# Identification of Endoplasmic Reticulum Stress-Related Biomarkers in Coronary Artery Disease

## TL;DR

This study identifies eight endoplasmic reticulum stress-related genes as potential biomarkers for diagnosing coronary artery disease and explores their immune-related functions.

## Contribution

The study introduces eight novel ERS-related biomarkers for CAD, validated through bioinformatics and qRT-PCR, with implications for diagnosis and treatment.

## Key findings

- Eight ERS-related genes (RCN2, HRC, DERL2, RNF183, CRH, TMED2, PPP1R15A, and IL1A) were validated as CAD biomarkers.
- Seven of the eight biomarkers showed strong diagnostic potential in ROC analysis.
- Biomarkers were linked to immune cell activity and chemokine interactions, offering new therapeutic insights.

## Abstract

Coronary artery disease (CAD) is caused by atherosclerotic lesions in the coronary vessels. Endoplasmic reticulum stress (ERS) acts in cardiovascular disease, and its role in CAD is not clear. A total of 13 differentially expressed ERS-related genes (DEERSRGs) in CAD were identified. Functional enrichment analysis demonstrated the DEERSRGs were mainly enriched in endoplasmic reticulum (ER)-related pathways. Then, eight genes (RCN2, HRC, DERL2, RNF183, CRH, TMED2, PPP1R15A, and IL1A) were authenticated as ERS-related biomarkers in CAD by least absolute shrinkage and selection operator (LASSO). The receiver operating characteristic (ROC) analysis showed that the LASSO logistic model constructed based on biomarkers had a better diagnostic effect, which was confirmed by the ANN and GSE23561 datasets. Also, ROC results showed that seven of the eight biomarkers had better diagnostic effects. The nomogram model had good predictive power, and biomarkers were mostly enriched in pathways associated with CAD. The biomarkers were significantly associated with 10 immune cells, and RCN2, DERL2, TMED2, and RNF183 were negatively correlated with most chemokines. Eight biomarkers had significant correlations with both immunoinhibitors and immunostimulators. In addition, eight biomarkers were significantly different in both CAD and control samples, CRH and HRC were upregulated in CAD. The quantitative reverse transcription-polymerase chain reaction (qRT-PCR) showed that RCN2, HRC, DERL2, CRH, and IL1A were consistent with the bioinformatics analysis. RCN2, HRC, DERL2, RNF183, CRH, TMED2, PPP1R15A, and IL1A were identified as biomarkers of CAD. Functional enrichment analysis and immunoassays for biomarkers provide new ideas for the treatment of CAD.