Pathological patterns of primary nephrotic syndrome in Central China: a retrospective study of 627 cases

Primary glomerular nephropathy among hospitalized patients in a national database in China

Background

Primary glomerular nephropathy (PGN) is a leading cause of end-stage renal disease in developing countries, however, nationwide studies investigating the spectrum of PGN are limited.

Methods

To evaluate the composition of various pathological types of PGN in a comprehensive geographic coverage in China, a national inpatient database covering 43.7 million patients was used in this analysis. Diagnoses were extracted from the discharge diagnoses.

Results

The percentage of patients with PGN in hospitalized patients decreased from 0.80% in 2010 to 0.67% in 2015. Among hospitalized patients with PGN, a decreasing trend of immunoglobulin A nephropathy (from 19.0% in 2010 to 10.6% in 2015) and an increasing trend of idiopathic membranous nephropathy (from 4.5% in 2010 to 8.8% in 2015) were revealed. A positive association between the percentage of idiopathic membranous nephropathy (iMN) and the exposure of particulate matter with a diameter < 2.5 μm was observed north of the Yangtze River (P < 0.001, R2 = 0.828). South of the Yangtze River, the proportion of the Zhuang population was positively correlated to the frequency of iMN (P = 0.012, r = 0.697).

Conclusions

In conclusion, a changing spectrum of PGN was observed between 2010 and 2015 in China and both environmental and genetic factors might play pivotal roles in the pathogenesis of iMN in the Chinese population.

A pilot and comparative study between pathological and serological levels of immunoglobulin and complement among three kinds of primary glomerulonephritis

Background

Immunoglobulin A nephropathy (IgAN), membranous nephropathy (MN) and minimal-change disease (MCD) are three common types of glomerulonephritis in China. Pathological diagnosis based on renal biopsy is the criterion and the golden standard for diagnosing the sub-types of primary or secondary glomerulonephritis. Immunoglobulin and complements might be used in the differential diagnosis of glomerulonephritis without renal biopsies. However, the relationship between IF intensities of immune proteins and the corresponding serum levels remained unclear, and seldom studies combine histopathological examination results and blood tests together for a predictive purpose. This study was considered as a pilot study for integrating histopathological indicators into serum parameters for exploring the relationship of IF intensity and serum values of immunoglobulin and complement, and for screening and investigating effective indicators inIgAN, MN and MCD.

Methods

Renal tissue immunofluorescence (IF) intensity grades and serum levels of immunoglobulin and complements (IgG, IgA, IgM, C3 and C4) were retrospectively analyzed in 236 cases with IgAN, MN or MCD. IF grades were grouped as negative (−), positive (+) or strong positive (++) with both high and low magnification of microscope. Other serum indicators such as urea nitrogen (BUN), creatinine (Crea) and estimated glomerular filtration rate (eGFR) were also evaluated among the groups.

Results

There were difference in IgA, IgG and C3 IF intensity grades among IgAN, MN and MCD groups (p = 9.82E-43, 4.60E-39, 7.45E-15, respectively). Serum values of BUN, Crea, eGFR, IgG, IgA, IgM and C4 showed difference in three groups (BUN: p = 0.045, Crea: p = 3.45E-5, eGFR: p = 0.005, IgG: p = 1.68E-14, IgA: p = 9.14E-9, IgM: p = 0.014, C4: p = 0.026). eGFR had the trend to decrease with enhanced IgA IF positive grades (p = 8.99E-4); Crea had trends to decrease with both enhanced IgA and IgG IF intensity grades (p = 2.06E-6, 2.94E-5, respectively). In all subjects, serum IgA levels was inversely correlated with eGFR(r = − 0.216, p = 0.001) and correlated with Crea levels(r = 0.189, p = 0.004); serum IgG and Crea showed no correlation which were discordance with inverse correlation of IgG IF grade and Crea(r = 0.058,p = 0.379). IgG serum level was inverse correlated with its IF grades (p = 3.54E-5, p = 7.08E-6, respectively); C3 serum levels had significantly difference between Neg and positive (+) group (p = 0.0003). IgA serum level was positive correlated with its IF grades (Neg-(+): p = 0.0001; (+)-(++): p = 0.022; Neg-(++): p = 2.01E-10). After matching comparison among C3 groups, C3 Neg. group and C3 ++ group had difference (*p = 0.017). C4 had all negative IF expression in all pathological groups. In IgAN subjects, there were statistical differences of serum C3 levels between its pathological Neg and positive (+) group(p = 0.026), and serum IgA levels showed difference between IgA pathological positive(+) and (++)(p = 0.007). In MN subjects, sIgG levels showed difference between IgG pathological IF grade positive (+) and (++)(p = 0.044); serum C3 levels showed difference between C3 pathological IF grade Neg and positive(+)(p = 0.005); and serum IgA levels showed difference between Neg and positive(+)(p = 0.040). In IgAN, eGFR showed serum IgA levels had significant differences among groups (p = 0.007) and had increasing trend with enhanced its IF grades(P_trend = 0.016). There were also difference between IgG group Neg and positive (+) (p = 0.005, P_trend = 0.007) in IgAN. In MN, serum IgG levels had significant differences among IF groups (p = 0.034) and had decreasing trend with its enhanced IF grades (P_trend = 0.014). Serum C3 concentrations also were found distinctive among IF groups (p = 0.016) and had in inverse correlation with its enhanced IF grades (P_trend = 0.004).

Discussion

Our research cross contrasts several immunoprotein IF intensities and relevant serum levels in three kinds of primary glomerular nephritis, and finally acquired helpful results for understanding the relationships between pathological presentation and serological presentation of immunoproteins in kidney diseases. Furthermore, this pilot study is offering a possible method for the analysis of combination of pathology and serology.

Conclusion

Different pathological types of nephritis presented different expression patterns of immunoglobulin and complement, especially IgA and IgG, which suggested different pathogenesis involved in the development of IgAN and MN. Furthermore, either in tissue or in serum, increased IgA level was closely related with renal function in all of the patients.

Electronic supplementary material

The online version of this article (10.1186/s12865-018-0254-z) contains supplementary material, which is available to authorized users.

A diagnostic model for minimal change disease based on biological parameters

Background

Minimal change disease (MCD) is a kind of nephrotic syndrome (NS). In this study, we aimed to establish a mathematical diagnostic model based on biological parameters to classify MCD.

Methods

A total of 798 NS patients were divided into MCD group and control group. The comparison of biological indicators between two groups were performed with t-tests. Logistic regression was used to establish the diagnostic model, and the diagnostic value of the model was estimated using receiver operating characteristic (ROC) analysis.

Results

Thirteen indicators including Anti-phospholipase A2 receptor (anti-PLA2R) (P = 0.000), Total protein (TP) (P = 0.000), Albumin (ALB) (P = 0.000), Direct bilirubin (DB) (P = 0.002), Creatinine (Cr) (P = 0.000), Total cholesterol (CH) (P = 0.000), Lactate dehydrogenase (LDH) (P = 0.007), High density lipoprotein cholesterol (HDL) (P = 0.000), Low density lipoprotein cholesterol (LDL) (P = 0.000), Thrombin time (TT) (P = 0.000), Plasma fibrinogen (FIB) (P = 0.000), Immunoglobulin A (IgA) (P = 0.008) and Complement 3 (C3) (P = 0.019) were significantly correlated with MCD. Furthermore, the area under ROC curves of CH, HDL, LDL, TT and FIB were more than 0.70. Logistic analysis demonstrated that CH and TT were risk factors for MCD. According to the ROC of “CH+TT”, the AUC was 0.827, with the sensitivity of 83.0% and the specificity of 69.8% (P = 0.000).

Conclusion

The established diagnostic model with CH and TT could be used for classified diagnosis of MCD.

Biopsy-Free Prediction of Pathologic Type of Primary Nephrotic Syndrome Using a Machine Learning Algorithm

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.