RNA-sequencing reveals that STRN, ZNF484 and WNK1 add to the value of mitochondrial MT-COI and COX10 as markers of unstable coronary artery disease

PLoS One. 2019 Dec 10;14(12):e0225621. doi: 10.1371/journal.pone.0225621. eCollection 2019.

Abstract

Markers in monocytes, precursors of macrophages, which are related to CAD, are largely unknown. Therefore, we aimed to identify genes in monocytes predictive of a new ischemic event in patients with CAD and/or discriminate between stable CAD and acute coronary syndrome. We included 66 patients with stable CAD, of which 24 developed a new ischemic event, and 19 patients with ACS. Circulating CD14+ monocytes were isolated with magnetic beads. RNA sequencing analysis in monocytes of patients with (n = 13) versus without (n = 11) ischemic event at follow-up and in patients with ACS (n = 12) was validated with qPCR (n = 85). MT-COI, STRN and COX10 predicted new ischemic events in CAD patients (power for separation at 1% error rate of 0.97, 0.90 and 0.77 respectively). Low MT-COI and high STRN were also related to shorter time between blood sampling and event. COX10 and ZNF484 together with MT-COI, STRN and WNK1 separated ACS completely from stable CAD patients. RNA expressions in monocytes of MT-COI, COX10, STRN, WNK1 and ZNF484 were independent of cholesterol lowering and antiplatelet treatment. They were independent of troponin T, a marker of myocardial injury. But, COX10 and ZNF484 in human plaques correlated to plaque markers of M1 macrophage polarization, reflecting vascular injury. Expression of MT-COI, COX10, STRN and WNK1, but not that of ZNF484, PBMCs paired with that in monocytes. The prospective study of relation of MT-COI, COX10, STRN, WNK1 and ZNF484 with unstable CAD is warranted.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Acute Coronary Syndrome / blood
  • Acute Coronary Syndrome / diagnosis*
  • Acute Coronary Syndrome / pathology
  • Aged
  • Alkyl and Aryl Transferases / blood
  • Alkyl and Aryl Transferases / metabolism
  • Biomarkers / blood
  • Biomarkers / metabolism
  • Calmodulin-Binding Proteins / blood
  • Calmodulin-Binding Proteins / metabolism*
  • Cholesterol / blood
  • Coronary Angiography
  • Coronary Artery Disease / blood
  • Coronary Artery Disease / diagnosis*
  • Coronary Artery Disease / pathology
  • Diagnosis, Differential
  • Electron Transport Complex IV / blood
  • Electron Transport Complex IV / metabolism
  • Female
  • Follow-Up Studies
  • Humans
  • Male
  • Membrane Proteins / blood
  • Membrane Proteins / metabolism*
  • Middle Aged
  • Mitochondria / metabolism
  • Monocytes / cytology
  • Monocytes / metabolism
  • Nerve Tissue Proteins / blood
  • Nerve Tissue Proteins / metabolism*
  • Plaque, Atherosclerotic / blood
  • Plaque, Atherosclerotic / pathology*
  • Prospective Studies
  • RNA-Seq
  • WNK Lysine-Deficient Protein Kinase 1 / blood
  • WNK Lysine-Deficient Protein Kinase 1 / metabolism*

Substances

  • Biomarkers
  • Calmodulin-Binding Proteins
  • Membrane Proteins
  • Nerve Tissue Proteins
  • STRN protein, human
  • Cholesterol
  • COX10 protein, human
  • Electron Transport Complex IV
  • cytochrome c oxidase subunit I, human
  • Alkyl and Aryl Transferases
  • WNK Lysine-Deficient Protein Kinase 1
  • WNK1 protein, human

Grants and funding

This work was funded by the Bijzonder Onderzoeksfonds of the KU Leuven (PF/10/014; Centre of Excellence), by the University of Padova (CPDA139317), and by Cariplo foundation (2016-1006), Italian Ministry of Health (GR-2011–02346845), AIRC (IG 2015 Id.17773), Agenzia Nazionale di Valutazione del Sistema Universitario e della Ricerca (ANVUR) (FFABR- 2017), and by grants from the Competitive Research Funding of the Tampere University Hospital (Grant 9M048 and 9N035 for T.L.), the Emil Aaltonen Foundation (T.L.), the Pirkanmaa Regional Fund of the Finnish Cultural Foundation, the Research Foundation of Orion Corporation, the Jenny and Antti Wihuri Foundation, and the Academy of Finland Grant no. 104821), the Finnish Foundation for Cardiovascular Research, the Yrjö Jahnsson Foundation and European Union 7th Framework Program, grant number 201668, AtheroRemo and EU Horizon 2020 (grant 755320 for TAXINOMISIS). P.S. and M.V. are researchers of the Research Foundation Flanders. The funding organizations had no role in design, in the collection, analysis, and interpretation of data; in the writing of the manuscript; and in the decision to submit the manuscript for publication. Bernward Klocke is employed by Intrexon Bioinformatics Germany which was hired by KU Leuven to deliver service in modeling. Intrexon Bioinformatics Germany provided support in the form of salary for author B.K., but did not have any additional role in the study design, data collection, decision to publish, or preparation of the manuscript. The specific role of this author is articulated in the ‘author contributions’ section.