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- W4366335814 abstract "Objective Bile acid diarrhoea (BAD) is debilitating yet treatable, but it remains underdiagnosed due to challenging diagnostics. We developed a blood test-based method to guide BAD diagnosis. Design We included serum from 50 treatment-naive patients with BAD diagnosed by gold standard 75 selenium homotaurocholic acid test, 56 feature-matched controls and 37 patients with non-alcoholic fatty liver disease (NAFLD). Metabolomes were generated using mass spectrometry covering 1295 metabolites and compared between groups. Machine learning was used to develop a BAD Diagnostic Score (BDS). Results Metabolomes of patients with BAD significantly differed from controls and NAFLD. We detected 70 metabolites with a discriminatory performance in the discovery set with an area under receiver-operating curve metric above 0.80. Logistic regression modelling using concentrations of decanoylcarnitine, cholesterol ester (22:5), eicosatrienoic acid, L-alpha-lysophosphatidylinositol (18:0) and phosphatidylethanolamine (O-16:0/18:1) distinguished BAD from controls with a sensitivity of 0.78 (95% CI 0.64 to 0.89) and a specificity of 0.93 (95% CI 0.83 to 0.98). The model was independent of covariates (age, sex, body mass index) and distinguished BAD from NAFLD irrespective of fibrosis stage. BDS outperformed other blood test-based tests (7-alpha-hydroxy-4-cholesten-3-one and fibroblast growth factor 19) currently under development. Conclusions BDS derived from serum metabolites in a single-blood sample showed robust identification of patients with BAD with superior specificity and sensitivity compared with current blood test-based diagnostics." @default.
- W4366335814 created "2023-04-20" @default.
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- W4366335814 date "2023-04-18" @default.
- W4366335814 modified "2023-10-18" @default.
- W4366335814 title "Serum lipidome unravels a diagnostic potential in bile acid diarrhoea" @default.
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- W4366335814 doi "https://doi.org/10.1136/gutjnl-2022-329213" @default.
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