Thursday, March 25, 2021

PharmGKB introduces scoring system for variant and clinical annotations and updated Levels of Evidence

Since their introduction in 2010, clinical annotations have become one of the most popular features of PharmGKB. Each clinical annotation summarizes a phenotypic association between a drug and genetic variant, shows relevant findings from the curated literature as variant annotations and is assigned a level of evidence to indicate the strength of support for that association in the literature.

As the number of variant and clinical annotations in PharmGKB has increased, it became a challenge to maintain consistency when assessing all the available evidence and assigning a level of evidence to clinical annotations. To address this, PharmGKB began a project at the end of 2019 to improve standardization across clinical annotations by establishing new curator tools and protocols. We are pleased to be able to release the first phase of this project to users today.

Central to this work has been the development of a scoring system which assigns scores to both variant and clinical annotations as a numerical summary of the evidence underlying each annotation. Variant annotations are scored in a five-step process which assesses various attributes found in both the main annotation and in the study parameters. This scoring of variant annotations is not a judgement of study quality. It is a metric used by PharmGKB curators when comparing variant annotations against each other as part of the process of creating and updating clinical annotations.

Annotation Scoring


The scoring process can be described using the following formula, with a list of attributes scored in each step given below. A more detailed description can be found on our Variant Annotation Scoring page.

(Step 1 + Step 2 + Step 3 + Step 4) x (Step 5a x Step 5b)

Step 1 – Phenotype category (toxicity, efficacy, etc.)
Step 2 – Reported p-value
Step 3 – Cohort size
Step 4 – Effect size
Step 5a – Weighting by study type
Step 5b – Weighting by reported association and significance

When a variant annotation is attached to a clinical annotation, the variant annotation’s score contributes to the score for the clinical annotation. Curators can mark any variant annotation which reports an association in the opposing direction to the assertion made in the clinical annotation as a conflicting variant annotation. For example, if a clinical annotation reports that the G allele is associated with decreased response to a drug, a variant annotation which reports that the G allele is associated with increased response would be considered to be conflicting.

Variant annotations which are marked as conflicting are assigned a negative score and receive a tag which can be seen on a clinical annotation’s page. It is important to realize that a variant annotation is only considered to be conflicting within the context of a specific clinical annotation and that the score of the variant annotation only changes in that clinical annotation.
Supporting CPIC and DPWG clinical guidelines or FDA-approved drug labels can also be added to a clinical annotation by curators and can contribute to that annotation’s score.

Assigning a score to guidelines and labels has helped us to better define our Level 1A clinical annotations. Now, any annotation with support from a qualifying CPIC or DPWG guideline or an FDA label is assigned as 1A. More information about clinical annotation scoring, including how a clinical guideline or drug label qualify for addition to a clinical annotation can be found here.

In this first release, only DPWG guidelines which mention specific alleles in the recommendation text have been used to support 1A clinical annotations. We are aware that DWPG provide additional mapping in supporting documents and plan to look at these in more detail in the near future. This will allow more DPWG guidelines to be used to support 1A clinical annotations.

A clinical annotation’s score is used to assign a suitable level of evidence for the annotation. A table with scoring ranges and detailed descriptions of each level can be found on our level of evidence page. We have introduced a separate scoring range for rare variants to account for the fact that these tend to only be reported in small studies, even though there is an underlying pharmacogenomic association. Information on how PharmGKB defines a rare variant can be found here. A clinical annotation’s score is only used to determine the level of evidence and is not intended to be used to rank or compare clinical annotations within a given level of evidence.

A clinical annotation’s score is now displayed on clinical annotation pages. This includes a score breakdown to indicate how different types of evidence are contributing to the annotation’s score. In rare cases, the team may feel that a clinical annotation’s score is not reflective of the underlying evidence and can, after group discussion and consensus, choose to override the scoring system. When an annotation’s level has been overridden, it is displayed on the annotation page along with a written justification for the override.

This scoring system minimizes subjectivity in the assessment of clinical annotations and makes the assignment of levels of evidence more consistent, reproducible and transparent to users. To complement the scoring system, PharmGKB clinical annotations are now being written to new standards as well as displaying additional information for users.

New Clinical Annotation Features


Clinical annotations will now begin to use a new template and set of standardized sentences to highlight caveats and other considerations to users. They are also now written only on a single drug, drug combination or drug class and a single phenotype category (e.g. dosage, efficacy, etc.). Additionally, we have introduced extra checks to ensure that all level 1 and 2 clinical annotations are supported by two independent pieces of evidence.

PharmGKB now offers two distinct types of clinical annotation: gene-level and variant-level. Variant-level annotations provide genotype-based summaries for a specific rsID (example), while gene-level clinical annotations display summaries for one of more star alleles of a gene (example). These formats have always been part of our clinical annotations, but have now been formalized with templates to standardize annotation writing.

The score and level of evidence assigned to gene-level clinical annotations represents the strength of evidence underlying the association at the level of the gene rather than at the level of the individual variant. A ‘Limited Evidence’ tag is used to highlight alleles which are supported by substantially less evidence than the overall level indicated by the level of evidence. Where possible, we also now display allele function as assigned by CPIC.

These changes mean that clinical annotations are easier to compare against each other and that the level of evidence is more representative of the evidence supporting a phenotypic association for the variant-drug pair. We acknowledge that this has reduced the number of clinical annotations at levels 1B, 2A and 2B however, these annotations are now more consistent and based on quantitative criteria.

This project has entailed detailed review of over 350 clinical annotations by our curation team and, as part of this release, all level 1 and 2 clinical annotations have been rewritten to our new standards and reviewed by at least two curators. Updating clinical annotations at levels 3 and 4 to our new standards will continue as part of our regular curation activities. Users can check the history section of each annotation to see if there has been a recent update.
We are excited to bring the first phase of this project to PharmGKB users and welcome user comments or suggestions sent to feedback@pharmgkb.org.

Tuesday, March 23, 2021

Two new pathways released: Allopurinol Pharmacokinetics and Pimozide Pharmacokinetics.



Allopurinol is a purine analogue used in the treatment of gout. This drug has a level A CPIC Guideline for allopurinol and HLA-B. The new pathway shows the candidate genes and metabolites involved in Allopurinol Pharmacokinetics.


Pimozide is a typical antipsychotic FDA approved for treatment of Tourette’s disorder. The FDA drug label has a testing recommendation for CYP2D6 poor metabolizers and the gene-drug pair is level A/B on the CPIC list and noted for future guideline development. The new pathway was developed by recent work from Chapron et al [PMID: 32847865], and shows candidate genes and metabolites involved in Pimozide Pharmacokinetics in a stylized liver cell.

Monday, March 1, 2021

Milestones in Payer Coverage Set to Expand Pharmacogenomic Testing

 A new perspective just out in Genetics in Medicine describes the improvements in the US payer landscape for pharmacogenomics test reimbursement from this past summer and their implications for the field moving forward.

The Medicare Administrative Contractors (MACs) participating in the Molecular Diagnostic Services (MolDx) program released their final local coverage determinations (LCDs) pharmacogenomic testing in July/August.

PharmGKB and CPIC view these as significant advances because of the large number of US Medicare patients impacted. Further, the LCDs state PGx testing as reasonable and necessary when medications have a clinically actionable gene(s)-drug interaction as defined by CPIC guidelines (category A and B) or the FDA (PGx information required for safe drug administration). Coverage for panel testing was also supported if more than one gene on the panel is considered reasonable and necessary for the safe use of a medication or if multiple drugs are being considered that have different relevant gene associations

The authors’ analysis lists >50 gene/drug pairs that are covered by the LCD and provides a map (below) of MAC regions impacted. They make a strong argument that harmonization of coverage is needed and that standardization, improved clarity in the regulatory landscape, practitioner education, and research to measure downstream clinical outcomes are needed more than ever to fully capture the value of pharmacogenomic testing. 




Geographical impact of the new LCDs. States within MolDx jurisdictions (shaded green) as well as those that are outside of the MolDx (in other MACs) are shown.


Edit 3/3/21 - Image was updated to correct a typo

Friday, February 19, 2021

PharmGKB and CPIC curated information displayed on ClinGen

PharmGKB and CPIC partnered with ClinGen last summer to bring curated pharmacogenomics (PGx) to the resource which defines the clinical relevance of genes and variants in the human genome. A new Pharmacogenomics column has been added to ClinGen's curated gene categories.  130 PGx genes curated by PharmGKB and/or CPIC are now listed on the ClinGen website with links back to the PharmGKB and CPIC websites for more detailed information.

ClinGen displays all gene-drug pairs from PharmGKB with Level 1 & 2 Clinical Annotations along with (1) a link to the relevant PharmGKB drug page, (2) the highest annotation level for the gene-drug pair (linked to the explanation of PharmGKB's Levels of Evidence), (3) the date of the last update and (4) a link to view all PharmGKB Clinical Annotations for that gene-drug pair.

ClinGen also displays all CPIC gene-drug pairs with levels A-D.  Where applicable, these are grouped by CPIC guideline with (1) a link to the CPIC guideline page and (2) gene-drug pairs list page.  Gene-drug pairs with provisional CPIC levels (i.e. those awaiting further evaluation and potentially guideline development) link to the gene-drug pairs list page. 



Thursday, February 18, 2021

Plavix manufacturers to pay $834 million to state of Hawaii

Bristol-Myers Squibb Co and Sanofi, the manufacturers of Plavix (clopidogrel) have been ordered to pay over $834 million to the state of Hawaii after failing to warn about the drug’s potential health risks to patients with combinations of CYP2C19 variants which result in a CYP2C19 poor metabolizer status.

Clopidogrel is metabolized to its active metabolite by CYP2C19, as shown in the PharmGKB clopidogrel pathway. Patients carrying CYP2C19 no function alleles (e.g. CYP2C19*2) have reduced or no conversion of clopidogrel to the active metabolite, which puts them at an increased risk of cardiovascular events. The CPIC guideline for clopidogrel recommends that CYP2C19 intermediate and poor metabolizers receive alternative antiplatelet therapy.

The companies were found to have violated Hawaii’s consumer protection laws by not disclosing that Plavix would be ineffective for as many as 30% of patients in Hawaii, many of whom are of Asian and Pacific Islander descent. Some CYP2C19 no function variants, such as CYP2C19*2, are found at higher frequencies in Asian and Pacific Islander populations compared to their frequency in European populations (see the CYP2C19 allele frequency table).

Judge Dean Ochiai ruled that Bristol-Myers Squibb Co and Sanofi “knowingly placed Plavix patients at grave risk of serious injury or death in order to substantially increase their profits” over a 12-year period from 1998 to 2010. Information about the effect of CYP2C19 no function alleles on the efficacy of Plavix was added to the drug label in 2009, and a Black Box warning to consider alternate therapy for CYP2C19 poor metabolizers was added in 2010. PharmGKB has annotated the Plavix label and highlights pharmacogenomic information found within the label.

Hawaii Attorney General Clare Connors emphasized the growing impact of pharmacogenomics on the pharmaceutical industry: “The order entered by the court today puts the pharmaceutical industry on notice that it will be held accountable for conduct that deceives the public and places profit above safety”.

In a joint statement, the companies said that “the overwhelming body of scientific evidence demonstrates that Plavix is a safe and effective therapy, including for people of Asian descent.” and that they plan to appeal.

Tuesday, February 16, 2021

HGVS annotations now available on PharmVar

We are excited to share that PharmVar is now providing HGVS annotations in addition to their more traditional annotations. To accommodate different styles, the Variation Window has been redesigned.

Clicking on any SNV on a PharmVar gene page will activate the variation window. The example shown below is for the CYP2C9*2 variant c.430C>T. This view provides SNV positions across all sequences, the link to the NCBI dbSNP identifier (rs number) as well as SNV frequency. There is also a bar providing the option to display all haplotypes with the selected variant.


The top portion of the variation window displays SNV coordinates according to Human Gene Variation Society (HGVS) nomenclature on the gene, transcript and genome (GRCh37 and GRCh38) levels. Coordinates are displayed as obtained through the NCBI Variation Services. 

The middle portion of the variation window displays SNV positions ‘PharmVar-style’ on the gene, transcript and genome (GRCh37 and GRCh38) levels giving positions for both count modes and detailing the reference and variant nucleotides. 

It is noted that HGVS and ‘PharmVar-style’ positions may differ for insertion/deletion variants in some instances, which is most likely explained by how sequences are aligned. Also, PharmVar displays single nucleotide insertions as ‘ins’ while HGVS displays them as duplications or ‘dup’. Additional details and examples are can be found in the PharmVar ‘Standards’ document. HGVS annotations are also accessible via API services.

PharmVar welcomes any feedback you may have through support@pharmvar.edu. 


Wednesday, February 10, 2021

Update to FDA-approved drug label annotations

In February 2020, we blogged about the FDA's newly released Table of Pharmacogenetic Associations. Since then, there has been much interest in understanding how that table was created, how it compares to the information on the drug labels, and how it compares to the FDA's Table of Pharmacogenomic Biomarkers in Drug Labeling, which has existed for many years and is routinely curated by PharmGKB.  With this in mind, PharmGKB has created a section on its FDA-approved drug label annotations for information from the Table of Pharmacogenetic Associations (Figure 1). 

Figure 1. Screenshot of part of the FDA-approved drug label annotation for codeine.









We also have a new landing page specifically for FDA-approved drug label annotations that can be sorted and filtered by different criteria in the column headings, including the category of the drug from the Table of Pharmacogenetic Associations ("FDA PGx Association"). The table can be downloaded in TSV format as either the full or filtered version (Figure 2).

Figure 2. Screenshot of the FDA Drug Label Annotations table.











This table can be found on the PharmGKB homepage under the "Annotation" and "Clinical" section (Figure 3) and is in addition to our Drug Label Annotations table that includes labels from multiple regulatory agencies found at the top left corner of the homepage.

Figure 3. PharmGKB homepage.
















As a reminder, PharmGKB drug label annotations provide (1) a brief summary of the PGx in the label, (2) an excerpt from the label, including any guidance from the label for patients with a particular genotype/metabolizer phenotype if it exists, (3) specific variants discussed on the label, particularly if there is prescribing guidance for them, and (4) a downloadable highlighted label PDF file.  PharmGKB also "tags" labels to indicate certain information, including: 

    (5) the "PGx Level" tag ("Testing required", "Testing recommended", "Actionable PGx" and "Informative PGx") which is the PharmGKB interpretation of the level of action implied in each label

    (6) the "Dosing Info" tag which indicates dosing information based on genotype/metabolizer phenotype exists on the label

    (7) the "Alternate Drug" tag which indicates if a drug is either indicated or contraindicated based on genotype/metabolizer status on the label

    (8) the "Prescribing Info" tag which indicates if any guidance from the label for patients with a particular genotype/metabolizer phenotype exists on the label

    (9) the "Cancer Genome" tag which indicates if the label discusses a gene or variant present in a tumor/cancer cell

    (10) the "On FDA Biomarker List" tag if the label is on the FDA's Table of Pharmacogenomic Biomarkers in Drug Labels.

Figure 4. Screenshot of the FDA-approved drug label annotation for irinotecan to illustrate the types of information found in a label annotation.