ArticleEuropean journal of medical research2026
Development of a tryptophan metabolomics-based diagnostic model for hepatic encephalopathy in liver cirrhosis.
Article in European journal of medical research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundTryptophan (TRP) metabolism is implicated in the pathogenesis of hepatic encephalopathy (HE). Abnormal TRP metabolites correlate with HE severity and may represent potential biomarkers. This study employed targeted metabolomics to characterize serum TRP metabolic profiles in patients with liver cirrhosis (LC) at different stages. Furthermore, a diagnostic model integrating clinical indicators was developed to facilitate the early detection of hepatic encephalopathy in LC patients.
methodNinety LC patients (25 without HE, 30 with covert HE, and 35 with overt HE) and 50 healthy controls were enrolled from January 2023 to December 2024. Serum TRP metabolites were quantified using targeted liquid chromatography-mass spectrometry (LC-MS). A diagnostic model was developed using logistic regression by integrating differential metabolites with clinical indicators. Diagnostic accuracy and utility were evaluated through the area under the curve (AUC), bootstrap validation, calibration curves, and decision curve analysis (DCA).
resultCompared with healthy controls, cirrhotic patients exhibited significant alterations in TRP metabolites. TRP and serotonin (SER) were consistently reduced (P < 0.001), whereas quinolinic acid, indole-3-lactic acid, 3-hydroxykynurenine, indole-3-acetic acid, and indole-3-carboxaldehyde were markedly elevated (P < 0.01). Between Non-HE LC and HE patients, only SER differed significantly, with lower levels in the HE group (P < 0.001). No significant metabolic differences were observed between the CHE and OHE groups. The diagnostic model integrating blood ammonia and SER achieved strong discriminatory performance, with an AUC of 0.902, sensitivity of 76.9%, and specificity of 88.0%. Bootstrap validation confirmed model robustness (AUC = 0.902, 95% CI: 0.839-0.965). Calibration curves demonstrated excellent agreement between predicted and observed outcomes, while decision curve analysis indicated substantial net clinical benefit.
conclusionTargeted TRP metabolomics distinguishes disease stages in cirrhotic patients, while a diagnostic model integrating blood ammonia and SER provides a reliable tool for early detection and monitoring of hepatic encephalopathy.
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