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MULTIMARKER DIAGNOSTIC PANELS FOR ATHEROSCLEROSIS

https://doi.org/10.15829/1560-4071-2018-8-65-73

Abstract

Aim. To consider an opportunity for application of different combinations of biochemical and bioimaging parameters to create different multimarker diagnostic panels designed for assessment of risk of coronary atherosclerosis and its complications.

Material and methods. To the analysis, data included, obtained from patients 18 y.o. and older (n=502), investigated at NMRCPR of the Ministry of Health in 2011-2013, who had undergone diagnostic coronary arteriography and duplex carotid scanning. Atherosclerosis burden was measured according the Gensini score. Subfractional spectrum of apoB-lipoproteides was assessed with the Quantimetrix Lipoprint LDL System (USA), biochemistry was done with standard lab. methods. Statistics was done with software Statistica v.10, IBM SPSS Statistics v.20, SAS v.9.4.

Results. Several multimarker combinations (panels) for non-invasive estimation of risk of coronary atherosclerosis detection and its severity were proposed. These are 1) an index K, calculated as ratio of the sum of potentially atherogenic subfractions to the large physiologically active LDL1 particles; index K >1,7 indicates an increased atherogenic potential of apo B-containing particles even with normal lipid profile, and can be used for non-invasive prediction of coronary atherosclerosis; 2) duplex complexes as adiponectin to endothelin ratio which <7,0 is associated with coronary atherosclerosis risk only in men, and as leptin to insulin ratio which <3,5 is associated with elevated atherosclerosis risk only in women; 3) integrated biomarker BIO represented the combination of individual visual and biochemical variables and permitted to discriminate patients from those with no coronary atherosclerosis or having subclinical or severe atherosclerotic lesions.

Conclusion. Proposed multimarker diagnostic panel could be regarded as novel potential biomarkers of coronary atherosclerosis risk and severity, however validation of these markers is necessary. The problem of cardiovascular risk stratification and further prevention activities should be solved with the search for novel markers and combinations of markers.

About the Author

V. A. Metelskaya
National Medical Research Center for Preventive Medicine of the Ministry of Health
Russian Federation
Moscow
Competing Interests: Конфликт интересов не заявляется


References

1. Oganov RG, Maslennikova GYa. Demographic trends in the Russian Federation: the impact of cardiovascular disease. Cardiovascular Therapy and Prevention. 2012;1(11):5-10. (In Russ.)

2. Maslennikova GYa, Oganov RG. Cardiovascular and other non-communicable disease in the countries of the Northen Dimension partnership in public health and social well-being: prorities and better prevention approaches. Cardiovascular Therapy and Prevention. 2017;16(5):4-10. (In Russ.) doi:10.15829/1728-8800-2017-5-4-10.

3. Roth GA, Johnson C, Abajobir A, et al. Global, Regional, and national burden of cardiovascular diseases for 10 causes, 1990 to 2015. JACC. 2017;1(70). doi:10.1016/j. jacc.2017.04.052.

4. Catapano AL, Reiner Z, De Backer G, et al. ESC/EAS Guidelines for the management of dyslipidaemias The Task Force for the management of dyslipidaemias of the European Society of Cardiology and the European Atherosclerosis Society. Atherosclerosis. 2011;217:3-46.

5. Wang TJ. Assessingtheroleofcirculating, genetic, andimagingbiomarkersincardiovascular risk rrediction. Circulation. 2011;123:551-65. doi:10.1161/CIRCULATIONAHA.109.912568.

6. Hoefer IE, Steffens S, Ala-Korpela M, et al. On behalf of the ESC Working Group Atherosclerosis and Vascular Biology Novel methodologies for biomarker discovery in atherosclerosis. Eur Heart J. 2015;36:2635-42. doi:10.1093/eurheartj/ehv236.

7. Vasan RS. Biomarkers of cardiovascular disease: molecular basis and practical considerations. Circulation. 2006;113:2335-62. doi:10.1161/CIRCULATIONAHA.104.482570.

8. Koenig W. Integrating biomarkers: the new frontier? Scand J Clin Lab Invest Suppl. 2010;242:117-23. doi:10.3109/00365513.2010.493427.

9. Cui J. Overview of risk prediction models in cardiovascular disease research. Ann Epidemiol. 2009;19(10):711-17.

10. Dallmeier D, Koenig W. Strategies for vascular disease prevention: the role of lipids and related markers including apolipoproteins, low-density lipoproteins (LDL)-particle size, high sensitivity C-reactive protein (hs-CRP), lipoprotein-associated phospholipase A2 (Lp-PLA₂) and lipoprotein(a) (Lp(a)). Best Pract Res Clin Endocrinol Metab. 2014;28(3):281-94. doi:10.1016/j.beem.2014.01.003.

11. Wang TJ, Gona P, Larson MG, et al. Multiple biomarkers for the prediction of first major cardiovascular events and death. N Engl J Med. 2006;355:2631-9. doi:10.1056/NEJMoa055373.

12. Hoefner DM. Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther. 2001;69:89-95. doi:10.1067/mcp.2001.113989.

13. Marcovina SM, Crea F, Davignon J, et al. Biochemical and bioimaging markers for risk assessment and diagnosis in major cardiovascular diseases: a road to integration of complementary diagnostic tools. J Intern Med. 2007;261:214-34. doi:10.1111/j.13652796.2006.01734.x

14. Pencina MJ, D’Agostino RB, Sr, D’Agostino RB, Jr, et al. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med. 2008;27:157-72. doi:10.1002/sim.2929.

15. Melander O, Newton-Cheh C, Almgren P, et al. Novel and conventional biomarkers for prediction of incident cardiovascular events in the community. JAMA. 2009;302:49-57. doi:10.1001/jama.2009.943.

16. Blankenberg S, Zeller T, Saarela O, et al. Contribution of 30 biomarkers to 10-year cardiovascular risk estimation in 2 population cohorts: the MONICA, risk, genetics, archiving, and monograph (MORGAM) biomarker project. Circulation. 2010;121:2388-97.

17. Merculov EV, Mironov VM, Samko AN. Coronary angiography, ventriculography, bypass angiography in graphics and diagrams. M.: Media Medika. 2011; 100p. (In Russ.)

18. Gensini G. A more meaningful scoring system for determining the severity of coronary artery disease. Am J Cardiol. 1983;51:606.

19. Gavrilova NE, Metelskaya VA, Perova NV, et al. Selection for the quintative evaluation method of coronary arteries based upon comparative analysis of angiographic scales. Russ J Cardiol. 2014;19(6):24-9. (In Russ.) Г

20. Berneis KK, Krauss RM. Metabolic origins and clinical significance of LDL heterogeneity. J Lipid Res. 2002;43(9):1363-79.

21. Carmena R, Duriez P, Fruchart J-C. Atherogenic lipoprotein particles in atherosclerosis. Circulation. 2004;109(Suppl 1):III2-7.

22. Srisawasdi P, Vanavanan S, Rochanawutanon M, et al. Heterogeneous properties of intermediateand low-density lipoprotein subpopulations. Clin Biochem. 2013;46(15):1509-15. doi:10.1016/j.clinbiochem.2013.06.021.

23. Ragino YuI. Small dense subfractions of low-density lipoproteins and atherogenesis. Rus J Cardiol. 2004;9(4):84-90. (In Russ.) Р

24. Diffenderfer MR, Schaefer EJ. The composition and metabolism of large and small LDL. Curr Opin Lipidol. 2014;25(3):221-6. doi:10.1097/MOL.0000000000000067.

25. Afanasieva OI, Utkina EA, Vikhrova EB, et al. The presence of small dense low-density lipoprotein subfractions in human serum induce the accumulation of cholesterol by monicyte-like THP-1 cells. J Atheroscl&Dyslipidemias. 2018;1:39-46. (In Russ.)

26. Hirayama S, Miida T. Small dense LDL: An emerging risk factor for cardiovascular disease. Clin Chim Acta. 2012;24(414):215-24. doi:10.1016/j.cca.2012.09.010.

27. Hoefner DM, Hodel SD, O’Brein JF, et al. Development of a rapid, quantitative method for LDL subfractionation with use of the Quantimetrix Lipoprint LDL System. Clin Chem. 2001;47(2):266-74.

28. Utkina EA, Afanasyeva OI, Yezhov MV, et al. Association between different lipoprotein subfractions and coronary atherosclerosis in middle-aged men on statin therapy. Kardiol Vestnik. 2014;9(1):68-76. (In Russ.)

29. Ozerova IN, Metelskaya VA, Perova NV, et al. The application of lipoprint-system for analysis of sub-fractional spectrum of lipoproteins of blood serum. Clin Labor Diagn. 2016;61(5):271-5. (In Russ.) doi:10.18821/0869-2084-2016-5-271-275.

30. Ozerova IN, Metelskaya VA, Perova NV, et al. Relationship of low densities lipoprotein subfractions with triglycerides level in patients with different grade of coronary arteries stenosis. Atherosclerosis and Dyslipidemias. 2014;2:33-7. (In Russ.) Озерова И. Н., Метельская В. А., Перова Н. В. и др. Связь субфракционного спектра липопротеидов низких плотностей с уровнем триглицеридов в крови при разной степени стенозов коронарных артерий. Атеросклероз и дислипидемии. 2014;2:33-7.

31. Ozerova IN, Metelskaya VA, Gavrilova NE. Subfractional profile of apo B-containing lipoproteins in men and women with coronary atherosclerosis treated by statins. Atheroscl and Dyslipidemias. 2018;2:17-24. (In Russ.)

32. Gavrilova NE, Metelskaya VA, Ozerova IN, et al. Specifics od subfractional spectrum of apolipoprotein B related lipoproteins in carotid or coronary atherosclerosis patients. Russ J Cardiol. 2016;21(10):64-70. (In Russ.)

33. Metelskaya VA, Gavrilova NE, Ozerova IN, et al. A new way to estimate the atherogenicity of apolipoprotein B-containing lipoproteins. Patent No 2601117; 06.10.2016. Bulletin of the Inventions. 2016;10. (In Russ.)

34. Oravec S, Dukat A, Gavornik P, et al. Atherogenic versus non-atherogenic lipoprotein profiles in healthy individuals. Is there a need to change our approach to diagnosing dyslipidemia? Curr Med Chem. 2014;21(25):2892-901. doi:10.2174/092986732166614 0303153048. •

35. Guzik TJ, Magnalat D, Korbuti R. Adipocytokines novel risk link between inflammation and vascular function? J Physiol Pharmacol. 2006;57(4):505-28.

36. Tilg H, Moschen AR. Adipocytikines: mediators linking adipose tissue, inflammation and immunity. Nat Rev Immunol. 2006;6:772-83. doi:10.1038/nri1937.

37. Trujillo ME, Sherer PE. Adipose tissue-derived factors: impact on health and disease. Endocr Rev. 2006;27:762-78. doi:10.1210/er.2006-0033.

38. Gumanova NG, Klimushina MV, Gavrilova NE, Metelskaya VA. Combined markers of initial stages of coronary atherosclerosis. Biomed Khim. 2017;63(3):272-7. (In Russ.) doi:10.18097/PBMC20176303272.

39. Gumanova NG, Gavrilova NE, Chernushevich OI, et al. Ratios of leptin to insulin and adiponectin to endothelin are sex-dependently associated with extent of coronary atherosclerosis. Biomarkers. 2017;22(3-4):239-45. doi:10.1080/1354750X.2016.1201539.

40. Metelskaya VA, Gavrilova NE, Gumanova NG, et al. Combination of visual and metabolic markers in assessment of probability of presence and severity of atherosclerosis of coronary arteries. Kardiologija. 2016;56(7):47-53. (In Russ.) doi:10.18565/cardio.2016.7.47-53.

41. Kashtanova EV, Polonskaya YaV, Yakovina IN, et al. Development of a calculator for laboratory diagnosis of the risk of coronary atherosclerosis. Atherosclerosis and Dyslipidemias. 2017;4:62-8. (In Russ.)

42. Metelskaya VA, Gavrilova NE, Yarovaya EA, Boytsov SA. An integrative biomarker: opportunities for non-invasive diagnostics of coronary atherosclerosis. Russ J Cardiol. 2017;22(6):132-8. (In Russ.)


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For citations:


Metelskaya V.A. MULTIMARKER DIAGNOSTIC PANELS FOR ATHEROSCLEROSIS. Russian Journal of Cardiology. 2018;(8):65-73. (In Russ.) https://doi.org/10.15829/1560-4071-2018-8-65-73

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ISSN 1560-4071 (Print)
ISSN 2618-7620 (Online)