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/lp/ou_press/genetic-analysis-of-the-complement-pathway-in-c3-glomerulopathy-m8SKDrRwBD
- Publisher
- Oxford University Press
- Copyright
- © The Author(s) 2018. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.
- ISSN
- 0931-0509
- eISSN
- 1460-2385
- DOI
- 10.1093/ndt/gfy033
- Publisher site
- See Article on Publisher Site
Abstract
Abstract Background C3 glomerulopathy often presents with a membranoproliferative glomerulonephritis (MPGN) pattern, and is principally caused by unrestricted activation of the complement alternative pathway. Genetic abnormalities of the complement system critically implicate in the pathogenesis of C3 glomerulopathy, but a systemic profile remains open, especially in Asia. Methods In this study, we completed a comprehensive screen of 11 candidate alternative pathway genes by using targeted genomic enrichment and massively parallel sequencing on 43 patients with sporadic C3 glomerulopathy, which were classified as dense deposit disease (DDD; n = 10) and C3 glomerulonephritis (C3GN; n = 33) cases. An additional 24 patients with immune complex-mediated MPGN were also enrolled. Results In total, 4 novel and 16 rare variants were identified: one was classified as likely pathogenic, and the remaining 19 were of uncertain significance. Three variants reportedly led to functional deficiency with supporting evidences. Variants in the CFH, CFI, CD46 and C3 genes were most frequently detected. A defective control of the complement alternative pathway due to hereditary abnormalities was found at frequencies of 50%, 27% and 17% in DDD, C3GN and immune complex-mediated MPGN, respectively. Irrespective of histological type, the patients with likely pathogenic and uncertain significant variants were clinically similar to those without. Conclusions Accurate genetic screening can give rise to progress in understanding the pathogenesis of C3 glomerulopathy, and the correct assignment of pathogenicity classification is of great importance for better patient care and prognostic or therapeutic advice. C3 glomerulonephritis, C3 glomerulopathy, complement system, dense deposit disease, genetic analysis INTRODUCTION C3 glomerulopathy has emerged as a kidney disease entity as knowledge of membranoproliferative glomerulonephritis (MPGN) has increased on the basis of pathophysiology [1]. MPGN kidney biopsies that show predominant glomerular C3 deposition with little or no immunoglobulin staining are referred to as complement-mediated MPGN cases, and defined as C3 glomerulopathy; otherwise, cases that have clear immunoglobulins accompanying the complement on immunofluorescence tests are referred to as immune complexes-mediated MPGN cases (shorted as IC-MPGN) [2]. C3 glomerulopathy is further divided into two groups, based on the presence or absence of highly intramembranous electron-dense deposits, including dense deposit disease (DDD) and C3 glomerulonephritis (C3GN). The current classification represents a landmark breakthrough in understanding the pathomechanism of C3 glomerulopathy, and increasing evidence recognizes abnormalities in the complement system’s activating or regulating factors as the main cause of those disorders. The complement cascade reaction is initiated by three pathways, including one in which the alternative pathway is spontaneously and continuously activated, followed by an amplification loop. Uncontrolled activation of the alternative pathway deposits excessive complement component and membrane attack complex in the glomeruli. Pathological observations from C3 glomerulopathy patients indicate selective alternative pathway overactivation and C3 consumption in the fluid phase. Conversely, the IC-MPGN cases have been distinguished as activated through the classical pathway [3]. Dysfunction of the alternative pathway occurs principally due to acquired or genetic abnormalities. Pedigree studies and limited genome-wide association studies allowed the recognition of genetic variants of different types as causes of the complement dysregulation. In C3 glomerulopathy, current knowledge is insufficient and not comparable to that of atypical hemolytic uremic syndrome (aHUS) [4], which shares common genetic risk factors with C3 glomerulopathy [5]. The recommended minimum set of genes that should be screened in C3 glomerulopathy includes CFH, CD46, CFI, C3, CFB, THBD, CFHR1, CFHR5 and DGKE [4], which may also indicate that a broad range of genetic contributors definitely implicate in the pathogenesis. Successful application of targeted genomic enrichment and next-generation sequencing generates a substantial number of variants, which definitely helps improve clinically relevant genetic testing. However, an evident requisite—and a new challenge—posed by the identification of abundant genetic information lies in rigorous assessment and expert interpretation. Correct assignment of pathogenicity is of great importance for prognostic and therapeutic advice [6]. In addition, inherited defects often exhibit ethnic differences, and the genetic profile of the complement system remains open. In this article, we use multigene panels to describe genetic characteristics in a relatively large cohort of patients from Eastern China who have C3 glomerulopathy and IC-MPGN. The genotype–phenotype correlations are further analyzed in this article, as well. MATERIALS AND METHODS Patients Kidney biopsies between September 1985 and February 2014, from the Renal Disease Biobank of the National Clinical Research Center of Kidney Diseases, were centrally re-reviewed by two expert pathologists, and final diagnoses were made based on their independent comments. Immunofluorescence was redone on the previous sections when necessary. Eventually, 43 patients were enrolled with a definite diagnosis of C3GN (n = 33) and DDD (n = 10) based on the pathologic criteria in the 2013 consensus report [1]. An additional 24 patients with primary IC-MPGN were diagnosed, based on the presence of typical histological findings and the absence of a recognized etiology. Detailed definitions for patient inclusion and exclusion are described in this article’s Supplementary Methods section, and the time of individual patient biopsies is recorded in Supplementary data, Figure S1. The majority (73%) of the C3GN cases were diagnosed after 2010. Nine patients experienced repeated kidney biopsies. In some cases, we observed progressive tubulointerstitial fibrosis. While no case changed by time span on histological type, subendothelial and mesangial C3 deposits in patients with C3 glomerulopathy were evident by immunohistochemistry as in the past. Informed consent was obtained from each patient, and the procedure was approved by the Ethics Committee of Nanjing University, School of Medicine. Detailed clinical and pathological data were collected at the time of the first kidney biopsy. Acute kidney injury (AKI) was defined according to the Kidney Disease Outcomes Quality Initiative clinical practice guidelines. AKI was defined as an increase of ≥0.3 mg/dl (26 μmol/l) in serum creatinine (SCr) within 48 h or ≥1.5 times the baseline, with renal impairment well-known or presumed to have occurred within the previous 7 days, or urine volume ≤0.5 ml/kg/h for 6 h (K/DOQI). All cases were regularly followed up at the outpatient clinic until February 2014, and the endpoint was defined as reaching AKI or estimated glomerular filtration rate (eGFR) <15 mL/min/1.73 m2. Target genomic enrichment and next-generation sequencing Genomic DNA was extracted from blood (GentraPure gene kit, Qiagen Inc., Valencia, CA, USA). The Reference Sequence coding exons of the 11 candidate complement genes were targeted for sequencing, including C3 (NM_000064), CD46 (NM_002389), CFB (NM_001710), CFH (NM_000186), CFHR1 (NM_002113), CFHR2 (NM_005666), CFHR3 (NM_021023), CFHR4 (NM_006684), CFHR5 (NM_030787), CFI (NM_000204) and THBD (NM_000361). After sequencing, the mean reads generated per sample was 326 601, with quality control of 87–94%; sequencing results were credible (Supplementary data, Table S1). Detailed methods for capture design, library preparation and Ion Torrent sequencing has been previously described [7, 8]. Variant calling and prioritization Variant filtration and classification workflow is shown in Figure 1 . A total of 6233 (86.0%) variants passed quality control, among which 2278 variants were filtered by focusing on nonsynonymous substitutions, frame shifts, splicing site changes or indels. These variants were further cross-referenced with data from the Exome Aggregation Consortium (ExAC) [exac.broadinstitute.org], 1000 Genomes [www.1000genomes.org] and the NHLBI Exome Sequencing Project (ESP) databases [evs.gs.washington.edu], and analyzed in comparison with 100 local healthy controls. They were further classified following the international guidelines based on minor allele frequency (MAF), nucleotide effect, in silico prediction and functional evidence [9]. The potential pathogenicity was evaluated by five online prediction methods, including SIFT [http://sift.jcvi.org], Align-GVGD [http://agvgd.iarc.fr], PROVEN [http://provean.jcvi.org/index.php], SNAP [https://rostlab.org/services/snap/] and PolyPhen 2.0 [http://genetics.bwh.harvard.edu/pph2/dbsearch.shtml]. Pathogenicity score was calculated as the sum of tools predicting the variant to be deleterious. Missense variants were considered as likely deleterious when the pathogenicity score was ≥3. Evolutionary sequence conservation was estimated by employing the Consurf server [10] [http://consurf.tau.ac.il]. The amino acids labeled in corresponding position are colored by their conservation grades using the color coding bar, with turquoise-through-maroon indicating variable-through-conserved (Figure 2). FIGURE 1 View largeDownload slide Variant filtration and classification. Variants were filtered by focusing on nonsynonymous substitutions, frame shifts, splicing site changes or indels variations, and further cross-referenced with data from the ExAC, 1000G and ESP databases and analyzed in comparison with 100 local healthy controls. Common variants with a MAF value of >1% in any population were defined as benign or likely benign and, therefore, were excluded. Those identified as novel or reported rare variants were further classified based on the international guidelines for variant interpretation [9]. FIGURE 1 View largeDownload slide Variant filtration and classification. Variants were filtered by focusing on nonsynonymous substitutions, frame shifts, splicing site changes or indels variations, and further cross-referenced with data from the ExAC, 1000G and ESP databases and analyzed in comparison with 100 local healthy controls. Common variants with a MAF value of >1% in any population were defined as benign or likely benign and, therefore, were excluded. Those identified as novel or reported rare variants were further classified based on the international guidelines for variant interpretation [9]. FIGURE 2 View largeDownload slide Location and evolutionary sequence conservation of overall identified variants. Locations of variants were labeled in the corresponding domain of individual complement proteins. Evolutionary sequence conservation was estimated employing the Consurf server [10] (http://consurf.tau.ac.il). The amino acids are colored using the color-coding bar according to their conservation grades, with turquoise-through-maroon indicating variable-through-conserved (top right). FIGURE 2 View largeDownload slide Location and evolutionary sequence conservation of overall identified variants. Locations of variants were labeled in the corresponding domain of individual complement proteins. Evolutionary sequence conservation was estimated employing the Consurf server [10] (http://consurf.tau.ac.il). The amino acids are colored using the color-coding bar according to their conservation grades, with turquoise-through-maroon indicating variable-through-conserved (top right). Common variants with MAF >1% in any population are either ‘likely benign’ or ‘benign’, and were, therefore, excluded. Ultra-rare variants (with MAF <0.1%) that lead to protein sequence variations, coupled with multiple lines of computational evidence, were classified as either pathogenic or likely pathogenic, while variants with well-established in vitro or in vivo functional studies that indicate a damaging effect were labeled pathogenic. Variants of uncertain significance are more common and have an unknown impact on protein function, contradicting the criteria for both benign and pathogenic [9]. Statistical analyses Statistical analyses were performed using SPSS 22.0. Categorical variables were expressed as n (%) and were compared using Fisher’s exact test. Continuous variables were expressed as the median and interquartile range, and were compared using Wilcoxon rank-sum test. Cumulative renal survival was analyzed by the Kaplan–Meier survival curves. Statistical significance was defined as a two-tailed P < 0.05. RESULTS Patients A total of 43 patients with C3 glomerulopathy (33 with C3GN and 10 with DDD) were enrolled in this Chinese cohort. An additional 24 patients with IC-MPGN served as the control group (Table 1). At the first diagnostic kidney biopsy, the median age was 21 years and 41.5 years in C3 glomerulopathy and IC-MPGN, respectively (P = 0.008). Approximately two-thirds of affected patients were male. A higher proportion of decreased serum C3 level was observed in C3 glomerulopathy and both subtypes (DDD and C3GN). Almost all patients received active therapy; 70% and 33% of patients with C3 glomerulopathy and IC-MPGN, respectively, were treated with steroids. After follow-up, nine C3 glomerulopathy patients (five DDD and four C3GN, P = 0.02) and eight MPGN patients progressed to end-stage renal disease (ESRD) or death. Table 1 Clinical and laboratory data collected at the time of first kidney biopsy in patients with C3 glomerulopathy and IC-MPGN IC-MPGN C3 glomerulopathy P-value Total C3GN DDD n 24 43 33 10 Male sex 16 (67) 27 (63) 20 (61) 7 (70) 0.8 and 0.7 Age of onset (years) 41.5 (30.5–50.5) 21 (15–45) 28 (16–50.5) 16 (12–17.75) 0.008 and <0.001 Nephrotic syndrome 7 (29) 20 (47) 12 (36) 8 (80) 0.2 and 0.03 AKI 11 (46) 10 (23) 7 (21) 3 (30) 0.06 and 0.7 Hypertension 15 (63) 15 (35) 14 (42) 1 (10) 0.03 and 0.1 Anemia 12 (50) 14 (33) 12 (36) 2 (20) 0.2 and 0.5 Serum creatinine 1.5 (0.9–2.5) 0.8 (0.7–1.2) 0.8 (0.8–1.15) 0.8 (0.6–1.4) 0.02 and 0.5 >1.24 (mg/dL) 14 (58) 9 (21) 6 (18) 3 (30) eGFR (mL/min/1.73 m2) 53.4 (32.6–93.7) 111 (70.8–157.2) 106.8 (72.3–133.5) 139.6 (69.3–199.8) <0.001 and 0.3 Urinary protein Median (g/day) 2.35 (1.0–4.7) 2.8 (1.2–5.9) 2.3 (1.1–5.1) 5.6 (2.6–6.7) 0.2 and 0.4 <400 mg 0 1 (2) 1 (3) 0 400 mg–3.5 g 15 (62.5) 23 (53) 19 (58) 4 (40) >3.5 g 9 (37.5) 19 (44) 13 (39) 6 (60) Hematuria 17 (79) 31 (72) 23 (70) 8 (80) 0.6 and 0.9 C3 levela Normal (0.8–1.8 g/L) 13 (54) 5 (12) 4 (12.5) 1 (10) <0.001 and 1.0 Low 11 (46) 37 (88) 28 (87.5) 9 (90) C4 levela Normal (0.1–0.4 g/L) 24 (100) 40 (95) 30 (94) 10 (100) 0.5 and 1.0 Low 0 2 (5) 2 (6) 0 Treatment Steroids 8 (33) 30 (70) 21 (64) 9 (90) 0.004 and 0.2 Other immunosuppression 9 (37.5) 15 (35) 9 (27) 6 (60) 0.8 and 0.07 ACEI/ARB 21 (87.5) 30 (70) 23 (70) 7 (70) 0.1 and 1.0 No specific treatment 2 (8) 6 (14) 6 (18) 0 0.7 and 0.3 Follow-up Median (months) 36.3 (8.4–58.1) 26.4 (7.6–47.7) 20.3 (6.9–40.7) 45.9 (8.4–81.2) 0.6 and 0.09 <5 years 19 (79) 38 (88) 31 (94) 7 (70) IC-MPGN C3 glomerulopathy P-value Total C3GN DDD n 24 43 33 10 Male sex 16 (67) 27 (63) 20 (61) 7 (70) 0.8 and 0.7 Age of onset (years) 41.5 (30.5–50.5) 21 (15–45) 28 (16–50.5) 16 (12–17.75) 0.008 and <0.001 Nephrotic syndrome 7 (29) 20 (47) 12 (36) 8 (80) 0.2 and 0.03 AKI 11 (46) 10 (23) 7 (21) 3 (30) 0.06 and 0.7 Hypertension 15 (63) 15 (35) 14 (42) 1 (10) 0.03 and 0.1 Anemia 12 (50) 14 (33) 12 (36) 2 (20) 0.2 and 0.5 Serum creatinine 1.5 (0.9–2.5) 0.8 (0.7–1.2) 0.8 (0.8–1.15) 0.8 (0.6–1.4) 0.02 and 0.5 >1.24 (mg/dL) 14 (58) 9 (21) 6 (18) 3 (30) eGFR (mL/min/1.73 m2) 53.4 (32.6–93.7) 111 (70.8–157.2) 106.8 (72.3–133.5) 139.6 (69.3–199.8) <0.001 and 0.3 Urinary protein Median (g/day) 2.35 (1.0–4.7) 2.8 (1.2–5.9) 2.3 (1.1–5.1) 5.6 (2.6–6.7) 0.2 and 0.4 <400 mg 0 1 (2) 1 (3) 0 400 mg–3.5 g 15 (62.5) 23 (53) 19 (58) 4 (40) >3.5 g 9 (37.5) 19 (44) 13 (39) 6 (60) Hematuria 17 (79) 31 (72) 23 (70) 8 (80) 0.6 and 0.9 C3 levela Normal (0.8–1.8 g/L) 13 (54) 5 (12) 4 (12.5) 1 (10) <0.001 and 1.0 Low 11 (46) 37 (88) 28 (87.5) 9 (90) C4 levela Normal (0.1–0.4 g/L) 24 (100) 40 (95) 30 (94) 10 (100) 0.5 and 1.0 Low 0 2 (5) 2 (6) 0 Treatment Steroids 8 (33) 30 (70) 21 (64) 9 (90) 0.004 and 0.2 Other immunosuppression 9 (37.5) 15 (35) 9 (27) 6 (60) 0.8 and 0.07 ACEI/ARB 21 (87.5) 30 (70) 23 (70) 7 (70) 0.1 and 1.0 No specific treatment 2 (8) 6 (14) 6 (18) 0 0.7 and 0.3 Follow-up Median (months) 36.3 (8.4–58.1) 26.4 (7.6–47.7) 20.3 (6.9–40.7) 45.9 (8.4–81.2) 0.6 and 0.09 <5 years 19 (79) 38 (88) 31 (94) 7 (70) Categorical variables are expressed as the number and percentage and were compared using Fisher’s exact test. Continuous variables are expressed as the median and interquartile range and were compared using Wilcoxon rank-sum test. a The data of serum C3 and C4 level were not available in one patient with C3GN. P value: IC-MPGN versus C3G (left); C3GN versus DDD (right). ACEI/ARB, angiotensin-converting enzyme inhibitor/angiotensin receptor blockers; n, number of cases. IC-MPGN, immune-complex-mediated membranoproliferative glomerulonephritis; C3GN, C3 glomerulonephritis; DDD, dense deposit disease. Table 1 Clinical and laboratory data collected at the time of first kidney biopsy in patients with C3 glomerulopathy and IC-MPGN IC-MPGN C3 glomerulopathy P-value Total C3GN DDD n 24 43 33 10 Male sex 16 (67) 27 (63) 20 (61) 7 (70) 0.8 and 0.7 Age of onset (years) 41.5 (30.5–50.5) 21 (15–45) 28 (16–50.5) 16 (12–17.75) 0.008 and <0.001 Nephrotic syndrome 7 (29) 20 (47) 12 (36) 8 (80) 0.2 and 0.03 AKI 11 (46) 10 (23) 7 (21) 3 (30) 0.06 and 0.7 Hypertension 15 (63) 15 (35) 14 (42) 1 (10) 0.03 and 0.1 Anemia 12 (50) 14 (33) 12 (36) 2 (20) 0.2 and 0.5 Serum creatinine 1.5 (0.9–2.5) 0.8 (0.7–1.2) 0.8 (0.8–1.15) 0.8 (0.6–1.4) 0.02 and 0.5 >1.24 (mg/dL) 14 (58) 9 (21) 6 (18) 3 (30) eGFR (mL/min/1.73 m2) 53.4 (32.6–93.7) 111 (70.8–157.2) 106.8 (72.3–133.5) 139.6 (69.3–199.8) <0.001 and 0.3 Urinary protein Median (g/day) 2.35 (1.0–4.7) 2.8 (1.2–5.9) 2.3 (1.1–5.1) 5.6 (2.6–6.7) 0.2 and 0.4 <400 mg 0 1 (2) 1 (3) 0 400 mg–3.5 g 15 (62.5) 23 (53) 19 (58) 4 (40) >3.5 g 9 (37.5) 19 (44) 13 (39) 6 (60) Hematuria 17 (79) 31 (72) 23 (70) 8 (80) 0.6 and 0.9 C3 levela Normal (0.8–1.8 g/L) 13 (54) 5 (12) 4 (12.5) 1 (10) <0.001 and 1.0 Low 11 (46) 37 (88) 28 (87.5) 9 (90) C4 levela Normal (0.1–0.4 g/L) 24 (100) 40 (95) 30 (94) 10 (100) 0.5 and 1.0 Low 0 2 (5) 2 (6) 0 Treatment Steroids 8 (33) 30 (70) 21 (64) 9 (90) 0.004 and 0.2 Other immunosuppression 9 (37.5) 15 (35) 9 (27) 6 (60) 0.8 and 0.07 ACEI/ARB 21 (87.5) 30 (70) 23 (70) 7 (70) 0.1 and 1.0 No specific treatment 2 (8) 6 (14) 6 (18) 0 0.7 and 0.3 Follow-up Median (months) 36.3 (8.4–58.1) 26.4 (7.6–47.7) 20.3 (6.9–40.7) 45.9 (8.4–81.2) 0.6 and 0.09 <5 years 19 (79) 38 (88) 31 (94) 7 (70) IC-MPGN C3 glomerulopathy P-value Total C3GN DDD n 24 43 33 10 Male sex 16 (67) 27 (63) 20 (61) 7 (70) 0.8 and 0.7 Age of onset (years) 41.5 (30.5–50.5) 21 (15–45) 28 (16–50.5) 16 (12–17.75) 0.008 and <0.001 Nephrotic syndrome 7 (29) 20 (47) 12 (36) 8 (80) 0.2 and 0.03 AKI 11 (46) 10 (23) 7 (21) 3 (30) 0.06 and 0.7 Hypertension 15 (63) 15 (35) 14 (42) 1 (10) 0.03 and 0.1 Anemia 12 (50) 14 (33) 12 (36) 2 (20) 0.2 and 0.5 Serum creatinine 1.5 (0.9–2.5) 0.8 (0.7–1.2) 0.8 (0.8–1.15) 0.8 (0.6–1.4) 0.02 and 0.5 >1.24 (mg/dL) 14 (58) 9 (21) 6 (18) 3 (30) eGFR (mL/min/1.73 m2) 53.4 (32.6–93.7) 111 (70.8–157.2) 106.8 (72.3–133.5) 139.6 (69.3–199.8) <0.001 and 0.3 Urinary protein Median (g/day) 2.35 (1.0–4.7) 2.8 (1.2–5.9) 2.3 (1.1–5.1) 5.6 (2.6–6.7) 0.2 and 0.4 <400 mg 0 1 (2) 1 (3) 0 400 mg–3.5 g 15 (62.5) 23 (53) 19 (58) 4 (40) >3.5 g 9 (37.5) 19 (44) 13 (39) 6 (60) Hematuria 17 (79) 31 (72) 23 (70) 8 (80) 0.6 and 0.9 C3 levela Normal (0.8–1.8 g/L) 13 (54) 5 (12) 4 (12.5) 1 (10) <0.001 and 1.0 Low 11 (46) 37 (88) 28 (87.5) 9 (90) C4 levela Normal (0.1–0.4 g/L) 24 (100) 40 (95) 30 (94) 10 (100) 0.5 and 1.0 Low 0 2 (5) 2 (6) 0 Treatment Steroids 8 (33) 30 (70) 21 (64) 9 (90) 0.004 and 0.2 Other immunosuppression 9 (37.5) 15 (35) 9 (27) 6 (60) 0.8 and 0.07 ACEI/ARB 21 (87.5) 30 (70) 23 (70) 7 (70) 0.1 and 1.0 No specific treatment 2 (8) 6 (14) 6 (18) 0 0.7 and 0.3 Follow-up Median (months) 36.3 (8.4–58.1) 26.4 (7.6–47.7) 20.3 (6.9–40.7) 45.9 (8.4–81.2) 0.6 and 0.09 <5 years 19 (79) 38 (88) 31 (94) 7 (70) Categorical variables are expressed as the number and percentage and were compared using Fisher’s exact test. Continuous variables are expressed as the median and interquartile range and were compared using Wilcoxon rank-sum test. a The data of serum C3 and C4 level were not available in one patient with C3GN. P value: IC-MPGN versus C3G (left); C3GN versus DDD (right). ACEI/ARB, angiotensin-converting enzyme inhibitor/angiotensin receptor blockers; n, number of cases. IC-MPGN, immune-complex-mediated membranoproliferative glomerulonephritis; C3GN, C3 glomerulonephritis; DDD, dense deposit disease. Variant identification and distribution We screened the exons and flanking regions of 11 complement-related genes, which were involved in the complement alternative pathway’s initiation phase. Common variants with MAF >1% in any population were excluded. A total of 20 variants were eventually identified and Sanger-confirmed (Supplementary data, Figure S2), including 16 reportedly rare and four novel variants (Table 2 and Supplementary data, Table S2). All variants were heterozygous and not found in 100 healthy control group members. Table 2 Profile of variants identified in this Chinese cohort Gene Nucleotide AA change MAF_Total MAF_High dbSNP Pathogenicity score Functional significance Patient ID Diagnosis Likely pathogenic CFI c.452A>G p.N151S 0.000008 0.00001498_EUR rs772044176 3 Lead to a dramatic decrease in the Factor I level, previously reported in aHUS [11, 12] 31 C3GN Variants of uncertain significance C3 c.1775G>A p.R592Q — — rs121909583 2 Lead to impaired binding to the regulator CD46 and resistance to cleavage by Factor I, previously reported in aHUS [11, 13, 14] 25 C3GN C3 c.521C>T p.P174L 0.0002 0.001_EAS rs199831618 1 31 C3GN CD46 c.293C>T p.T98I 0.0002 0.003048_EAS rs116800126 1 Lead to a defective expression of protein, previously reported in aHUS [8, 15] 19 C3GN CD46 c.932C>T p.A296V 0.00005 0.0002313_EAS rs753859532 1 46 IC-MPGN CD46 c.1076C>G p.A359G 0.00002 0.0002311_EAS rs767322836 1 Undetermined, previously reported in aHUS [16] 26 C3GN CFH c.1150C>T p.P384S 0.00003 0.0004649_EAS rs778180494 5 42 DDD CFH c.2221C>T p.L741F 0.00002 0.0003487_EAS rs780794196 2 41 DDD CFH c.3172T>C p.Y1058H 0.0008 0.0097150_EAS rs55679475 1 CTCF binding site, regulatory region variant, previously reported in aHUS [11, 17, 18] 32 51 C3GN IC-MPGN CFH c.3178G>C p.V1060L 0.0008 0.009602_EAS rs55771831 0 CTCF binding site, regulatory region variant, previously reported in aHUS [11, 17, 18] 32 51 C3GN IC-MPGN CFHR2 c.383C>A p.S128Stop 0.00003 0.0004623_EAS rs778808347 — 17 C3GN CFHR5 c.242C>T p.P81L 0.0001 0.001272_EAS rs544857720 4 Undetermined, previously reported in aHUS [8] 18 C3GN CFHR5 c.1357C>T p.P453S 0.0001 0.001502_EAS rs184883943 5 43 45 DDD IC-MPGN CFI c.848A>G p.D283G 0.00002 0.0003467_EAS rs756201106 5 31 C3GN CFI c.1547G>T p.G516V 0.00005 0.0006986_EAS rs764347930 5 30 C3GN THBD c.1208G>A p.R403K 0.0007 0.004411_LAT rs41400249 0 Undetermined, previously reported in aHUS [17] 52 IC-MPGN Novel C3 c.3307G>C p.A1103P — — — 3 24 C3GN CD46 c.83T>A p.L28Q — — — 5 40 DDD CFH c.1778T>C p.L593S — — — 5 40 DDD THBD c.1149A>C p.Q383H — — — 0 39 DDD Gene Nucleotide AA change MAF_Total MAF_High dbSNP Pathogenicity score Functional significance Patient ID Diagnosis Likely pathogenic CFI c.452A>G p.N151S 0.000008 0.00001498_EUR rs772044176 3 Lead to a dramatic decrease in the Factor I level, previously reported in aHUS [11, 12] 31 C3GN Variants of uncertain significance C3 c.1775G>A p.R592Q — — rs121909583 2 Lead to impaired binding to the regulator CD46 and resistance to cleavage by Factor I, previously reported in aHUS [11, 13, 14] 25 C3GN C3 c.521C>T p.P174L 0.0002 0.001_EAS rs199831618 1 31 C3GN CD46 c.293C>T p.T98I 0.0002 0.003048_EAS rs116800126 1 Lead to a defective expression of protein, previously reported in aHUS [8, 15] 19 C3GN CD46 c.932C>T p.A296V 0.00005 0.0002313_EAS rs753859532 1 46 IC-MPGN CD46 c.1076C>G p.A359G 0.00002 0.0002311_EAS rs767322836 1 Undetermined, previously reported in aHUS [16] 26 C3GN CFH c.1150C>T p.P384S 0.00003 0.0004649_EAS rs778180494 5 42 DDD CFH c.2221C>T p.L741F 0.00002 0.0003487_EAS rs780794196 2 41 DDD CFH c.3172T>C p.Y1058H 0.0008 0.0097150_EAS rs55679475 1 CTCF binding site, regulatory region variant, previously reported in aHUS [11, 17, 18] 32 51 C3GN IC-MPGN CFH c.3178G>C p.V1060L 0.0008 0.009602_EAS rs55771831 0 CTCF binding site, regulatory region variant, previously reported in aHUS [11, 17, 18] 32 51 C3GN IC-MPGN CFHR2 c.383C>A p.S128Stop 0.00003 0.0004623_EAS rs778808347 — 17 C3GN CFHR5 c.242C>T p.P81L 0.0001 0.001272_EAS rs544857720 4 Undetermined, previously reported in aHUS [8] 18 C3GN CFHR5 c.1357C>T p.P453S 0.0001 0.001502_EAS rs184883943 5 43 45 DDD IC-MPGN CFI c.848A>G p.D283G 0.00002 0.0003467_EAS rs756201106 5 31 C3GN CFI c.1547G>T p.G516V 0.00005 0.0006986_EAS rs764347930 5 30 C3GN THBD c.1208G>A p.R403K 0.0007 0.004411_LAT rs41400249 0 Undetermined, previously reported in aHUS [17] 52 IC-MPGN Novel C3 c.3307G>C p.A1103P — — — 3 24 C3GN CD46 c.83T>A p.L28Q — — — 5 40 DDD CFH c.1778T>C p.L593S — — — 5 40 DDD THBD c.1149A>C p.Q383H — — — 0 39 DDD All MAF data come from the ExAC database (exac.broadinstitute.org) except for the rs199831618, which is only recorded in the 1000 Genomes database (www.1000genomes.org). ‘MAF_Total’ denotes the MAF data from the entire population. ‘MAF_High’ denotes the MAF data in high expressing population. dbSNP denotes the ID for each variant in the Single Nucleotide Polymorphism database. Pathogenicity score was calculated as the sum of tools predicting the variant to be deleterious. Missense variants were considered likely deleterious when the pathogenicity score ≥3. EAS, East Asian; EUR, European; LAT, Latino. Table 2 Profile of variants identified in this Chinese cohort Gene Nucleotide AA change MAF_Total MAF_High dbSNP Pathogenicity score Functional significance Patient ID Diagnosis Likely pathogenic CFI c.452A>G p.N151S 0.000008 0.00001498_EUR rs772044176 3 Lead to a dramatic decrease in the Factor I level, previously reported in aHUS [11, 12] 31 C3GN Variants of uncertain significance C3 c.1775G>A p.R592Q — — rs121909583 2 Lead to impaired binding to the regulator CD46 and resistance to cleavage by Factor I, previously reported in aHUS [11, 13, 14] 25 C3GN C3 c.521C>T p.P174L 0.0002 0.001_EAS rs199831618 1 31 C3GN CD46 c.293C>T p.T98I 0.0002 0.003048_EAS rs116800126 1 Lead to a defective expression of protein, previously reported in aHUS [8, 15] 19 C3GN CD46 c.932C>T p.A296V 0.00005 0.0002313_EAS rs753859532 1 46 IC-MPGN CD46 c.1076C>G p.A359G 0.00002 0.0002311_EAS rs767322836 1 Undetermined, previously reported in aHUS [16] 26 C3GN CFH c.1150C>T p.P384S 0.00003 0.0004649_EAS rs778180494 5 42 DDD CFH c.2221C>T p.L741F 0.00002 0.0003487_EAS rs780794196 2 41 DDD CFH c.3172T>C p.Y1058H 0.0008 0.0097150_EAS rs55679475 1 CTCF binding site, regulatory region variant, previously reported in aHUS [11, 17, 18] 32 51 C3GN IC-MPGN CFH c.3178G>C p.V1060L 0.0008 0.009602_EAS rs55771831 0 CTCF binding site, regulatory region variant, previously reported in aHUS [11, 17, 18] 32 51 C3GN IC-MPGN CFHR2 c.383C>A p.S128Stop 0.00003 0.0004623_EAS rs778808347 — 17 C3GN CFHR5 c.242C>T p.P81L 0.0001 0.001272_EAS rs544857720 4 Undetermined, previously reported in aHUS [8] 18 C3GN CFHR5 c.1357C>T p.P453S 0.0001 0.001502_EAS rs184883943 5 43 45 DDD IC-MPGN CFI c.848A>G p.D283G 0.00002 0.0003467_EAS rs756201106 5 31 C3GN CFI c.1547G>T p.G516V 0.00005 0.0006986_EAS rs764347930 5 30 C3GN THBD c.1208G>A p.R403K 0.0007 0.004411_LAT rs41400249 0 Undetermined, previously reported in aHUS [17] 52 IC-MPGN Novel C3 c.3307G>C p.A1103P — — — 3 24 C3GN CD46 c.83T>A p.L28Q — — — 5 40 DDD CFH c.1778T>C p.L593S — — — 5 40 DDD THBD c.1149A>C p.Q383H — — — 0 39 DDD Gene Nucleotide AA change MAF_Total MAF_High dbSNP Pathogenicity score Functional significance Patient ID Diagnosis Likely pathogenic CFI c.452A>G p.N151S 0.000008 0.00001498_EUR rs772044176 3 Lead to a dramatic decrease in the Factor I level, previously reported in aHUS [11, 12] 31 C3GN Variants of uncertain significance C3 c.1775G>A p.R592Q — — rs121909583 2 Lead to impaired binding to the regulator CD46 and resistance to cleavage by Factor I, previously reported in aHUS [11, 13, 14] 25 C3GN C3 c.521C>T p.P174L 0.0002 0.001_EAS rs199831618 1 31 C3GN CD46 c.293C>T p.T98I 0.0002 0.003048_EAS rs116800126 1 Lead to a defective expression of protein, previously reported in aHUS [8, 15] 19 C3GN CD46 c.932C>T p.A296V 0.00005 0.0002313_EAS rs753859532 1 46 IC-MPGN CD46 c.1076C>G p.A359G 0.00002 0.0002311_EAS rs767322836 1 Undetermined, previously reported in aHUS [16] 26 C3GN CFH c.1150C>T p.P384S 0.00003 0.0004649_EAS rs778180494 5 42 DDD CFH c.2221C>T p.L741F 0.00002 0.0003487_EAS rs780794196 2 41 DDD CFH c.3172T>C p.Y1058H 0.0008 0.0097150_EAS rs55679475 1 CTCF binding site, regulatory region variant, previously reported in aHUS [11, 17, 18] 32 51 C3GN IC-MPGN CFH c.3178G>C p.V1060L 0.0008 0.009602_EAS rs55771831 0 CTCF binding site, regulatory region variant, previously reported in aHUS [11, 17, 18] 32 51 C3GN IC-MPGN CFHR2 c.383C>A p.S128Stop 0.00003 0.0004623_EAS rs778808347 — 17 C3GN CFHR5 c.242C>T p.P81L 0.0001 0.001272_EAS rs544857720 4 Undetermined, previously reported in aHUS [8] 18 C3GN CFHR5 c.1357C>T p.P453S 0.0001 0.001502_EAS rs184883943 5 43 45 DDD IC-MPGN CFI c.848A>G p.D283G 0.00002 0.0003467_EAS rs756201106 5 31 C3GN CFI c.1547G>T p.G516V 0.00005 0.0006986_EAS rs764347930 5 30 C3GN THBD c.1208G>A p.R403K 0.0007 0.004411_LAT rs41400249 0 Undetermined, previously reported in aHUS [17] 52 IC-MPGN Novel C3 c.3307G>C p.A1103P — — — 3 24 C3GN CD46 c.83T>A p.L28Q — — — 5 40 DDD CFH c.1778T>C p.L593S — — — 5 40 DDD THBD c.1149A>C p.Q383H — — — 0 39 DDD All MAF data come from the ExAC database (exac.broadinstitute.org) except for the rs199831618, which is only recorded in the 1000 Genomes database (www.1000genomes.org). ‘MAF_Total’ denotes the MAF data from the entire population. ‘MAF_High’ denotes the MAF data in high expressing population. dbSNP denotes the ID for each variant in the Single Nucleotide Polymorphism database. Pathogenicity score was calculated as the sum of tools predicting the variant to be deleterious. Missense variants were considered likely deleterious when the pathogenicity score ≥3. EAS, East Asian; EUR, European; LAT, Latino. A total of nine (27%), five (50%) and four (17%) patients with C3GN, DDD and IC-MPGN, respectively, were found with genetic abnormalities in complement genes. Considering the patients with hereditary abnormalities of overall pathological patterns, 22% (4/18) of cases harbored two or more variants; moreover, the occurrence might be an underestimate, owing to a lack of sufficient investigation into other genetic contributors. One C3GN patient (Case 31) harbored three variants in C3 and CFI, and one DDD patient (Case 40) harbored two variants in CFH and CD46. Interestingly, two unrelated individuals (Case 32 and 51, respectively, diagnosed as C3GN and IC-MPGN) harbored two contiguous CFH variants only six bases apart. Considering the variant distribution in individual complement genes, the variants were mainly identified in the CFH families, CFI, CD46 and C3. This issue appeared in consistent with previous reports in Caucasians [19, 20]. Missense mutations in the CFH family genes were most frequently found combined with other variants among the screened genes, suggesting a common mechanism driving the pathogenesis of this disease. For C3 and CFI, the variants were only observed in the subtype C3GN. Variant interpretation We identified a total of 2278 variations, 1 of which was classified as likely pathogenic and 19 of which were of uncertain significance. Others were considered benign or likely benign, following the recommended guideline (Table 2). Sequence analysis showed that c.383 C>A in CFHR2 led to a premature stop in protein, and all others resulted in single amino acid substitutions. As shown in Table 2, N151S, R592Q, T98I, Y1058H, V1060L, P81L and R403K variants were reportedly associated with aHUS with supporting functional evidences [8, 11–15, 17, 18]. The location and evolutionary sequence conservation of 20 identified variants were labeled in the corresponding position (Figure 2). Variants that appeared as relatively conserved mainly accumulate in CFH, CFHR5 and CFI. Of the variants having a conservation score ≥7, six (75%) were considered to be deleterious by combined prediction methods, which indicated a causal role for the CFI and CFH family genes in the disease pathogenesis. Genotype–phenotype correlations We analyzed the patterns of progression toward ESRD or death in correlation with the presence of histological, serological or genetic data. As shown in Supplementary data, Figure S3, patients with DDD seem associated with a more rapidly progressive evolution toward ESRD as compared with other histological types. Moreover, the worst prognoses seemed tied to C3 glomerulopathy, especially for adult patients. We further subgrouped the C3 glomerulopathy patients based on the presence or absence of complement gene variants (Figure 3). Genetically diagnosed patients were seemingly associated with good kidney survival as compared with undiagnosed patients, whether in overall groups or subgroups (including MPGN, C3 glomerulopathy and C3GN). This issue was in consistent with an Italian cohort [21]. The serum C3 level was similar among patients with or without variants (Figure 4), but a normal value was only observed in four genetically undiagnosed C3GN patients. Of the patients with available data on C3 nephritic factor (C3NeF) (26 C3GN and 4 DDD), only one C3GN patient diagnosed with a single variant in the C3 gene, whose serum C3 level was the lowest in this cohort, was positive for C3NeF. Patients harboring variants were not statistically different from those without variants for the majority of the clinical or pathological parameters, irrespective of pathological type (Supplementary data, Tables S3 and S4). FIGURE 3 View largeDownload slide Kidney survival curves. (A) Kaplan–Meier kidney survival curve in genetically diagnosed and undiagnosed patients with C3 glomerulopathy, (B) C3GN, (C) DDD and (D) IC-MPGN. Genetically diagnosed patients were seemingly associated with a good kidney survival versus undiagnosed patients in an early stage, whether in overall groups or in subgroups. FIGURE 3 View largeDownload slide Kidney survival curves. (A) Kaplan–Meier kidney survival curve in genetically diagnosed and undiagnosed patients with C3 glomerulopathy, (B) C3GN, (C) DDD and (D) IC-MPGN. Genetically diagnosed patients were seemingly associated with a good kidney survival versus undiagnosed patients in an early stage, whether in overall groups or in subgroups. FIGURE 4 View largeDownload slide C3 level distribution. Serum C3 level distribution was not significantly different between genetically diagnosed and undiagnosed patients with C3 glomerulopathy (P = 0.8). Normal serum C3 level was observed only in four genetically undiagnosed C3GN patients. FIGURE 4 View largeDownload slide C3 level distribution. Serum C3 level distribution was not significantly different between genetically diagnosed and undiagnosed patients with C3 glomerulopathy (P = 0.8). Normal serum C3 level was observed only in four genetically undiagnosed C3GN patients. DISCUSSION C3 glomerulopathy was considered as a rare kidney disorder, with a percent of DDD and C3GN under kidney biopsy (the ratio between the number of DDD and C3GN diagnosed and the number of patients under kidney biopsy per year) of <0.04% and 0.16% per year, respectively [22]. Dysregulation of the complement system has been described as the cause of some rare kidney diseases, and multiple variants in complement genes and their functional impact have been characterized in affected patients. In this study, we simultaneously screened 11 genes involved in the complement alternative pathway in Chinese patients with C3 glomerulopathy and IC-MPGN. We reported in this study on the largest cohort of C3 glomerulopathy that has been genetically studied to date in Asia, and focused on the effect of the presence of genetic alterations on the evolution toward ESRD to explore the genotype–phenotype correlations. Our data confirmed that C3 glomerulopathy is a complex multigenic complement-mediated disease. With the use of next-generation sequencing technologies, a genetic defect was found in 33% (14/43) of the cases. If we consider only CFH, CFHR5, CFI, CD46, THBD and C3, the variant burden (calculated as the sum of variants divided by the number of patients) was 0.42, in accordance with previous reporting [20]. Further comparing the prevalence with IC-MPGN, we noted that complement gene defects seemed prone to implicate in C3 glomerulopathy, especially for DDD. As more genetic factors involved in the complement system were screened, a broader range of genetic contributors was found to be relevant to the prediction component of this disease. We recommend that all patients with C3 glomerulopathy and other complement-correlated diseases undergo comprehensive genetic assessment for complement dysfunction. The N151S variant was located at the α-helix of CD5 domain of the factor I protein. An in vitro expression model demonstrated that variant N151S led to a dramatic decrease in the Factor I level, and 3D structural analysis predicted a quantitative deficiency [19, 20]. The variant R592Q, together with R592W, were reported in aHUS and led to impaired binding to the regulator CD46 and resistance to cleavage by Factor I [11, 13, 14] (Figure 2). The T98I variant was located on the short consensus repeat-2 (SCR2) of the CD46 protein, which acts as the binding site for C3b, together with the other three extracellular SCRs. Variant T98I has been detected in Caucasian, Japanese and Chinese aHUS patients, leading to a defective expression of protein [8, 11]. Both Y1058H and V1060L were located on the SCR18 domain of CFH only six bases apart. The majority of CFH variants were found at the C-terminal SCR15–SCR20 [11], and these sites primarily mediate target recognition and surface binding. Sanger sequencing confirmed these were two independent variants, but not a short indel. Most of the variants reportedly implicated in the complement system were often found in patients with distinct renal lesions, including hemolytic uremic syndrome, age-related macular degeneration, C3 glomerulopathy and IC-MPGN, which share phenotypic similarities and underlying genetic commonalities [5, 20]. In our previous study [23], the concomitant presence of three missense variations, with partial C3 convertase deficiency, was identified in four patients with different renal lesions. That may partly reflect the fact that several variants detected in this cohort were previously associated with aHUS patients. This issue provides insight into the implication of dysregulation of the complement system in C3 glomerulopathy. Interestingly, we observed the frequent concomitant occurrence of Y1058H and V1060L in the Asian population, including six Chinese and three Japanese [17, 18]. Undeniably, these are most likely two linked missense variants. The frequency of both of these two variations was ∼0.0008 in the ExAC database. However, it is indeed quite possible that some of these alleles are common in other populations, especially if some individuals are of mixed ancestry. It is important to set up an ‘ethnic-matched people in the 1000 Genomes Project’ for genetic diagnosis of patients in certain regions. Moreover, it is difficult to analyze linkage for rare variations. Considering the rare haplotype in CFHRx genes, it might suggest that a certain haplotype in CFH family genes should receive more attention for the genetic diagnosis of complement-related diseases. Otherwise, we have demonstrated strong linkage disequilibrium among three variations (CFH c.2509 G>A, CFHR3 c.424 C>T and CFHR5 c.434 G>A) and increased susceptibility due to the haplotype ATA . Real-time quantitative polymerase chain reaction and western blotting analysis had excluded the potential existence of copy number variation and hybrid genes of three fragments at 1q31.3 (Supplementary Methods and Supplementary data, Table S5). Surface plasmon resonance binding analysis further demonstrated the decrease by two orders of magnitude in C3b-binding properties, with a declined cofactor activity in the fluid phase [23]. Nevertheless, they were excluded from this article because they are common variants in some other population groups in the ExAC database. Overall variants were filtered and classified, employing a common practice based on the MAF, nucleotide effect, bioinformatic analysis and functional evidence [9]. Potential pathogenicity prediction and evolutionary sequence conservation are widely used indicators of deleteriousness for assessing variations [6]. Variants classified as ‘pathogenic’ or ‘likely pathogenic’ should satisfy all those criteria, and 19 (95%) of the variants identified in this study were, therefore, referred to as ‘variant(s) of uncertain significance’. In a recent large genetic screen of 193 patients with thrombotic microangiopathies and C3 glomerulopathies, variants reported as of uncertain significance occurred at a frequency of 75% [20]. As is intended, a substantial number of variants are not reported as ‘causative’ following such rigorous evaluation [9]. It is very important to separate genuine disease-causing or disease-associated variants reliably from the broader genetic background of variants present in all human genomes that are rare but not actually pathogenic [6]. Otherwise, we must recognize that the predictive power of those bioinformatic tools would not be very reliable, due to both statistical and biological factors [6]. Predicted variant damage effect sometimes is not in line with functional evidence, and variants that present as ‘variable’ across species may be vulnerable to even relatively weak selective pressure, which leads to considerable effects on disease risk. The clinical presentation, severity and progression of kidney impairment of C3 glomerulopathy are extremely variable, which is caused by the difference in the pathogenesis [24]. Individuals carrying overlapping variations in this study often present heterogeneous manifestations that can occur at any life stage. Different abnormalities can also affect the same biological pathway, and give rise to similar clinical and histopathological features. No significant discrepancy was observed between genetically diagnosed and undiagnosed patients regardless of clinical or pathological parameters, indicating that the variants in the alternative pathway genes, all presenting in heterozygosity in this study, are probably not insignificant in determining the disease phenotype by themselves. Furthermore, we cannot exclude the potential existence of unknown genetic contributors (factors such as the modifier genes or epigenetic changes) or acquired drivers, and potentially the environment, that critically impact the nature and duration of kidney pathology [24]. Kaplan–Meier survival analysis showed no statistical difference between groups. Genetically undiagnosed patients seem to have a higher risk of progression to ESRD or death, and a similar observation in an Italian cohort adds additional support [21]. Some potential limitations of this study should be noted. First, although it is the largest cohort of C3 glomerulopathy from Asia, the sample size is still relatively small. Variation diversity is large and genotype–phenotype correlations are loose, reflecting in part the insufficient study population size due to the rarity of the disorder. Expert interpretation of genetic profiles in a wide, comprehensive multicenter network is an urgent requisite. Second, acquired contributors like the serum C3NeF are reported positive in 80% of DDD and up to 50% of IC-MPGN [25] cases, and are usually detectable among individuals carrying variants by lines of evidence [15, 26–28]. However, data and analysis are incomplete in the retrospective study, and only a small proportion of patients with C3GN have undergone serologic testing for C3NeF and autoantibody against factor H, and the positive rate is far lower than their prevalence. Additionally, all patients ruled out a family history of related kidney diseases in first-degree relatives; however, we could not obtain samples from those healthy relatives of the affected patients for genetic testing. We are at present investigating ways of improving the detection rate and accuracy to ascertain the implication of acquired autoantibodies in the disease process, as well the hereditary characteristics. In summary, variant screening using multigene panels has improved diagnostic efficiency and implicated a broad range of genetic contributors in C3 glomerulopathy, which allows for an improved genetic understanding of complement alternative pathway regulation. Larger work scopes in multicenter collaborations and the development of expert interpretations are urgently needed to establish a complete and accurate genetic profile to ultimately provide genetic counseling and assessment for clinical diagnosis and treatment choice. ACKNOWLEDGEMENTS We thank all the patients and their families who participated in this study. FUNDING This work was supported by grants from the National Natural Science Foundation of China (No. 81570714 and 81611130131). AUTHORS’ CONTRIBUTIONS W.Z. was responsible for experiment performance, data analysis and interpretation, figure preparation and writing the manuscript. Y.D. performed data analysis and interpretation and figure preparation; J.L. and T.Z.: sample recruitment, organization of DNA collections; D.C. and C.Z.: histological and laboratory analysis and interpretation; H.Z.: patient recruitment, counseling and follow-up; Z.L.: study design, patient selection and clinical analysis and interpretation; H.C.: study design, data interpretation, writing and drawing. Each author contributed important intellectual content during manuscript drafting or revision and accepts accountability for the overall work by ensuring that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved. CONFLICT OF INTEREST STATEMENT This manuscript has been reviewed and approved by all of the authors, and the results reported in this manuscript have not been published elsewhere, in whole or in part. We declare that we have no conflicts of interest. REFERENCES 1 Pickering MC , D’Agati VD , Nester CM et al. C3 glomerulopathy: consensus report . Kidney Int 2013 ; 84 : 1079 – 1089 Google Scholar Crossref Search ADS PubMed 2 Sethi S , Fervenza FC. Membranoproliferative glomerulonephritis: pathogenetic heterogeneity and proposal for a new classification . Semin Nephrol 2011 ; 31 : 341 – 348 Google Scholar Crossref Search ADS PubMed 3 Fakhouri F , Fremeaux-Bacchi V , Noel LH et al. 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Journal
Nephrology Dialysis Transplantation – Oxford University Press
Published: Nov 1, 2018