Skeletal muscle loss is associated with diabetes in middle-aged and older Chinese men without non-alcoholic fatty liver disease

The skeletal muscle mass index is a predictor for all-cause mortality in US adults with type 2 diabetes or pre-diabetes

AIMS

To investigate the relationship between the skeletal muscle mass index (SMI) with all-cause mortality in patients with type 2 diabetes mellitus (T2DM) or pre-diabetes (pre-DM) among American adults.

METHODS

This study included 3684 patients with T2DM or pre-DM from the National Health and Nutrition Examination Survey 2011-2018.

RESULTS

Our study revealed an inverse J-shaped relationship between the SMI with all-cause mortality in US adults with T2DM or pre-DM. We determined the inflection points for all-cause mortality in patients with T2DM or pre-DM were 9.07 kg/m2 in males and 7.82 kg/m2 in females. In men, the all-cause mortality decreased by approximately 72 % (HR, 0.28; 95 % CI, 0.09-0.93) for each unit increased in the SMI below the inflection point. In women, all-cause mortality was reduced by 60 % (HR, 0.40; 95 % CI, 0.16-0.91) for each unit increased in SMI below the threshold. A reverse J-shaped SMI-mortality association emerged in patients with T2DM, contrasting with a U-shaped pattern in pre-DM individuals.

CONCLUSIONS

An inverse J-shaped association was observed between the SMI with all-cause mortality in in US adults with T2DM or pre-DM. SMI is a valuable tool for predicting all-cause mortality in patients with T2DM or pre-DM.

Intrapatient Changes in CT-Based Body Composition After Initiation of Semaglutide (Glucagon-Like Peptide-1 Receptor Agonist) Therapy

BACKGROUND. The long-acting glucagon-like peptide-1 receptor agonist semaglutide is used to treat type 2 diabetes or obesity in adults. Clinical trials have observed associations of semaglutide with weight loss, improved control of diabetes, and cardiovascular risk reduction. OBJECTIVE. The purpose of this study was to evaluate intrapatient changes in body composition after initiation of semaglutide therapy by applying an automated suite of CT-based artificial intelligence (AI) body composition tools. METHODS. This retrospective study included adult patients who were receiving semaglutide treatment and who, between January 2016 and November 2023, underwent abdominopelvic CT within both 5 years before and 5 years after initiation of semaglutide. An automated suite of previously validated CT-based AI body composition tools was applied to scans obtained before semaglutide initiation (hereafter, presemaglutide scans) and scans obtained after semaglutide initiation (hereafter, postsemaglutide scans) to quantify visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) area, skeletal muscle area and attenuation, intermuscular adipose tissue (IMAT) area, liver volume and attenuation, and trabecular bone mineral density (BMD). Patients with weight loss of 5 kg or more and those with weight gain of 5 kg or more between the scans were compared. RESULTS. The study included 241 patients (151 women and 90 men; mean age, 60.4 ± 12.4 [SD] years). In the weight-loss group (n = 67), the postsemaglutide scan, compared with the presemaglutide scan, showed a decrease in VAT area (309.4 vs 341.1 cm2, p < .001), SAT area (371.4 vs 410.7 cm2, p < .001), muscle area (179.2 vs 193.0, p < 0.001), and liver volume (2379.0 vs 2578 HU, p = .009) and an increase in liver attenuation (74.5 vs 67.6 HU, p = .03). In the weight-gain group (n = 48), the postsemaglutide scan, compared with the presemaglutide scan, showed an increase in VAT area (334.0 vs 312.8, p = .002), SAT area (485.8 vs 448.8 cm2, p = .01), and IMAT area (48.4 vs 37.6, p = .009) and a decrease in muscle attenuation (5.9 vs 13.1, p < .001). Other comparisons were not statistically significant (p > .05). CONCLUSION. Patients using semaglutide who lost versus gained weight showed distinct patterns of changes in CT-based body composition measures. Those with weight loss had overall favorable shifts in measures related to cardiometabolic risk. A decrease in muscle attenuation in those with weight gain is consistent with decreased muscle quality. CLINICAL IMPACT. Among patients using semaglutide, automated CT-based AI tools provide biomarkers of changes in body composition beyond those that are evident by standard clinical measures.

Correlation of HbA1c levels with CT-based body composition biomarkers in diabetes mellitus and metabolic syndrome

Diabetes mellitus and metabolic syndrome are closely linked with visceral body composition, but clinical assessment is limited to external measurements and laboratory values including hemoglobin A1c (HbA1c). Modern deep learning and AI algorithms allow automated extraction of biomarkers for organ size, density, and body composition from routine computed tomography (CT) exams. Comparing visceral CT biomarkers across groups with differing glycemic control revealed significant, progressive CT biomarker changes with increasing HbA1c. For example, in the unenhanced female cohort, mean changes between normal and poorly-controlled diabetes showed: 53% increase in visceral adipose tissue area, 22% increase in kidney volume, 24% increase in liver volume, 6% decrease in liver density (hepatic steatosis), 16% increase in skeletal muscle area, and 21% decrease in skeletal muscle density (myosteatosis) (all p < 0.001). The multisystem changes of metabolic syndrome can be objectively and retrospectively measured using automated CT biomarkers, with implications for diabetes, metabolic syndrome, and GLP-1 agonists.

Hindlimb immobilization induces insulin resistance and elevates mitochondrial ROS production in the hippocampus of female rats

Alzheimer's disease (AD) is the fifth leading cause of death in older adults, and treatment options are severely lacking. Recent findings demonstrate a strong relationship between skeletal muscle and cognitive function, with evidence supporting that muscle quality and cognitive function are positively correlated in older adults. Conversely, decreased muscle function is associated with a threefold increased risk of cognitive decline. Based on these observations, the purpose of this study was to investigate the negative effects of muscle disuse [via a model of hindlimb immobilization (HLI)] on hippocampal insulin sensitivity and mitochondrial function and identify the potential mechanisms involved. HLI for 10 days in 4-mo-old female Wistar rats resulted in the following novel findings: 1) hippocampal insulin resistance and deficits in whole body glucose homeostasis, 2) dramatically increased mitochondrial reactive oxygen species (ROS) production in the hippocampus, 3) elevated markers for amyloidogenic cleavage of amyloid precursor protein (APP) and tau protein in the hippocampus, 4) and reduced brain-derived neurotrophic factor (BDNF) expression. These findings were associated with global changes in iron homeostasis, with muscle disuse producing muscle iron accumulation in association with decreased serum and whole brain iron levels. We report the novel finding that muscle disuse alters brain iron homeostasis and reveal a strong negative correlation between muscle and brain iron content. Overall, HLI-induced muscle disuse has robust negative effects on hippocampal insulin sensitivity and ROS production in association with altered brain iron homeostasis. This work provides potential novel mechanisms that may help explain how loss of muscle function contributes to cognitive decline and AD risk.NEW & NOTEWORTHY Muscle disuse via hindlimb immobilization increased oxidative stress and insulin resistance in the hippocampus. These findings were in association with muscle iron overload in connection with iron dysregulation in the brain. Overall, our work identifies muscle disuse as a contributor to hippocampal dysfunction, potentially through an iron-based muscle-brain axis, highlighting iron dysregulation as a potential novel mechanism in the relationship between muscle health, cognitive function, and Alzheimer's disease risk.

Associations of muscle mass and strength with new-onset diabetes among middle-aged and older adults: evidence from the China health and retirement longitudinal study (CHARLS)

BACKGROUND

The associations of muscle mass and strength with new-onset Type 2 diabetes mellitus (T2DM) remain controversial. We aimed to longitudinally evaluate muscle mass and strength in predicting T2DM among Chinese middle-aged and older adults.

METHODS

We enrolled 6033 participants aged ≥ 45 years from the China Health and Retirement Longitudinal Study (CHARLS), a cohort survey, between 2011 and 2012. The appendicular skeletal muscle mass (normalized by weight, ASM/BW%), relative hand grip strength (normalized by weight, HGS/BW), and five-repetition chair stand test (5CST). were all categorized into tertiles (lowest, middle, and highest groups) at baseline, respectively. Individuals were followed up until the occurrence of diabetes or the end of CHARLS 2018, whichever happened first. Cox proportional hazards models to calculate hazard ratios with 95% confidence intervals (CI) and mediation analysis were used.

RESULTS

During follow-up, 815 (13.5%) participants developed T2DM. After adjusting for covariates, lower ASW/BW% was not associated with a higher risk of diabetes. Compared with individuals in the highest tertile of HGS/BW, those in the lowest tertile had 1.296 (95%CI 1.073-1.567) higher risk of diabetes. Compared with individuals in the lowest tertile of 5CST, those in the highest tertile had 1.329 times (95%CI 1.106-1.596) higher risk of diabetes. By subgroup, both the lowest HGS/BW and highest 5CST were risk factors for diabetes among obesity. The mediation analysis revealed that the effect of HGS/BW on the risk of diabetes is mainly mediated by insulin resistance.

CONCLUSIONS

Lower muscle strength is associated with an increased risk of diabetes, especially in obese populations.

Using hyperhomocysteinemia and body composition to predict the risk of non-alcoholic fatty liver disease in healthcare workers

Purpose

This study investigated associations between serum homocysteine levels, body composition, and the probability of having nonalcoholic fatty liver disease (NAFLD) in Chinese healthcare workers.

Patients and Methods

A total of 4028 healthcare workers were enrolled in this study, and all underwent a physical examination. Body composition was measured using multifrequency bioelectrical impedance analysis.

Results

There were 1507 NAFLD patients (72.26% male, 27.74% female) and 2521 controls (39.83% male, 60.17% female). Body mass index (BMI), waistline, neck-circumference (NC), abdominal visceral fat area (AVFA), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), glucose (Glu), homocysteinemia (hcy) were higher in the NAFLD group than controls. Additionally, the skeletal-muscle was associated with a lower risk of NAFLD, whereas BMI, waistline, NC, hyperhomocysteinemia (HHcy) were associated with a higher risk of NAFLD. The best NC cut-off point for NAFLD was 34.45 cm (sensitivity 83.3% and specificity 83.9%) in women with HHcy, and the best skeletal-muscle content cut-off point for NAFLD was 41.335% (sensitivity 74.2% and specificity 65.6%) in men with HHcy.

Conclusion

Interactions between skeletal-muscle content, NC, and HHcy may affect the incidence of NAFLD in healthcare workers. This may provide a novel approach for diagnosing NAFLD.

Loss of skeletal muscle mass is not specific to type 2 diabetes

Skeletal muscle is a massive insulin-sensitive tissue in the body. Loss of muscle mass is associated with mitochondrial dysfunction, and is often a result of diabetes. Insulin deficiency or insulin resistance can only be seen as reduced skeletal muscle mass. Diabetes is caused by insulin deficiency or insulin resistance; however, insulin resistance is not unique to diabetics. Insulin resistance also exists in many diseases.