Comparison of Circulating Biomarkers in Predicting Diabetic Kidney Disease Progression With Autoantibodies to Erythropoietin Receptor

Association between Anti-Erythropoietin Receptor Antibodies and Cardiac Function in Patients on Hemodialysis: A Multicenter Cross-Sectional Study

Cardiac dysfunction is an important prognostic predictor of cardiovascular mortality in patients on hemodialysis (HD). Erythropoietin (EPO) has been reported to improve cardiac function by binding to the EPO receptor (EPOR) on cardiomyocytes. This study investigated whether anti-EPOR antibodies were associated with left ventricular cardiac function in patients undergoing HD. This multicenter, cross-sectional observational study included 377 patients (median age, 70 years; 267 (70.8%) males) with chronic kidney disease (CKD) undergoing stable maintenance HD. Serum levels of anti-EPOR antibodies were measured, and echocardiography was used to assess the left ventricular mass index (LVMI) and left ventricular ejection fraction (LVEF). Anti-EPOR antibodies were found in 17 patients (4.5%). LVMI was greater (median of 135 g/m2 vs. 115 g/m2, p = 0.042), and the prevalence of LVEF < 50% was higher (35.3% vs. 15.6%, p = 0.032) in patients with anti-EPOR antibodies than in those without. Multivariable linear regression and logistic regression analysis (after adjusting for known risk factors of heart failure) revealed that anti-EPOR antibodies were independently associated with LVMI (coefficient 16.2%; 95% confidence interval (CI) 1.0−35.0%, p = 0.043) and LVEF <50% (odds ratio 3.20; 95% CI 1.05−9.73, p = 0.041). Thus, anti-EPOR antibody positivity was associated with left ventricular dysfunction in patients undergoing HD.

The Signaling Pathway of TNF Receptors: Linking Animal Models of Renal Disease to Human CKD

Chronic kidney disease (CKD) has been recognized as a global public health problem. Despite the current advances in medicine, CKD-associated morbidity and mortality remain unacceptably high. Several studies have highlighted the contribution of inflammation and inflammatory mediators to the development and/or progression of CKD, such as tumor necrosis factor (TNF)-related biomarkers. The inflammation pathway driven by TNF-α, through TNF receptors 1 (TNFR1) and 2 (TNFR2), involves important mediators in the pathogenesis of CKD. Circulating levels of TNFRs were associated with changes in other biomarkers of kidney function and injury, and were described as predictors of disease progression, cardiovascular morbidity, and mortality in several cohorts of patients. Experimental studies describe the possible downstream signaling pathways induced upon TNFR activation and the resulting biological responses. This review will focus on the available data on TNFR1 and TNFR2, and illustrates their contributions to the pathophysiology of kidney diseases, their cellular and molecular roles, as well as their potential as CKD biomarkers. The emerging evidence shows that TNF receptors could act as biomarkers of renal damage and as mediators of the disease. Furthermore, it has been suggested that these biomarkers could significantly improve the discrimination of clinical CKD prognostic models.

Trajectories of kidney function in diabetes: a clinicopathological update

Diabetic nephropathy has been traditionally diagnosed based on persistently high albuminuria and a subsequent decline in glomerular filtration rate (GFR), which is widely recognized as the classical phenotype of diabetic kidney disease (DKD). Several studies have emphasized that trajectories of kidney function in patients with diabetes (specifically, changes in GFR and albuminuria over time) can differ from this classical DKD phenotype. Three alternative DKD phenotypes have been reported to date and are characterized by albuminuria regression, a rapid decline in GFR, or non-proteinuric or non-albuminuric DKD. Although kidney biopsies are not typically required for the diagnosis of DKD, a few studies of biopsy samples from patients with DKD have demonstrated that changes in kidney function associate with specific histopathological findings in diabetes. In addition, various clinical and biochemical parameters are related to trajectories of GFR and albuminuria. Collectively, pathological and clinical characteristics can be used to predict trajectories of GFR and albuminuria in diabetes. Furthermore, cohort studies have suggested that the risks of kidney and cardiovascular outcomes might vary among different phenotypes of DKD. A broader understanding of the clinical course of DKD is therefore crucial to improve risk stratification and enable early interventions that prevent adverse outcomes.

An Aging-Related Gene Signature-Based Model for Risk Stratification and Prognosis Prediction in Lung Adenocarcinoma

Aging is an inevitable time-dependent process associated with a gradual decline in many physiological functions. Importantly, some studies have supported that aging may be involved in the development of lung adenocarcinoma (LUAD). However, no studies have described an aging-related gene (ARG)-based prognosis signature for LUAD. Accordingly, in this study, we analyzed ARG expression data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). After LASSO and Cox regression analyses, a six ARG-based signature (APOC3, EPOR, H2AFX, MXD1, PLCG2, and YWHAZ) was constructed using TCGA dataset that significantly stratified cases into high- and low-risk groups in terms of overall survival (OS). Cox regression analysis indicated that the ARG signature was an independent prognostic factor in LUAD. A nomogram based on the ARG signature and clinicopathological factors was developed in TCGA cohort and validated in the GEO dataset. Moreover, to visualize the prediction results, we established a web-based calculator yurong.shinyapps.io/ARGs_LUAD/. Calibration plots showed good consistency between the prediction of the nomogram and actual observations. Receiver operating characteristic curve and decision curve analyses indicated that the ARG nomogram had better OS prediction and clinical net benefit than the staging system. Taken together, these results established a genetic signature for LUAD based on ARGs, which may promote individualized treatment and provide promising novel molecular markers for immunotherapy.