Crohn's disease (CD) and ulcerative colitis (UC) affect over 1.4 million Americans. Over the past 15 years, considerable progress has been made in the therapy of CD and UC with monoclonal antibodies against tumor necrosis factor ? (anti-TNF) representing the most significant therapeutic breakthrough. However, many patients fail to respond adequately. Recent genome wide associations studies (GWAS) have significantly increased our understanding of the pathogenesis of CD and UC. The role of these genetic variants in predicting response to anti-TNF therapy is yet to be defined adequately. In addition, significant safety concerns remain with the use of these agents with serious infections occurring in up to 10% of patients. There is a strong genetic component to susceptibility to infections, in particular involving polymorphisms in innate immunity. Given the key role of innate immunity in IBD pathogenesis, whether such shared polymorphisms also influence risk of infections on anti-TNF therapy has not been examined previously. Thus, the development of tools to define likelihood of treatment response and infections are a key unmet need in the field. Our overarching objective is to identify clinical and genetic predictors of both short-term and long-term response as well as infectious complications of anti-TNF therapy. To achieve these aims, we will utilize the complementary strengths of two large cohorts - a prospective registry cohort of over 1200 patients with CD or UC, and a novel EMR-based cohort of over 11,000 patients with CD or UC linked to a biospecimen repository. This proposal utilizes the mentorship and significant expertise in key areas including analytical genetics, translational immunology, and bioinformatics and allows the candidate to develop fundamental skills in these novel content areas and research methods. The access to expertise at the NIH-funded center Informatics for Integrating Biology and the Bedside, the Center for Study of Inflammatory Bowel Disease, and the Broad Institute is a key strength of this application. This career development award will be critical in providing training in bioinformatics and genetic epidemiology, thus contributing to the candidate's long-term goal of establishing an independent IBD research career with focus on defining at-risk cohorts and personalizing therapy. The training component of the award includes graduate-level courses in the relevant content areas in genetic epidemiology, and bioinformatics at the Harvard Medical School, School of Public Health, and Massachusetts Institute of Technology. The candidate will continue to actively engage with an established group of multidisciplinary researchers who have demonstrated the utility of the EMR-based approach to accurately define autoimmune diseases, link it to biospecimen collection, and use it successfully for genotyping-phenotype research. This will help foster collaborative development of future proposals as the work proposed in this application has the potential for applicability in other cohorts.

Public Health Relevance

The novel information gained from this study regarding genetic predictors of treatment response and infectious complications has the potential to transform clinical practice by leading to clinical trials focused on selected cohorts of patients most likely to respond to therapies with low risk of adverse events, thus preventing unnecessary exposure to potentially toxic therapies with low likelihood of benefit. Such work is a step toward developing personalized medicine approaches to tailor therapy based on likelihood of benefit and risk. The methodology developed here will also have applications in other EMR-based cohorts to investigate novel therapeutic agents and disease outcomes.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Mentored Patient-Oriented Research Career Development Award (K23)
Project #
4K23DK097142-05
Application #
9070599
Study Section
Special Emphasis Panel (ZDK1)
Program Officer
Saslowsky, David E
Project Start
2012-09-15
Project End
2017-05-31
Budget Start
2016-06-01
Budget End
2017-05-31
Support Year
5
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
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