Ha-Na Kim , John C. Newman , Ji Hyun Lee , Yun-Ah Lee , Yuji Jeong , Se-Hong Kim
{"title":"肌肉减少症发病率的代谢组学决定因素:一项为期14年的前瞻性研究,33,797名参与者","authors":"Ha-Na Kim , John C. Newman , Ji Hyun Lee , Yun-Ah Lee , Yuji Jeong , Se-Hong Kim","doi":"10.1016/j.jnha.2025.100668","DOIUrl":null,"url":null,"abstract":"<div><h3>Objectives</h3><div>Sarcopenia, an age-related loss of skeletal muscle mass and strength, increases the risk of adverse health outcomes and socioeconomic burden; however, the metabolic causes of sarcopenia are unclear. This study investigated the association between plasma metabolites and incident sarcopenia and evaluated their predictive value for the incidence of sarcopenia.</div></div><div><h3>Methods</h3><div>This prospective cohort study included 33,797 participants aged 40–69 years from the UK Biobank who were free of sarcopenia and had plasma metabolomic data available. Plasma metabolite levels, including amino acids, fatty acids, lipid/lipoprotein subclasses, creatinine, and glycoprotein acetyls, were measured using nuclear magnetic resonance-based profiling. Incident sarcopenia was defined using the ICD-10 codes or criteria for low skeletal muscle mass and muscle strength.</div></div><div><h3>Results</h3><div>During a follow-up period of over 14 years, 829 participants developed sarcopenia. Of the 249 metabolites tested, 38 were significantly associated with the incidence of sarcopenia. The area under the ROC curve (AUC) of sarcopenia incidence for the 38 metabolites was 0.696 (95% CI: 0.666–0.726), and the AUC for conventional risk factors was 0.738–0.892, according to the models. The combined model, which integrated conventional risk factors and metabolites, significantly improved prediction (AUC: 0.779–0.898).</div></div><div><h3>Conclusions</h3><div>This study identified 38 plasma metabolites associated with incident sarcopenia. Incorporating these metabolites into models with conventional risk factors yielded statistically significant improvements in prediction beyond that of conventional factors alone; however, the gain was modest, and its clinical relevance remains to be determined. These findings suggest that although the clinical utility of these metabolites for predicting sarcopenia incidence has not yet been fully established, they may nevertheless provide insights into underlying biological pathways and could contribute to the development of preventive or therapeutic strategies in geriatric care.</div></div>","PeriodicalId":54778,"journal":{"name":"Journal of Nutrition Health & Aging","volume":"29 11","pages":"Article 100668"},"PeriodicalIF":4.0000,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Metabolomic determinants of sarcopenia incidence: A 14-year prospective study of 33,797 participants\",\"authors\":\"Ha-Na Kim , John C. Newman , Ji Hyun Lee , Yun-Ah Lee , Yuji Jeong , Se-Hong Kim\",\"doi\":\"10.1016/j.jnha.2025.100668\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objectives</h3><div>Sarcopenia, an age-related loss of skeletal muscle mass and strength, increases the risk of adverse health outcomes and socioeconomic burden; however, the metabolic causes of sarcopenia are unclear. This study investigated the association between plasma metabolites and incident sarcopenia and evaluated their predictive value for the incidence of sarcopenia.</div></div><div><h3>Methods</h3><div>This prospective cohort study included 33,797 participants aged 40–69 years from the UK Biobank who were free of sarcopenia and had plasma metabolomic data available. Plasma metabolite levels, including amino acids, fatty acids, lipid/lipoprotein subclasses, creatinine, and glycoprotein acetyls, were measured using nuclear magnetic resonance-based profiling. Incident sarcopenia was defined using the ICD-10 codes or criteria for low skeletal muscle mass and muscle strength.</div></div><div><h3>Results</h3><div>During a follow-up period of over 14 years, 829 participants developed sarcopenia. Of the 249 metabolites tested, 38 were significantly associated with the incidence of sarcopenia. The area under the ROC curve (AUC) of sarcopenia incidence for the 38 metabolites was 0.696 (95% CI: 0.666–0.726), and the AUC for conventional risk factors was 0.738–0.892, according to the models. The combined model, which integrated conventional risk factors and metabolites, significantly improved prediction (AUC: 0.779–0.898).</div></div><div><h3>Conclusions</h3><div>This study identified 38 plasma metabolites associated with incident sarcopenia. Incorporating these metabolites into models with conventional risk factors yielded statistically significant improvements in prediction beyond that of conventional factors alone; however, the gain was modest, and its clinical relevance remains to be determined. These findings suggest that although the clinical utility of these metabolites for predicting sarcopenia incidence has not yet been fully established, they may nevertheless provide insights into underlying biological pathways and could contribute to the development of preventive or therapeutic strategies in geriatric care.</div></div>\",\"PeriodicalId\":54778,\"journal\":{\"name\":\"Journal of Nutrition Health & Aging\",\"volume\":\"29 11\",\"pages\":\"Article 100668\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2025-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Nutrition Health & Aging\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1279770725001939\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GERIATRICS & GERONTOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Nutrition Health & Aging","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1279770725001939","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GERIATRICS & GERONTOLOGY","Score":null,"Total":0}
Metabolomic determinants of sarcopenia incidence: A 14-year prospective study of 33,797 participants
Objectives
Sarcopenia, an age-related loss of skeletal muscle mass and strength, increases the risk of adverse health outcomes and socioeconomic burden; however, the metabolic causes of sarcopenia are unclear. This study investigated the association between plasma metabolites and incident sarcopenia and evaluated their predictive value for the incidence of sarcopenia.
Methods
This prospective cohort study included 33,797 participants aged 40–69 years from the UK Biobank who were free of sarcopenia and had plasma metabolomic data available. Plasma metabolite levels, including amino acids, fatty acids, lipid/lipoprotein subclasses, creatinine, and glycoprotein acetyls, were measured using nuclear magnetic resonance-based profiling. Incident sarcopenia was defined using the ICD-10 codes or criteria for low skeletal muscle mass and muscle strength.
Results
During a follow-up period of over 14 years, 829 participants developed sarcopenia. Of the 249 metabolites tested, 38 were significantly associated with the incidence of sarcopenia. The area under the ROC curve (AUC) of sarcopenia incidence for the 38 metabolites was 0.696 (95% CI: 0.666–0.726), and the AUC for conventional risk factors was 0.738–0.892, according to the models. The combined model, which integrated conventional risk factors and metabolites, significantly improved prediction (AUC: 0.779–0.898).
Conclusions
This study identified 38 plasma metabolites associated with incident sarcopenia. Incorporating these metabolites into models with conventional risk factors yielded statistically significant improvements in prediction beyond that of conventional factors alone; however, the gain was modest, and its clinical relevance remains to be determined. These findings suggest that although the clinical utility of these metabolites for predicting sarcopenia incidence has not yet been fully established, they may nevertheless provide insights into underlying biological pathways and could contribute to the development of preventive or therapeutic strategies in geriatric care.
期刊介绍:
There is increasing scientific and clinical interest in the interactions of nutrition and health as part of the aging process. This interest is due to the important role that nutrition plays throughout the life span. This role affects the growth and development of the body during childhood, affects the risk of acute and chronic diseases, the maintenance of physiological processes and the biological process of aging. A major aim of "The Journal of Nutrition, Health & Aging" is to contribute to the improvement of knowledge regarding the relationships between nutrition and the aging process from birth to old age.