Pre-transplant T-cell Clonality: An Observational Study of a Biomarker for Prediction of Sepsis in Liver Transplant Recipients.

2021 
OBJECTIVE This study investigated the ability of pre-transplant T-cell clonality to predict sepsis after liver transplant (LT). SUMMARY BACKGROUND DATA Sepsis is a leading cause of death in LT recipients. Currently, no biomarkers predict sepsis before clinical symptom manifestation. METHODS Between December 2013 and March 2018, our institution performed 478 LTs. After exclusions (eg, patients with marginal donor livers, autoimmune disorders, nonabdominal multi-organ, and liver retransplantations), 180 consecutive LT were enrolled. T-cell characterization was assessed within 48 hours before LT (immunoSEQ Assay, Adaptive Biotechnologies, Seattle, WA). Sepsis-2 and Sepsis-3 cases, defined by presence of acute infection plus ≥2 SIRS criteria, or clinical documentation of sepsis, were identified by chart review. Receiver-operating characteristic analyses determined optimal T-cell repertoire clonality for predicting post-LT sepsis. Kaplan-Meier and Cox proportional hazard modeling assessed outcome-associated prognostic variables. RESULTS Patients with baseline T-cell repertoire clonality ≥0.072 were 3.82 (1.25, 11.40; P = 0.02), and 2.40 (1.00, 5.75; P = 0.049) times more likely to develop sepsis 3 and 12 months post-LT, respectively, when compared to recipients with lower (<0.072) clonality. T-cell repertoire clonality was the only predictor of sepsis 3 months post-LT in multivariate analysis (C-Statistic, 0.75). Adequate treatment resulted in equivalent survival rates between both groups: (93.4% vs 96.2%, respectively, P = 0.41) at 12 months post-LT. CONCLUSIONS T-cell repertoire clonality is a novel biomarker predictor of sepsis before development of clinical symptoms. Early sepsis monitoring and management may reduce post-LT mortality. These findings have implications for developing sepsis-prevention protocols in transplantation and potentially other populations.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    42
    References
    0
    Citations
    NaN
    KQI
    []