Abstract
ABSTRACTPurposeBiomedical databases combining electronic medical records and phenotypic and genomic data constitute a powerful resource for the personalization of treatment. To leverage the wealth of information provided, algorithms are required that systematically translate the contained information into treatment recommendations based on existing genotype–phenotype associations.MethodsWe developed and tested algorithms for translation of preexisting genotype data of over 44,000 participants of the Estonian biobank into pharmacogenetic recommendations. We compared the results obtained by genome sequencing, exome sequencing, and genotyping using microarrays, and evaluated the impact of pharmacogenetic reporting based on drug prescription statistics in the Nordic countries and Estonia.ResultsOur most striking result was that the performance of genotyping arrays is similar to that of genome sequencing, whereas exome sequencing is not suitable for pharmacogenetic predictions. Interestingly, 99.8% of all assessed individuals had a genotype associated with increased risks to at least one medication, and thereby the implementation of pharmacogenetic recommendations based on genotyping affects at least 50 daily drug doses per 1000 inhabitants.ConclusionWe find that microarrays are a cost-effective solution for creating preemptive pharmacogenetic reports, and with slight modifications, existing databases can be applied for automated pharmacogenetic decision support for clinicians.
Highlights
Genetic variation causing interindividual differences in drug response poses major problems for pharmacological therapy and drug development
We find that microarrays are a cost-effective solution for creating preemptive pharmacogenetic reports, and with slight modifications, existing databases can be applied for automated pharmacogenetic decision support for clinicians
For CYP2C19*2, which is defined by two variants that are in complete linkage disequilibrium (r2 = 1.0), we found that a single variant is sufficient for its detection
Summary
Genetic variation causing interindividual differences in drug response poses major problems for pharmacological therapy and drug development. In recent decades a plethora of associations between genetic variants and treatment efficacy or adverse drug reactions have been identified.[1] the implementation of clinical pharmacogenomics is lagging far behind these discoveries.[2] Fast, accurate, and cost-effective genotyping of genes involved in drug response is a crucial first step for the implementation of pharmacogenomics in clinical care. The genotype data should already exist in an individual’s health record at the time when personalized treatment is necessary. The currently most widely used genotyping method is the array-based interrogation of (candidate) variants. Due to recent progress in sequencing technologies, next-generation sequencing (NGS)-
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
