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Bridging Inflammatory Bowel Diseases and Hepatobiliary Disorders Through Pathway Enrichment and Module-Based Approach

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Bridging Inflammatory Bowel Diseases and Hepatobiliary Disorders Through Pathway Enrichment and Module-Based Approach BRIDGING INFLAMMATORY BOWEL DISEASES AND HEPATOBILIARY DISORDERS THROUGH PATHWAY ENRICHMENT AND MODULE-BASED APPROACH Master Degree Project in bioinformatics One year 30 ECTS Spring term 2020 Alaa Saloum [email protected] Supervisor: Zelmina Lubovac Email: [email protected] Examiner: Björn Olsson Email: [email protected] Abstract Inflammatory bowel diseases (IBD) including Crohn’s disease (CD) and ulcerative colitis (UC) are associated with various hepatobiliary disorders. Two of the chronic hepatobiliary disorders that may coexist with inflammatory bowel diseases are: primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC). Previous studies have hypothesized that IBD, PBC, and PSC might share an underlying mechanism which contributes to the pathogenesis of the three conditions. In this study, a module-based network analysis and pathway enrichment analysis was applied on IBD, PSC, and PBC differentially expressed genes (DEGs). The sample data were obtained from the study by Ostrowski et al. (2019). A network module- based approach was applied to examine generated results where additional information about biological processes, pathways and molecular functions can be inferred. FunRich and Enrichr were utilized as functional enrichment tools. A protein interaction network was constructed for the three conditions using STRING. Functional modules and overlapping modules of IBD, PSC, and PBC were identified using different plug-ins in Cytoscape. Some of the results were consistent with the findings of Ostrowski et al. (2019) such as the ATP synthesis and signal transduction that is shared among the overlapping genes in IBD, PBC, and PSC. ModuLand highlighted nodes that have been previously reported to have a role in the pathogenesis of autoimmune diseases. The proposed approach demonstrated that the module-based approach contributes to similar results regarding biological processes and pathway enrichment of generated modules, compared to enrichment analysis of DEGs. In addition, the utilization of the ModuLand plug-in to find hierarchal layers of disease genes is still poorly researched and would benefit from more in-depth comparison with related tools for module discovery. For instance, implementing ModuLand plug-in can potentially support research in elucidating complex diseases. Table of Contents Abstract ........................................................................................................................................................... Abbreviations .................................................................................................................................................. 1. Introduction .............................................................................................................................................. 1 1.1. Background of inflammatory bowel disease and hepatobiliary disorders ........................................ 1 1.2. Hepatobiliary associations with inflammatory bowel disease .......................................................... 1 1.3. Networks and module-based approach ............................................................................................. 2 2. Materials and Methods ............................................................................................................................. 3 2.1. Analysis of differentially expressed genes (DEGs) ............................................................................. 4 2.2. Pathway enrichment analysis ............................................................................................................ 4 2.3. Protein-protein interaction network ................................................................................................. 6 2.4. Functional modules ............................................................................................................................ 7 2.5. Identification of shared modules ....................................................................................................... 8 3. Alternative methods ................................................................................................................................. 9 3.1. Analysis of differentially expressed genes (DEGs) ............................................................................. 9 3.2. Pathway enrichment analysis .......................................................................................................... 10 3.3. Protein-protein interaction network ............................................................................................... 10 3.4. Functional modules .......................................................................................................................... 11 3.5. Identification of shared modules ..................................................................................................... 11 4. Implementation and Results ................................................................................................................... 12 4.1. Analysis of differentially expressed genes (DEGs) ........................................................................... 12 4.2. Pathway enrichment analysis .......................................................................................................... 13 4.2.1. PBC DEGs enrichment analysis.................................................................................................. 13 4.2.2. PSC DEGs enrichment analysis .................................................................................................. 14 4.2.3. IBD DEGs enrichment analysis .................................................................................................. 14 4.2.4. Comparison between functional enrichment of PBC, PSC, and IBD DEGs ................................ 14 4.2.5. Comparison between biological pathways in PBC, PSC and IBD using FunRich ....................... 14 4.2.6. Comparison between biological processes in PBC, PSC and IBD using FunRich ....................... 16 4.2.7. Enrichment analysis of overlapping genes between PBC, PSC and IBD using FunRich ............ 16 4.3. Protein-Protein Interaction Network ............................................................................................... 19 4.4. Functional modules .......................................................................................................................... 19 4.4.1. PSC, PBC, and IBD functional modules ...................................................................................... 20 4.4.2. Enrichment analysis of the functional modules ........................................................................ 20 4.5. Identification of modules ................................................................................................................. 23 5. Discussion ................................................................................................................................................ 25 6. Ethical Aspects ........................................................................................................................................ 29 7. Impact on Society and Future Directions ................................................................................................ 30 8. References .............................................................................................................................................. 31 9. Appendix ................................................................................................................................................. 38 Abbreviations BioGRID Biological general repository for interaction data sets CD Crohn’s disease DEG Differentially expressed genes Database for Annotation, Visualization, and Integrated DAVID Discovery FunRich Functional Enrichment GO Gene Ontology GEO Gene Expression Omnibus IBD Inflammatory bowel disease KEGG Kyoto Encyclopedia of Genes and Genomes MCODE Molecular Complex Detection MCL Markov CLustering Algorithm NCBI National Center for Biotechnology Information PPI Protein-protein interaction PBC Primary biliary cholangitis PSC Primary sclerosing cholangitis STRING Search Tool for the Retrieval of Interacting Genes/Proteins UC Ulcerative colitis 1. Introduction 1.1. Background of inflammatory bowel disease and hepatobiliary disorders Inflammatory bowel disease (IBD) is defined as a chronic intestinal inflammation that pursues a protracted relapsing and remitting course (Rubin et al., 2012). The disease encompasses two major types, ulcerative colitis (UC) and Crohn's disease (CD). Both UC and CD exhibit severe diarrhea, fatigue, abdominal pain and weight loss in patients (Fakhoury et al., 2014). Despite the similar clinical and pathological features that UC and CD share, both diseases are heterogeneous with marked differences in clinical presentation, underlying genetic factors, and also response to treatment. In terms of inflammation location, CD is characterized by its inflammation anywhere in the gastrointestinal tract that occurs in a patchy distribution (Vasquez et al., 2007). On the other hand, UC mainly presents with inflammation of the rectal and sigmoid colon (Vasquez et al., 2007). Both IBD subtypes are reported to be prevalent in highly developed nations. For example, CD has a prevalence of 30–50 of 100,000 people in western countries (Fakhoury et al., 2014). IBD including CD and UC are associated with various hepatobiliary disorders.
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