A framework designed for discovery
Overview
This project combines cell-free DNA methylation profiling with single-nucleus RNA sequencing and a novel computational matching method to establish non-invasive biomarkers for lupus nephritis class and characterize its cellular landscape. The work integrates molecular and epigenetic approaches to move from discovery to diagnostic application.
Experimental / Computational Methods
ddPCR-based analysis of DNA methylation patterns in urine cell-free DNA, single-nucleus RNA sequencing from FFPE kidney tissue, bulk methylation sequencing from urine pellets, and application of Matchmaker — a novel computational method for matching single-cell RNA sequencing clusters to single-nucleus methylation data.
Data Sources / Models Used
Urine cell-free DNA and pellet samples from individuals with lupus nephritis, FFPE kidney tissue for single-nucleus RNA sequencing, and paired methylation and transcriptomic datasets used to build and validate the epigenetic atlas of lupus nephritis.
Analytical / Translational Focus
Identification of urine DNA methylation signatures that distinguish lupus nephritis classes and correlate with disease progression, with the goal of developing a cost-effective, non-invasive diagnostic tool applicable across kidney disease contexts and scalable for clinical use.
Powering the science
Christine Bakhoum, MD, MAS, Colton Consortium Member
Assistant Professor, Department of Pediatrics (Pediatric Nephrology), Yale School of Medicine, Yale University