[{"volume":26,"publication":"Pharmacogenomics Journal","department":[{"_id":"MaRo"}],"file":[{"content_type":"application/pdf","date_created":"2026-03-30T07:04:08Z","success":1,"file_size":2618963,"file_id":"21506","checksum":"2fd3d7e48b779ac24245f6c35449b89a","creator":"dernst","file_name":"2026_PharmacogenomicsJour_Hajto.pdf","access_level":"open_access","date_updated":"2026-03-30T07:04:08Z","relation":"main_file"}],"_id":"21503","abstract":[{"text":"Currently, pharmacogenetics relies on partially annotated star alleles, leaving novel variants and complex haplotypes uninterpretable. Computational scoring frameworks could overcome these limitations. Here, we comprehensively evaluated the ability of existing (CADD, FATHMM-XF, PROVEAN, MutationAssessor, SIFT, PhyloP100, APF, APF2) and novel (PharmGScore and PharmMLScore) variant effect predictors to assess pharmacogenetic alleles in multiple scenarios. Altogether we analyzed 541 PharmVar alleles, high‑throughput CYP2C9 and CYP2C19 mutational maps, and 200 642 UK Biobank exomes linked with health records containing antidepressant treatment outcomes. Many evaluated tools, especially ensemble frameworks, matched or exceeded star allele classifications (ROC‑AUC up to 0.85 for allele definitions, 0.95 in vitro; TPR up to 0.99 for exomes) and accurately predicted severe antidepressant adverse events for carriers of deleterious variants in CYP2C19 (OR 1.20–1.35). Our findings show that computational predictors deliver star allele accuracy while overcoming their limitations. With additional validation, computational tools could enhance clinical decision frameworks by enabling continuous scoring, incorporating previously unknown variants, and providing genome-wide applicability.","lang":"eng"}],"intvolume":"        26","article_type":"original","month":"03","oa":1,"date_updated":"2026-03-30T07:10:50Z","external_id":{"pmid":["41803106"]},"publication_identifier":{"eissn":["1473-1150"],"issn":[" 1470-269X"]},"has_accepted_license":"1","doi":"10.1038/s41397-026-00399-0","tmp":{"image":"/images/cc_by_nc_nd.png","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","short":"CC BY-NC-ND (4.0)"},"OA_type":"hybrid","quality_controlled":"1","article_number":"8","citation":{"chicago":"Hajto, Jacek, Marcin Piechota, Ilse Krätschmer, Paula Konowalska, Gabriel E. Boyle, Douglas M. Fowler, Malgorzata Borczyk, and Michal Korostynski. “Computational Variant Predictors for Pharmacogenomics: From Evaluation of Single Alleles to Assessment of Adverse Drug Reactions to Antidepressants.” <i>Pharmacogenomics Journal</i>. Springer Nature, 2026. <a href=\"https://doi.org/10.1038/s41397-026-00399-0\">https://doi.org/10.1038/s41397-026-00399-0</a>.","apa":"Hajto, J., Piechota, M., Krätschmer, I., Konowalska, P., Boyle, G. E., Fowler, D. M., … Korostynski, M. (2026). Computational variant predictors for pharmacogenomics: From evaluation of single alleles to assessment of adverse drug reactions to antidepressants. <i>Pharmacogenomics Journal</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41397-026-00399-0\">https://doi.org/10.1038/s41397-026-00399-0</a>","ista":"Hajto J, Piechota M, Krätschmer I, Konowalska P, Boyle GE, Fowler DM, Borczyk M, Korostynski M. 2026. Computational variant predictors for pharmacogenomics: From evaluation of single alleles to assessment of adverse drug reactions to antidepressants. Pharmacogenomics Journal. 26(2), 8.","mla":"Hajto, Jacek, et al. “Computational Variant Predictors for Pharmacogenomics: From Evaluation of Single Alleles to Assessment of Adverse Drug Reactions to Antidepressants.” <i>Pharmacogenomics Journal</i>, vol. 26, no. 2, 8, Springer Nature, 2026, doi:<a href=\"https://doi.org/10.1038/s41397-026-00399-0\">10.1038/s41397-026-00399-0</a>.","ieee":"J. Hajto <i>et al.</i>, “Computational variant predictors for pharmacogenomics: From evaluation of single alleles to assessment of adverse drug reactions to antidepressants,” <i>Pharmacogenomics Journal</i>, vol. 26, no. 2. Springer Nature, 2026.","short":"J. Hajto, M. Piechota, I. Krätschmer, P. Konowalska, G.E. Boyle, D.M. Fowler, M. Borczyk, M. Korostynski, Pharmacogenomics Journal 26 (2026).","ama":"Hajto J, Piechota M, Krätschmer I, et al. Computational variant predictors for pharmacogenomics: From evaluation of single alleles to assessment of adverse drug reactions to antidepressants. <i>Pharmacogenomics Journal</i>. 2026;26(2). doi:<a href=\"https://doi.org/10.1038/s41397-026-00399-0\">10.1038/s41397-026-00399-0</a>"},"file_date_updated":"2026-03-30T07:04:08Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","language":[{"iso":"eng"}],"scopus_import":"1","day":"09","ddc":["570"],"type":"journal_article","license":"https://creativecommons.org/licenses/by-nc-nd/4.0/","issue":"2","date_published":"2026-03-09T00:00:00Z","acknowledgement":"This research has been conducted using the UK Biobank Resource under Application Number 62979. We are grateful to the UK Biobank and all its voluntary participants. This work used data provided by patients and collected by the NHS as part of their care and support.\r\n\r\nThis study was funded by the National Science Center, Poland: PRELUDIUM BIS-3 grant no. 2021/43/O/NZ7/01187 (development and benchmarking of variant scores) and SONATINA 5 grant 2021/40/C/NZ2/00218 (UKB analyses). Additional support came from the statutory funds of the Maj Institute of Pharmacology PAS. We gratefully acknowledge Poland’s high-performance Infrastructure PLGrid ACK Cyfronet AGH, for providing computer facilities and support within computational grant no PLG/2022/015861. DMF and GEB were funded by NIH grants NIH R35GM152106 and UM1HG011969.","date_created":"2026-03-29T22:07:08Z","status":"public","publication_status":"published","publisher":"Springer Nature","pmid":1,"title":"Computational variant predictors for pharmacogenomics: From evaluation of single alleles to assessment of adverse drug reactions to antidepressants","article_processing_charge":"Yes (in subscription journal)","oa_version":"Published Version","author":[{"last_name":"Hajto","first_name":"Jacek","full_name":"Hajto, Jacek"},{"first_name":"Marcin","full_name":"Piechota, Marcin","last_name":"Piechota"},{"orcid":"0000-0002-5636-9259","first_name":"Ilse","full_name":"Krätschmer, Ilse","id":"30d4014e-7753-11eb-b44b-db6d61112e73","last_name":"Krätschmer"},{"last_name":"Konowalska","full_name":"Konowalska, Paula","first_name":"Paula"},{"last_name":"Boyle","full_name":"Boyle, Gabriel E.","first_name":"Gabriel E."},{"full_name":"Fowler, Douglas M.","first_name":"Douglas M.","last_name":"Fowler"},{"first_name":"Malgorzata","full_name":"Borczyk, Malgorzata","last_name":"Borczyk"},{"first_name":"Michal","full_name":"Korostynski, Michal","last_name":"Korostynski"}],"year":"2026","OA_place":"publisher"}]