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)
Research Program--Cooperative Agreements (U19)
Project #
Application #
Study Section
Special Emphasis Panel (ZRG1)
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Mayo Clinic, Rochester
United States
Zip Code
Laurie, Cathy C; Laurie, Cecelia A; Smoley, Stephanie A et al. (2014) Acquired chromosomal anomalies in chronic lymphocytic leukemia patients compared with more than 50,000 quasi-normal participants. Cancer Genet 207:19-30
Rasmussen-Torvik, L J; Stallings, S C; Gordon, A S et al. (2014) Design and anticipated outcomes of the eMERGE-PGx project: a multicenter pilot for preemptive pharmacogenomics in electronic health record systems. Clin Pharmacol Ther 96:482-9
Li, Liang; Fridley, Brooke L; Kalari, Krishna et al. (2014) Discovery of genetic biomarkers contributing to variation in drug response of cytidine analogues using human lymphoblastoid cell lines. BMC Genomics 15:93
Pu, X; Wang, L; Chang, J Y et al. (2014) Inflammation-related genetic variants predict toxicity following definitive radiotherapy for lung cancer. Clin Pharmacol Ther 96:609-15
Zhu, Qian; Tao, Cui; Shen, Feichen et al. (2014) Exploring the pharmacogenomics knowledge base (PharmGKB) for repositioning breast cancer drugs by leveraging Web ontology language (OWL) and cheminformatics approaches. Pac Symp Biocomput :172-82
Alvarellos, Maria L; Lamba, Jatinder; Sangkuhl, Katrin et al. (2014) PharmGKB summary: gemcitabine pathway. Pharmacogenet Genomics 24:564-74
Bell, Gillian C; Crews, Kristine R; Wilkinson, Mark R et al. (2014) Development and use of active clinical decision support for preemptive pharmacogenomics. J Am Med Inform Assoc 21:e93-9
Province, M A; Goetz, M P; Brauch, H et al. (2014) CYP2D6 genotype and adjuvant tamoxifen: meta-analysis of heterogeneous study populations. Clin Pharmacol Ther 95:216-27
Pereira, Naveen L; Redfield, Margaret M; Scott, Christopher et al. (2014) A functional genetic variant (N521D) in natriuretic peptide receptor 3 is associated with diastolic dysfunction: the prevalence of asymptomatic ventricular dysfunction study. PLoS One 9:e85708
Wang, Liewei; Weinshilboum, Richard (2014) Metformin pharmacogenomics: biomarkers to mechanisms. Diabetes 63:2609-10

Showing the most recent 10 out of 51 publications