Developing a Non-Invasive Biomarker Test to Classify Lupus Nephritis

Identifying DNA methylation signatures in blood and urine as non-invasive biomarkers to classify lupus nephritis and guide treatment without repeated biopsies.
Completed Systemic Diseases Systemic Lupus Erythematosus (SLE) Bioinformatics Biomarker Discovery Data-Driven & Quantitative Disease Subtyping Experimental Platforms & Models Human Cohorts Translational & Clinical

Funding Year: 2023

Project Overview

Lupus nephritis affects one-third of SLE patients and is currently diagnosed and monitored through kidney biopsies — an invasive procedure with significant risks. This project develops a non-invasive alternative by identifying DNA methylation changes in blood and urine samples from 39 patients with biopsy-confirmed lupus nephritis. Using a novel workflow designed to detect methylation changes even in low-DNA urine samples, the team identified 284 CpG loci associated with fibrinoid necrosis and fibrous crescents, and two regions differentially methylated by cellular/fibrocellular crescent score — including genes TNXB and VTRNA2-1. Findings will be validated in prospective cohorts across institutions, with a long-term goal of implementing liquid biopsy as standard of care in SLE.

Impact & Innovation

Liquid biopsy as a new standard for lupus nephritis monitoring.

 

By identifying DNA methylation signatures that distinguish lupus nephritis histopathological classes from blood and urine, this project lays the groundwork for replacing repeated kidney biopsies with a safer, scalable liquid biopsy approach.

  • Identifies specific CpG loci and differentially methylated regions associated with lupus nephritis disease class, establishing a novel epigenetic biomarker panel for non-invasive classification
  • Generates translational potential through a submitted R01 to NIDDK and planned multi-institution prospective validation, with applicability to other autoimmune kidney pathologies
  • Advances the Consortium’s From Mechanistic Insight to Translation pillar by converting epigenetic discovery directly into a clinically deployable diagnostic tool for lupus nephritis management
Research Approach

A framework designed for discovery

This project applies DNA methylation profiling to blood and urine samples from lupus nephritis patients to identify epigenetic biomarkers that correlate with histopathological disease class, developing a non-invasive alternative to kidney biopsy for disease classification and monitoring.


Novel methylation detection workflow optimized for low-DNA urine samples; DNA methylation analysis of buffy coat-derived and urine cell-free DNA from 39 patients with biopsy-confirmed lupus nephritis; identification of CpG loci and differentially methylated regions associated with fibrinoid necrosis, fibrous crescents, and cellular/fibrocellular crescent score.

Blood and urine samples from 39 lupus nephritis patients with biopsy-confirmed histopathological classification, methylation profiling datasets identifying 284 CpG loci and two differentially methylated regions, and paired biopsy-methylation datasets used to validate epigenetic correlates of disease class.

Validation of DNA methylation signatures as non-invasive classifiers of lupus nephritis histopathology, with next steps including multi-institution prospective cohort validation and a submitted R01 to NIDDK to support further development. The long-term goal is implementation of liquid biopsy as standard of care for SLE patients, with broader applicability to other autoimmune kidney diseases.

Investigators & Institutions

Powering the science

Principal Investigator

Christine Bakhoum, MD, MAS, Colton Consortium Member

Assistant Professor, Department of Pediatrics (Pediatric Nephrology), Yale School of Medicine, Yale University

Colton Centers & Institutions

Colton Center for Autoimmunity at Yale University

Research Outputs

From insight to impact

Publications

Associations between blood DNA methylation and histopathologic features in lupus nephritis

Kidney360
Demkowicz, PC; Kavaliauskaitė, I; Faulkner, SC; Kent, C; Shaw, M; Kumar, D; Ix, JH; Wilson, FP; Moledina, DG; Bakhoum, MF; Bakhoum, CY August 2025
BioinformaticsBiological & MechanisticBiomarker DiscoveryData-Driven & QuantitativeDisease SubtypingExperimental Platforms & ModelsHuman CohortsHuman GeneticsMulti-omics IntegrationTranslational & ClinicalSystemic DiseasesSystemic Lupus Erythematosus (SLE)Yale University

Additional Outputs

R01 submitted to NIDDK; pending Council review.