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Motivation, Perception, and Treatment Beliefs in the Myocardial Infarction Genes (MI-GENES) Randomized Clinical Trial

  • Original Research
  • Published:
Journal of Genetic Counseling

Abstract

Little is known about individuals’ motivation, perception, and treatment beliefs towards the use of genetic information in risk estimates for coronary heart disease (CHD). In this study, participants at intermediate 10-year risk of CHD were randomized to receive either their estimated conventional risk score (CRS) alone, or a CRS and a genetic risk score (GRS), by a genetic counselor. Surveys on motivation to participate in and perception of genetic testing for CHD were administered at 3 months and treatment beliefs at 6 months following risk disclosure. Survey responses used Likert scales. Linear and logistic regression were used for analysis. Overall, motivation to participate in genomic clinical trials was favorable and did not differ between the CRS and GRS groups (16.95 ± 0.82 vs. 17.58 ± 0.83, p = 0.091), but participants who initially received their GRS indicated a greater desire to find ways to improve health as a reason for participation (OR: 0.53 (95%CI: 0.29, 0.94), p = 0.028). Perception of genetic testing was also favorable in both groups (15.29 ± 0.39 vs. 15.12 ± 0.40, p = 0.835). Participants who initially received their GRS were more inclined to recommend genetic testing to family and friends (9.95 ± 1.88 vs. 10.52 ± 2.17, p = 0.023). In the MI-GENES study, motivation to participate in and perception of genetic testing among study participants were overall favorable. Genetic risk disclosure was associated with increased motivation to recommend genetic testing to family and friends.

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References

  • Blanchette, P. S., Spreafico, A., Miller, F. A., Chan, K., Bytautas, J., Kang, S., et al. (2014). Genomic testing in cancer: Patient knowledge, attitudes, and expectations. Cancer, 120(19), 3066–3073. doi:10.1002/cncr.28807.

    Article  PubMed  Google Scholar 

  • Branstrom, R., Kasparian, N. A., Affleck, P., Tibben, A., Chang, Y. M., Azizi, E., et al. (2012). Perceptions of genetic research and testing among members of families with an increased risk of malignant melanoma. European Journal of Cancer, 48(16), 3052–3062. doi:10.1016/j.ejca.2012.05.017.

    Article  PubMed  Google Scholar 

  • Brautbar, A., Pompeii, L. A., Dehghan, A., Ngwa, J. S., Nambi, V., Virani, S. S., et al. (2012). A genetic risk score based on direct associations with coronary heart disease improves coronary heart disease risk prediction in the atherosclerosis risk in communities (ARIC), but not in the Rotterdam and Framingham offspring, studies. Atherosclerosis, 223(2), 421–426. doi:10.1016/j.atherosclerosis.2012.05.035.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Burns, C., McGaughran, J., Davis, A., Semsarian, C., & Ingles, J. (2016). Factors influencing uptake of familial long QT syndrome genetic testing. Am J Med Genet A, 170a(2), 418–425. doi:10.1002/ajmg.a.37455.

    Article  PubMed  Google Scholar 

  • Calsbeek, H., Morren, M., Bensing, J., & Rijken, M. (2007). Knowledge and attitudes towards genetic testing: A two year follow-up study in patients with asthma, diabetes mellitus and cardiovascular disease. Journal of Genetic Counseling, 16(4), 493–504. doi:10.1007/s10897-006-9085-9.

    Article  PubMed  Google Scholar 

  • Chan, L., & Boerwinkle, E. (1994). Gene-environment interactions and Gene therapy in atherosclerosis. Cardiology in Review, 2(3), 7.

    Article  Google Scholar 

  • Christiaans, I., Birnie, E., Bonsel, G. J., Wilde, A. A., & van Langen, I. M. (2008). Uptake of genetic counselling and predictive DNA testing in hypertrophic cardiomyopathy. European Journal of Human Genetics, 16(10), 1201–1207. doi:10.1038/ejhg.2008.92.

    Article  PubMed  Google Scholar 

  • Clarke, V. A., Lovegrove, H., Williams, A., & Machperson, M. (2000). Unrealistic optimism and the health belief model. Journal of Behavioral Medicine, 23(4), 367–376.

    Article  CAS  PubMed  Google Scholar 

  • Collins, F. S., & Varmus, H. (2015). A new initiative on precision medicine. The New England Journal of Medicine, 372(9), 793–795. doi:10.1056/NEJMp1500523.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Collins, R. E., Wright, A. J., & Marteau, T. M. (2011). Impact of communicating personalized genetic risk information on perceived control over the risk: A systematic review. Genetics in Medicine, 13(4), 273–277. doi:10.1097/GIM.0b013e3181f710ca.

    Article  PubMed  Google Scholar 

  • Daly, M. B., Montgomery, S., Bingler, R., & Ruth, K. (2016). Communicating genetic test results within the family: Is it lost in translation? A survey of relatives in the randomized six-step study. Familial Cancer, 15(4), 697–706. doi:10.1007/s10689-016-9889-1.

    Article  PubMed  PubMed Central  Google Scholar 

  • Deloukas, P., Kanoni, S., Willenborg, C., Farrall, M., Assimes, T. L., Thompson, J. R., et al. (2013). Large-scale association analysis identifies new risk loci for coronary artery disease. Nature Genetics, 45(1), 25–33. doi:10.1038/ng.2480.

    Article  CAS  PubMed  Google Scholar 

  • Ding, K., Bailey, K. R., & Kullo, I. J. (2011). Genotype-informed estimation of risk of coronary heart disease based on genome-wide association data linked to the electronic medical record. BMC Cardiovascular Disorders, 11, 66. doi:10.1186/1471-2261-11-66.

    Article  PubMed  PubMed Central  Google Scholar 

  • Erdmann, J., Grosshennig, A., Braund, P. S., König, I. R., Hengstenberg, C., Hall, A. S., et al. (2009). New susceptibility locus for coronary artery disease on chromosome 3q22.3. Nature Genetics, 41(3), 280–282. doi:10.1038/ng.307.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Erskine, K. E., Hidayatallah, N. Z., Walsh, C. A., McDonald, T. V., Cohen, L., Marion, R. W., & Dolan, S. M. (2014). Motivation to pursue genetic testing in individuals with a personal or family history of cardiac events or sudden cardiac death. Journal of Genetic Counseling, 23(5), 849–859. doi:10.1007/s10897-014-9707-6.

    Article  PubMed  PubMed Central  Google Scholar 

  • Facio, F. M., Brooks, S., Loewenstein, J., Green, S., Biesecker, L. G., & Biesecker, B. B. (2011). Motivators for participation in a whole-genome sequencing study: Implications for translational genomics research. European Journal of Human Genetics, 19(12), 1213–1217. doi:10.1038/ejhg.2011.123.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Farrall, M., Green, F. R., Peden, J. F., Olsson, P. G., Clarke, R., Hellenius, M. L., et al. (2006). Genome-wide mapping of susceptibility to coronary artery disease identifies a novel replicated locus on chromosome 17. PLoS Genetics, 2(5), e72. doi:10.1371/journal.pgen.0020072.

    Article  PubMed  PubMed Central  Google Scholar 

  • Finegold, J. A., Asaria, P., & Francis, D. P. (2013). Mortality from ischaemic heart disease by country, region, and age: Statistics from World Health Organisation and United Nations. International Journal of Cardiology, 168(2), 934–945. doi:10.1016/j.ijcard.2012.10.046.

    Article  PubMed  PubMed Central  Google Scholar 

  • Finlay, E., Stopfer, J. E., Burlingame, E., Evans, K. G., Nathanson, K. L., Weber, B. L., et al. (2008). Factors determining dissemination of results and uptake of genetic testing in families with known BRCA1/2 mutations. Genetic Testing, 12(1), 81–91. doi:10.1089/gte.2007.0037.

    Article  PubMed  PubMed Central  Google Scholar 

  • Freedman, B. I., Fletcher, A. J., Sanghani, V. R., Spainhour, M., Graham, A. W., Russell, G. B., et al. (2013). Perceptions regarding genetic testing in populations at risk for nephropathy. American Journal of Nephrology, 38(6), 453–457. doi:10.1159/000356244.

    Article  PubMed  PubMed Central  Google Scholar 

  • Ganna, A., Magnusson, P. K., Pedersen, N. L., de Faire, U., Reilly, M., Arnlöv, J., et al. (2013). Multilocus genetic risk scores for coronary heart disease prediction. Arteriosclerosis, Thrombosis, and Vascular Biology, 33(9), 2267–2272. doi:10.1161/ATVBAHA.113.301218.

    Article  CAS  PubMed  Google Scholar 

  • Goldstein, B., Knowles, J., Salfati, E., Ioannidis, J., & Assimes, T. (2014). Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example. Frontiers in Genetics, 5.

  • Gollust, S. E., Gordon, E. S., Zayac, C., Griffin, G., Christman, M. F., Pyeritz, R. E., et al. (2012). Motivations and perceptions of early adopters of personalized genomics: Perspectives from research participants. Public Health Genomics, 15(1), 22–30. doi:10.1159/000327296.

    Article  CAS  PubMed  Google Scholar 

  • Grant, R. W., Hivert, M., Pandiscio, J. C., Florez, J. C., Nathan, D. M., & Meigs, J. B. (2009). The clinical application of genetic testing in type 2 diabetes: A patient and physician survey. Diabetologia, 52(11), 2299–2305. doi:10.1007/s00125-009-1512-7.

    Article  CAS  PubMed  Google Scholar 

  • Gupte, M., Alcalay, R. N., Mejia-Santana, H., Raymond, D., Saunders-Pullman, R., Roos, E., et al. (2015). Interest in genetic testing in Ashkenazi Jewish Parkinson's disease patients and their unaffected relatives. Journal of Genetic Counseling, 24(2), 238–246. doi:10.1007/s10897-014-9756-x.

    Article  PubMed  Google Scholar 

  • Haga, S. B., Barry, W. T., Mills, R., Ginsburg, G. S., Svetkey, L., Sullivan, J., & Willard, H. F. (2013). Public knowledge of and attitudes toward genetics and genetic testing. Genetic Testing and Molecular Biomarkers, 17(4), 327–335. doi:10.1089/gtmb.2012.0350.

    Article  PubMed  PubMed Central  Google Scholar 

  • Hall, M. J., Forman, A. D., Montgomery, S. V., Rainey, K. L., & Daly, M. B. (2015). Understanding patient and provider perceptions and expectations of genomic medicine. Journal of Surgical Oncology, 111, 9–17. doi:10.1002/jso.23712.

    Article  PubMed  Google Scholar 

  • Hardcastle, S. J., Legge, E., Laundy, C. S., Egan, S. J., French, R., Watts, G. F., & Hagger, M. S. (2015). Patients' perceptions and experiences of familial hypercholesterolemia, cascade genetic screening and treatment. International Journal of Behavioral Medicine, 22(1), 92–100. doi:10.1007/s12529-014-9402-x.

    Article  PubMed  Google Scholar 

  • Henneman, L., Vermeulen, E., van El, C. G., Claassen, L., Timmermans, D. R., & Cornel, M. C. (2013). Public attitudes towards genetic testing revisited: Comparing opinions between 2002 and 2010. European Journal of Human Genetics, 21(8), 793–799. doi:10.1038/ejhg.2012.271.

    Article  PubMed  Google Scholar 

  • Kammin, T., Fenton, A. K., & Thirlaway, K. (2015). A genetic lung cancer susceptibility test may have a positive effect on smoking cessation. Journal of Genetic Counseling, 24(3), 522–531. doi:10.1007/s10897-014-9766-8.

    Article  PubMed  Google Scholar 

  • Katapodi, M. C., Dodd, M. J., Facione, N. C., Humphreys, J. C., & Lee, K. A. (2010). Why some women have an optimistic or a pessimistic bias about their breast cancer risk: Experiences, heuristics, and knowledge of risk factors. Cancer Nursing, 33(1), 64–73. doi:10.1097/NCC.0b013e3181b430f9.

    Article  PubMed  Google Scholar 

  • Kraft, P., & Hunter, D. J. (2009). Genetic risk prediction--are we there yet? The New England Journal of Medicine, 360(17), 1701–1703. doi:10.1056/NEJMp0810107.

    Article  CAS  PubMed  Google Scholar 

  • Kullo, I. J., & Cooper, L. T. (2010). Early identification of cardiovascular risk using genomics and proteomics. Nature Reviews. Cardiology, 7(6), 309–317. doi:10.1038/nrcardio.2010.53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kullo, I. J., Jouni, H., Olson, J. E., Montori, V. M., & Bailey, K. R. (2015). Design of a randomized controlled trial of disclosing genomic risk of coronary heart disease: The myocardial infarction genes (MI-GENES) study. BMC Medical Genomics, 8(1), 51. doi:10.1186/s12920-015-0122-0.

    Article  PubMed  PubMed Central  Google Scholar 

  • Kullo, I. J., Jouni, H., Austin, E. E., Brown, S. A., Kruisselbrink, T. M., Isseh, I. N., et al. (2016). Incorporating a genetic risk score into coronary heart disease risk estimates: Effect on LDL cholesterol levels (the MIGENES clinical trial). Circulation. doi:10.1161/circulationaha.115.020109.

    PubMed Central  Google Scholar 

  • Leenen, C. H., Heijer, M., van der Meer, C., Kuipers, E. J., van Leerdam, M. E., & Wagner, A. (2016). Genetic testing for lynch syndrome: Family communication and motivation. Familial Cancer, 15(1), 63–73. doi:10.1007/s10689-015-9842-8.

    Article  CAS  PubMed  Google Scholar 

  • Lloyd-Jones, D. M., Nam, B. H., D'Agostino Sr., R. B., Levy, D., Murabito, J. M., Wang, T. J., et al. (2004). Parental cardiovascular disease as a risk factor for cardiovascular disease in middle-aged adults: A prospective study of parents and offspring. JAMA, 291(18), 2204–2211. doi:10.1001/jama.291.18.2204.

    Article  CAS  PubMed  Google Scholar 

  • Marenberg, M., Risch, N., Berkman, L., Floderus, B., & Faire, U. d. (1994). Genetic susceptibility to death from coronary heart disease in a study of twins. The New England Journal of Medicine, 330(15), 1041–1046.

    Article  CAS  PubMed  Google Scholar 

  • Marteau, T. M., French, D. P., Griffin, S. J., Prevost, A. T., Sutton, S., Watkinson, C.,. .. Hollands, G. J. (2010). Effects of communicating DNA-based disease risk estimates on risk-reducing behaviours. Cochrane Database Syst Rev(10), Cd007275. doi:10.1002/14651858.CD007275.pub2

  • McGuire, A. L., Diaz, C. M., Wang, T., & Hilsenbeck, S. G. (2009). Social networkers' attitudes toward direct-to-consumer personal genome testing. The American Journal of Bioethics, 9(6–7), 3–10. doi:10.1080/15265160902928209.

    Article  PubMed  PubMed Central  Google Scholar 

  • Mega, J. L., Stitziel, N. O., Smith, J. G., Chasman, D. I., Caulfield, M. J., Devlin, J. J., et al. (2015). Genetic risk, coronary heart disease events, and the clinical benefit of statin therapy: An analysis of primary and secondary prevention trials. Lancet, 385(9984), 2264–2271. doi:10.1016/S0140-6736(14)61730-X.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Nikpay, M., Goel, A., Won, H. H., Hall, L. M., Willenborg, C., Kanoni, S., et al. (2015). A comprehensive 1,000 genomes-based genome-wide association meta-analysis of coronary artery disease. Nature Genetics, 47(10), 1121–1130. doi:10.1038/ng.3396.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Petrie, K. J., Weinman, J., Sharpe, N., & Buckley, J. (1996). Role of patients' view of their illness in predicting return to work and functioning after myocardial infarction: Longitudinal study. BMJ, 312(7040), 1191–1194.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Pocock, S. J., & Simon, R. (1975). Sequential treatment assignment with balancing for prognostic factors in the controlled clinical trial. Biometrics, 31(1), 103–115.

    Article  CAS  PubMed  Google Scholar 

  • Prince, A. E., & Roche, M. I. (2014). Genetic information, non-discrimination, and privacy protections in genetic counseling practice. Journal of Genetic Counseling, 23(6), 891–902. doi:10.1007/s10897-014-9743-2.

    Article  PubMed  PubMed Central  Google Scholar 

  • Roberts, R. (2015). A genetic basis for coronary artery disease. Trends in Cardiovascular Medicine, 25(3), 171–178. doi:10.1016/j.tcm.2014.10.008.

    Article  CAS  PubMed  Google Scholar 

  • Roberts, J. S., & Connell, C. M. (2000). Illness representations among first-degree relatives of people with Alzheimer disease. Alzheimer Disease and Associated Disorders, 14(3), 129–136 Discussion 127-128.

    Article  CAS  PubMed  Google Scholar 

  • Roberts, R., & Stewart, A. F. (2012). Genes and coronary artery disease: Where are we? Journal of the American College of Cardiology, 60(18), 1715–1721. doi:10.1016/j.jacc.2011.12.062.

    Article  CAS  PubMed  Google Scholar 

  • Sanderson, S. C., Persky, S., & Michie, S. (2010). Psychological and behavioral responses to genetic test results indicating increased risk of obesity: Does the causal pathway from gene to obesity matter? Public Health Genomics, 13(1), 34–47. doi:10.1159/000217794.

    Article  CAS  PubMed  Google Scholar 

  • Scheinfeldt, L. B., Schmidlen, T. J., Gharani, N., MacKnight, M., Jarvis, J. P., Delaney, S. K., et al. (2016). Coronary artery disease genetic risk awareness motivates heart health behaviors in the Coriell personalized medicine collaborative. Expert Review of Precision Medicine and Drug Development, 1(4), 407–413. doi:10.1080/23808993.2016.1197039.

    Article  Google Scholar 

  • Schunkert, H., König, I. R., Kathiresan, S., Reilly, M. P., Assimes, T. L., Holm, H., et al. (2011). Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. Nature Genetics, 43(4), 333–338. doi:10.1038/ng.784.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Thanassoulis, G., Peloso, G. M., & O'Donnell, C. J. (2013). Genomic medicine for improved prediction and primordial prevention of cardiovascular disease. Arteriosclerosis, Thrombosis, and Vascular Biology, 33(9), 2049–2050. doi:10.1161/ATVBAHA.113.301814.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • The White House, O. o. t. P. S. (2015). FACT SHEET: President Obama’s Precision Medicine Initiative.

  • Tikkanen, E., Havulinna, A. S., Palotie, A., Salomaa, V., & Ripatti, S. (2013). Genetic risk prediction and a 2-stage risk screening strategy for coronary heart disease. Arteriosclerosis, Thrombosis, and Vascular Biology, 33(9), 2261–2266. doi:10.1161/ATVBAHA.112.301120.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Waxler, J. L., O'Brien, K. E., Delahanty, L. M., Meigs, J. B., Florez, J. C., Park, E. R., et al. (2012). Genetic counseling as a tool for type 2 diabetes prevention: A genetic counseling framework for common polygenetic disorders. Journal of Genetic Counseling, 21(5), 684–691. doi:10.1007/s10897-012-9486-x.

    Article  PubMed  Google Scholar 

  • Willis, A. M., Smith, S. K., Meiser, B., Ballinger, M. L., Thomas, D. M., & Young, M. A. (2016). Sociodemographic, psychosocial and clinical factors associated with uptake of genetic counselling for hereditary cancer: A systematic review. Clinical Genetics. doi:10.1111/cge.12868.

    Google Scholar 

  • Wilson, P. W., D'Agostino, R. B., Levy, D., Belanger, A. M., Silbershatz, H., & Kannel, W. B. (1998). Prediction of coronary heart disease using risk factor categories. Circulation, 97(18), 1837–1847.

    Article  CAS  PubMed  Google Scholar 

  • Zdravkovic, S., Wienke, A., Pedersen, N. L., & de Faire, U. (2007). Genetic influences on angina pectoris and its impact on coronary heart disease. European Journal of Human Genetics, 15(8), 872–877. doi:10.1038/sj.ejhg.5201846.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgments

We would like to acknowledge the staff of the Mayo Cardiovascular Health Clinic for their help with MI-GENES study.

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Authors and Affiliations

  1. Department of Cardiovascular Diseases, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA

    Sharma Kattel, Sherry-Ann Brown, Hayan Jouni, Erin Austin & Iftikhar J. Kullo

  2. School of Medicine, Medical University of South Carolina, Charleston, SC, USA

    Tochukwu Onyekwelu

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  1. Sharma Kattel
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Correspondence to Iftikhar J. Kullo.

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Sharma Kattel, Tochukwu Onyekwelu, Sherry-Ann Brown, Hayan Jouni, Erin E. Austin, and Iftikhar J Kullo declare that they have no conflict of interest.

Funding Sources

This study was funded as part of the NHGRI-supported eMERGE (Electronic Records and Genomics) Network (HG04599 and HG006379). Additional support was provided by the Mayo Center for Individualized Medicine. Use of REDCap is funded by the Center for Clinical and Translational Science grant support (UL1TR000135).

Human Studies and Informed Consent

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000 (5). Informed consent was obtained from all patients for being included in the study.

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No animal studies were carried out by the authors for this article.

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Kattel, S., Onyekwelu, T., Brown, SA. et al. Motivation, Perception, and Treatment Beliefs in the Myocardial Infarction Genes (MI-GENES) Randomized Clinical Trial. J Genet Counsel 26, 1153–1161 (2017). https://doi.org/10.1007/s10897-017-0092-9

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