{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T03:57:18Z","timestamp":1785297438183,"version":"3.55.0"},"reference-count":51,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2018,2,5]],"date-time":"2018-02-05T00:00:00Z","timestamp":1517788800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal Orthopaedic Research"],"published-print":{"date-parts":[[2018,7]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:sec><jats:label\/><jats:p>ACL rupture is a major risk factor for post\u2010traumatic osteoarthritis (PTOA) development. Little information exists on acute systemic metabolic indicators of disease development. Thirty\u2010six female Lewis rats were randomized to Control or noninvasive anterior cruciate ligament rupture (ACLR) and to three post\u2010injury time points: 72\u2009h, 4 weeks, 10 weeks (<jats:italic>n<\/jats:italic>\u2009=\u20096). Serum was collected and analyzed by<jats:sup>1<\/jats:sup>H nuclear magnetic resonance (NMR) spectroscopy and combined direct injection and liquid chromatography (LC)\u2010mass spectrometry (MS)\/MS (DI\u2010MS). Univariate and multivariate statistics were used to analyze metabolomic data, and predictive biomarker models were analyzed by receiver operating characteristic (ROC) analysis. Topological pathway analysis was used to identify perturbed pathways. Two hundred twenty\u2010two metabolites were identified by<jats:sup>1<\/jats:sup>H NMR and DI\u2010MS. Differences in the serum metabolome between ACLR and Control were dominated by medium\u2010 and long\u2010chain acylcarnitine species. Further, decreases in several tryptophan metabolites were either found to be significantly different in univariate analysis or to play important contributory roles to multivariate model separation. In addition to acylcarnitines and tryptophan metabolites, glycine, carnosine, and D\u2010mannose were found to differentiate ACLR from Control. Glycine, 9\u2010hexadecenoylcarnitine, trans\u20102\u2010Dodecenoylcarnitine, linoelaidyl carnitine, hydroxypropionylcarnitine, and D\u2010Mannose were identified as biomarkers with high area under ROC curve values and high predictive accuracies. Our analysis provides new information regarding the potential contribution of inflammatory processes and immune dysregulation to the onset and progression of PTOA following ACL injury. As these processes have most commonly been associated with inflammatory arthropathies, larger\u2010scale studies elucidating their involvement in PTOA development and progression are necessary. \u00a9 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. 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