Federico Melograna ¹ Padhmanand Sudhakar ² Behnam Yousefi ³ Clara Caenepeel ⁴ Gwen Falony ⁵ Sara Vieira-Silva ⁶ Sreenikhitha Krishnamoorthy ² David Fardo ⁷ Bram Verstockt ⁴ Jeroen Raes ⁸ Severine Vermeire ^4* Kristel Van Steen ^9*

• ¹ Department of Human Genetics, Faculty of Medicine, KU Leuven, Leuven, Brussels, Belgium
• ² Department of Biotechnology, Kumaraguru College of Technology, Coimbatore, India
• ³ Center for Molecular Neurobiology Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Hamburg, Germany
• ⁴ Department of Gastroenterology and Hepatology, University Hospitals Leuven, Leuven, Brussels, Belgium
• ⁵ Department of Pediatric Hematology, Oncology, Hemostaseology, Center for Pediatric and Adolescent Medicine, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Rhineland-Palatinate, Germany
• ⁶ Institute of Molecular Biology, Mainz, Rhineland-Palatinate, Germany
• ⁷ College of Public Health, University of Kentucky, Lexington, Kentucky, United States
• ⁸ Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium
• ⁹ Laboratory for Complex Genetics, Department of Human Genetics, Faculty of Medicine, KU Leuven, Leuven, Belgium

Inflammatory Bowel Disease (IBD), which includes Ulcerative Colitis (UC) and Crohn's Disease (CD), is marked by dysbiosis of the gut microbiome. Despite therapeutic interventions with biological agents like Vedolizumab, Ustekinumab, and anti-TNF agents, the variability in clinical, histological, and molecular responses remains significant due to inter-individual and inter-population differences. This study introduces a novel approach using Individual Specific Networks (ISNs) derived from faecal microbial measurements of IBD patients across multiple cohorts. These ISNs, constructed from baseline and follow-up data post-treatment, successfully predict therapeutic outcomes based on endoscopic remission criteria. Our analysis revealed that ISNs characterised by core gut microbial families, including Lachnospiraceae and Ruminococcaceae, are predictive of treatment responses. We identified significant changes in abundance levels of specific bacterial genera in response to treatment, confirming the robustness of ISNs in capturing both linear and non-linear microbiota signals. Utilising network topological metrics, we further validated these findings, demonstrating that critical microbial features identified through ISNs can differentiate responders from non-responders with respect to various therapeutic outcomes. The study highlights the potential of ISNs to provide individualised insights into microbiota-driven therapeutic responses, emphasising the need for larger cohort studies to enhance the accuracy of molecular biomarkers. This innovative methodology paves the way for more personalised and effective treatment strategies in managing IBD.