AND SPECIFIC AIMS: NETWORK RESOURCE Pharmacogenomics is a multidisciplinary science;it has also become a data-intensive science. Therefore, it requires increasingly clear annotation and representation of phenotypes (disease, adverse event, or clinical and physiological outcomes) to support data integration and cross-database analyses. In fact, the consistent and interpretable characterization of drug-related phenotypes, including treatment response, adverse events, and clinical outcomes, has become a rate-limiting factor in large-scale pharmacogenomic research. We propose a PGRN Network Resource focused on the codification of standardized phenotype definitions and relationships, in coordination with other established government-funded efforts, with a clear and constant focus on pharmacogenomics. Because the standardized representation of phenotypes depends on standards, our first two aims focus on making vocabularies and ontologies (computationally formal vocabularies) about clinical and physiologic concepts accessible and usable to the PGRN community. While necessary, such terminological resources are pedantic absent methods and machinery to integrate them into practical phenotypes. Additionally, we will foster the creation of pharmacogenomically relevant value sets, drawn from standards-based terminologies that satisfy relevant domain-specific requirements, such as anatomy, drug names, or gene names. Finally, a PGRN resource must support outreach to PGRN members and the larger pharmacogenomics community to establish standard phenotypes, stnjctured in a way that these pharmacogenomically relevant phenotypes conform to community and government standards, provide grounding for extension to related conditions, and serve as examples for the broader scientific community. We anticipate that this resource will help to enable consistent and comparable large-scale phenotyping for pharmacogenomics.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Program--Cooperative Agreements (U19)
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Special Emphasis Panel (ZRG1-GGG-M)
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Mayo Clinic, Rochester
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Ho, Ming-Fen; Weinshilboum, Richard M (2017) Immune Mediator Pharmacogenomics: TCL1A SNPs and Estrogen-Dependent Regulation of Inflammation. J Nat Sci 3:
St Sauver, Jennifer L; Olson, Janet E; Roger, Veronique L et al. (2017) CYP2D6 phenotypes are associated with adverse outcomes related to opioid medications. Pharmgenomics Pers Med 10:217-227
Sá, Ana Caroline C; Webb, Amy; Gong, Yan et al. (2017) Whole Transcriptome Sequencing Analyses Reveal Molecular Markers of Blood Pressure Response to Thiazide Diuretics. Sci Rep 7:16068
Gonzalez, Velda J; Saligan, Leorey N; Fridley, Brooke L et al. (2017) Gene Expression, and Fatigue in Puerto Rican Men during Radiotherapy for Prostate Cancer: an Exploratory Study. P R Health Sci J 36:223-231
Giacomini, Kathleen M; Yee, Sook Wah; Mushiroda, Taisei et al. (2017) Genome-wide association studies of drug response and toxicity: an opportunity for genome medicine. Nat Rev Drug Discov 16:1
Dudenkov, Tanda M; Ingle, James N; Buzdar, Aman U et al. (2017) SLCO1B1 polymorphisms and plasma estrone conjugates in postmenopausal women with ER+ breast cancer: genome-wide association studies of the estrone pathway. Breast Cancer Res Treat 164:189-199
Qin, Sisi; Liu, Duan; Kohli, Manish et al. (2017) TSPYL Family Regulates CYP17A1 and CYP3A4 Expression: Potential Mechanism Contributing to Abiraterone Response in Metastatic Castration-Resistant Prostate Cancer. Clin Pharmacol Ther :
Lanz, Henriette L; Saleh, Anthony; Kramer, Bart et al. (2017) Therapy response testing of breast cancer in a 3D high-throughput perfused microfluidic platform. BMC Cancer 17:709
Yu, Jia; Qin, Bo; Wu, Fengying et al. (2017) Regulation of Serine-Threonine Kinase Akt Activation by NAD+-Dependent Deacetylase SIRT7. Cell Rep 18:1229-1240
Caraballo, Pedro J; Hodge, Lucy S; Bielinski, Suzette J et al. (2017) Multidisciplinary model to implement pharmacogenomics at the point of care. Genet Med 19:421-429

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