Kidney involvement in human SLE is common and usually severe. Treatment is often effective, but accompanied by considerable toxicity. Morbidity from treatment could be considerably reduced if it could be started early, tailored to disease severity, and tapered off quickly in patients destined to have a durable response. To use therapy in this way requires biomarkers that predict the onset of SLE renal flare, the severity of the flare, and the response to therapy. The goal of this pilot project is to determine whether the phenotype of SLE renal flare can be modeled by examining the urine proteome throughout the renal flare cycle. This work will utilize the Ohio SLE Study database and specimen bank, developed at the Ohio State University, and which contains serial clinical information and urine and plasma samples from a cohort of SLE patients followed prospectively every 2 months over 5 years.
Aim 1 will use surface-enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS) to test the feasibility of profiling changes in the urine proteome of SLE patients before renal flare onset, during flare, and following treatment of flare. Proteins that change expression before a renal flare may be forecasters of impending flare and/or flare severity. Proteins that are differentially expressed during flare may be relevant to the pathogenesis of kidney injury, and may thus reflect potential novel therapeutic targets. Proteins that change after flare treatment may be useful in predicting response to treatment.
Aim 2 will test the feasibility of using liquid chromatography-tandem mass spectrometry to positively identify differentially expressed proteins detected by SELDI-TOF-MS in Aim 1.
In Aim 3, candidate SLE nephritis biomarkers identified in Aim 2 will be quantified in the original sample set using immunodetection or quantitative mass spectrometery-based techniques. In summary, this project is expected to demonstrate the feasibility of biomarker identification and validation by monitoring changes in the urine proteome during the SLE nephritis flare cycle.
This research will facilitate the development of novel diagnostic tools to predict onset, severity, and outcome of SLE renal flare. These tools will be based on changes in urine proteins during SLE renal flares. This will lead to earlier diagnosis and treatment, and thus more effective use of currently available medications, resulting in improved clinical outcomes for SLE nephritis.
