{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T15:27:26Z","timestamp":1785770846291,"version":"3.56.0"},"reference-count":37,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T00:00:00Z","timestamp":1785715200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Nutr."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Metabolic dysfunction-associated steatotic liver disease (MASLD) poses a critical global health challenge, yet traditional anthropometric indices fail to precisely capture its metabolic heterogeneity. This study aimed to identify novel body composition phenotypes using nonlinear dimensionality reduction and to develop a predictive model for MASLD.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A total of 7,946 participants were enrolled. Uniform Manifold Approximation and Projection (UMAP) was applied to bioelectrical impedance analysis (BIA) data for unsupervised clustering to identify latent phenotypes. Key variables were selected using a combination of Boruta, XGBoost, and Random Forest algorithms, followed by the construction of a Logistic regression model to evaluate associations and predictive performance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>UMAP robustly identified three distinct phenotypes: Low-Mass Lean (LML), High-Mass Obesogenic (HMO), and Fluid-Imbalanced, High-Parameters (FIHP). In terms of frequency, LML was the most common (47.7% in males, 49.2% in females), followed by HMO (45.8% and 44.8%, respectively) and the rare FIHP subtype (6.5% and 6.0%, respectively). LML exhibited normal size and metabolic balance, whereas HMO was characterized by high adiposity and metabolic risk, and FIHP by fluid imbalance. Compared to the LML group, HMO and FIHP phenotypes were associated with significantly higher risks of MASLD (adjusted OR: 3.10 [95% CI: 2.74\u20133.51] and 1.39 [95% CI: 1.08\u20131.78], respectively). The integrated model demonstrated superior predictive performance (AUC = 0.863) and favorable clinical utility in calibration and decision curve analyses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Our study identified three distinct body composition phenotypes significantly associated with MASLD risk using unsupervised clustering and demonstrated that a prediction model integrating these phenotypes with routine indicators exhibited superior performance, suggesting their potential utility for early risk stratification and clinical management.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fnut.2026.1873472","type":"journal-article","created":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T14:36:41Z","timestamp":1785767801000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Association between UMAP-identified body composition phenotypes and metabolic dysfunction-associated steatotic liver disease in the general population of China"],"prefix":"10.3389","volume":"13","author":[{"given":"Huimin","family":"Yin","sequence":"first","affiliation":[{"name":"Department of Clinical Nutrition, Taikang Xianlin Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yangtian","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Endocrinology, Taikang Xianlin Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Yuan","sequence":"additional","affiliation":[{"name":"Department of Endocrinology, Taikang Xianlin Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuaiju","family":"Liao","sequence":"additional","affiliation":[{"name":"Department of Endocrinology, Taikang Xianlin Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Ding","sequence":"additional","affiliation":[{"name":"Department of Endocrinology, Taikang Xianlin Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lili","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Clinical Nutrition, Taikang Xianlin Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Xiang","sequence":"additional","affiliation":[{"name":"Department of Endocrinology, Taikang Xianlin Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,3]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"893","DOI":"10.1016\/j.jare.2025.05.029","article-title":"Association between dietary amino acid intake and the risk of metabolic dysfunction-associated steatotic liver disease.","volume":"80","author":"Zhou","year":"2026","journal-title":"J Adv Res"},{"key":"B2","doi-asserted-by":"publisher","first-page":"e70075","DOI":"10.1002\/jcsm.70075","article-title":"Comment on \u2018association between handgrip strength and cardiovascular disease risk in MASLD: a prospective study from UK Biobank\u2019 by T. S. lim et al.-authors\u2019 reply.","volume":"16","author":"Lim","year":"2025","journal-title":"J Cachexia Sarcopenia Muscle"},{"key":"B3","doi-asserted-by":"publisher","first-page":"S32","DOI":"10.3350\/cmh.2024.0431","article-title":"Epidemiology of metabolic dysfunction-associated steatotic liver disease.","volume":"31","author":"Younossi","year":"2025","journal-title":"Clin Mol Hepatol"},{"key":"B4","doi-asserted-by":"publisher","first-page":"S43","DOI":"10.3350\/cmh.2022.0351","article-title":"Causes and risk profiles of mortality among individuals with nonalcoholic fatty liver disease.","volume":"29","author":"Konyn","year":"2023","journal-title":"Clin Mol Hepatol"},{"key":"B5","doi-asserted-by":"publisher","first-page":"235","DOI":"10.3350\/cmh.2023.0485","article-title":"Global incidence of adverse clinical events in non-alcoholic fatty liver disease: a systematic review and meta-analysis.","volume":"30","author":"Le","year":"2024","journal-title":"Clin Mol Hepatol"},{"key":"B6","doi-asserted-by":"publisher","first-page":"697","DOI":"10.1016\/j.tem.2024.02.007","article-title":"Current status and future trends of the global burden of MASLD.","volume":"35","author":"Miao","year":"2024","journal-title":"Trends Endocrinol Metab"},{"key":"B7","doi-asserted-by":"publisher","first-page":"15473","DOI":"10.3390\/ijms242015473","article-title":"Metabolic-dysfunction-associated steatotic liver disease-its pathophysiology, association with atherosclerosis and cardiovascular disease, and treatments.","volume":"24","author":"Yanai","year":"2023","journal-title":"Int J Mol Sci"},{"key":"B8","doi-asserted-by":"publisher","first-page":"102400","DOI":"10.1016\/j.clinre.2024.102400","article-title":"Diagnostic performance of sixteen biomarkers for MASLD: a study in a Mexican cohort.","volume":"48","author":"Priego-Parra","year":"2024","journal-title":"Clin Res Hepatol Gastroenterol"},{"key":"B9","doi-asserted-by":"publisher","first-page":"772","DOI":"10.1136\/gutjnl-2025-336127","article-title":"Long-term prognosis of lean MASLD: evidence from three population-based prospective cohorts.","volume":"75","author":"Huo","year":"2026","journal-title":"Gut"},{"key":"B10","doi-asserted-by":"publisher","first-page":"2301","DOI":"10.3390\/diagnostics14202301","article-title":"Bioelectrical impedance analysis demonstrates reliable agreement with dual-energy x-ray absorptiometry in identifying reduced skeletal muscle mass in patients with metabolic dysfunction-associated steatotic liver disease and hypertension.","volume":"14","author":"Sheptulina","year":"2024","journal-title":"Diagnostics"},{"key":"B11","doi-asserted-by":"publisher","first-page":"e13844","DOI":"10.1111\/obr.13844","article-title":"Development and clinical application of bioelectrical impedance analysis method for body composition assessment.","volume":"26","author":"Son","year":"2025","journal-title":"Obes Rev"},{"key":"B12","doi-asserted-by":"publisher","first-page":"5771","DOI":"10.1038\/s41467-025-60822-1","article-title":"GAUDI: interpretable multi-omics integration with UMAP embeddings and density-based clustering.","volume":"16","author":"Castellano-Escuder","year":"2025","journal-title":"Nat Commun"},{"key":"B13","doi-asserted-by":"publisher","first-page":"1231","DOI":"10.1002\/jpen.1994","article-title":"The comparison of segmental multifrequency bioelectrical impedance analysis and dual-energy x-ray absorptiometry for estimating fat free mass and percentage body fat in an ambulatory population.","volume":"45","author":"Hurt","year":"2021","journal-title":"JPEN J Parenter Enteral Nutr"},{"key":"B14","doi-asserted-by":"publisher","first-page":"1542","DOI":"10.1016\/j.jhep.2023.06.003","article-title":"A multisociety Delphi consensus statement on new fatty liver disease nomenclature.","volume":"79","author":"Rinella","year":"2023","journal-title":"J Hepatol"},{"key":"B15","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1186\/s12872-018-0877-2","article-title":"Association between nonalcoholic fatty liver disease and subclinical atherosclerosis: a cross-sectional study on population over 40 years old.","volume":"18","author":"Zheng","year":"2018","journal-title":"BMC Cardiovasc Disord"},{"key":"B16","doi-asserted-by":"publisher","first-page":"1148","DOI":"10.1038\/s41598-020-58059-7","article-title":"Multi-omics characterization of a diet-induced obese model of non-alcoholic steatohepatitis.","volume":"10","author":"\u00c6gidius","year":"2020","journal-title":"Sci Rep"},{"key":"B17","doi-asserted-by":"publisher","first-page":"e1012427","DOI":"10.1371\/journal.pcbi.1012427","article-title":"Calibrating dimension reduction hyperparameters in the presence of noise.","volume":"20","author":"Lin","year":"2024","journal-title":"PLoS Comput Biol"},{"key":"B18","doi-asserted-by":"publisher","first-page":"1705683","DOI":"10.3389\/fnut.2025.1705683","article-title":"Dietary patterns and obesity are associated with type 2 diabetes risk in elderly Chinese men: a machine learning approach.","volume":"12","author":"Sun","year":"2025","journal-title":"Front Nutr"},{"key":"B19","doi-asserted-by":"publisher","first-page":"3598","DOI":"10.1111\/dom.70536","article-title":"Association of four insulin resistance indices with liver-related adverse outcomes: a prospective cohort study.","volume":"28","author":"Wang","year":"2026","journal-title":"Diabetes Obes Metab"},{"key":"B20","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1111\/apt.70174","article-title":"Anthropometric measures and mortality risk in individuals with metabolic dysfunction-associated steatotic liver disease (MASLD): a population-based cohort study.","volume":"62","author":"Yeo","year":"2025","journal-title":"Aliment Pharmacol Ther"},{"key":"B21","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1186\/s12872-023-03126-w","article-title":"Association of normal-weight central obesity with hypertension: a cross-sectional study from the China health and nutrition survey.","volume":"23","author":"Ren","year":"2023","journal-title":"BMC Cardiovasc Disord"},{"key":"B22","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1002\/jpen.70017","article-title":"Association between bioelectrical impedance analysis parameters and metabolic dysfunction-associated steatotic liver disease relative to handgrip strength in children and adolescents in Korea: a comparative study.","volume":"50","author":"Song","year":"2026","journal-title":"JPEN J Parenter Enteral Nutr"},{"key":"B23","doi-asserted-by":"publisher","first-page":"1382","DOI":"10.14309\/ajg.0000000000003657","article-title":"A comparison of the predictive value of 12 body composition markers for metabolic dysfunction-associated steatotic liver disease, at-risk metabolic dysfunction-associated steatohepatitis, and increased liver stiffness in a general population setting.","volume":"121","author":"van Kleef","year":"2026","journal-title":"Am J Gastroenterol"},{"key":"B24","doi-asserted-by":"publisher","first-page":"e0299487","DOI":"10.1371\/journal.pone.0299487","article-title":"Machine learning approaches to enhance diagnosis and staging of patients with MASLD using routinely available clinical information.","volume":"19","author":"McTeer","year":"2024","journal-title":"PLoS One"},{"key":"B25","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1186\/s12967-025-06387-5","article-title":"Machine learning models for predicting metabolic dysfunction-associated steatotic liver disease prevalence using basic demographic and clinical characteristics.","volume":"23","author":"Zhu","year":"2025","journal-title":"J Transl Med"},{"key":"B26","doi-asserted-by":"publisher","first-page":"1701729","DOI":"10.3389\/fendo.2025.1701729","article-title":"Machine learning-based model for predicting metabolic dysfunction-associated steatotic liver disease using non-invasive parameters in young adults.","volume":"16","author":"Song","year":"2025","journal-title":"Front Endocrinol"},{"key":"B27","doi-asserted-by":"publisher","first-page":"e0262675","DOI":"10.1371\/journal.pone.0262675","article-title":"The importance of body composition assessment for patients with advanced hepatocellular carcinoma by bioelectrical impedance analysis in lenvatinib treatment.","volume":"17","author":"Yamaoka","year":"2022","journal-title":"PLoS One"},{"key":"B28","doi-asserted-by":"publisher","first-page":"1347","DOI":"10.21873\/invivo.11912","article-title":"Association of an overhydrated state with the liver fibrosis and prognosis of cirrhotic patients.","volume":"34","author":"Kishino","year":"2020","journal-title":"In Vivo"},{"key":"B29","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1007\/s11154-022-09775-0","article-title":"Phase angle and cellular health: inflammation and oxidative damage.","volume":"24","author":"da Silva","year":"2023","journal-title":"Rev Endocr Metab Disord"},{"key":"B30","doi-asserted-by":"publisher","first-page":"596","DOI":"10.3892\/etm.2021.10028","article-title":"Microcirculatory disturbance in acute liver injury.","volume":"21","author":"Kuwano","year":"2021","journal-title":"Exp Ther Med"},{"key":"B31","doi-asserted-by":"publisher","first-page":"e71451","DOI":"10.7759\/cureus.71451","article-title":"Diagnosis and management of lean metabolic dysfunction-associated steatotic liver disease (MASLD): a systematic review.","volume":"16","author":"Njei","year":"2024","journal-title":"Cureus"},{"key":"B32","doi-asserted-by":"publisher","first-page":"599","DOI":"10.1038\/s41575-021-00448-y","article-title":"The complex link between NAFLD and type 2 diabetes mellitus - mechanisms and treatments.","volume":"18","author":"Targher","year":"2021","journal-title":"Nat Rev Gastroenterol Hepatol"},{"key":"B33","doi-asserted-by":"publisher","first-page":"1114836","DOI":"10.3389\/fmed.2023.1114836","article-title":"Improved body composition decreases the fat content in non-alcoholic fatty liver disease, a meta-analysis and systematic review of longitudinal studies.","volume":"10","author":"M\u00e1tis","year":"2023","journal-title":"Front Med"},{"key":"B34","doi-asserted-by":"publisher","first-page":"1857","DOI":"10.1016\/j.jacc.2018.02.055","article-title":"Metabolically healthy obesity, transition to metabolic syndrome, and cardiovascular risk.","volume":"71","author":"Mongraw-Chaffin","year":"2018","journal-title":"J Am Coll Cardiol."},{"key":"B35","doi-asserted-by":"publisher","first-page":"1433857","DOI":"10.3389\/fcell.2024.1433857","article-title":"Systemic impacts of metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH) on heart, muscle, and kidney related diseases.","volume":"12","author":"Sandireddy","year":"2024","journal-title":"Front Cell Dev Biol"},{"key":"B36","doi-asserted-by":"publisher","first-page":"2608","DOI":"10.1002\/jcsm.13605","article-title":"Body composition and progression of biopsy-proven non-alcoholic fatty liver disease in patients with obesity.","volume":"15","author":"Wan","year":"2024","journal-title":"J Cachexia Sarcopenia Muscle"},{"key":"B37","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1186\/s12944-024-02100-5","article-title":"Increased visceral fat area to skeletal muscle mass ratio is positively associated with the risk of metabolic dysfunction-associated steatotic liver disease in a Chinese population.","volume":"23","author":"Liu","year":"2024","journal-title":"Lipids Health Dis"}],"container-title":["Frontiers in Nutrition"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fnut.2026.1873472\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T14:36:42Z","timestamp":1785767802000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fnut.2026.1873472\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,3]]},"references-count":37,"alternative-id":["10.3389\/fnut.2026.1873472"],"URL":"https:\/\/doi.org\/10.3389\/fnut.2026.1873472","relation":{},"ISSN":["2296-861X"],"issn-type":[{"value":"2296-861X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,3]]},"article-number":"1873472"}}