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This study utilizes clustering analysis to identify muscle health patterns and their relationships with various brain magnetic resonance imaging (MRI) indices.<\/jats:p><\/jats:sec><jats:sec><jats:title>Research Design and Methods<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Brain MRI indices that revealed significant associations with the clusters included gray matter volume (GMV) in cerebellum (p &amp;lt; .001), superior frontal gyrus (p = .019), inferior frontal gyrus (p = .003), posterior cingulum (p = .021), vermis (p = .045), and gray matter density (GMD) in gyrus rectus (p &amp;lt; .001) and temporal pole (p &amp;lt; .001). The leptin-resistant group had most degree of reduction in GMV, whereas the sarcopenia group had most degree of reduction in GMD.<\/jats:p><\/jats:sec><jats:sec><jats:title>Discussion and Implications<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec>","DOI":"10.1093\/geroni\/igac073","type":"journal-article","created":{"date-parts":[[2022,12,29]],"date-time":"2022-12-29T08:39:04Z","timestamp":1672303144000},"source":"Crossref","is-referenced-by-count":6,"title":["Muscle Health Patterns and Brain MRI Indices: A Cluster Analysis"],"prefix":"10.1093","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1338-1079","authenticated-orcid":false,"given":"Shou-En","family":"Wu","sequence":"first","affiliation":[{"name":"Department of Dermatology, Tri-Service General Hospital; and School of Medicine, National Defense Medical Center , Taipei, Taiwan , Republic of 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