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1.
J Mol Diagn ; 18(3): 438-445, 2016 05.
Artículo en Inglés | MEDLINE | ID: mdl-26947514

RESUMEN

Significant barriers, such as lack of professional guidelines, specialized training for interpretation of pharmacogenomics (PGx) data, and insufficient evidence to support clinical utility, prevent preemptive PGx testing from being widely clinically implemented. The current study, as a pilot project for the Right Drug, Right Dose, Right Time-Using Genomic Data to Individualize Treatment Protocol, was designed to evaluate the impact of preemptive PGx and to optimize the workflow in the clinic setting. We used an 84-gene next-generation sequencing panel that included SLCO1B1, CYP2C19, CYP2C9, and VKORC1 together with a custom-designed CYP2D6 testing cascade to genotype the 1013 subjects in laboratories approved by the Clinical Laboratory Improvement Act. Actionable PGx variants were placed in patient's electronic medical records where integrated clinical decision support rules alert providers when a relevant medication is ordered. The fraction of this cohort carrying actionable PGx variant(s) in individual genes ranged from 30% (SLCO1B1) to 79% (CYP2D6). When considering all five genes together, 99% of the subjects carried an actionable PGx variant(s) in at least one gene. Our study provides evidence in favor of preemptive PGx testing by identifying the risk of a variant being present in the population we studied.


Asunto(s)
Citocromo P-450 CYP2D6/genética , Genotipo , Secuenciación de Nucleótidos de Alto Rendimiento , Farmacogenética/métodos , Medicina de Precisión/métodos , Alelos , Citocromo P-450 CYP2C19/genética , Citocromo P-450 CYP2C19/metabolismo , Citocromo P-450 CYP2D6/metabolismo , Activación Enzimática , Duplicación de Gen , Humanos , Fenotipo
2.
Mayo Clin Proc ; 89(1): 25-33, 2014 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-24388019

RESUMEN

OBJECTIVE: To report the design and implementation of the Right Drug, Right Dose, Right Time-Using Genomic Data to Individualize Treatment protocol that was developed to test the concept that prescribers can deliver genome-guided therapy at the point of care by using preemptive pharmacogenomics (PGx) data and clinical decision support (CDS) integrated into the electronic medical record (EMR). PATIENTS AND METHODS: We used a multivariate prediction model to identify patients with a high risk of initiating statin therapy within 3 years. The model was used to target a study cohort most likely to benefit from preemptive PGx testing among the Mayo Clinic Biobank participants, with a recruitment goal of 1000 patients. We used a Cox proportional hazards model with variables selected through the Lasso shrinkage method. An operational CDS model was adapted to implement PGx rules within the EMR. RESULTS: The prediction model included age, sex, race, and 6 chronic diseases categorized by the Clinical Classifications Software for International Classification of Diseases, Ninth Revision codes (dyslipidemia, diabetes, peripheral atherosclerosis, disease of the blood-forming organs, coronary atherosclerosis and other heart diseases, and hypertension). Of the 2000 Biobank participants invited, 1013 (51%) provided blood samples, 256 (13%) declined participation, 555 (28%) did not respond, and 176 (9%) consented but did not provide a blood sample within the recruitment window (October 4, 2012, through March 20, 2013). Preemptive PGx testing included CYP2D6 genotyping and targeted sequencing of 84 PGx genes. Synchronous real-time CDS was integrated into the EMR and flagged potential patient-specific drug-gene interactions and provided therapeutic guidance. CONCLUSION: This translational project provides an opportunity to begin to evaluate the impact of preemptive sequencing and EMR-driven genome-guided therapy. These interventions will improve understanding and implementation of genomic data in clinical practice.


Asunto(s)
Pruebas Genéticas/normas , Farmacogenética/métodos , Guías de Práctica Clínica como Asunto , Medicina de Precisión/métodos , Aterosclerosis/tratamiento farmacológico , Estudios de Cohortes , Toma de Decisiones , Diabetes Mellitus/tratamiento farmacológico , Dislipidemias/tratamiento farmacológico , Registros Electrónicos de Salud , Femenino , Técnicas de Genotipaje , Hematopoyesis/efectos de los fármacos , Humanos , Inhibidores de Hidroximetilglutaril-CoA Reductasas/uso terapéutico , Hipertensión/tratamiento farmacológico , Masculino , Persona de Mediana Edad , Farmacogenética/normas , Proyectos Piloto , Medicina de Precisión/normas , Valor Predictivo de las Pruebas , Estados Unidos
3.
Pharmacogenet Genomics ; 19(10): 813-22, 2009 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-19741566

RESUMEN

OBJECTIVE: CYP2D6 is a polymorphic gene. It has been observed to be deleted, to be duplicated and to undergo recombination events involving the CYP2D7 pseudogene and surrounding sequences. The objective of this study was to discover the genomic structure of CYP2D6 recombinants that interfere with clinical genotyping platforms that are available today. METHODS: Clinical samples containing rare homozygous CYP2D6 alleles, ambiguous readouts, and those with duplication signals and two different alleles were analyzed by long-range PCR amplification of individual genes, PCR fragment analysis, allele-specific primer extension assay, and DNA sequencing to characterize alleles and genomic structure. RESULTS: Novel alleles, genomic structures, and the DNA sequence of these structures are described. Interestingly, in 49 of 50 DNA samples that had CYP2D6 gene duplications or multiplications where two alleles were detected, the chromosome containing the duplication or multiplication had identical tandem alleles. CONCLUSION: Several new CYP2D6 alleles and genomic structures are described which will be useful for CYP2D6 genotyping. The findings suggest that the recombination events responsible for CYP2D6 duplications and multiplications are because of mechanisms other than interchromosomal crossover during meiosis.


Asunto(s)
Alelos , Citocromo P-450 CYP2D6/genética , Duplicación de Gen , Variación Genética , Genotipo , Humanos , Datos de Secuencia Molecular , Fenotipo , Polimorfismo Genético
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