ArticleInnovation in aging2023
Muscle Health Patterns and Brain MRI Indices: A Cluster Analysis.
Article in Innovation in aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Speech as a dynamic biomarker of physical aging: a longitudinal study.GeroScience · 2026Article
- Association between dietary inflammatory index and sarcopenia development in Polish population.Scientific reports · 2025Article
- Causal association of sarcopenia-related traits with brain cortical structure: a bidirectional Mendelian randomization study.Aging clinical and experimental research · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Background and Objectives: The interplay between muscle and brain lacks a holistic approach to assess the combined effect of multiple factors. This study utilizes clustering analysis to identify muscle health patterns and their relationships with various brain magnetic resonance imaging (MRI) indices. Research Design and Methods: Two hundred and seventy-five cognitively intact participants who completed brain MRI from the Health, Aging, and Body Composition Study were enrolled. Muscle health-related markers that showed significant relationship with total gray matter volume entered the cluster analysis. Subsequently, macrostructural and microstructural MRI indices were examined with analysis of variance and multiple linear regression analysis to determine significant associations with muscle health clusters. The muscle health cluster included 6 variables: age, skeletal muscle mass index, gait speed, handgrip strength, change of total body fat, and serum leptin level. Clustering method produced 3 clusters which had characteristics of obese, leptin-resistant, and sarcopenia, respectively. Results: Brain MRI indices that revealed significant associations with the clusters included gray matter volume (GMV) in cerebellum ( Discussion and Implications: The leptin-resistant and sarcopenia populations had higher risk of neuroimaging alterations. Clinicians should raise awareness on the brain MRI findings in clinical settings. Because these patients mostly had central nervous system conditions or other critical illnesses, the risk of sarcopenia as a comorbidity will substantially affect the prognosis and medical care.
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