RESUMEN
BACKGROUND AND AIMS: HBV infection is a major etiology of acute-on-chronic liver failure (ACLF). At present, the pattern and regulation of hepatocyte death during HBV-ACLF progression are still undefined. Evaluating the mode of cell death and its inducers will provide new insights for developing therapeutic strategies targeting cell death. In this study, we aimed to elucidate whether and how immune landscapes trigger hepatocyte death and lead to the progression of HBV-related ACLF. APPROACH AND RESULTS: We identified that pyroptosis represented the main cell death pattern in the liver of patients with HBV-related ACLF. Deficiency of MHC-I in HBV-reactivated hepatocytes activated cytotoxic NK cells, which in turn operated in a perforin/granzyme-dependent manner to trigger GSDMD/caspase-8-dependent pyroptosis of hepatocytes. Neutrophils selectively accumulated in the pyroptotic liver, and HMGB1 derived from the pyroptotic liver constituted an important factor triggering the generation of pathogenic extracellular traps in neutrophils (NETs). Clinically, elevated plasma levels of myeloperoxidase-DNA complexes were a promising prognostic biomarker for HBV-related ACLF. More importantly, targeting GSDMD pyroptosis-HMGB1 release in the liver abrogates NETs that intercept the development of HBV-related ACLF. CONCLUSIONS: Studying the mechanisms that selectively modulate GSDMD-dependent pyroptosis, as well as its immune landscapes, will provide a novel strategy for restoring the liver function of patients with HBV-related ACLF.
RESUMEN
BACKGROUND: Primary non-function (PNF) and early allograft failure (EAF) after liver transplantation (LT) seriously affect patient outcomes. In clinical practice, effective prognostic tools for early identifying recipients at high risk of PNF and EAF were urgently needed. Recently, the Model for Early Allograft Function (MEAF), PNF score by King's College (King-PNF) and Balance-and-Risk-Lactate (BAR-Lac) score were developed to assess the risks of PNF and EAF. This study aimed to externally validate and compare the prognostic performance of these three scores for predicting PNF and EAF. METHODS: A retrospective study included 720 patients with primary LT between January 2015 and December 2020. MEAF, King-PNF and BAR-Lac scores were compared using receiver operating characteristic (ROC) and the net reclassification improvement (NRI) and integrated discrimination improvement (IDI) analyses. RESULTS: Of all 720 patients, 28 (3.9%) developed PNF and 67 (9.3%) developed EAF in 3 months. The overall early allograft dysfunction (EAD) rate was 39.0%. The 3-month patient mortality was 8.6% while 1-year graft-failure-free survival was 89.2%. The median MEAF, King-PNF and BAR-Lac scores were 5.0 (3.5-6.3), -2.1 (-2.6 to -1.2), and 5.0 (2.0-11.0), respectively. For predicting PNF, MEAF and King-PNF scores had excellent area under curves (AUCs) of 0.871 and 0.891, superior to BAR-Lac (AUC = 0.830). The NRI and IDI analyses confirmed that King-PNF score had the best performance in predicting PNF while MEAF served as a better predictor of EAD. The EAF risk curve and 1-year graft-failure-free survival curve showed that King-PNF was superior to MEAF and BAR-Lac scores for stratifying the risk of EAF. CONCLUSIONS: MEAF, King-PNF and BAR-Lac were validated as practical and effective risk assessment tools of PNF. King-PNF score outperformed MEAF and BAR-Lac in predicting PNF and EAF within 6 months. BAR-Lac score had a huge advantage in the prediction for PNF without post-transplant variables. Proper use of these scores will help early identify PNF, standardize grading of EAF and reasonably select clinical endpoints in relative studies.