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
Variability in drug response can be explained, in part, by genetic differences among patients. A clear role in drug toxicity and efficacy has been established for some gene-drug combinations, yet implementation of pharmacogenomic tests in clinical practice lags behind this knowledge. The evidence – adoption gap for many pharmacogenomic tests can be addressed in the short term through the development of consensus-based practice guidelines and clinician education.For genetic variants associated with severe drug toxicities, there is a strong impetus for adoption. An example is the HLA-B*15:02 variant, associated with the potentially lethal Stevens-Johnson syndrome in Asian patients treated with carbamazepine.1 Another example is the poor metabolizers of cytochrome p450 2D6 substrates that represent a range of risk when exposed to specific medications. The death of a child treated with fluoxetine illustrates the importance of identifying patients with impaired metabolism as well as the ethical dilemma of knowingly exposing patients with minimal metabolic capacity to substrates that require a specific enzyme for clearance.2
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[Show abstract] [Hide abstract] 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.
- "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 "
[Show abstract] [Hide abstract] 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.
- "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]. "
[Show abstract] [Hide abstract] ABSTRACT: This study assessed physician attitudes toward adopting genome-guided prescribing through clinical decision support (CDS), prior to enlisting in the Clinical Implementation of Personalized Medicine through Electronic Health Records and Genomics pilot pharmacogenomics project (CLIPMERGE PGx). We developed a survey instrument that includes the Evidence Based Practice Attitude Scale, adapted to measure attitudes toward adopting genome-informed interventions (EBPAS-GII). The survey also includes items to measure physicians' characteristics (awareness, experience, and perceived usefulness), attitudes about personal genome testing (PGT) services, and comfort using technology. We surveyed 101 General Internal Medicine physicians from the Icahn School of Medicine at Mount Sinai (ISMMS). The majority were residency program trainees (~88%). Prior to enlisting into CLIPMERGE PGx, most physicians were aware of and had used decision support aids. Few physicians, however, were aware of and had used genome-guided prescribing. The majority of physicians viewed decision support aids and genotype data as being useful for making prescribing decisions. Most physicians had not heard of, but were willing to use, PGT services and felt comfortable interpreting PGT results. Most physicians were comfortable with technology. Physicians who perceived genotype data to be useful in making prescribing decisions, had more positive attitudes toward adopting genome-guided prescribing through CDS. Our findings suggest that internal medicine physicians have a deficit in their familiarity and comfort interpreting and using genomic information. This has reinforced the importance of gathering feedback and guidance from our enrolled physicians when designing genome-guided CDS and the importance of prioritizing genomic medicine education at our institutions.
- "Though a clear role has been established for pharmacogenomics in the efficacy and toxicity of numerous drugs, the implementation of pharmacogenomic tests in clinical practice has not kept pace with the emerging knowledge base [1,2]. There are numerous potential explanations for this lag, including an insufficient knowledge of and experience with pharmacogenomic testing345. "