frailty risk.

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 B12, vitamin B6, 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 (ß = -0.059, p = 0.35), vitamin B6 (ß = 0.006, p = 0.80), vitamin E (ß = -0.011, p = 0.79), vitamin C (ß = -0.044, p = 0.06), vitamin B12 (ß = -0.027, p = 0.37), and folate (ß = 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.

Metabolome-Wide Mendelian Randomization Assessing the Causal Relationship Between Blood Metabolites and Sarcopenia-Related Traits.

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 pIVW < pBonferroni [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.

A bi-directional Mendelian randomization study of sarcopenia-related traits and type 2 diabetes mellitus.

Background: Previous studies have reported an association between sarcopenia and type 2 diabetes mellitus (T2DM), but causation was prone to confounding factors. A more robust research approach is urgently required to investigate the causal relationship between sarcopenia and T2DM. Methods: The bi-directional two-sample MR study was carried out in two stages: Sarcopenia-related traits were investigated as exposure while T2DM was investigated as an outcome in the first step, whereas the second step was reversed. The GWAS summary data for hand-grip strength (n = 256,523), appendicular lean mass (ALM, n = 450,243), and walking pace (n = 459,915) were obtained from the UK Biobank. T2DM data were obtained from one of the biggest case-control studies on diabetes (DIAGRAM; n = 180,834 cases and 492,191 controls), which was published in 2022. The inverse-variance weighted (IVW) approach was used to obtain MR estimates, and various sensitivity analysis was also performed. Results: Low hand-grip strength had a potential causal relationship with an increased incidence of T2DM (OR = 1.109; 95% CI, 1.008-1.222; p = 0.0350). T2DM risk was reduced by increasing ALM and walking pace: A 1 kg/m2 increase in ALM decreased the risk of T2DM by 10.2% (OR = 0.898; 95% CI, 0.830-0.952; p < 0.001). A 1 m/s increase in walking pace decreased the risk of T2DM by 90.0% (OR = 0.100; 95% CI, 0.053-0.186; p < 0.001). The relationship was bidirectional, with T2DM as a causative factor of sarcopenia-related traits (p < 0.05) except for ALM (ß = 0.018; 95% CI, -0.008 to -0.044; p = 0.168). Conclusions: Hand-grip strength and T2DM had a potential bidirectional causal relationship, as did walking pace and T2DM. We suggest that sarcopenia and T2DM may mutually have a significant causal effect on each other.

Factors affecting concurrent sarcopenia among patients with cardiovascular diseases / 预防医学

Objective @#To investigate the factors affecting concurrent sarcopenia among patients with cardiovascular diseases, so as to provide insights into early identification and prevention of cardiovascular diseases complicated with sarcopenia. @*Methods@#A total of 250 inpatients with cardiovascular diseases in the Sixth Division Hospital of Xinjiang Production and Construction Corps were recruited and divided into the sarcopenia and non-sarcopenia groups according to the diagnostic criteria of sarcopenia. Subjects' basic characteristics, body mass index, blood biochemical indicators and human body composition parameters were collected using questionnaire surveys, and factors affecting concurrent sarcopenia among patients with cardiovascular diseases using a multivariable logistic regression model. @*Results@#Among the 250 patients with cardiovascular diseases, there were 149 males (59.60%) and 101 females (40.40%). The overall prevalence of sarcopenia was 8.40% among the study subjects. The mean age and body mass index were (75.19±9.74) and (20.77±2.19) kg/m2 in the sarcopenia group and (65.24±11.50) years and (25.85±2.87) kg/m2 in the non-sarcopenia group. Multivariable logistic regression analysis identified age (OR=1.115, 95%CI: 1.030-1.207) and body mass index (OR=0.582, 95%CI: 0.445-0.761) were as factors affecting concurrent sarcopenia among patients with cardiovascular diseases. @*Conclusion@#Advanced age and low body mass index may increase the risk of concurrent sarcopenia among patients with cardiovascular diseases.