Haidar, Cyrine E.

AbstractThe DPYD gene encodes dihydropyrimidine dehydrogenase, the rate‐limiting enzyme for the metabolism of fluoropyrimidines 5‐fluorouracil and capecitabine. Genetic variants in DPYD have been associated with altered enzyme activity, therefore accurate detection and interpretation is critical to predict metabolizer status for individualized fluoropyrimidine therapy. The most commonly observed deleterious variation is the causal variant linked to the previously described HapB3 haplotype, c.1129‐5923C>G (rs75017182) in intron 10, which introduces a cryptic splice site. A benign synonymous variant in exon 11, c.1236G>A (rs56038477) is also linked to HapB3 and is commonly used for testing. Previously, these single‐nucleotide polymorphisms (SNPs) have been reported to be in perfect linkage disequilibrium (LD); therefore, c.1236G>A is often utilized as a proxy for the function‐altering intronic variant. Clinical genotyping of DPYD identified a patient who had c.1236G>A, but not c.1129‐5923C>G, suggesting that these two SNPs may not be in perfect LD, as previously assumed. Additional individuals with c.1236G>A, but not c.1129‐5923C>G, were identified in the Children's Mercy Data Warehouse and the All of Us Research Program version 7 cohort substantiating incomplete SNP linkage. Consequently, testing only c.1236G>A can generate false‐positive results in some cases and lead to suboptimal dosing that may negatively impact patient therapy and prospect of survival. Our data show that DPYD genotyping should include the functional variant c.1129‐5923C>G, and not the c.1236G>A proxy, to accurately predict DPD activity.

Numerous pharmacogenetic clinical guidelines and recommendations have been published, but barriers have hindered the clinical implementation of pharmacogenetics. The Translational Pharmacogenetics Program (TPP) of the National Institutes of Health (NIH) Pharmacogenomics Research Network was established in 2011 to catalog and contribute to the development of pharmacogenetic implementations at eight US healthcare systems, with the goal to disseminate real‐world solutions for the barriers to clinical pharmacogenetic implementation. The TPP collected and normalized pharmacogenetic implementation metrics through June 2015, including gene–drug pairs implemented, interpretations of alleles and diplotypes, numbers of tests performed and actionable results, and workflow diagrams. TPP participant institutions developed diverse solutions to overcome many barriers, but the use of Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines provided some consistency among the institutions. The TPP also collected some pharmacogenetic implementation outcomes (scientific, educational, financial, and informatics), which may inform healthcare systems seeking to implement their own pharmacogenetic testing programs.