The recent increase in global incidence and severity of disease caused by toxigenic Clostridium difficile is of major concern. C. difficile infection (CDI), ranging from mild antibiotic-associated diarrhea to lethal pseudomembranous colitis, consumes increasing resources for diagnosis, treatment, and infection control. The emergence of epidemic strains capable of toxin hyper-production and increased disease severity have further increased the urgency of improving methods for diagnosis and management of CDI. Disease caused by C. difficile is due to production of toxins A and B by strains harboring the toxin genes. Despite mounting evidence that detection of toxin in stool has highest clinical specificity and predictive value, current methods for toxin detection remain inadequate. The cytotoxicity assay has good analytical sensitivity for toxin B [limit of detection (LOD) 1-10 ?g/L] but is laborious and unstandardized. Conventional qualitative immunoassays have high LODs (~0.8-2.5 ng/mL) and poor sensitivity (52-75%). The field has rapidly moved towards nucleic acid testing for ultrasensitive detection of toxigenic organisms, but is increasingly recognizing that its utility (like that of the classic gold standard, toxigenic culture) is confounded by asymptomatic colonization by toxigenic C. difficile. Given these limitations, the field is poised fr the introduction of a simple, ultrasensitive stool toxin detection test that combines high analyticl sensitivity with the clinical specificity of toxin detection. The fact that disease severity has ben preliminarily correlated to toxin levels in the host suggests that the ability to quantify toxin in stool could be valuable to predict disease and treatment outcomes, and to identify those who need aggressive therapy. Such a test could in fact lead to a paradigm shift in the way we diagnose and manage CDI. Under our recent NIAID R21 (5R21AI103612-02), we have successfully developed ultrasensitive and quantitative digital ELISA assays for toxins A and B based on single molecule array (Simoa) technology. Our novel assays detect native toxins in stool with LODs of 0.45 (A) and 1.5 (B) ?g/mL, can quantify toxin across a 4-log dynamic range, and detect toxins from all major clinical strains studied. With these assays in hand, we are positioned to answer some of the most pressing questions in the CDI field. Our goal is to test the central hypothesis that the clinical course of CDI is influenced by the concentrations of toxins A and B in the colon, and thus that accurate and quantitative stool toxin measurement can improve the diagnosis of CDI, aid prediction of disease outcomes, and guide management.
In Aim 1, we will test the hypotheses that toxin levels can predict CDI severity and response to treatment in adults; evaluate the contribution of C. difficile toxinotype to these outcomes; and explore these approaches in a pediatric cohort.
In Aim 2, we will test the hypothesis that toxin levels can distinguish colonization from disease and predict CDI severity in children < 3. Finally, in Aim 3 we will test the hypothesis that binding and neutralization of toxins A and B by host antibodies alter free toxin in the stool and in the blood and influence disease expression and outcomes.
The recent increase in global incidence and severity of disease caused by toxigenic Clostridium difficile presents a major clinical and diagnostic problem. Current methods for diagnosis of C. difficile infection (CDI) have major limitations and improved diagnostics are urgently needed. With the support of an NIAID R21 grant, we have recently developed a simple stool test, using a technology called 'digital ELISA,' that combines high analytical sensitivity with the clinical specificity of C. difficile toxin detection. In this proposal, we will use this newly developed tool to investigate the central hypothesis that the clinical course of CDI is influenced by the concentrations of Toxins A and B in the colon, and that accurate and quantitative stool toxin measurement can improve the diagnosis of CDI, aid prediction of disease outcomes, and guide management.
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