Genetics of Cardiovascular Disease: How Far Are We from Personalized CVD Risk Prediction and Management?

. 2021 Apr 17 ; 22 (8) : . [epub] 20210417

Jazyk angličtina Země Švýcarsko Médium electronic

Typ dokumentu časopisecké články, přehledy

Perzistentní odkaz   https://www.medvik.cz/link/pmid33920733

Grantová podpora
IN 00023001 Ministerstvo Zdravotnictví Ceské Republiky
NV18-01-00046 Ministerstvo Zdravotnictví Ceské Republiky
NV17-28882A Ministerstvo Zdravotnictví Ceské Republiky
NU-20-06-00061 Ministerstvo Zdravotnictví Ceské Republiky
conceptual development of research organization 64165 Ministerstvo Zdravotnictví Ceské Republiky

Despite the rapid progress in diagnosis and treatment of cardiovascular disease (CVD), this disease remains a major cause of mortality and morbidity. Recent progress over the last two decades in the field of molecular genetics, especially with new tools such as genome-wide association studies, has helped to identify new genes and their variants, which can be used for calculations of risk, prediction of treatment efficacy, or detection of subjects prone to drug side effects. Although the use of genetic risk scores further improves CVD prediction, the significance is not unambiguous, and some subjects at risk remain undetected. Further research directions should focus on the "second level" of genetic information, namely, regulatory molecules (miRNAs) and epigenetic changes, predominantly DNA methylation and gene-environment interactions.

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Timmis A., Townsend N., Gale C.P., Torbica A., Lettino M., Petersen S.E., Mossialos E.A., Maggioni A.P., Kazakiewicz D., May H.T., et al. European Society of Cardiology: Cardiovascular disease statistics 2019. Eur. Heart J. 2020;41:12–85. doi: 10.1093/eurheartj/ehz859. PubMed DOI

Wilkins E., Wilson L., Wickramasinghe K., Bhatnagar P., Leal J., Luengo-Fernandez R., Burns R., Rayner M., Townsend N. European Cardiovascular Disease Statistics 2017. European Heart Network; Brussels, Belgium: 2017.

Hartley A., Marshall D.C., Salciccioli J.D., Sikkel M.B., Maruthappu M., Shalhoub J. Trends in mortality from ischemic heart disease and cerebrovascular disease in Europe: 1980 to 2009. Circulation. 2016;133:1916–1926. doi: 10.1161/CIRCULATIONAHA.115.018931. PubMed DOI

Gersh B.J., Maron B.J., Bonow R.O., Dearani J.A., Fifer M.A., Link M.S., Naidu S.S., Nishimura R.A., Ommen S.R., Rakowski H., et al. 2011 ACCF/AHA guideline for the diagnosis and treatment of hypertrophic cardiomyopathy: A report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Circulation. 2011;124:e783–e831. doi: 10.1161/CIR.0b013e318223e2bd. PubMed DOI

Musunuru K., Kathiresan S. Genetics of common, complex coronary artery disease. Cell. 2019;177:132–145. doi: 10.1016/j.cell.2019.02.015. PubMed DOI

Vrablik M., Tichý L., Freiberger T., Blaha V., Satny M., Hubacek J.A. Genetics of familial hypercholesterolemia: New insights. Front. Genet. 2020;11:574474. doi: 10.3389/fgene.2020.574474. PubMed DOI PMC

Mytilinaiou M., Kyrou I., Khan M., Grammatopoulos D.K., Randeva H.S. Familial hypercholesterolemia: New horizons for diagnosis and effective management. Front. Pharmacol. 2018;9:707. doi: 10.3389/fphar.2018.00707. PubMed DOI PMC

Sturm A.C., Knowles J.W., Gidding S.S., Ahmad Z.S., Ahmed C.D., Ballantyne C.M., Baum S.J., Bourbon M., Carrié A., Cuchel M., et al. Clinical genetic testing for familial hypercholesterolemia: JACC Scientific Expert Panel. J. Am. Coll. Cardiol. 2018;72:662–680. doi: 10.1016/j.jacc.2018.05.044. PubMed DOI

Sharifi M., Futema M., Nair D., Humphries S.E. Genetic architecture of familial hypercholesterolaemia. Curr. Cardiol. Rep. 2017;19:44. doi: 10.1007/s11886-017-0848-8. PubMed DOI PMC

Brandts J., Dharmayat K.I., Ray K.K., Vallejo-Vaz A.J. Familial hypercholesterolemia: Is it time to separate monogenic from polygenic familial hypercholesterolemia? Curr. Opin. Lipidol. 2020;31:111–118. doi: 10.1097/MOL.0000000000000675. PubMed DOI

Zou Y.B., Hui R.T., Song L. The era of clinical application of gene diagnosis in cardiovascular diseases is coming. Chronic Dis. Transl. Med. 2020;5:214–220. doi: 10.1016/j.cdtm.2019.12.005. PubMed DOI PMC

Berge K.E., Tian H., Graf G.A., Yu L., Grishin N.V., Schultz J., Kwiterovich P., Shan B., Barnes R., Hobbs H.H. Accumulation of dietary cholesterol in sitosterolemia caused by mutations in adjacent ABC transporters. Science. 2000;290:1771–1775. doi: 10.1126/science.290.5497.1771. PubMed DOI

Lu K., Lee M.H., Hazard S., Brooks-Wilson A., Hidaka H., Kojima H., Ose L., Stalenhoef A.F., Mietinnen T., Bjorkhem I., et al. Two genes that map to the STSL locus cause sitosterolemia: Genomic structure and spectrum of mutations involving sterolin-1 and sterolin-2, encoded by ABCG5 and ABCG8, respectively. Am. J. Hum. Genet. 2001;69:278–290. doi: 10.1086/321294. PubMed DOI PMC

Sakai L.Y., Keene D.R., Renard M., De Backer J. FBN1: The disease-causing gene for Marfan syndrome and other genetic disorders. Gene. 2016;591:279–291. doi: 10.1016/j.gene.2016.07.033. PubMed DOI PMC

Marais A.D. Apolipoprotein E in lipoprotein metabolism, health and cardiovascular disease. Pathology. 2019;51:165–176. doi: 10.1016/j.pathol.2018.11.002. PubMed DOI

Pennacchio L.A., Olivier M., Hubacek J.A., Cohen J.C., Cox D.R., Fruchart J.C., Krauss R.M., Rubin E.M. An apolipoprotein influencing triglycerides in humans and mice revealed by comparative sequencing. Science. 2001;294:169–173. doi: 10.1126/science.1064852. PubMed DOI

Loos R.J. The genetic epidemiology of melanocortin 4 receptor variants. Eur. J. Pharmacol. 2011;660:156–164. doi: 10.1016/j.ejphar.2011.01.033. PubMed DOI

Gianfagna F., Cugino D., Santimone I., Iacoviello L. From candidate gene to genome-wide association studies in cardiovascular disease. Thromb. Res. 2012;129:320–324. doi: 10.1016/j.thromres.2011.11.014. PubMed DOI

Uitterlinden A.G. An introduction to genome-wide association studies: GWAS for dummies. Semin. Reprod. Med. 2016;34:196–204. doi: 10.1055/s-0036-1585406. PubMed DOI

Larson M.G., Atwood L.D., Benjamin E.J., Cupples L.A., D’Agostino R.B., Sr., Fox C.S., Govindaraju D.R., Guo C.Y., Heard-Costa N.L., Hwang S.J., et al. Framingham Heart Study 100K project: Genome-wide associations for cardiovascular disease outcomes. BMC Med. Genet. 2007;8(Suppl. 1):S5. doi: 10.1186/1471-2350-8-S1-S5. PubMed DOI PMC

Samani N.J., Erdmann J., Hall A.S., Hengstenberg C., Mangino M., Mayer B., Dixon R.J., Meitinger T., Braund P., Wichmann H.E., et al. Genomewide association analysis of coronary artery disease. N. Engl. J. Med. 2007;357:443–453. doi: 10.1056/NEJMoa072366. PubMed DOI PMC

Scott L.J., Mohlke K.L., Bonnycastle L.L., Willer C.J., Li Y., Duren W.L., Erdos M.R., Stringham H.M., Chines P.S., Jackson A.U., et al. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science. 2007;316:1341–1345. doi: 10.1126/science.1142382. PubMed DOI PMC

Erdmann J., Kessler T., Munoz Venegas L., Schunkert H. A decade of genome-wide association studies for coronary artery disease: The challenges ahead. Cardiovasc. Res. 2018;114:1241–1257. doi: 10.1093/cvr/cvy084. PubMed DOI

Palomaki G.E., Melillo S., Bradley L.A. Association between 9p21 genomic markers and heart disease: A meta-analysis. JAMA. 2010;303:648–656. doi: 10.1001/jama.2010.118. PubMed DOI

Li W.Q., Pfeiffer R.M., Hyland P.L., Shi J., Gu F., Wang Z., Bhattacharjee S., Luo J., Xiong X., Yeager M., et al. Genetic polymorphisms in the 9p21 region associated with risk of multiple cancers. Carcinogenesis. 2014;35:2698–2705. doi: 10.1093/carcin/bgu203. PubMed DOI PMC

Wiggs J.L., Yaspan B.L., Hauser M.A., Kang J.H., Allingham R.R., Olson L.M., Abdrabou W., Fan B.J., Wang D.Y., Brodeur W., et al. Common variants at 9p21 and 8q22 are associated with increased susceptibility to optic nerve degeneration in glaucoma. PLoS Genet. 2012;8:e1002654. doi: 10.1371/journal.pgen.1002654. PubMed DOI PMC

Safa A., Noroozi R., Taheri M., Ghafouri-Fard S. Association analysis of ANRIL polymorphisms and haplotypes with autism spectrum disorders. J. Mol. Neurosci. 2021;71:187–192. doi: 10.1007/s12031-020-01657-x. PubMed DOI

Teslovich T.M., Musunuru K., Smith A.V., Edmondson A.C., Stylianou I.M., Koseki M., Pirruccello J.P., Ripatti S., Chasman D.I., Willer C.J., et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature. 2010;466:707–713. doi: 10.1038/nature09270. PubMed DOI PMC

Strong A., Rader D.J. Sortilin as a regulator of lipoprotein metabolism. Curr. Atheroscler. Rep. 2012;14:211–218. doi: 10.1007/s11883-012-0248-x. PubMed DOI PMC

Zhong L.Y., Cayabyab F.S., Tang C.K., Zheng X.L., Peng T.H., Lv Y.C. Sortilin: A novel regulator in lipid metabolism and atherogenesis. Clin. Chim. Acta. 2016;460:11–17. doi: 10.1016/j.cca.2016.06.013. PubMed DOI

Musunuru K., Strong A., Frank-Kamenetsky M., Lee N.E., Ahfeldt T., Sachs K.V., Li X., Li H., Kuperwasser N., Ruda V.M., et al. From noncoding variant to phenotype via SORT1 at the 1p13 cholesterol locus. Nature. 2010;466:714–719. doi: 10.1038/nature09266. PubMed DOI PMC

Kjolby M., Andersen O.M., Breiderhoff T., Fjorback A.W., Pedersen K.M., Madsen P., Jansen P., Heeren J., Willnow T.E., Nykjaer A. Sort1, encoded by the cardiovascular risk locus 1p13.3, is a regulator of hepatic lipoprotein export. Cell Metab. 2010;12:213–223. doi: 10.1016/j.cmet.2010.08.006. PubMed DOI

Tveten K., Strøm T.B., Cameron J., Berge K.E., Leren T.P. Mutations in the SORT1 gene are unlikely to cause autosomal dominant hypercholesterolemia. Atherosclerosis. 2012;225:370–375. doi: 10.1016/j.atherosclerosis.2012.10.026. PubMed DOI

Dina C., Meyre D., Gallina S., Durand E., Körner A., Jacobson P., Carlsson L.M., Kiess W., Vatin V., Lecoeur C., et al. Variation in FTO contributes to childhood obesity and severe adult obesity. Nat. Genet. 2007;39:724–726. doi: 10.1038/ng2048. PubMed DOI

Frayling T.M., Timpson N.J., Weedon M.N., Zeggini E., Freathy R.M., Lindgren C.M., Perry J.R., Elliott K.S., Lango H., Rayner N.W., et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science. 2007;316:889–894. doi: 10.1126/science.1141634. PubMed DOI PMC

Diabetes Genetics Initiative of Broad Institute of Harvard and MIT. Lund University. Novartis Institutes of BioMedical Research. Saxena R., Voight B.F., Lyssenko V., Burtt N.P., de Bakker P.I., Chen H., Roix J.J., et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science. 2007;316:1331–1336. PubMed

Loos R.J., Yeo G.S. The bigger picture of FTO: The first GWAS-identified obesity gene. Nat. Rev. Endocrinol. 2014;10:51–61. doi: 10.1038/nrendo.2013.227. PubMed DOI PMC

Hubacek J.A., Stanek V., Gebauerová M., Pilipcincová A., Dlouhá D., Poledne R., Aschermann M., Skalická H., Matousková J., Kruger A., et al. A FTO variant and risk of acute coronary syndrome. Clin. Chim. Acta. 2010;411:1069–1072. doi: 10.1016/j.cca.2010.03.037. PubMed DOI

Doney A.S., Dannfald J., Kimber C.H., Donnelly L.A., Pearson E., Morris A.D., Palmer C.N. The FTO gene is associated with an atherogenic lipid profile and myocardial infarction in patients with type 2 diabetes: A Genetics of Diabetes Audit and Research Study in Tayside Scotland (Go-DARTS) study. Circ. Cardiovasc Genet. 2009;2:255–259. doi: 10.1161/CIRCGENETICS.108.822320. PubMed DOI PMC

Hubacek J.A., Viklicky O., Dlouha D., Bloudickova S., Kubinova R., Peasey A., Pikhart H., Adamkova V., Brabcova I., Pokorna E., et al. The FTO gene polymorphism is associated with end-stage renal disease: Two large independent case-control studies in a general population. Nephrol. Dial. Transplant. 2012;27:1030–1035. doi: 10.1093/ndt/gfr418. PubMed DOI PMC

Reitz C., Tosto G., Mayeux R., Luchsinger J.A., NIA-LOAD/NCRAD Family Study Group. Alzheimer’s Disease Neuroimaging Initiative Genetic variants in the Fat and Obesity Associated (FTO) gene and risk of Alzheimer’s disease. PLoS ONE. 2012;7:e50354. doi: 10.1371/journal.pone.0050354. PubMed DOI PMC

Hubacek J.A., Dlouha D., Klementova M., Lanska V., Neskudla T., Pelikanova T. The FTO variant is associated with chronic complications of diabetes mellitus in Czech population. Gene. 2018;642:220–224. doi: 10.1016/j.gene.2017.11.040. PubMed DOI

Zimmermann E., Kring S.I., Berentzen T.L., Holst C., Pers T.H., Hansen T., Pedersen O., Sørensen T.I., Jess T. Fatness-associated FTO gene variant increases mortality independent of fatness—In cohorts of Danish men. PLoS ONE. 2009;4:e4428. doi: 10.1371/journal.pone.0004428. PubMed DOI PMC

Tung Y.C.L., Yeo G.S.H., O’Rahilly S., Coll A.P. Obesity and FTO: Changing focus at a complex locus. Cell Metab. 2014;20:710–718. doi: 10.1016/j.cmet.2014.09.010. PubMed DOI

Gerken T., Girard C.A., Tung Y.C., Webby C.J., Saudek V., Hewitson K.S., Yeo G.S., McDonough M.A., Cunliffe S., McNeill L.A., et al. The obesity-associated FTO gene encodes a 2-oxoglutarate-dependent nucleic acid demethylase. Science. 2007;318:1469–1472. doi: 10.1126/science.1151710. PubMed DOI PMC

Dlouha D., Pitha J., Lanska V., Hubacek J.A. Association between FTO 1st intron tagging variant and telomere length in middle aged females. 3PMFs study. Clin. Chim. Acta. 2012;413:1222–1225. doi: 10.1016/j.cca.2012.03.025. PubMed DOI

Zhou Y., Hambly B.D., McLachlan C.S. FTO associations with obesity and telomere length. J. Biomed. Sci. 2017;24:65. doi: 10.1186/s12929-017-0372-6. PubMed DOI PMC

Wu Q., Saunders R.A., Szkudlarek-Mikho M., Serna Ide L., Chin K.V. The obesity-associated Fto gene is a transcriptional coactivator. Biochem. Biophys. Res. Commun. 2010;401:390–395. doi: 10.1016/j.bbrc.2010.09.064. PubMed DOI PMC

Nadkarni G.N., Gignoux C.R., Sorokin E.P., Daya M., Rahman R., Barnes K.C., Wassel C.L., Kenny E.E. Worldwide frequencies of APOL1 renal risk variants. N. Engl. J. Med. 2018;379:2571–2572. doi: 10.1056/NEJMc1800748. PubMed DOI PMC

Grant S.F.A. The TCF7L2 locus: A genetic window into the pathogenesis of type 1 and type 2 diabetes. Diabetes Care. 2019;42:1624–1629. doi: 10.2337/dci19-0001. PubMed DOI PMC

Xi B., Chandak G.R., Shen Y., Wang Q., Zhou D. Association between common polymorphism near the MC4R gene and obesity risk: A systematic review and meta-analysis. PLoS ONE. 2012;7:e45731. doi: 10.1371/journal.pone.0045731. PubMed DOI PMC

Saccone N.L., Saccone S.F., Hinrichs A.L., Stitzel J.A., Duan W., Pergadia M.L., Agrawal A., Breslau N., Grucza R.A., Hatsukami D., et al. Multiple distinct risk loci for nicotine dependence identified by dense coverage of the complete family of nicotinic receptor subunit (CHRN) genes. Am. J. Med. Genet. B Neuropsychiatr. Genet. 2009;150:453–466. doi: 10.1002/ajmg.b.30828. PubMed DOI PMC

Lip S., Padmanabhan S. Genomics of blood pressure and hypertension: Extending the mosaic theory toward stratification. Can. J. Cardiol. 2020;36:694–705. doi: 10.1016/j.cjca.2020.03.001. PubMed DOI PMC

Lambert S.A., Abraham G., Inouye M. Towards clinical utility of polygenic risk scores. Hum. Mol. Genet. 2019;28:R133–R142. doi: 10.1093/hmg/ddz187. PubMed DOI

Rao A.S., Knowles J.W. Polygenic risk scores in coronary artery disease. Curr. Opin. Cardiol. 2019;34:435–440. doi: 10.1097/HCO.0000000000000629. PubMed DOI

Igo R.P., Jr., Kinzy T.G., Cooke Bailey J.N. Genetic risk scores. Curr. Protoc. Hum. Genet. 2019;104:e95. doi: 10.1002/cphg.95. PubMed DOI PMC

Kooner J.S., Chambers J.C., Aguilar-Salinas C.A., Hinds D.A., Hyde C.L., Warnes G.R., Gómez Pérez F.J., Frazer K.A., Elliott P., Scott J., et al. Genome-wide scan identifies variation in MLXIPL associated with plasma triglycerides. Nat. Genet. 2008;40:149–151. doi: 10.1038/ng.2007.61. PubMed DOI

Vrablik M., Ceska R., Adamkova V., Peasey A., Pikhart H., Kubinova R., Marmot M., Bobak M., Hubacek J.A. MLXIPL variant in individuals with low and high triglyceridemia in white population in Central Europe. Hum. Genet. 2008;124:553–555. doi: 10.1007/s00439-008-0577-6. PubMed DOI

Rašlová K., Dobiášová M., Hubáček J.A., Bencová D., Siváková D., Danková Z., Franeková J., Jabor A., Gašparovič J., Vohnout B. Association of metabolic and genetic factors with cholesterol esterification rate in HDL plasma and atherogenic index of plasma in a 40 years old Slovak population. Physiol. Res. 2011;60:785–795. doi: 10.33549/physiolres.932069. PubMed DOI

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;12:1436–1444. doi: 10.1016/j.jacl.2018.08.006. PubMed DOI

Poledne R., Hubácek J., Písa Z., Pistulková H., Valenta Z. Genetic markers in hypercholesterolemic and normocholesterolemic Czech children. Clin. Genet. 1994;46:88–91. doi: 10.1111/j.1399-0004.1994.tb04208.x. PubMed DOI

Pedersen J.C., Berg K. Gene-gene interaction between the low density lipoprotein receptor and apolipoprotein E loci affects lipid levels. Clin. Genet. 1990;38:287–294. PubMed

Shabana, Shahid S.U., Hasnain S. Use of a gene score of multiple low-modest effect size variants can predict the risk of obesity better than the individual SNPs. Lipids Health Dis. 2018;17:155. doi: 10.1186/s12944-018-0806-5. PubMed DOI PMC

Hubacek J.A., Dlouha D., Adamkova V., Schwarzova L., Lanska V., Ceska R., Satny M., Vrablik M. The gene score for predicting hypertriglyceridemia: New insights from a Czech case-control study. Mol. Diagn. Ther. 2019;23:555–562. doi: 10.1007/s40291-019-00412-2. PubMed DOI

Johansen C.T., Wang J., Lanktree M.B., McIntyre A.D., Ban M.R., Martins R.A., Kennedy B.A., Hassell R.G., Visser M.E., Schwartz S.M., et al. An increased burden of common and rare lipid-associated risk alleles contributes to the phenotypic spectrum of hypertriglyceridemia. Arterioscler. Thromb. Vasc. Biol. 2011;31:1916–1926. doi: 10.1161/ATVBAHA.111.226365. PubMed DOI PMC

El Rouby N., McDonough C.W., Gong Y., McClure L.A., Mitchell B.D., Horenstein R.B., Talbert R.L., Crawford D.C., eMERGE Network. Gitzendanner M.A., et al. Genome-wide association analysis of common genetic variants of resistant hypertension. Pharmacogenom. J. 2019;19:295–304. doi: 10.1038/s41397-018-0049-x. PubMed DOI PMC

Talmud P.J., Cooper J.A., Morris R.W., Dudbridge F., Shah T., Engmann J., Dale C., White J., McLachlan S., Zabaneh D., et al. Sixty-five common genetic variants and prediction of type 2 diabetes. Diabetes. 2015;64:1830–1840. doi: 10.2337/db14-1504. PubMed DOI PMC

Läll K., Mägi R., Morris A., Metspalu A., Fischer K. Personalized risk prediction for type 2 diabetes: The potential of genetic risk scores. Genet. Med. 2017;19:322–329. doi: 10.1038/gim.2016.103. PubMed DOI PMC

Morris R.W., Cooper J.A., Shah T., Wong A., Drenos F., Engmann J., McLachlan S., Jefferis B., Dale C., Hardy R., et al. Marginal role for 53 common genetic variants in cardiovascular disease prediction. Heart. 2016;102:1640–1647. doi: 10.1136/heartjnl-2016-309298. PubMed DOI PMC

Trinder M., Li X., DeCastro M.L., Cermakova L., Sadananda S., Jackson L.M., Azizi H., Mancini G.B.J., Francis G.A., Frohlich J., et al. Risk of premature atherosclerotic disease in patients with monogenic versus polygenic familial hypercholesterolemia. J. Am. Coll. Cardiol. 2019;74:512–522. doi: 10.1016/j.jacc.2019.05.043. PubMed DOI

Khera A.V., Chaffin M., Zekavat S.M., Collins R.L., Roselli C., Natarajan P., Lichtman J.H., D’Onofrio G., Matera J., Dreyer R., et al. Whole-genome sequencing to characterize monogenic and polygenic contributions in patients hospitalized with early-onset myocardial infarction. Circulation. 2019;139:1593–1602. doi: 10.1161/CIRCULATIONAHA.118.035658. PubMed DOI PMC

GBD 2015 Risk Factors Collaborators Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: A systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388:1659–1724. doi: 10.1016/S0140-6736(16)31679-8. PubMed DOI PMC

Hubacek J.A., Bobkova D. Role of cholesterol 7alpha-hydroxylase (CYP7A1) in nutrigenetics and pharmacogenetics of cholesterol lowering. Mol. Diagn. Ther. 2006;10:93–100. doi: 10.1007/BF03256448. PubMed DOI

Hubacek J.A., Pitha J., Skodová Z., Poledne R., Lánská V., Waterworth D.M., Humphries S.E., Talmud P.J. Czech MONICA Study. Polymorphisms in CYP-7A1, not APOE, influence the change in plasma lipids in response to population dietary change in an 8 year follow-up; results from the Czech MONICA study. Clin. Biochem. 2003;36:263–267. doi: 10.1016/S0009-9120(03)00025-0. PubMed DOI

Kovár J., Suchánek P., Hubácek J.A., Poledne R. The A-204C polymorphism in the cholesterol 7alpha-hydroxylase (CYP7A1) gene determines the cholesterolemia responsiveness to a high-fat diet. Physiol. Res. 2004;53:565–568. PubMed

MacKay D.S., Eck P.K., Gebauer S.K., Baer D.J., Jones P.J. CYP7A1-rs3808607 and APOE isoform associate with LDL cholesterol lowering after plant sterol consumption in a randomized clinical trial. Am. J. Clin. Nutr. 2015;102:951–957. doi: 10.3945/ajcn.115.109231. PubMed DOI

Hofman M.K., Weggemans R.M., Zock P.L., Schouten E.G., Katan M.B., Princen H.M. CYP7A1 A-278C polymorphism affects the response of plasma lipids after dietary cholesterol or cafestol interventions in humans. J. Nutr. 2004;134:2200–2204. doi: 10.1093/jn/134.9.2200. PubMed DOI

Merritt D.C., Jamnik J., El-Sohemy A. FTO genotype, dietary protein intake, and body weight in a multiethnic population of young adults: A cross-sectional study. Genes Nutr. 2018;13:4. doi: 10.1186/s12263-018-0593-7. PubMed DOI PMC

Qi Q., Downer M.K., Kilpeläinen T.O., Taal H.R., Barton S.J., Ntalla I., Standl M., Boraska V., Huikari V., Kiefte-de Jong J.C., et al. Dietary intake, FTO genetic variants, and adiposity: A combined analysis of over 16,000 children and adolescents. Diabetes. 2015;64:2467–2476. doi: 10.2337/db14-1629. PubMed DOI PMC

Kim J. Are genes destiny? Exploring the role of intrauterine environment in moderating genetic influences on body mass. Am. J. Hum. Biol. 2020;32:e23354. doi: 10.1002/ajhb.23354. PubMed DOI

Holmes M.V., Newcombe P., Hubacek J.A., Sofat R., Ricketts S.L., Cooper J., Breteler M.M., Bautista L.E., Sharma P., Whittaker J.C., et al. Effect modification by population dietary folate on the association between MTHFR genotype, homocysteine, and stroke risk: A meta-analysis of genetic studies and randomised trials. Lancet. 2011;378:584–594. doi: 10.1016/S0140-6736(11)60872-6. PubMed DOI PMC

Zheng Y., Li Y., Huang T., Cheng H.L., Campos H., Qi L. Sugar-sweetened beverage intake, chromosome 9p21 variants, and risk of myocardial infarction in Hispanics. Am. J. Clin. Nutr. 2016;103:1179–1184. doi: 10.3945/ajcn.115.107177. PubMed DOI PMC

Peña-Romero A.C., Navas-Carrillo D., Marín F., Orenes-Piñero E. The future of nutrition: Nutrigenomics and nutrigenetics in obesity and cardiovascular diseases. Crit. Rev. Food Sci. Nutr. 2018;58:3030–3041. doi: 10.1080/10408398.2017.1349731. PubMed DOI

Barrea L., Annunziata G., Bordoni L., Muscogiuri G., Colao A., Savastano S., Obesity Programs of Nutrition, Education, Research and Assessment (OPERA) Group Nutrigenetics-personalized nutrition in obesity and cardiovascular diseases. Int. J. Obes. Suppl. 2020;10:1–13. doi: 10.1038/s41367-020-0014-4. PubMed DOI PMC

Mullins V.A., Bresette W., Johnstone L., Hallmark B., Chilton F.H. Genomics in personalized nutrition: Can you “Eat for your genes”? Nutrients. 2020;12:3118. doi: 10.3390/nu12103118. PubMed DOI PMC

Hubacek J.A., Pikhart H., Peasey A., Malyutina S., Pajak A., Tamosiunas A., Voevoda M., Holmes M.V., Bobak M. The association between the FTO gene variant and alcohol consumption and binge and problem drinking in different gene-environment background: The HAPIEE study. Gene. 2019;707:30–35. doi: 10.1016/j.gene.2019.05.002. PubMed DOI

Johnson J.A., Cavallari L.H. Pharmacogenetics and cardiovascular disease—Implications for personalized medicine. Pharmacol. Rev. 2013;65:987–1009. doi: 10.1124/pr.112.007252. PubMed DOI PMC

Rodríguez Vicente A.E., Herrero Cervera M.J., Bernal M.L., Rojas L., Peiró A.M. Personalized medicine into health national services: Barriers and potentialities. Drug Metab. Pers. Ther. 2018;33:159–163. doi: 10.1515/dmpt-2018-0017. PubMed DOI

Vrablik M., Zlatohlavek L., Stulc T., Adamkova V., Prusikova M., Schwarzova L., Hubacek J.A., Ceska R. Statin-associated myopathy: From genetic predisposition to clinical management. Physiol. Res. 2014;63(Suppl. 3):S327–S334. doi: 10.33549/physiolres.932865. PubMed DOI

Canestaro W.J., Austin M.A., Thummel K.E. Genetic factors affecting statin concentrations and subsequent myopathy: A HuGENet systematic review. Genet. Med. 2014;16:810–819. doi: 10.1038/gim.2014.41. PubMed DOI PMC

Neřoldová M., Stránecký V., Hodaňová K., Hartmannová H., Piherová L., Přistoupilová A., Mrázová L., Vrablík M., Adámková V., Hubáček J.A., et al. Rare variants in known and novel candidate genes predisposing to statin-associated myopathy. Pharmacogenomics. 2016;17:1405–1414. doi: 10.2217/pgs-2016-0071. PubMed DOI

SEARCH Collaborative Group. Link E., Parish S., Armitage J., Bowman L., Heath S., Matsuda F., Gut I., Lathrop M., Collins R. SLCO1B1 variants and statin-induced myopathy—A genomewide study. N. Engl. J. Med. 2008;359:789–799. PubMed

Voora D., Shah S.H., Spasojevic I., Ali S., Reed C.R., Salisbury B.A., Ginsburg G.S. The SLCO1B1*5 genetic variant is associated with statin-induced side effects. J. Am. Coll. Cardiol. 2009;54:1609–1616. doi: 10.1016/j.jacc.2009.04.053. PubMed DOI PMC

Brunham L.R., Lansberg P.J., Zhang L., Miao F., Carter C., Hovingh G.K., Visscher H., Jukema J.W., Stalenhoef A.F., Ross C.J., et al. Differential effect of the rs4149056 variant in SLCO1B1 on myopathy associated with simvastatin and atorvastatin. Pharmacogenom. J. 2012;12:233–237. doi: 10.1038/tpj.2010.92. PubMed DOI

Hubáček J.A., Dlouhá D., Adámková V., Zlatohlavek L., Viklický O., Hrubá P., Češka R., Vrablík M. SLCO1B1 polymorphism is not associated with risk of statin-induced myalgia/myopathy in a Czech population. Med. Sci. Monit. 2015;21:1454–1459. PubMed PMC

Swen J., Nijenhuis M., de Boer A., Grandia L., Maitland-van der Zee A., Mulder H., Rongen G., van Schaik R., Schalekamp T., Touw D., et al. Pharmacogenetics: From bench to byte—An update of guidelines. Clin. Pharmacol. Ther. 2011;89:662–673. doi: 10.1038/clpt.2011.34. PubMed DOI

Abi Khalil C. The emerging role of epigenetics in cardiovascular disease. Ther. Adv. Chronic. Dis. 2014;5:178–187. doi: 10.1177/2040622314529325. PubMed DOI PMC

Xu Y., Fang F. Histone methylation and transcriptional regulation in cardiovascular disease. Cardiovasc Hematol. Disord. Drug Targets. 2014;14:89–97. doi: 10.2174/1871529X14666140505122144. PubMed DOI

Kaikkonen M.U., Lam M.T., Glass C.K. Non-coding RNAs as regulators of gene expression and epigenetics. Cardiovasc Res. 2011;90:430–440. doi: 10.1093/cvr/cvr097. PubMed DOI PMC

Obsteter J., Dovc P., Kunej T. Genetic variability of microRNA regulome in human. Mol. Genet. Genomic Med. 2015;3:30–39. doi: 10.1002/mgg3.110. PubMed DOI PMC

Dlouhá D., Hubáček J.A. Regulatory RNAs and cardiovascular disease—With a special focus on circulating microRNAs. Physiol. Res. 2017;66(Suppl. 1):S21–S38. doi: 10.33549/physiolres.933588. PubMed DOI

Wang Z., Luo X., Lu Y., Yang B. MiRNAs at the heart of the matter. J. Mol. Med. 2008;86:771–783. doi: 10.1007/s00109-008-0341-3. PubMed DOI PMC

Laffont B., Rayner K.J. Micrornas in the pathobiology and therapy of atherosclerosis. Can. J. Cardiol. 2017;33:313–324. doi: 10.1016/j.cjca.2017.01.001. PubMed DOI PMC

De Gonzalo-Calvo D., Iglesias-Gutiérrez E., Llorente-Cortés V. Epigenetic biomarkers and cardiovascular disease: Circulating microRnas. Rev. Esp. Cardiol. 2017;70:763–769. doi: 10.1016/j.recesp.2017.02.027. PubMed DOI

Sun T., Dong Y.H., Du W., Shi C.Y., Wang K., Tariq M.A., Wang J.X., Li P.F. The role of microRnas in myocardial infarction: From molecular mechanism to clinical application. Int. J. Mol. Sci. 2017;18:745. doi: 10.3390/ijms18040745. PubMed DOI PMC

Economou E.K., Oikonomou E., Siasos G., Papageorgiou N., Tsalamandris S., Mourouzis K., Papaioanou S., Tousoulis D. The role of micrornas in coronary artery disease: From pathophysiology to diagnosis and treatment. Atherosclerosis. 2015;241:624–633. doi: 10.1016/j.atherosclerosis.2015.06.037. PubMed DOI

Deng S., Wang H., Jia C., Zhu S., Chu X., Ma Q., Wei J., Chen E., Zhu W., Macon C.J., et al. MicroRna-146a induces lineage-negative bone marrow cell apoptosis and senescence by targeting polo-like kinase 2 expression. Arterioscler. Thromb. Vasc. Biol. 2017;37:280–290. doi: 10.1161/ATVBAHA.116.308378. PubMed DOI PMC

Menghini R., Casagrande V., Cardellini M., Martelli E., Terrinoni A., Amati F., Vasa-Nicotera M., Ippoliti A., Novelli G., Melino G., et al. MicroRna 217 modulates endothelial cell senescence via silent information regulator 1. Circulation. 2009;120:1524–1532. doi: 10.1161/CIRCULATIONAHA.109.864629. PubMed DOI

Suarez Y., Wang C., Manes T.D., Pober J.S. Cutting edge: TNF-induced microRNAs regulate TNF-induced expression of e-selectin and intercellular adhesion molecule-1 on human endothelial cells: Feedback control of inflammation. J. Immunol. 2010;184:21–25. doi: 10.4049/jimmunol.0902369. PubMed DOI PMC

Asgeirsdottir S.A., Van Solingen C., Murniati N.F., Zwiers P.J., Heeringa P., Van Meurs M., Satchell S.C., Saleem M.A., Mathieson P.W., Banas B., et al. MicroRna-126 contributes to renal macrovascular heterogeneity of vcam-1 protein expression in acute inflammation. Am. J. Physiol. Renal. Physiol. 2012;302:F1630–F1639. doi: 10.1152/ajprenal.00400.2011. PubMed DOI

Kumar S., Williams D., Sur S., Wang J.Y., Jo H. Role of flow-sensitive microRNAs and long noncoding RNAs in vascular dysfunction and atherosclerosis. Vascul. Pharmacol. 2019;114:76–92. doi: 10.1016/j.vph.2018.10.001. PubMed DOI PMC

Zampetaki A., Dudek K., Mayr M. Oxidative Stress in Atherosclerosis: The role of microRnas in arterial remodeling. Free Radic. Biol. Med. 2013;64:69–77. doi: 10.1016/j.freeradbiomed.2013.06.025. PubMed DOI

Lu Y., Thavarajah T., Gu W., Cai J., Xu Q. Impact of miRna in atherosclerosis. Arterioscler. Thromb. Vasc. Biol. 2018;38:E159–E170. doi: 10.1161/ATVBAHA.118.310227. PubMed DOI PMC

Huang R.S., Hu G.Q., Lin B., Lin Z.Y., Sun C.C. MicroRNA-155 silencing enhances inflammatory response and lipid uptake in oxidized low-density lipoprotein-stimulated human THP-1 macrophages. J. Investig. Med. 2010;58:961–967. doi: 10.2310/JIM.0b013e3181ff46d7. PubMed DOI

Chen T., Huang Z., Wang L., Wang Y., Wu F., Meng S., Wang C. MicroRNA-125a-5p partly regulates the inflammatory response, lipid uptake, and ORP9 expression in oxLDL-stimulated monocyte/macrophages. Cardiovasc. Res. 2009;83:131–139. doi: 10.1093/cvr/cvp121. PubMed DOI

Fernández-Hernando C., Suárez Y., Rayner K.J., Moore K.J. MicroRnas in lipid metabolism. Curr. Opin. Lipidol. 2011;22:86–92. doi: 10.1097/MOL.0b013e3283428d9d. PubMed DOI PMC

Rotllan N., Price N., Pati P., Goedeke L., Fernández-Hernando C. MicroRNAs in lipoprotein metabolism and cardiometabolic disorders. Atherosclerosis. 2016;246:352–360. doi: 10.1016/j.atherosclerosis.2016.01.025. PubMed DOI PMC

Dlouha D., Blaha M., Blaha V., Fatorova I., Hubacek J.A., Stavek P., Lanska V., Parikova A., Pitha J. Analysis of circulating miRNAs in patients with familial hypercholesterolaemia treated by LDL/Lp(a) apheresis. Atheroscler. Suppl. 2017;30:128–134. doi: 10.1016/j.atherosclerosissup.2017.05.037. PubMed DOI

Zampetaki A., Willeit P., Drozdov I., Kiechl S., Mayr M. Profiling of circulating microRNAs: From single biomarkers to re-wired networks. Cardiovasc Res. 2012;93:555–562. doi: 10.1093/cvr/cvr266. PubMed DOI PMC

Prasher D., Greenway S.C., Singh R.B. The impact of epigenetics on cardiovascular disease. Biochem. Cell. Biol. 2020;98:12–22. doi: 10.1139/bcb-2019-0045. PubMed DOI

Wilson A.G. Epigenetic regulation of gene expression in the inflammatory response and relevance to common diseases. J. Periodontol. 2008;79:1514–1519. doi: 10.1902/jop.2008.080172. PubMed DOI

Sae-Lee C., Corsi S., Barrow T.M., Kuhnle G.G.C., Bollati V., Mathers J.C., Byun H.M. Dietary intervention modifies DNA methylation age assessed by the epigenetic clock. Mol. Nutr. Food Res. 2018;62:e1800092. doi: 10.1002/mnfr.201800092. PubMed DOI

Agha G., Mendelson M.M., Ward-Caviness C.K., Joehanes R., Huan T., Gondalia R., Salfati E., Brody J.A., Fiorito G., Bressler J., et al. Blood leukocyte DNA methylation predicts risk of future myocardial infarction and coronary heart disease. Circulation. 2019;140:645–657. doi: 10.1161/CIRCULATIONAHA.118.039357. PubMed DOI PMC

Talens R.P., Jukema J.W., Trompet S., Kremer D., Westendorp R.G., Lumey L.H., Sattar N., Putter H., Slagboom P.E., Heijmans B.T., et al. Hypermethylation at loci sensitive to the prenatal environment is associated with increased incidence of myocardial infarction. Int. J. Epidemiol. 2012;41:106–115. doi: 10.1093/ije/dyr153. PubMed DOI PMC

Pfeiffer L., Wahl S., Pilling L.C., Reischl E., Sandling J.K., Kunze S., Holdt L.M., Kretschmer A., Schramm K., Adamski J., et al. DNA methylation of lipid-related genes affects blood lipid levels. Circ. Cardiovasc. Genet. 2015;8:334–342. doi: 10.1161/CIRCGENETICS.114.000804. PubMed DOI PMC

López-Otín C., Blasco M.A., Partridge L., Serrano M., Kroemer G. The hallmarks of aging. Cell. 2013;153:1194–1217. doi: 10.1016/j.cell.2013.05.039. PubMed DOI PMC

Pusceddu I., Kleber M., Delgado G., Herrmann W., März W., Herrmann M. Telomere length and mortality in the Ludwigshafen Risk and Cardiovascular Health study. PLoS ONE. 2018;13:e0198373. doi: 10.1371/journal.pone.0198373. PubMed DOI PMC

Arbeev K.G., Verhulst S., Steenstrup T., Kark J.D., Bagley O., Kooperberg C., Reiner A.P., Hwang S.J., Levy D., Fitzpatrick A.L., et al. Association of leukocyte telomere length with mortality among adult participants in 3 longitudinal studies. JAMA Netw. Open. 2020;3:e200023. doi: 10.1001/jamanetworkopen.2020.0023. PubMed DOI PMC

Mundstock E., Sarria E.E., Zatti H., Mattos Louzada F., Kich Grun L., Herbert Jones M., Guma F.T., Mazzola I.M.J., Epifanio M., Stein R.T., et al. Effect of obesity on telomere length: Systematic review and meta-analysis. Obesity. 2015;23:2165–2174. doi: 10.1002/oby.21183. PubMed DOI

Tellechea M.L., Pirola C.J. The impact of hypertension on leukocyte telomere length: A systematic review and meta-analysis of human studies. J. Hum. Hypertens. 2017;31:99–105. doi: 10.1038/jhh.2016.45. PubMed DOI

Koriath M., Müller C., Pfeiffer N., Nickels S., Beutel M., Schmidtmann I., Rapp S., Münzel T., Westermann D., Karakas M., et al. Relative telomere length and cardiovascular risk factors. Biomolecules. 2019;9:192. doi: 10.3390/biom9050192. PubMed DOI PMC

Yang C., Zhang M., Niu W., Yang R., Zhang Y., Qiu Z., Sun B., Zhao Z. Analysis of DNA methylation in various swine tissues. PLoS ONE. 2011;6:e16229. doi: 10.1371/journal.pone.0016229. PubMed DOI PMC

Dlouha D., Maluskova J., Kralova Lesna I., Lanska V., Hubacek J.A. Comparison of the relative telomere length measured in leukocytes and eleven different human tissues. Physiol. Res. 2014;63(Suppl. 3):S343–S350. doi: 10.33549/physiolres.932856. PubMed DOI

Jiang R., Jones M.J., Chen E., Neumann S.M., Fraser H.B., Miller G.E., Kobor M.S. Discordance of DNA methylation variance between two accessible human tissues. Sci. Rep. 2015;5:8257. doi: 10.1038/srep08257. PubMed DOI PMC

Estrella M.M., Parekh R.S. The expanding role of APOL1 risk in chronic kidney disease and cardiovascular disease. Semin. Nephrol. 2017;37:520–529. doi: 10.1016/j.semnephrol.2017.07.005. PubMed DOI

Vanhamme L., Paturiaux-Hanocq F., Poelvoorde P., Nolan D.P., Lins L., Van Den Abbeele J., Pays A., Tebabi P., Van Xong H., Jacquet A., et al. Apolipoprotein L-I is the trypanosome lytic factor of human serum. Nature. 2003;422:83–87. doi: 10.1038/nature01461. PubMed DOI

Hubacek J.A. Apolipoprotein A5 fifteen years anniversary: Lessons from genetic epidemiology. Gene. 2016;592:193–199. doi: 10.1016/j.gene.2016.07.070. PubMed DOI PMC

Hubáček J.A., Šedová L., Olišarová V., Adámková V., Tóthová V. Different prevalence of T2DM risk alleles in Roma population in comparison with the majority Czech population. Mol. Genet. Genom. Med. 2020;8:e1361. doi: 10.1002/mgg3.1361. PubMed DOI PMC

Werissa N.A., Piko P., Fiatal S., Kosa Z., Sandor J., Adany R. SNP-based genetic risk score modeling suggests no increased genetic susceptibility of the Roma population to type 2 diabetes mellitus. Genes. 2019;10:942. doi: 10.3390/genes10110942. PubMed DOI PMC

Dick D.M., Bierut L.J. The genetics of alcohol dependence. Curr. Psychiatry Rep. 2006;8:151–157. doi: 10.1007/s11920-006-0015-1. PubMed DOI

Borinskaya S., Kal’ina N., Marusin A., Faskhutdinova G., Morozova I., Kutuev I., Koshechkin V., Khusnutdinova E., Stepanov V., Puzyrev V., et al. Distribution of the alcohol dehydrogenase ADH1B*47His allele in Eurasia. Am. J. Hum. Genet. 2009;84:89–92. doi: 10.1016/j.ajhg.2008.12.007. PubMed DOI PMC

Hopkins P.N., Williams R.R. A survey of 246 suggested coronary risk factors. Atherosclerosis. 1981;40:1–52. doi: 10.1016/0021-9150(81)90122-2. PubMed DOI

Authors/Task Force Members. ESC Committee for Practice Guidelines (CPG) ESC National Cardiac Societies 2019 ESC/EAS guidelines for the management of dyslipidaemias: Lipid modification to reduce cardiovascular risk. Atherosclerosis. 2019;290:140–205. Erratum in: Atherosclerosis2020, 292, 160–162. Erratum in: Atherosclerosis2020, 294, 80–82. PubMed

Graziano F., Biino G., Bonati M.T., Neale B.M., Do R., Concas M.P., Vaccargiu S., Pirastu M., Terradura-Vagnarelli O., Cirillo M., et al. Estimation of metabolic syndrome heritability in three large populations including full pedigree and genomic information. Hum. Genet. 2019;138:739–748. doi: 10.1007/s00439-019-02024-6. PubMed DOI

Taron M., Llerena A., Manolopoulos V.G., Rodriguez-Antona C., Stankovic S., van Schaik R.H.N. The need of the clinical implementation of pharmacogenetics in European health services for routine drug prescription. What’s next? An urgent clinical unmet need for patients. Drug Metab. Pers. Ther. 2020 doi: 10.1515/dmdi-2020-0172. in press. PubMed DOI

Merched A.J., Chan L. Nutrigenetics and nutrigenomics of atherosclerosis. Curr. Atheroscler. Rep. 2013;15:328. doi: 10.1007/s11883-013-0328-6. PubMed DOI PMC

Lovegrove J.A., Gitau R. Personalized nutrition for the prevention of cardiovascular disease: A future perspective. J. Hum. Nutr. Diet. 2008;21:306–316. doi: 10.1111/j.1365-277X.2008.00889.x. PubMed DOI

Di Renzo L., Gualtieri P., Romano L., Marrone G., Noce A., Pujia A., Perrone M.A., Aiello V., Colica C., De Lorenzo A. Role of personalized nutrition in chronic-degenerative diseases. Nutrients. 2019;11:1707. doi: 10.3390/nu11081707. PubMed DOI PMC

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