Individual-network based predictions of microbial interaction signatures for response to biological therapies in IBD patients
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...
Saved in:
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-01-01
|
| Series: | Frontiers in Molecular Biosciences |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fmolb.2024.1490533/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832582943489392640 |
|---|---|
| author | Federico Melograna Padhmanand Sudhakar Behnam Yousefi Behnam Yousefi Clara Caenepeel Gwen Falony Gwen Falony Gwen Falony Sara Vieira-Silva Sara Vieira-Silva Sara Vieira-Silva Sreenikhitha Krishnamoorthy David Fardo Bram Verstockt Bram Verstockt Jeroen Raes Jeroen Raes Severine Vermeire Severine Vermeire Kristel Van Steen |
| author_facet | Federico Melograna Padhmanand Sudhakar Behnam Yousefi Behnam Yousefi Clara Caenepeel Gwen Falony Gwen Falony Gwen Falony Sara Vieira-Silva Sara Vieira-Silva Sara Vieira-Silva Sreenikhitha Krishnamoorthy David Fardo Bram Verstockt Bram Verstockt Jeroen Raes Jeroen Raes Severine Vermeire Severine Vermeire Kristel Van Steen |
| author_sort | Federico Melograna |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-4d9a156576864cbb94aaa84c27003804 |
| institution | Kabale University |
| issn | 2296-889X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Molecular Biosciences |
| spelling | doaj-art-4d9a156576864cbb94aaa84c270038042025-01-29T05:21:25ZengFrontiers Media S.A.Frontiers in Molecular Biosciences2296-889X2025-01-011110.3389/fmolb.2024.14905331490533Individual-network based predictions of microbial interaction signatures for response to biological therapies in IBD patientsFederico Melograna0Padhmanand Sudhakar1Behnam Yousefi2Behnam Yousefi3Clara Caenepeel4Gwen Falony5Gwen Falony6Gwen Falony7Sara Vieira-Silva8Sara Vieira-Silva9Sara Vieira-Silva10Sreenikhitha Krishnamoorthy11David Fardo12Bram Verstockt13Bram Verstockt14Jeroen Raes15Jeroen Raes16Severine Vermeire17Severine Vermeire18Kristel Van Steen19BIO3 Laboratory for Systems Medicine, Department of Human Genetics, KU Leuven, Leuven, BelgiumDepartment of Biotechnology, Kumaraguru College Technology, Coimbatore, Tamil Nadu, IndiaInstitute of Medical Systems Biology, Center for Biomedical AI (bAIome), Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf, Hamburg, GermanyGerman Center for Child and Adolescent Health (DZKJ), Partner Site Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, GermanyDepartment of Gastroenterology and Hepatology, University Hospitals Leuven, KU Leuven, Leuven, BelgiumLaboratory of Molecular Bacteriology, Department of Microbiology and Immunology, Rega Institute, Katholieke Universiteit Leuven, Leuven, BelgiumCenter for Microbiology, Vlaams Instituut voor Biotechnologie (VIB), Leuven, BelgiumInstitute of Medical Microbiology and Hygiene and Research Center for Immunotherapy (FZI), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, GermanyLaboratory of Molecular Bacteriology, Department of Microbiology and Immunology, Rega Institute, Katholieke Universiteit Leuven, Leuven, BelgiumInstitute of Medical Microbiology and Hygiene and Research Center for Immunotherapy (FZI), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, GermanyInstitute of Molecular Biology (IMB), Mainz, GermanyDepartment of Biotechnology, Kumaraguru College Technology, Coimbatore, Tamil Nadu, India0College of Public Health, University of Kentucky, Lexington, KY, United States1KU Leuven Department of Chronic Diseases and Metabolism, Translational Research Center for Gastrointestinal Disorders (TARGID), Leuven, BelgiumDepartment of Gastroenterology and Hepatology, University Hospitals Leuven, KU Leuven, Leuven, BelgiumLaboratory of Molecular Bacteriology, Department of Microbiology and Immunology, Rega Institute, Katholieke Universiteit Leuven, Leuven, BelgiumCenter for Microbiology, Vlaams Instituut voor Biotechnologie (VIB), Leuven, Belgium1KU Leuven Department of Chronic Diseases and Metabolism, Translational Research Center for Gastrointestinal Disorders (TARGID), Leuven, BelgiumDepartment of Gastroenterology and Hepatology, University Hospitals Leuven, KU Leuven, Leuven, BelgiumBIO3 Laboratory for Systems Medicine, Department of Human Genetics, KU Leuven, Leuven, BelgiumInflammatory 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.https://www.frontiersin.org/articles/10.3389/fmolb.2024.1490533/fullinflammatory bowel diseasetherapyfecal microbiota16S profilingindividual specific networksresponse prediction |
| spellingShingle | Federico Melograna Padhmanand Sudhakar Behnam Yousefi Behnam Yousefi Clara Caenepeel Gwen Falony Gwen Falony Gwen Falony Sara Vieira-Silva Sara Vieira-Silva Sara Vieira-Silva Sreenikhitha Krishnamoorthy David Fardo Bram Verstockt Bram Verstockt Jeroen Raes Jeroen Raes Severine Vermeire Severine Vermeire Kristel Van Steen Individual-network based predictions of microbial interaction signatures for response to biological therapies in IBD patients Frontiers in Molecular Biosciences inflammatory bowel disease therapy fecal microbiota 16S profiling individual specific networks response prediction |
| title | Individual-network based predictions of microbial interaction signatures for response to biological therapies in IBD patients |
| title_full | Individual-network based predictions of microbial interaction signatures for response to biological therapies in IBD patients |
| title_fullStr | Individual-network based predictions of microbial interaction signatures for response to biological therapies in IBD patients |
| title_full_unstemmed | Individual-network based predictions of microbial interaction signatures for response to biological therapies in IBD patients |
| title_short | Individual-network based predictions of microbial interaction signatures for response to biological therapies in IBD patients |
| title_sort | individual network based predictions of microbial interaction signatures for response to biological therapies in ibd patients |
| topic | inflammatory bowel disease therapy fecal microbiota 16S profiling individual specific networks response prediction |
| url | https://www.frontiersin.org/articles/10.3389/fmolb.2024.1490533/full |
| work_keys_str_mv | AT federicomelograna individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients AT padhmanandsudhakar individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients AT behnamyousefi individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients AT behnamyousefi individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients AT claracaenepeel individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients AT gwenfalony individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients AT gwenfalony individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients AT gwenfalony individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients AT saravieirasilva individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients AT saravieirasilva individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients AT saravieirasilva individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients AT sreenikhithakrishnamoorthy individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients AT davidfardo individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients AT bramverstockt individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients AT bramverstockt individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients AT jeroenraes individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients AT jeroenraes individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients AT severinevermeire individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients AT severinevermeire individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients AT kristelvansteen individualnetworkbasedpredictionsofmicrobialinteractionsignaturesforresponsetobiologicaltherapiesinibdpatients |