Abstract

Non-steroidal anti-inflammatory drugs (NSAIDs) are among the most frequently used classes of medications in the world, yet they induce an enteropathy that is associated with high morbidity and mortality. A major limitation to better understanding the pathophysiology and diagnosis of this enteropathy is the difficulty of obtaining information about the primary site of injury, namely the distal small intestine. We investigated the utility of using mRNA from exfoliated cells in stool as a means to surveil the distal small intestine in a murine model of NSAID enteropathy. Specifically, we performed RNA-Seq on exfoliated cells found in feces and compared these data to RNA-Seq from both the small intestinal mucosa and colonic mucosa of healthy control mice or those exhibiting NSAID-induced enteropathy. Global gene expression analysis, data intersection, pathway analysis, and computational approaches including linear discriminant analysis (LDA) and sparse canonical correlation analysis (CCA) were used to assess the inter-relatedness of tissue (invasive) and stool (noninvasive) datasets. These analyses revealed that the exfoliated cell transcriptome closely mirrored the transcriptome of the small intestinal mucosa. Thus, the exfoliome may serve as a non-invasive means of detecting and monitoring NSAID enteropathy (and possibly other gastrointestinal mucosal inflammatory diseases).

Details

Title
The non-invasive exfoliated transcriptome (exfoliome) reflects the tissue-level transcriptome in a mouse model of NSAID enteropathy
Author
Whitfield-Cargile, Canaan M 1 ; Cohen, Noah D 2   VIAFID ORCID Logo  ; He, Kejun 3 ; Ivanov, Ivan 4 ; Goldsby, Jennifer S 5 ; Chamoun-Emanuelli, Ana 1 ; Weeks, Brad R 6 ; Davidson, Laurie A 5 ; Chapkin, Robert S 5 

 Department of Large Animal Clinical Sciences, College of Veterinary Medicine & Biomedical Sciences, Texas A&M University, College Station, Texas, United States of America 
 Department of Large Animal Clinical Sciences, College of Veterinary Medicine & Biomedical Sciences, Texas A&M University, College Station, Texas, United States of America; Center for Translational Environmental Health Research, Texas A&M University, College Station, Texas, USA 
 Department of Statistics, College of Science, Texas A&M University, College Station, Texas, USA; Institute of Statistics and Big Data, Renmin University of China, Beijing, China 
 Department of Veterinary Physiology and Pharmacology, College of Veterinary Medicine & Biomedical Sciences, Texas A&M University, College Station, Texas, USA; Center for Translational Environmental Health Research, Texas A&M University, College Station, Texas, USA 
 Program in Integrative Nutrition & Complex Diseases, College of Agriculture and Life Sciences, Texas A&M University, College Station, Texas, USA; Center for Translational Environmental Health Research, Texas A&M University, College Station, Texas, USA 
 Department of Veterinary Pathobiology, College of Veterinary Medicine & Biomedical Sciences, Texas A&M University, College Station, Texas, USA 
Pages
1-13
Publication year
2017
Publication date
Oct 2017
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1958553814
Copyright
© 2017. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.