Deflating the Genomic Bubble

Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Science (Impact Factor: 33.61). 02/2011; 331(6019). DOI: 10.1126/science.1198039
Source: PubMed


Unrealistic expectations and uncritical translation of genetic discoveries may undermine other promising approaches to preventing disease and improving health.

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Available from: Eric Meslin, Sep 30, 2015
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    • "Initial optimism about the prospect of genomic medicine has given way to the realization that clinical applications will be challenging to identify and implement [1,2]. Efforts to predict disease incidence or severity based on common genetic variants have shown limited success [1], raising questions about the utility of genomic applications in assessing risk for common health conditions. However, advances in pharmacogenetics have already led to treatment innovations in tertiary care contexts. "
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    ABSTRACT: Despite advances in characterizing genetic influences on addiction liability and treatment response, clinical applications of these efforts have been slow to evolve. Although challenges to clinical translation remain, stakeholders already face decisions about evidentiary thresholds for the uptake of pharmacogenetic tests in practice. There is optimism about potential pharmacogenetic applications for the treatment of alcohol use disorders, with particular interest in the OPRM1 A118G polymorphism as a moderator of naltrexone response. Findings from human and animal studies suggest preliminary evidence for the clinical validity of this association; on this basis, arguments for clinical implementation can be made in accordance with existing frameworks for the uptake of genomic applications. However, generating evidence-based guidelines requires evaluating the clinical utility of pharmacogenetic tests. This goal will remain challenging, largely due to minimal data to inform clinical utility estimates. The pace of genomic discovery highlights the need for clinical utility and implementation research to inform future translation efforts. Near-term implementation of promising pharmacogenetic tests can help expedite this goal, generating an evidence base to enable efficient translation as additional gene-drug associations are discovered.
    Addiction science & clinical practice 09/2014; 9(1):20. DOI:10.1186/1940-0640-9-20
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    • "Piot [45] argued that these new technologies were essential for global public health, not just for high-income countries. The complete mapping of the human genome, begun in 1990 and finally achieved early this century, generated both great public interest and hopes for medical breakthroughs [46]. However, genomics has not lived up to these expectations, partly because of the 'complex interactions between multiple genes' [47]. "
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    ABSTRACT: Many observers see advances in technology as the key means for ensuring continued economic growth, and with it human progress as well. In particular, three modern technologies—biotechnology, information technology (sometimes including robotics and cognitive technologies) and nanotechnology—are seen by some researchers as converging and thus bringing about unprecedented benefits for humanity in the coming decades. The aim of this paper is to answer the question: can the on-going rapid advances in these new technologies lead to a better future for all? By examining three important sectors—transport, health/medicine, and agriculture/food—we show that application of these technologies are either largely irrelevant, too expensive, or too risky to meet the future needs of all humans in these sectors.
    Futures 01/2014; 55. DOI:10.1016/j.futures.2013.12.003 · 1.29 Impact Factor
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    • "The potential for genomics to contribute to clinical care has long been recognized, and many optimistic scenarios for clinical use of information about a patient's genome have been proposed.1,2,3 The pace of realizing this potential has appeared slow to some,4,5 although clinical adoption of scientific discoveries has been estimated to take up to 17 years6 and a recent genetic example7 required 18 years after the initial 1991 report.8 Indeed, relatively robust genotype–phenotype associations for common, complex diseases only began to become available around 2005.9 Yet several academic medical centers and integrated health systems have already begun programs for implementing genomic medicine, which we define here as using an individual patient's genotypic information in his or her clinical care. "
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    ABSTRACT: Although the potential for genomics to contribute to clinical care has long been anticipated, the pace of defining the risks and benefits of incorporating genomic findings into medical practice has been relatively slow. Several institutions have recently begun genomic medicine programs, encountering many of the same obstacles and developing the same solutions, often independently. Recognizing that successful early experiences can inform subsequent efforts, the National Human Genome Research Institute brought together a number of these groups to describe their ongoing projects and challenges, identify common infrastructure and research needs, and outline an implementation framework for investigating and introducing similar programs elsewhere. Chief among the challenges were limited evidence and consensus on which genomic variants were medically relevant; lack of reimbursement for genomically driven interventions; and burden to patients and clinicians of assaying, reporting, intervening, and following up genomic findings. Key infrastructure needs included an openly accessible knowledge base capturing sequence variants and their phenotypic associations and a framework for defining and cataloging clinically actionable variants. Multiple institutions are actively engaged in using genomic information in clinical care. Much of this work is being done in isolation and would benefit from more structured collaboration and sharing of best practices. Genet Med 2013:15(4):258–267
    Genetics in medicine: official journal of the American College of Medical Genetics 01/2013; 15(4). DOI:10.1038/gim.2012.157 · 7.33 Impact Factor
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