Associations between Hair Mineral Concentrations and Skeletal Muscle Mass in Korean Adults

Lipoprotein profile as a predictor of type 2 diabetes with sarcopenia: a cross-sectional study

PURPOSE

This study investigated the relationship between lipoprotein profiles and sarcopenia in patients with type 2 diabetes mellitus (T2DM). The objective is to provide a solid theoretical foundation and treatment strategies for clinical prevention and management of diabetes, particularly in individuals with concurrent sarcopenia.

METHODS

In this study, we selected inpatients aged over 60 years diagnosed with T2DM who were admitted to the Department of Geriatrics at Qinghai University Affiliated Hospital from July 2023 to June 2024 as research subjects. We collected general patient data, including gender, age, ethnicity, height, weight, and calculated body mass index (BMI). Key indices measured included glycated hemoglobin (HbA1c), triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoproteins A and B (ApoA and ApoB), phospholipids, lipoprotein(a) [Lp(a)], very low-density lipoprotein (VLDL), and free fatty acids (FFA). Additionally, we assessed limb skeletal muscle mass, grip strength, walking speed, and calculated the appendicular skeletal muscle mass index (ASMI). Based on Asian diagnostic criteria for sarcopenia, patients were categorized into a non-sarcopenic group or a group with T2DM combined with sarcopenia. Baseline laboratory data along with ASMI measurements, grip strength assessments, and walking speeds were statistically analyzed for both groups.

RESULTS

Compared with T2DM patients without sarcopenia, the levels of HbA1c, Lp(a), FFA, serum albumin, TC, TG, HDL-C, ApoA and VLDL in type 2 diabetic patients with sarcopenia were statistically significant (all P < 0.05). When multivariate adjustments were made for these clinical features, age (OR = 1.18, 95%CI: 1.11-1.25, P < 0.001), BMI (OR = 0.81, 95%CI: 0.72-0.92, P < 0.001), ApoA (OR = 0.03, 95%CI: 0.00-0.90, P = 0.043), Lp(a) > = 15.5 mg/dL (OR = 3.14, 95%CI: 1.51-6.54, P = 0.002) and FFA > = 0.48 g/L (OR = 4.11, 95%CI: 1.97-8.57, P < 0.001) were independent predictors of diabetes mellitus with sarcopenia. ROC curve analysis showed that free fatty acids (AUC = 0.721, 95%CI: 0.660-0.782, P < 0.001) in T2DM with sarcopenia has good predictive value judgment.

CONCLUSION

Age, BMI, ApoA, Lp(a), and FFA were independent predictors of T2DM with sarcopenia. Serum free fatty acids have a good predictive value in the judgment of T2DM complicated with sarcopenia.

Inhibition of CTR1 expression improves hypoxia/reoxygenation-induced myoblast injury by blocking cuproptosis

Skeletal muscle ischemia-reperfusion injury (IRI) is a common severe disease with a complex pathological process. This study found that copper chloride (CuCl2) inhibited cell viability in a concentration dependent manner, increased intracellular copper levels and downregulated copper transporter 1 (CTR1) expression. CTR1 upregulation promoted copper uptake by myoblasts and then enhanced cuproptosis, leading to a significant increase in the levels of dihydrolipoamide S-acetyltransferase (DLAT) oligomers, while a significant decrease in the levels of lipoylated (Lip)-dihydrolipoamide S-succinyltransferase (DLST) and Lip-DLAT, ultimately inhibiting cell viability and inducing cell injury. Inducing cuproptosis with elesclomol plus CuCl2 (ES + Cu) further confirmed that "ES + Cu" treatment significantly reduced the contents of adenosine triphosphate (ATP) and glutathione (GSH), decreased the activities of mitochondrial complex I and III, and increased the contents of lactate (LA), malondialdehyde (MDA), creatine kinase (CK) and lactate dehydrogenase (LDH); when tetrathiomolybdate (TTM) was added to inhibit cuproptosis, myoblast injury was recovered significantly. Meanwhile, hypoxia/reoxygenation (H/R) induced CTR1 expression, increased the levels of intracellular copper, DLAT oligomers, LA, MDA, CK and LDH, reduced the levels of Lip-DLST, Lip-DLAT, ATP and GSH, and weakened the activities of mitochondrial complex I and III; after knocking down CTR1 expression, the levels of intracellular copper and the activation of cuproptosis pathway were decreased, and cell viability, injury and inflammation levels were significantly improved. Therefore, cuproptosis can promote myoblast injury, while H/R enhances copper uptake by inducing CTR1 expression, thereby enhancing cuproptosis and inducing cell injury, indicating that cuproptosis is a new mechanism of H/R-induced myoblast injury.

Higher Plasma Copper Exposure was Adversely Associated with Skeletal Muscle Indicators in Chinese Children Aged 6-9 Years: A Cross-Sectional Study

It is unclear whether blood concentrations of copper (Cu), magnesium (Mg), and calcium (Ca) influence skeletal muscle mass and strength in children. We aimed to explore the associations between plasma Cu, Mg, and Ca and skeletal muscle indicators in Chinese children. A total of 452 children aged 6 to 9 years old were recruited for this cross-sectional study. Whole body lean soft tissue mass (WLSTM), trunk lean soft tissue mass (TLSTM), and appendicular skeletal muscle mass (ASMM) were measured using dual-energy X-ray absorptiometry. Parameters of these indicators divided by Height2 (Ht2) and Weight (Wt) at the corresponding sites were calculated. Handgrip strength was also measured. Parameters of skeletal muscle indicators and handgrip strength that were below the sex-specific 20th percentile were considered low levels. Plasma concentrations of Cu, Mg, and Ca were measured using ICP-MS. After adjusting for several potential covariates, among the total subjects, for every one standard deviation increase in Cu concentrations, there was a 0.939% decrease in WLSTM/Wt, a 0.415% decrease in TLSTM/Wt, and a 0.47% decrease in ASMM/Wt. For every one standard deviation increase in Cu concentrations, there was a higher odd (OR: 1.36, 95%CI 1.06, 1.75) of low WLSTM/Wt, TLSTM/Wt (OR: 1.33, 95%CI 1.03, 1.71), ASMM/Ht2 (OR: 1.32, 95%CI 1.02, 1.69), as well as ASMM/Wt (OR: 1.56, 95%CI 1.23, 1.99). No significant associations were found between Mg, Ca, and most skeletal muscle indicators. Higher plasma Cu concentrations were adversely associated with skeletal muscle indicators at multiple sites in Chinese children.

Preventive machine learning models incorporating health checkup data and hair mineral analysis for low bone mass identification

Machine learning (ML) models have been increasingly employed to predict osteoporosis. However, the incorporation of hair minerals into ML models remains unexplored. This study aimed to develop ML models for predicting low bone mass (LBM) using health checkup data and hair mineral analysis. A total of 1206 postmenopausal women and 820 men aged 50 years or older at a health promotion center were included in this study. LBM was defined as a T-score below - 1 at the lumbar, femur neck, or total hip area. The proportion of individuals with LBM was 59.4% (n = 1205). The features used in the models comprised 50 health checkup items and 22 hair minerals. The ML algorithms employed were Extreme Gradient Boosting (XGB), Random Forest (RF), Gradient Boosting (GB), and Adaptive Boosting (AdaBoost). The subjects were divided into training and test datasets with an 80:20 ratio. The area under the receiver operating characteristic curve (AUROC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and an F1 score were evaluated to measure the performances of the models. Through 50 repetitions, the mean (standard deviation) AUROC for LBM was 0.744 (± 0.021) for XGB, the highest among the models, followed by 0.737 (± 0.023) for AdaBoost, and 0.733 (± 0.023) for GB, and 0.732 (± 0.021) for RF. The XGB model had an accuracy of 68.7%, sensitivity of 80.7%, specificity of 51.1%, PPV of 70.9%, NPV of 64.3%, and an F1 score of 0.754. However, these performance metrics did not demonstrate notable differences among the models. The XGB model identified sulfur, sodium, mercury, copper, magnesium, arsenic, and phosphate as crucial hair mineral features. The study findings emphasize the significance of employing ML algorithms for predicting LBM. Integrating health checkup data and hair mineral analysis into these models may provide valuable insights into identifying individuals at risk of LBM.

Association between serum copper levels and muscle mass: results from NHANES 2011-2016

Copper is essential for various biological processes. However, excess copper has several adverse health effects. The effects of serum copper on muscle mass are poorly understood. This study aimed to investigate the association between serum copper levels and muscle mass in the US population. We utilized National Health and Nutrition Examination Survey (NHANES) data between 2011 and 2016 for analysis. Data on serum copper, muscle mass (measured using the appendicular skeletal muscle mass index (ASMI)), and covariates were extracted and analyzed. Weighted multivariate linear regression analyses and smooth curve fittings were performed to investigate the association between serum copper levels and ASMI. Subgroup analyses stratified according to age and sex were performed. In the presence of nonlinearity, threshold effect analysis was performed using a two-piecewise linear regression model. A total of 3860 participants were included in the final analysis. Serum copper levels were negatively associated with ASMI in the fully adjusted model. Furthermore, by comparing participants in the highest and lowest tertiles of serum copper levels, we found that the ASMI decreased by 0.292 kg/m2. In the sex-stratified subgroup analysis, we observed an inverse association between serum copper levels and the ASMI in both men and women. When stratified by age, the association remained significant among participants < 40 years of age, but not among those ≥ 40 years old. Smooth curve fitting revealed a nonlinear relationship between serum copper and ASMI, with an inflection point identified at 150.6 μg/dL. Our study revealed an inverse relationship between serum copper levels and muscle mass. This finding improves the current knowledge on the impact of serum copper on muscle loss and highlights the importance of serum copper homeostasis in muscle health.

Effect of dietary supplementation with multinutrient soy flour on body composition and cognitive function in elderly individuals at the risk of low protein: a randomized, double-blind, placebo-controlled study

Insufficient protein intake and cognitive decline are common in older adults; however, there have been few studies on low protein risk screening and complex nutrient interventions for elderly individuals in rural communities. This study aimed to evaluate the effect of dietary multinutrient soy flour (MNSF) on body composition and cognitive function in elderly individuals who are at risk of protein deficiency in a randomized, double-blind, placebo-controlled clinical trial. Nutritional interventions were given to those found to have low protein levels using bioelectrical impedance analysis (BIA). Among 733 older adults screened, 62 participants were included and randomly assigned into two groups, one taking soy flour and the other taking MNSF for 12 weeks. A previous cross-sectional survey found that 35.1% of the elderly people with an average age of 71.61 ± 5.94 years had an inadequate body protein mass proportion. After the intervention, the MNSF group demonstrated a significant improvement in protein mass, muscle mass, mineral levels, skeletal muscle mass, and fat-free mass compared with baseline (all P < 0.05), as well as a better upward trend compared with the soy flour group (P = 0.08; P = 0.07; P = 0.05; P = 0.08; P = 0.07). Regarding the mini-mental state examination (MMSE) scores, the MNSF group showed a significant decrease after 12 weeks (P < 0.05), which were significantly different compared with the soy flour group (P < 0.05). In the future, the application of MNSF as a food-based supplement to improve nutrition and delay cognitive decline in older adults at the risk of protein deficiency may be considered.