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Updated: Jan 19, 2026

Analyses of Proteinuria, Renal Infiltration of Leukocytes, and Renal Deposition of Proteins in Lupus-prone MRL/lpr Mice
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Rethinking Lupus Nephritis Classification on a Molecular Level.

Salem Almaani1, Stephenie D Prokopec2, Jianying Zhang3

  • 1Division of Nephrology, The Ohio State University, Columbus, OH 43210, USA. almaani.1@osu.edu.

Journal of Clinical Medicine
|September 25, 2019
PubMed
Summary

Molecular profiling of lupus nephritis (LN) kidney biopsies reveals potential for refining the current ISN/RPS classification. Integrating molecular data with histology may improve disease classification and identify new treatment targets.

Keywords:
ISN/RPS classificationlupus nephritismRNA

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Area of Science:

  • Nephrology
  • Immunology
  • Molecular Biology

Background:

  • The International Society of Nephrology/Renal Pathology Society (ISN/RPS) classification for lupus nephritis (LN) faces challenges in inter-rater reliability and treatment response correlation.
  • Integrating molecular data with traditional histologic evaluation could enhance diagnostic precision and identify therapeutic targets in LN.

Purpose of the Study:

  • To investigate the relationship between histological and molecular phenotypes and clinical responses in lupus nephritis.
  • To explore the potential of molecular classifiers to refine the existing ISN/RPS classification system.

Main Methods:

  • Measured renal compartmental mRNA abundance in 54 LN biopsy specimens.
  • Correlated mRNA levels with ISN/RPS classification and individual histologic lesions.
  • Evaluated a subset of transcripts in sequential biopsies from 36 patients during flare and follow-up.

Main Results:

  • Unsupervised clustering of mRNA abundance did not correlate with the ISN/RPS classification.
  • Exploratory analyses indicated correlations between specific transcripts (e.g., FN1, SPP1, LGALS3) and individual histologic lesions, as well as disease activity.
  • Certain transcripts, including interferon-regulated genes, showed relationships with specific histologic features.

Conclusions:

  • The current LN classification could be improved by incorporating molecular descriptors.
  • Combining molecular and pathologic phenotypes from kidney biopsies shows promise for better disease classification and identification of therapeutic targets.
  • Further research in larger cohorts is warranted to validate these findings.