Modern approaches to the assessment of individual risk of CHD development: status, problems, prospects
https://doi.org/10.52727/2078-256X-2024-20-2-154-161
Abstract
Cardiovascular diseases are the leading cause of non-violent deaths in the world. Criteria for the formation of high-risk groups are necessary for primary prevention of disease development. This was the reason for research on the development of riskmeters. A brief description of the history of the creation of CHD riskmeters. The review provides a description of the current challenges in assessing individual risk for CHD. The main approaches to the creation of riskmeters have not changed significantly for several decades. The increase in the size of study groups and the number of molecular genetic markers undoubtedly give certain results. However, in order to move from the population level to the individual level, it is necessary to take into account many more factors in the assessment. That is, it is necessary to learn how to analyze the most complex set of data of one person (genome, transcriptome, proteome, and maybe even microbiome) not only with a deep understanding of the mechanisms of its functioning (from conception to death), but also possible disorders, based on the available features. And for this purpose it is necessary to rely not only and not so much on statistical data, but on maximally similar sets of individual data (first of all, relatives). It seems that similarity should be evaluated by an artificial intelligence system trained on a colossal array of individual data.
Keywords
About the Authors
V. N. MaksimovRussian Federation
Vladimir N. Maximov, doctor of medical sciences, professor, head. laboratory
laboratory of molecular genetic research of therapeutic diseases
630089; 175/1, Boris Bogatkov str.; 630091; 52, Krasny av.; 630090; 10, Academician Lavrentiev av.; Novosibirsk
S. V. Minnikh
Russian Federation
Sofya V. Minnikh, junior researcher
laboratory of molecular genetic studies of therapeutic diseases
630089; 175/1, Boris Bogatkov str.; 630091; 52, Krasny av.; Novosibirsk
A. A. Ivanova
Russian Federation
Anastasiya A. Ivanova, Doctor of Medical Sciences, Senior researcher
laboratory of molecular genetic studies of therapeutic diseases
630089; 175/1, Boris Bogatkov str.; Novosibirsk
References
1. Khan M.A., Hashim M.J., Mustafa H., Baniyas M.Y., Al Suwaidi S.K.B.M., Al Katheeri R., Alblooshi F.M.K, Almatrooshi M.E.A.H., Alzaabi M.E.H., Al Darmaki R.S., Lootah S.N.A.H. Global epidemiology of ischemic heart disease: results from the global burden of disease study. Cureus, 2020; 12 (7): e9349. doi: 10.7759/cureus.9349
2. Nowbar A.N., Gitto M., Howard J.P., Francis D.P., Al-Lamee R. Mortality from ischemic heart disease. Circ. Cardiovasc. Qual. Outcomes., 2019; 12 (6): e005375. doi: 10.1161/CIRCOUTCOMES.118.005375
3. Brindle P., Emberson J., Lampe F., Walker M., Whincup P., Fahey T., Ebrahim S. Predictive accuracy of the framingham coronary risk score in British men: prospective cohort study. BMJ, 2003; 327 (7426): 1267. doi: 10.1136/bmj.327.7426.1267
4. Assmann G., Cullen P., Schulte H. Simple scoring scheme for calculating the risk of acute coronary events based on the 10-year follow-up of the prospective cardiovascular Mьnster (PROCAM) study. Circulation, 2002; 105 (3): 310–315. doi: 10.1161/hc0302.102575
5. Conroy R.M., Pyörälä K., Fitzgerald A.P., Sans S., Menotti A., de Backer G., de Bacquer D., Ducimetière P., Jousilahti P., Keil U., Njølstad I., Oganov R.G., Thomsen T., Tunstall-Pedoe H., Tverdal A., Wedel H., Whincup P., Wilhelmsen L., Graham I.M.; SCORE project group. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur. Heart J., 2003; 24 (11): 987–1003. doi: 10.1016/s0195-668x(03)00114-3
6. Morrison A.C., Bare L.A., Chambless L.E., Ellis S.G., Malloy M., Kane J.P., Pankow J.S., Devlin J.J., Willerson J.T., Boerwinkle E. Prediction of coronary heart disease risk using a genetic risk score: the atherosclerosis risk in communities study. Am. J. Epidemiol., 2007; 166 (1): 28–35. doi: 10.1093/aje/kwm060
7. Bare L.A., Morrison A.C., Rowland C.M., Shiffman D., Luke M.M., Iakoubova O.A., Kane J.P., Malloy M.J., Ellis S.G., Pankow J.S., Willerson J.T., Devlin J.J., Boerwinkle E. Five common gene variants identify elevated genetic risk for coronary heart disease. Genet. Med., 2007; 9 (10): 682–689. doi: 10.1097/gim.0b013e318156fb62
8. Assimes T.L., Hуlm H., Kathiresan S., Reilly M.P., Thorleifsson G., Voight B.F., Erdmann J., Willenborg C., Vaidya D., Xie C., Patterson C.C. Lack of association between the Trp719Arg polymorphism in kinesin-like protein-6 and coronary artery disease in 19 case-control studies. J. Am. Coll. Cardiol., 2010; 56 (19): 1552–1563. doi: 10.1016/j.jacc.2010.06.022
9. Semaev S., Shakhtshneider E. Genetic risk score for coronary heart disease : review. J. Pers. Med., 2020; 10 (4): 239. doi: 10.3390/jpm10040239
10. Campos A.I., Namba S., Lin S.C., Nam K., Sidorenko J., Wang H., Kamatani Y; Biobank Japan Project; Wang L.H., Lee S., Lin Y.F., Feng Y.A., Okada Y., Visscher P.M., Yengo L. Boosting the power of genome-wide association studies within and across ancestries by using polygenic scores. Nat. Genet., 2023: 5 5 (10): 1769–1776. doi: 10.1038/s41588-023-01500-0
11. Mn W., L J., Jw H., Ks R., J T., At H., Cf W. Use of SNP chips to detect rare pathogenic variants: retrospective, population based diagnostic evaluation. BMJ, 2021; 372: n214. doi: 10.1136/bmj.n214
12. Jurgens S.J., Choi S.H., Morrill V.N., Chaffin M., Pirruccello J.P., Halford J.L., Weng L.C., Nauffal V., Roselli C., Hall A.W., Oetjens M.T. Analysis of rare genetic variation underlying cardiometabolic diseases and traits among 200,000 individuals in the UK Biobank. Nat. Genet., 2022; 54 (3): 240–250. doi: 10.1038/s41588-021-01011-w
13. Nachtegael C., Gravel B., Dillen A., Smits G., Nowé A., Papadimitriou S., Lenaerts T. Scaling up oligogenic diseases research with OLIDA: the Oligogenic Diseases Database. Database (Oxford), 2022; 2022: baac023. doi: 10.1093/database/baac023
14. Nishikawa R., Furuhashi M., Hori M., Ogura M., Harada-Shiba M., Okada T., Koseki M., Kujiraoka T., Hattori H., Ito R., Muranaka A., Kokubu N., Miura T. A resuscitated case of acute myocardial infarction with both familial hypercholesterolemia phenotype caused by possibly oligogenic variants of the PCSK9 and ABCG5 genes and type I CD36 deficiency. J. Atheroscler. Thromb., 2022; 29 (4): 551–557. doi: 10.5551/jat.58909
15. Brænne I., Kleinecke M., Reiz B., Graf E., Strom T., Wieland T., Fischer M., Kessler T., Hengstenberg C., Meitinger T., Erdmann J., Schunkert H. Systematic analysis of variants related to familial hypercholesterolemia in families with premature myocardial infarction. Eur. J. Hum. Genet., 2016; 24 (2): 191–197. doi: 10.1038/ejhg.2015.100
16. Tada H., Kawashiri M.A., Nomura A., Teramoto R., Hosomichi K., Nohara A., Inazu A., Mabuchi H., Tajima A., Yamagishi M. Oligogenic familial hypercholesterolemia, LDL cholesterol, and coronary artery disease. J. Clin. Lipidol., 2018; 12 (6): 1436–1444. doi: 10.1016/j.jacl.2018.08.006
17. Pandey K.N. Genetic ablation and guanylyl cyclase/natriuretic peptide receptor-A: impact on the pathophysiology of cardiovascular dysfunction. Int. J. Mol. Sci., 2019; 20 (16): 3946. doi: 10.3390/ijms20163946
18. Salvatori F., d’Aversa E., Serino M.L., Singh A.V., Secchiero P., Zauli G., Tisato V., Gemmati D. miRNAs epigenetic tuning of wall remodeling in the early phase after myocardial infarction: a novel epidrug approach. Int. J. Mol. Sci., 2023; 24 (17): 13268. doi: 10.3390/ijms241713268
19. Shi H., Nguyen T., Zhao Q., Cheng P., Sharma D., Kim H.J., Brian Kim J., Wirka R., Weldy C.S., Monteiro J.P., Quertermous T. Discovery of transacting long noncoding RNAs that regulate smooth muscle cell phenotype. Circ. Res., 2023; 132 (7): 795–811. doi: 10.1161/CIRCRESAHA.122.321960
20. Wang Y., Selvaraj M.S., Li X., Li Z., Holdcraft J.A., Arnett D.K., Bis J.C., Blangero J., Boerwinkle E., Bowden D.W., Cade B.E. Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed whole-genome sequencing study. Am. J. Hum. Genet., 2023; 110 (10): 1704–1717. doi: 10.1016/j.ajhg.2023.09.003
21. Li A.L., Lian L., Chen X.N., Cai W.H., Fan X.B., Fan Y.J., Li T.T., Xie Y.Y., Zhang J.P. The role of mitochondria in myocardial damage caused by energy metabolism disorders: From mechanisms to therapeutics. Free Radic. Biol. Med., 2023; 208: 236–251. doi: 10.1016/j.freeradbiomed.2023.08.009
22. Malyutina S., Maximov V., Chervova O., Orlov P., Ivanova A., Mazdorova E., Ryabikov A., Simonova G., Voevoda M. The relationship between all-cause natural mortality and copy number of mitochondrial DNA in a 15-year follow-up study. Int. J. Mol. Sci., 2023; 24 (13): 10469. doi: 10.3390/ijms241310469
23. Choudhury S., Huang A.Y., Kim J., Zhou Z., Morillo K., Maury E.A., Tsai J.W., Miller M.B., Lodato M.A., Araten S., Hilal N., Lee E.A., Chen M.H., Walsh C.A. Somatic mutations in single human cardiomyocytes reveal age-associated DNA damage and widespread oxidative genotoxicity. Nat. Aging., 2022; 2 (8): 714–725. doi: 10.1038/s43587-022-00261-5
24. Stefler D., Malyutina S., Maximov V., Orlov P., Ivanoschuk D., Nikitin Y., Gafarov V., Ryabikov A., Voevoda M., Bobak M., Holmes M.V. Leukocyte telomere length and risk of coronary heart disease and stroke mortality: prospective evidence from a Russian cohort. Sci. Rep., 2018; 8 (1): 16627. doi: 10.1038/s41598-018-35122-y
25. Jin J., Zhao X., Zhu C., Li M., Wang J., Fan Y., Liu C., Shen C., Yang R. Hypomethylation of ABCG1 in peripheral blood as a potential marker for the detection of coronary heart disease. Clin. Epigenetics., 2023; 15 (1): 120. doi: 10.1186/s13148-023-01533-6
26. Hillary R.F., McCartney D.L., Smith H.M., Bernabeu E., Gadd D.A., Chybowska A.D., Cheng Y., Murphy L., Wrobel N., Campbell A., Walker R.M., Hayward C., Evans K.L., McIntosh A.M., Marioni R.E. Blood-based epigenome-wide analyses of 19 common disease states: A longitudinal, population-based linked cohort study of 18,413 Scottish individuals. PLoS Med., 2023; 20 (7): e1004247. doi: 10.1371/journal.pmed.1004247
27. Wu T., Zhou K., Hua Y., Zhang W., Li Y. The molecular mechanisms in prenatal drug exposure-induced fetal programmed adult cardiovascular disease. Front. Pharmacol., 2023; 14: 1164487. doi: 10.3389/fphar.2023.1164487
28. Chervova O., Chernysheva E., Panteleeva K., Widayati T.A., Hrbkova N., Schneider J., Maximov V., Ryabikov A., Tillmann T., Pikhart H., Bobak M., Voloshin V., Malyutina S., Beck S. Evaluation of epigenetic age acceleration scores and their associations with CVD-related phenotypes in a population cohort. Biology (Basel), 2022; 12 (1): 68. doi: 10.3390/biology12010068
29. Si J., Chen L., Yu C., Guo Y., Sun D., Pang Y., Millwood I.Y., Walters R.G., Yang L., Chen Y., Du H., Feng S., Yang X., Avery D., Chen J., Chen Z., Liang L., Li L., Lv J.; China Kadoorie Biobank Collaborative Group. Healthy lifestyle, DNA methylation age acceleration, and incident risk of coronary heart disease. Clin. Epigenetics., 2023; 15 (1): 52. doi: 10.1186/s13148-023-01464-2
30. Sánchez-Cabo F., Fuster V., Silla-Castro J.C., González G., Lorenzo-Vivas E., Alvarez R., Callejas S., Benguría A., Gil E., Núñez E., Oliva B., Mendiguren J.M. Subclinical atherosclerosis and accelerated epigenetic age mediated by inflammation: a multi-omics study. Eur. Heart J., 2023; 44 (29): 2698–2709. doi: 10.1093/eurheartj/ehad361
31. Tada H., Melander O., Louie J.Z., Catanese J.J., Rowland C.M., Devlin J.J., Kathiresan S., Shiffman D. Risk prediction by genetic risk scores for coronary heart disease is independent of self-reported family history. Eur. Heart J., 2016; 37 (6): 561–567. doi: 10.1093/eurheartj/ehv462
32. Inouye M., Abraham G., Nelson C.P., Wood A.M., Sweeting M.J., Dudbridge F., Lai F.Y., Kaptoge S., Brozynska M., Wang T., Ye S., Webb T.R., Rutter M.K., Tzoulaki I., Patel R.S., Loos R.J.F., Keavney B., Hemingway H., Thompson J., Watkins H., Deloukas P., di Angelantonio E., Butterworth A.S., Danesh J., Samani N.J.; UK Biobank Cardio-Metabolic Consortium CHD Working Group. Genomic risk prediction of coronary artery disease in 480,000 adults: implications for primary prevention. J. Am. Coll. Cardiol., 2018; 72 (16): 1883–1893. doi: 10.1016/j.jacc.2018.07.079
Review
For citations:
Maksimov V.N., Minnikh S.V., Ivanova A.A. Modern approaches to the assessment of individual risk of CHD development: status, problems, prospects. Ateroscleroz. 2024;20(2):154-161. (In Russ.) https://doi.org/10.52727/2078-256X-2024-20-2-154-161