Facilitating Clinical Implementation of Pharmacogenomics

Department of Psychiatry, Mayo Clinic College of Medicine, 200 First St SW, Rochester, MN 55905, USA.
JAMA The Journal of the American Medical Association (Impact Factor: 35.29). 07/2011; 306(3):304-5. DOI: 10.1001/jama.2011.1010
Source: PubMed
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    • "Another area of medicine where genetic information can influence greatly is pharmacogenomics, by keeping in mind that around 100,000 people die each year in the USA due to adverse drug reactions (Lazarou et al., 1998) and despite efforts to improve patient safety in the past few years it has not been successful (Landrigan et al., 2010; Phillips and Barker, 2010). Although until now there have been no robust findings of common genetic variants associated to drug response that could be translated in clinical practice in psychiatry, the road has been paved for the identification of genetic determinants to personalised psychiatric treatment (Kato and Serretti, 2010; Kim et al., 2006; Kirchheiner et al., 2005; Mrazek and Lerman, 2011; Tansey et al., 2012). The efficacy of polygenic models for risk prediction, intervention and personalised medicine can only "
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    ABSTRACT: Genetic factors account for up to 80% of the liability for schizophrenia and bipolar disorder. Genome-wide association studies (GWAS) have successfully identified several single nucleotide polymorphisms (SNPs) and genes associated with increased risk for both disorders. Single SNP analyses alone do not address the overall genomic or polygenic architecture of psychiatric disorders as the amount of phenotypic variation explained by each GWAS-supported SNP is small whereas the number of SNPs/regions underlying risk for illness is thought to be very large. The polygenic risk score models the aggregate effect of alleles associated with disease status present in each individual and allows us to utilise the power of large GWAS to be applied robustly in small samples. Here we make the case that risk prediction, intervention and personalised medicine can only benefit with the inclusion of polygenic risk scores in imaging genetics research. © The Author(s) 2015.
    Journal of Psychopharmacology 05/2015; 29(8). DOI:10.1177/0269881115584470 · 3.59 Impact Factor
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    • "Drawing from discussions in other disciplines, several recommendations can be made for near-term efforts to promote translation research in addiction therapeutics. A general goal is to evaluate candidate pharmacogenetic applications with approaches that balance methodological rigor with clinical applicability [8,13,54]. To meet this aim, a comprehensive, portfolio-based approach to translation research has been recommended [8,12]. "
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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
  • Therapeutic Drug Monitoring, 01/2012: pages 121-142; , ISBN: 9780123854674
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