Members of the public in the USA, UK, Canada and Australia expressing genetic exceptionalism say they are more willing to donate genomic data.
Journal
European journal of human genetics : EJHG
ISSN: 1476-5438
Titre abrégé: Eur J Hum Genet
Pays: England
ID NLM: 9302235
Informations de publication
Date de publication:
04 2020
04 2020
Historique:
received:
13
08
2019
accepted:
01
11
2019
revised:
29
10
2019
pubmed:
1
12
2019
medline:
1
5
2021
entrez:
1
12
2019
Statut:
ppublish
Résumé
Public acceptance is critical for sharing of genomic data at scale. This paper examines how acceptance of data sharing pertains to the perceived similarities and differences between DNA and other forms of personal data. It explores the perceptions of representative publics from the USA, Canada, the UK and Australia (n = 8967) towards the donation of DNA and health data. Fifty-two percent of this public held 'exceptionalist' views about genetics (i.e., believed DNA is different or 'special' compared to other types of medical information). This group was more likely to be familiar with or have had personal experience with genomics and to perceive DNA information as having personal as well as clinical and scientific value. Those with personal experience with genetics and genetic exceptionalist views were nearly six times more likely to be willing to donate their anonymous DNA and medical information for research than other respondents. Perceived harms from re-identification did not appear to dissuade publics from being willing to participate in research. The interplay between exceptionalist views about genetics and the personal, scientific and clinical value attributed to data would be a valuable focus for future research.
Identifiants
pubmed: 31784701
doi: 10.1038/s41431-019-0550-y
pii: 10.1038/s41431-019-0550-y
pmc: PMC7080803
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
424-434Subventions
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 206194
Pays : United Kingdom
Organisme : Wellcome Trust (Wellcome)
ID : 206194
Pays : International
Références
Stark Z, Dolman L, Manolio TA, Ozenberger B, Hill SL, Caulfield MJ. et al. Integrating genomics into healthcare: a global responsibility. Am J Hum Genet. 2019;104:13–20. https://doi.org/10.1016/j.ajhg.2018.11.014 .
doi: 10.1016/j.ajhg.2018.11.014
pubmed: 30609404
pmcid: 6323624
Aronson SJ, Rehm HL. Building the foundation for genomics in precision medicine. Nature. 2015;526:336. https://doi.org/10.1038/nature15816 .
doi: 10.1038/nature15816
pubmed: 26469044
pmcid: 5669797
Bustamante CD, Burchard EG, De la Vega FM. Genomics for the world. Nature. 2011;475:163–5. https://doi.org/10.1038/475163a .
doi: 10.1038/475163a
pubmed: 21753830
pmcid: 3708540
Popejoy AB, Fullerton SM. Genomics is failing on diversity. Nature. 2016;538:161–4. https://doi.org/10.1038/538161a .
doi: 10.1038/538161a
pubmed: 27734877
pmcid: 5089703
Collins FS, Varmus H. A new initiative on precision medicine. N. Engl J Med. 2015;372:793–5. https://doi.org/10.1056/NEJMp1500523 .
doi: 10.1056/NEJMp1500523
pubmed: 25635347
pmcid: 5101938
Knoppers BM. Framework for responsible sharing of genomic and health-related. data. Hugo J. 2014;8:3. https://doi.org/10.1186/s11568-014-0003-1 .
doi: 10.1186/s11568-014-0003-1
pubmed: 27090251
pmcid: 4685158
Roche PA, Annas GJ. Protecting genetic privacy. Nat Rev Genet. 2001;2:392–6. https://doi.org/10.1038/35072029 .
doi: 10.1038/35072029
pubmed: 11331906
McGuire AL, Fisher R, Cusenza P, Hudson K, Rothstein MA, McGraw D. et al. Confidentiality, privacy, and security of genetic and genomic test information in electronic health records: points to consider. Genet Med. 2008;10:495–9. https://doi.org/10.1097/GIM.0b013e31817a8aaa .
doi: 10.1097/GIM.0b013e31817a8aaa
Evans JP, Burke W. Genetic exceptionalism. Too much of a good thing?. Genet Med.2008;10:500–1. https://doi.org/10.1097/GIM.0b013e31817f280a .
doi: 10.1097/GIM.0b013e31817f280a
Sulmasy DP. Naked bodies, naked genomes: the special (but not exceptional) nature of genomic information. Genet Med. 2015;17:331–6. https://doi.org/10.1038/gim.2014.111 .
doi: 10.1038/gim.2014.111
pubmed: 25232853
Wright CF, FitzPatrick DR, Firth HV. Paediatric genomics: diagnosing rare disease in children. Nat Rev Genet.2018;19:253–68. https://doi.org/10.1038/nrg.2017.116 .
doi: 10.1038/nrg.2017.116
pubmed: 29398702
Auffray C, Balling R, Barroso I, Bencze L, Benson M, Bergeron J. et al. Making sense of big data in health research: towards an EU action plan. Genome Med. 2016;8:71. https://doi.org/10.1186/s13073-016-0323-y .
doi: 10.1186/s13073-016-0323-y
pubmed: 27338147
pmcid: 4919856
Nuffield Council on Bioethics. The collection, linking and use of data in biomedical research and health care: ethical issues. London; 2015. Accessed 27 November 2019. https://nuffieldbioethics.org/wp-content/uploads/Biodata-a-guide-to-the-report-PDF.pdf .
Kaye J, Terry SF, Juengst E, Coy S, Harris JR, Chalmers D. et al. Including all voices in international data-sharing governance. Hum Genomics. 2018;12:13. https://doi.org/10.1186/s40246-018-0143-9 .
doi: 10.1186/s40246-018-0143-9
pubmed: 29514717
pmcid: 5842530
Aitken M, de St. Jorre J, Pagliari C, Jepson R, Cunningham-Burley S. Public responses to the sharing and linkage of health data for research purposes: a systematic review and thematic synthesis of qualitative studies. BMC Med Ethics. 2016;17:73. https://doi.org/10.1186/s12910-016-0153-x .
doi: 10.1186/s12910-016-0153-x
pubmed: 27832780
pmcid: 5103425
Lemke AAA, Wolf WAA, Hebert-Beirne J, Smith MEE. Public and biobank participant attitudes toward genetic research participation and data sharing. Public Health Genomics. 2010;13:368–77. https://doi.org/10.1159/000276767 .
doi: 10.1159/000276767
pubmed: 20805700
pmcid: 2951726
Trinidad SB, Fullerton SM, Bares JM, Jarvik GP, Larson EB, Burke W. Genomic research and wide data sharing: views of prospective participants. Genet Med. 2010;12:486–95. https://doi.org/10.1097/GIM.0b013e3181e38f9e .
doi: 10.1097/GIM.0b013e3181e38f9e
pubmed: 20535021
pmcid: 3045967
Oliver JM, Slashinski MJ, Wang T, Kelly PA, Hilsenbeck SG, McGuire AL. Balancing the risks and benefits of genomic data sharing: genome research participants’ perspectives. Public Health Genomics. 2012;15:106–14. https://doi.org/10.1159/000334718 .
doi: 10.1159/000334718
pubmed: 22213783
Middleton A, Niemiec E, Prainsack B, Bobe J, Farley L, Steed C. et al. ‘Your DNA, Your Say’: global survey gathering attitudes toward genomics: design, delivery and methods. Per Med. 2018;15:311–8. https://doi.org/10.2217/pme-2018-0032 .
doi: 10.2217/pme-2018-0032
pubmed: 29856292
Middleton A. Your DNA, your say. N. Bioeth. 2017;23:74–80. https://doi.org/10.1080/20502877.2017.1314890 .
doi: 10.1080/20502877.2017.1314890
Middleton A. Society and personal genome data. Hum Mol Genet. 2018;27(R1):R8–13. https://doi.org/10.1093/hmg/ddy084 .
doi: 10.1093/hmg/ddy084
pubmed: 29522190
pmcid: 5946868
Gibbons RD, Hedeker D, DuToit S. Advances in analysis of longitudinal data. Annu Rev Clin Psychol. 2010;6:79–107. https://doi.org/10.1146/annurev.clinpsy.032408.153550 .
doi: 10.1146/annurev.clinpsy.032408.153550
pubmed: 20192796
pmcid: 2971698
Hubbard AE, Ahern J, Fleischer NL, Van der Laan M, Lippman SA, Jewell N. et al. To GEE or not to GEE: comparing population average and mixed models for estimating the associations between neighborhood risk factors and health. Epidemiology. 2010;21:467–74. https://doi.org/10.1097/EDE.0b013e3181caeb90 .
doi: 10.1097/EDE.0b013e3181caeb90
pubmed: 20220526
Condit CM. Public attitudes and beliefs about genetics. Annu Rev Genomics Hum Genet. 2010;11:339–59. https://doi.org/10.1146/annurev-genom-082509-141740 .
doi: 10.1146/annurev-genom-082509-141740
pubmed: 20690816
Allum N, Sibley E, Sturgis P, Stoneman P. Religious beliefs, knowledge about science and attitudes towards medical genetics. Public Underst Sci. 2014;23:833–49. https://doi.org/10.1177/0963662513492485 .
doi: 10.1177/0963662513492485
pubmed: 23838683
Haga SB, Barry WT, Mills R, Ginsburg GS, Svetkey L, Sullivan J. et al. Public knowledge of and attitudes toward genetics and genetic testing. Genet Test Mol Biomark. 2013;17:327–35. https://doi.org/10.1089/gtmb.2012.0350 .
doi: 10.1089/gtmb.2012.0350
Merlo J, Chaix B, Ohlsson H, Beckman A, Johnell K, Hjerpe P. et al. A brief conceptual tutorial of multilevel analysis in social epidemiology: using measures of clustering in multilevel logistic regression to investigate contextual phenomena. J Epidemiol Community Health. 2006;60:290–7. https://doi.org/10.1136/jech.2004.029454 .
doi: 10.1136/jech.2004.029454
pubmed: 16537344
pmcid: 2566165
Shmueli G. To explain or to predict?. Stat Sci. 2010;25:289–310. https://doi.org/10.1214/10-STS330 .
doi: 10.1214/10-STS330
Snijders TAB, Bosker RJ. Multilevel analysis: an introduction to basic and advanced multilevel modeling. Thousand Oaks California; London: SAGE; 1999.
R Core Team. R: A language and environment for statistical computing. R Core Team; 2016. Accessed 27 November 2019. https://www.r-project.org/ .
Bates D, Mächler M, Bolker BM, Walker SC. Fitting linear mixed-effects models using lme4. J Stat Softw. 2015;67:1–48. https://doi.org/10.18637/jss.v067.i01 .
doi: 10.18637/jss.v067.i01
Merlo J, Chaix B, Yang M, Lynch J, Råstam L. A brief conceptual tutorial of multilevel analysis in social epidemiology: linking the statistical concept of clustering to the idea of contextual phenomenon. J Epidemiol Community Health. 2005;59:443–9. https://doi.org/10.1136/jech.2004.023473 .
doi: 10.1136/jech.2004.023473
pubmed: 15911637
pmcid: 1757045
Gaskell G, Gottweis H, Starkbaum J, Gerber MM, Broerse J, Gottweis U. et al. Publics and biobanks: Pan-European diversity and the challenge of responsible innovation. Eur J Hum Genet. 2013;21:14–20. https://doi.org/10.1038/ejhg.2012.104 .
doi: 10.1038/ejhg.2012.104
pubmed: 22669414
McCormack P, Kole A, Gainotti S, Mascalzoni D, Molster C, Lochmüller H. et al. ‘You should at least ask’. The expectations, hopes and fears of rare disease patients on large-scale data and biomaterial sharing for genomics research. Eur J Hum Genet. 2016;24:1403–8. https://doi.org/10.1038/ejhg.2016.30 .
doi: 10.1038/ejhg.2016.30
pubmed: 27049302
pmcid: 5027679
Darquy S, Moutel G, Lapointe AS, D’Audiffret D, Champagnat J, Guerroui S. et al. Patient/family views on data sharing in rare diseases: study in the European LeukoTreat project. Eur J Hum Genet. 2016;24:338–43. https://doi.org/10.1038/ejhg.2015.115 .
doi: 10.1038/ejhg.2015.115
pubmed: 26081642
Middleton A, Morley KI, Bragin E, Firth HV, Hurles ME, Wright CF. et al. Attitudes of nearly 7000 health professionals, genomic researchers and publics toward the return of incidental results from sequencing research. Eur J Hum Genet. 2016;24:21–9. https://doi.org/10.1038/ejhg.2015.58 .
doi: 10.1038/ejhg.2015.58
pubmed: 25920556
National Science Board. Science and Engineering Indicators 2012. Washington DC: OmniStudio, Inc; 2012. https://nsf.gov/statistics/seind12/pdf/seind12.pdf .
Ley BL, Jankowski N, Brewer PR. Investigating CSI: portrayals of DNA testing on a forensic crime show and their potential effects. Public Underst Sci. 2012;21:51–67. https://doi.org/10.1177/0963662510367571 .
doi: 10.1177/0963662510367571
pubmed: 22530487
Brewer PR, Ley BL. Media use and public perceptions of DNA evidence. Sci Commun. 2009;32:93–117. https://doi.org/10.1177/1075547009340343 .
doi: 10.1177/1075547009340343
Sjoberg L. Factors in risk perception. Risk Anal. 2000;20:1–11. https://www.ncbi.nlm.nih.gov/pubmed/10841699
doi: 10.1111/0272-4332.00001
Glasman LR, Albarracín D. Forming attitudes that predict future behavior: a meta-analysis of the attitude–behavior relation. Psychol Bull. 2006;132:778–822. https://doi.org/10.1037/0033-2909.132.5.778 .
doi: 10.1037/0033-2909.132.5.778
pubmed: 16910754
pmcid: 4815429