Probing predilection to Crohn's disease and Crohn's disease flares: A crowd-sourced bioinformatics approach
Background: Crohn's Disease (CD) is an inflammatory disease of the gastrointestinal tract that affects millions of patients. While great strides have been made in treatment, namely in biologic therapy such as anti-TNF drugs, CD remains a significant health burden. Method: We conducted two meta-...
Main Authors: | , , , , , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2022-01-01
|
Series: | Journal of Pathology Informatics |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2153353922006605 |
_version_ | 1797976980903165952 |
---|---|
author | Jihad Aljabban Michael Rohr Vincent J. Borkowski Mary Nemer Eli Cohen Naima Hashi Hisham Aljabban Emmanuel Boateng Saad Syed Mohammed Mohammed Ali Mukhtar Dexter Hadley Maryam Panahiazar |
author_facet | Jihad Aljabban Michael Rohr Vincent J. Borkowski Mary Nemer Eli Cohen Naima Hashi Hisham Aljabban Emmanuel Boateng Saad Syed Mohammed Mohammed Ali Mukhtar Dexter Hadley Maryam Panahiazar |
author_sort | Jihad Aljabban |
collection | DOAJ |
description | Background: Crohn's Disease (CD) is an inflammatory disease of the gastrointestinal tract that affects millions of patients. While great strides have been made in treatment, namely in biologic therapy such as anti-TNF drugs, CD remains a significant health burden. Method: We conducted two meta-analyses using our STARGEO platform to tag samples from Gene Expression Omnibus. One analysis compares inactive colonic biopsies from CD patients to colonic biopsies from healthy patients as a control and the other compares colonic biopsies from active CD lesions to inactive lesions. Separate tags were created to tag colonic samples from inflamed biopsies (total of 65 samples) and quiescent tissue in CD patients (total of 39 samples), and healthy tissue from non-CD patients (total of 30 samples). Results from the two meta-analyses were analyzed using Ingenuity Pathway Analysis. Results: For the inactive CD vs healthy tissue analysis, we noted FXR/RXR and LXR/RXR activation, superpathway of citrulline metabolism, and atherosclerosis signaling as top canonical pathways. The top upstream regulators include genes implicated in innate immunity, such as TLR3 and HNRNPA2B1, and sterol regulation through SREBF2. In addition, the sterol regulator SREBF2, lipid metabolism was the top disease network identified in IPA (Fig. 1). Top upregulated genes hold implications in innate immunity (DUOX2, REG1A/1B/3A) and cellular transport and absorption (ABCG5, NPC1L1, FOLH1, and SLC6A14). Top downregulated genes largely held roles in cell adhesion and integrity, including claudin 8, PAQR5, and PRKACB.For the active vs inactive CD analysis, we found immune cell adhesion and diapedesis, hepatic fibrosis/hepatic stellate cell activation, LPS/IL-1 inhibition of RXR function, and atherosclerosis as top canonical pathways. Top upstream regulators included inflammatory mediators LPS, TNF, IL1B, and TGFB1. Top upregulated genes function in the immune response such as IL6, CXCL1, CXCR2, MMP1/7/12, and PTGS2. Downregulated genes dealt with cellular metabolism and transport such as CPO, RBP2, G6PC, PCK1, GSTA1, and MEP1B. Conclusion: Our results build off established and recently described research in the field of CD. We demonstrate the use of our user-friendly platform, STARGEO, in investigating disease and finding therapeutic avenues. |
first_indexed | 2024-04-11T04:59:40Z |
format | Article |
id | doaj.art-3c6f74dc15c54fb1af07f5af121c6bb6 |
institution | Directory Open Access Journal |
issn | 2153-3539 |
language | English |
last_indexed | 2024-04-11T04:59:40Z |
publishDate | 2022-01-01 |
publisher | Elsevier |
record_format | Article |
series | Journal of Pathology Informatics |
spelling | doaj.art-3c6f74dc15c54fb1af07f5af121c6bb62022-12-26T04:08:35ZengElsevierJournal of Pathology Informatics2153-35392022-01-0113100094Probing predilection to Crohn's disease and Crohn's disease flares: A crowd-sourced bioinformatics approachJihad Aljabban0Michael Rohr1Vincent J. Borkowski2Mary Nemer3Eli Cohen4Naima Hashi5Hisham Aljabban6Emmanuel Boateng7Saad Syed8Mohammed Mohammed9Ali Mukhtar10Dexter Hadley11Maryam Panahiazar12University of Wisconsin Hospitals and Clinics, Madison, WI, United States; Corresponding author.University of Central Florida College of Medicine, Orlando, FL, United StatesUniversity of Wisconsin Hospitals and Clinics, Madison, WI, United States; University of Wisconsin Hospitals and Clinics, Madison, WI, United StatesUniversity of Wisconsin Hospitals and Clinics, Madison, WI, United States; University of Wisconsin Hospitals and Clinics, Madison, WI, United StatesVanderbilt University Medical Center, Nashville, TN, United StatesMayo Clinic Minnesota, Rochester, MN, United StatesBarry University, Miami Shores, FL, United StatesVanderbilt University Medical Center, Nashville, TN, United StatesNorthwestern Memorial Hospital, Chicago, IL, United StatesWindsor University School of Medicine, Saint Ketts and Nevis, CayonColumbia University Vagelos College of Physicians and Surgeons, New York, NY, United StatesUniversity of Central Florida College of Medicine, Orlando, FL, United StatesUniversity of California San Francisco, San Francisco, CA, United StatesBackground: Crohn's Disease (CD) is an inflammatory disease of the gastrointestinal tract that affects millions of patients. While great strides have been made in treatment, namely in biologic therapy such as anti-TNF drugs, CD remains a significant health burden. Method: We conducted two meta-analyses using our STARGEO platform to tag samples from Gene Expression Omnibus. One analysis compares inactive colonic biopsies from CD patients to colonic biopsies from healthy patients as a control and the other compares colonic biopsies from active CD lesions to inactive lesions. Separate tags were created to tag colonic samples from inflamed biopsies (total of 65 samples) and quiescent tissue in CD patients (total of 39 samples), and healthy tissue from non-CD patients (total of 30 samples). Results from the two meta-analyses were analyzed using Ingenuity Pathway Analysis. Results: For the inactive CD vs healthy tissue analysis, we noted FXR/RXR and LXR/RXR activation, superpathway of citrulline metabolism, and atherosclerosis signaling as top canonical pathways. The top upstream regulators include genes implicated in innate immunity, such as TLR3 and HNRNPA2B1, and sterol regulation through SREBF2. In addition, the sterol regulator SREBF2, lipid metabolism was the top disease network identified in IPA (Fig. 1). Top upregulated genes hold implications in innate immunity (DUOX2, REG1A/1B/3A) and cellular transport and absorption (ABCG5, NPC1L1, FOLH1, and SLC6A14). Top downregulated genes largely held roles in cell adhesion and integrity, including claudin 8, PAQR5, and PRKACB.For the active vs inactive CD analysis, we found immune cell adhesion and diapedesis, hepatic fibrosis/hepatic stellate cell activation, LPS/IL-1 inhibition of RXR function, and atherosclerosis as top canonical pathways. Top upstream regulators included inflammatory mediators LPS, TNF, IL1B, and TGFB1. Top upregulated genes function in the immune response such as IL6, CXCL1, CXCR2, MMP1/7/12, and PTGS2. Downregulated genes dealt with cellular metabolism and transport such as CPO, RBP2, G6PC, PCK1, GSTA1, and MEP1B. Conclusion: Our results build off established and recently described research in the field of CD. We demonstrate the use of our user-friendly platform, STARGEO, in investigating disease and finding therapeutic avenues.http://www.sciencedirect.com/science/article/pii/S2153353922006605Crohn's diseaseInflammatory bowel diseaseBioinformaticsPathologyGenomics |
spellingShingle | Jihad Aljabban Michael Rohr Vincent J. Borkowski Mary Nemer Eli Cohen Naima Hashi Hisham Aljabban Emmanuel Boateng Saad Syed Mohammed Mohammed Ali Mukhtar Dexter Hadley Maryam Panahiazar Probing predilection to Crohn's disease and Crohn's disease flares: A crowd-sourced bioinformatics approach Journal of Pathology Informatics Crohn's disease Inflammatory bowel disease Bioinformatics Pathology Genomics |
title | Probing predilection to Crohn's disease and Crohn's disease flares: A crowd-sourced bioinformatics approach |
title_full | Probing predilection to Crohn's disease and Crohn's disease flares: A crowd-sourced bioinformatics approach |
title_fullStr | Probing predilection to Crohn's disease and Crohn's disease flares: A crowd-sourced bioinformatics approach |
title_full_unstemmed | Probing predilection to Crohn's disease and Crohn's disease flares: A crowd-sourced bioinformatics approach |
title_short | Probing predilection to Crohn's disease and Crohn's disease flares: A crowd-sourced bioinformatics approach |
title_sort | probing predilection to crohn s disease and crohn s disease flares a crowd sourced bioinformatics approach |
topic | Crohn's disease Inflammatory bowel disease Bioinformatics Pathology Genomics |
url | http://www.sciencedirect.com/science/article/pii/S2153353922006605 |
work_keys_str_mv | AT jihadaljabban probingpredilectiontocrohnsdiseaseandcrohnsdiseaseflaresacrowdsourcedbioinformaticsapproach AT michaelrohr probingpredilectiontocrohnsdiseaseandcrohnsdiseaseflaresacrowdsourcedbioinformaticsapproach AT vincentjborkowski probingpredilectiontocrohnsdiseaseandcrohnsdiseaseflaresacrowdsourcedbioinformaticsapproach AT marynemer probingpredilectiontocrohnsdiseaseandcrohnsdiseaseflaresacrowdsourcedbioinformaticsapproach AT elicohen probingpredilectiontocrohnsdiseaseandcrohnsdiseaseflaresacrowdsourcedbioinformaticsapproach AT naimahashi probingpredilectiontocrohnsdiseaseandcrohnsdiseaseflaresacrowdsourcedbioinformaticsapproach AT hishamaljabban probingpredilectiontocrohnsdiseaseandcrohnsdiseaseflaresacrowdsourcedbioinformaticsapproach AT emmanuelboateng probingpredilectiontocrohnsdiseaseandcrohnsdiseaseflaresacrowdsourcedbioinformaticsapproach AT saadsyed probingpredilectiontocrohnsdiseaseandcrohnsdiseaseflaresacrowdsourcedbioinformaticsapproach AT mohammedmohammed probingpredilectiontocrohnsdiseaseandcrohnsdiseaseflaresacrowdsourcedbioinformaticsapproach AT alimukhtar probingpredilectiontocrohnsdiseaseandcrohnsdiseaseflaresacrowdsourcedbioinformaticsapproach AT dexterhadley probingpredilectiontocrohnsdiseaseandcrohnsdiseaseflaresacrowdsourcedbioinformaticsapproach AT maryampanahiazar probingpredilectiontocrohnsdiseaseandcrohnsdiseaseflaresacrowdsourcedbioinformaticsapproach |