| Literature DB >> 32009179 |
Petr Jabandziev1,2, Julia Bohosova2, Tereza Pinkasova1, Lumir Kunovsky3,4, Ondrej Slaby2, Ajay Goel5.
Abstract
Prevalence of inflammatory bowel disease (IBD), a chronic inflammatory disorder of the gut, has been on the rise in recent years-not only in the adult population but also especially in pediatric patients. Despite the absence of curative treatments, current therapeutic options are able to achieve long-term remission in a significant proportion of cases. To this end, however, there is a need for biomarkers enabling accurate diagnosis, prognosis, and prediction of response to therapies to facilitate a more individualized approach to pediatric IBD patients. In recent years, evidence has continued to evolve concerning noncoding RNAs (ncRNAs) and their roles as integral factors in key immune-related cellular pathways. Specific deregulation patterns of ncRNAs have been linked to pathogenesis of various diseases, including pediatric IBD. In this article, we provide an overview of current knowledge on ncRNAs, their altered expression profiles in pediatric IBD patients, and how these are emerging as potentially valuable clinical biomarkers as we enter an era of personalized medicine.Entities:
Keywords: Crohn’s disease; inflammatory bowel disease; microRNA; noncoding RNA; pediatrics; ulcerative colitis
Year: 2020 PMID: 32009179 PMCID: PMC7301403 DOI: 10.1093/ibd/izaa009
Source DB: PubMed Journal: Inflamm Bowel Dis ISSN: 1078-0998 Impact factor: 5.325
Summary of Tissue ncRNAs Associated With Various Aspects of Pediatric IBD
| Study | ncRNA | Change in expression (patients) | Compared groups | Number of patients, sample type | Statistical parameters | Technological platform | ||
|---|---|---|---|---|---|---|---|---|
| Best | AUC | Sensitivity/ Specificity (%) | ||||||
| Koukos et al., 2013 [ | miR-101 | Down | IBD vs. non-IBD | 45 biopsies | — | — | — | MicroRNA-library screen, RT-qPCR |
| miR-26 | Down | — | ||||||
| miR-124 | Down | pUC vs. pCD/non-IBD | <0.0001/<0.01 | |||||
| Koukos et al., 2015 [ | miR-4284 | Down | pIBD vs. non-IBD | 37 biopsies | <0.05 | — | — | mirCURY microRNA array, RT-qPCR |
| Zahm et al., 2014 [ | miR-192 miR-194 miR-200b miR-375 | Down | pUC vs. controls | 50 biopsies | 0.0006 0.0019 0.0056 0.0001 | — | — | nCounter, TaqMan low density array, RT-qPCR |
| miR-142-3p miR-146a miR-21 let-7i | Up | 0.0048 0.0027 0.0003 0.0007 | — | — | ||||
| miR-24 | — | pUC vs. pCD | — | 0.83 | 83.3/85.7 | |||
| Béres et al., 2016 [ | miR-122 miR-146a miR-155 | Up Up UP | ipCD vs. C/pUC pUC vs. C ipCD vs. C | 28 FF samples, 71 FFPE samples | <0.01 <0.001 <0.001 | — | — | RT-qPCR |
| Szűcs et al., 2016 [ | miR-146a miR-155 | Up | ipCD vs. inpCD vs. C | 30 FFPE samples | <0.001 | — | — | RT-qPCR |
| Béres et al., 2017 [ | miR-185 miR-223 | Up | ipCD vs. C | 44 FF samples | <0.05 <0.001 | 0.81 1 | 62.5/100 100/100 | NGS, RT-qPCR |
| miR-146a miR-142–3p | — | pCD vs. pUC | <0.01 <0.01 | 0.838 0.888 | 80/76.92 77.78/90.31 | |||
| Tang et al., 2018 [ | miR-15a | Down | CDre vs. CDac | 54 FF samples | <0.05 | — | — | RT-qPCR |
Abbreviations: AUC, area under the curve; C, control; FFPE, formalin-fixed paraffin-embedded; CDac, active Crohn’s disease; CDre, Crohn’s disease in remission; FF, fresh frozen tissue; ipCD, histologically intact tissue of pediatric patients with Crohn’s disease; inpCD, histologically inflamed tissue of pediatric patients with Crohn’s disease; NGS, next-generation sequencing; pCD, pediatric patients with Crohn’s disease; pIBD, pediatric patients with inflammatory bowel disease; pUC, pediatric patients with ulcerative colitis; non-IBD, control patients without inflammation typical for IBD; RT-qPCR, real-time quantitative polymerase chain reaction.
Serum ncRNAs With Successfully Validated Biomarker Potential for Various Aspects of Pediatric IBD
| Study | ncRNA | Change in expression (patients) | Compared groups | Number of patients, sample type | Statistical parameters | Technological platform | |||
|---|---|---|---|---|---|---|---|---|---|
| Best | AUC | Sensitivity/ Specificity (%) | |||||||
| Zahm et al., 2011[ | miR-484 miR-16 | Up | pCD vs. control vs. celiac | 102 blood serum samples | <0.0001 | 0.917 0.912 | 82.61/84.38 73.91/100 | TaqMan human microRNA array, RT-qPCR | |
| Zahm et al., 2014[ | miR-192 miR-142–3p miR-21 | Up | pUC vs. control | 47 blood serum samples | 0.0045 0.0078 — | 0.757 0.723 0.718 | 79.31/77.78 75.86/66.67 75.86/66.67 | TaqMan low density array human microRNA panel, RT-qPCR | |
| Heier et al., 2016[ | miR-146a miR-146b miR-320 miR-486 | Down | pIBD pharmaco-dynamics | 19 PBMC samples | <0.05 <0.01 <0.01 <0.01 | — | — | RT-qPCR | |
| De Iucidibus et al., 2018[ | miR-29c-3p | Up | pIBD pharmaco-dynamics | 10 PBMC samples | <0.01 | — | — | NGS, RT-qPCR | |
| Lucafò et al., 2018[ | GAS5 | Up | pIBD pharmaco-dynamics | 19 PBMC samples | <0.05 | — | — | RT-qPCR |
Abbreviations: AUC, area under the curve; C, control; GAS5, growth arrest-specific transcript 5; NGS, next-generation sequencing; PBMC, peripheral blood mononuclear cells; pCD, pediatric patients with Crohn’s disease; pIBD, pediatric patients with inflammatory bowel disease; pUC, pediatric patients with ulcerative colitis; RT-qPCR, real-time quantitative polymerase chain reaction.
FIGURE 1.Tissue miRNAs involved in the development of pediatric IBD (modified from Park et al., 2017).[107]Abbreviations: TLR, toll-like receptor; TNF, tumor necrosis factor; ANCA, anti-neutrophil cytoplasmic antibodies; IFN, interferon; TIMP, tissue inhibitor of metalloproteinases; MMP, matrix metalloproteinase; Bcl2, B-cell lymphoma 2; BAX, BCL2 associated X; CCL, CC chemokine ligand; CCR, CC chemokine receptor; ompC, outer membrane protein C precursor.