Clostridium difficile infection (CDI) is implicated in nearly 3 million cases of diarrhea and colitis in the U.S. each year. CDI, which disproportionately affects older adults, can result in fulminant, life-threatening colitis and lead to multiple recurrnt episodes. There is an urgent need for validated biomarker-based clinical decision-making tools to predict which patients will experience adverse outcomes from CDI. There is a gap in knowledge regarding which known and yet to-be-discovered biomarkers, derived from the host, microbiome and pathogen, will best predict complications and recurrence. Our long-term goal is to develop and validate accurate risk-prediction models for adverse outcomes following CDI that can be used to guide therapy. The next step in pursuit of that goal, and our overall objective for the proposed research, is to discover new candidate biomarkers and determine which ones together best predict complicated CDI in an adjusted model. Our central hypothesis is that a biomarker-based model will better predict complicated CDI compared to models based on clinical variables alone. To address this hypothesis we propose three specific aims: 1) validate host biomarkers previously shown to associate with complicated CDI; 2) discover novel microbial biomarkers for complicated CDI; and 3) develop a candidate biomarker-based predictive model for complicated CDI. We will collect sera and stool prospectively in a cohort of older adults to determine if characteristics of the microbiome, microbial features of C. difficile, levels of antitoxin antibodies, and/or inflammatory mediators associate with complications. Multivariable models will be constructed using linear regression and machine learning techniques and model diagnostics will be used to generate a final portable, biomarker-based predictive model for use in future studies.

Public Health Relevance

Clostridium difficile infection (CDI) is implicated in nearly 3 million cases of diarrhea and colitis in the U.S. each year. We currently lack a complete understanding as to why certain patients with CDI progress to severe disease with increased complications, including death, while others recover. Our research proposes to discovery objective, readily obtainable indicators from serum/stool that predict adverse outcomes from CDI early after initial disease onset. It is envisioned that this could lead to a paradigm-shift in management by directing specific treatment strategies, including more costly therapeutics such as antibody treatment, fecal transplant and newer antibiotics, towards patients who would most benefit. This research takes the first steps towards development of a biomarker-based predictive tool to aid clinicians in treatment decisions.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21AI120599-01
Application #
8987064
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Ranallo, Ryan
Project Start
2015-07-01
Project End
2017-06-30
Budget Start
2015-07-01
Budget End
2016-06-30
Support Year
1
Fiscal Year
2015
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Seekatz, Anna M; Wolfrum, Emily; DeWald, Christopher M et al. (2018) Presence of multiple Clostridium difficile strains at primary infection is associated with development of recurrent disease. Anaerobe :
Rao, Krishna; Higgins, Peter D R; Young, Vincent B (2018) An Observational Cohort Study of Clostridium difficile Ribotype 027 and Recurrent Infection. mSphere 3:
Seekatz, Anna M; Theriot, Casey M; Rao, Krishna et al. (2018) Restoration of short chain fatty acid and bile acid metabolism following fecal microbiota transplantation in patients with recurrent Clostridium difficile infection. Anaerobe :
Ulrich, Robert J; Santhosh, Kavitha; Mogle, Jill A et al. (2017) Is Clostridium difficile infection a risk factor for subsequent bloodstream infection? Anaerobe 48:27-33
Rao, Krishna; Young, Vincent B (2017) Probiotics for Prevention of Clostridium difficile Infection in Hospitalized Patients: Is the Jury Still Out? Gastroenterology 152:1817-1819
Seekatz, Anna Maria; Rao, Anna Maria; Santhosh, Kavitha et al. (2016) Dynamics of the fecal microbiome in patients with recurrent and nonrecurrent Clostridium difficile infection. Genome Med 8:47
Rao, Krishna; Safdar, Nasia (2016) Fecal microbiota transplantation for the treatment of Clostridium difficile infection. J Hosp Med 11:56-61
Seekatz, Anna Maria; Rao, Krishna; Santhosh, Kavitha et al. (2016) Dynamics of the fecal microbiome in patients with recurrent and nonrecurrent Clostridium difficile infection. Genome Med 8:47
Rao, Krishna; Higgins, Peter D R (2016) Epidemiology, Diagnosis, and Management of Clostridium difficile Infection in Patients with Inflammatory Bowel Disease. Inflamm Bowel Dis 22:1744-54
Rao, Krishna; Santhosh, Kavitha; Mogle, Jill A et al. (2016) Elevated fecal calprotectin associates with adverse outcomes from Clostridium difficile infection in older adults. Infect Dis (Lond) 48:663-9

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