Looking to the Future: Spotlight on Emerging Biomarkers for Predicting Cardiovascular Risk
Purpose of Review
Coronary artery disease (CAD) continues to be a major contributor to death and disability worldwide. Emerging biomarkers that are linked to CAD pathophysiology have the potential to phenotype CAD severity and identify individuals at high risk for experiencing future CAD events. This review discusses the utility of emergent biomarkers for CAD risk prediction.
Monocytes and neutrophils are key effectors of cardiovascular inflammation, and aspects of their biology have recently been associated with cardiovascular risk. In particular, intermediate (Mon2) monocytosis is robustly associated with major adverse cardiovascular events (MACE) and surrogate markers of neutrophil extracellular trap (NET) formation have also emerged as independent predictors of MACE. MicroRNAs (miRNAs) are essential regulators of cardiovascular physiology, and a wealth of data suggests that circulating miRNA levels are linked with risk of future CAD events. A number of studies demonstrate the predictive value of a multi-miRNA panel in assessing risk and this approach is likely to more accurately predict progression of CAD to a clinically overt event, over a single-marker approach.
A number of emerging inflammatory and miRNA biomarkers hold promise for phenotyping an individual’s risk of future CAD events. Research into these particular biomarkers is in its infancy, and independent validation and methodological standardization is now required to facilitate their translation into clinical use. Ultimately, a biomarker-based methodology for identifying a high-risk phenotype will allow for targeted and personalized therapy for CAD prevention.
KeywordsCoronary artery disease Monocytes Neutrophils Inflammation MicroRNAs Prognosis
Compliance with Ethical Standards
Conflict of Interest
K.E.H. reports grants from Wellington Medical Research Foundation, Lottery Health Research, and Victoria University of Wellington, outside the submitted work. K.M.D. declares no conflicts of interest. P.D.L. reports grants from Wellington Medical Research Foundation, Lotteries Health Research, Otago Medical School Research Grant, Dean’s Research Grant University of Otago, and Health Research Council New Zealand, outside the submitted work.
Human and Animal Rights and Informed Consent
This article does not contain any studies with human or animal subjects performed by any of the authors.
Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance
- 1.Cardiovascular diseases (CVDs). World Health Organization. 2017. http://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds). Accessed February 2018.
- 4.Fang L, Moore X-L, Dart AM, Wang L-M. Systemic inflammatory response following acute myocardial infarction. J Geriatr Cardiol. 2015;12(3):305–12. https://doi.org/10.11909/j.issn.1671-5411.2015.03.020. PubMedPubMedCentralGoogle Scholar
- 8.Nouraee N, Mowla SJ. miRNA therapeutics in cardiovascular diseases: promises and problems. Front Genet. 2015;6(232) https://doi.org/10.3389/fgene.2015.00232.
- 10.Owens AP, Passam FH, Antoniak S, Marshall SM, McDaniel AL, Rudel L, et al. Monocyte tissue factor–dependent activation of coagulation in hypercholesterolemic mice and monkeys is inhibited by simvastatin. J Clin Invest. 2012;122(2):558–68. https://doi.org/10.1172/JCI58969.CrossRefPubMedPubMedCentralGoogle Scholar
- 11.Gremmel T, Ay C, Riedl J, Kopp CW, Eichelberger B, Koppensteiner R, et al. Platelet-specific markers are associated with monocyte-platelet aggregate formation and thrombin generation potential in advanced atherosclerosis. Thromb Haemost. 2016;115(3):615–21. https://doi.org/10.1160/th15-07-0598.CrossRefPubMedGoogle Scholar
- 12.Nahrendorf M, Swirski FK, Aikawa E, Stangenberg L, Wurdinger T, Figueiredo J-L, et al. The healing myocardium sequentially mobilizes two monocyte subsets with divergent and complementary functions. J Exp Med. 2007;204(12):3037–47. https://doi.org/10.1084/jem.20070885.CrossRefPubMedPubMedCentralGoogle Scholar
- 13.Weber C, Shantsila E, Hristov M, Caligiuri G, Guzik T, Heine GH, et al. Role and analysis of monocyte subsets in cardiovascular disease. Joint consensus document of the European Society of Cardiology (ESC) working groups “Atherosclerosis & Vascular Biology” and “Thrombosis”. Thromb Haemost. 2016;116(4):626–37. https://doi.org/10.1160/th16-02-0091. PubMedGoogle Scholar
- 23.Cappellari R, D'Anna M, Bonora BM, Rigato M, Cignarella A, Avogaro A, et al. Shift of monocyte subsets along their continuum predicts cardiovascular outcomes. Atherosclerosis. 2017;266:95–102. https://doi.org/10.1016/j.atherosclerosis.2017.09.032.CrossRefPubMedGoogle Scholar
- 24.Cignarella A, Tedesco S, Cappellari R, Fadini GP. The continuum of monocyte phenotypes: experimental evidence and prognostic utility in assessing cardiovascular risk. J Leukoc Biol 2018. doi: https://doi.org/10.1002/jlb.5ru1217-477rr.
- 25.•• Zeng S, Yan LF, Luo YW, Liu XL, Liu JX, Guo ZZ, et al. Trajectories of circulating monocyte subsets after ST-elevation myocardial infarction during hospitalization: latent class growth modeling for high-risk patient identification. J Cardiovasc Transl Res. 2018;11(1):22–32. https://doi.org/10.1007/s12265-017-9782-9. This study was the first to apply latent class growth modelling (LCGM) to identify a high-risk Mon2 phenotype in STEMI patients. LCGM searches for distinct “trajectories” of a measurement over time and can be used to examine the association of these trajectories with clinical outcome. The most common use of LCGM within the literature is to examine trends within epidemiology data collected over years. Zeng and colleagues shorten this time frame: trajectories were identified during hospitalization for STEMI, and the authors demonstrate the feasibility of translating this tool into clinical cardiology studies. CrossRefPubMedGoogle Scholar
- 26.Zhou X, Liu XL, Ji WJ, Liu JX, Guo ZZ, Ren D, et al. The kinetics of circulating monocyte subsets and monocyte-platelet aggregates in the acute phase of ST-elevation myocardial infarction: associations with 2-year cardiovascular events. Medicine (Baltimore). 2016;95(18):e3466. https://doi.org/10.1097/md.0000000000003466.CrossRefGoogle Scholar
- 27.•• Zawada AM, Fell LH, Untersteller K, Seiler S, Rogacev KS, Fliser D, et al. Comparison of two different strategies for human monocyte subsets gating within the large-scale prospective care for home study. Cytometry A. 2015;87(8):750–8. https://doi.org/10.1002/cyto.a.22703. This study recognizes that a limitation for Mon2 monocytosis as a risk biomarker is that delineating this subset from Mon3 monocytes is non-standardized and subjective. There are two flow cytometry gating strategies (rectangular versus trapezoid gating) that are most commonly used to identify Mon2 monocytes, and Zawada and colleagues demonstrate that Mon2 monocytosis was significantly associated with future cardiovascular risk irrespective of the type of gating strategy used. Either of these gating strategies is sufficient to delineate these monocyte populations, and this study standardizes the gating options that should be used in future studies. CrossRefPubMedGoogle Scholar
- 29.Rogacev KS, Cremers B, Zawada AM, Seiler S, Binder N, Ege P, et al. CD14++CD16+ monocytes independently predict cardiovascular events: a cohort study of 951 patients referred for elective coronary angiography. J Am Coll Cardiol. 2012;60(16):1512–20. https://doi.org/10.1016/j.jacc.2012.07.019. CrossRefPubMedGoogle Scholar
- 30.Stull DE, Wiklund I, Gale R, Capkun-Niggli G, Houghton K, Jones P. Application of latent growth and growth mixture modeling to identify and characterize differential responders to treatment for COPD. Contemp Clin Trials. 2011;32(6):818–28. https://doi.org/10.1016/j.cct.2011.06.004.CrossRefPubMedGoogle Scholar
- 31.Koning M, Hoekstra T, de Jong E, Visscher TL, Seidell JC, Renders CM. Identifying developmental trajectories of body mass index in childhood using latent class growth (mixture) modelling: associations with dietary, sedentary and physical activity behaviors: a longitudinal study. BMC Public Health. 2016;16(1):1128. https://doi.org/10.1186/s12889-016-3757-7. CrossRefPubMedPubMedCentralGoogle Scholar
- 36.Herman MP, Sukhova GK, Libby P, Gerdes N, Tang N, Horton DB, et al. Expression of neutrophil collagenase (matrix metalloproteinase-8) in human atheroma: a novel collagenolytic pathway suggested by transcriptional profiling. Circulation. 2001;104(16):1899–904. https://doi.org/10.1161/hc4101.097419.CrossRefPubMedGoogle Scholar
- 41.Litt MR, Jeremy RW, Weisman HF, Winkelstein JA, Becker LC. Neutrophil depletion limited to reperfusion reduces myocardial infarct size after 90 minutes of ischemia. Evidence for neutrophil-mediated reperfusion injury. Circulation. 1989;80(6):1816–27. https://doi.org/10.1161/01.CIR.80.6.1816.CrossRefPubMedGoogle Scholar
- 46.McDonald B, Davis RP, Kim SJ, Tse M, Esmon CT, Kolaczkowska E, et al. Platelets and neutrophil extracellular traps collaborate to promote intravascular coagulation during sepsis in mice. Blood. 2017;129(10):1357–67. https://doi.org/10.1182/blood-2016-09-741298.CrossRefPubMedPubMedCentralGoogle Scholar
- 47.Maugeri N, Campana L, Gavina M, Covino C, De Metrio M, Panciroli C, et al. Activated platelets present high mobility group box 1 to neutrophils, inducing autophagy and promoting the extrusion of neutrophil extracellular traps. J Thromb Haemost. 2014;12(12):2074–88. https://doi.org/10.1111/jth.12710.CrossRefPubMedGoogle Scholar
- 49.Mangold A, Alias S, Scherz T, Hofbauer T, Jakowitsch J, Panzenbock A, et al. Coronary neutrophil extracellular trap burden and deoxyribonuclease activity in ST-elevation acute coronary syndrome are predictors of ST-segment resolution and infarct size. Circ Res. 2015;116(7):1182–92. https://doi.org/10.1161/circresaha.116.304944. CrossRefPubMedGoogle Scholar
- 50.Riegger J, Byrne RA, Joner M, Chandraratne S, Gershlick AH, Ten Berg JM, et al. Histopathological evaluation of thrombus in patients presenting with stent thrombosis. A multicenter European study: a report of the prevention of late stent thrombosis by an interdisciplinary global European effort consortium. Eur Heart J. 2016;37(19):1538–49. https://doi.org/10.1093/eurheartj/ehv419.CrossRefPubMedGoogle Scholar
- 51.Borissoff JI, Joosen IA, Versteylen MO, Brill A, Fuchs TA, Savchenko AS, et al. Elevated levels of circulating DNA and chromatin are independently associated with severe coronary atherosclerosis and a prothrombotic state. Arterioscler Thromb Vasc Biol. 2013;33(8):2032–40. https://doi.org/10.1161/atvbaha.113.301627.CrossRefPubMedPubMedCentralGoogle Scholar
- 52.•• Langseth MS, Opstad TB, Bratseth V, Solheim S, Arnesen H, Pettersen AÅ, et al. Markers of neutrophil extracellular traps are associated with adverse clinical outcome in stable coronary artery disease. Eur J Prev Cardiol. 2018;25(7):762–9. https://doi.org/10.1177/2047487318760618. Double-stranded DNA was identified in this study as a marker of NET formation, and was shown to have prognostic utility in a stable CAD cohort. This study suggests that enhanced NET formation may play a role in the risk of atherothrombosis and, subsequently, the risk of future cardiovascular events. CrossRefPubMedGoogle Scholar
- 54.Arroyo AB, de Los Reyes-Garcia AM, Rivera-Caravaca JM, Valledor P, Garcia-Barbera N, Roldan V, et al. MiR-146a regulates neutrophil extracellular trap formation that predicts adverse cardiovascular events in patients with atrial fibrillation. Arterioscler Thromb Vasc Biol. 2018;38(4):892–902. https://doi.org/10.1161/atvbaha.117.310597.CrossRefPubMedGoogle Scholar
- 55.Ebrahimi F, Giaglis S, Hahn S, Blum CA, Baumgartner C, Kutz A, et al. Markers of neutrophil extracellular traps predict adverse outcome in community-acquired pneumonia: secondary analysis of a randomised controlled trial. Eur Respir J. 2018;51(4):1701389. https://doi.org/10.1183/13993003.01389-2017.CrossRefPubMedGoogle Scholar
- 56.• Kessenbrock K, Krumbholz M, Schönermarck U, Back W, Gross WL, Werb Z, et al. Netting neutrophils in autoimmune small-vessel vasculitis. Nat Med. 2009;15:623–5. https://doi.org/10.1038/nm.1959. The methodology for identifying myeloperoxidase–DNA complexes by ELISA described in this paper is used extensively in neutrophil extracellular trap (NET) research. We suggest that this methodology should be used as a standard for future studies investigating this NET biomarker. CrossRefPubMedPubMedCentralGoogle Scholar
- 57.Jiménez-Alcázar M, Limacher A, Panda R, Méan M, Bitterling J, Peine S, et al. Circulating extracellular DNA is an independent predictor of mortality in elderly patients with venous thromboembolism. PLoS One. 2018;13(2):e0191150. https://doi.org/10.1371/journal.pone.0191150.CrossRefPubMedPubMedCentralGoogle Scholar
- 58.Miyoshi A, Yamada M, Shida H, Nakazawa D, Kusunoki Y, Nakamura A, et al. Circulating neutrophil extracellular trap levels in well-controlled type 2 diabetes and pathway involved in their formation induced by high-dose glucose. Pathobiology. 2016;83(5):243–51. https://doi.org/10.1159/000444881. CrossRefPubMedGoogle Scholar
- 61.• Kong T, Kim TH, Park YS, Chung SP, Lee HS, Hong JH, et al. Usefulness of the delta neutrophil index to predict 30-day mortality in patients with ST segment elevation myocardial infarction. Sci Rep. 2017;7(1):15718. https://doi.org/10.1038/s41598-017-15878-5. This is one of the first studies to translate the use of delta neutrophil index from the setting of sepsis into the setting of cardiovascular disease. CrossRefPubMedPubMedCentralGoogle Scholar
- 72.Zuin M, Rigatelli G, Picariello C, dell'Avvocata F, Marcantoni L, Pastore G, et al. Correlation and prognostic role of neutrophil to lymphocyte ratio and SYNTAX score in patients with acute myocardial infarction treated with percutaneous coronary intervention: a six-year experience. Cardiovasc Revasc Med. 2017;18(8):565–71. https://doi.org/10.1016/j.carrev.2017.05.007.CrossRefPubMedGoogle Scholar
- 73.Wada H, Dohi T, Miyauchi K, Shitara J, Endo H. S et al. pre-procedural neutrophil-to-lymphocyte ratio and long-term cardiac outcomes after percutaneous coronary intervention for stable coronary artery disease. Atherosclerosis. 2017;265:35–40. https://doi.org/10.1016/j.atherosclerosis.2017.08.007. CrossRefPubMedGoogle Scholar
- 75.Xu N, Tang XF, Yao Y, Zhao X, Chen J, Gao Z, et al. Predictive value of neutrophil to lymphocyte ratio in long-term outcomes of left main and/or three-vessel disease in patients with acute myocardial infarction. Catheter Cardiovasc Interv. 2018;91(S1):551–7. https://doi.org/10.1002/ccd.27495.CrossRefPubMedGoogle Scholar
- 78.• Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova-Agadjanyan EL, et al. Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci. 2008;105(30):10513–8. https://doi.org/10.1073/pnas.0804549105. This sentinel study demonstrated the stability and robustness of miRNAs in human plasma and serum, and paved the way for circulating miRNA biomarker research. CrossRefPubMedGoogle Scholar
- 82.Jakob P, Kacprowski T, Briand-Schumacher S, Heg D, Klingenberg R, Stahli BE, et al. Profiling and validation of circulating microRNAs for cardiovascular events in patients presenting with ST-segment elevation myocardial infarction. Eur Heart J. 2017;38(7):511–5. https://doi.org/10.1093/eurheartj/ehw563.PubMedGoogle Scholar
- 83.Karakas M, Schulte C, Appelbaum S, Ojeda F, Lackner KJ, Munzel T, et al. Circulating microRNAs strongly predict cardiovascular death in patients with coronary artery disease—results from the large AtheroGene study. Eur Heart J. 2017;38(7):516–23. https://doi.org/10.1093/eurheartj/ehw250.PubMedGoogle Scholar
- 85.Schulte C, Molz S, Appelbaum S, Karakas M, Ojeda F, Lau DM, et al. miRNA-197 and miRNA-223 predict cardiovascular death in a cohort of patients with symptomatic coronary artery disease. PLoS One. 2015;10(12):e0145930. https://doi.org/10.1371/journal.pone.0145930.CrossRefPubMedPubMedCentralGoogle Scholar
- 88.Devaux Y, Vausort M, McCann GP, Kelly D, Collignon O, Ng LL, et al. A panel of 4 microRNAs facilitates the prediction of left ventricular contractility after acute myocardial infarction. PLoS One. 2013;8(8):e70644. https://doi.org/10.1371/journal.pone.0070644.CrossRefPubMedPubMedCentralGoogle Scholar
- 92.Poon K-S, Palanisamy K, Chang S-S, Sun K-T, Chen K-B, Li P-C, et al. Plasma exosomal miR-223 expression regulates inflammatory responses during cardiac surgery with cardiopulmonary bypass. Sci Rep. 2017;7(1):10807. https://doi.org/10.1038/s41598-017-09709-w. CrossRefPubMedPubMedCentralGoogle Scholar
- 96.• Moldovan L, Batte KE, Trgovcich J, Wisler J, Marsh CB, Piper M. Methodological challenges in utilizing miRNAs as circulating biomarkers. J Cell Mol Med. 2014;18(3):371–90. https://doi.org/10.1111/jcmm.12236. Moldovan and colleagues succinctly describe the limitations to circulating miRNA biomarker research and highlight the need to standardize the methodology for miRNA isolation, detection, and normalization. CrossRefPubMedPubMedCentralGoogle Scholar
- 100.Montgomery RL, Hullinger TG, Semus HM, Dickinson BA, Seto AG, Lynch JM, et al. Therapeutic inhibition of miR-208a improves cardiac function and survival during heart failure. Circulation. 2011;124(14):1537–47. https://doi.org/10.1161/circulationaha.111.030932.CrossRefPubMedPubMedCentralGoogle Scholar
- 102.van der Ree MH, van der Meer AJ, van Nuenen AC, de Bruijne J, Ottosen S, Janssen HL, et al. Miravirsen dosing in chronic hepatitis C patients results in decreased microRNA-122 levels without affecting other microRNAs in plasma. Aliment Pharmacol Ther. 2016;43(1):102–13. https://doi.org/10.1111/apt.13432.CrossRefPubMedGoogle Scholar
- 103.Hong DS, Kang Y-K, Brenner AJ, Sachdev JC, Ejadi S, Borad MJ, et al. MRX34, a liposomal miR-34 mimic, in patients with advanced solid tumors: final dose-escalation results from a first-in-human phase I trial of microRNA therapy. J Clin Oncol. 2016;34(15_suppl):2508. https://doi.org/10.1200/JCO.2016.34.15_suppl.2508.Google Scholar