RNAseq profiling of blood from patients with coronary artery disease: Signature of a T cell imbalance

Timothy A. McCaffrey, Department of Medicine, Division of Genomic Medicine, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Ian Toma, Department of Medicine, Division of Genomic Medicine, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Zhaoqing Yang, Department of Medicine, Division of Genomic Medicine, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Richard Katz, Department of Medicine, Division of Cardiology, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Jonathan Reiner, Department of Medicine, Division of Cardiology, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Ramesh Mazhari, Department of Medicine, Division of Cardiology, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Palak Shah, INOVA Heart and Vascular Institute, 3300 Gallows Road, Fairfax, VA 22042, United States of America.
Zachary Falk, Department of Medicine, Division of Genomic Medicine, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Richard Wargowsky, Department of Medicine, Division of Genomic Medicine, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Jennifer Goldman, Department of Medicine, Division of Genomic Medicine, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Dan Jones, SeqLL, Inc., 3 Federal Street, Billerica, MA 01821, United States of America.
Dmitry Shtokalo, The St. Laurent Institute, 317 New Boston Street, Woburn, MA 01801, United States of America.
Denis Antonets, The St. Laurent Institute, 317 New Boston Street, Woburn, MA 01801, United States of America.
Tisha Jepson, Department of Medicine, Division of Genomic Medicine, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Anastasia Fetisova, Department of Medicine, Division of Genomic Medicine, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Kevin Jaatinen, Department of Medicine, Division of Genomic Medicine, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Natalia Ree, Center for Mitochondrial Functional Genomics, Institute of Living Systems, Immanuel Kant Baltic Federal University, Kalingrad 236040, Russia.
Maxim Ri, The St. Laurent Institute, 317 New Boston Street, Woburn, MA 01801, United States of America.

Document Type

Journal Article

Publication Date

6-1-2023

Journal

Journal of molecular and cellular cardiology plus

Volume

4

DOI

10.1016/j.jmccpl.2023.100033

Keywords

Atherosclerosis; Cilia; Coronary artery disease; Immune synapse; Network analysis; RNA sequencing; Regulatory T cells; Transcriptome; Treg

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.

Department

Medicine

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