Clostridium difficile is the leading cause of nosocomial infection in the U.S., outpacing both antibiotic-resistant staphylococcus and enterococcus. The high prevalence of Clostridium difficile infection (CDI) represents a major health problem for hospitals and long-term care facilities alike due to common patient risk factors; notably advanced age and comorbidity, use of antimicrobials and difficulty in C. difficile spore disinfection. Newly-emerged hypervirulent C. difficile strains have also contributed to CDI escalation resulting in increased disease severity and mortality. Furthermore, 35% of patients will experience recurrent CDI, a significant clinical issue that often results in poor clinical outcome. Despite the fact that early diagnosis of CDI is crucial for optimal clinical management and improved prognosis, diagnostic assays that accurately predict CDI recurrence do not exist and risk factors for recurrent CDI remain elusive. The high frequency of CDI recurrence, coupled with poor clinical outcomes for cases not promptly and effectively treated, underscores the need to identify accurate biomarkers of disease recurrence that can be developed into new diagnostic assays. This is the major goal of our study. Although antimicrobial disruption of the protective gut microflora is known to strongly correlate with the development of symptoms in infected individuals, there is still a major gap in our understanding of CDI susceptibility and recurrence. In this revised application, we demonstrate that integration of next generation DNA sequencing with global metabolomics into microbial ecosystem networks provides an analytical framework for the discovery of new diagnostic and treatment options for recurrent CDI. The significance of our multi-omics approach is the identification of candidate 16S rRNA and biochemical biomarkers in primary CDI patients who go on to develop recurrent disease (misclassification rate of 12%). These multi-omic studies led to the following novel observations in CDI patients: Identification of a major potential deficiency when using molecular-based testing to diagnose CDI. A 54% misdiagnosis rate was indicated when using sensitive nucleic acid amplification tests that cannot discriminate CDI from asymptomatic C. difficile carriage. Based on our identification of ?-aminobutyric acid (GABA) and precursors of GABA synthesis as candidate biomarkers of CDI recurrence, a 4.88-fold higher CDI risk association was identified in hospitalized patients prescribed Zolpidem (Ambien), a GABA receptor A agonist. Our goal for Aim 1 is to validate candidate 16S rRNA biomarkers of CDI recurrence in a larger 200 patient based cohort and correlate these findings with clinical metadata.
For Aim 2, we expect to validate candidate metabolomic biomarkers of CDI recurrence in the same 200 patient cohort and perform multi-omic analysis. We expect that the multi-omic biomarkers - alone or in combination - will accurately predict CDI recurrence. Considering the complete lack of recurrent CDI diagnostic assays, we aim to develop one or more biomarkers for use as a gold standard method that will validate other cost effective assays enabling differentiation of CDI from asymptomatic colonization, as well as identification of patients at risk for recurrent CDI. This type of diagnostic represents a priority clinical need and a major biomedical market opportunity. We also anticipate that newly adopted nucleic acid amplification testing is greatly overestimating CDI incidence. Our preliminary data indicate that such patients are likely receiving wholly inappropriate treatment options resulting from their apparent misdiagnosis e.g. fecal microbiota transplantation in children.
This project will validate innovative multi-omic methods to improve the diagnosis and clinical management of Clostridium difficile infection, which currently causes widespread, and potentially fatal intestinal disease.
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