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Understanding the Molecular Drivers of Disease Heterogeneity in Crohn’s Disease Using Multi-omic Data Integration and Network Analysis

Crohn’s disease (CD), a form of inflammatory bowel disease (IBD), is characterized by heterogeneity along multiple clinical axes, which in turn impacts disease progression and treatment modalities. Using advanced data integration approaches and systems biology tools, we studied the contribution of C...

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Autores principales: Sudhakar, Padhmanand, Verstockt, Bram, Cremer, Jonathan, Verstockt, Sare, Sabino, João, Ferrante, Marc, Vermeire, Séverine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8128416/
https://www.ncbi.nlm.nih.gov/pubmed/33313682
http://dx.doi.org/10.1093/ibd/izaa281
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author Sudhakar, Padhmanand
Verstockt, Bram
Cremer, Jonathan
Verstockt, Sare
Sabino, João
Ferrante, Marc
Vermeire, Séverine
author_facet Sudhakar, Padhmanand
Verstockt, Bram
Cremer, Jonathan
Verstockt, Sare
Sabino, João
Ferrante, Marc
Vermeire, Séverine
author_sort Sudhakar, Padhmanand
collection PubMed
description Crohn’s disease (CD), a form of inflammatory bowel disease (IBD), is characterized by heterogeneity along multiple clinical axes, which in turn impacts disease progression and treatment modalities. Using advanced data integration approaches and systems biology tools, we studied the contribution of CD susceptibility variants and gene expression in distinct peripheral immune cell subsets (CD14+ monocytes and CD4+ T cells) to relevant clinical traits. Our analyses revealed that most clinical traits capturing CD heterogeneity could be associated with CD14+ and CD4+ gene expression rather than disease susceptibility variants. By disentangling the sources of variation, we identified molecular features that could potentially be driving the heterogeneity of various clinical traits of CD patients. Further downstream analyses identified contextual hub proteins such as genes encoding barrier functions, antimicrobial peptides, chemokines, and their receptors, which are either targeted by drugs used in CD or other inflammatory diseases or are relevant to the biological functions implicated in disease pathology. These hubs could be used as cell type–specific targets to treat specific subtypes of CD patients in a more individualized approach based on the underlying biology driving their disease subtypes. Our study highlights the importance of data integration and systems approaches to investigate complex and heterogeneous diseases such as IBD.
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spelling pubmed-81284162021-05-21 Understanding the Molecular Drivers of Disease Heterogeneity in Crohn’s Disease Using Multi-omic Data Integration and Network Analysis Sudhakar, Padhmanand Verstockt, Bram Cremer, Jonathan Verstockt, Sare Sabino, João Ferrante, Marc Vermeire, Séverine Inflamm Bowel Dis Basic Science Research Crohn’s disease (CD), a form of inflammatory bowel disease (IBD), is characterized by heterogeneity along multiple clinical axes, which in turn impacts disease progression and treatment modalities. Using advanced data integration approaches and systems biology tools, we studied the contribution of CD susceptibility variants and gene expression in distinct peripheral immune cell subsets (CD14+ monocytes and CD4+ T cells) to relevant clinical traits. Our analyses revealed that most clinical traits capturing CD heterogeneity could be associated with CD14+ and CD4+ gene expression rather than disease susceptibility variants. By disentangling the sources of variation, we identified molecular features that could potentially be driving the heterogeneity of various clinical traits of CD patients. Further downstream analyses identified contextual hub proteins such as genes encoding barrier functions, antimicrobial peptides, chemokines, and their receptors, which are either targeted by drugs used in CD or other inflammatory diseases or are relevant to the biological functions implicated in disease pathology. These hubs could be used as cell type–specific targets to treat specific subtypes of CD patients in a more individualized approach based on the underlying biology driving their disease subtypes. Our study highlights the importance of data integration and systems approaches to investigate complex and heterogeneous diseases such as IBD. Oxford University Press 2020-12-14 /pmc/articles/PMC8128416/ /pubmed/33313682 http://dx.doi.org/10.1093/ibd/izaa281 Text en © 2020 Crohn’s & Colitis Foundation. Published by Oxford University Press on behalf of Crohn’s & Colitis Foundation. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Basic Science Research
Sudhakar, Padhmanand
Verstockt, Bram
Cremer, Jonathan
Verstockt, Sare
Sabino, João
Ferrante, Marc
Vermeire, Séverine
Understanding the Molecular Drivers of Disease Heterogeneity in Crohn’s Disease Using Multi-omic Data Integration and Network Analysis
title Understanding the Molecular Drivers of Disease Heterogeneity in Crohn’s Disease Using Multi-omic Data Integration and Network Analysis
title_full Understanding the Molecular Drivers of Disease Heterogeneity in Crohn’s Disease Using Multi-omic Data Integration and Network Analysis
title_fullStr Understanding the Molecular Drivers of Disease Heterogeneity in Crohn’s Disease Using Multi-omic Data Integration and Network Analysis
title_full_unstemmed Understanding the Molecular Drivers of Disease Heterogeneity in Crohn’s Disease Using Multi-omic Data Integration and Network Analysis
title_short Understanding the Molecular Drivers of Disease Heterogeneity in Crohn’s Disease Using Multi-omic Data Integration and Network Analysis
title_sort understanding the molecular drivers of disease heterogeneity in crohn’s disease using multi-omic data integration and network analysis
topic Basic Science Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8128416/
https://www.ncbi.nlm.nih.gov/pubmed/33313682
http://dx.doi.org/10.1093/ibd/izaa281
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