Tuesday, July 26, 2016

Pharmacogenomics discussed in the Summer 2016 issue of Genome magazine

The current issue of Genome magazine includes the article "Determining a Drug Response", which provides a discussion of pharmacogenomics and contains interviews with multiple members of the Clinical Pharmacogenetics Implementation Consortium (CPIC), including Mark Dunnenberger (director of the pharmacogenomics program at NorthShore University HealthSystem), Stuart Scott (assistant professor of genetics and genomic sciences at Mt. Sinai's Icahn School of Medicine) and Mary Relling (chair of Pharmaceutical Sciences at St. Jude Children's Research Hospital and CoPI of CPIC). The article discusses several important genes within the field of pharmacogenetics, including CYP2D6HLA-B, and G6PD; it also briefly covers CYP2C19 and its role in response to antidepressants and antipsychotics.

CYP2D6 is responsible for metabolizing a large number of commonly prescribed drugs. The Genome article focuses on its role in converting codeine into morphine: CYP2D6 poor metabolizers cannot effectively metabolize codeine, and therefore often do not experience sufficient pain relief, while CYP2D6 ultra-rapid metabolizers metabolize codeine into morphine too efficiently, increasing the risk for morphine intoxication. The CPIC guideline for CYP2D6 and codeine recommends use of an alternative agent in these two types of CYP2D6 metabolizers. Indeed, as Mark Dunnenberger notes in the article, there have been several reports of severe or fatal toxicity in breastfeeding infants whose CYP2D6 ultra-rapid metabolizer mothers received codeine; these instances prompted the FDA to place a warning on the codeine drug label regarding breastfeeding infants. The codeine drug label also contains a black box warning regarding potential respiratory depression and death in CYP2D6 ultrarapid metabolizer children who receive codeine following tonsillectomy or adenoidectomy.

Variants within the HLA-B gene have been strongly linked with adverse reactions to a variety of different drugs. Odds ratios in the double, triple or even quadruple digits have been seen for the risk of abacavir-induced hypersensitivity reactions in individuals with HLA-B*57:01, and allopurinol-induced Stevens-Johnson Syndrome (SJS) or toxic epidermal necrolysis (TEN) in individuals with HLA-B*58:01. In fact, the association between abacavir hypersensitivity and HLA-B*57:01 is significant enough that the FDA-approved drug label for abacavir currently states that genetic testing for this variant must be performed prior to initiating treatment, and that abacavir is contraindicated in carriers of *57:01. No such recommendations currently exist on the allopurinol label. Other significant HLA-B pharmacogenetic associations include the risk for carbamazepine- or phenytoin-induced SJS/TEN in patients with HLA-B*15:02.

While alternative agents exist for codeine, abacavir and allopurinol, some drugs do not have safe or effective alternatives. Rasburicase, as the article notes, is one example: leukemia or lymphoma patients are treated with the drug for tumor lysis syndrome, a potentially life-threatening condition. However, individuals with a deficiency in glucose-6-phosphate dehydrogenase (G6PD) who receive rasburicase are at a high risk for experiencing hemolytic anemia, which is itself a life-threatening adverse reaction. As Mary Relling comments in the article, alternatives exist for rasburicase but they are not optimal, meaning clinicians need to carefully weigh the pros and cons of prescribing the drug.

The article concludes with a discussion of the present and future directions of pharmacogenetics. While strong, consistent and clinically relevant associations exist for a large number of genes and drugs, the healthcare system infrastructure has not caught up with research. Stuart Scott comments on the current difficulties of getting reimbursement for genetic tests and receiving genetic results in a timely manner. He also discusses the potential benefits of having patients' genetic information integrated into the electronic medical record, which would allow doctors and pharmacists to easily access genetic data and receive alerts on pharmacogenetic associations.


View the CPIC guideline for CYP2D6 and codeine
View the CPIC guidelines for HLA-B and abacavir and allopurinol
View the CPIC guideline for G6PD and rasburicase

Thursday, July 21, 2016

Standardized allele function and phenotype terms for clinical pharmacogenetic test results

In December 2014 and February 2015, we blogged about the CPIC term standardization project. CPIC (Clinical Pharmacogenetics Implementation Consortium) just published the results of this project in Genetics in Medicine.

Consensus terms for allele function and phenotype were determined by starting with a broad list of terms currently used by genetic testing laboratories and in the literature followed by a modified Delphi method surveying experts in the pharmacogenomics field. Ninety percent of the participants agreed on the final sets of pharmacogenetic terms.

Defining this standard vocabulary is an important step forward to reduce confusion across clinicians, laboratories, and patients.  Electronic health records with clinical decision support are essential for the implementation of pharmacogenetics, and wide use of these terms will facilitate sharing pharmacogenetic data across diverse electronic health record systems.

The terminology will be used in new and updated CPIC guidelines. Furthermore, Dr. James Hoffman, senior author of the study, told us: "We have already seen great interest in various organizations adopting these terms, and we hope this will only continue. For example, LOINC has already included the terms in a recent release, and the terms have been endorsed by the Association for Molecular Pathology."

Read the article on Genetics in Medicine: 

Standardizing terms for clinical pharmacogenetic test results: consensus terms from the Clinical Pharmacogenetics Implementation Consortium. Kelly E. Caudle, Henry M. Dunnenberger, Robert R. Freimuth, Josh F. Peterson, Jonathan D. Burlison, Michelle Whirl-Carrillo, Stuart A. Scott, Heidi L. Rehm, Marc S. Williams, Teri E. Klein, Mary V. Relling, James M. Hoffman.

Monday, July 11, 2016

Improvements for Variant data in PharmGKB

PharmGKB is constantly improving the way we organize and annotate data in the field of pharmacogenomics. One of our recent improvements involves how we store and refer to Variants. Genetic variation is a very important part of what we do here at PharmGKB. That importance means we need a clear and effective way to store and use genetic variations throughout the site and services we offer.

The primary change is that Variant objects are now assigned PharmGKB Accession Identifiers (i.e. PA numbers). You’ve probably already seen that Genes and Chemicals have Accession Identifers (e.g. CYP2C19 has id PA124) and now that same system of identifiers is extended to the Variants that we annotate. This may not seem like a big change on the outside but it has big implications for how we can use Variants in our tools and through our API. One of these implications is that we’ll be able to more easily integrate rare variants and variations that aren’t tied to records in dbSNP.

The second change is that we will only store data on variants that we’ve annotated. It was previously possible to link to https://www.pharmgkb.org/rsid/{rsid} and get a summary of the variant whether PharmGKB had annotated that dbSNP record or not. PharmGKB has a large amount of annotations on pharmacogenomic knowledge but that covers a very, very small percentage of the 153,953,962 variants cataloged in the current release of dbSNP. This method made our system bloated and more complex so we trimmed it down. PharmGKB curators now add Variant records as they annotate them and can update Variant information when necessary.

Other improvements to Variant records include:
  • Each variant gets a mandatory name and optional symbol (e.g. rs# if applicable)
  • Variants have a primary sequence location that we consider canonical for our annotations but this location is optional for variants that haven’t been located on a specific sequence yet.
  • Variants can also have alternate sequence locations. For example, our primary location for a variant is on GRCh37 but we may have an alternate sequence location for GRCh38.
  • We now have better support for tracking alternate names given to a Variant in publications
  • Variants will use the GRCh37 assembly for their primary location when possible
Existing URLs for Variant pages on PharmGKB remain in the same format (i.e. https://www.pharmgkb.org/rsid/{rsid}) and we also support the new URL format of https://www.pharmgkb.org/variant/{PA#}. The layout of the Variant page has been updated slightly to add in the new information about sequence locations and other properties.

Keep an eye out for more changes to Variant pages and data as we take advantage of these new features.

Friday, July 8, 2016

Prediction of CYP2D6 phenotype from genotype across world populations

A. Gaedigk and S. Leeder together with PharmGKB published an article in Genetics in Medicine about the prediction of CYP2D6 phenotypes from genotype data across world populations (http://www.nature.com/gim/journal/vaop/ncurrent/full/gim201680a.html).

In the supplemental materials of Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines involving CYP2D6 (https://www.pharmgkb.org/view/dosing-guidelines.do?source=CPIC and https://cpicpgx.org/guidelines/), allele frequencies across populations have been systematically captured and updated with each new guideline or update. Using this frequency table, the article describes the calculation of diplotype frequencies and the translation into phenotype based on the activity score system. The prevalence of genetically predicted poor, intermediate, normal, and ultrarapid metabolizer phenotypes are presented for major populations.

The article also includes a critical discussion highlighting the challenges of phenotype prediction from genotype data. This includes the overestimation of certain alleles in studies with minimal CYP2D6 genotyping and issues of grouping alleles and resulting diplotypes into functional and phenotype categories.

Thursday, July 7, 2016

Common variant found in populations of African descent linked with increased risk of venous thromboembolism

Roxana Daneshjou, along with co-authors Teri Klein and Russ Altman of PharmGKB, have published a paper describing a previously uncharacterized SNP in the Protein S (PROS1) gene that increases risk of venous thromboembolism (VTE).  VTE is more common in African American populations than in populations of European descent, yet the genetic risk factors identified previously are found predominantly in European populations. The V510M (rs138925964) variant in PROS1 described in Daneshjou, et al. was validated in a multi-center cohort and is expected to have a damaging effect on protein S function. This SNP was found at about 1% in populations of African descent but was found rarely in populations of European descent and is expected to confer an odds ratio of 4.61 (95% CI = 1.51- 15.20) for VTE. This finding highlights the importance of including diverse populations in genetic research. 

A video describing the study and findings can be found on Wiley's Youtube Channel and on the Molecular Genetics and Genomic Medicine website.