Friday, October 26, 2018

PharmGKB data used to establish a minimum genetic testing panel for psychiatry

The lack of standardization of which genes or alleles should be included in pharmacogenetic testing panels is a major barrier to the full implementation of pharmacogenomics in the clinic. In an effort to help clinicians select an appropriate pharmacogenetic test, Dr. Chad Bousman and Dr. Abdullah Al Maruf of the University of Calgary and Dr. Daniel Mueller of the University of Toronto gathered available pharmacogenetic evidence from a number of sources, including PharmGKB, CPIC and the Pharmacogene Variation Consortium(PharmVar). This evidence informed the authors’ recommendations of which genes and variants should be included in a minimum pharmacogenetic testing panel for psychiatry.

For inclusion on the panel, a variant drug interaction needed to be associated with a Level 1A or Level 1B Clinical Annotation in PharmGKB, an FDA or EMA drug label which specifically recommended or required pharmacogenetic testing prior to administering the drug and/or a CPIC or DPWG dosing guideline recommendation. Variants also had to be present at a frequency of >1% in at least two of the seven major Human Genome Diversity Project - Centre d'Etude du Polymorphisme Humain (HGDP-CEPH) populations, which are used in the PharmGKB gene information tables. To ensure that the panel could be easily validated, each variant had to have reference material available through the Genetic TestingReference Materials Coordination (GeT-RM) Program.

Starting from a list of 91 drugs which are used in psychiatry, 448 initial gene-drug interactions were identified. Following visualization of the data using a network map showing the strength of evidence for each interaction, 31 drug-gene pairs were determined to have sufficient evidence to warrant their inclusion on the minimum testing panel. The resulting panel, published in Current Opinion in Psychiatry, contains 16 alleles in the genes CYP2D6, CYP2C9, CYP2C19, HLA-A and HLA-B.

The authors emphasize that this panel should be considered a minimum standard for pharmacogenetic testing in psychiatry and that potential gene-gene interactions are not covered. The panel will also need to be regularly updated to include new genes and variants as new guidelines and published evidence become available.

We would like to note a few relevant points about the paper. Given the reliance on our Level 1A/1B Clinical Annotations, it is important to state that some genes with a high level pharmacogenomic association may have variants or alleles which are not covered by a Level 1A or 1B Clinical Annotation, due to a lack of published evidence specifically studying these alleles.  As an example, CYP2D6 has over 100 documented variant alleles.  While PharmGKB has multiple Level 1 Clinical Annotations summarizing associations between CYP2D6 alleles and drugs, not every allele in every diplotype that CPIC provides recommendations for will be represented in our clinical annotations.

It is unclear how exactly information from PharmVar was used in the process of designing this panel. While PharmVar provides a wealth of information about pharmacogenetic allele definition and nomenclature, it does not assign a level of evidence to pharmacogenetic variants in the way that PharmGKB assigns a level of evidence in our Clinical Annotations. The paper also does not explicitly state whether drug labels which recommend or require testing were identified using the PharmGKB drug label annotations or by another method. In any case, we would like to emphasize that the PGx level of drug labels annotated in PharmGKB is determined by PharmGKB curators rather than any regulatory body.

Readers should also note that using allele frequencies as a condition for inclusion on a testing panel will, by definition, result in rare pharmacogenetic alleles remaining undetected in patients.

Further information about the levels of evidence assigned to our Clinical Annotations can be found here while information about the PGx levels assigned to our annotated drug labels can be found here. You can access annotated drug labels and annotated CPIC and DPWG guidelines through the PharmGKB website.

Wednesday, October 24, 2018

DPYD genotyping implementation study published

In a journal article published online last week in The Lancet Oncology, Henricks et al. reported that DPYD genotype-based dose reductions of fluorouracil and capecitabine in cancer patients resulted in improved safety outcomes and was feasible in clinical practice. 

The authors prospectively genotyped four DPYD variants: rs3918290 (1905+1G>A; DPYD*2A)rs55886062 (1679T>G; DPYD*13)rs56038477 (1236G>A; haplotype B3) and rs67376798 (2846A>T). Heterozygous DPYD variant allele carriers for rs3918290 and rs55886062 received an initial dose reduction of 50%. Heterozygous variant allele carriers for rs56038477 and rs67376798 received an initial dose reduction of 25%, since these variants result in moderately reduced DPYD activity. Wild-type patients were treated according to the current standard of care, and homozygous or compound heterozygous variant allele carriers were excluded.

Results showed that the genotype-guided dosing reduced the risk of severe fluoropyrimidine-related toxicity in patients carrying the rs3918290, rs55886062 and rs67376798 variants, though patients carrying the rs67376798 variant still had an increased risk for toxicity compared with wild-type patients. Carriers of the rs56038477 variant did not have a reduction in severe toxicity. The authors concluded that a dose reduction of 25% in patients with rs56038477 and rs67376798 variants was not sufficient to lower the risk of severe toxicity, and suggested that a larger dose reduction may be required. 

Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for DPYD genotype-guided fluoropyrimidine dosing recommend a dose reduction of 50% in heterozygous carriers of the rs3918290 and rs55886062 variants. However, they do not recommend an exact dose reduction for heterozygous carriers of the rs56038477 and rs67376798 variants, rather, they suggest a range of 25-50%. This lack of specificity was due to limited evidence for genotype-guided dosing of these variants. However, Amstutz and Largiadèr, in their accompanying commentary, suggest that the Henricks et al. study  provides evidence to support a recommendation for a 50% dose reduction in all heterozygous variant allele carriers. Amstutz and Largiadèr also note that 8% of white patients carry one of these four variants, meaning that the benefits shown in this study affect a substantial proportion of patients treated with fluoropyrimidines. 


Read the CPIC dosing guideline for DPYD and fluoropyrimidine dosing
Read the DPWG dosing guidelines for fluorouracil and capecitabine
Read the PharmGKB annotations of the CPIC dosing guideline for fluorouracil and capecitabine

Monday, October 8, 2018

PharmGKB oxycodone pathway published in Pharmacogenetics and Genomics

The PharmGKB Oxycodone Pathway, Pharmacokinetics is featured on the cover of the October 2018 issue of Pharmacogenetics and Genomics. Oxycodone is an opioid analgesic metabolized by CYP2D6 and CYP3A4/5 to a number of metabolites, including oxymorphone which itself can be used as an analgesic.

The pathway was produced by scientific curator Dr. Rachel Huddart in collaboration with Dr. Melissa Clarke of the Medical Home Development Group and Whole Genome Science Foundation. It discusses the current state of knowledge of both the pharmacokinetics and pharmacodynamics of oxycodone as well as pharmacogenetic research into the drug. Oxycodone is covered by a DPWG guideline, an annotated version of which can be found on the PharmGKB website. You can access the Oxycodone Pathway, Pharmacokinetics on the PharmGKB website here.

Thursday, October 4, 2018

CPIC grant awarded

The co-PIs of the Clinical Pharmacogenetics Implementation Consortium (CPIC), Drs. Mary Relling of St. Jude Children's Research Hospital (SJCRH) and Teri Klein of Stanford University, will receive $5 million over the next 5 years from the National Institutes of Health (NIH) to continue and expand the project.  CPIC was created in 2009 as a partnership between the Pharmacogenomics Research Network (PGRN) and PharmGKB to provide peer-reviewed, evidence-based genotype-directed drug prescribing guidelines for clinicians.  The new funding will enable CPIC to continue its mission to create and update guideline publications and supporting materials to enable translation of pharmacogenomics into the clinic and electronic health care records.  For more information, see the announcement from SJCRH.

Monday, October 1, 2018

Curators' Favorite Papers

An article in Pharmacogenomics Journal puts the spotlight on the need to continue look for candidate genes and variants in many populations even when it seems as though current candidates explain a large amount of variability.  [PMID: 30100615] identifies new candidate genes and variants that are important when the most well known variants are not present.

Rosuvastatin is a HMG-CoA reductase (HMGCR) inhibitor or statin, used in the treatment of high cholesterol and heart disease. The pharmacokinetics of individual statin drugs are influenced by their hydrophobicity, with the more hydrophobic statins being highly dependent on transporters for transport in and out of cells. Rosuvastatin is a hydrophobic statin and undergoes minimal metbolism with around 80% of drug dose excreted unchanged in feces [PMID: 14693307]. The transporter variants SLCO1B1 c.521T>C (rs4149056 p. Val174Ala) and ABCG2 c.421C>A (rs2231142, p. Gln141Lys) are key candidates in rosuvastatin PGx [PMID:16198652][PMID: 25630984]. Soko et al demonstrate that these variants differ in frequency in a range of African populations and are absent in some. They studied rosuvastatin PK in a group of individuals of Bantu decent and identified new variants in the SLCO1B1 and ABCG2 transporters and additional variants in other transporter genes  and regulatory genes that influence transporter expression. PharmGKB will be updating our rosuvastatin PK pathway to include these new genes and variants.