Long non-coding RNAs in biomarking COVID-19: a machine learning-based approach.

Journal: Virology journal
PMID: 38849961

Abstract

BACKGROUND: The coronavirus pandemic that started in 2019 has caused the highest mortality and morbidity rates worldwide. Data on the role of long non-coding RNAs (lncRNAs) in coronavirus disease 2019 (COVID-19) is scarce. We aimed to elucidate the relationship of three important lncRNAs in the inflammatory states, H19, taurine upregulated gene 1 (TUG1), and colorectal neoplasia differentially expressed (CRNDE) with key factors in inflammation and fibrosis induction including signal transducer and activator of transcription3 (STAT3), alpha smooth muscle actin (α-SMA), tumor necrosis factor-alpha (TNF-α), and interleukin-6 (IL-6) in COVID-19 patients with moderate to severe symptoms.

Authors

  • Raheleh Heydari
    Basic and Molecular Epidemiology of Gastrointestinal Disorders Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Mohammad Javad Tavassolifar
    Basic and Molecular Epidemiology of Gastrointestinal Disorders Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Sara Fayazzadeh
    Bioinformatics and Computational Omics Lab (BioCOOL), Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran.
  • Omid Sadatpour
    Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
  • Anna Meyfour
    Basic and Molecular Epidemiology of Gastrointestinal Disorders Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran. a.meyfour@gmail.com.

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