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TUG1 and H19 lncRNAs Can Predict Anti-TNF Unresponsiveness in Patients With Ulcerative Colitis: A Machine

Raheleh Heydari¹, Mohammad Javad Tavassolifar¹, Mohammad Hossein Derakhshan Nazari¹

¹Basic and Molecular Epidemiology of Gastrointestinal Disorders Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran, sbmu.ac.ir.

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Summary

This summary is machine-generated.

Long noncoding RNAs (lncRNAs), specifically H19 and TUG1, show distinct expression patterns in ulcerative colitis (UC) patients. These lncRNAs can serve as biomarkers to monitor disease activity and predict response to anti-tumor necrosis factor (TNF)-α therapy.

Keywords:

H19 TUG1 anti-TNF-α therapy long noncoding RNA ulcerative colitis

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Published on: September 12, 2019

Area of Science:

Molecular Biology
Gastroenterology
Immunology

Background:

Ulcerative colitis (UC) is a chronic inflammatory bowel disease.
Predicting response to anti-tumor necrosis factor (TNF)-α therapy remains a clinical challenge.
Long noncoding RNAs (lncRNAs) are increasingly recognized for their roles in disease pathogenesis.

Purpose of the Study:

To investigate the association of lncRNAs with inflammation and disease activity in UC.
To evaluate the potential of lncRNAs as biomarkers for predicting response to anti-TNF therapy in UC patients.

Main Methods:

Analysis of lncRNA expression (H19 and TUG1) in whole blood and inflamed biopsies from UC patients (discovery and validation cohorts).
Monitoring of disease activity using colonoscopy, histopathology, and clinical symptoms.
Application of machine learning and ROC curve analysis for predictive performance assessment.

Main Results:

H19 expression was higher in nonresponders compared to responders, and correlated with disease activity markers (ESR, CRP).
H19 and TUG1 demonstrated strong predictive performance for anti-TNF response in both tissue and blood samples.
Expression patterns were validated in an independent cohort, confirming high predictive accuracy.

Conclusions:

lncRNAs, particularly H19 and TUG1, exhibit distinct expression profiles in UC patients.
These lncRNAs hold significant potential as biomarkers for monitoring UC disease activity.
lncRNAs can accurately predict treatment response to anti-TNF therapy in UC, aiding personalized medicine approaches.