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Comparing the immune response in patients with systemic and cutaneous lupus

Most research on lupus does not address whether the immune response in people with systemic lupus is different from the immune response in those with organ-specific lupus such as lupus nephritis (inflammation of the kidney) and cutaneous (skin) lupus. Since skin samples can be obtained without invasive surgery, cutaneous lupus is well suited for research. Dr. Kahlenberg’s study will compare the immune response in systemic lupus to cutaneous lupus. Using blood and skin samples from lupus patients, her laboratory is measuring differences in the immune cells over the course of treatment. The immune response in the blood and skin will be compared between patients with systemic or cutaneous lupus. This will help Dr. Kahlenberg determine what is both similar and different between these groups of patients. She will also measure the immune response to treatment within each patient over time. This will allow Dr. Kahlenberg to learn whether certain immune cells can predict when patients will best respond to treatment.


What this study means for people with lupus

The information obtained from this study will help researchers better understand the difference in immune response between systemic and cutaneous lupus. Identifying these differences is important for the development of more specialized treatments. Dr. Kahlenberg’s study will also help healthcare providers better predict which drugs will benefit each lupus patient.

Research into the mechanisms driving systemic lupus erythematosus (SLE) has made great strides in identifying abnormal activation of immune pathways, yet trials of new medications for systemic lupus patients have not been overwhelmingly successful; in fact, two recent positive trials for anifrolumab and voclosporin demonstrate at best a 50% response rate. While the impact of trial design can be debated, the scientific community now accepts that our poor understanding of disease heterogeneity and the mechanisms which drive it contribute to drug failure. Indeed, our published work supports the notion that how we clinically define disease may not accurately reflect the ongoing pathobiology in the tissue and which treatments will work. Thus, our group is pursuing a long-term goal to create a better understanding of the heterogeneity of molecular mechanisms driving tissue vs. systemic immune system aberrancies in SLE patients so that we can generate novel biomarkers for disease classification, treatment response and disease outcome. In this application, we will address the hypothesis that integration of high-resolution single cell-level data with immune and -omic data will facilitate the identification of the mechanisms influencing disease manifestation, disease course, and therapeutic response. To do this, we will leverage our unique Taubman Institute Innovative Program: Personalized Medicine through Integration of Immune Phenotypes in Autoimmune Skin Disease (TIIP-PerMIPA) longitudinal cohort of patients with systemic lupus and healthy controls to develop matched single cell RNA-seq (scRNAseq) studies that can be compared with the comprehensive genomic and immune response data collected in this cohort. This approach of adding scRNAseq data to existing analyses can profoundly increase our ability to determine the mechanisms involved in pathologic states, even with a limited number of subjects. In AIM 1, we will utilize single cell RNA-seq to compare the immune cell populations in blood and skin of patients with systemic lupus erythematosus(SLE)/cutaneous lupus erythematosus (CLE) with tissue transcriptomics, and cellular responses, and patient data. In AIM 2, we will compare the immune cell populations over time following treatment within single patients and correlate with treatment response. These data will provide enhanced distinction for disease mechanisms between systemic and organ-specific (cutaneous) lupus at the cellular and pathway levels and utilize inflammatory responses of tissues and immune cells as a priori information to classify and subset patient populations to better understand disease diversity, behavior and therapeutic responses. This will lead to informed patient recruitment and higher rates of success for SLE trials and SLE patients.



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