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Publication - Dr Philippa Lait

    Ex vivo T cell cytokine expression predicts survival in patients with severe alcoholic hepatitis

    Citation

    Dhanda, A, Yates, E, Schewitz-Bowers, L, Lait, P, Lee, R & Cramp, M, 2019, ‘Ex vivo T cell cytokine expression predicts survival in patients with severe alcoholic hepatitis’. Gut and Liver.

    Abstract

    Aim
    Alcoholic hepatitis (AH) is an acute inflammatory liver condition with high early mortality. Steroids have proven short-term survival benefit but non-responders have the worst outcomes. There is a clinical need to identify these high-risk individuals at presentation. T cells have been implicated in alcoholic hepatitis and steroid responsiveness. We aimed to measure ex vivo T cell cytokine expression as a candidate biomarker of outcome in patients with AH.

    Methods
    Consecutive patients with AH (bilirubin >80µmol/L and AST:ALT>1.5 in heavy alcohol consumers with discriminant function [DF]≥32), were recruited from University Hospitals Plymouth NHS Trust. T cells were obtained and stimulated ex vivo before cytokine expression was determined by flow cytometry and protein multiplex analysis.

    Results
    Twenty-three patients were recruited (10 male; median age 51; baseline DF 67; 30% 90-day mortality). Compared to non-survivors at day 90, T cells from survivors had higher baseline intracellular IL-10:IL-17A ratio (0.43 v 1.20; p=0.02). Multiplex protein analysis identified IFNγ and TNFα as independent predictors of 90-day mortality (p=0.04 and p=0.01 respectively). The ratio of IFNγ/TNFα was predictive of 90-day mortality (1.4 v 0.2; p=0.03).

    Conclusions
    These data demonstrate the potential utility of T cell cytokine release assays performed on pre-treatment blood samples as biomarkers of survival in severe AH. Our key findings were that both the ratio of intracellular IL-10 to IL-17A and the ratio of IFNγ to TNFα in culture supernatants were predictors of 90-day mortality. This offers the promise of developing T cell based diagnostic tools for risk stratification.

    Full details in the University publications repository