New biomarkers in acute kidney injury

Nanoparticles transfected with plasmid-encoded lncRNA-OIP5-AS1 inhibit renal ischemia-reperfusion injury in mice via the miR-410-3p/Nrf2 axis

Nanostructures composed of liposomes and polydopamine (PDA) have demonstrated efficacy as carriers for delivering plasmids, effectively alleviating renal cell carcinoma. However, their role in acute kidney injury (AKI) remains unclear. This study aimed to investigate the effects of the plasmid-encoded lncRNA-OIP5-AS1@PDA nanoparticles (POP-NPs) on renal ischemia/reperfusion (RI/R) injury and explore the underlying mechanisms. RI/R or OGD/R models were established in mice and HK-2 cells, respectively. In vivo, vector or POP-NPs were administered (10 nmol, IV) 48 h after RI/R treatment. In the RI/R mouse model, the OIP5-AS1 and Nrf2/HO-1 expressions were down-regulated, while miR-410-3p expression was upregulated. POP-NPs treatment effectively reversed RI/R-induced renal tissue injury, restoring altered levels of blood urea nitrogen, creatinine, malondialdehyde, inflammatory factors (IL-8, IL-6, TNF-α), ROS, apoptosis, miR-410-3p, as well as the suppressed expression of SOD and Nrf2/HO-1 in the model mice. Similar results were obtained in cell models treated with POP-NPs. Additionally, miR-410-3p mimics could reverse the effects of POP-NPs on cellular models, partially counteracted by Nrf2 agonists. The binding relationship between OIP5-AS1 and miR-410-3p, alongside miR-410-3p and Nrf2, has been substantiated by dual-luciferase reporter and RNA pull-down assays. The study revealed that POP-NPs can attenuate RI/R-induced injury through miR-410-3p/Nrf2 axis. These findings lay the groundwork for future targeted therapeutic approaches utilizing nanoparticles for RI/R-induced AKI.

Multi-parametric MRI-based machine learning model for prediction of pathological grade of renal injury in a rat kidney cold ischemia-reperfusion injury model

BACKGROUND

Renal cold ischemia-reperfusion injury (CIRI), a pathological process during kidney transplantation, may result in delayed graft function and negatively impact graft survival and function. There is a lack of an accurate and non-invasive tool for evaluating the degree of CIRI. Multi-parametric MRI has been widely used to detect and evaluate kidney injury. The machine learning algorithms introduced the opportunity to combine biomarkers from different MRI metrics into a single classifier.

OBJECTIVE

To evaluate the performance of multi-parametric magnetic resonance imaging for grading renal injury in a rat model of renal cold ischemia-reperfusion injury using a machine learning approach.

METHODS

Eighty male SD rats were selected to establish a renal cold ischemia -reperfusion model, and all performed multiparametric MRI scans (DWI, IVIM, DKI, BOLD, T1mapping and ASL), followed by pathological analysis. A total of 25 parameters of renal cortex and medulla were analyzed as features. The pathology scores were divided into 3 groups using K-means clustering method. Lasso regression was applied for the initial selecting of features. The optimal features and the best techniques for pathological grading were obtained. Multiple classifiers were used to construct models to evaluate the predictive value for pathology grading.

RESULTS

All rats were categorized into mild, moderate, and severe injury group according the pathologic scores. The 8 features that correlated better with the pathologic classification were medullary and cortical Dp, cortical T2*, cortical Fp, medullary T2*, ∆T1, cortical RBF, medullary T1. The accuracy(0.83, 0.850, 0.81, respectively) and AUC (0.95, 0.93, 0.90, respectively) for pathologic classification of the logistic regression, SVM, and RF are significantly higher than other classifiers. For the logistic model and combining logistic, RF and SVM model of different techniques for pathology grading, the stable and perform are both well. Based on logistic regression, IVIM has the highest AUC (0.93) for pathological grading, followed by BOLD(0.90).

CONCLUSION

The multi-parametric MRI-based machine learning model could be valuable for noninvasive assessment of the degree of renal injury.

Selenoprotein-P1 (SEPP1) Expression in Human Proximal Tubule Cells after Ischemia-Reperfusion Injury: An In Vitro Model

Background and Objectives: Selenium deficiency represents a risk factor for the occurrence of severe diseases, such as acute kidney injury (AKI). Recently, selenoprotein-p1 (SEPP1), a selenium transporter, mainly released by the liver, has emerged as a promising plasmatic biomarker of AKI as a consequence of cardio-surgery operations. The aim of the present study was to investigate, on an in vitro model of hypoxia induced in renal tubular cells, HK-2, the effects of sodium selenite (Na2SeO3) and to evaluate the expression of SEPP1 as a marker of injury. Materials and Methods: HK-2 cells were pre-incubated with 100 nM Na2SeO3 for 24 h, and then, treated for 24 h with CoCl2 (500 µM), a chemical hypoxia inducer. The results were derived from an ROS assay, MTT, and Western blot analysis. Results: The pre-treatment determined an increase in cells' viability and a reduction in reactive oxygen species (ROS), as shown by MTT and the ROS assay. Moreover, by Western blot an increase in SEPP1 expression was observed after hypoxic injury as after adding sodium selenite. Conclusions: Our preliminary results shed light on the possible role of selenium supplementation as a means to prevent oxidative damage and to increase SEPP1 after acute kidney injury. In our in vitro model, SEPP1 emerges as a promising biomarker of kidney injury, although further studies in vivo are necessary to validate our findings.

Pharmacotherapy considerations in patients who develop acute kidney injury during anti-cancer therapy

INTRODUCTION

Acute kidney injury (AKI) frequently develops in patients receiving cancer therapy and requires a wide differential diagnosis due to possible role of unique cancer and drug-related factors, in addition to common pre- and post-renal causes. Rapid development of new molecular targeted anti-cancer drugs and immunotherapies has opened unprecedented possibilities of treatment at the price of an increased spectrum of renal side effects.

AREAS COVERED

The present review aims at providing a state-of-the-art picture of AKI in cancer patient (PubMed and Embase libraries were searched from inception to January 2024), with a focus on differential diagnosis and management of diverse clinical settings. Reports of parenchymal AKI due to glomerular, microvascular, tubular and interstitial damage have been constantly increasing. Complex electrolyte and acid-base disorders can coexist. The role of renal biopsy and possible therapeutic approaches are also discussed.

EXPERT OPINION

Onconephrology has become an important subspecialty of clinical nephrology, requiring constantly updated skills and a high degree of interdisciplinary integration to tackle diagnostic challenges and even therapeutic and ethical dilemmas. Integrated onconephrological guidelines and availability of biomarkers may provide new tools for management of this unique type of patients in the near future.

SAH and SAM/SAH ratio associate with acute kidney injury in critically ill patients: A case-control study

BACKGROUND

Acute kidney injury (AKI) is a serious clinical emergency with an acute onset, rapid progression and poor prognosis, which has high morbidity and mortality in hospitalized patients. DNA methylation plays an important role in the occurrence and progression of kidney disease, and aberrant methylation and certain altered methylation-related metabolites have been reported in AKI patients. However, the specific alterations of methylation-related metabolites in the AKI patients were not investigated clearly.

METHOD

In this study, 61 AKI and 61 matched non-AKI inpatients were recruited after propensity score matching the age and hypertension. And 11 methylation-related metabolites in the plasma and urine of the two groups were quantified by using UHPLC-MS/MS method.

RESULTS

Certain methylation-relate intermediates were up-regulated in the plasma (choline, trimethylamine N-oxide (TMAO), trimethyl lysine (TML), S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH)) and down-regulated in the urine of AKI inpatients (choline, betaine, TMAO, dimethylglycine (DMG), SAM and taurine). The correlation analysis revealed a relatively strong correlation between plasma SAH, SAM/SAH ratio and renal function index (serum creatinine (SCr) and estimated glomerular filtration rate (eGFR), r = 0.523-0.616), and the correlation of urinary intermediates with renal function index was weaker than that in the plasma. Furthermore, receiver operating characteristic (ROC) analysis showed that plasma SAH and urinary SAM/SAH ratio represented the best distinguishing efficiency with AUC 0.844 and 0.794, respectively. Moreover, the findings of binary regression analysis demonstrated plasma choline, TMAO, TML, SAM and SAH were the risk markers of AKI (up-regulation in plasma, OR > 1), urinary choline, betaine, TMAO, DMG and SAM were protective markers of AKI (down-regulation in urine, OR < 1), and SAM/SAH ratio was a protective marker in plasma and urine (down-regulation in both two biofluids, OR = 0.510, 0.383-0.678 in plasma, OR = 0.904, 0.854-0.968 in urine), indicating the increased risk of AKI when combined with the alteration of plasma and urinary levels.

CONCLUSION

The comprehensive analysis of plasma and urine samples from AKI inpatients offers a more extensive assessment of methylated metabolic alterations, suggesting a close relationship between AKI stress and altered methylation ability. The plasma level of SAH and SAM/SAH ratio and urinary SAM/SAH ratio both showed a strong correlation with renal function (SCr and eGFR) and good accuracy for distinguishing AKI in the two biomatrices, which exhibited promising prospects in predicting renal function decline and providing further information for the pathogenesis of AKI.