Are short-term complications associated with poor allograft and patient survival after liver transplantation? A systematic review of the literature and expert panel recommendations

Gp78 deficiency in hepatocytes alleviates hepatic ischemia-reperfusion injury via suppressing ACSL4-mediated ferroptosis

Ferroptosis, which is driven by iron-dependent lipid peroxidation, plays an essential role in liver ischemia-reperfusion injury (IRI) during liver transplantation (LT). Gp78, an E3 ligase, has been implicated in lipid metabolism and inflammation. However, its role in liver IRI and ferroptosis remains unknown. Here, hepatocyte-specific gp78 knockout (HKO) or overexpressed (OE) mice were generated to examine the effect of gp78 on liver IRI, and a multi-omics approach (transcriptomics, proteomics, and metabolomics) was performed to explore the potential mechanism. Gp78 expression decreased after reperfusion in LT patients and mice with IRI, and gp78 expression was positively correlated with liver damage. Gp78 absence from hepatocytes alleviated liver damage in mice with IRI, ameliorating inflammation. However, mice with hepatic gp78 overexpression showed the opposite phenotype. Mechanistically, gp78 overexpression disturbed lipid homeostasis, remodeling polyunsaturated fatty acid (PUFA) metabolism, causing oxidized lipids accumulation and ferroptosis, partly by promoting ACSL4 expression. Chemical inhibition of ferroptosis or ACSL4 abrogated the effects of gp78 on ferroptosis and liver IRI. Our findings reveal a role of gp78 in liver IRI pathogenesis and uncover a mechanism by which gp78 promotes hepatocyte ferroptosis by ACSL4, suggesting the gp78-ACSL4 axis as a feasible target for the treatment of IRI-associated liver damage.

Development of a nomogram for the prediction of acute kidney injury after liver transplantation: a model based on clinical parameters and postoperative cystatin C level

BACKGROUND

Acute kidney injury (AKI) is common after liver transplantation (LT). We developed a nomogram model to predict post-LT AKI.

METHODS

A total of 120 patients were eligible for inclusion in the study. Clinical information was extracted from the institutional electronic medical record system. Blood samples were collected prior to surgery and immediately after surgery. Univariable and multivariate logistic regression were used to identify independent risk factors. Finally, a nomogram was developed based on the final multivariable logistic regression model.

RESULTS

In total, 58 (48.3%) patients developed AKI. Multivariable logistic regression revealed four independent risk factors for post-LT AKI: operation duration [odds ratio (OR) = 1.728, 95% confidence interval (CI) = 1.121-2.663, p = 0.013], intraoperative hypotension (OR = 3.235, 95% CI = 1.316-7.952, p = 0.011), postoperative cystatin C level (OR = 1.002, 95% CI = 1.001-1.004, p = 0.005) and shock (OR = 4.002, 95% CI = 0.893-17.945, p = 0.070). Receiver operating characteristic curve analysis was used to evaluate model discrimination. The area under the curve value was 0.815 (95% CI = 0.737-0.894).

CONCLUSION

The model based on combinations of clinical parameters and postoperative cystatin C levels had a higher predictive performance for post-LT AKI than the model based on clinical parameters or postoperative cystatin C level alone. Additionally, we developed an easy-to-use nomogram based on the final model, which could aid in the early detection of AKI and improve the prognosis of patients after LT.