Developing microbiome-based markers for pediatric inflammatory bowel disease (PIBD) is challenging. Here, we evaluated the diagnostic and prognostic potential of the gut microbiome in PIBD through a case-control study and cross-cohort analyses. In a Korean PIBD cohort (24 patients with PIBD, 43 controls), we observed that microbial diversity and composition shifted in patients with active PIBD versus controls and recovered at remission. We employed a differential abundance meta-analysis approach to identify microbial markers consistently associated with active inflammation and remission across seven PIBD cohorts from six countries (n = 1,670) including our dataset. Finally, we trained and tested various machine learning models for their ability to predict a patient's future remission based on baseline bacterial composition. An ensemble model trained with the amplicon sequence variants effectively predicted future remission of PIBD. This research highlights the gut microbiome's potential to guide precision therapy for PIBD.

CJ Bioscience Seoul 04527 Republic of Korea

Department of Integrative Biology and Physiology UCLA Los Angeles CA 957246 USA

Department of Medical Microbiology 2nd Faculty of Medicine Charles University and Motol University Hospital 15006 Prague Czechia

Department of Paediatrics 2nd Faculty of Medicine Charles University and Motol University Hospital 15006 Prague Czechia

Department of Pediatrics Korea Cancer Center Hospital Korea Institute of Radiological and Medical Sciences Seoul 01812 Republic of Korea

Department of Pediatrics Korea University College of Medicine Korea University Guro Hospital Seoul 08308 Republic of Korea

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