ASSOCIATION BETWEEN NOVEL METABOLOMIC BIOMARKERS AND C.DIFFICILE RECURRENCE
DDW ePoster Library. Allegretti J. 05/21/21; 319723; Fr573
Dr. Jessica Allegretti
Dr. Jessica Allegretti
Contributions Biography
Abstract

Number: Fr573
ASSOCIATION BETWEEN NOVEL METABOLOMIC BIOMARKERS AND C.DIFFICILE RECURRENCE

Society: AGA
Track: Microbiome in Gastrointestinal and Liver Diseases
Category: Microbiome & Microbial Therapy

Author(s): Jessica R. Allegretti3, Benjamin H. Mullish1, Julian Marchesi1, Kevin Kennedy2, Georg Gerber3, Lynn Bry31 Imperial College London, London, United Kingdom; 2 Kansas City Veteran Hospital, Kansas City, Kansas, United States; 3 Brigham and Women's Hospital, Boston, Massachusetts, United States

Background: Commensal gut microbiota have the ability to metabolize primary bile acids (BA) into secondary BA which inhibit Clostridioides difficile growth and germination (CDI), an ongoing public health threat. Current prediction tools for CDI recurrence do not incorporate microbiota-derived metabolites. We investigated novel metabolomic biomarkers as potential predictors of C. difficile recurrence.

Methods: We conducted a prospective study of patients experiencing a first CDI episode. Patients diagnosed with CDI by toxin immunoassay (EIA) or polymerase chain reaction (PCR), and undergoing treatment, were eligible for inclusion. Stool samples were collected serially for 8 weeks after completion of anti-CDI therapy if no recurrence was reported, or until the point of recurrence (defined as diarrhea with positive stool toxin B EIA). Liquid chromatography-mass spectrometry was performed to profile fecal BAs. The week 1 and 2 post-antibiotic time points were used to identify potential predictors. Student's T test was performed on continuous variables. Multivariable logistic regression models were constructed. First, a BA only model using a univariate screen. Stepwise selection was performed with a stay-criteria of 0.10. We constructed a second model that incorporated clinical variables previously shown to be predictive of recurrence. We then tested the nested area under the curves (AUC) using methods by DeLong.

Results: Of 59 first episode CDI patients, 20 patients recurred (34%) during 8-weeks of follow-up. Average time to recurrence was 1.9 weeks. At week 1 and 2, several predictive BA metabolites were identified between re-currers and non-re-currers including; isolithocholic acid (0.05), lithocholenic acid (p=0.04), murocholic acid (p=0.03), glycoursocholanic acid (p=0.02) and 5-beta-cholanic acid (p=0.05). Logistic regression model that included these co-variates with two selected to stay after the stepwise procedure: 5-beta-cholanic acid (OR 0.98, 95% CI .97-1, p=0.05) and glycoursocholanic acid (OR 3.08, 95%CI 1.43-6.61, p=.004). The AUC, when combining these two BAs, was 0.823. Two clinical factors previously found to be predictive of recurrence were subsequently included: use of metronidazole vs vancomycin and diagnosis with EIA vs PCR. The addition of these clinical factors increased the AUC to only 0.838. We found no significant difference in performance between the model with only BAs compared to the model with BAs and clinical variables (p=0.64) (Figure 1)

Conclusion: In this cohort, higher relative abundance of glycoursocholanic acid was associated with recurrence and higher relative abundance of 5-beta-cholanic acid was associated with non-recurrence. The BA analyses may be best utilized as a marker for microbiota recover. Further independent validation of these potential novel biomarkers is required to assess their role as predictors.

Number: Fr573
ASSOCIATION BETWEEN NOVEL METABOLOMIC BIOMARKERS AND C.DIFFICILE RECURRENCE

Society: AGA
Track: Microbiome in Gastrointestinal and Liver Diseases
Category: Microbiome & Microbial Therapy

Author(s): Jessica R. Allegretti3, Benjamin H. Mullish1, Julian Marchesi1, Kevin Kennedy2, Georg Gerber3, Lynn Bry31 Imperial College London, London, United Kingdom; 2 Kansas City Veteran Hospital, Kansas City, Kansas, United States; 3 Brigham and Women's Hospital, Boston, Massachusetts, United States

Background: Commensal gut microbiota have the ability to metabolize primary bile acids (BA) into secondary BA which inhibit Clostridioides difficile growth and germination (CDI), an ongoing public health threat. Current prediction tools for CDI recurrence do not incorporate microbiota-derived metabolites. We investigated novel metabolomic biomarkers as potential predictors of C. difficile recurrence.

Methods: We conducted a prospective study of patients experiencing a first CDI episode. Patients diagnosed with CDI by toxin immunoassay (EIA) or polymerase chain reaction (PCR), and undergoing treatment, were eligible for inclusion. Stool samples were collected serially for 8 weeks after completion of anti-CDI therapy if no recurrence was reported, or until the point of recurrence (defined as diarrhea with positive stool toxin B EIA). Liquid chromatography-mass spectrometry was performed to profile fecal BAs. The week 1 and 2 post-antibiotic time points were used to identify potential predictors. Student's T test was performed on continuous variables. Multivariable logistic regression models were constructed. First, a BA only model using a univariate screen. Stepwise selection was performed with a stay-criteria of 0.10. We constructed a second model that incorporated clinical variables previously shown to be predictive of recurrence. We then tested the nested area under the curves (AUC) using methods by DeLong.

Results: Of 59 first episode CDI patients, 20 patients recurred (34%) during 8-weeks of follow-up. Average time to recurrence was 1.9 weeks. At week 1 and 2, several predictive BA metabolites were identified between re-currers and non-re-currers including; isolithocholic acid (0.05), lithocholenic acid (p=0.04), murocholic acid (p=0.03), glycoursocholanic acid (p=0.02) and 5-beta-cholanic acid (p=0.05). Logistic regression model that included these co-variates with two selected to stay after the stepwise procedure: 5-beta-cholanic acid (OR 0.98, 95% CI .97-1, p=0.05) and glycoursocholanic acid (OR 3.08, 95%CI 1.43-6.61, p=.004). The AUC, when combining these two BAs, was 0.823. Two clinical factors previously found to be predictive of recurrence were subsequently included: use of metronidazole vs vancomycin and diagnosis with EIA vs PCR. The addition of these clinical factors increased the AUC to only 0.838. We found no significant difference in performance between the model with only BAs compared to the model with BAs and clinical variables (p=0.64) (Figure 1)

Conclusion: In this cohort, higher relative abundance of glycoursocholanic acid was associated with recurrence and higher relative abundance of 5-beta-cholanic acid was associated with non-recurrence. The BA analyses may be best utilized as a marker for microbiota recover. Further independent validation of these potential novel biomarkers is required to assess their role as predictors.

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