Merging and emerging cohorts: necessary but not sufficient.

National Human Genome Research Institute, National Institutes of Health, 31 Center Drive, Bethesda, Maryland 20892-2152, USA.
Nature (Impact Factor: 42.35). 02/2007; 445(7125):259.
Source: PubMed
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    ABSTRACT: The electronic MEdical Records & GEnomics (eMERGE) network was established in 2007 by the National Human Genome Research Institute (NHGRI) of the National Institutes of Health (NIH) in part to explore the utility of electronic medical records (EMRs) in genome science. The initial focus was on discovery primarily using the genome-wide association paradigm, but more recently, the network has begun evaluating mechanisms to implement new genomic information coupled to clinical decision support into EMRs. Herein, we describe this evolution including the development of the individual and merged eMERGE genomic datasets, the contribution the network has made toward genomic discovery and human health, and the steps taken toward the next generation genotype-phenotype association studies and clinical implementation.
    Frontiers in Genetics 06/2014; 5:184.
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    ABSTRACT: Many commentators seem in agreement that the ‘promise’ of the genomics revolution is to be realized through the creation of large-scale biobanks: that is, collections of human tissue and associated data from populations ranging from tens to hundreds of thousands of subjects. Yet obtaining access to such large volumes of biospecimens and data is often difficult, and especially so in the United States. Drawing on published material and interviews with biobank managers conducted between 2006 and 2011, this article provides a tripartite typology of strategies currently employed by US biobanking advocates, distinguishing between de novo, networking and repurposing biobanking strategies. This typology emphasizes the economic aspects of biobanking, and emphasizes as well a conflict between two different understandings of biological citizenship: on the one hand, a mode of biological citizenship that links donation to a form of clinical labor in order to enable access to tissues and health biographies of individuals; on the other, an approach to biovalue that seeks to avoid both clinical labor and biological citizenship in favor of protocols designed to extract biovalue unobtrusively from already existing patterns of health-care and life by means of what I call ‘biomedical immaterial labor’.
    BioSocieties 09/2012; 7(3). · 1.26 Impact Factor
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    ABSTRACT: Purpose:Recent policies specifying criteria about which individual research results to return leave considerable discretion to researchers. This study investigated the types of results that the public wants when participating in genetic research and whether preferences differ based on willingness to participate.Methods:A representative survey of US adults used conjoint analysis to measure priorities among eight principles of a results policy for a proposed large-cohort study. Policy preferences were measured using 12 tasks in which respondents chose between two groupings of the policy principles. Stratified analysis compared those self-identified as likely or unlikely to participate in genomic research.Results:Of 1,515 respondents, 56% would participate in the proposed study. All eight principles were positively endorsed by participants (all P < 0.003), with priority placed on providing results at no cost and returning well-validated results for treatable and serious diseases. Providing detailed result reports was more highly valued than providing staff to explain results (P = 0.0005). Receiving results about major changes in risk was marginally disvalued by those unlikely to participate (P = 0.35).Conclusion:Public preferences for well-validated individual research results for serious, actionable diseases agree with emerging recommendations. However, because preferences for receiving individual research results vary, some choices should be offered to research participants.Genet Med advance online publication 22 May 2014Genetics in Medicine (2014); doi:10.1038/gim.2014.50.
    Genetics in medicine: official journal of the American College of Medical Genetics 05/2014; · 3.92 Impact Factor