Utilizing Polymorphic Variability to Predict Cytokines Profiles and Response to Therapy

An estimated 5-7% of the population suffers from autoimmune diseases including rheumatoid arthritis (RA), multiple sclerosis (MS), systemic lupus erythematosus (SLE), and psoriasis. Genome-wide association studies (GWAS) have found genetic variants associated with increased risk of developing autoimmunity. These studies have identified common SNPs among different autoimmune diseases. Thus along with epidemiological and clinical evidence, this suggests that some genetic risk factors with their biologic effects may be shared across diseases. However, the impact that most of these genetic variations have on cellular responses and systemic immunity has not been determined. 

My research focuses on the effect of the common genetic polymorphisms in signaling molecules involved in responses to cytokines. Variants within the TNF-α, IL-12, and pSTAT3 (including IL-23, IL-10, IL-6) pathways have been described as being associated with susceptibility to multiple sclerosis (MS), rheumatoid arthritis (RA), Crohn’s disease, and psoriasis. We have demonstrated that variants associated with these pathways change the strength of signal received from cytokine stimulation, thereby suggesting a predisposition to increased inflammation in susceptible individuals.  Current studies are underway to elucidate the cellular and biochemical mechanisms by which these variants alter signaling pathways.

A second emphasis of my research is to understand how genetic variability impacts response to treatment. Many therapeutic drugs have been developed to interfere with autoimmune inflammation by blocking pro-inflammatory cytokines. For example, the TNF-a inhibitors are used to treat RA, Crohn’s disease, psoriasis, and ankylosing spondylitis. While these drugs have dramatically improved treatment of certain autoimmune disorders, they are only effective in 30-50% of patients. Moreover, this class of drugs was also found to exacerbate MS and some cases of psoriasis, and drive new onset SLE. This suggests that responsiveness to TNF-a varies between diseases, and even potentially between individuals suffering from the same disease.  My research aims to understand how genetic variability in cytokine signaling genes may contribute to these different therapeutic responses.

Ultimately, the goal of my research is to identify new therapeutic targets and improve treatment efficacy by personalizing treatment plans to individual patients based on genetic biomarkers.