Anti-tumor necrosis factor (TNF) therapy is a mainstay for induction and maintenance of remission in moderate- to-severe Crohn?s disease (CD) and ulcerative colitis (UC), but is not effective for many, leading to protracted morbidity, hospitalizations, and surgery. Up to thirty percent of patients demonstrate no response to anti-TNF induction therapy (primary non-response), and an additional 10-15% lose response annually. With the emergence of novel therapeutics with different mechanisms of action, a priori prediction of response to a particular therapeutic class before exposure to therapy is increasingly important. Such a targeted approach will benefit the patient by avoiding unnecessary exposure to ineffective therapies and allowing attainment of earlier remission through initial selection of the therapy most likely to benefit. Importantly, it may also benefit society from a cost-effectiveness standpoint by reducing costs related to ineffective therapies and healthcare utilization. To date, clinical predictors of response to anti-TNF therapy have not been widely replicated and do not provide a reliable model for use in clinical practice. Our central hypothesis is that genetic polymorphisms related to inflammatory bowel disease pathogenesis or the mechanisms of action of anti-TNF agents may influence response to these drugs, and that use of these polymorphisms to predict response to anti-TNF therapy will provide a precision medicine approach for improved quality and cost-effective care in the clinical setting. Our group has recently established the ability to use a genetic risk score to predict response to anti-TNF therapy in Crohn?s disease, and has demonstrated superiority of this model to one including only clinical variables for primary anti-TNF non-response. Whether a similar approach is also beneficial in ulcerative colitis is unknown, but is important to establish given different disease-related loci, disease phenotype, and likelihood of response. We plan to investigate our hypothesis through three specific aims. First, we will define the association of genetic polymorphisms with primary non-response to anti-TNF therapy in patients with ulcerative colitis using a large rigorously-phenotyped cohort and validate this in an external independent cohort. We will test these polymorphisms in a predictive model for anti-TNF non-response. In our second aim, we will define the role of genetics in determining durable response to therapy, with particular focus on their impact on drug pharmacokinetics and immunogenicity. Finally, we will develop a cost-effectiveness model examining the utility of our precision medicine genotype-driven therapeutic algorithm compared to an unselective approach with respect to costs, clinical outcomes, and quality of life. We will determine the necessary predictive value threshold of this personalized approach to achieve cost-effectiveness on a societal scale. The long-term goal of this work is to understand and utilize human biology in inflammatory bowel disease to create a personalized, precise approach to therapy to improve outcomes and quality of life.

Public Health Relevance

The proposed research seeks to elucidate genetic polymorphisms predictive of primary non-response and durable response to anti-tumor necrosis factor therapy in patients with moderate-to-severe ulcerative colitis in two large cohorts, and utilize candidate polymorphisms in a predictive model of therapy response for clinical application, with the aim of improving clinical outcomes. We will evaluate the cost-effectiveness of our precision- medicine model by comparing tailored initiation of therapy based on a priori predicted likelihood of response using our personalized approach with an unselective sequential step-up approach. The proposed project is directly relevant to the NIH mission of understanding the biology of human systems, and using this knowledge to enhance health and to reduce illness and disability.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
5F32DK115134-02
Application #
9650395
Study Section
Special Emphasis Panel (ZDK1)
Program Officer
Densmore, Christine L
Project Start
2018-02-01
Project End
2020-01-31
Budget Start
2019-02-01
Budget End
2020-01-31
Support Year
2
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02114