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RNAseq Profiling of Blood from Patients with Coronary Artery Disease: Signature of a T Cell Imbalance

Abstract

Background: Cardiovascular disease had a global prevalence of 523 million cases and 18.6 million deaths in 2019. The current standard for diagnosing coronary artery disease (CAD) is coronary angiography either by invasive catheterization (ICA) or computed tomography (CTA). Prior studies employed single-molecule, amplification-independent RNA sequencing of whole blood to identify an RNA signature in patients with angiographically confirmed CAD. The present studies employed Illumina RNAseq and network co-expression analysis to identify systematic changes underlying CAD.

Methods: Whole blood RNA was depleted of ribosomal RNA (rRNA) and analyzed by Illumina total RNA sequencing (RNAseq) to identify transcripts associated with CAD in 177 patients presenting for elective invasive coronary catheterization. The resulting transcript counts were compared between groups to identify differentially expressed genes (DEGs) and to identify patterns of changes through whole genome co-expression network analysis (WGCNA).

Results: The correlation between Illumina amplified RNAseq and the prior SeqLL unamplified RNAseq was quite strong (r = 0.87), but there was only 9 % overlap in the DEGs identified. Consistent with the prior RNAseq, the majority (93 %) of DEGs were down-regulated ~1.7-fold in patients with moderate to severe CAD (>20 % stenosis). DEGs were predominantly related to T cells, consistent with known reductions in Tregs in CAD. Network analysis did not identify pre-existing modules with a strong association with CAD, but patterns of T cell dysregulation were evident. DEGs were enriched for transcripts associated with ciliary and synaptic transcripts, consistent with changes in the immune synapse of developing T cells.

Conclusions: These studies confirm and extend a novel mRNA signature of a Treg-like defect in CAD. The pattern of changes is consistent with stress-related changes in the maturation of T and Treg cells, possibly due to changes in the immune synapse.

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References
1.
From A, Kane G, Bruce C, Pellikka P, Scott C, McCully R . Characteristics and outcomes of patients with abnormal stress echocardiograms and angiographically mild coronary artery disease (<50% stenoses) or normal coronary arteries. J Am Soc Echocardiogr. 2010; 23(2):207-14. DOI: 10.1016/j.echo.2009.11.023. View

2.
Langfelder P, Horvath S . WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics. 2008; 9:559. PMC: 2631488. DOI: 10.1186/1471-2105-9-559. View

3.
Liu W, Li P, Zhan X, Qu L, Xiong T, Hou F . Identification of molecular subtypes of coronary artery disease based on ferroptosis- and necroptosis-related genes. Front Genet. 2022; 13:870222. PMC: 9531137. DOI: 10.3389/fgene.2022.870222. View

4.
Pencina M, DAgostino Sr R, Larson M, Massaro J, Vasan R . Predicting the 30-year risk of cardiovascular disease: the framingham heart study. Circulation. 2009; 119(24):3078-84. PMC: 2748236. DOI: 10.1161/CIRCULATIONAHA.108.816694. View

5.
Cheng X, Yu X, Ding Y, Fu Q, Xie J, Tang T . The Th17/Treg imbalance in patients with acute coronary syndrome. Clin Immunol. 2008; 127(1):89-97. DOI: 10.1016/j.clim.2008.01.009. View