{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T00:48:18Z","timestamp":1787014098782,"version":"build-2736575974"},"reference-count":45,"publisher":"Wiley","issue":"12","license":[{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2021YFC2701900"],"award-info":[{"award-number":["2021YFC2701900"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2021YFC2701901"],"award-info":[{"award-number":["2021YFC2701901"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2021YFC2701903"],"award-info":[{"award-number":["2021YFC2701903"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82170869"],"award-info":[{"award-number":["82170869"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dom-pubs.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Diabetes Obesity Metabolism"],"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>Metabolic dysfunction\u2010associated steatotic liver disease (MASLD) represents a major health burden in children and adolescents with obesity. This study aimed to characterize metabolic alterations associated with obesity\u2010related MASLD and to evaluate the potential of tryptophan (TRP)\u2010derived metabolites as non\u2010invasive biomarkers for early diagnosis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods<\/jats:title>\n                    <jats:p>A total of 30 normal\u2010weight individuals and 80 patients diagnosed with obesity were included in the discovery cohort. Circulating metabolites were quantified and compared among normal\u2010weight individuals, patients with obesity, and those with obesity\u2010related MASLD to identify metabolic changes associated with disease status. In vitro experiments using mouse hepatocytes and liver organoids were conducted to assess the effects of TRP\u2010derived metabolites on intracellular lipid accumulation. Finally, a non\u2010invasive diagnostic model was developed using machine learning techniques and validated in an independent cohort of 112 individuals.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Circulating TRP metabolism was markedly elevated in children and adolescents with obesity\u2010related MASLD compared with both normal\u2010weight controls and individuals with simple obesity. TRP\u2010derived metabolites significantly promoted intracellular lipid accumulation in mouse hepatocytes and liver organoids via the induction of oxidative stress. The non\u2010invasive diagnostic model based on TRP\u2010derived metabolites demonstrated robust performance in differentiating obesity\u2010related MASLD from simple obesity in both the discovery and validation cohorts.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>These findings highlight the pivotal role of TRP metabolism in the pathogenesis of MASLD in children and adolescents with obesity. Elevated TRP\u2010derived metabolites may contribute to hepatic lipid accumulation through oxidative stress and serve as promising non\u2010invasive biomarkers for the early diagnosis of obesity\u2010related MASLD. The machine learning\u2013based diagnostic model offers a practical and less invasive alternative to current diagnostic approaches such as liver biopsy.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/dom.70162","type":"journal-article","created":{"date-parts":[[2025,10,2]],"date-time":"2025-10-02T03:36:50Z","timestamp":1759376210000},"page":"7544-7560","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Tryptophan derivatives as non\u2010invasive diagnostic indicators for obesity\u2010related\n                    <scp>MASLD<\/scp>\n                    in children and adolescents"],"prefix":"10.1111","volume":"27","author":[{"given":"Shumin","family":"Zhan","sequence":"first","affiliation":[{"name":"Department of Endocrinology, Children's Hospital, Zhejiang University School of Medicine National Clinical Research Center for Child Health  Hangzhou China"},{"name":"Hongqiao International Institute of Medicine 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