Sensing of mitochondrial DNA by ZBP1 promotes RIPK3-mediated necroptosis and ferroptosis in response to diquat poisoning.

Diquat (DQ) poisoning is a severe medical condition associated with life-threatening implications and multiorgan dysfunction. Despite its clinical significance, the precise underlying mechanism remains inadequately understood. This study elucidates that DQ induces instability in the mitochondrial genome of endothelial cells, resulting in the accumulation of Z-form DNA. This process activates Z-DNA binding protein 1 (ZBP1), which then interacts with receptor-interacting protein kinase 3 (RIPK3), ultimately leading to RIPK3-dependent necroptotic and ferroptotic signaling cascades. Specific deletion of either Zbp1 or Ripk3 in endothelial cells simultaneously inhibits both necroptosis and ferroptosis. This dual inhibition significantly reduces organ damage and lowers mortality rate. Notably, our investigation reveals that RIPK3 has a dual role. It not only phosphorylates MLKL to induce necroptosis but also phosphorylates FSP1 to inhibit its enzymatic activity, promoting ferroptosis. The study further shows that deletion of mixed lineage kinase domain-like (Mlkl) and the augmentation of ferroptosis suppressor protein 1 (FSP1)-dependent non-canonical vitamin K cycling can provide partial protection against DQ-induced organ damage. Combining Mlkl deletion with vitamin K treatment demonstrates a heightened efficacy in ameliorating multiorgan damage and lethality induced by DQ. Taken together, this study identifies ZBP1 as a crucial sensor for DQ-induced mitochondrial Z-form DNA, initiating RIPK3-dependent necroptosis and ferroptosis. These findings suggest that targeting the ZBP1/RIPK3-dependent necroptotic and ferroptotic pathways could be a promising approach for drug interventions aimed at mitigating the adverse consequences of DQ poisoning.

GSDMD and GSDME synergy in the transition of acute kidney injury to chronic kidney disease.

BACKGROUND AND HYPOTHESIS: Acute kidney injury (AKI) could progress to chronic kidney disease (CKD) and the AKI-CKD transition has major clinical significance. A growing body of evidence has unveiled the role of pyroptosis in kidney injury. We postulate that GSDMD and GSDME exert cumulative effects on the AKI-CKD transition by modulating different cellular responses. METHODS: We established an AKI-CKD transition model induced by folic acid in wildtype (WT), Gsdmd-/-, Gsdme-/-, and Gsdmd-/-Gsdme-/- mice. Tubular injury, renal fibrosis and inflammatory responses were evaluated. In vitro studies were conducted to investigate the interplay among tubular cells, neutrophils, and macrophages. RESULTS: Double deletion of Gsdmd and Gsdme conferred heightened protection against AKI, mitigating inflammatory responses, including the formation of neutrophil extracellular traps (NETs), macrophage polarization and differentiation, and ultimately renal fibrosis, compared with wildtype mice and mice with single deletion of either Gsdmd or Gsdme. Gsdme, but not Gsdmd deficiency, shielded tubular cells from pyroptosis. GSDME-dependent tubular cell death stimulated NETs formation and prompted macrophage polarization towards a pro-inflammatory phenotype. Gsdmd deficiency suppressed NETs formation and subsequently hindered NETs-induced macrophage-to-myofibroblast transition (MMT). CONCLUSION: GSDMD and GSDME collaborate to contribute to AKI and subsequent renal fibrosis induced by folic acid. Synchronous inhibition of GSDMD and GSDME could be an innovative therapeutic strategy for mitigating the AKI-CKD transition.

Gasdermin D-Mediated Pyroptosis Promotes the Development of Atherosclerosis.

Atherosclerosis is a chronic inflammatory cardiovascular disease with a high-morbidity and mortality rate. An increasing number of studies have addressed the crucial contribution of gasdermin D (GSDMD)-mediated pyroptosis, which is triggered by the inflammasomes to the development of atherosclerosis. However, the underlying mechanism is still unclear. This study aimed to uncover the detailed role of GSDMD in the development of atherosclerosis. An atherosclerotic model was established in Gsdmd-/-/Ldlr-/- mice and Gsdmd+/+/Ldlr-/- mice fed with a high-fat diet. The atherosclerotic lesions, the activation of GSDMD, and the expression level of inflammatory cytokines and chemokines were evaluated. Gsdmd deletion ameliorated the atherosclerotic lesion sizes and the infiltration of immune cells and inflammatory cells in the aortas of mice. Additionally, Gsdmd deletion suppressed the pyroptosis of macrophages and endothelial cells induced by the serum of Ldlr-/- mice fed with a high-fat diet. Furthermore, the formation of neutrophil extracellular traps was also attenuated by knockout of Gsdmd. Bone marrow chimeras confirmed that the genetic deficiency of Gsdmd in both immune cells and intrinsic cells played a role in the promotion of arteriosclerosis. Collectively, our study demonstrated that Gsdmd deletion hindered the pathogenesis of atherosclerosis by inhibiting endothelial cell and macrophage cell death, and the formation of neutrophil extracellular traps.

Development and Validation of a Predictive Model for Acute Kidney Injury in Sepsis Patients Based on Recursive Partition Analysis.

BACKGROUND: Sepsis-associated acute kidney injury (SA-AKI) is a critical condition with significant clinical implications, yet there is a need for a predictive model that can reliably assess the risk of its development. This study is undertaken to bridge a gap in healthcare by creating a predictive model for SA-AKI with the goal of empowering healthcare providers with a tool that can revolutionize patient care and ultimately lead to improved outcomes. METHODS: A cohort of 615 patients afflicted with sepsis, who were admitted to the intensive care unit, underwent random stratification into 2 groups: a training set (n = 435) and a validation set (n = 180). Subsequently, a multivariate logistic regression model, imbued with nonzero coefficients via LASSO regression, was meticulously devised for the prognostication of SA-AKI. This model was thoughtfully rendered in the form of a nomogram. The salience of individual risk factors was assessed and ranked employing Shapley Additive Interpretation (SHAP). Recursive partition analysis was performed to stratify the risk of patients with sepsis. RESULTS: Among the panoply of clinical variables examined, hypertension, diabetes mellitus, C-reactive protein, procalcitonin (PCT), activated partial thromboplastin time, and platelet count emerged as robust and independent determinants of SA-AKI. The receiver operating characteristic curve analysis for SA-AKI risk discrimination in both the training set and validation set yielded an area under the curve estimates of 0.843 (95% CI: 0.805 to 0.882) and 0.834 (95% CI: 0.775 to 0.893), respectively. Notably, PCT exhibited the most conspicuous influence on the model's predictive capacity. Furthermore, statistically significant disparities were observed in the incidence of SA-AKI and the 28-day survival rate across high-risk, medium-risk, and low-risk cohorts (P < .05). CONCLUSION: The composite predictive model, amalgamating the quintet of SA-AKI predictors, holds significant promise in facilitating the identification of high-risk patient subsets.

Single-cell sequencing reveals homogeneity and heterogeneity of the cytopathological mechanisms in different etiology-induced AKI.

Homogeneity and heterogeneity of the cytopathological mechanisms in different etiology-induced acute kidney injury (AKI) are poorly understood. Here, we performed single-cell sequencing (scRNA) on mouse kidneys with five common AKI etiologies (CP-Cisplatin, IRI-Ischemia-reperfusion injury, UUO-Unilateral ureteral obstruction, FA-Folic acid, and SO-Sodium oxalate). We constructed a potent multi-model AKI scRNA atlas containing 20 celltypes with 80,689 high-quality cells. The data suggest that compared to IRI and CP-AKI, FA- and SO-AKI exhibit injury characteristics more similar to UUO-AKI, which may due to tiny crystal-induced intrarenal obstruction. Through scRNA atlas, 7 different functional proximal tubular cell (PTC) subtypes were identified, we found that Maladaptive PTCs and classical Havcr1 PTCs but not novel Krt20 PTCs affect the pro-inflammatory and pro-fibrotic levels in different AKI models. And cell death and cytoskeletal remodeling events are widespread patterns of injury in PTCs. Moreover, we found that programmed cell death predominated in PTCs, whereas apoptosis and autophagy prevailed in the remaining renal tubules. We also identified S100a6 as a novel AKI-endothelial injury biomarker. Furthermore, we revealed that the dynamic and active immune (especially Arg1 Macro_2 cells) -parenchymal cell interactions are important features of AKI. Taken together, our study provides a potent resource for understanding the pathogenesis of AKI and early intervention in AKI progression at single-cell resolution.

Machine learning for the prediction of acute kidney injury in critical care patients with acute cerebrovascular disease.

PURPOSE: Acute kidney injury (AKI) is a common complication and associated with a poor clinical outcome. In this study, we developed and validated a model for predicting the risk of AKI through machine learning methods in critical care patients with acute cerebrovascular disease. METHODS: This study was a retrospective study based on two different cohorts. Five machine learning methods were used to develop AKI risk prediction models. We used six popular metrics (AUROC, F2-Score, accuracy, sensitivity, specificity and precision) to evaluate the performance of these models. RESULTS: We identified 2935 patients in the MIMIC-III database and 499 patients in our local database to develop and validate the AKI risk prediction model. The incidence of AKI in these two different cohorts was 18.3% and 61.7%, respectively. Analysis showed that several laboratory parameters (serum creatinine, hemoglobin, white blood cell count, bicarbonate, blood urea nitrogen, sodium, albumin, and platelet count), age, and length of hospital stay, were the top ten important factors associated with AKI. The analysis demonstrated that the XGBoost had higher AUROC (0.880, 95%CI: 0.831-0.929), indicating that the XGBoost model was better at predicting AKI risk in patients with acute cerebrovascular disease than other models. CONCLUSIONS: This study developed machine learning methods to identify critically ill patients with acute cerebrovascular disease who are at a high risk of developing AKI. This result suggested that machine learning techniques had the potential to improve the prediction of AKI risk models in critical care.

GSDME-mediated pyroptosis promotes inflammation and fibrosis in obstructive nephropathy.

Renal tubular cell (RTC) death and inflammation contribute to the progression of obstructive nephropathy, but its underlying mechanisms have not been fully elucidated. Here, we showed that Gasdermin E (GSDME) expression level and GSDME-N domain generation determined the RTC fate response to TNFα under the condition of oxygen-glucose-serum deprivation. Deletion of Caspase-3 (Casp3) or Gsdme alleviated renal tubule damage and inflammation and finally prevented the development of hydronephrosis and kidney fibrosis after ureteral obstruction. Using bone marrow transplantation and cell type-specific Casp3 knockout mice, we demonstrated that Casp3/GSDME-mediated pyroptosis in renal parenchymal cells, but not in hematopoietic cells, played predominant roles in this process. We further showed that HMGB1 released from pyroptotic RTCs amplified inflammatory responses, which critically contributed to renal fibrogenesis. Specific deletion of Hmgb1 in RTCs alleviated caspase11 and IL-1ß activation in macrophages. Collectively, our results uncovered that TNFα/Casp3/GSDME-mediated pyroptosis is responsible for the initiation of ureteral obstruction-induced renal tubule injury, which subsequentially contributes to the late-stage progression of hydronephrosis, inflammation, and fibrosis. This novel mechanism will provide valuable therapeutic insights for the treatment of obstructive nephropathy.

RIPK3 collaborates with GSDMD to drive tissue injury in lethal polymicrobial sepsis.

Sepsis is a systemic inflammatory disease causing life-threatening multi-organ dysfunction. Accumulating evidences suggest that two forms of programmed necrosis, necroptosis and pyroptosis triggered by the pathogen component lipopolysaccharide (LPS) and inflammatory cytokines, play important roles in the development of bacterial sepsis-induced shock and tissue injury. Sepsis-induced shock and tissue injury required receptor-interacting protein kinase-3 (RIPK3) and mixed lineage kinase domain-like protein (MLKL) phosphorylation, caspase11 activation and gasdermin D (GSDMD) cleavage. However, the synergistic effect of necroptosis and pyroptosis in the pathological progress of sepsis remains elusive. In this study, we found that blockage of both necroptosis and pyroptosis (double deletion of Ripk3/Gsdmd or Mlkl/Gsdmd) resulted in accumulative protection against septic shock, systemic blood clotting and multi-organ injury in mice. Bone marrow transplantation confirmed that necroptosis and pyroptosis in both myeloid and nonmyeloid cells are indispensable in the progression of sepsis-induced multi-organ injury. Both RIPK3 and GSDMD signaling collaborated to amplify necroinflammation and tissue factor release in macrophages and endothelial cells, which led to tissue injury. Furthermore, cell death induced by inflammatory cytokines and high-mobility group box 1 could be prevented by double ablation of Ripk3/Gsdmd or Mlkl/Gsdmd, suggesting that a positive feedback loop interconnecting RIPK3/MLKL and GSDMD machinery and inflammation facilitated sepsis progression. Collectively, our findings demonstrated that RIPK3-mediated necroptosis and GSDMD-mediated pyroptosis collaborated to amply inflammatory signaling and enhance tissue injury in the process of sepsis, which may shed new light on two potential targets of combined therapeutic interventions for this highly lethal disorder.