Digital Biomarkers of Ulcerative Colitis Flare

This project will evaluate longitudinally collected physiological metrics, with a focus on autonomic nervous system function (heart rate variability [HRV]), using wearable devices. It will investigate the ability of these physiological metrics to identify and predict symptomatic ulcerative colitis (UC) flares. It will explore the

modifiability of these metrics through a HRV directed biofeedback intervention and its impact on UC symptoms. Candidate: The primary objective of this application is to support the development of Dr. Robert Hirten into an independent patient-oriented researcher in the field of digital health and inflammatory bowel disease (IBD)

research. Dr. Hirten’s career goal is to be an independent researcher and leader in leveraging the dense physiological data acquired through novel wearable technologies in IBD research. Dr. Hirten’s proposed training activities are in five areas: (1) Advanced statistical methodology, (2) Digital health, (3) Clinical trial design, (4)

Behavioral intervention science, (5) Career development. To achieve these goals Dr. Hirten has assembled a mentorship team led by Dr. Bruce Sands, Chief of Gastroenterology at The Mount Sinai Hospital who has expertise in longitudinal and clinical trial research in IBD. Environment: The Icahn School of Medicine at Mount

Sinai has a strong tradition of research and is a top 20 medical school in NIH funding. The Mount Sinai Division of Gastroenterology is a top 10 division in the country by US News and World Report and is a leader in IBD research and clinical care. The Hasso Plattner Institute for Digital Health at Mount Sinai is an international

institute with expertise in data science, biomedical and digital engineering. Research: UC is a chronic inflammatory disease affecting the colon with symptomatic flares characterized by diarrhea, blood per rectum and abdominal pain. Flares are frequent, occurring in at least 30% of patients per year, and are associated with

morbidity and impaired quality of life. Current methods to identify and predict flare are suboptimal and limited. If flares can be identified earlier and predicted strategies for mitigation or prevent could be instituted. Advances in digital and wearable technology allow for collection of continuous, non-invasive physiological parameters

potentially linked with disease activity. Therefore, our specific aims are to (1) To determine the association of physiological metrics, including HRV, with symptomatic flare in UC, (2) To assess the predictive ability of physiological metrics, with a focus on HRV, for the development of symptomatic flare in UC, (3) Determine the

feasibility, acceptability, and effect size of a HRV biofeedback intervention in subjects with symptomatic UC. To accomplish this we will perform a longitudinal cohort study enrolling 160 subjects with UC in remission and follow them for 12 months or until flare, collecting physiological indices from a wearable device (Apple Watch) and

survey metrics from a smart phone application. In addition, we will perform a HRV directed biofeedback intervention in 23 subjects with UC and symptomatic flare. The general approach and skills acquired during this award can be applied to future R01 grants aimed at building upon the findings from this work.