Muscle Health Patterns and Brain MRI Indices: A Cluster Analysis

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 (p