The Uneasy Ethical and Legal Underpinnings of Large-Scale Genomic Biobanks

Stanford University, Stanford, California 94305, USA.
Annual Review of Genomics and Human Genetics (Impact Factor: 8.96). 02/2007; 8(1):343-64. DOI: 10.1146/annurev.genom.7.080505.115721
Source: PubMed


Abstract Large-scale genomic databases are becoming increasingly common. These databases, and the underlying biobanks, pose several substantial legal and ethical problems. Neither the usual methods for protecting subject confidentiality, nor even anonymity, are likely to protect subjects' identities in richly detailed databases. Indeed, in these settings, anonymity is itself ethically suspect. New methods of consent will need to be created to replace the blanket consent common to such endeavors, with a consent procedure that gives subjects some real control over what they might consider inappropriate use of their information and biological material. Through their use, these biobanks are also likely to yield information that will be of some clinical significance to the subjects, information that they should have access to. Failure to adjust to these new challenges is not only legally and ethically inappropriate, but puts at risk the political support on which biomedical research depends.

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    • "Where an agronomist sees the challenges of feeding billions of people (McCouch et al. 2013), we see many carriers of every nonlethal de novo mutation (Kong et al. 2012) and homozygotes or compound heterozygotes for loss-of-function alleles in thousands of genes (MacArthur et al. 2012). Of course, nontrivial obstacles must be overcome, particularly to craft data sharing and research protocols that truly engage, inform, protect, and respect research participants (Greely 2007; Erlich et al. 2014), but the availability of millions of genomes attached to at least some phenotypic information is realistic in the coming years. Genomic annotations in variant assessment Although more, better, and broadly available human genetic data are obviously necessary, genomic annotations are and will in the future be essential. "
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    ABSTRACT: Human genome sequencing is routine and will soon be a staple in research and clinical genetics. However, the promise of sequencing is often just that, with genome data routinely failing to reveal useful insights about disease in general or a person's health in particular. Nowhere is this chasm between promise and progress more evident than in the designation, "variant of uncertain significance" (VUS). Although it serves an important role, careful consideration of VUS reveals it to be a nebulous description of genomic information and its relationship to disease, symptomatic of our inability to make even crude quantitative assertions about the disease risks conferred by many genetic variants. In this perspective, I discuss the challenge of "variant interpretation" and the value of comparative and functional genomic information in meeting that challenge. Although already essential, genomic annotations will become even more important as our analytical focus widens beyond coding exons. Combined with more genotype and phenotype data, they will help facilitate more quantitative and insightful assessments of the contributions of genetic variants to disease.
    Preview · Article · Oct 2015 · Genome Research
    • "Research with stored biospecimens can provide substantial societal benefits, including greater understanding of disease mechanisms and discovery of new therapeutic modalities (Davey Smith et al. 2005; Hansson et al. 2006; Khoury et al. 2004; Stjernschantz Forsberg et al. 2011). However, participants who donate biospecimens for research may face some risks (Meslin and Quaid 2004; Trinidad et al. 2011) including unwanted information disclosure, particularly as genetic data generated in biobank research is increasingly linked to clinical data (Greely 2007; Wendler and Emanuel 2002). A critical social and ethical issue in biobank research is secondary research use of biospecimens, or the use of samples for research that was unplanned at the time of biospecimen collection (Chen et al. 2005; Murphy et al. 2009; Salvaterra et al. 2008; Simon et al. 2011; Williams and Wolf 2013). "
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    ABSTRACT: Biobanks are essential resources, and participation by individuals from diverse groups is needed. Various models of consent have been proposed for secondary research use of biospecimens, differing in level of donor control and information received. Data are needed regarding participant preferences for models of consent, particularly among minorities. We conducted qualitative semi-structured interviews with 60 women to examine their attitudes about different models of consent. Recruitment was stratified by race (Black/White) and prior biobank participation (yes/no). Two coders independently coded interview transcripts. Qualitative thematic analysis was conducted using NVivo 10. The majority of Black and White participants preferred "broad" consent (i.e., blanket permission for secondary research use of biospecimens), and the second most preferred model for both groups was "study-specific" consent (i.e., consent for each future research study). The qualitative analysis showed that participants selected their most preferred model for 3 major reasons: having enough information, having control over their sample, and being asked for permission. Least preferred was notice model (i.e., participants notified that biospecimens may be used in future research). Attitudes toward models of consent differed somewhat by race and prior biobank participation. Participants preferred models of consent for secondary research use of biospecimens that provided them with both specific and general information, control over their biospecimens, and asked them to give permission for use. Our findings suggest that it will be important for researchers to provide information about future uses of biospecimens to the extent possible and have an explicit permission step for secondary research use.
    No preview · Article · Aug 2015 · Journal of community genetics
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    • "personalized medicine. For example, many diseases are associated with single-nucleotide polymorphisms, and performing genome-wide association studies using large collections of samples which represent tens or hundreds of thousands of individuals can help to identify disease biomarkers as stated by Greely (2007). Hewitt (2011) and many other researchers have identified biobanking as a key area for infrastructure development in order to promote drug discovery and drug development. "
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    ABSTRACT: This article describes the software architecture designed to cope with the computing demand of research usage of complex data from the Imaging Biobank of the Regional Ministry of Health in the Valencia Region (CS). It proposes the use of self-configured virtual clusters on top of on-premise and public cloud infrastructures. It uses a model based on recipes and autoconfiguration to deploy virtual elastic clusters that adjust themselves to the actual workload of the study, therefore reducing operating costs and preventing the need of up-front investments both at the level of the Imaging Biobank or the final user. All the software used is released under open-source licenses.
    Full-text · Article · Mar 2015
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