Yanxia Lu1, Leonidas G Karagounis2,3, Tze Pin Ng4, Christophe Carre5, Vipin Narang6, Glenn Wong1, Crystal Tze Ying Tan1, Ma Shwe Zin Nyunt4, Qi Gao4, Brian Abel7, Michael Poidinger6, Tamas Fulop8, Nabil Bosco9, Anis Larbi1,8,10. 1. Biology of Aging Laboratory, Singapore Immunology Network (SIgN), Agency for Science Technology and Research (A*STAR), Immunos Building, Biopolis, Singapore. 2. Experimental Myology and Integrative Physiology Cluster, Plymouth Marjon University, Plymouth, UK. 3. Nestle Health Science, Vevey, Switzerland. 4. Gerontology Research Programme, Department of Psychological Medicine, National University Health System, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. 5. Biostat, Bioinformatics & Omics, Sanofi Pasteur, Marcy l'Etoile, France. 6. Bioinformatics group, Singapore Immunology Network (SIgN), Agency for Science Technology and Research (A*STAR), Immunos Building, Biopolis, Singapore. 7. Immunomonitoring platform, Singapore Immunology Network (SIgN), Agency for Science Technology and Research (A*STAR), Immunos Building, Biopolis, Singapore. 8. Geriatrics Division, Department of Medicine, Research Center on Ageing, University of Sherbrooke, Sherbrooke, Quebec, Canada. 9. Nestlé Research Singapore Hub, Singapore. 10. Department of Biology, Faculty of Sciences, University Tunis El Manar, Tunis, Tunisia.
Abstract
Background: Evidence suggests the pivotal contribution of nutrition as a modifiable risk factor for sarcopenia. The present cross-sectional study characterized the nutritional and metabolic profile of sarcopenia through an extensive exploration of a wide array of blood biomarkers related to muscle protein metabolism and transcriptomic signatures in community-dwelling elderly. Methods: Among 189 older individuals with a mean age of 73.2 years, sarcopenia was diagnosed according to the Asian Working Group for Sarcopenia (AWGS) criteria based on appendicular lean mass measured by dual-energy X-ray absorptiometry (DXA) scan, muscle strength, and gait speed. Nutritional status was evaluated using the Mini Nutritional Assessment (MNA). In addition, we assessed specific blood biomarkers of nutritional status (plasma essential amino acids (EAAs), vitamins), nicotine-derived metabolites, and an extensive microarray analysis from peripheral blood mononuclear cells. Results: Malnutrition defined by low MNA score was independently associated with sarcopenia (p<0.001). Sarcopenic elderly showed lower BMI and leptin and higher adiponectin and high-density lipoproteins. Levels of EAAs including lysine, methionine, phenylalanine, threonine, as well as branched-chain AAs and choline, were inversely associated with sarcopenia. Furthermore, nicotine metabolites (cotinine and trans-3'-hydroxycotine) and vitamin B6 status were linked to one or more clinical and functional measures of sarcopenia. Differentially expressed genes and Ingenuity pathway analysis supported the association of nutrition with sarcopenia. Conclusions: Herein, the characterization of a nutritional and metabolic signature of sarcopenia provides a firm basis and potential identification of specific targets and directions for the nutritional approach to the prevention and treatment of sarcopenia in ageing populations.
Background: Evidence suggests the pivotal contribution of nutrition as a modifiable risk factor for sarcopenia. The present cross-sectional study characterized the nutritional and metabolic profile of sarcopenia through an extensive exploration of a wide array of blood biomarkers related to muscle protein metabolism and transcriptomic signatures in community-dwelling elderly. Methods: Among 189 older individuals with a mean age of 73.2 years, sarcopenia was diagnosed according to the Asian Working Group for Sarcopenia (AWGS) criteria based on appendicular lean mass measured by dual-energy X-ray absorptiometry (DXA) scan, muscle strength, and gait speed. Nutritional status was evaluated using the Mini Nutritional Assessment (MNA). In addition, we assessed specific blood biomarkers of nutritional status (plasma essential amino acids (EAAs), vitamins), nicotine-derived metabolites, and an extensive microarray analysis from peripheral blood mononuclear cells. Results: Malnutrition defined by low MNA score was independently associated with sarcopenia (p<0.001). Sarcopenic elderly showed lower BMI and leptin and higher adiponectin and high-density lipoproteins. Levels of EAAs including lysine, methionine, phenylalanine, threonine, as well as branched-chain AAs and choline, were inversely associated with sarcopenia. Furthermore, nicotine metabolites (cotinine and trans-3'-hydroxycotine) and vitamin B6 status were linked to one or more clinical and functional measures of sarcopenia. Differentially expressed genes and Ingenuity pathway analysis supported the association of nutrition with sarcopenia. Conclusions: Herein, the characterization of a nutritional and metabolic signature of sarcopenia provides a firm basis and potential identification of specific targets and directions for the nutritional approach to the prevention and treatment of sarcopenia in ageing populations.
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