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. 2018 Jan;29(1):283-294.
doi: 10.1681/ASN.2017030258. Epub 2017 Oct 13.

Cluster Analysis Identifies Distinct Pathogenetic Patterns in C3 Glomerulopathies/Immune Complex-Mediated Membranoproliferative GN

Collaborators, Affiliations

Cluster Analysis Identifies Distinct Pathogenetic Patterns in C3 Glomerulopathies/Immune Complex-Mediated Membranoproliferative GN

Paraskevas Iatropoulos et al. J Am Soc Nephrol. 2018 Jan.

Abstract

Membranoproliferative GN (MPGN) was recently reclassified as alternative pathway complement-mediated C3 glomerulopathy (C3G) and immune complex-mediated membranoproliferative GN (IC-MPGN). However, genetic and acquired alternative pathway abnormalities are also observed in IC-MPGN. Here, we explored the presence of distinct disease entities characterized by specific pathophysiologic mechanisms. We performed unsupervised hierarchical clustering, a data-driven statistical approach, on histologic, genetic, and clinical data and data regarding serum/plasma complement parameters from 173 patients with C3G/IC-MPGN. This approach divided patients into four clusters, indicating the existence of four different pathogenetic patterns. Specifically, this analysis separated patients with fluid-phase complement activation (clusters 1-3) who had low serum C3 levels and a high prevalence of genetic and acquired alternative pathway abnormalities from patients with solid-phase complement activation (cluster 4) who had normal or mildly altered serum C3, late disease onset, and poor renal survival. In patients with fluid-phase complement activation, those in clusters 1 and 2 had massive activation of the alternative pathway, including activation of the terminal pathway, and the highest prevalence of subendothelial deposits, but those in cluster 2 had additional activation of the classic pathway and the highest prevalence of nephrotic syndrome at disease onset. Patients in cluster 3 had prevalent activation of C3 convertase and highly electron-dense intramembranous deposits. In addition, we provide a simple algorithm to assign patients with C3G/IC-MPGN to specific clusters. These distinct clusters may facilitate clarification of disease etiology, improve risk assessment for ESRD, and pave the way for personalized treatment.

Keywords: C3 glomerulonephritis; C3 glomerulopathy; Complement system; Dense Deposit Disease; Rare diseases; membranoproliferative glomerulonephritis (MPGN).

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Figures

None
Graphical abstract
Figure 1.
Figure 1.
Dendrogram illustrating the identification of 4 clusters in 173 patients with C3G or IC-MPGN. Each vertical line at the extremity of the dendrogram (bottom) represents a patient, and the length of the vertical lines represents the degree of dissimilarity between patients or groups of patients. The boxes define the four clusters.
Figure 2.
Figure 2.
Algorithm to assign patients to the different clusters. A three-step algorithm was created based on features available at onset to assign patients with C3G/IC-MPGN to specific clusters.
Figure 3.
Figure 3.
Patients in cluster 4 have poor renal outcomes. Kaplan–Meier renal survival analysis according to (A) the groups obtained by the cluster analysis, (B) the clusters defined by the three-step algorithm, and (C) the histologic groups.
Figure 4.
Figure 4.
The four clusters show differences in distribution of LPVs and in C3NeF residual activity. (A and B) Distribution of the LPVs according to (A) the clusters and (B) the algorithm-based clusters. LPVs in C3 and CFB are over-represented in clusters 1 and 2 compared with cluster 3. *P<0.05; **P<0.01. (C and D) C3NeF residual activity evaluated by hemolytic assay in C3NeF-positive patients according to (C) the clusters and (D) the algorithm-based clusters. C3NeFs of patients in cluster 1 stabilize alternative pathway C3 convertase less efficiently than those of patients in clusters 2 and 3. The central box represents the values from the 25th to 75th percentiles. The blue lines represent the medians. Lines extend from the minimum to the maximum values. *P<0.05; **P<0.01.

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