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Bioinformatics approach to identify the hub gene associated with COVID-19 and idiopathic pulmonary fibrosis

Wenchao Shi1, Tinghui Li2, Huiwen Li3

  • 1Department of Respiration, The Fourth Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin, Heilongjiang, China.

IET Systems Biology
|October 10, 2023
PubMed

Insights

This study identifies six genes, including S100A8, linked to severe COVID-19 and pulmonary fibrosis. A predictive model using these genes aids in assessing patient prognosis and suggests therapeutic targets.

Area of Science:

  • Bioinformatics
  • Genomics
  • Pulmonary Medicine

Background:

  • Coronavirus disease 2019 (COVID-19) is a global health crisis.
  • Pulmonary fibrosis is a significant complication of SARS-CoV-2 infection.
  • Understanding COVID-19's long-term effects like pulmonary fibrosis is crucial.

Purpose of the Study:

  • To identify key genes associated with pulmonary fibrosis in severe COVID-19 patients.
  • To develop a predictive model for assessing prognosis in SARS-CoV-2 infected individuals.
  • To explore potential therapeutic targets for COVID-19-related pulmonary fibrosis.

Main Methods:

  • Utilized Gene Expression Omnibus datasets for COVID-19 and idiopathic pulmonary fibrosis.
  • Employed the Random Forest algorithm to screen for hub genes based on disease severity.
  • Developed and validated a risk prediction model using a neural network approach.

Main Results:

  • Identified six candidate genes (NELL2, GPR183, S100A8, ALPL, CD177, IL1R2) potentially involved in pulmonary fibrosis development in severe COVID-19.
  • Highlighted S100A8 as a key gene strongly associated with both COVID-19 and pulmonary fibrosis.
  • Successfully constructed a neural network model for predicting COVID-19 patient prognosis.

Conclusions:

  • Bioinformatic analysis can identify predictive biomarkers for COVID-19 complications.
  • The identified genes offer potential targets for diagnosing and treating COVID-19-associated pulmonary fibrosis.
  • This research provides insights for developing targeted therapies and vaccines.

Keywords:
big databioinformatics

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