Muscular dystrophies (MD) are a genetically diverse group of muscle disorders, many of which arise from mutations in genes encoding components of the sarcolemma dystrophin-associated glycoprotein complex (DGC). Despite their notorious heterogeneity, MDs consistently lead to chronic myofiber weakening, necrosis and loss of muscle mass, yet few unifying molecular pathways have been identified to explain this shared pathology.
In light of recent findings characterizing muscle symptoms in limb-girdle MD recessive 28 (LGMDR28) – a condition caused by mutations to the rate-limiting cholesterol synthesis enzyme and statin target 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (HMGCR) – we summarize 4 decades of robust evidence describing how muscle ‘cholesterol depletion’ causes statin-associated myopathies (SAM), which range from mild hyperCKmia to life-threatening rhabdomyolysis during hypercholesterolemia management. After discussing myopathies caused by variants to 2 additional cholesterol pathway enzymes, we examine emerging data depicting circulating cholesterol abnormalities, muscle ‘cholesterol overload’ and lysosomal defects in multiple forms of rodent and human MD including Duchenne muscular dystrophy (DMD).
When taken in combination with evidence showing extreme exacerbation of the notoriously mild phenotypes of dystrophin-deficient mdx and dysferlin-deficient mice by hypercholesterolemia, therapeutic responses to simvastatin and cholesterol absorption blocker ezetimibe in pre-clinical studies, these findings suggest that multiple forms of MD may interfere with muscle cholesterol homeostasis to cause muscle wasting, akin to statins.
Further causal and mechanistic evidence of MDs being cholesterol-handling diseases may ultimately lead to the counter-intuitive testing of statins, ezetimibe and other cholesterol medications in certain MD populations and shed light on the muscle side-effects of the most-widely prescribed drug class.
Sarcopenia, the age-related decline in skeletal muscle mass and strength, is a growing public health concern, yet several meta-analyses may be unreliable due to methodological and systemic challenges. This article examines issues compromising meta-analytic validity: flexibility in study design and analysis, lack of control for parameters influencing muscle health, heterogeneity in definitions and measurements, epidemiological pitfalls, impact of comorbidities, and examination of sarcopenia combined with prolonged sedentary lifestyle. Specifically, flexible designs and p-hacking may inflate spurious findings, while heterogeneity in definitions and measurement methods, often resulting in modest effect sizes, could challenge clinical interpretation. Publication bias may favour positive results, while epidemiological pitfalls, including reverse causality (e.g., sarcopenia as a consequence rather than the cause of conditions) and associative claims (e.g., gut microbiome correlations), may hinder causal inferences. Unadjusted comorbidities, heterogeneous interventions (e.g., combining heterogeneous therapies), comparators (e.g., placebo vs. usual care), and uncontrolled dietary intake and sleep quality may further obscure results. Sarcopenia-based studies may also be confounded by lifelong sedentary behaviour, as lack of physical activity/exercise history could limit the isolation of age-related sarcopenia from physical inactivity combined with age-related sarcopenia. To enhance rigour in meta-analyses in the field, standardized definitions, pre-registered protocols, harmonized assessments, comorbidity phenotyping, intervention and comparator stratification, and causal inference techniques seem essential. Well-controlled longitudinal studies tracking exercise history are warranted, whereas advanced statistical methods and data sharing could improve validity. Overall, these applications may help establish robust evidence to inform tailored clinical interventions and policy decisions for ageing populations.
Progressive functional decline is a defining feature of cancer cachexia. We evaluated the effects of multicomponent interventions for adults with cancer cachexia on physical function outcomes. We also explored whether changes in physical function outcomes or overall quality of life varied following interventions with or without components directly targeting physical function (e.g., exercise training).
We analysed functional outcomes from studies included in our published systematic review of multicomponent interventions for adults with cancer cachexia, supplemented with an updated search. We conducted meta-analyses of change scores from randomised trials comparing physical function outcomes following multicomponent interventions versus standard care. Exploratory analyses of standardised effect measures, including studies of any design, compared interventions based on whether or not they directly targeted physical function.
We analysed data from 35 studies of multicomponent interventions, 19 of which included components directly targeting physical function. Handgrip strength was on average 1.06 kg greater (95% CI, −0.72–2.84 kg), and 6-min walk distance was on average 16.20 m greater (95% CI, −38.27–70.67 m), following multicomponent intervention compared with standard care. Exploratory analysis showed improvement in fatigue was highest following an intervention with a specific fatigue self-management component (standardised mean change: 4.76). Standardised mean change in quality of life was slightly lower following interventions with components directly targeting physical function (0.28 vs. 0.59) though effects were varied.
Multicomponent interventions appear to be superior to standard care for improving some measures of physical function for adults with cancer cachexia, namely, handgrip strength and the 6-min walk distance. Interventions targeting specific aspects of physical function (e.g., fatigue) may lead to greater improvements in those outcomes.
Muscle mass is an important determinant of clinical outcome in chronic diseases as well as in acute infectious diseases such as COVID-19. Both dual-energy x-ray absorptiometry (DXA) and computed tomography (CT) imaging are utilized to quantify muscle. The objective of this study was to assess the agreement between CT segmental analysis of muscle and whole-body muscle mass from DXA.
A prospective observational study was carried out among COVID-19 survivors at least 1 year after the infection. The participants underwent a comprehensive multidimensional health assessment, including DXA and an extended chest CT. Lean mass (LM) and appendicular skeletal muscle mass (SMM) were derived from DXA, and pectoralis, L1 and L3 muscle cross-sectional area (CSA) were assessed using Slice-O-Matic software version 5.0 from the CT scans. Agreement between the two methods was assessed using Pearson correlation and Bland–Altman plots.
One hundred thirty COVID-19 survivors (age 60.8 ± 13.1 years, female % 31.5, BMI 29.9 ± 5.2 kg/m2) were included in the analysis. 83.9% of the participants were obese or overweight. Muscle CSA at L1 and L3 had a strong positive correlation with DXA LM and SMM (L1: r = 0.866 and r = 0.853 for LM and SMM, respectively; L3: r = 0.845 and r = 0.845, p < 0.001). Bland–Altman plots showed good agreement between the two methods. CT pectoralis showed a moderate correlation with DXA LM and SMM (r = 0.659 and r = 0.684, respectively, p < 0.001).
Muscle CSA at L1 and L3 from CT scans is strongly correlated, and pectoralis muscle CSA is moderately correlated with whole-body muscle mass measurement from DXA scans among COVID-19 survivors.
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