Article

Journal of Cardiovascular Translational Research

, Volume 6, Issue 1, pp 81-93

Transcriptome Analysis in Patients with Progressive Coronary Artery Disease: Identification of Differential Gene Expression in Peripheral Blood

  • Thomas G. NührenbergAffiliated withKlinik für Kardiologie und Angiologie II, Universitäts-Herzzentrum Freiburg • Bad Krozingen Email author 
  • , Nicole LangwieserAffiliated withMedizinische Klinik mit Schwerpunkt Kardiologie, Campus Virchow Klinikum, CharitéBerlin-Brandenburg Center for Regenerative Therapies
  • , Harald BinderAffiliated withInstitut für Medizinische Biometrie, Epidemiologie und Informatik, Universitätsmedizin der Johannes-Gutenberg-Universität MainzInstitut für Medizinische Biometrie und Medizinische Informatik, Universitätsklinikum Freiburg
  • , Thorsten KurzAffiliated withZentrum für Biosystemanalyse der Universität Freiburg
  • , Christian StratzAffiliated withKlinik für Kardiologie und Angiologie II, Universitäts-Herzzentrum Freiburg • Bad Krozingen
  • , Rolf-Peter KienzleAffiliated withKlinik für Kardiologie und Angiologie II, Universitäts-Herzzentrum Freiburg • Bad Krozingen
  • , Dietmar TrenkAffiliated withKlinik für Kardiologie und Angiologie II, Universitäts-Herzzentrum Freiburg • Bad Krozingen
  • , Dietlind Zohlnhöfer-MommAffiliated withMedizinische Klinik mit Schwerpunkt Kardiologie, Campus Virchow Klinikum, CharitéBerlin-Brandenburg Center for Regenerative Therapies
  • , Franz-Josef NeumannAffiliated withKlinik für Kardiologie und Angiologie II, Universitäts-Herzzentrum Freiburg • Bad Krozingen

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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.

Keywords

Coronary artery disease Atherosclerosis Plaque progression Gene expression