Evidence mapPaperPMID 37303712Full record

ArticleJournal of molecular and cellular cardiology plus2023

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

Timothy A McCaffrey, Ian Toma, Zhaoqing Yang, Richard Katz, Jonathan Reiner, Ramesh Mazhari, Palak Shah, Zachary Falk, Richard Wargowsky, Jennifer Goldman and 8 more

Open access · diamondAbstract read
In one paragraph

Article in Journal of molecular and cellular cardiology plus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors at 4 institutions in 2 countries.

Timothy A McCaffreyDepartment of Medicine, Division of Genomic Medicine, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Ian TomaDepartment of Medicine, Division of Genomic Medicine, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Zhaoqing YangDepartment of Medicine, Division of Genomic Medicine, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Richard KatzDepartment of Medicine, Division of Cardiology, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Jonathan ReinerDepartment of Medicine, Division of Cardiology, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Ramesh MazhariDepartment of Medicine, Division of Cardiology, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Palak ShahINOVA Heart and Vascular Institute, 3300 Gallows Road, Fairfax, VA 22042, United States of America.
Zachary FalkDepartment of Medicine, Division of Genomic Medicine, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Richard WargowskyDepartment of Medicine, Division of Genomic Medicine, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Jennifer GoldmanDepartment of Medicine, Division of Genomic Medicine, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Dan JonesSeqLL, Inc., 3 Federal Street, Billerica, MA 01821, United States of America.
Dmitry ShtokaloThe St. Laurent Institute, 317 New Boston Street, Woburn, MA 01801, United States of America.
Denis AntonetsThe St. Laurent Institute, 317 New Boston Street, Woburn, MA 01801, United States of America.
Tisha JepsonDepartment of Medicine, Division of Genomic Medicine, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Anastasia FetisovaDepartment of Medicine, Division of Genomic Medicine, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Kevin JaatinenDepartment of Medicine, Division of Genomic Medicine, The George Washington University, 2300 I Street NW, Washington, DC 20037, United States of America.
Natalia ReeCenter for Mitochondrial Functional Genomics, Institute of Living Systems, Immanuel Kant Baltic Federal University, Kalingrad 236040, Russia.
Maxim RiThe St. Laurent Institute, 317 New Boston Street, Woburn, MA 01801, United States of America.
George Washington University · USSt. Laurent Institute · USImmanuel Kant Baltic Federal University · RUSiberian Branch of the Russian Academy of Sciences · RU

Funding

NCATS NIH HHS UL1 TR001876NIH HHS S10 OD021622
6 · The paper itself

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.

Indexed as

AtherosclerosisCiliaCoronary artery diseaseImmune synapseNetwork analysisRegulatory T cellsRNA sequencingTranscriptomeTreg

Identifiers

PMID37303712
PMCPMC10256136
OpenAlexW4360954186

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.