{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T05:13:49Z","timestamp":1768281229308,"version":"3.49.0"},"reference-count":24,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T00:00:00Z","timestamp":1761609600000},"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. Endocrinol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>We analyzed metabolites directly obtained from gallbladder bile, providing novel insights and identifying a potential antifibrotic target in metabolic dysfunction-associated steatotic liver disease (MASLD).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We conducted metabolomic profiling of gallbladder bile samples collected during cholecystectomy from 68 individuals, including 19 healthy controls and 49 MASLD patients with varying degrees of hepatic fibrosis. We used mass spectrometry-based metabolomics to identify fibrosis-associated metabolites. Functional validation included\n                      <jats:italic>in vitro<\/jats:italic>\n                      experiments in colon epithelial cells (HT-29), RNA sequencing, gene set enrichment analysis (GSEA), and a comprehensive G protein-coupled receptor (GPCR) screening assay.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 68 subjects were classified into healthy controls (n = 19), fibrosis stage 0\u20131 (n = 35), and fibrosis stage 2\u20133 (n = 14). Bile metabolomic profiling revealed distinct clustering among the groups, with eight metabolites showing a stepwise increase with fibrosis severity. Using the Human Metabolome Database, eight fibrosis-associated metabolites (M1\u2013M8) were identified, among which M5 (\n                      <jats:italic>m\/z<\/jats:italic>\n                      199.1693) was confirmed as allyl nonanoate. Allyl nonanoate levels were significantly higher in patients with hepatic fibrosis and increased progressively across fibrosis stages. Transcriptomic analysis demonstrated the downregulation of cell cycle-related pathways, including the G2\/M checkpoint. GPCR screening identified GPR119 as the most responsive receptor, exhibiting the highest agonist activity (21.8%). The overexpression of GPR119 in HT-29 cells enhanced allyl nonanoate-induced GLP-1 expression.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Bile metabolomic profiling in MASLD revealed distinct clustering patterns, with several fibrosis-associated metabolites demonstrating a stepwise increase with hepatic fibrosis.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fendo.2025.1707492","type":"journal-article","created":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T05:17:44Z","timestamp":1761628664000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Allyl nonanoate as a novel bile-derived biomarker in metabolic dysfunction-associated steatotic liver disease"],"prefix":"10.3389","volume":"16","author":[{"given":"Soo 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