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Decision-Making in the Age of Whole Genome Sequencing

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Handbook of Health Decision Science

Abstract

Whole genome sequencing (WGS) is increasingly used for clinical and research purposes. Patients and research participants will be required to make decisions about having WGS done and receiving results from it, acknowledging that the context in which they are having it done is constantly changing and evolving, and that therefore all of the future outcomes of the research or clinical procedures cannot be predicted at baseline. In this chapter, we focus primarily on WGS in the context of “healthy” individuals, that is, individuals not selected specifically for having an initial disease or phenotype of interest. Although much of WGS being done today is, for example, to uncover the cause of an undiagnosed disease or to try to help treat a patient diagnosed with cancer, we anticipate that in the coming years WGS will not be restricted to individuals and families affected with rare genetic disorders and diseases, but that rather we are moving toward a future where every individual across society will have their genome sequenced. We discuss how decision-making about WGS may differ from decision-making about past health-related tests, review the limited evidence at present on decision-making about WGS, discuss how the rate of evidence is growing exponentially and so decision-making is a moving target that we can expect to be constantly changing and very dynamic for the foreseeable future, and discuss the challenges and future directions for the field.

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References

  • Altshuler, D., Daly, M. J., et al. (2008). Genetic mapping in human disease. Science, 322(5903), 881–888.

    Article  PubMed  PubMed Central  Google Scholar 

  • Angrist, M. (2009). Eyes wide open: The personal genome project, citizen science and veracity in informed consent. Personalized Medicine, 6(6), 691–699.

    Article  PubMed  PubMed Central  Google Scholar 

  • Ashley, E. A., Butte, A. J., et al. (2010). Clinical assessment incorporating a personal genome. Lancet, 375(9725), 1525–1535.

    Article  PubMed  PubMed Central  Google Scholar 

  • Ball, M. P., Thakuria, J. V., et al. (2012). A public resource facilitating clinical use of genomes. Proceedings of the National Academy of Sciences of the United States of America, 109(30), 11920–11927.

    Article  PubMed  PubMed Central  Google Scholar 

  • Bandura, D. R., Baranov, V. I., et al. (2009). Mass cytometry: Technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry. Analytical Chemistry, 81(16), 6813–6822.

    Article  PubMed  Google Scholar 

  • Barabasi, A. L., & Oltvai, Z. N. (2004). Network biology: understanding the cell’s functional organization. Nature Reviews Genetics, 5(2), 101–113.

    Article  PubMed  Google Scholar 

  • Bernstein, B. E., Birney, E., et al. (2012). An integrated encyclopedia of DNA elements in the human genome. Nature, 489(7414), 57–74.

    Article  Google Scholar 

  • Biesecker, L. G. (2012). Opportunities and challenges for the integration of massively parallel genomic sequencing into clinical practice: Lessons from the ClinSeq project. Genetics in Medicine, 14(4), 393–398.

    Article  PubMed  PubMed Central  Google Scholar 

  • Biesecker, L. G., Mullikin, J. C., et al. (2009). The ClinSeq Project: piloting large-scale genome sequencing for research in genomic medicine. Genome Research, 19(9), 1665–1674.

    Article  PubMed  PubMed Central  Google Scholar 

  • Bloss, C. S., Ornowski, L., et al. (2010). Consumer perceptions of direct-to-consumer personalized genomic risk assessments. Genetics in Medicine, 12(9), 556–566.

    Article  PubMed  Google Scholar 

  • Bloss, C. S., Schork, N. J., et al. (2011). Effect of direct-to-consumer genomewide profiling to assess disease risk. New England Journal of Medicine, 364(6), 524–534.

    Article  PubMed  PubMed Central  Google Scholar 

  • Brunham, L. R., & Hayden, M. R. (2012). Medicine. Whole-genome sequencing: the new standard of care? Science, 336(6085), 1112–1113.

    Article  PubMed  Google Scholar 

  • Cassa, C. A., Savage, S. K., et al. (2012). Disclosing pathogenic genetic variants to research participants: Quantifying an emerging ethical responsibility. Genome Research, 22(3), 421–428.

    Article  PubMed  PubMed Central  Google Scholar 

  • Chen, R., Mias, G. I., et al. (2012). Personal omics profiling reveals dynamic molecular and medical phenotypes. Cell, 148(6), 1293–1307.

    Article  PubMed  PubMed Central  Google Scholar 

  • Church, G. M. (2005). The personal genome project. Molecular Systems Biology, 1(2005), 0030.

    PubMed  Google Scholar 

  • Codori, A. M., Hanson, R., et al. (1994). Self-selection in predictive testing for Huntington’s disease. American Journal of Medical Genetics, 54(3), 167–173.

    Article  PubMed  Google Scholar 

  • International Human Genome Sequencing Consortium. (2004). Finishing the euchromatic sequence of the human genome. Nature, 431(2011), 931–945.

    Article  Google Scholar 

  • National Research Council (2011). Toward precision medicine: Building a knowledge network for biomedical research and a new taxonomy of disease. Washington DC: National Academy of Sciences.

    Google Scholar 

  • Creighton, S., Almqvist, E. W., et al. (2003). Predictive, pre-natal and diagnostic genetic testing for Huntington’s disease: The experience in Canada from 1987 to 2000. Clinical Genetics, 63(6), 462–475.

    Article  PubMed  Google Scholar 

  • Dewey, F. E., Chen, R., et al. (2011). Phased whole-genome genetic risk in a family quartet using a major allele reference sequence. PLoS Genetics, 7(9), e1002280.

    Article  PubMed  PubMed Central  Google Scholar 

  • Dohany, L., Gustafson, S., et al. (2012). Psychological distress with direct-to-consumer genetic testing: A case report of an unexpected BRCA positive test result. Journal of Genetic Counseling, 21(3), 399–401.

    Article  PubMed  Google Scholar 

  • Drmanac, R., Sparks, A. B., et al. (2010). Human genome sequencing using unchained base reads on self-assembling DNA nanoarrays. Science, 327(5961), 78–81.

    Article  PubMed  Google Scholar 

  • Eid, J., Fehr, A., et al. (2009). Real-time DNA sequencing from single polymerase molecules. Science, 323(5910), 133–138.

    Article  PubMed  Google Scholar 

  • Elwyn, G., O’Connor, A., et al. (2006). Developing a quality criteria framework for patient decision aids: Online international delphi consensus process. BMJ, 333(7565), 417.

    Article  PubMed  PubMed Central  Google Scholar 

  • Emilsson, V., Thorleifsson, G., et al. (2008). Genetics of gene expression and its effect on disease. Nature, 452(7186), 423–428.

    Article  PubMed  Google Scholar 

  • Fabsitz, R. R., McGuire, A., et al. (2010). Ethical and practical guidelines for reporting genetic research results to study participants: Updated guidelines from a national heart, lung, and blood institute working group. Circulation: Cardiovascular Genetics, 3(6), 574–580.

    PubMed Central  Google Scholar 

  • Facio, F. M., Brooks, S., et al. (2011). Motivators for participation in a whole-genome sequencing study: Implications for translational genomics research. European Journal of Human Genetics, 19(12), 1213–1217.

    Article  PubMed  PubMed Central  Google Scholar 

  • Facio, F. M., Eidem, H., et al. (2012). Intentions to receive individual results from whole-genome sequencing among participants in the ClinSeq study. European Journal of Human Genetics, 21(3), 261–265.

    Google Scholar 

  • Feldman-Stewart, D., Brennenstuhl, S., et al. (2006). An explicit values clarification task: Development and validation. Patient Education and Counseling, 63(3), 350–356.

    Article  PubMed  Google Scholar 

  • Gollust, S. E., Gordon, E. S., et al. (2012). Motivations and perceptions of early adopters of personalized genomics: Perspectives from research participants. Public Health Genomics, 15(1), 22–30.

    Article  PubMed  Google Scholar 

  • Green, E. D., & Guyer, M. S. (2011). Charting a course for genomic medicine from base pairs to bedside. Nature, 470(7333), 204–213.

    Article  PubMed  Google Scholar 

  • Green, M. J., Peterson, S. K., et al. (2004). Effect of a computer-based decision aid on knowledge, perceptions, and intentions about genetic testing for breast cancer susceptibility: A randomized controlled trial. JAMA, 292(4), 442–452.

    Article  PubMed  PubMed Central  Google Scholar 

  • Halder, I., Shriver, M., et al. (2008). A panel of ancestry informative markers for estimating individual biogeographical ancestry and admixture from four continents: Utility and applications. Human Mutation, 29(5), 648–658.

    Article  PubMed  Google Scholar 

  • Han, J. D., Bertin, N., et al. (2004). Evidence for dynamically organized modularity in the yeast protein–protein interaction network. Nature, 430(6995), 88–93.

    Article  PubMed  Google Scholar 

  • Hatemi, P. K., & McDermott, R. (2012). The genetics of politics: Discovery, challenges, and progress. Trends in Genetics, 28(10), 525–533.

    Article  PubMed  Google Scholar 

  • Hensley Alford, S., McBride, C. M., et al. (2011). Participation in genetic testing research varies by social group. Public Health Genomics, 14(2), 85–93.

    Article  PubMed  Google Scholar 

  • Jibaja-Weiss, M. L., Volk, R. J., et al. (2006). Preliminary testing of a just-in-time, user-defined values clarification exercise to aid lower literate women in making informed breast cancer treatment decisions. Health Expectations, 9(3), 218–231.

    Article  PubMed  Google Scholar 

  • Jibaja-Weiss, M. L., & Volk, R. J. (2007). Utilizing computerized entertainment education in the development of decision aids for lower literate and naive computer users. Journal of Health Communication, 12(7), 681–697.

    Article  PubMed  Google Scholar 

  • Jibaja-Weiss, M. L., Volk, R. J., et al. (2011). Entertainment education for breast cancer surgery decisions: a randomized trial among patients with low health literacy. Patient Education and Counseling, 84(1), 41–48.

    Article  PubMed  Google Scholar 

  • Kaphingst, K., Facio, F., et al. (2012). Effects of informed consent for individual genome sequencing on relevant knowledge. Clinical Genetics, 82(5), 408–415.

    Google Scholar 

  • Koenig, L. B., McGue, M., et al. (2005). Genetic and environmental influences on religiousness: Findings for retrospective and current religiousness ratings. Journal of Personality, 73(2), 471–488.

    Article  PubMed  Google Scholar 

  • Kravets, D. (2010). Privacy in peril: Lawyers, nations clamor for Google Wi-Fi data. Wired Magazine.

    Google Scholar 

  • Lander, E. S., Linton, L. M., et al. (2001). Initial sequencing and analysis of the human genome. Nature, 409(6822), 860–921.

    Article  PubMed  Google Scholar 

  • Lerman, C., Croyle, R. T., et al. (2002). Genetic testing: Psychological aspects and implications. Journal of Consulting and Clinical Psychology, 70(3), 784–797.

    Article  PubMed  Google Scholar 

  • Lerman, C., Narod, S., et al. (1996). BRCA1 testing in families with hereditary breast-ovarian cancer. A prospective study of patient decision making and outcomes. JAMA, 275(24), 1885–1892.

    Article  PubMed  Google Scholar 

  • Levy, S., Sutton, G., et al. (2007). The diploid genome sequence of an individual human. PLoS Biology, 5(10), e254.

    Article  PubMed  PubMed Central  Google Scholar 

  • Lin, Z., Altman, R. B., et al. (2006). Confidentiality in genome research. Science, 313(5786), 441–442.

    Article  PubMed  Google Scholar 

  • Lunshof, J. E., Bobe, J., et al. (2010). Personal genomes in progress: from the human genome project to the personal genome project. Dialogues in Clinical Neuroscience, 12(1), 47–60.

    PubMed  Google Scholar 

  • Lunshof, J. E., Chadwick, R., et al. (2008). From genetic privacy to open consent. Nature Reviews Genetics, 9(5), 406–411.

    Article  PubMed  Google Scholar 

  • Luscombe, N. M., Babu, M. M., et al. (2004). Genomic analysis of regulatory network dynamics reveals large topological changes. Nature, 431(7006), 308–312.

    Article  PubMed  Google Scholar 

  • McBride, C. M., Alford, S. H., et al. (2009). Characteristics of users of online personalized genomic risk assessments: Implications for physician-patient interactions. Genetics in Medicine, 11(8), 582–587.

    Article  PubMed  PubMed Central  Google Scholar 

  • McGuire, A. L., & Gibbs, R. A. (2006). Genetics. No longer de-identified. Science, 312(5772), 370–371.

    Article  PubMed  Google Scholar 

  • O’Connor, A. M., Bennett, C. L., et al. (2009). Decision aids for people facing health treatment or screening decisions. The Cochrane Database of Systamatic Reviews, 3, CD001431.

    Google Scholar 

  • Pinto, S., Roseberry, A. G., et al. (2004). Rapid rewiring of arcuate nucleus feeding circuits by leptin. Science, 304(5667), 110–115.

    Article  PubMed  Google Scholar 

  • Reid, R. J., McBride, C. M,. et al. (2012). Association between health-service use and multiplex genetic testing. Genetics in Medicine, 14(10), 852–859.

    Google Scholar 

  • Roberts, J. S., Barber, M., et al. (2004). Who seeks genetic susceptibility testing for Alzheimer’s disease? Findings from a multisite, randomized clinical trial. Genetics in Medicine, 6(4), 197–203.

    Article  PubMed  Google Scholar 

  • Roberts, J. S., LaRusse, S. A., et al. (2003). Reasons for seeking genetic susceptibility testing among first-degree relatives of people with Alzheimer disease. Alzheimer Disease and Associated Disorders, 17(2), 86–93.

    Article  PubMed  Google Scholar 

  • Sanderson, S. C., Suckiel, S. A., Zweig, M., Bottinger, E. P., Jabs, E. W., Richardson, L. D. (2016). Development and preliminary evaluation of an online educational video about whole-genome sequencing for research participants, patients, and the general public. Genetics in Medicine, 18(5), 501–512.

    Google Scholar 

  • Sanderson, S. C., Linderman, M. D., Suckiel, S. A., Diaz, G. A., Zinberg, R. E., Ferryman, K., Wasserstein, M., Kasarskis, A., Schadt, E. E. (2016). Motivations, concerns and preferences of personal genome sequencing research participants: Baseline findings from the HealthSeq project. European Journal of Human Genetics, 24(1),14–20.

    Google Scholar 

  • Schadt, E. E. (2012). The changing privacy landscape in the era of big data. Molecular Systems Biology, 8, 612.

    Article  PubMed  PubMed Central  Google Scholar 

  • Schadt, E. E., Turner, S., et al. (2010). A window into third-generation sequencing. Human Molecular Genetics, 19(R2), R227–R240.

    Article  PubMed  Google Scholar 

  • Schadt, E. E., Woo, S., et al. (2012). Bayesian method to predict individual SNP genotypes from gene expression data. Nature Genetics, 44(5), 603–608.

    Article  PubMed  Google Scholar 

  • Sheehan, J., & Sherman, K. A. (2012). Computerised decision aids: A systematic review of their effectiveness in facilitating high-quality decision-making in various health-related contexts. Patient Education and Counseling, 88(1), 69–86.

    Article  PubMed  Google Scholar 

  • Speicher, M. R., Geigl, J. B., et al. (2010). Effect of genome-wide association studies, direct-to-consumer genetic testing, and high-speed sequencing technologies on predictive genetic counselling for cancer risk. Lancet Oncology, 11(9), 890–898.

    Article  PubMed  Google Scholar 

  • Tabor, H. K., Stock, J., et al. (2012). Informed consent for whole genome sequencing: A qualitative analysis of participant expectations and perceptions of risks, benefits, and harms. American Journal of Medical Genetics Part A, 158A(6), 1310–1319.

    Article  PubMed  PubMed Central  Google Scholar 

  • van der Steenstraten, I. M., Tibben, A., et al. (1994). Predictive testing for Huntington disease: Nonparticipants compared with participants in the Dutch program. American Journal of Human Genetics, 55(4), 618–625.

    PubMed  PubMed Central  Google Scholar 

  • Venter, J. C., Adams, M. D., et al. (2001). The sequence of the human genome. Science, 291(5507), 1304–1351.

    Article  PubMed  Google Scholar 

  • Volk, R. J., Jibaja-Weiss, M. L., et al. (2008). Entertainment education for prostate cancer screening: A randomized trial among primary care patients with low health literacy. Patient Education and Counseling, 73(3), 482–489.

    Article  PubMed  PubMed Central  Google Scholar 

  • Walker, A. P. (2009). The practice of genetic counseling. In W. S. Uhlmann, J. B. Yashar (Eds.),. A Guide to genetic counseling (pp. 1–35). Hoboken, New Jersey: Wiley.

    Google Scholar 

  • Wheeler, D. A., Srinivasan, M., et al. (2008). The complete genome of an individual by massively parallel DNA sequencing. Nature, 452(7189), 872–876.

    Article  PubMed  Google Scholar 

  • Zerhouni, E. (2003). Medicine. The NIH roadmap. Science, 302(5642), 63–72.

    Article  PubMed  Google Scholar 

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Authors and Affiliations

  1. Great Ormond Street Hospital and University College London (UCL), London, UK

    Saskia C. Sanderson

  2. Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA

    Eric E. Schadt

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  1. Saskia C. Sanderson
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  2. Eric E. Schadt
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Correspondence to Saskia C. Sanderson .

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Editors and Affiliations

  1. Department of Urology, Icahn School of Medicine at Mount Sinai, New York, New York, USA

    Michael A. Diefenbach

  2. Fox Chase Cancer Center, Philadelphia, Pennsylvania, USA

    Suzanne Miller-Halegoua

  3. Department of Community Health Sciences, Boston University, Boston, Massachusetts, USA

    Deborah J. Bowen

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Sanderson, S.C., Schadt, E.E. (2016). Decision-Making in the Age of Whole Genome Sequencing. In: Diefenbach, M., Miller-Halegoua, S., Bowen, D. (eds) Handbook of Health Decision Science. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-3486-7_25

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