Literature DB >> 23188564

Transcriptome analysis in patients with progressive coronary artery disease: identification of differential gene expression in peripheral blood.

Thomas G Nührenberg1, Nicole Langwieser, Harald Binder, Thorsten Kurz, Christian Stratz, Rolf-Peter Kienzle, Dietmar Trenk, Dietlind Zohlnhöfer-Momm, Franz-Josef Neumann.   

Abstract

Inflammation as a systemic process plays a central role in atherosclerotic plaque progression (PP). Here we investigated other systemic correlates of PP by global gene expression profiling (GEP) in peripheral blood. From a database of 45,727 coronary angiograms, we identified two patient groups with good risk factor control, but different clinical evolution: First, 16 patients had significant PP leading to repeated coronary interventions, and second, 16 patients had angiographically documented stable courses. GEP revealed 93 differentially expressed genes, of which 23 have unknown function. Among the remaining 70 genes, 10 were associated with progenitor and pluripotent cells, but only three genes with atherosclerosis. We developed a risk prediction gene signature by a multivariable statistical model integrating comprehensive laboratory and clinical patient data. This signature identified PP with high sensitivity and specificity for new patients, as estimated by resampling techniques. GEP results were validated by qPCR for ANK2 and GSTT1.

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Year:  2012        PMID: 23188564     DOI: 10.1007/s12265-012-9420-5

Source DB:  PubMed          Journal:  J Cardiovasc Transl Res        ISSN: 1937-5387            Impact factor:   4.132


  30 in total

1.  Gene profiling identifies secreted protein transcripts from peripheral blood cells in coronary artery disease.

Authors:  Jun Ma; Choong-Chin Liew
Journal:  J Mol Cell Cardiol       Date:  2003-08       Impact factor: 5.000

2.  A reporting system on patients evaluated for coronary artery disease. Report of the Ad Hoc Committee for Grading of Coronary Artery Disease, Council on Cardiovascular Surgery, American Heart Association.

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Review 3.  The peripheral-blood transcriptome: new insights into disease and risk assessment.

Authors:  Steve Mohr; Choong-Chin Liew
Journal:  Trends Mol Med       Date:  2007-10-04       Impact factor: 11.951

4.  Circulating transcriptome reveals markers of atherosclerosis.

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Journal:  Proc Natl Acad Sci U S A       Date:  2005-02-22       Impact factor: 11.205

5.  Mammalian Gcm genes induce Hes5 expression by active DNA demethylation and induce neural stem cells.

Authors:  Seiji Hitoshi; Yugo Ishino; Akhilesh Kumar; Salma Jasmine; Kenji F Tanaka; Takeshi Kondo; Shigeaki Kato; Toshihiko Hosoya; Yoshiki Hotta; Kazuhiro Ikenaka
Journal:  Nat Neurosci       Date:  2011-07-17       Impact factor: 24.884

6.  Reduced number of circulating endothelial progenitor cells predicts future cardiovascular events: proof of concept for the clinical importance of endogenous vascular repair.

Authors:  Caroline Schmidt-Lucke; Lothar Rössig; Stephan Fichtlscherer; Mariuca Vasa; Martina Britten; Ulrike Kämper; Stefanie Dimmeler; Andreas M Zeiher
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Review 7.  Pathophysiology of coronary artery disease.

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8.  Cluster analysis and display of genome-wide expression patterns.

Authors:  M B Eisen; P T Spellman; P O Brown; D Botstein
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9.  Efficacy and safety of more intensive lowering of LDL cholesterol: a meta-analysis of data from 170,000 participants in 26 randomised trials.

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10.  GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists.

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  13 in total

Review 1.  Transcriptomic Signature of Atherosclerosis in the Peripheral Blood: Fact or Fiction?

Authors:  Hsiao-Huei Chen; Alexandre F R Stewart
Journal:  Curr Atheroscler Rep       Date:  2016-12       Impact factor: 5.113

Review 2.  Analysis of the transcriptome in molecular epidemiology studies.

Authors:  Cliona M McHale; Luoping Zhang; Reuben Thomas; Martyn T Smith
Journal:  Environ Mol Mutagen       Date:  2013-08-01       Impact factor: 3.216

Review 3.  RNA metabolism and links to inflammatory regulation and disease.

Authors:  Hui-Chi Lai; Uda Y Ho; Alexander James; Paul De Souza; Tara L Roberts
Journal:  Cell Mol Life Sci       Date:  2021-12-31       Impact factor: 9.261

4.  Associations of carotid intima media thickness with gene expression in whole blood and genetically predicted gene expression across 48 tissues.

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Journal:  Hum Mol Genet       Date:  2022-03-31       Impact factor: 5.121

Review 5.  Linking Genes to Cardiovascular Diseases: Gene Action and Gene-Environment Interactions.

Authors:  Ares Pasipoularides
Journal:  J Cardiovasc Transl Res       Date:  2015-11-06       Impact factor: 4.132

6.  The shared crosstalk of multiple pathways involved in the inflammation between rheumatoid arthritis and coronary artery disease based on a digital gene expression profile.

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Journal:  PLoS One       Date:  2014-12-16       Impact factor: 3.240

7.  Blood-based omic profiling supports female susceptibility to tobacco smoke-induced cardiovascular diseases.

Authors:  Aristotelis Chatziioannou; Panagiotis Georgiadis; Dennie G Hebels; Irene Liampa; Ioannis Valavanis; Ingvar A Bergdahl; Anders Johansson; Domenico Palli; Marc Chadeau-Hyam; Alexandros P Siskos; Hector Keun; Maria Botsivali; Theo M C M de Kok; Almudena Espín Pérez; Jos C S Kleinjans; Paolo Vineis; Soterios A Kyrtopoulos
Journal:  Sci Rep       Date:  2017-02-22       Impact factor: 4.379

8.  Peripheral-blood gene expression profiling studies for coronary artery disease and its severity in Xinjiang population in China.

Authors:  Meng Liu; Shubin Jiang; Yu Ma; Jun Ma; Waseem Hassan; Jing Shang
Journal:  Lipids Health Dis       Date:  2018-07-18       Impact factor: 3.876

9.  Alternative splicing regulation in tumor necrosis factor-mediated inflammation.

Authors:  Eduardo López-Urrutia; Alma Campos-Parra; Luis Alonso Herrera; Carlos Pérez-Plasencia
Journal:  Oncol Lett       Date:  2017-09-06       Impact factor: 2.967

10.  Weighted gene coexpression network analysis identifies the key role associated with acute coronary syndrome.

Authors:  Yong Wang; Liu Miao; Lin Tao; Jian-Hong Chen; Chuan-Meng Zhu; Ye Li; Bin Qi; Fei Liao; Rong-Shan Li
Journal:  Aging (Albany NY)       Date:  2020-10-14       Impact factor: 5.682

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