BackgroundFamily members of patients with end stage renal disease were reported to have an increased prevalence of chronic kidney disease (CKD). However, studies differentiated genetic and non-genetic family members are limited. We sought to investigate the prevalence of CKD among fist-degree relatives and spouses of dialysis patients in China.MethodsSeventeen dialysis facilities from 4 cities of China including 1062 first-degree relatives and 450 spouses of dialysis patients were enrolled. Sex- and age- matched controls were randomly selected from a representative sample of general population in Beijing. CKD was defined as decreased estimated glomerular (eGFR < 60 mL/min/1.73 m2) or albuminuria.ResultsThe prevalence of eGFR less than 60 mL/min/1.73 m2, albuminuria and the overall prevalence of CKD in dialysis spouses were compared with their counterpart controls, which was 3.8% vs. 7.8% (P < 0.01), 16.8% vs. 14.6% (P = 0.29) and 18.4% vs. 19.8% (P = 0.61), respectively. The prevalence of eGFR less than 60 mL/min/1.73 m2, albuminuria and the overall prevalence of CKD in dialysis relatives were also compared with their counterpart controls, which was 1.5% vs. 2.4% (P = 0.12), 14.4% vs. 8.4% (P < 0.01) and 14.6% vs. 10.5% (P < 0.01), respectively. Multivariable Logistic regression analysis indicated that being spouses of dialysis patients is negatively associated with presence of low eGFR, and being relatives of dialysis patients is positively associated with presence of albuminuria.ConclusionsThe association between being family members of dialysis patients and presence of CKD is different between first-degree relatives and spouses. The underlying mechanisms deserve further investigation.

Membranous nephropathy is typically classified as idiopathic and secondary, but nowadays the number of atypical membranous nephropathy (aMN) is increasing, many of which cannot determine its etiology in China. In this study, we compared the clinical and pathological characteristics of idiopathic membranous nephropathy (iMN) with aMN with unknown etiology from a single center in China.We retrospectively reviewed the clinical data of 577 patients with iMN and aMN at Peking University People's Hospital from January 2006 to December 2015 over a 10-year period, and analyzed their clinical and pathological characteristics. The level of serum phospholipase A2 receptors (PLA2R) antibody was detected in 106 iMN and 162 aMN patients.There were 278 iMN patients and 299 aMN patients who were included into this study in 3210 cases of renal biopsy during a 10-year period in our hospital. The average age of patients with iMN was significantly older than those with aMN (54.77 ± 13.01 vs 47.13 ± 16.16, P < .001). Around 75 patients (27%) were smokers in iMN patients, and 111 patients (37.1%) in aMN patients (P = .009). The mainly clinical manifestation of these 2 groups was nephrotic syndrome (61.5% in iMN group vs 58.4% in aMN group), but there were more patients accompanied with nephritis syndrome in aMN group than iMN group (17.1% vs 6.1%, P < .001). The immunofluorescence of renal biopsy showed “full house” in aMN group; and IgG subclass of the glomeruli demonstrated IgG4 (90.4%) was commonest in iMN group, but IgG1 (94.6%) in aMN group. 51 (48.1%) patients with iMN were detected positive PLA2R antibody in their serum, and 93 (57.4%) in aMN patients (P = .168). The patients with positive PLA2R antibody had higher positive rate of microscopic hematuria and urinary protein, lower albumin.The aMN patients are younger, higher smoking rate, its main clinical manifestation is nephrotic syndrome, but more of them accompanied with nephritis syndrome than those in iMN patients. Serum PLA2R antibody could not distinguish aMN from iMN. aMN could be a special glomerular disease in China, and need a further research on a larger scale.

Glomeruli instance segmentation from pathologic images is a fundamental step in the automatic analysis of renal biopsies. Glomerular histologic manifestations vary widely among diseases and cases, and several special staining methods are necessary for pathologic diagnosis. A robust model is needed to segment and classify glomeruli with different staining methods and apply in cases with various glomerular pathologic changes. Herein, pathologic images from renal biopsy slides stained with three basic special staining methods were used to build the data sets. The snapshot group included 1970 glomeruli from 516 patients, and the whole-slide image group included 8665 glomeruli from 148 patients. Cascade Mask region-based convolutional neural net architecture was trained to detect, classify, and segment glomeruli into three categories: i) GN, structural normal; ii) global sclerosis; and iii) glomerular with other lesions. In the snapshot group, total glomeruli, GN, global sclerosis, and glomerular with other lesions achieved an F1 score of 0.914, 0.896, 0.681, and 0.756, respectively, which were comparable with those in the whole-slide image group (0.940, 0.839, 0.806, and 0.753, respectively). Among the three categories, GN achieved the best instance segmentation effect in both groups, as determined by average precision, average recall, F1 score, and Mask mean Intersection over Union. The present model segments and classifies multistained glomeruli with efficiency and robustness. It can be applied as the first step for more detailed glomerular histologic analysis.