Development of an Index Score for Intestinal Inflammation-Associated Dysbiosis Using Real-World Stool Test Results

Abstract

Background Gut microbiota play an important role in human health. However, the application of gut microbiome in regular clinical practice is limited by interindividual variations and complexity of test results. Hypothesis It is possible to address interindividual variation by using large data-based exploratory-pattern analysis. Methods The current study was conducted using a large data set (n = 173,221) of nonselective incoming patients' test results from a stool test. The data set included assays for the detection of 24 selected commensal microorganisms and multiple biomarkers in feces. Patients were grouped based on their levels of inflammation biomarkers such as calprotectin, eosinophil protein X, and IgA. Group mean values of biomarkers and commensal microbes were used in an exploratory-pattern analysis for association from which an index score for intestinal inflammation-associated dysbiosis (IAD) was developed. The IAD score was evaluated in one questionnaire-based study (n = 7263) and one prospective case series study (n = 122) with patients of inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), and celiac disease. Results We identified a microbial profile strongly associated with fecal inflammation biomarkers. Developed on the pattern of the microbial profile, the IAD score demonstrated a strong association with fecal inflammation biomarkers and was significantly different between patients with IBD and those with IBS or celiac disease. Conclusion Using real-world data, we have developed a method to predict gut dysbiosis associated with different GI disease conditions. It may help clinicians simplify the process of interpreting gut microbial status and provide gut health assessment and treatment evaluation.

Human gut microbiome and metabolite dynamics under simulated microgravity

“…While moieties diverged between samples, the cumulative amount was maintained over time. Valerate, isovalerate, and isobutyrate, labeled as putrefactive byproducts, 28 accounted for up to 10% of SCFAs and tended to increase with HDT and decline during recovery periods at R9. The response was particularly pronounced in the centrifugation groups.…”

“…We looked into the biomarkers reported for severe inflammatory disease among the peptides identified in the AGBRESA samples indicating intestinal inflammation, 28 risk of occurrence of pro-carcinogens, 47 and the severity of inflammation. 48 , 49 Overall, neither the microgravity simulation with HDT nor the countermeasure protocols significantly affected the abundance of severe inflammatory bowel disorder biomarkers, yet these values lack verification with antigen-specific methodology used for clinical diagnosis.…”

Impact of 2′-Fucosyllactose on Gut Microbiota Composition in Adults with Chronic Gastrointestinal Conditions: Batch Culture Fermentation Model and Pilot Clinical Trial Findings

“…The GIQLI, DSFQ, and IBDQ were scored as previously described [ 55 , 56 , 57 ]. Stool samples were shipped to Genova Diagnostics (Asheville, NC, USA) within twenty-four hours of collection; commensal gut microbiota were identified using 16S ribosomal RNA gene PCR and concentrations of SCFA were measured using gas chromatography–mass spectrometry (GC-MS) as previously described [ 58 ].…”

Dys-R Questionnaire: A Novel Screening Tool for Dysbiosis Linked to Impaired Gut Microbiota Richness

“…In addition to these indexes, there is mention in the literature of the ongoing development of a multiplatform Health app (mHealth) for dysbiosis detection (mDys), which takes a multiomic approach, specifically for individuals with inflammatory bowel disease (IBD) [35]. Other fecal-based tests and algorithms have also been created, primarily focused on IBD, and typically require the collection of fecal samples [36].…”