Multicenter Human Derivatives Prospective Cohort Study: Clinical information will be collected from patients with ankylosing spondylitis and their families who have provided research consent. And clinical samples including blood, saliva, feces, and mucosal biopsy tissue (from patients scheduled for sigmoid colonoscopy or routine colonoscopy examinations) will be collected. Multi-omics data production and laboratory analysis will be conducted using the collected samples, followed by integrated bioinformatic analysis using the produced data."
Enrollment of ankylosing spondylitis patients and family controls who meet the exclusion criteria 2) Collection of standard clinical information items 3) Collect biological samples according to standardized protocols 4) Produce microbiome and multi-omics data from biosamples 5) Conduct clinical research using clinical information items and microbiome and multi-omics data
Study Type
OBSERVATIONAL
Enrollment
600
Kyung Hee University Medical Center
Seoul, Kyungheedae-ro 23, South Korea
RECRUITINGHanyang University Hospital for Rheumatic Diseases
Seoul, Wangsimni-ro222-1, South Korea
RECRUITINGCollect clinical information data for ankylosing spondylitis patients and their families
"Clinical information data will be collected from both ankylosing spondylitis patients and their families. Biosamples collected from these individuals will be used to establish a multi-omics analysis platform, including the examination of the intestinal microbiome. With this platform, comparative clinical studies will be conducted to uncover the disease's pathophysiology and identify potential biomarkers."
Time frame: Visit 1 (0week)
Multi-omics data for ankylosing spondylitis patients and their families with consent.
Diversity analysis: Alpha and beta diversity analyses are conducted to determine differences in the composition of gut microbiota between healthy individuals and patients. Important feature selection: Differential abundance analysis (e.g., using methods like LEfSe or ANCOM) or machine learning (e.g., random forest, support vector machine) is employed to identify microbiota. Functional profile prediction: In cases where metagenomic analysis is not feasible, the PICRUSt2 program is utilized to predict and analyze functional profiles based on the phylogeny of the microbiota present in healthy individuals and patients.
Time frame: Follow up Visit (24week)
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.