Potential Biomarkers for Predicting the Risk of Developing Into Long COVID After COVID-19 Infection.

ABSTRACT:

Background

Long COVID, a heterogeneous condition characterized by a range of physical and neuropsychiatric presentations, can be presented with a proportion of COVID-19-infected individuals.

Methods

Transcriptomic data sets of those within gene expression profiles of COVID-19, long COVID, and healthy controls were retrieved from the GEO database. Differentially expressed genes (DEGs) falling under COVID-19 and long COVID were identified with R packages, and contemporaneously conducted module detection was performed with the Modular Pharmacology Platform (http://112.86.129.72:48081/). The integration of both DEGs and differentially expressed module-genes (DEMGs) regarding long COVID and COVID-19 was intersected by following Gene Ontology (GO), Kyoto Encyclopedia of Genes and

SUBMITTER: Hou Z 

PROVIDER: S-EPMC11760981 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature