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Investigating the genetic characteristics of CAD: Is there a role for myocardial perfusion imaging techniques?

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  • Published:
Journal of Nuclear Cardiology Aims and scope

Abstract

Several environmental and genetic factors have been found to influence the development and progression of coronary artery disease (CAD). Although the effects of the environmental hazards on CAD pathophysiology are well documented, the genetic architecture of the disease remains quite unclear. A number of single-nucleotide polymorphisms have been identified based on the results of the genome-wide association studies. However, there is a lack of strong evidence regarding molecular causality. The minority of the reported predisposing variants can be related to the conventional risk factors of CAD, while most of the polymorphisms occur in non-protein-coding regions of the DNA. However, independently of the specific underlying mechanisms, genetic information could lead to the identification of a population at higher genetic risk for the long-term development of CAD. Myocardial single-photon emission computed tomography (SPECT) and positron emission tomography (PET) are functional imaging techniques that can evaluate directly myocardial perfusion, and detect vascular and/or endothelial dysfunction. Therefore, these techniques could have a role in the investigation of the underlying mechanisms associated with the identified predisposing variants, advancing our understanding regarding molecular causality. In the population at higher genetic risk, myocardial SPECT or PET could provide important evidence through the early depiction of sub-clinical dysfunctions, well before any atherosclerosis marker could be identified. Notably, SPECT and PET techniques have been already used for the investigation of the functional consequences of several CAD-related polymorphisms, as well as the response to certain treatments (statins). Furthermore, therefore, in the clinical setting, the combination of genetic evidence with the findings of myocardial SPECT, or PET, functional imaging techniques could lead to more efficient screening methods and may improve decision making with regard to the diagnostic investigation and patients’ management.

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Abbreviations

CAD:

Coronary artery disease

GRS:

Genetic risk score

GWAS:

Genome-wide association studies

PET:

Positron emission tomography

SNP:

Single-nucleotide polymorphism

SPECT:

Single-photon emission computed tomography

References

  1. Hao YD, Ohene BE, Yang SW, Zhou YJ. First-degree relatives with similar phenotypic characterisation of acute myocardial infarction: A case report and review of the literature. BMC Cardiovasc Disord 2019;19:314.

    Article  Google Scholar 

  2. Dai X, Wiernek S, Evans JP, Runge MS. Genetics of coronary artery disease and myocardial infarction. World J Cardiol 2016;8:1-23.

    Article  CAS  Google Scholar 

  3. Karunathilake SP, Ganegoda GU. Secondary prevention of cardiovascular diseases and application of technology for early diagnosis. Biomed Res Int 2018;2018:5767864.

    Article  Google Scholar 

  4. Liu B, Wang L, Jiang W, Xiong Y, Pang L, Zhong Y, et al. Myocyte enhancer factor 2A delays vascular endothelial cell senescence by activating the PI3K/p-Akt/SIRT1 pathway. Aging (Albany NY) 2019;11:3768-84.

    Article  CAS  Google Scholar 

  5. InanloorRhatloo K, Zand Parsa AF, Huse K, Rasooli P, Davaran S, Platzer M, et al. Mutation in CYP27A1 identified in family with coronary artery disease. Eur J Med Genet 2013;56:655-60.

    Article  Google Scholar 

  6. InanlooRahatloo K, Parsa AF, Huse K, Rasooli P, Davaran S, Platzer M, et al. Mutation in ST6GALNAC5 identified in family with coronary artery disease. Sci Rep 2014;4:3595.

    Article  Google Scholar 

  7. Riveros-Mckay F, Oliver-Williams C, Karthikeyan S, Walter K, Kundu K, Ouwehand WH, et al. The influence of rare variants in circulating metabolic biomarkers. PLoS Genet 2020;16:e1008605.

    Article  CAS  Google Scholar 

  8. Veljkovic N, Zaric B, Djuric I, et al. Genetic markers for coronary artery disease. Medicina (Kaunas) 2018;54:36.

    Article  Google Scholar 

  9. Abifadel M, Varret M, Rabès JP, et al. Mutations in PCSK9 cause autosomal dominant hypercholesterolemia. Nat Genet 2003;34:154-6.

    Article  CAS  Google Scholar 

  10. Roberts R, Campillo A, Schmitt M. Prediction and management of CAD risk based on genetic stratification. Trends Cardiovasc Med 2019;S1050-1738(19)30115-X.

  11. Shadrina AS, Shashkova TI, Torgasheva AA, Sharapov SZ, Klarić L, Pakhomov ED, et al. Prioritization of causal genes for coronary artery disease based on cumulative evidence from experimental and in silico studies. Sci Rep 2020;10:10486.

    Article  CAS  Google Scholar 

  12. Tibaut M, Caprnda M, Kubatka P, Sinkovič A, Valentova V, Filipova S, et al. Markers of atherosclerosis: Part 2: Genetic and imaging markers. Heart Lung Circ 2019;28:678-89.

    Article  Google Scholar 

  13. Marie PY, Visvikis-Siest S. Do we need diagnostic strategies enhanced with genetic information for ischemic heart disease? J Nucl Cardiol 2019;26:1309-12.

    Article  Google Scholar 

  14. Abraham G, Havulinna AS, Bhalala OG, et al. Genomic prediction of coronary heart disease. Eur Heart J 2016;37:3267-78.

    Article  CAS  Google Scholar 

  15. Leopold JA. Microvascular dysfunction: Genetic polymorphisms suggest sex-specific differences in disease phenotype. Coron Artery Dis 2014;25:275-6.

    Article  Google Scholar 

  16. Kunnas TA, Lehtimäki T, Laaksonen R, et al. Endothelial nitric oxide synthase genotype modulates the improvement of coronary blood flow by pravastatin: A placebo-controlled PET study. J Mol Med (Berl) 2002;80:802-7.

    Article  CAS  Google Scholar 

  17. Lehtimäki T, Laaksonen R, Janatuinen T, et al. Interleukin-1B genotype modulates the improvement of coronary artery reactivity by lipid-lowering therapy with pravastatin: a placebo-controlled positron emission tomography study in young healthy men. Pharmacogenetics 2003;13:633-9.

    Article  Google Scholar 

  18. Aittoniemi J, Fan YM, Laaksonen R, et al. The effect of mannan-binding lectin variant alleles on coronary artery reactivity in healthy young men. Int J Cardiol 2004;97:317-8.

    Article  Google Scholar 

  19. Ilveskoski E, Lehtimäki T, Laaksonen R, et al. Improvement of myocardial blood flow by lipid-lowering therapy with pravastatin is modulated by apolipoprotein E genotype. Scand J Clin Lab Invest 2007;67:723-34.

    Article  CAS  Google Scholar 

  20. Kim MP, Wahl LM, Yanek LR, et al. A monocyte chemoattractant protein-1 gene polymorphism is associated with occult ischemia in a high-risk asymptomatic population. Atherosclerosis 2007;193:366-72.

    Article  CAS  Google Scholar 

  21. Georgoulias P, Wozniak G, Samara M, et al. Impact of ACE and ApoE polymorphisms on myocardial perfusion: correlation with myocardial single photon emission computed tomographic imaging. J Hum Genet 2009;54:595-602.

    Article  CAS  Google Scholar 

  22. Acampa W, Di Taranto MD, Morgante A, et al. C-reactive protein levels are associated with paraoxonase polymorphism L55M in patients undergoing cardiac SPECT imaging. Scand J Clin Lab Invest 2011;71:179-84.

    Article  CAS  Google Scholar 

  23. Dunet V, Ruiz J, Allenbach G, et al. Effects of paraoxonase activity and gene polymorphism on coronary vasomotion. EJNMMI Res 2011;1:27.

    Article  Google Scholar 

  24. Satra M, Samara M, Wozniak G, et al. Sequence variations in the FII, FV, F13A1, FGB and PAI-1 genes are associated with differences in myocardial perfusion. Pharmacogenomics 2011;12:195-203.

    Article  CAS  Google Scholar 

  25. Angelidis G, Samara M, Papathanassiou M, et al. Impact of renin-angiotensin-aldosterone system polymorphisms on myocardial perfusion: Correlations with myocardial single photon emission computed tomography-derived parameters. J Nucl Cardiol 2019;26:1298-308.

    Article  Google Scholar 

  26. Yang E, Vargas JD, Bluemke DA. Understanding the genetics of coronary artery disease through the lens of noninvasive imaging. Expert Rev Cardiovasc Ther 2012;10:27-36.

    Article  Google Scholar 

  27. Phelps CE, O’Sullivan AK, Ladapo JA, et al. Cost effectiveness of a gene expression score and myocardial perfusion imaging for diagnosis of coronary artery disease. Am Heart J 2014;167:697-706.e2.

    Article  Google Scholar 

  28. Ronan G, Wolk MJ, Bailey SR, Doherty JU, Douglas PS, Hendel RC, et al. ACCF/AHA/ASE/ASNC/HFSA/HRS/SCAI/SCCT/SCMR/STS 2013 multimodality appropriate use criteria for the detection and risk assessment of stable ischemic heart disease: A report of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, American Heart Association, American Society of Echocardiography, American Society of Nuclear Cardiology, Heart Failure Society of America, Heart Rhythm Society, Society for Cardiovascular Angiography and Interventions, Society of Cardiovascular Computed Tomography, Society for Cardiovascular Magnetic Resonance, and Society of Thoracic Surgeons. J Nucl Cardiol 2014;21:192-220.

    Article  Google Scholar 

  29. Stillman AE, Oudkerk M, Bluemke DA, et al. Imaging the myocardial ischemic cascade. Int J Cardiovasc Imaging 2018;34:1249-63.

    Article  Google Scholar 

  30. Lee SH, Shin DJ, Jang Y. Personalized medicine in coronary artery disease: Insights from genomic research. Korean Circ J 2009;39:129-37.

    Article  CAS  Google Scholar 

  31. Dainis AM, Ashley EA. Cardiovascular precision medicine in the genomics era. JACC Basic Transl Sci 2018;3:313-26.

    Article  Google Scholar 

  32. Ndiaye NC, Azimi Nehzad M, El Shamieh S, et al. Cardiovascular diseases and genome-wide association studies. Clin Chim Acta 2011;412:1697-701.

    Article  CAS  Google Scholar 

  33. Marian AJ, Belmont J. Strategic approaches to unraveling genetic causes of cardiovascular diseases. Circ Res 2011;108:1252-69.

    Article  CAS  Google Scholar 

  34. Ballestar E. An introduction to epigenetics. Adv Exp Med Biol 2011;711:1-11.

    Article  CAS  Google Scholar 

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Disclosures

The authors George Angelidis, Varvara Valotassiou, Maria Satra, Dimitrios Psimadas, John Koutsikos, John Skoularigis, Panagoula Kollia, and Panagiotis Georgoulias have nothing to declare.

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Correspondence to G. Angelidis MD, PhD.

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Angelidis, G., Valotassiou, V., Satra, M. et al. Investigating the genetic characteristics of CAD: Is there a role for myocardial perfusion imaging techniques?. J. Nucl. Cardiol. 29, 2909–2916 (2022). https://doi.org/10.1007/s12350-020-02403-x

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  • DOI: https://doi.org/10.1007/s12350-020-02403-x

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