Updated UGT1A1 VIP Summary

We have updated the UGT1A1 VIP summary to provide more in-depth information on this important pharmacogene. UGT1A1 is a member of the uridine diphosphate glucuronosyltransferase (UGT) enzyme family, and is responsible for the glucuronidation of target substrates. The transfer of glucuronic acid renders xenobiotics and other endogenous compounds water soluble, allowing for their biliary or renal elimination. Pharmaceutical drugs are a common substrate of UGT1A1, making this enzyme relevant to pharmacogenetic research.

The VIP summary posted on PharmGKB gives background on the UGT family and summarizes the function of UGT1A1, as well as the roles of UGT1A1 alleles in diseases and pharmacogenetics. In particular, certain genetic variants of UGT1A1 have been implicated in adverse reactions to irinotecan. For more information, please read the entire UGT1A1 VIP summary at PharmGKB.

View all VIP gene summaries at PharmGKB. 

The PGRN Translational Pharmacogenetics Program (TPP) publishes paper on overcoming challenges of real-world implementation

The Translational Pharmacogenetics Program (TPP) is a Pharmacogenomics Research Network (PGRN)-led initiative with the goal to identify barriers and develop real-world solutions to implement evidence-based pharmacogenetic tests in diverse health care settings. The participating sites include 6 implementation institutions (Universityof Maryland, University of Florida, St. Jude Children's Research Hospital, Vanderbilt University, Mayo Clinic, and Ohio State University),  as well as PharmGKB which serves a coordination and knowledge sharing and dissemination role and  Pharmacogenomic Ontology (PHONT) at the Mayo Clinic which provides data harmonization and standardization support.

The TPP investigators has published the design manuscript in Clin Pharmacol Ther this month. This paper discusses challenges and implementation barriers to translation of pharmacogenomics in clinical practice. Each implementation site institutes CLIA-based pharmacogenomics testing, reports results in EHR for clinical decision and tracks summary descriptions and implementation metrics to objectively evaluate the effectiveness of implementation. TPP also creates "look up" tables (posted on PharmGKB) which contain phenotype and clinical decision support system information based on haplotypes and diplotypes. These tables “complement the existing CPIC guidelines by providing therapy recommendations for a more comprehensive coverage of pharmacogenetic test results. They represent the current state of knowledge and demonstrate the range of observed results and recommended actions across sites”.

Read more:

The Pharmacogenomics Research Network Translational Pharmacogenetics Program: Overcoming Challenges of Real-World Implementation.

Shuldiner AR, Relling MV, Peterson JF, Hicks K, Freimuth RR, Sadee W, Pereira NL, Roden DM, Johnson JA, Klein TE. Clin Pharmacol Ther. 2013 Mar 19. doi: 10.1038/clpt.2013.59.

Implementing pharmacogenetics: more than one gene at a time

It has been well recognized that drug response is complex and determined by not only one gene, but rather by the interplay of multiple gene products. However, studies of combined impact of more than one gene are scarce, limiting the potential for making strong dosing recommendations based on multiple genes. In this issue of Clinical Pharmacology & Therapeutics, Johnson et al. highlight the importance of multigenic approaches for pharmacogenetics research and clinical implementation, using the examples of tricyclic antidepressant (CYP2D6/CYP2C19) and warfarin (VKORC1/CYP2C9). The authors recommend investigators to conduct “studies in the context of well-defined pharmacogenetic markers, so that the additional impact of the new gene can be placed in the context of the existing pharmacogenetics literature for that drug. More important, it suggests that discoveries of additional pharmacogenes may actually be enhanced by consideration of known pharmacogenetic markers”.

Read more:

Clinical implementation of pharmacogenetics: more than one gene at a time.

Johnson JA, Klein TE, Relling MV. Clin Pharmacol Ther. 2013 May;93(5):384-5. doi: 10.1038/clpt.2013.7.

Clinical notes used for pharmacovigilance

A team at Stanford University have computationally extracted information from free-text clinical notes in medical records, in order to identify drug-induced adverse events and adverse reactions from drug-drug interactions. Information from the notes was deidentified and transformed into a patient-feature matrix using a medical ontology hierarchy system. They demonstrate that the method could be used to flag potential adverse reactions earlier than FDA alerts are reported by current methods.

Read More:

Pharmacovigilance Using Clinical Notes

Lependu P, Iyer SV, Bauer-Mehren A, Harpaz R, Mortensen JM, Podchiyska T, Ferris TA, Shah NH. 
Clin Pharmacol Ther. 2013 Mar 4. doi: 10.1038/clpt.2013.47.

Venlafaxine Pathway

Venlafaxine is a serotonin-norepinephrine reuptake inhibitor (SNRI) marketed for the treatment of depression disorders. The molecular targets of venlafaxine are the serotonin and norepinephrine transporters, resulting in inhibition of serotonin and noradrenaline reuptake from the synaptic cleft.

A new pathway is posted on PharmGKB summarizing the metabolism of venlafaxine.

Demethylation to O-desmethylvenlafaxine, a pharmacological active metabolite, is the primary route of the first pass metabolism of venlafaxine. Cytochrome P450 2D6 (CYP2D6) is the major enzyme involved in the O-desmethylvenlafaxine formation.

The pharmacokinetics of venlafaxine is affected by the CYP2D6 metabolizer phenotype. Read the entire pathway description for more information about the influence of genetic variations on venlafaxine metabolism and treatment outcome.

View all pathways at PharmGKB.