Scientific Reports (Sep 2023)

Exploring shared pathways and the shared biomarker ERRFI1 in Obstructive sleep apnoea and atherosclerosis using integrated bioinformatics analysis

  • Bowen Chen,
  • Liping Dong,
  • Jihua Zhang,
  • Ying Hao,
  • Weiwei Chi,
  • Dongmei Song

DOI
https://doi.org/10.1038/s41598-023-42184-0
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 14

Abstract

Read online

Abstract Obstructive sleep apnea (OSA) is an upper airway disorder occurring during sleep and is associated with atherosclerosis (AS). AS is a cardiovascular disease caused by environmental and genetic factors, with a high global mortality rate. This study investigated common pathways and potential biomarkers of OSA and AS. Microarray data were downloaded from the Gene Expression Omnibus (GEO) database and used to screen for differentially expressed genes (DEGs) in the OSA and AS datasets. A weighted gene co-expression network analysis (WGCNA) was used to identify the co-expression modules of OSA and AS. The least absolute shrinkage and selection operators (LASSO) were used to determine critical biomarkers. Immune cell infiltration analysis was used to investigate the correlation between immune cell infiltration and common biomarkers of OSA and AS. Results revealed that differentially expressed genes may be involved in inflammatory processes, chemokine signaling pathways, and molecular changes in cell adhesion. ERBB receptor feedback inhibitor 1 (ERRFI1) was the best-shared biomarker for OSA and AS. Immune infiltration analysis showed that ERRFI1 expression was correlated with immune cell changes. Changes in immune pathways, inflammatory processes, and cell adhesion molecules may underlie the pathogenesis of both diseases, and ERRFI1 may be a potential diagnostic marker for patients with OSA and AS.