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Introduction: Membranoproliferative glomerulonephritis (MPGN) is currently stratified into complement C3 glomerulopathy (C3G) and immune complex-mediated MPGN (IC-MPGN). However, classification is subject to continued debate. Methods: Here, we applied hierarchical clustering to a much larger cohort of patients with C3G/ICMPGN (295 individuals), extensively characterized for genetic and autoimmune complement abnormalities, with the goal of unraveling specific disease patterns. We also designed a user-friendly web application that with input of data at diagnosis could make cluster classification clinically applicable. Results: Five clusters with unique phenotypic and complement profiles were identified. Cluster 1 and 2 patients showed systemic complement activation until C5. Consistently, C5 nephritic factor and anti-factor B antibodies were prevalent in these clusters. Cluster 2 was distinguished from cluster 1 for classical pathway activation markers in biopsy. Cluster 3 showed C3-restricted systemic complement activation associated with the prevalence of C3 nephritic factor. Cluster 4 and 5 patients shared a normal complement profile and intense glomerular C3 staining, consistent with solid-phase complement activation, but cluster 5 distinguished for the higher prevalence of genetic abnormalities. Cluster 4 patients had the highest incidence of kidney failure during follow-up, while cluster 1 had the best kidney prognosis. However, clusters 1 and 2 showed a high risk of post-transplant recurrence. Through our web application, we could visually compare the predicted profile of new patients with those of patients included in clustering analysis and assign these patients to different clusters. The cluster-based classification allows etiologic diagnosis of C3G/IC-MPGN and had better prognostic value than current approaches. Conclusion: Our proposed strategy may possibly guide anti-complement treatment.
Ariela, B., Erica, D., Henry, L., Rossella, P., Miriam, R., Maria, S., et al. (2025). Hierarchical clustering uncovered disease patterns and further untangled complexities in immune complex-mediated idiopathic MPGN and C3 glomerulopathy. KIDNEY INTERNATIONAL, S0085-2538(25)00772-0, 1-32 [10.1016/j.kint.2025.08.035].
Hierarchical clustering uncovered disease patterns and further untangled complexities in immune complex-mediated idiopathic MPGN and C3 glomerulopathy
Introduction: Membranoproliferative glomerulonephritis (MPGN) is currently stratified into complement C3 glomerulopathy (C3G) and immune complex-mediated MPGN (IC-MPGN). However, classification is subject to continued debate. Methods: Here, we applied hierarchical clustering to a much larger cohort of patients with C3G/ICMPGN (295 individuals), extensively characterized for genetic and autoimmune complement abnormalities, with the goal of unraveling specific disease patterns. We also designed a user-friendly web application that with input of data at diagnosis could make cluster classification clinically applicable. Results: Five clusters with unique phenotypic and complement profiles were identified. Cluster 1 and 2 patients showed systemic complement activation until C5. Consistently, C5 nephritic factor and anti-factor B antibodies were prevalent in these clusters. Cluster 2 was distinguished from cluster 1 for classical pathway activation markers in biopsy. Cluster 3 showed C3-restricted systemic complement activation associated with the prevalence of C3 nephritic factor. Cluster 4 and 5 patients shared a normal complement profile and intense glomerular C3 staining, consistent with solid-phase complement activation, but cluster 5 distinguished for the higher prevalence of genetic abnormalities. Cluster 4 patients had the highest incidence of kidney failure during follow-up, while cluster 1 had the best kidney prognosis. However, clusters 1 and 2 showed a high risk of post-transplant recurrence. Through our web application, we could visually compare the predicted profile of new patients with those of patients included in clustering analysis and assign these patients to different clusters. The cluster-based classification allows etiologic diagnosis of C3G/IC-MPGN and had better prognostic value than current approaches. Conclusion: Our proposed strategy may possibly guide anti-complement treatment.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/1026690
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simulazione ASN
Il report seguente simula gli indicatori relativi alla propria produzione scientifica in relazione alle soglie ASN 2023-2025 del proprio SC/SSD. Si ricorda che il superamento dei valori soglia (almeno 2 su 3) è requisito necessario ma non sufficiente al conseguimento dell'abilitazione. La simulazione si basa sui dati IRIS e sugli indicatori bibliometrici alla data indicata e non tiene conto di eventuali periodi di congedo obbligatorio, che in sede di domanda ASN danno diritto a incrementi percentuali dei valori. La simulazione può differire dall'esito di un’eventuale domanda ASN sia per errori di catalogazione e/o dati mancanti in IRIS, sia per la variabilità dei dati bibliometrici nel tempo. Si consideri che Anvur calcola i valori degli indicatori all'ultima data utile per la presentazione delle domande.
La presente simulazione è stata realizzata sulla base delle specifiche raccolte sul tavolo ER del Focus Group IRIS coordinato dall’Università di Modena e Reggio Emilia e delle regole riportate nel DM 589/2018 e allegata Tabella A. Cineca, l’Università di Modena e Reggio Emilia e il Focus Group IRIS non si assumono alcuna responsabilità in merito all’uso che il diretto interessato o terzi faranno della simulazione. Si specifica inoltre che la simulazione contiene calcoli effettuati con dati e algoritmi di pubblico dominio e deve quindi essere considerata come un mero ausilio al calcolo svolgibile manualmente o con strumenti equivalenti.