{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T23:19:05Z","timestamp":1780096745461,"version":"3.54.0"},"reference-count":36,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"6","license":[{"start":{"date-parts":[[2018,4,16]],"date-time":"2018-04-16T00:00:00Z","timestamp":1523836800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Hepatology Communications"],"published-print":{"date-parts":[[2018,6]]},"abstract":"<jats:p>Severe alcoholic hepatitis (SAH) has a high mortality rate, and corticosteroid therapy is effective in 60% patients. This study aimed to investigate a baseline metabolic phenotype that could help stratify patients not likely to respond to steroid therapy and to have an unfavorable outcome. Baseline urine metabolome was studied in patients with SAH using ultra\u2010high performance liquid chromatography and high\u2010resolution mass spectrometry. Patients were categorized as responders (Rs, n = 52) and nonresponders (NRs, n = 8) at day 7 according to the Lille score. Multivariate projection analysis identified metabolites in the discovery cohort (n = 60) and assessed these in a validation cohort of 80 patients (60 Rs, 20 NRs). A total of 212 features were annotated by using metabolomic\/biochemical\/spectral databases for metabolite identification. After a stringent selection procedure, a total of nine urinary metabolites linked to mitochondrial functions significantly discriminated nonresponders, most importantly by increased acetyl\u2010L\u2010carnitine (12\u2010fold), octanoylcarnitine (4\u2010fold), decanoylcarnitine (4\u2010fold), and alpha\u2010ketoglutaric acid (2\u2010fold) levels. Additionally, urinary acetyl\u2010L\u2010carnitine and 3\u2010hydroxysebasic acid discriminated nonsurvivors (<jats:italic toggle=\"yes\">P &lt;<\/jats:italic>0.01). These urinary metabolites significantly correlated to severity indices and mortality (<jats:italic toggle=\"yes\">r &gt;<\/jats:italic>0.3;<jats:italic toggle=\"yes\">P &lt;<\/jats:italic>0.01) and were associated with nonresponse (odds ratio &gt;3.0;<jats:italic toggle=\"yes\">P &lt;<\/jats:italic>0.001). In the validation cohort, baseline urinary acetyl\u2010L\u2010carnitine documented an area under the receiver operating curve of 0.96 (0.85\u20100.99) for nonresponse prediction and a hazard ratio of 3.5 (1.5\u20108.3) for the prediction of mortality in patients with SAH. Acetyl\u2010L\u2010carnitine at a level of &gt;2,500 ng\/mL reliably segregated survivors from nonsurvivors (<jats:italic toggle=\"yes\">P &lt;<\/jats:italic>0.01, log\u2010rank test) in our study cohort.<jats:italic toggle=\"yes\">Conclusion:<\/jats:italic>Urinary metabolome signatures related to mitochondrial functions can predict pretherapy steroid response and disease outcome in patients with SAH. (<jats:italic toggle=\"yes\">Hepatology Communications<\/jats:italic>2018;2:628\u2010643)<\/jats:p>","DOI":"10.1002\/hep4.1176","type":"journal-article","created":{"date-parts":[[2018,4,16]],"date-time":"2018-04-16T14:28:30Z","timestamp":1523888910000},"page":"628-643","source":"Crossref","is-referenced-by-count":14,"title":["Baseline urine metabolic phenotype in patients with severe alcoholic hepatitis and its association with outcome"],"prefix":"10.1097","volume":"2","author":[{"given":"Jaswinder Singh","family":"Maras","sequence":"first","affiliation":[{"name":"Department of Molecular and Cellular Medicine,Institute of Liver and Biliary Sciences,New Delhi,India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sukanta","family":"Das","sequence":"additional","affiliation":[{"name":"Department of Molecular and Cellular Medicine,Institute of Liver and Biliary Sciences,New Delhi,India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shvetank","family":"Sharma","sequence":"additional","affiliation":[{"name":"Department of Molecular and Cellular Medicine,Institute of Liver and Biliary Sciences,New Delhi,India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saggere M.","family":"Shasthry","sequence":"additional","affiliation":[{"name":"Department of Hepatology,Institute of Liver and Biliary Sciences,New Delhi,India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benoit","family":"Colsch","sequence":"additional","affiliation":[{"name":"Service de Pharmacologie et Immunoanalyse, Laboratoire d'Etude du M\u00e9tabolisme des M\u00e9dicaments, DRF\/Institut Joliot, CEA\u2010Saclay, MetaboHUB,Universit\u00e9 Paris\u2010Saclay,Gif\u2010sur\u2010Yvette,France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christophe","family":"Junot","sequence":"additional","affiliation":[{"name":"Service de Pharmacologie et Immunoanalyse, Laboratoire d'Etude du M\u00e9tabolisme des M\u00e9dicaments, DRF\/Institut Joliot, CEA\u2010Saclay, MetaboHUB,Universit\u00e9 Paris\u2010Saclay,Gif\u2010sur\u2010Yvette,France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard","family":"Moreau","sequence":"additional","affiliation":[{"name":"Department of Hepatology,Institute of Liver and Biliary Sciences,New Delhi,India"},{"name":"INSERM, Universit\u00e9 Paris Diderot, Centre de Recherche sur l'Inflammation,Paris,France"},{"name":"D\u00e9partement Hospitalo\u2010Universitaire UNITY, Service d'H\u00e9patologie, H\u00f4pital Beaujon,Assistance Publique\u2010H\u00f4pitaux de Paris,Clichy,France"},{"name":"Laboratoire d'Excellence Inflamex,COMUE Sorbonne Paris Cit\u00e9,Paris,France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiv Kumar","family":"Sarin","sequence":"additional","affiliation":[{"name":"Department of Hepatology,Institute of Liver and Biliary 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