Praise for PharmGKB

PharmGKB is “the Holy Grail” for DNA STAT, a company that provides pharmacogenomics testing for patients. DNA STAT goes on to praise PharmGKB’s “accessibility and comprehensiveness” and highlights its “interactive SNP features and tools for education and clinical implementation of genetic data.”

Ifosfamide PK and PD pathways published in PG&G

Ifosfamide is a produg used in combination chemotherapy for the treatment of solid tumors. Around 20% of patients experience toxicity. Pathways depicting the genes involved in the pharmacokinetics and pharmacodynamics of ifosfamide have been published in PG&G. Variants in these genes that are associated with toxicity and drug resistance are discussed.

Click on the pictures to view the pathways:

Pharmacokinetics

Pharmacodynamics

Read the publication:

PharmGKB summary: ifosfamide pathways, pharmacokinetics and pharmacodynamics.
Lowenberg D, Thorn CF, Desta Z, Flockhart DA, Altman RB, Klein TE.

Pharmacogenetics & Genomics. 2014 Feb;24(2):133-8.

New PharmGKB VIP Summary: CYP4F2

Cytochrome p450, family 2, subfamily F, polypeptide 2 (CYP4F2) is known to catalyze multiple biological reactions.  It is predominantly expressed in the liver and kidneys, although there is evidence that it is also expressed in the intestines. Of specific interest in pharmacogenetics, hepatic CYP4F2 regulates the bioavailability of vitamin K and vitamin E and is currently studied to determine how polymorphisms in CYP4F2 affect warfarin dosing in patients. A single variant in CYP4F2 (rs2108622) is significantly associated with small, but significant alterations in warfarin dosage in Asian and Caucasian populations.

For more information on this VIP gene and variant, please see the VIP tab for CYP4F2.

Introducing CFTR as a Very Important Pharmacogene (VIP)

Variants within the CFTR gene underlie Cystic Fibrosis (CF). Traditionally, drugs used in the treatment of this disease have focused on ameliorating symptoms, fighting infection, thinning mucus and dampening inflammation. Now, drug development is focusing on pharmaceuticals that correct the underlying CFTR defect. The PharmGKB CFTR VIP summary describes potential treatment strategies that target defects conferred by particular classes of CFTR variants.

Read VIP information about these CFTR variants: 

• F508del-CFTR is prematurely degraded, failing to reach the plasma membrane. 

          Variants resulting in CFTR gating defects:

• G551D
• S549N
• G1244E 
• G1349D
• G178R
• G551S
• S1251N
• S1255P
• S549R(A>C) and S549R(T>G) 

                                                             

CPIC simvastatin & SLCO1B1 guideline 2014 update published

The 2014 update of CPIC guideline regarding SLCO1B1 and simvastatin-induced myopathy, has been published in Clinical Pharmacology and Therapeutics. CPIC extensively reviewed the literature from February 2011 to December 2013 and concluded that the dosing recommendations provided in the 2012 CPIC guideline for SLCO1B1 and simvastatin-induced myopathy have not changed.

The 2014 update includes the following additions:

• Created comprehensive translation tables mapping SLCO1B1 genotypes to coded genotype/phenotype summaries, electronic health record (EHR) priority result notation and interpretation (consultation) text to facilitate incorporation of SLCO1B1 pharmacogenetics into EHR with clinical decision support.
• Provided a brief review regarding SLCO1B1 genotype and risk of myopathy for other statins.
• Updated SLCO1B1 * allele nomenclature and functional status (Supplemental Table S1 and S2)
• Updated evidence linking SLCO1B1 genotype to phenotype (Supplemental Table S5).
• Updated FDA dosing recommendations (Supplemental Table S7)
• Added figure depicting clinical implementation workflow for EHR (Supplemental table S2)

View the interactive CPIC simvastatin dosing guideline based on SLCO1B1 genotypes, with the available full update and original published guidelines.


Read the article:
The Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for SLCO1B1 and simvasatin-induced myopathy: 2014 update. Ramsey LB, Johnson SG, Caudle KE, Haidar CE, Voora D, Wilke RA, Maxwell WD, McLeod HL, Krauss RM, Roden DM, Feng Q, Cooper-DeHoff RM, Gong L, Klein TE, Wadelius M, Niemi M.
Clinical Pharmacology & Therapeutics accepted article preview online 2014 Jun 11. doi: 10.1038/clpt.2014.125.

New publication: PharmGKB Uric acid-lowering drugs pathway

Disorders involving uric acid levels are prevalent (e.g. gout, hyperuricemia and resultant kidney failure) and pharmaceuticals that reduce the generation, increase the removal or prevent the absorption of uric acid have been developed to treat these disorders.

Two PharmGKB pathways depicting the mechanism of action of these drugs and the genes involved in these pathways have been published in PG&G.

The article details the genetic associations behind severe adverse reactions induced by allopurinol (Stevens-Johnson syndrome and toxic epidermal necrolysis) and rasburicase (hemolysis).

Read the article:
PharmGKB summary: uric acid-lowering drugs pathway, pharmacodynamics.

McDonagh EM, Thorn CF, Callaghan JT, Altman RB, Klein TE.
Pharmacogenetics & Genomics. 2014 Jun 9. (Epub ahead of print)

Click on each picture to view an interactive version of the pathway in PharmGKB

Big Data Conference Videos

Videos of the talks at the Stanford Big Data Conference 2014 are now available to watch online (view agenda).

A selection of our favorite talks that are currently available to watch: 

• Michelle Whirl-Carrillo (Associate Director of PharmGKB, Stanford University) discusses the benefits and barriers of implementing pharmacogenetics into a patient's electronic medical record and the hope that big data could enable us to overcome some of these barriers. 
• Philip Bourne (NIH) raises current issues in data science (including a need for reproducibility, data citation and reward) and discusses some of the options that could begin to address these issues.
• Vinod Khosla (Khosla Ventures) controversially argues for taking humans out of the decision-making process to improve healthcare, and that medical monitoring devices and machine learning will lead us to new discoveries and guide new research opportunities.
• John Ioannidis (Stanford University) argues that we have been most successful in finding genetic associations when consortia groups have pooled cohorts together, and that we need more big data of big data. 
• Teri Manolio (NHGRI) uses the example of HLA-B*1502 as a strong predictor for carbamazepine-induced Steven-Johnson-Syndrome to argue for the clinical implementation of genomic information, discusses assessing clinically-relevant variants and raises the next big questions in genomic medicine implementation. 
• Dan Roden (Vanderbilt University) reiterates the need for large numbers of patients in order to extract rare phenotypes or genetic variants, and discusses using Vanderbilt's electronic medical records to discover novel genetic associations.