{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T11:38:48Z","timestamp":1773920328403,"version":"3.50.1"},"reference-count":38,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T00:00:00Z","timestamp":1773878400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Bioinform."],"abstract":"<jats:p>Pharmacogenomics (PGx) incorporates population level allele frequencies into its analyses. Often these population groupings are based on current or ancestral geographic location. However, these groupings can obscure internal variance caused by population heterogeneity. In order to increase the data accuracy and specificity for researchers, it is necessary to refine the population groupings. Often the necessary datasets have already been collected but have not been fully analyzed past their initial purpose. Here we provide a secondary pipeline that demonstrates a divergence between two datasets: the Clinical Pharmacogenetics Implementation Consortium (CPIC) collection of geographic populations and a Whole Genome Sequencing PGx dataset consisting of 632 Japanese individuals. Three classes of drugs and the relevant genes as identified by CPIC are examined: SSRIs (CYP2D6, CYP2B6, CYP2C19), opioid analgesics (CYP2D6) and statins (SLCO1B1). A meaningful divergence is shown between CPIC\u2019s East Asian population and the Japanese population for opioid analgesics and statins. For opioid analgesics the Japanese population saw an increase in the \u201cUse as directed\u201d designation compared to the East Asian population from 53.2% to 71.0%; the statins data showed a decrease from 75.7% in the East Asian population 67.6% in the Japanese population. This divergence demonstrates that existing WGS data can reveal PGx patterns masked by broad geographic groups through the application of an appropriate secondary pipeline, enabling 0population specific implementation and refined population-level PGx inference without the need for further sample collection.<\/jats:p>","DOI":"10.3389\/fbinf.2026.1770550","type":"journal-article","created":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T06:51:31Z","timestamp":1773903091000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Japanese genomes for pharmacogenomics: primary and secondary pipelines for population-specific insights"],"prefix":"10.3389","volume":"6","author":[{"given":"Charles W.","family":"Crawford","sequence":"first","affiliation":[{"name":"Genesis Institute of Genetic Research, A.D.A.M. Innovations Corporation","place":["Shibuya-ku, Japan"]}]},{"given":"Yuka","family":"Nakano","sequence":"additional","affiliation":[{"name":"Genesis Institute of Genetic Research, A.D.A.M. Innovations Corporation","place":["Shibuya-ku, Japan"]}]},{"given":"Marika","family":"Hayashi","sequence":"additional","affiliation":[{"name":"Genesis Institute of Genetic Research, A.D.A.M. Innovations Corporation","place":["Shibuya-ku, Japan"]}]},{"given":"Antony","family":"Ibrahim","sequence":"additional","affiliation":[{"name":"Genesis Institute of Genetic Research, A.D.A.M. Innovations Corporation","place":["Shibuya-ku, Japan"]}]},{"given":"Issei","family":"Kono","sequence":"additional","affiliation":[{"name":"Genesis Institute of Genetic Research, A.D.A.M. Innovations Corporation","place":["Shibuya-ku, Japan"]}]},{"given":"Iri","family":"Sato-Baran","sequence":"additional","affiliation":[{"name":"Genesis Institute of Genetic Research, A.D.A.M. 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