Background: Chronic kidney disease (CKD) leads to end-stage renal failure and cardiovascular events. An attribute to these progressions is abnormalities in inflammation, which can be evaluated using the neutrophil-to-lymphocyte ratio (NLR). We aimed to investigate the association of NLR with the progression of end stage of renal disease (ESRD), cardiovascular disease (CVD) and all-cause mortality in Chinese patients with stages 1–4 CKD. Methods: Patients with stages 1–4 CKD (18–74 years of age) were recruited at 39 centers in 28 cities across 22 provinces in China since 2011. A total of 938 patients with complete NLR and other relevant clinical variables were included in the current analysis. Cox regression analysis was used to estimate the association between NLR and the outcomes including ESRD, CVD events or all-cause mortality. Results: Baseline NLR was related to age, hypertension, serum triglycerides, total serum cholesterol, CVD history, urine albumin to creatinine ratio (ACR), chronic kidney disease-mineral and bone disorder (CKD-MBD), hyperlipidemia rate, diabetes, and estimated glomerular filtration rate (eGFR). The study duration was 4.55 years (IQR 3.52–5.28). Cox regression analysis revealed an association of NLR and the risk of ESRD only in patients with stage 4 CKD. We did not observe any significant associations between abnormal NLR and the risk of either CVD or all-cause mortality in CKD patients in general and CKD patients grouped according to the disease stages in particular. Conclusion: Our results suggest that NLR is associated with the risk of ESRD in Chinese patients with stage 4 CKD. NLR can be used in risk assessment for ESRD among patients with advanced CKD; this application is appealing considering NLR being a routine test. Trial registration ClinicalTrials.gov Identifier NCT03041987. Registered January 1, 2012. (retrospectively registered) (https://www.clinicaltrials.gov/ct2/show/NCT03041987?term=Chinese+Cohort+Study+of+Chronic+Kidney+Disease+%28C-STRIDE%29&rank=1)

Membranous nephropathy (MN) is an autoimmune disease of the kidney glomerulus and one of the leading causes of nephrotic syndrome. The disease exhibits heterogenous outcomes with approximately 30% of cases progressing to end-stage renal disease. The clinical management of MN has steadily advanced owing to the identification of autoantibodies to the phospholipase A2 receptor (PLA2R) in 2009 and thrombospondin domain-containing 7A (THSD7A) in 2014 on the podocyte surface. Approximately 50–80% and 3–5% of primary MN (PMN) cases are associated with either anti-PLA2R or anti-THSD7A antibodies, respectively. The presence of these autoantibodies is used for MN diagnosis; antibody levels correlate with disease severity and possess significant biomarker values in monitoring disease progression and treatment response. Importantly, both autoantibodies are causative to MN. Additionally, evidence is emerging that NELL-1 is associated with 5–10% of PMN cases that are PLA2R- and THSD7A-negative, which moves us one step closer to mapping out the full spectrum of PMN antigens. Recent developments suggest exostosin 1 (EXT1), EXT2, NELL-1, and contactin 1 (CNTN1) are associated with MN. Genetic factors and other mechanisms are in place to regulate these factors and may contribute to MN pathogenesis. This review will discuss recent developments over the past 5 years.

Vascular calcification (VC) is a major cause of mortality in patients with chronic kidney disease (CKD). While elevations in serum phosphorus contribute to VC, we provide evidence here for a major role of oxidative stress (OS) in VC pathogenesis without an apparent increase in serum phosphorus in early CKD. In a rat model for stage 5 CKD (CKD5), we observed 1) robust increases of VC and OS, 2) significant reductions of smooth muscle 22 alpha (SM22α) and calponin, and 3) upregulations in Runt-related transcription factor 2 (RUNX2) and collagen I in vascular smooth muscle cells (VSMCs). Inhibition of OS using MnTMPyP dramatically reduced these events without normalization of hyperphosphatemia. In CKD5 patients with VC (n = 11) but not in those without VC (n = 13), OS was significantly elevated. While the serum levels of calcium and phosphate were not altered in the animal model for early stage CKD (ECKD), OS, VC, SM22α, calponin, RUNX2, collagen I and NADPH oxidase 1 (NOX1) in VSMCs were all significantly changed. More importantly, serum (5%) derived from patients with ECKD (n = 30) or CKD5 (n = 30) induced SM22α and calponin downregulation, and RUNX2, collagen I, NOX1 upregulation along with a robust elevation of OS and calcium deposition in primary rat VSMCs. These alterations were all reduced by MnTMPyP, ML171 (a NOX1 inhibitor), and U0126 (an inhibitor of Erk signaling). Collectively, we provide a comprehensive set of evidence supporting an important role of OS in promoting VC development in CKD patients (particularly in those with ECKD); this was at least in part through induction of osteoblastic transition in VSMCs which may involve the Erk singling. Our research thus suggests that reductions in OS may prevent VC in CKD patients.

Background: Clear cell renal cell carcinoma (ccRCC), which is the most prevalent type of renal cell carcinoma, has a high mortality rate. Lipid metabolism reprogramming is a hallmark of ccRCC progression, but its specific mechanism remains unclear. Here, the relationship between dysregulated lipid metabolism genes (LMGs) and ccRCC progression was investigated.Methods: The ccRCC transcriptome data and patients’ clinical traits were obtained from several databases. A list of LMGs was selected, differentially expressed gene screening performed to detect differential LMGs, survival analysis performed, a prognostic model established, and immune landscape evaluated using the CIBERSORT algorithm. Gene Set Variation Analysis and Gene set enrichment analysis were conducted to explore the mechanism by which LMGs affect ccRCC progression. Single-cell RNA-sequencing data were obtained from relevant datasets. Immunohistochemistry and RT-PCR were used to validate the expression of prognostic LMGs.Results: Seventy-one differential LMGs were identified between ccRCC and control samples, and a novel risk score model established comprising 11 LMGs (ABCB4, DPEP1, IL4I1, ENO2, PLD4, CEL, HSD11B2, ACADSB, ELOVL2, LPA, and PIK3R6); this risk model could predict ccRCC survival. The high-risk group had worse prognoses and higher immune pathway activation and cancer development.Conclusion: Our results showed that this prognostic model can affect ccRCC progression.

Chronic kidney disease (CKD) is a major public health burden around the world. The gut microbiome may contribute to CKD progression and serve as a promising therapeutic target. Colonic dialysis has long been used in China to help remove gut-derived toxins to delay CKD progression. Since disturbances in the gut biome may influence disease progression, we wondered whether colonic dialysis may mitigate the condition by influencing the biome. We compared the gut microbiota, based on 16S rRNA gene sequencing, in fecal samples of 25 patients with CKD (stages 3–5) who were receiving colonic dialysis(group CD), 25 outpatients with CKD not receiving colonic dialysis(group OP), and 34 healthy subjects(group HS). Richness of gut microbiota was similar between patients on colonic dialysis and healthy subjects, and richness in these two groups was significantly higher than that in patients not on colonic dialysis. Colonic dialysis also altered the profile of microbes in the gut of CKD patients, bringing it closer to the profile in healthy subjects. Colonic dialysis may protect renal function in pre-dialysis CKD by mitigating dysbiosis of gut microbiota.

Background/Aims: Renal biopsy is the gold standard to determine the pathologic type of primary nephrotic syndrome, which is critical for diagnosis, choice of treatment and evaluation of prognosis. However, in some cases, renal biopsy cannot be performed. Methods: To explore the possibility of predicting the histology type of primary nephrotic syndrome without the need for biopsy, we trained and validated a machine learning algorithm using data from 222 patients with biopsy-confirmed primary nephrotic syndrome treated at our hospital between May 2008 and January 2016. The model was then tested prospectively on another sample of 63 patients with biopsy-confirmed primary nephrotic syndrome. Results: Overall accuracy of prediction from the retrospective set of 222 patients was 62.2% across all types of nephrotic syndrome. The accuracy of model prediction for the prospectively collected dataset of 63 patients was 61.9%. The algorithm identified 17 of 33 variables as contributing strongly to type of renal pathology. Conclusion: To our knowledge, this is the first such application of machine learning to predict the pathologic type of primary nephrotic syndrome, which may be clinically useful by itself as well as helpful for guiding future efforts at machine learning-based prediction in other disease contexts.