Plasma microRNA Profile Differentiates Crohn’s Colitis From Ulcerative Colitis
Author(s) -
Uri Netz,
Jane Carter,
M. Robert Eichenberger,
Kayla Feagins,
Norman Galbraith,
Gerald W. Dryden,
Jianmin Pan,
N. Shesh,
Susan Galandiuk
Publication year - 2017
Publication title -
inflammatory bowel diseases
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.932
H-Index - 146
eISSN - 1536-4844
pISSN - 1078-0998
DOI - 10.1093/ibd/izx009
Subject(s) - ulcerative colitis , microrna , medicine , inflammatory bowel disease , crohn's disease , gastroenterology , colitis , confidence interval , disease , crohn disease , biology , gene , biochemistry
Background Inflammatory bowel disease (IBD) is commonly divided into 2 entities: Crohn’s disease (CD) and ulcerative colitis (UC). Differentiating between these entities when dealing with IBD confined to the colon is important, especially when planning surgical treatment. Due to ambiguous histological or endoscopic findings, accurate diagnosis is not possible in up to 15% of cases. The aim of this study was to determine whether plasma microRNAs (miRNAs) can help differentiate Crohn’s colitis (CC) from ulcerative colitis. Methods Patients with isolated CC and with UC were enrolled in our study from January 2010 to May 2016. Peripheral blood was collected, and total RNA was isolated from plasma. Screening was performed for 380 common miRNAs. miRNAs that were differentially expressed between these 2 groups were chosen, and their differential expression was confirmed using single miRNA assays in a larger sample size. A predictive model was generated using these data. Significantly differentially expressed miRNAs were then validated utilizing the predictive model to assess blinded data from the single assays. Results Screening was performed on 8 patients from each group. Seven differentially expressed miRNAs were chosen for single assay confirmation. Two miRNAs (miR-598, miR-642) were consistently different between the patient groups (P = 0.013, P = 0.005). Using blinded data, these 2 miRNAs were validated using the predictive model, achieving an overall accuracy of 75% (95% confidence interval, 40.7–92.9). Conclusions We identified 2 plasma miRNAs that differentiated CC from UC. Our data indicate the promise and feasibility of a plasma miRNA–based assay to distinguish between these 2 conditions.
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