To assess the differential expression of IBD-related microbiome-derived biomarkers including bacterial strains and peptides such as antimicrobial peptides (AMP) found in inner-colonic samples (HygiSample™) in comparison to home collected stool samples in patients with active IBD colonic disease. The HygiSample will be collected during a defecation-inducing high-volume (\>40 L) colon irrigation bowel prep (HygiPrepⓇ).
This study is a preliminary study aimed to assess the ability to differentially detect IBD-related microbiome-derived biomarkers in colon effluent samples collected using the Hygieacare System. The proposed sample size of 20 patients (10 in the control arm, 10 in the IBD arm), where each patient provides both stool and three inner-colonic samples is sufficient to provide preliminary results for such an assessment. Categorical variables will be summarized by frequencies and percentages, while quantitative variables will be summarized by descriptive statistics (mean, median, standard deviation, minimum, and maximum). The investigators will compare taxonomy and phylogeny biodiversity between the control and the IBD arms and between stool and colon effluent samples.
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Enrollment
20
The device is an FDA cleared colon irrigation device, it will be used according to clearance. The sampling of the colon effluent sampled is the are of study.
Hygieacare Center
Norfolk, Virginia, United States
Detection of IBD-related microbiome-derived biomarkers in stool samples
Each patient provides both stool (when possible) and inner-colonic samples. The samples will be analyzed to identify microorganisms' presence and abundance, diversity, and functional genomics. Specifically, we will look at the alpha and beta diversity of the microbiota (% of prediction on the most dominant vectors of the system) and the taxonomic differences between the samples - represented by percentages over taxonomic groups. If the data allows (based on our omics results), we will look at the potential abundance of calprotectin (IBD biomarker, % from control). We will analyze the data for the study participants by age, gender, BMI (average, median, standard deviation), and prevalence of underlying diseases. The questionnaires will be used to find correlations between the patient's overall health, exercise routine, nutritional habits, and diet. Results will be presented using R\^2 when applies.
Time frame: analysis end of study enrollment
unpaired T-test
We will track the patients demographic and physiological parameters - age (years), gender (male/female), height (feet inches), weight (lbs), BMI. We will collect information about the patients eating, heath, and exercise habits using a questionnaire.
Time frame: analysis end of study enrollment
cox wilcoxon test
We will track the patients demographic and physiological parameters - age (years), gender (male/female), height (feet inches), weight (lbs), BMI. We will collect information about the patients eating, heath, and exercise habits using a questionnaire
Time frame: through study completion, an average of 1 year
Differential abundance analysis
For our comparative analyses, we will carry out clustering and differential abundance. we will qualify the bacteria abundance using 16S and meta genomics analysis and provide information of the available species using Alpha diversity and Shannon index and beta diversity using PCoA analysis. analysis with correction for multiple comparisons by false discovery rate.
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Time frame: through study completion, an average of 1 year
Alpha diversity
16S and meta genomics analysis
Time frame: through study completion, an average of 1 year
Shannon index
16S and meta genomics analysis
Time frame: through study completion, an average of 1 year
beta diversity
PCoA analysis
Time frame: through study completion, an average of 1 year