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Updated: Jan 7, 2026

Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis
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Published on: June 18, 2020

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Disentangling disease heterogeneity in C3 glomerulopathies: a slippery road

Caroline Duineveld1, Jack F M Wetzels1

  • 1Department of Nephrology, Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, the Netherlands.

Kidney International
|January 4, 2026
PubMed

Insights

Anticomplement therapies require classifying C3 glomerulopathy patients. A new tool uses cluster analysis to identify 5 patient subgroups based on disease causes, aiding clinical decisions.

Area of Science:

  • Nephrology
  • Immunology
  • Genetics

Background:

  • C3 glomerulopathy (C3G)/immune complex membranoproliferative glomerulonephritis (IC-MPGN) requires precise classification for targeted therapies.
  • Anticomplement therapies necessitate homogeneous patient subgroups reflecting distinct disease etiologies.

Purpose of the Study:

  • To develop a method for classifying C3G/IC-MPGN patients into homogeneous subgroups.
  • To facilitate the application of anticomplement therapies by understanding disease heterogeneity.

Main Methods:

  • Hierarchical cluster analysis was employed to analyze patient data.
  • A web-based tool was developed for practical clinical application of the classification.

Main Results:

  • The analysis identified 5 distinct patient clusters within C3G/IC-MPGN.
  • These clusters represent subgroups with potentially different disease mechanisms and treatment responses.

Conclusions:

  • The study provides a novel classification framework for C3G/IC-MPGN patients.
  • Clinicians can utilize the web-based tool for patient stratification, but validation is pending.

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