Serum Anti-PLA2R Antibody and Renal Complement Deposition: Associations with Clinicopathological Features in Primary Membranous Nephropathy

Serum Anti-PLA2R Antibody and Renal Complement Deposition: Associations with Clinicopathological Features in Primary Membranous Nephropathy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Serum Anti-PLA2R Antibody and Renal Complement Deposition: Associations with Clinicopathological Features in Primary Membranous Nephropathy Qianqian Xu, Jiayi Li, Cong Zhang, Min Tan, Wenge Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6637635/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The pathogenic roles of serum anti-phospholipase A2 receptor (PLA2R) antibodies and complement deposition in renal tissue remain incompletely understood in primary membranous nephropathy (PMN). This study aimed to evaluate their prevalence and associations with clinicopathological features and renal prognosis. Methods A retrospective analysis was conducted in 302 biopsy-proven PMN patients, stratified into anti-PLA2R antibody-positive (≥ 20 IU/mL, n = 136) and -negative (< 20 IU/mL, n = 166) groups. Baseline clinical data, renal histopathology, and follow-up outcomes were analyzed. Multivariate logistic regression and Cox proportional hazards models were applied to identify independent predictors of non-remission and renal dysfunction. Results Compared to antibody-negative patients, those with anti-PLA2R positivity had significantly higher proteinuria and serum cholesterol levels, lower albumin and IgG levels, and a higher rate of glomerular IgG4 deposition (all P < 0.01). Among 225 patients with follow-up data, the antibody-positive group exhibited more frequent renal dysfunction and increased use of immunosuppressive therapy. Stronger C3 deposition in renal tissue was associated with lower serum albumin and C3 levels, higher anti-PLA2R antibody titers, and more glomerulosclerosis. Multivariate analyses identified hypoalbuminemia and glomerulosclerosis as independent predictors of non-remission, while older age and intense C3 deposition independently predicted renal dysfunction. Conclusions Anti-PLA2R antibody positivity and prominent C3 deposition are associated with more severe clinical presentation and poorer renal outcomes in PMN. These findings highlight their potential as prognostic biomarkers and therapeutic targets. Primary membranous nephropathy anti-PLA2R antibody complement prognosis renal pathology Figures Figure 1 Introduction Membranous nephropathy (MN) is a leading cause of nephrotic syndrome (NS) in adults, accounting for 9.83–30% of primary glomerulonephritis in China [ 1 , 2 ]. Histologically, MN is characterized by subepithelial immune complex deposition and diffuse thickening of the glomerular basement membrane (GBM) observed by light microscopy [ 3 ]. While approximately 75% of MN cases are considered idiopathic or primary, the remaining cases are secondary to infections, autoimmune diseases, malignancies, or drug exposure [ 4 ]. Primary membranous nephropathy (PMN) is increasingly recognized as an autoimmune glomerular disease. The identification of circulating autoantibodies against the M-type phospholipase A2 receptor (PLA2R) on podocytes has transformed our understanding of PMN pathogenesis[ 5 ]. Anti-PLA2R antibodies are present in approximately 70–80% of patients with idiopathic MN and serving as a diagnostic biomarker and a predictor of disease activity and treatment response[ 6 ]. In addition to autoantibodies, complement activation is increasingly implicated in the pathophysiology of PMN. Despite the predominance of IgG4—an isotype traditionally considered incapable of activating the classical complement pathway—complement components such as C3 and C1q are frequently deposited in glomeruli. This paradox suggests that complement activation may occur through alternative or lectin pathways, contributing to podocyte injury and disease progression The clinical implications of complement deposition patterns in PMN remain incompletely defined. Although previous studies have reported associations between C3 deposition and more severe proteinuria or worse renal outcomes, the interaction between serum anti-PLA2R antibodies and complement components in renal tissue has not been fully elucidated. It also remains unclear whether the intensity of glomerular complement staining can serve as a prognostic indicator for long-term renal function. In this retrospective study, we aimed to investigate the relationships among serum anti-PLA2R antibody levels, glomerular deposition of complement components (particularly C3 and C1q), and the clinicopathological features and renal prognosis of patients with biopsy-proven PMN. By integrating clinical, serological, and pathological parameters, this study seeks to provide new insights into disease stratification and potential therapeutic targets in PMN. Materials and Methods Data Sources and Patient Cohort A total of 302 patients diagnosed with primary membranous nephropathy (PMN) via renal biopsy at our hospital were included in this study. The cohort comprised 186 males and 116 females, with a mean age of 47.9 ± 14.4 years. All patients were followed longitudinally from August 2016 to December 2022. Patient Selection Criteria The inclusion criteria were as follows: (1) renal histological and immunopathological findings consistent with PMN ; (2) exclusion of known secondary causes, including systemic lupus erythematosus, hepatitis B and C infections; (3) no history of exposure to non-steroidal anti-inflammatory drugs, gold compounds, penicillamine, or other potentially nephrotoxic agents; and (4) no prior exposure to organic solvents or mercury. This study was approved by the Ethics Committee of China-Japan Friendship Hospital (Approval No. 2019-17-K12). Clinical and Biological Data The following clinical parameters were collected for all patients with Primary membranous nephropathy (PMN): age, sex, 24-hour urinary protein excretion, serum albumin, creatinine, estimated glomerular filtration rate (eGFR), cholesterol, triglycerides, presence of hypertension or hematuria, serum immunoglobulin levels (IgG, IgA, IgM), complement components (C3, C4, C1q), and anti-PLA2R antibody levels. Renal biopsy specimens were assessed by immunofluorescence staining for IgG, IgA, IgM, C3, C1q, fibrin-related antigen (FRA), and IgG subclasses (IgG1–IgG4). Serum anti-PLA2R antibody levels were used to stratify patients into antibody-positive and antibody-negative groups based on a predefined threshold. Comparative analysis of clinical features and renal pathological findings was performed between the two groups to identify statistically significant differences. In addition, baseline and follow-up data were used to explore independent risk factors associated with non-remission and renal function deterioration. The eGFR was calculated using the CKD-EPI equation [ 7 ]. Analysis of Kidney Biopsies Percutaneous renal biopsy was performed in all cases, and kidney tissue specimens were collected in three parts for light microscopy, immunofluorescence, and electron microscopy. Light Microscopy : All specimens contained more than 10 glomeruli and were paraffin-embedded, sectioned at a thickness of 2 µm, and stained with hematoxylin-eosin (HE), periodic acid–Schiff (PAS), periodic acid–silver methenamine (PASM), and Masson's trichrome. Immunofluorescence : Frozen sections were analyzed by direct immunofluorescence for the presence of IgG, IgA, IgM, C3, C1q, fibrin-related antigen (FRA), and IgG subclasses (IgG1, IgG2, IgG3, and IgG4). Electron Microscopy : All kidney biopsy specimens were sent to the electron microscopy laboratory of the China-Japan Friendship Hospital for further examination. Renal pathological classification and diagnosis were conducted following institutional standards for renal biopsies. Fluorescence Intensity and Chronic Tubulointerstitial Injury Assessment The fluorescence intensity of IgG, IgM, IgA, C3, C1q, and IgG subclasses was assessed using a semi-quantitative scale ranging from 0 to 3: 0 (negative), 1 (weak staining), 2 (moderate staining), and 3 (strong staining). Chronic tubulointerstitial injury, defined as tubular atrophy and interstitial fibrosis, was graded on a semi-quantitative scale from 0 to 3: 0 (0–5% of the interstitium affected), 1 (6–25%), 2 (26–50%), and 3 (> 50%). Detection of Serum Anti-PLA2R Antibodies Patients enrolled after August 2016 were tested for serum anti-phospholipase A2 receptor (anti-PLA2R) antibodies using a human anti-PLA2R enzyme-linked immunosorbent assay (ELISA) kit (Shanghai Lianshuo Biological). All procedures were performed according to the manufacturer’s instructions. The serum anti-PLA2R antibody level was determined based on a standard curve, with values ≥ 20 IU/mL considered positive. Responses to treatment and kidney outcomes The use of corticosteroids and immunosuppressive agents, as well as the definitions of remission and relapse, adhered to the 2021 KDIGO (Kidney Disease: Improving Global Outcomes) guidelines for glomerulonephritis. To evaluate renal outcomes, the primary endpoint was end-stage kidney disease (ESKD). The secondary endpoint was renal dysfunction, defined as a decrease in estimated glomerular filtration rate (eGFR) of more than 30% from baseline at the time of kidney biopsy, with a final eGFR of less than 60 mL/min/1.73 m². Statistical analysis Statistical analyses were conducted using SPSS software, version 19.0 (SPSS Inc., Chicago, IL). Normally distributed variables were expressed as the mean ± standard deviation (SD), while non-normally distributed continuous variables were reported as the median with interquartile range (IQR). Categorical variables were presented as absolute values and percentages. For continuous variables, comparisons between two groups were performed using Student’s t -test for normally distributed data and the Wilcoxon rank-sum test for nonparametric data. Comparisons among three or more groups were conducted using analysis of variance (ANOVA) for normally distributed data and the Kruskal-Wallis test for nonparametric data. Categorical variables were analyzed using the Chi-square test, Fisher’s exact test, or Pearson’s Chi-square test, as appropriate. Risk factors for non-remission following treatment were analyzed using a logistic regression model, while predictors of kidney dysfunction were assessed using a Cox regression model. Statistically significant parameters (P < 0.10) were included in the multivariate Cox regression models. Results were expressed as odds ratios (ORs) or hazard ratios (HRs) with 95% confidence intervals (CIs). All statistical analyses were two-tailed, with statistical significance set at P < 0.05. Results Demographic and clinical data of patients A total of 302 patients with primary membranous nephropathy were followed up, including 186 males, with a mean age of 47.9 ± 14.4 years. Based on serum anti-PLA2R antibody levels, patients were categorized into a negative group (< 20 IU/mL, n = 166) and a positive group (≥ 20 IU/mL, n = 136). Of the 302 patients initially enrolled, a follow-up analysis was conducted over a three-year period. After excluding patients with incomplete follow-up data, a total of 225 cases with complete clinical and pathological information were included in the final analysis. Logistic regression analysis was performed to identify the risk factors associated with non-remission of membranous nephropathy. Additionally, Cox proportional hazards regression analysis was conducted to evaluate independent predictors of renal dysfunction during the follow-up period. The study flowchart, depicted in Fig. 1 , illustrates the patient selection process. The clinical and pathological features of PMN patients Clinical and Pathological Characteristics of Anti-PLA2R Antibody–Positive and –negative PMN Patients are shown in Table 1 . The urine protein and serum cholesterol levels in the anti-PLA2R antibody-positive group were significantly higher than those in the negative group (P < 0.01), whereas serum albumin and IgG levels were significantly lower (P < 0.01). The positive rate of IgG4 in renal tissue was significantly higher in patients with positive serum anti-PLA2R antibodies than in those in the negative group (P < 0.01). However, no significant differences were observed in other IgG subclasses between the two groups. Table 1 Clinical and Pathological Characteristics of Anti-PLA2R Antibody–Positive and –negative PMN Patients Parameters anti-PLA2R antibody-negative(n = 166) anti-PLA2R antibody-positive(n = 136) P Age(years) 47.6 ± 14.9 48.4 ± 13.7 0.616 Gender(male/%) 105(63.2%) 81(59.5%) 0.511 Hematuria, n (%) 46(27.7%) 35(25.7%) 0.700 Hypertension, n (%) 81(48.8%) 62(45.6%) 0.579 Serum albumin (g/L) 30.2 ± 6.5 26.1 ± 4.3 < 0.001 Serum creatinine(µmol/L) 71.2 (57.6–81.7) 71.5 (61.7–89.2) 0.270 eGFR (ml/min/1.73m 2 ) 99.8 (88.4-113.1) 98.8(84.3-111.5) 0.311 Proteinuria (g/24h) 5.1 (2.8-8.0) 6.4 (4.6–8.4) 0.008 Uric acid(umol/L) 385.9 ± 96.2 375.6 ± 98.6 0.419 Triglycerides (mmol/L) 2.2 (1.4–3.4) 2.3 (1.6–3.3) 0.542 Cholesterol (mmol/L) 6.5 (5.2–7.4) 7.5 (6.2–9.6) < 0.001 Serum-IgG (mg/dl) 693.5 (522–951) 603.5(445-738.7) < 0.001 Serum-IgM (mg/dl) 97.6 (69.3-137.2) 100.5(74.8-140.2) 0.635 Serum-IgA (mg/dl) 205 (163.7-264.7) 193.5(132-279.2) 0.311 Serum-C3 (mg/dl) 102.1 ± 22.9 99.8 ± 22.1 0.387 Serum-C4 (mg/dl) 24.6 ± 7.2 25.5 ± 7.0 0.270 Serum-C1q (mg/dl) 201.2 ± 35.4 203.6 ± 34.7 0.539 Anti-PLA2R antibody level (IU/ml) 5.1 (4.4–7.7) 66.3 (27.6-190.2) < 0.001 Global sclerosis (%) 0 (0-8.2) 2.1 (0-8.3) 0.616 Chronic tubulointerstitial injury (0/1/2/3, n) 69/47/34/14 46/39/38/13 0.389 IgG deposit, n (%) 164(98.8%) 134(98.5%) 0.841 IgM deposit, n (%) 125(75.3%) 108(79.4%) 0.397 IgA deposit, n (%) 150(90.4%) 125(91.9%) 0.639 C3 deposit, n (%) 158(95.2%) 135(99.3%) 0.082 C1q deposit, n (%) 152(91.5%) 124(91.2%) 0.904 FRA deposit, n (%) 150(90.4%) 121(89.0%) 0.692 IgG1 deposit, n (%) 164(98.8%) 135(99.3%) 0.678 IgG2 deposit, n (%) 141(84.9%) 108(79.4%) 0.209 IgG3 deposit, n (%) 39(23.5%) 21(15.4%) 0.081 IgG4 deposit, n (%) 152(91.5%) 135(99.3%) 0.005 Treatment responses and kidney outcomes of PMN patients As shown in Table 2 , There were 113 (50.2%) patients treated with immunosuppressive regimens. 115 (51.1%) patients achieved complete remission in 18 (12, 36) months and 36 (16.0%) patients achieved partial remission in 8 (4, 15) months. Among them, 10 (4.4%) patients relapsed. During the follow-up period of 36 (24,51) months, 28 (12.4%) patients developed renal dysfunction and 4 (1.8%) patients deteriorated to ESRD. A follow-up analysis of 225 patients with primary membranous nephropathy revealed that the incidence of renal impairment and the use of immunosuppressive agents were significantly higher in the anti-PLA2R antibody-positive group than in the anti-PLA2R antibody-negative group (P < 0.05). Table 2 Comparison of Clinical Remission Rates Between Anti-PLA2R Antibody–Positive and –Negative Groups anti-PLA2R antibody-positive(n = 110) anti-PLA2R antibody-negative(n = 115) P值 Remission, n (%) 69(62.7%) 82(71.3%) 0.171 Complete remission, n (%) 51(46.4%) 64(55.6%) Partial remission, n (%) 18(16.3%) 18(15.7%) No remission, n (%) 36(32.7%) 28(24.3%) 0.164 Relapse, n (%) 5(4.5%) 5(4.3%) 0.943 Kidney dysfunction, n (%) 19(17.3%) 9(7.8%) 0.032 ESKD, n (%) 3(2.7%) 1(0.9%) 0.282 Immunosuppressive treatments, n (%) 65(59.1%) 48(41.7%) 0.011 The clinical and pathological features of PMN patients with C3 deposition As shown in Table 3 , Patients with stronger C3 deposition exhibited lower serum albumin and complement C3 levels (P < 0.01) and higher serum cholesterol levels, anti-PLA2R antibody concentrations, positive rates of anti-PLA2R antibodies, and proportions of glomerulosclerosis (P < 0.01). Table 3 Clinical Features of PMN Patients Stratified by C3 Deposition Intensity C3 -(N = 9) C3 1+(N = 11) C3 2+ (N = 147) C3 3+(N = 133) P Age(years) 43.3 ± 9.7 50.6 ± 12.5 46.7 ± 14.0 49.5 ± 15.1 0.278 Gender(male/%) 4(44.5) 5(45.4) 84(57.1) 75(56.4) 0.784 Serum albumin (g/L) 31.0 ± 8.4 32.5 ± 8.1 29.4 ± 5.7 26.7 ± 5.4 < 0.001 Proteinuria (g/24h) 5.9 (2.5–9.1) 5.8(3.5–8.6) 5.4(3.5–8.4) 5.8(3.7–8.4) 0.994 Serum creatinine (umol/L) 73.7 (70.6–88.8) 77.8 (67.9–96.2) 67.9 (58.0−81.3) 71.8 (58.4–92.3) 0.122 eGFR(ml/min/1.73m 2 ) 106.4(76.8−115.4) 96.1(82.7−101.9) 101.1(90.6−115.1) 98.8(80.2−109.8) 0.058 Uric acid (umol/L) 389.9 ± 127.7 451.2 ± 114.7 375.9 ± 100.9 381.7 ± 114.2 0.175 Triglycerides (mmol/L) 3.5 (1.5–4.2) 2.8 (1.9−4.0) 2.1 (1.5–3.3) 2.1 (1.5–3.1) 0.542 Cholesterol (mmol/L) 6.2(5.6–7.1) 6.5(5.1–8.3) 6.5(5.3–7.8) 7.4(6.2–9.7) < 0.001 Serum-IgG (mg/dl) 580.0(495.0−907.5) 876.5(567.0−1140.0) 693.5(519.5−850.2) 595.5(450.0−821.0) 0.035 Serum-IgM (mg/dl) 90.7(61.2−145.5) 82.3(66.2–92.6) 98.9(69.4−137.2) 104.0(75.8–149.0) 0.206 Serum-IgA (mg/dl) 208.0(155.0−248.0) 209.0(176.0−263.5) 200.0(157.5−261.2) 201.5(150.5−289.2) 0.722 Serum-C3(mg/dl) 103.6 ± 14.0 120.0 ± 28.1 102.6 ± 22.8 97.6 ± 21.3 0.008 Serum-C4(mg/dl) 24.6 ± 8.1 27.7 ± 8.6 24.2 ± 6.9 25.6 ± 7.2 0.208 Serum-C1q (mg/dl) 203.9 ± 27.2 195.6 ± 30.1 203.8 ± 36.0 201.3 ± 35.1 0.850 Anti-PLA2R antibody level (IU/ml) 5.1 (4.5–6.3) 4.9 (4.1–8.3) 10.0 (4.7–35.1) 25.4 (7.2−130.8) < 0.001 Anti-PLA2R antibody positivity, n (%) 1(11.1) 2(18.2) 62(42.2) 75(56.4) 0.002 Global sclerosis (%) 0.0(0.0–0.0) 0.0(0.0−9.2) 0.0(0.0−7.1) 3.5(0.0−10.5) 0.004 Chronic tubulointerstitial injury (0/1/2/3, n) 2/3/4/0 4/3/2/2 62/41/37/7 47/39/29/18 0.208 The clinical and pathological features of PMN patients with C1q deposition As shown in Table 4 , Serum cholesterol levels were higher in the group with stronger C1q deposition in the kidney tissue (P < 0.05), and there were no significant differences in other indexes among the groups. Table 4 Clinical Features of PMN Patients Stratified by C1q Deposition Intensity C1q- (N = 29) C1q 1+(N = 56) C1q 2+(N = 215) P Age(years) 47.9 ± 15.3 50.2 ± 11.9 47.4 ± 14.8 0.422 Gender(male/%) 15(51.7) 35(62.5) 127(59.1) 0.632 Serum albumin (g/L) 28.3 ± 5.6 28.7 ± 6.4 28.2 ± 5.8 0.849 Proteinuria (g/24h) 5.2(3.6–7.3) 5.0(3.4–8.6) 5.8(3.9–8.4) 0.900 Serum creatinine (umol/L) 66.3(57.1–74.8) 76.2(63.1–99.2) 71.0(58.0−83.4) 0.054 eGFR(ml/min/1.73m 2 ) 98.4(91.1−108.4) 95.3(75.7−107.1) 101.4(88.3−114.2) 0.067 Uric acid (umol/L) 352.6 ± 114.9 377.7 ± 101.1 386.6 ± 109.5 0.286 Triglycerides (mmol/L) 2.1(1.3−3.0) 2.3(1.4–3.7) 2.1(1.5–3.2) 0.825 Cholesterol (mmol/L) 6.1(4.9−7.0) 6.4(5.8–8.3) 7.0(5.9–8.8) 0.033 Serum-IgG (mg/dl) 680.5(526.5−834.2) 638.5(458.7−838.7) 624.0(493.0−860.0) 0.837 Serum-IgM (mg/dl) 94.5 (75.4−121.5) 93.4 (63.5–133.0) 104.0 (74.0−144.0) 0.306 Serum-IgA (mg/dl) 233.0(169.0−322.7) 176.5(143.0−242.5) 205.0(159.0−272.0) 0.124 Serum-C3(mg/dl) 106.5 ± 19.7 102.7 ± 26.5 99.8 ± 21.7 0.903 Serum-C4(mg/dl) 27.3 ± 7.9 24.8 ± 7.1 24.7 ± 6.9 0.336 Serum-C1q (mg/dl) 200.2 ± 28.4 196.8 ± 36.9 204.2 ± 35.4 0.111 Anti-PLA2R antibody level (IU/ml) 11.9(5.1–75.7) 12.9(4.5–79.4) 12.6(5.0−58.4) 0.743 Anti-PLA2R antibody positivity, n (%) 15(51.7) 31(55.3) 115(53.5) 0.946 Global sclerosis (%) 0.0(0.0−6.7) 3.4(0.0−8.5) 0.0(0.0−8.3) 0.437 Chronic tubulointerstitial injury (0/1/2/3, n) 8/12/7/2 17/19/14/6 90/55/51/19 0.451 Risk factors for non-remission in PMN patients As shown in Table 5 , Logistic regression analysis of non-remission factors in patients with primary membranous nephropathy identified decreased serum albumin (OR = 0.931, 95% CI: 0.868–0.999, P = 0.047) and exacerbation of glomerulosclerosis (OR = 1.038, 95% CI: 1.010–1.067, P = 0.008) as independent risk factors for non-remission of PMN patients. Table 5 The logistic regression analysis of risk factors for non-remission in PMN patients. Parameters Univariate analysis OR(95%CI) P Multivariate analysis OR(95%CI) P Age(years) 1.017(0.995–1.039) 0.122 Gender(male/%) 1.044(0.563–1.938) 0.890 Proteinuria 1.036(0.951–1.128) 0.422 Serum albumin 0.907(0.856–0.961) 0.001 0.931(0.868–0.999) 0.047 Serum creatinine 1.001(0.996–1.006) 0.805 Uric acid 0.997(0.994-1.000) 0.038 0.997(0.994–1.001) 0.105 Triglycerides 0.958(0.806–1.138) 0.622 Cholesterol 1.121(0.987–1.272) 0.078 Serum-IgG 0.999(0.998-1.000) 0.035 1.000(0.998–1.001) 0.686 Serum-IgM 1.003(0.997–1.008) 0.315 Serum-IgA 1.000(0.997–1.003) 0.922 Serum-C3 0.979(0.964–0.995) 0.011 0.988(0.971–1.005) 0.173 Serum-C4 1.017(0.977–1.059) 0.406 Serum-C1q 0.998(0.990–1.007) 0.678 eGFR 0.994(0.983–1.006) 0.310 Anti-PLA2R antibody level 1.001(1.000-1.003) 0.036 1.001(0.999–1.002) 0.244 Anti-PLA2R antibody positivity 1.798(0.973–3.321) 0.061 C1q deposition 0.962(0.620–1.494) 0.864 C3 deposition 1.511(0.929–2.457) 0.096 Chronic tubulointerstitial injury 1.227(0.864–1.745) 0.253 Global sclerosis 1.028(1.003–1.053) 0.031 1.038(1.010–1.067) 0.008 Risk factors for renal dysfunction in PMN patients As shown in Table 6 , Multivariate Cox regression analysis of renal dysfunction in these patients demonstrated that older age (HR = 1.048, 95% CI: 1.007–1.091, P = 0.022) and increased intensity of C3 deposition in renal tissue (HR = 2.170, 95% CI: 1.083–4.348, P = 0.029) were independent risk factors for renal dysfunction. Table 6 The Cox regression analysis of risk factors for renal dysfunction in PMN patients. Parameters Univariate analysis HR(95%CI) P Multivariate analysis HR(95%CI) P Age(years) 1.088(1.051–1.126) < 0.001 1.048(1.007–1.091) 0.022 Gender(male/%) 0.677(0.345–1.328) 0.257 Proteinuria 1.025(0.936–1.123) 0.593 Serum albumin 0.963(0.908–1.021) 0.204 Serum creatinine 1.005(1.003–1.007) < 0.001 0.999(0.994–1.005) 0.807 Uric acid 1.003(1.000-1.006) 0.089 eGFR(ml/min/1.73m 2 ) 0.962(0.951–0.972) < 0.001 0.980(0.957–1.003) 0.082 Serum-IgG 1.002(1.001–1.003) 0.003 1.001(0.999–1.002) 0.329 Serum-IgM 0.995(0.987–1.002) 0.174 Serum-IgA 1.002(1.000-1.005) 0.044 Serum-C3 0.990(0.975–1.006) 0.225 Serum-C4 1.030(0.992–1.071) 0.127 Serum-C1q 0.994(0.985–1.003) 0.189 Anti-PLA2R antibody level 1.001(0.999–1.002) 0.728 Anti-PLA2R antibody positivity 1.501(0.751–2.999) 0.251 C3 deposition 3.343(1.672–6.683) 0.001 2.170(1.083–4.348) 0.029 C1q deposition 1.001(0.608–1.647) 0.998 Chronic tubulointerstitial injury 3.696(2.396–5.701) 0.001 1.802(0.868–3.738) 0.114 Global sclerosis 1.039(1.023–1.056) 0.001 0.990(0.966–1.016) 0.456 No remission 2.589(1.310–5.117) 0.006 1.482(0.625–3.515) 0.372 Discussion Membranous nephropathy (MN) is one of the most common causes of adult-onset nephrotic syndrome. Secondary MN is frequently associated with infections (such as hepatitis B virus), autoimmune diseases like systemic lupus erythematosus, or malignancies. A diagnosis of primary membranous nephropathy (PMN) is typically established when these secondary causes are excluded through clinical and serological evaluation and confirmed via renal biopsy. Interestingly, recent reports have described atypical MN cases with immune deposits not only on the subepithelial side of the glomerular basement membrane but also in mesangial and subendothelial areas, despite lacking an identifiable secondary etiology [ 8 ]. These cases, once considered “atypical MN,” may in fact represent part of the PMN spectrum. The identification of anti-phospholipase A2 receptor (PLA2R) antibodies by Beck et al. in 2009 [ 5 ] was a pivotal discovery in PMN research. These circulating autoantibodies are detected in approximately 70–80% of patients with idiopathic MN and are strongly associated with disease activity and prognosis [ 5 , 6 ]. Although initially believed to be specific for PMN, subsequent studies found anti-PLA2R antibodies in patients with hepatitis B virus (HBV)-associated MN and malignancy-related MN [ 9 – 11 ]. Thus, while highly suggestive, seropositivity for anti-PLA2R does not definitively exclude secondary MN, underscoring the need for careful clinical evaluation and longitudinal follow-up. Additionally, deposition of C1q—traditionally a marker of secondary MN—has occasionally been observed in otherwise typical PMN cases, further complicating the differential diagnosis [ 12 ]. In our cohort of 302 biopsy-confirmed PMN patients, we observed that those who were anti-PLA2R antibody-positive had significantly higher 24-hour urinary protein and serum cholesterol levels, along with lower serum albumin and IgG levels compared to antibody-negative patients. These findings suggest a more active disease state in antibody-positive individuals. Furthermore, IgG4 deposition in renal tissue was significantly more frequent in this group, consistent with the established role of IgG4 in PLA2R-mediated immune complex formation. Importantly, during follow-up, the antibody-positive group exhibited a higher incidence of renal dysfunction and received immunosuppressive therapy more frequently. These observations reinforce the prognostic value of anti-PLA2R antibody levels in guiding treatment decisions and risk stratification. Complement activation is another key feature of PMN pathogenesis. Granular deposition of IgG and C3 along the glomerular capillary wall is a pathological hallmark of the disease. Our results showed that stronger C3 deposition was significantly associated with reduced serum albumin and C3 levels, elevated serum cholesterol, higher anti-PLA2R antibody titers, greater anti-PLA2R positivity, and increased glomerulosclerosis. Furthermore, multivariate Cox regression identified C3 deposition as an independent predictor of renal dysfunction, highlighting its clinical relevance. These findings are in line with previous work from Peking University First Hospital, which demonstrated that higher C3 staining intensity was correlated with more severe proteinuria, lower albumin levels, and increased anti-PLA2R antibody levels and serum creatinine, whereas the intensity of IgG deposition showed no such associations [ 13 ]. It has been hypothesized that intense glomerular C3 deposition reflects enhanced complement activation and systemic C3 consumption, contributing to progressive glomerular injury and adverse renal outcomes [ 14 ]. Supporting this, several studies have linked low serum C3 levels with poor prognosis in PMN [ 15 , 16 ], emphasizing its potential as a biomarker of disease severity [ 17 ]. The observed relationship between C3 deposition, anti-PLA2R antibody levels, and clinical severity suggests that PLA2R–IgG immune complex formation may serve as a trigger for autoimmune injury, with complement activation mediating subsequent glomerular damage. Complement components such as C3a and C5a have been found to be elevated in both serum and urine of PMN patients, further supporting this pathogenic mechanism [ 18 ]. Although classical pathway activation is generally linked to C1q deposition and IgG1/IgG3 subclasses, PLA2R-associated IgG4 antibodies—typically considered non-complement activating—may trigger the lectin or alternative pathways. This is supported by evidence indicating that mannan-binding lectin can bind IgG4–PLA2R complexes and activate the lectin pathway[ 19 – 21 ], while C3 deposition in antibody-negative PMN suggests involvement of the alternative pathway [ 22 , 23 ]. The pathogenic role of complement activation in PMN progression suggests that targeting complement components may be a promising therapeutic strategy[ 24 ]. However, the mechanisms determining which complement pathway predominates in a given patient remain unclear. In our study, despite the frequent detection of C1q deposition, we did not observe any significant association between C1q staining intensity and anti-PLA2R levels, clinical indices, or renal outcomes. These findings are consistent with previous reports suggesting that classical pathway activation may occur in a subset of PMN patients but is not necessarily linked to disease severity or progression [ 25 ]. Recent studies have highlighted the pivotal role of complement activation in the pathogenesis of membranous nephropathy (MN), with the C3a/C3aR signaling pathway emerging as a key effector mechanism in complement-mediated podocyte injury. It has been demonstrated that both plasma C3a levels and glomerular C3aR expression are significantly elevated in MN patients compared to healthy individuals, and these elevations correlate with disease severity and prognosis[ 26 , 27 ]. In vitro experiments revealed that C3a derived from the plasma of MN patients disrupts podocyte function and viability, effects that are effectively mitigated by C3aR antagonists. Moreover, in vivo studies using Heymann nephritis rat models—a classical model for MN—confirmed that pharmacologic blockade of C3aR can attenuate renal injury[ 28 , 29 ]. These findings provide compelling evidence that the C3a/C3aR axis plays a crucial role in MN pathogenesis and represents a promising therapeutic target. Additionally, our study contributes novel insights into the mechanisms of complement-mediated podocyte injury by identifying pyroptosis as a key mode of cell death involved in this process. We further demonstrate that mitochondrial dysfunction may underlie this pyroptotic response. These observations suggest that targeting pyroptosis could represent an innovative therapeutic strategy for MN in future research [ 30 ]. In summary, our study demonstrates that both anti-PLA2R antibody positivity and pronounced glomerular C3 deposition are associated with more severe clinical manifestations and unfavorable renal outcomes in PMN. These markers may serve as useful tools for prognostic assessment and therapeutic decision-making. Moreover, our findings highlight the critical role of complement activation—particularly via non-classical pathways—in PMN pathogenesis. Further prospective and mechanistic studies are warranted to explore complement-targeted therapies in this disease. Declarations Financial support This work was supported by College-level projects in China-Japan Friendship Hospital ( 2017-2-QN-19) CRediT authorship contribution statement XQQ ： Writing – review & editing, Writing – original draft, Software, Project administration, Methodology, Investigation, Formal analysis, Data curation. LJY ： Data curation, Methodology, Writing-original draft, Formal analysis. ZC: Data curation, Methodology. TM: Data curation, Methodology, Validation. LWG: Supervision, Resources, Funding acquisition, Conceptualization. Project administration. All authors read and approved the final manuscript. Ethics approval and consent to participate This study was conducted in accordance with the guidelines of the Declaration of Helsinki and was approved by the Ethics Committee of China-Japan Friendship Hospital (approval number: 2019-17-K12). Informed consent Informed consent was obtained from all study participants. Conflict of interest The authors declare no conflict of interest. Data availability Data will be made available on request References Wu YQ, Wang Z, Xu HF, et al. Frequency of primary glomerulardisease in northeastern China [J]. Braz J Med Biol Res, 2011, 44(8): 810-813. Li LS, Liu ZH. Epidemiologic data of renal diseases from a single unit in China: analysis based on 13, 519 renal biopsies [J]. Kidney Int, 2004, 66(3): 920-923. Beck LH, SalantDJ. Membranous nephropathy: recent travels and new roads ahead［J］. Kidney Int, 2010, 77（9）: 765-70. DOI：10.1038/ki.2010.34. Ponticelli C, Glassock RJ. Glomerular diseases: membranous nephropathy-a modern view. Clin J Am Soc Nephrol (2014) 9 (3):609–16. doi: 10.2215/CJN.04160413 Beck LH, Bonegio RGB, Lambeau G, et al. M-type phospholipase A2 receptor as target antigen in idiopathic membranous nephropathy. N Engl J Med. 2009;361(1):11-21. doi: 10.1056/NEJMoa0810457. Qin W, Beck LH, Zeng C, et al. Anti-phospholipase A2 receptor antibody in membranous nephropathy. J Am Soc Nephrol. 2011;22(6):1137–1143. doi: 10.1681/ASN.2010090967. Stevens LA, Claybon MA, Schmid CH, Chen J, Horio M, Imai E, et al. Evaluation of the chronic kidney disease epidemiology collaboration equation for estimating the glomerular filtration rate in multiple ethnicities. Kidney Int (2011) 79 (5): 555-62. doi: 10.1038/ki.2010.462 Glassock RJ. Secondary membranous glomerulonephritis. Nephrol Dial Transplant(1992) 7(Suppl 1): 64-71. Xie Q, Li Y, Xue J, et al. Renal phospholipase A2 receptor in hepatitis B virus-associated membranous nephropathy. Am J Nephrol. 2015;41(4-5):345–353. doi: 10.1159/000431331. Gunnarsson I, Schlumberger W, Rönnelid J.. Antibodies to M-type phospholipase A2 receptor (PLA2R) and membranous lupusnephritis. Am J Kidney Dis. 2012;59(4):585–586. doi: 10.1053/j.ajkd.2011.10.044. Lönnbro-Widgren J, Ebefors K, Mölne J, et al. Glomerular IgG subclasses in idiopathic and malignancy-associated membranous nephropathy. Clin Kidney J. 2015;8(4):433–439. doi: 10.1093/ckj/sfv049. Jiang Z, Cai M, Dong B, et al. Clinicopathological features of atypical membranous nephropathy with unknown ­etiology in adult Chinese patients. Medicine. 2018;97(32):32(e11608. doi: 10.1097/MD.0000000000011608. Zhang XD, Cui Z, Zhang MF, et al. Clinical implications of pathological features of primary membranous nephropathy[J]. BMC Nephrology, 2018, 19(1):215. DOI: 10.1186/s12882- 018- 1011-5. Mufan Zhang, Jing Huang, Yimiao Zhang, et al. Complement activation products in the circulation and urine of primary membranous nephropathy. BMC Nephrology (2019) 20:313 . Tsai SF,Wu MJ,Chen CH.Low serum C3 level,high neutrophil-lymphocyte-ratio, and high platelet-lymphocyte-ratio all predicted poor long-term renal survivals in biopsy -confirmed idiopathic membranous nephropathy [J].Sci Rep,2019,9 (1):6209. Yamaguchi M,Ando M,Katsuno T,et al.Urinary protein and renal prognosis in idiopathic membranous nephropathy:a multicenter retrospective cohort study in Japan [J].Renal Failure, 2018,40(1):435-441. Dong J,Peng T,Gao J,et al. A pilot and comparative study between pathological and serological levels of immunoglobulin and complement among three kinds of primary glomerulonephritis[J]. BMC Immunology,2018,19(1):18. Bally S, Debiec H, Ponard D, Dijoud F, Rendu J, Faure J, Ronco P, Dumestre-Perard C. Phospholipase A2 receptor-related membranous nephropathy and Mannan-binding lectin deficiency. J Am Soc Nephrol. 2016;27(12):3539–44. Yang Y, Wang C, Jin L, He F, et al. IgG4 anti-phospholipase A2 receptor might activate lectin and alternative complement pathway meanwhile in idiopathic membranous nephropathy:an inspiration from a cross-sectional study.Immunol Res. 2016;64(4):919–30. Petri C, Thiel S, Jensenius JC, Herlin T. Investigation of complement-activating pattern recognition molecules and associated enzymes as possible inflammatory markers in Oligoarticular and systemic juvenile idiopathic arthritis. J Rheumatol. 2015;42(7):1252–8. Haddad G, Lorenzen JM, Ma H, de Haan N, Seeger H, Zaghrini C, et al. Altered glycosylation of IgG4 promotes lectin complement pathway activation in anti-PLA2R-associated membranous nephropathy. J Clin Invest. 2021;131(5):140453. doi: 10.1172/JCI140453. Blom AM, Corvillo F, Magda M, Stasilojc G, et al.Testing the activity of complement convertases in serum/plasma for diagnosis of C4NeF-mediated C3 glomerulonephritis. J Clin Immunol. 2016;36(5):517–27. Mathern DR, Heeger PS. Molecules great and small: the complement system. Clin J Am Soc Nephrol. 2015;10(9):1636–50. Ma H, Sandor DG, Beck LH Jr. The role of complement in membranous nephropathy. Semin Nephrol. 2013;33(6):531–42. Mufan Zhang, Zhao Cui, Yimiao Zhang, et al. Clinical and prognostic significance of glomerular C1q deposits in primary MN. Clinica Chimica Acta.485 (2018) :152–157. Kistler AD, Salant DJ. Complement activation and effector pathways in membranous nephropathy. Kidney Int. 2024 Mar;105(3):473-483. doi: 10.1016/j.kint.2023.10.035. Gao S, Cui Z, Zhao MH.Complement C3a and C3a Receptor Activation Mediates Podocyte Injuries in the Mechanism of Primary Membranous Nephropathy. J Am Soc Nephrol. 2022 Sep;33(9):1742-1756. doi: 10.1681/ASN.2021101384. Zhang Q, Bin S, Budge K, Petrosyan A, Villani V, Aguiari P, Vink C. C3aR-initiated signaling is a critical mechanism of podocyte injury in membranous nephropathy. JCI Insight. 2024 Jan 16;9(4):e172976. doi: 10.1172/jci.insight.172976. Shanshen Yu , Jia Sun. A review of progress on complement and primary membranous nephropathy. Medicine. 2024;103(29):e38990. doi: 10.1097/MD.0000000000038990 Wang H, Lv D, Jiang S, Hou Q, Zhang L, Li S. Complement induces podocyte pyroptosis in membranous nephropathy by mediating mitochondrial dysfunction. Cell Death Dis. 2022 Mar 29;13(3):281. doi: 10.1038/s41419-022-04737-5. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6637635","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":481797512,"identity":"d635bdc6-b647-463b-9aee-b23894e9882f","order_by":0,"name":"Qianqian Xu","email":"","orcid":"","institution":"china-japan friendship hospital","correspondingAuthor":false,"prefix":"","firstName":"Qianqian","middleName":"","lastName":"Xu","suffix":""},{"id":481797513,"identity":"588176c3-a3bd-4b75-9d60-e89307541fd4","order_by":1,"name":"Jiayi Li","email":"","orcid":"","institution":"Peking University China-Japan Friendship School of Clinical Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jiayi","middleName":"","lastName":"Li","suffix":""},{"id":481797514,"identity":"bc6d4e5f-65ff-492c-976f-98280e586136","order_by":2,"name":"Cong Zhang","email":"","orcid":"","institution":"china-japan friendship hospital","correspondingAuthor":false,"prefix":"","firstName":"Cong","middleName":"","lastName":"Zhang","suffix":""},{"id":481797515,"identity":"13fee36f-ece0-4772-9a5e-701c5ec82981","order_by":3,"name":"Min Tan","email":"","orcid":"","institution":"china-japan friendship hospital","correspondingAuthor":false,"prefix":"","firstName":"Min","middleName":"","lastName":"Tan","suffix":""},{"id":481797517,"identity":"f10b8d4d-3342-4ef4-b747-398fb8745d01","order_by":4,"name":"Wenge Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYPACCwYG9sbGBxIVEnL8RGqRYGDgOXzYwOKMhbFkA9FaJNLSJCrbKhI3ENJicLz38IsPDCD35BhI3JwnwbiBgfnhoxv4tJw5l2Y5g0EC6J4zBoYzt0kwmzOwGRvn4NFidiPHzJiHQSJxw8Eeg2TJbRJslg08bNJ4tdx/Y2b8h0Gifv9hHoPDf+dI8BgcIKTlBo/xY6DfEwzY2BIbJBskJAhqsT+TY8bYwyBhOOMM82EGiWMSBpLNBPwi2X7G+MMPBht5/vkP239I1NTV97M3P3yMTwsQsEkw/kPmM+NXDlbygbCaUTAKRsEoGNEAAEViSKwSXF2XAAAAAElFTkSuQmCC","orcid":"","institution":"china-japan friendship hospital","correspondingAuthor":true,"prefix":"","firstName":"Wenge","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2025-05-11 04:53:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6637635/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6637635/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86642801,"identity":"1ea08a3b-6a03-4857-b29d-aeaf05b0e244","added_by":"auto","created_at":"2025-07-14 08:31:47","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":776187,"visible":true,"origin":"","legend":"\u003cp\u003eThe study flowchart. PMN: primary membranous nephropathy.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6637635/v1/d970747db9122af2cbad6266.jpeg"},{"id":90480286,"identity":"b6a84688-94f9-4543-a1b9-a100242ef9fc","added_by":"auto","created_at":"2025-09-03 07:54:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2158963,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6637635/v1/c45b77ec-1cd4-4966-b966-b41adeacd42a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Serum Anti-PLA2R Antibody and Renal Complement Deposition: Associations with Clinicopathological Features in Primary Membranous Nephropathy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMembranous nephropathy (MN) is a leading cause of nephrotic syndrome (NS) in adults, accounting for 9.83\u0026ndash;30% of primary glomerulonephritis in China [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Histologically, MN is characterized by subepithelial immune complex deposition and diffuse thickening of the glomerular basement membrane (GBM) observed by light microscopy [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. While approximately 75% of MN cases are considered idiopathic or primary, the remaining cases are secondary to infections, autoimmune diseases, malignancies, or drug exposure [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePrimary membranous nephropathy (PMN) is increasingly recognized as an autoimmune glomerular disease. The identification of circulating autoantibodies against the M-type phospholipase A2 receptor (PLA2R) on podocytes has transformed our understanding of PMN pathogenesis[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Anti-PLA2R antibodies are present in approximately 70\u0026ndash;80% of patients with idiopathic MN and serving as a diagnostic biomarker and a predictor of disease activity and treatment response[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In addition to autoantibodies, complement activation is increasingly implicated in the pathophysiology of PMN. Despite the predominance of IgG4\u0026mdash;an isotype traditionally considered incapable of activating the classical complement pathway\u0026mdash;complement components such as C3 and C1q are frequently deposited in glomeruli. This paradox suggests that complement activation may occur through alternative or lectin pathways, contributing to podocyte injury and disease progression\u003c/p\u003e\u003cp\u003eThe clinical implications of complement deposition patterns in PMN remain incompletely defined. Although previous studies have reported associations between C3 deposition and more severe proteinuria or worse renal outcomes, the interaction between serum anti-PLA2R antibodies and complement components in renal tissue has not been fully elucidated. It also remains unclear whether the intensity of glomerular complement staining can serve as a prognostic indicator for long-term renal function.\u003c/p\u003e\u003cp\u003eIn this retrospective study, we aimed to investigate the relationships among serum anti-PLA2R antibody levels, glomerular deposition of complement components (particularly C3 and C1q), and the clinicopathological features and renal prognosis of patients with biopsy-proven PMN. By integrating clinical, serological, and pathological parameters, this study seeks to provide new insights into disease stratification and potential therapeutic targets in PMN.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData Sources and Patient Cohort\u003c/h2\u003e\u003cp\u003eA total of 302 patients diagnosed with primary membranous nephropathy (PMN) via renal biopsy at our hospital were included in this study. The cohort comprised 186 males and 116 females, with a mean age of 47.9\u0026thinsp;\u0026plusmn;\u0026thinsp;14.4 years. All patients were followed longitudinally from August 2016 to December 2022.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePatient Selection Criteria\u003c/h3\u003e\n\u003cp\u003eThe inclusion criteria were as follows: (1) renal histological and immunopathological findings consistent with PMN ; (2) exclusion of known secondary causes, including systemic lupus erythematosus, hepatitis B and C infections; (3) no history of exposure to non-steroidal anti-inflammatory drugs, gold compounds, penicillamine, or other potentially nephrotoxic agents; and (4) no prior exposure to organic solvents or mercury. This study was approved by the Ethics Committee of China-Japan Friendship Hospital (Approval No. 2019-17-K12).\u003c/p\u003e\n\u003ch3\u003eClinical and Biological Data\u003c/h3\u003e\n\u003cp\u003eThe following clinical parameters were collected for all patients with Primary membranous nephropathy (PMN): age, sex, 24-hour urinary protein excretion, serum albumin, creatinine, estimated glomerular filtration rate (eGFR), cholesterol, triglycerides, presence of hypertension or hematuria, serum immunoglobulin levels (IgG, IgA, IgM), complement components (C3, C4, C1q), and anti-PLA2R antibody levels.\u003c/p\u003e\u003cp\u003eRenal biopsy specimens were assessed by immunofluorescence staining for IgG, IgA, IgM, C3, C1q, fibrin-related antigen (FRA), and IgG subclasses (IgG1\u0026ndash;IgG4). Serum anti-PLA2R antibody levels were used to stratify patients into antibody-positive and antibody-negative groups based on a predefined threshold.\u003c/p\u003e\u003cp\u003eComparative analysis of clinical features and renal pathological findings was performed between the two groups to identify statistically significant differences. In addition, baseline and follow-up data were used to explore independent risk factors associated with non-remission and renal function deterioration.\u003c/p\u003e\u003cp\u003eThe eGFR was calculated using the CKD-EPI equation [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eAnalysis of Kidney Biopsies\u003c/h3\u003e\n\u003cp\u003ePercutaneous renal biopsy was performed in all cases, and kidney tissue specimens were collected in three parts for light microscopy, immunofluorescence, and electron microscopy. \u003cb\u003eLight Microscopy\u003c/b\u003e: All specimens contained more than 10 glomeruli and were paraffin-embedded, sectioned at a thickness of 2 \u0026micro;m, and stained with hematoxylin-eosin (HE), periodic acid\u0026ndash;Schiff (PAS), periodic acid\u0026ndash;silver methenamine (PASM), and Masson's trichrome. \u003cb\u003eImmunofluorescence\u003c/b\u003e: Frozen sections were analyzed by direct immunofluorescence for the presence of IgG, IgA, IgM, C3, C1q, fibrin-related antigen (FRA), and IgG subclasses (IgG1, IgG2, IgG3, and IgG4). \u003cb\u003eElectron Microscopy\u003c/b\u003e: All kidney biopsy specimens were sent to the electron microscopy laboratory of the China-Japan Friendship Hospital for further examination. Renal pathological classification and diagnosis were conducted following institutional standards for renal biopsies.\u003c/p\u003e\n\u003ch3\u003eFluorescence Intensity and Chronic Tubulointerstitial Injury Assessment\u003c/h3\u003e\n\u003cp\u003eThe fluorescence intensity of IgG, IgM, IgA, C3, C1q, and IgG subclasses was assessed using a semi-quantitative scale ranging from 0 to 3: 0 (negative), 1 (weak staining), 2 (moderate staining), and 3 (strong staining). Chronic tubulointerstitial injury, defined as tubular atrophy and interstitial fibrosis, was graded on a semi-quantitative scale from 0 to 3: 0 (0\u0026ndash;5% of the interstitium affected), 1 (6\u0026ndash;25%), 2 (26\u0026ndash;50%), and 3 (\u0026gt;\u0026thinsp;50%).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eDetection of Serum Anti-PLA2R Antibodies\u003c/h2\u003e\u003cp\u003ePatients enrolled after August 2016 were tested for serum anti-phospholipase A2 receptor (anti-PLA2R) antibodies using a human anti-PLA2R enzyme-linked immunosorbent assay (ELISA) kit (Shanghai Lianshuo Biological). All procedures were performed according to the manufacturer\u0026rsquo;s instructions. The serum anti-PLA2R antibody level was determined based on a standard curve, with values\u0026thinsp;\u0026ge;\u0026thinsp;20 IU/mL considered positive.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eResponses to treatment and kidney outcomes\u003c/h3\u003e\n\u003cp\u003e The use of corticosteroids and immunosuppressive agents, as well as the definitions of remission and relapse, adhered to the 2021 KDIGO (Kidney Disease: Improving Global Outcomes) guidelines for glomerulonephritis.\u003c/p\u003e\u003cp\u003eTo evaluate renal outcomes, the primary endpoint was end-stage kidney disease (ESKD). The secondary endpoint was renal dysfunction, defined as a decrease in estimated glomerular filtration rate (eGFR) of more than 30% from baseline at the time of kidney biopsy, with a final eGFR of less than 60 mL/min/1.73 m\u0026sup2;.\u003c/p\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eStatistical analyses were conducted using SPSS software, version 19.0 (SPSS Inc., Chicago, IL). Normally distributed variables were expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), while non-normally distributed continuous variables were reported as the median with interquartile range (IQR). Categorical variables were presented as absolute values and percentages. For continuous variables, comparisons between two groups were performed using Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test for normally distributed data and the Wilcoxon rank-sum test for nonparametric data. Comparisons among three or more groups were conducted using analysis of variance (ANOVA) for normally distributed data and the Kruskal-Wallis test for nonparametric data. Categorical variables were analyzed using the Chi-square test, Fisher\u0026rsquo;s exact test, or Pearson\u0026rsquo;s Chi-square test, as appropriate. Risk factors for non-remission following treatment were analyzed using a logistic regression model, while predictors of kidney dysfunction were assessed using a Cox regression model. Statistically significant parameters (P\u0026thinsp;\u0026lt;\u0026thinsp;0.10) were included in the multivariate Cox regression models. Results were expressed as odds ratios (ORs) or hazard ratios (HRs) with 95% confidence intervals (CIs). All statistical analyses were two-tailed, with statistical significance set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eDemographic and clinical data of patients\u003c/h2\u003e\u003cp\u003eA total of 302 patients with primary membranous nephropathy were followed up, including 186 males, with a mean age of 47.9\u0026thinsp;\u0026plusmn;\u0026thinsp;14.4 years. Based on serum anti-PLA2R antibody levels, patients were categorized into a negative group (\u0026lt;\u0026thinsp;20 IU/mL, n\u0026thinsp;=\u0026thinsp;166) and a positive group (\u0026ge;\u0026thinsp;20 IU/mL, n\u0026thinsp;=\u0026thinsp;136).\u003c/p\u003e\u003cp\u003eOf the 302 patients initially enrolled, a follow-up analysis was conducted over a three-year period. After excluding patients with incomplete follow-up data, a total of 225 cases with complete clinical and pathological information were included in the final analysis. Logistic regression analysis was performed to identify the risk factors associated with non-remission of membranous nephropathy. Additionally, Cox proportional hazards regression analysis was conducted to evaluate independent predictors of renal dysfunction during the follow-up period.\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe study flowchart, depicted in\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cb\u003eillustrates the patient selection process.\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eThe clinical and pathological features of PMN patients\u003c/h2\u003e\u003cp\u003eClinical and Pathological Characteristics of Anti-PLA2R Antibody\u0026ndash;Positive and \u0026ndash;negative PMN Patients are shown in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The urine protein and serum cholesterol levels in the anti-PLA2R antibody-positive group were significantly higher than those in the negative group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), whereas serum albumin and IgG levels were significantly lower (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The positive rate of IgG4 in renal tissue was significantly higher in patients with positive serum anti-PLA2R antibodies than in those in the negative group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). However, no significant differences were observed in other IgG subclasses between the two groups.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical and Pathological Characteristics of Anti-PLA2R Antibody\u0026ndash;Positive and \u0026ndash;negative PMN Patients\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eanti-PLA2R antibody-negative(n\u0026thinsp;=\u0026thinsp;166)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eanti-PLA2R antibody-positive(n\u0026thinsp;=\u0026thinsp;136)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge(years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47.6\u0026thinsp;\u0026plusmn;\u0026thinsp;14.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.616\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender(male/%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e105(63.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e81(59.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.511\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHematuria, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46(27.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35(25.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.700\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e81(48.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e62(45.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.579\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum albumin (g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30.2\u0026thinsp;\u0026plusmn;\u0026thinsp;6.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum creatinine(\u0026micro;mol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e71.2 (57.6\u0026ndash;81.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e71.5 (61.7\u0026ndash;89.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.270\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eeGFR (ml/min/1.73m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e99.8 (88.4-113.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e98.8(84.3-111.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.311\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProteinuria (g/24h)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.1 (2.8-8.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.4 (4.6\u0026ndash;8.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUric acid(umol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e385.9\u0026thinsp;\u0026plusmn;\u0026thinsp;96.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e375.6\u0026thinsp;\u0026plusmn;\u0026thinsp;98.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.419\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTriglycerides (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.2 (1.4\u0026ndash;3.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.3 (1.6\u0026ndash;3.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.542\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCholesterol (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.5 (5.2\u0026ndash;7.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.5 (6.2\u0026ndash;9.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-IgG (mg/dl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e693.5 (522\u0026ndash;951)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e603.5(445-738.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-IgM (mg/dl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e97.6 (69.3-137.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100.5(74.8-140.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.635\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-IgA (mg/dl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e205 (163.7-264.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e193.5(132-279.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.311\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-C3 (mg/dl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e102.1\u0026thinsp;\u0026plusmn;\u0026thinsp;22.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e99.8\u0026thinsp;\u0026plusmn;\u0026thinsp;22.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.387\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-C4 (mg/dl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.270\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-C1q (mg/dl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e201.2\u0026thinsp;\u0026plusmn;\u0026thinsp;35.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e203.6\u0026thinsp;\u0026plusmn;\u0026thinsp;34.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.539\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnti-PLA2R antibody level\u003c/p\u003e\u003cp\u003e(IU/ml)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.1 (4.4\u0026ndash;7.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e66.3 (27.6-190.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlobal sclerosis (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0-8.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.1 (0-8.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.616\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChronic tubulointerstitial injury (0/1/2/3, n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e69/47/34/14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46/39/38/13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.389\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIgG deposit, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e164(98.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134(98.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.841\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIgM deposit, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e125(75.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e108(79.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.397\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIgA deposit, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e150(90.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e125(91.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.639\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC3 deposit, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e158(95.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e135(99.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.082\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC1q deposit, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e152(91.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e124(91.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.904\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFRA deposit, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e150(90.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e121(89.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.692\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIgG1 deposit, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e164(98.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e135(99.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.678\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIgG2 deposit, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e141(84.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e108(79.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.209\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIgG3 deposit, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39(23.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21(15.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.081\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIgG4 deposit, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e152(91.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e135(99.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eTreatment responses and kidney outcomes of PMN patients\u003c/h2\u003e\u003cp\u003eAs shown in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, There were 113 (50.2%) patients treated with immunosuppressive regimens. 115 (51.1%) patients achieved complete remission in 18 (12, 36) months and 36 (16.0%) patients achieved partial remission in 8 (4, 15) months. Among them, 10 (4.4%) patients relapsed. During the follow-up period of 36 (24,51) months, 28 (12.4%) patients developed renal dysfunction and 4 (1.8%) patients deteriorated to ESRD.\u003c/p\u003e\u003cp\u003eA follow-up analysis of 225 patients with primary membranous nephropathy revealed that the incidence of renal impairment and the use of immunosuppressive agents were significantly higher in the anti-PLA2R antibody-positive group than in the anti-PLA2R antibody-negative group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of Clinical Remission Rates Between Anti-PLA2R Antibody\u0026ndash;Positive and \u0026ndash;Negative Groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eanti-PLA2R antibody-positive(n\u0026thinsp;=\u0026thinsp;110)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eanti-PLA2R antibody-negative(n\u0026thinsp;=\u0026thinsp;115)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP值\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRemission, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e69(62.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e82(71.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.171\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eComplete remission, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e51(46.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e64(55.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePartial remission, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e18(16.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18(15.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo remission, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e36(32.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e28(24.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.164\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRelapse, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5(4.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5(4.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.943\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKidney dysfunction, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e19(17.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9(7.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.032\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eESKD, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3(2.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1(0.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.282\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eImmunosuppressive\u003c/p\u003e\u003cp\u003etreatments, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e65(59.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e48(41.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eThe clinical and pathological features of PMN patients with C3 deposition\u003c/h2\u003e\u003cp\u003eAs shown in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Patients with stronger C3 deposition exhibited lower serum albumin and complement C3 levels (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and higher serum cholesterol levels, anti-PLA2R antibody concentrations, positive rates of anti-PLA2R antibodies, and proportions of glomerulosclerosis (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical Features of PMN Patients Stratified by C3 Deposition Intensity\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC3 -(N\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eC3 1+(N\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC3 2+ (N\u0026thinsp;=\u0026thinsp;147)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eC3 3+(N\u0026thinsp;=\u0026thinsp;133)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge(years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43.3\u0026thinsp;\u0026plusmn;\u0026thinsp;9.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50.6\u0026thinsp;\u0026plusmn;\u0026thinsp;12.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46.7\u0026thinsp;\u0026plusmn;\u0026thinsp;14.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e49.5\u0026thinsp;\u0026plusmn;\u0026thinsp;15.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.278\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender(male/%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4(44.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5(45.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e84(57.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e75(56.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.784\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum albumin (g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e31.0\u0026thinsp;\u0026plusmn;\u0026thinsp;8.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32.5\u0026thinsp;\u0026plusmn;\u0026thinsp;8.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e26.7\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProteinuria (g/24h)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.9 (2.5\u0026ndash;9.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.8(3.5\u0026ndash;8.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.4(3.5\u0026ndash;8.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.8(3.7\u0026ndash;8.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.994\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum creatinine (umol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e73.7 (70.6\u0026ndash;88.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77.8 (67.9\u0026ndash;96.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e67.9 (58.0\u0026minus;81.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e71.8 (58.4\u0026ndash;92.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.122\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eeGFR(ml/min/1.73m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e106.4(76.8\u0026minus;115.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e96.1(82.7\u0026minus;101.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e101.1(90.6\u0026minus;115.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e98.8(80.2\u0026minus;109.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.058\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUric acid (umol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e389.9\u0026thinsp;\u0026plusmn;\u0026thinsp;127.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e451.2\u0026thinsp;\u0026plusmn;\u0026thinsp;114.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e375.9\u0026thinsp;\u0026plusmn;\u0026thinsp;100.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e381.7\u0026thinsp;\u0026plusmn;\u0026thinsp;114.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.175\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTriglycerides (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.5 (1.5\u0026ndash;4.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.8 (1.9\u0026minus;4.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.1 (1.5\u0026ndash;3.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.1 (1.5\u0026ndash;3.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.542\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCholesterol (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.2(5.6\u0026ndash;7.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.5(5.1\u0026ndash;8.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.5(5.3\u0026ndash;7.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.4(6.2\u0026ndash;9.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-IgG (mg/dl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e580.0(495.0\u0026minus;907.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e876.5(567.0\u0026minus;1140.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e693.5(519.5\u0026minus;850.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e595.5(450.0\u0026minus;821.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.035\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-IgM (mg/dl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e90.7(61.2\u0026minus;145.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e82.3(66.2\u0026ndash;92.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e98.9(69.4\u0026minus;137.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e104.0(75.8\u0026ndash;149.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.206\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-IgA (mg/dl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e208.0(155.0\u0026minus;248.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e209.0(176.0\u0026minus;263.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e200.0(157.5\u0026minus;261.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e201.5(150.5\u0026minus;289.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.722\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-C3(mg/dl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e103.6\u0026thinsp;\u0026plusmn;\u0026thinsp;14.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e120.0\u0026thinsp;\u0026plusmn;\u0026thinsp;28.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e102.6\u0026thinsp;\u0026plusmn;\u0026thinsp;22.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e97.6\u0026thinsp;\u0026plusmn;\u0026thinsp;21.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-C4(mg/dl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.6\u0026thinsp;\u0026plusmn;\u0026thinsp;8.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.7\u0026thinsp;\u0026plusmn;\u0026thinsp;8.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24.2\u0026thinsp;\u0026plusmn;\u0026thinsp;6.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e25.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.208\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-C1q (mg/dl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e203.9\u0026thinsp;\u0026plusmn;\u0026thinsp;27.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e195.6\u0026thinsp;\u0026plusmn;\u0026thinsp;30.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e203.8\u0026thinsp;\u0026plusmn;\u0026thinsp;36.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e201.3\u0026thinsp;\u0026plusmn;\u0026thinsp;35.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.850\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnti-PLA2R antibody level\u003c/p\u003e\u003cp\u003e(IU/ml)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.1 (4.5\u0026ndash;6.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.9 (4.1\u0026ndash;8.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.0 (4.7\u0026ndash;35.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e25.4 (7.2\u0026minus;130.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnti-PLA2R antibody positivity, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1(11.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2(18.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e62(42.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e75(56.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlobal sclerosis (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0(0.0\u0026ndash;0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0(0.0\u0026minus;9.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0(0.0\u0026minus;7.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.5(0.0\u0026minus;10.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChronic tubulointerstitial injury (0/1/2/3, n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2/3/4/0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4/3/2/2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e62/41/37/7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e47/39/29/18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.208\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eThe clinical and pathological features of PMN patients with C1q deposition\u003c/h2\u003e\u003cp\u003eAs shown in Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Serum cholesterol levels were higher in the group with stronger C1q deposition in the kidney tissue (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and there were no significant differences in other indexes among the groups.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical Features of PMN Patients Stratified by C1q Deposition Intensity\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC1q- (N\u0026thinsp;=\u0026thinsp;29)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eC1q 1+(N\u0026thinsp;=\u0026thinsp;56)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC1q 2+(N\u0026thinsp;=\u0026thinsp;215)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge(years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47.9\u0026thinsp;\u0026plusmn;\u0026thinsp;15.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50.2\u0026thinsp;\u0026plusmn;\u0026thinsp;11.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e47.4\u0026thinsp;\u0026plusmn;\u0026thinsp;14.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.422\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender(male/%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15(51.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35(62.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e127(59.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.632\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum albumin (g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28.7\u0026thinsp;\u0026plusmn;\u0026thinsp;6.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.849\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProteinuria (g/24h)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.2(3.6\u0026ndash;7.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.0(3.4\u0026ndash;8.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.8(3.9\u0026ndash;8.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.900\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum creatinine (umol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e66.3(57.1\u0026ndash;74.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76.2(63.1\u0026ndash;99.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e71.0(58.0\u0026minus;83.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.054\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eeGFR(ml/min/1.73m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e98.4(91.1\u0026minus;108.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95.3(75.7\u0026minus;107.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e101.4(88.3\u0026minus;114.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.067\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUric acid (umol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e352.6\u0026thinsp;\u0026plusmn;\u0026thinsp;114.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e377.7\u0026thinsp;\u0026plusmn;\u0026thinsp;101.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e386.6\u0026thinsp;\u0026plusmn;\u0026thinsp;109.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.286\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTriglycerides (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.1(1.3\u0026minus;3.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.3(1.4\u0026ndash;3.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.1(1.5\u0026ndash;3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.825\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCholesterol (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.1(4.9\u0026minus;7.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.4(5.8\u0026ndash;8.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.0(5.9\u0026ndash;8.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.033\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-IgG (mg/dl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e680.5(526.5\u0026minus;834.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e638.5(458.7\u0026minus;838.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e624.0(493.0\u0026minus;860.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.837\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-IgM (mg/dl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e94.5 (75.4\u0026minus;121.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e93.4 (63.5\u0026ndash;133.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e104.0 (74.0\u0026minus;144.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.306\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-IgA (mg/dl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e233.0(169.0\u0026minus;322.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e176.5(143.0\u0026minus;242.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e205.0(159.0\u0026minus;272.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.124\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-C3(mg/dl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e106.5\u0026thinsp;\u0026plusmn;\u0026thinsp;19.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e102.7\u0026thinsp;\u0026plusmn;\u0026thinsp;26.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99.8\u0026thinsp;\u0026plusmn;\u0026thinsp;21.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.903\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-C4(mg/dl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24.7\u0026thinsp;\u0026plusmn;\u0026thinsp;6.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.336\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-C1q (mg/dl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e200.2\u0026thinsp;\u0026plusmn;\u0026thinsp;28.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e196.8\u0026thinsp;\u0026plusmn;\u0026thinsp;36.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e204.2\u0026thinsp;\u0026plusmn;\u0026thinsp;35.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.111\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnti-PLA2R antibody level\u003c/p\u003e\u003cp\u003e(IU/ml)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.9(5.1\u0026ndash;75.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.9(4.5\u0026ndash;79.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12.6(5.0\u0026minus;58.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.743\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnti-PLA2R antibody positivity, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15(51.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31(55.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e115(53.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.946\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlobal sclerosis (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0(0.0\u0026minus;6.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.4(0.0\u0026minus;8.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0(0.0\u0026minus;8.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.437\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChronic tubulointerstitial injury (0/1/2/3, n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8/12/7/2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17/19/14/6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e90/55/51/19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.451\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eRisk factors for non-remission in PMN patients\u003c/h2\u003e\u003cp\u003e\u003cb\u003eAs shown in\u003c/b\u003e Table \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Logistic regression analysis of non-remission factors in patients with primary membranous nephropathy identified decreased serum albumin (OR\u0026thinsp;=\u0026thinsp;0.931, 95% CI: 0.868\u0026ndash;0.999, P\u0026thinsp;=\u0026thinsp;0.047) and exacerbation of glomerulosclerosis (OR\u0026thinsp;=\u0026thinsp;1.038, 95% CI: 1.010\u0026ndash;1.067, P\u0026thinsp;=\u0026thinsp;0.008) as independent risk factors for non-remission of PMN patients.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe logistic regression analysis of risk factors for non-remission in PMN patients.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnivariate analysis\u003c/p\u003e\u003cp\u003eOR(95%CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMultivariate analysis OR(95%CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge(years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.017(0.995\u0026ndash;1.039)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.122\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender(male/%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.044(0.563\u0026ndash;1.938)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.890\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProteinuria\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.036(0.951\u0026ndash;1.128)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.422\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum albumin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.907(0.856\u0026ndash;0.961)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.931(0.868\u0026ndash;0.999)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.047\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum creatinine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.001(0.996\u0026ndash;1.006)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.805\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUric acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.997(0.994-1.000)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.038\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.997(0.994\u0026ndash;1.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.105\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTriglycerides\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.958(0.806\u0026ndash;1.138)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.622\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCholesterol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.121(0.987\u0026ndash;1.272)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-IgG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.999(0.998-1.000)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.000(0.998\u0026ndash;1.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.686\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-IgM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.003(0.997\u0026ndash;1.008)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.315\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-IgA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.000(0.997\u0026ndash;1.003)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.922\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-C3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.979(0.964\u0026ndash;0.995)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.988(0.971\u0026ndash;1.005)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.173\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-C4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.017(0.977\u0026ndash;1.059)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.406\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-C1q\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.998(0.990\u0026ndash;1.007)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.678\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eeGFR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.994(0.983\u0026ndash;1.006)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.310\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnti-PLA2R antibody level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.001(1.000-1.003)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.001(0.999\u0026ndash;1.002)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.244\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnti-PLA2R antibody positivity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.798(0.973\u0026ndash;3.321)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.061\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC1q deposition\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.962(0.620\u0026ndash;1.494)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.864\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC3 deposition\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.511(0.929\u0026ndash;2.457)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.096\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChronic tubulointerstitial injury\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.227(0.864\u0026ndash;1.745)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.253\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlobal sclerosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.028(1.003\u0026ndash;1.053)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.031\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.038(1.010\u0026ndash;1.067)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eRisk factors for renal dysfunction in PMN patients\u003c/h2\u003e\u003cp\u003eAs shown in Table \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, Multivariate Cox regression analysis of renal dysfunction in these patients demonstrated that older age (HR\u0026thinsp;=\u0026thinsp;1.048, 95% CI: 1.007\u0026ndash;1.091, P\u0026thinsp;=\u0026thinsp;0.022) and increased intensity of C3 deposition in renal tissue (HR\u0026thinsp;=\u0026thinsp;2.170, 95% CI: 1.083\u0026ndash;4.348, P\u0026thinsp;=\u0026thinsp;0.029) were independent risk factors for renal dysfunction.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe Cox regression analysis of risk factors for renal dysfunction in PMN patients.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnivariate analysis\u003c/p\u003e\u003cp\u003eHR(95%CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMultivariate analysis HR(95%CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge(years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.088(1.051\u0026ndash;1.126)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.048(1.007\u0026ndash;1.091)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender(male/%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.677(0.345\u0026ndash;1.328)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.257\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProteinuria\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.025(0.936\u0026ndash;1.123)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.593\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum albumin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.963(0.908\u0026ndash;1.021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.204\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum creatinine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.005(1.003\u0026ndash;1.007)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.999(0.994\u0026ndash;1.005)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.807\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUric acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.003(1.000-1.006)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.089\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eeGFR(ml/min/1.73m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.962(0.951\u0026ndash;0.972)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.980(0.957\u0026ndash;1.003)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.082\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-IgG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.002(1.001\u0026ndash;1.003)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.001(0.999\u0026ndash;1.002)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.329\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-IgM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.995(0.987\u0026ndash;1.002)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.174\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-IgA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.002(1.000-1.005)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-C3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.990(0.975\u0026ndash;1.006)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.225\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-C4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.030(0.992\u0026ndash;1.071)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.127\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum-C1q\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.994(0.985\u0026ndash;1.003)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.189\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnti-PLA2R antibody level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.001(0.999\u0026ndash;1.002)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.728\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnti-PLA2R antibody positivity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.501(0.751\u0026ndash;2.999)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC3 deposition\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.343(1.672\u0026ndash;6.683)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.170(1.083\u0026ndash;4.348)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.029\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC1q deposition\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.001(0.608\u0026ndash;1.647)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.998\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChronic tubulointerstitial injury\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.696(2.396\u0026ndash;5.701)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.802(0.868\u0026ndash;3.738)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.114\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlobal sclerosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.039(1.023\u0026ndash;1.056)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.990(0.966\u0026ndash;1.016)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.456\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo remission\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.589(1.310\u0026ndash;5.117)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.482(0.625\u0026ndash;3.515)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.372\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eMembranous nephropathy (MN) is one of the most common causes of adult-onset nephrotic syndrome. Secondary MN is frequently associated with infections (such as hepatitis B virus), autoimmune diseases like systemic lupus erythematosus, or malignancies. A diagnosis of primary membranous nephropathy (PMN) is typically established when these secondary causes are excluded through clinical and serological evaluation and confirmed via renal biopsy. Interestingly, recent reports have described atypical MN cases with immune deposits not only on the subepithelial side of the glomerular basement membrane but also in mesangial and subendothelial areas, despite lacking an identifiable secondary etiology [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. These cases, once considered \u0026ldquo;atypical MN,\u0026rdquo; may in fact represent part of the PMN spectrum.\u003c/p\u003e\u003cp\u003eThe identification of anti-phospholipase A2 receptor (PLA2R) antibodies by Beck et al. in 2009 [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] was a pivotal discovery in PMN research. These circulating autoantibodies are detected in approximately 70\u0026ndash;80% of patients with idiopathic MN and are strongly associated with disease activity and prognosis [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Although initially believed to be specific for PMN, subsequent studies found anti-PLA2R antibodies in patients with hepatitis B virus (HBV)-associated MN and malignancy-related MN [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Thus, while highly suggestive, seropositivity for anti-PLA2R does not definitively exclude secondary MN, underscoring the need for careful clinical evaluation and longitudinal follow-up. Additionally, deposition of C1q\u0026mdash;traditionally a marker of secondary MN\u0026mdash;has occasionally been observed in otherwise typical PMN cases, further complicating the differential diagnosis [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn our cohort of 302 biopsy-confirmed PMN patients, we observed that those who were anti-PLA2R antibody-positive had significantly higher 24-hour urinary protein and serum cholesterol levels, along with lower serum albumin and IgG levels compared to antibody-negative patients. These findings suggest a more active disease state in antibody-positive individuals. Furthermore, IgG4 deposition in renal tissue was significantly more frequent in this group, consistent with the established role of IgG4 in PLA2R-mediated immune complex formation.\u003c/p\u003e\u003cp\u003eImportantly, during follow-up, the antibody-positive group exhibited a higher incidence of renal dysfunction and received immunosuppressive therapy more frequently. These observations reinforce the prognostic value of anti-PLA2R antibody levels in guiding treatment decisions and risk stratification.\u003c/p\u003e\u003cp\u003eComplement activation is another key feature of PMN pathogenesis. Granular deposition of IgG and C3 along the glomerular capillary wall is a pathological hallmark of the disease. Our results showed that stronger C3 deposition was significantly associated with reduced serum albumin and C3 levels, elevated serum cholesterol, higher anti-PLA2R antibody titers, greater anti-PLA2R positivity, and increased glomerulosclerosis. Furthermore, multivariate Cox regression identified C3 deposition as an independent predictor of renal dysfunction, highlighting its clinical relevance.\u003c/p\u003e\u003cp\u003eThese findings are in line with previous work from Peking University First Hospital, which demonstrated that higher C3 staining intensity was correlated with more severe proteinuria, lower albumin levels, and increased anti-PLA2R antibody levels and serum creatinine, whereas the intensity of IgG deposition showed no such associations [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. It has been hypothesized that intense glomerular C3 deposition reflects enhanced complement activation and systemic C3 consumption, contributing to progressive glomerular injury and adverse renal outcomes [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Supporting this, several studies have linked low serum C3 levels with poor prognosis in PMN [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], emphasizing its potential as a biomarker of disease severity [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe observed relationship between C3 deposition, anti-PLA2R antibody levels, and clinical severity suggests that PLA2R\u0026ndash;IgG immune complex formation may serve as a trigger for autoimmune injury, with complement activation mediating subsequent glomerular damage. Complement components such as C3a and C5a have been found to be elevated in both serum and urine of PMN patients, further supporting this pathogenic mechanism [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Although classical pathway activation is generally linked to C1q deposition and IgG1/IgG3 subclasses, PLA2R-associated IgG4 antibodies\u0026mdash;typically considered non-complement activating\u0026mdash;may trigger the lectin or alternative pathways. This is supported by evidence indicating that mannan-binding lectin can bind IgG4\u0026ndash;PLA2R complexes and activate the lectin pathway[\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], while C3 deposition in antibody-negative PMN suggests involvement of the alternative pathway [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe pathogenic role of complement activation in PMN progression suggests that targeting complement components may be a promising therapeutic strategy[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. However, the mechanisms determining which complement pathway predominates in a given patient remain unclear. In our study, despite the frequent detection of C1q deposition, we did not observe any significant association between C1q staining intensity and anti-PLA2R levels, clinical indices, or renal outcomes. These findings are consistent with previous reports suggesting that classical pathway activation may occur in a subset of PMN patients but is not necessarily linked to disease severity or progression [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRecent studies have highlighted the pivotal role of complement activation in the pathogenesis of membranous nephropathy (MN), with the C3a/C3aR signaling pathway emerging as a key effector mechanism in complement-mediated podocyte injury. It has been demonstrated that both plasma C3a levels and glomerular C3aR expression are significantly elevated in MN patients compared to healthy individuals, and these elevations correlate with disease severity and prognosis[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In vitro experiments revealed that C3a derived from the plasma of MN patients disrupts podocyte function and viability, effects that are effectively mitigated by C3aR antagonists. Moreover, in vivo studies using Heymann nephritis rat models\u0026mdash;a classical model for MN\u0026mdash;confirmed that pharmacologic blockade of C3aR can attenuate renal injury[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. These findings provide compelling evidence that the C3a/C3aR axis plays a crucial role in MN pathogenesis and represents a promising therapeutic target.\u003c/p\u003e\u003cp\u003eAdditionally, our study contributes novel insights into the mechanisms of complement-mediated podocyte injury by identifying pyroptosis as a key mode of cell death involved in this process. We further demonstrate that mitochondrial dysfunction may underlie this pyroptotic response. These observations suggest that targeting pyroptosis could represent an innovative therapeutic strategy for MN in future research [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn summary, our study demonstrates that both anti-PLA2R antibody positivity and pronounced glomerular C3 deposition are associated with more severe clinical manifestations and unfavorable renal outcomes in PMN. These markers may serve as useful tools for prognostic assessment and therapeutic decision-making. Moreover, our findings highlight the critical role of complement activation\u0026mdash;particularly via non-classical pathways\u0026mdash;in PMN pathogenesis. Further prospective and mechanistic studies are warranted to explore complement-targeted therapies in this disease.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFinancial support\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThis work was supported by College-level projects in China-Japan Friendship Hospital ( 2017-2-QN-19)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCRediT authorship contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eXQQ\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e Writing \u0026ndash; review \u0026amp; editing, Writing \u0026ndash; original draft, Software, Project administration, Methodology, Investigation, Formal analysis, Data curation. \u003cstrong\u003e\u003cem\u003eLJY\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e：\u003c/em\u003e\u003c/strong\u003eData curation, Methodology, Writing-original draft, Formal analysis. \u003cstrong\u003e\u003cem\u003eZC:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eData curation, Methodology. \u003cstrong\u003e\u003cem\u003eTM:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eData curation, Methodology, Validation. \u003cstrong\u003e\u003cem\u003eLWG:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eSupervision, Resources, Funding acquisition, Conceptualization. Project administration. \u0026nbsp;All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the guidelines of the Declaration of Helsinki and was approved by the Ethics Committee of China-Japan Friendship Hospital (approval number: 2019-17-K12).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all study participants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available on request\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWu YQ, Wang Z, Xu HF, et al. Frequency of primary glomerulardisease in northeastern China [J]. Braz J Med Biol Res, 2011, 44(8): 810-813.\u003c/li\u003e\n\u003cli\u003eLi LS, Liu ZH. Epidemiologic data of renal diseases from a single unit in China: analysis based on 13, 519 renal biopsies [J]. Kidney Int, 2004, 66(3): 920-923.\u003c/li\u003e\n\u003cli\u003eBeck LH, SalantDJ. Membranous nephropathy: recent travels and new roads ahead［J］. Kidney Int, 2010, 77（9）: 765-70. DOI：10.1038/ki.2010.34.\u003c/li\u003e\n\u003cli\u003ePonticelli C, Glassock RJ. Glomerular diseases: membranous nephropathy-a modern view. Clin J Am Soc Nephrol (2014) 9 (3):609\u0026ndash;16. doi: 10.2215/CJN.04160413\u003c/li\u003e\n\u003cli\u003eBeck LH, Bonegio RGB, Lambeau G, et al. M-type phospholipase A2 receptor as target antigen in idiopathic membranous nephropathy. N Engl J Med. 2009;361(1):11-21. doi: 10.1056/NEJMoa0810457. \u003c/li\u003e\n\u003cli\u003eQin W, Beck LH, Zeng C, et al. Anti-phospholipase A2 receptor antibody in membranous nephropathy. J Am Soc Nephrol. 2011;22(6):1137\u0026ndash;1143. doi: 10.1681/ASN.2010090967. \u003c/li\u003e\n\u003cli\u003eStevens LA, Claybon MA, Schmid CH, Chen J, Horio M, Imai E, et al. Evaluation of the chronic kidney disease epidemiology collaboration equation for estimating the glomerular filtration rate in multiple ethnicities. Kidney Int (2011) 79 (5): 555-62. doi: 10.1038/ki.2010.462\u003c/li\u003e\n\u003cli\u003eGlassock RJ. Secondary membranous glomerulonephritis. Nephrol Dial Transplant(1992) 7(Suppl 1): 64-71. \u003c/li\u003e\n\u003cli\u003eXie Q, Li Y, Xue J, et al. Renal phospholipase A2 receptor in hepatitis B virus-associated membranous nephropathy. Am J Nephrol. 2015;41(4-5):345\u0026ndash;353. doi: 10.1159/000431331. \u003c/li\u003e\n\u003cli\u003eGunnarsson I, Schlumberger W, R\u0026ouml;nnelid J.. Antibodies to M-type phospholipase A2 receptor (PLA2R) and membranous lupusnephritis. Am J Kidney Dis. 2012;59(4):585\u0026ndash;586. doi: 10.1053/j.ajkd.2011.10.044.\u003c/li\u003e\n\u003cli\u003eL\u0026ouml;nnbro-Widgren J, Ebefors K, M\u0026ouml;lne J, et al. Glomerular IgG subclasses in idiopathic and malignancy-associated membranous nephropathy. Clin Kidney J. 2015;8(4):433\u0026ndash;439. doi: 10.1093/ckj/sfv049. \u003c/li\u003e\n\u003cli\u003eJiang Z, Cai M, Dong B, et al. Clinicopathological features of atypical membranous nephropathy with unknown \u0026shy;etiology in adult Chinese patients. Medicine. 2018;97(32):32(e11608. doi: 10.1097/MD.0000000000011608. \u003c/li\u003e\n\u003cli\u003eZhang XD, Cui Z, Zhang MF, et al. Clinical implications of pathological features of primary membranous nephropathy[J]. BMC Nephrology, 2018, 19(1):215. DOI: 10.1186/s12882- 018- 1011-5.\u003c/li\u003e\n\u003cli\u003eMufan Zhang, Jing Huang, Yimiao Zhang, et al. Complement activation products in the circulation and urine of primary membranous nephropathy. BMC Nephrology (2019) 20:313 .\u003c/li\u003e\n\u003cli\u003eTsai SF,Wu MJ,Chen CH.Low serum C3 level,high neutrophil-lymphocyte-ratio, and high platelet-lymphocyte-ratio all predicted poor long-term renal survivals in biopsy -confirmed idiopathic membranous nephropathy [J].Sci Rep,2019,9 (1):6209. \u003c/li\u003e\n\u003cli\u003eYamaguchi M,Ando M,Katsuno T,et al.Urinary protein and renal prognosis in idiopathic membranous nephropathy:a multicenter retrospective cohort study in Japan [J].Renal Failure, 2018,40(1):435-441.\u003c/li\u003e\n\u003cli\u003eDong J,Peng T,Gao J,et al. A pilot and comparative study between pathological and serological levels of immunoglobulin and complement among three kinds of primary glomerulonephritis[J]. BMC Immunology,2018,19(1):18.\u003c/li\u003e\n\u003cli\u003eBally S, Debiec H, Ponard D, Dijoud F, Rendu J, Faure J, Ronco P, Dumestre-Perard C. Phospholipase A2 receptor-related membranous nephropathy and Mannan-binding lectin deficiency. J Am Soc Nephrol. 2016;27(12):3539\u0026ndash;44.\u003c/li\u003e\n\u003cli\u003eYang Y, Wang C, Jin L, He F, et al. IgG4 anti-phospholipase A2 receptor might activate lectin and alternative complement pathway meanwhile in idiopathic membranous nephropathy:an inspiration from a cross-sectional study.Immunol Res. 2016;64(4):919\u0026ndash;30.\u003c/li\u003e\n\u003cli\u003ePetri C, Thiel S, Jensenius JC, Herlin T. Investigation of complement-activating pattern recognition molecules and associated enzymes as possible inflammatory markers in Oligoarticular and systemic juvenile idiopathic arthritis. J Rheumatol. 2015;42(7):1252\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eHaddad G, Lorenzen JM, Ma H, de Haan N, Seeger H, Zaghrini C, et al. Altered glycosylation of IgG4 promotes lectin complement pathway activation in anti-PLA2R-associated membranous nephropathy. J Clin Invest. 2021;131(5):140453. doi: 10.1172/JCI140453.\u003c/li\u003e\n\u003cli\u003eBlom AM, Corvillo F, Magda M, Stasilojc G, et al.Testing the activity of complement convertases in serum/plasma for diagnosis of C4NeF-mediated C3 glomerulonephritis. J Clin Immunol. 2016;36(5):517\u0026ndash;27.\u003c/li\u003e\n\u003cli\u003eMathern DR, Heeger PS. Molecules great and small: the complement system. Clin J Am Soc Nephrol. 2015;10(9):1636\u0026ndash;50.\u003c/li\u003e\n\u003cli\u003eMa H, Sandor DG, Beck LH Jr. The role of complement in membranous nephropathy. Semin Nephrol. 2013;33(6):531\u0026ndash;42.\u003c/li\u003e\n\u003cli\u003eMufan Zhang, Zhao Cui, Yimiao Zhang, et al. Clinical and prognostic significance of glomerular C1q deposits in primary MN. Clinica Chimica Acta.485 (2018) :152\u0026ndash;157.\u003c/li\u003e\n\u003cli\u003eKistler AD, Salant DJ. Complement activation and effector pathways in membranous nephropathy. Kidney Int. 2024 Mar;105(3):473-483. doi: 10.1016/j.kint.2023.10.035.\u003c/li\u003e\n\u003cli\u003eGao S, Cui Z, Zhao MH.Complement C3a and C3a Receptor Activation Mediates Podocyte Injuries in the Mechanism of Primary Membranous Nephropathy. J Am Soc Nephrol. 2022 Sep;33(9):1742-1756. doi: 10.1681/ASN.2021101384.\u003c/li\u003e\n\u003cli\u003eZhang Q, Bin S, Budge K, Petrosyan A, Villani V, Aguiari P, Vink C. C3aR-initiated signaling is a critical mechanism of podocyte injury in membranous nephropathy. JCI Insight. 2024 Jan 16;9(4):e172976. doi: 10.1172/jci.insight.172976.\u003c/li\u003e\n\u003cli\u003eShanshen Yu , Jia Sun. A review of progress on complement and primary membranous nephropathy. Medicine. 2024;103(29):e38990. doi: 10.1097/MD.0000000000038990\u003c/li\u003e\n\u003cli\u003eWang H, Lv D, Jiang S, Hou Q, Zhang L, Li S. Complement induces podocyte pyroptosis in membranous nephropathy by mediating mitochondrial dysfunction. Cell Death Dis. 2022 Mar 29;13(3):281. doi: 10.1038/s41419-022-04737-5.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Primary membranous nephropathy, anti-PLA2R antibody, complement, prognosis, renal pathology","lastPublishedDoi":"10.21203/rs.3.rs-6637635/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6637635/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eThe pathogenic roles of serum anti-phospholipase A2 receptor (PLA2R) antibodies and complement deposition in renal tissue remain incompletely understood in primary membranous nephropathy (PMN). This study aimed to evaluate their prevalence and associations with clinicopathological features and renal prognosis.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA retrospective analysis was conducted in 302 biopsy-proven PMN patients, stratified into anti-PLA2R antibody-positive (\u0026ge;\u0026thinsp;20 IU/mL, n\u0026thinsp;=\u0026thinsp;136) and -negative (\u0026lt;\u0026thinsp;20 IU/mL, n\u0026thinsp;=\u0026thinsp;166) groups. Baseline clinical data, renal histopathology, and follow-up outcomes were analyzed. Multivariate logistic regression and Cox proportional hazards models were applied to identify independent predictors of non-remission and renal dysfunction.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eCompared to antibody-negative patients, those with anti-PLA2R positivity had significantly higher proteinuria and serum cholesterol levels, lower albumin and IgG levels, and a higher rate of glomerular IgG4 deposition (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Among 225 patients with follow-up data, the antibody-positive group exhibited more frequent renal dysfunction and increased use of immunosuppressive therapy. Stronger C3 deposition in renal tissue was associated with lower serum albumin and C3 levels, higher anti-PLA2R antibody titers, and more glomerulosclerosis. Multivariate analyses identified hypoalbuminemia and glomerulosclerosis as independent predictors of non-remission, while older age and intense C3 deposition independently predicted renal dysfunction.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eAnti-PLA2R antibody positivity and prominent C3 deposition are associated with more severe clinical presentation and poorer renal outcomes in PMN. These findings highlight their potential as prognostic biomarkers and therapeutic targets.\u003c/p\u003e","manuscriptTitle":"Serum Anti-PLA2R Antibody and Renal Complement Deposition: Associations with Clinicopathological Features in Primary Membranous Nephropathy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-14 08:31:42","doi":"10.21203/rs.3.rs-6637635/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0f11bafa-605d-4308-b06b-4caad5f02bd7","owner":[],"postedDate":"July 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-03T07:54:26+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-14 08:31:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6637635","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6637635","identity":"rs-6637635","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}