{"entity": "researcher", "timestamp": "2026-11-06T18:28:51.856Z", "family": "Zhou", "given": "Yitian", "initials": "Y", "orcid": "0000-0003-3066-5444", "affiliations": ["Department of Physiology and Pharmacology, Karolinska Institutet, 17177, Stockholm, Sweden."], "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d"}}, "publications": [{"entity": "publication", "iuid": "8b6a3e2b3b5c41e28df60177f0529796", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/8b6a3e2b3b5c41e28df60177f0529796.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/8b6a3e2b3b5c41e28df60177f0529796"}}, "title": "CYP2C19 Genotype is Associated with Citalopram Treatment Outcomes in a Real-World Setting.", "authors": [{"family": "Park", "given": "Yoomi", "initials": "Y", "orcid": "0000-0003-3070-938X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a7d4b85b74a44cdd803c4d336947cf7c.json"}}, {"family": "Zhou", "given": "Yitian", "initials": "Y", "orcid": "0000-0003-3066-5444", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d.json"}}, {"family": "Lauschke", "given": "Volker M", "initials": "VM", "orcid": "0000-0002-1140-6204", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/82048d4da61547d08aa9d2bb3bae12dd.json"}}], "type": "journal article", "published": "2026-08-00", "journal": {"title": "Clin. Pharmacol. Ther.", "issn": "1532-6535", "volume": "120", "issue": "2", "pages": "412-419", "issn-l": "0009-9236"}, "abstract": "CYP2C19 metabolizes various selective serotonin reuptake inhibitors (SSRIs) and genetic CYP2C19 variants are associated with SSRI tolerability and response. Yet, whether CYP2C19 variability also impacts citalopram response remained unclear. We here evaluated associations between CYP2C19 genotypes and citalopram prescription data of 11,079 patients from the UK Biobank. Importantly, CYP2C19 ultrarapid metabolizers (UMs) were more likely to experience therapeutic failure (OR 2.03, P = 0.002) and both CYP2C19 poor metabolizers (PMs) and UMs exhibited an increased likelihood of treatment resistance (PMs, OR 1.85, P = 0.06; UMs, OR 1.74, P = 0.05). Furthermore, inferred CYP2C19 metabolizer status showed significant monotonic trends with citalopram maintenance dose (from 19.7 mg/d in PMs to 24.4 mg/d in UMs; Jonckheere-Terpstra P = 0.017) and time to dose escalation (2.5 years in PMs to 1.7 years in UMs; P = 0.006). Besides CYP2C19, rare variant analyses identified BMP2K as a novel candidate locus for SSRI response. BMP2K variants were significantly associated with therapeutic failure in citalopram patients (P = 5.49 \u00d7 10-6) and this association was replicated in 220 escitalopram users (P = 0.042). Furthermore, higher BMP2K variant burden significantly correlated with lower maintenance dose. These findings provide the first report of a U-shaped association between CYP2C19 metabolizer status and citalopram therapeutic outcomes and pinpoint BMP2K as a novel candidate gene with potential contribution to interindividual differences in citalopram response. Collectively, these results demonstrate that CYP2C19 genotype is significantly associated with citalopram outcomes in a real-world setting in which patient treatment was not guided by pharmacogenetics, thus avoiding open-label awareness, eliminating expectation bias of genetic testing and highlighting the value of large-scale biobank data for advancing precision psychiatry.", "doi": "10.1002/cpt.70285", "pmid": "41979220", "labels": {"DDLS Fellow": null, "Yitian Zhou": null}, "xrefs": [{"db": "pmc", "key": "PMC13339076"}], "notes": [], "created": "2026-11-06T09:38:19.288Z", "modified": "2026-11-06T09:38:19.330Z"}, {"entity": "publication", "iuid": "ff620e29e0de4d02ac17b35a7cb3e51f", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/ff620e29e0de4d02ac17b35a7cb3e51f.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/ff620e29e0de4d02ac17b35a7cb3e51f"}}, "title": "Prediction of drug hypersensitivity by comprehensive modeling of HLA-peptidomes.", "authors": [{"family": "Zhong", "given": "Yi", "initials": "Y", "orcid": "0000-0002-0929-8224", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/f5fdb847e9c944d5bba66333c80d40e6.json"}}, {"family": "Lauschke", "given": "Volker M", "initials": "VM", "orcid": "0000-0002-1140-6204", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/82048d4da61547d08aa9d2bb3bae12dd.json"}}, {"family": "Wang", "given": "Yi", "initials": "Y", "orcid": "0000-0002-3676-9183", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a03091d5222a409ba70c5fe26ac5455f.json"}}, {"family": "Zhou", "given": "Yitian", "initials": "Y", "orcid": "0000-0003-3066-5444", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d.json"}}], "type": "journal article", "published": "2026-07-03", "journal": {"title": "Brief. Bioinformatics", "issn": "1477-4054", "volume": "27", "issue": "4", "issn-l": "1467-5463"}, "abstract": "Human leukocyte antigen (HLA)-B*57:01 associated with abacavir-induced hypersensitivity syndrome (ABC-HSS) is one of the most extensively studied immune-mediated drug hypersensitivity reactions (DHRs). The high odds ratio and strong predictive values of HLA-B*57:01 for ABC-HSS have prompted the Food and Drug Administration and European Medicines Agency to require genetic testing before abacavir treatment. Abacavir binds to HLA-B*57:01 and alters the repertoire of presented peptides, resulting in the activation of autoimmunity. Previous studies employing computational approaches to investigate such DHRs have relied solely on a few crystallized tripartite structures, thus overlooking the full presented peptidome, leading to unsatisfactory predictive results. Here, we employed a state-of-the-art modeling approach to generate HLA structures complexed with over 13 000 presented peptides. We then established a novel computational modeling pipeline to simulate the binding of abacavir to these HLA-peptide complexes. Benchmarking against experimentally determined structures showed that this approach successfully recapitulated the crystalized tripartite structures with high accuracy (RMSD<2.2 \u00c5). We then profiled alterations of the peptide repertoire at key positions in the presence of abacavir and proposed a method that accurately predicts compounds known to trigger T-cell activation. Overall, these results show that comprehensive modeling of the HLA-bound peptidome using advanced structural approaches can enhance the prediction and mechanistic understanding of immune-mediated DHRs.", "doi": "10.1093/bib/bbag350", "pmid": "42398070", "labels": {"DDLS Fellow": null, "Yitian Zhou": null}, "xrefs": [{"db": "pmc", "key": "PMC13331351"}, {"db": "pii", "key": "8724529"}], "notes": [], "created": "2026-11-06T09:38:50.984Z", "modified": "2026-11-06T09:38:51.075Z"}, {"entity": "publication", "iuid": "095a98be04f1467087159c2ba09b883b", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/095a98be04f1467087159c2ba09b883b.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/095a98be04f1467087159c2ba09b883b"}}, "title": "Feed-Forward Deep Neural Networks Predict Substrate-Specific Effects of Transporter Variants to Explain Drug Response Variability.", "authors": [{"family": "Park", "given": "Yoomi", "initials": "Y", "orcid": "0000-0003-3070-938X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a7d4b85b74a44cdd803c4d336947cf7c.json"}}, {"family": "Zhou", "given": "Yitian", "initials": "Y", "orcid": "0000-0003-3066-5444", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d.json"}}, {"family": "Xiao", "given": "Ming", "initials": "M", "orcid": "0000-0002-5407-0835", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0e3f113ea31d464b9f32799aa7bab8e6.json"}}, {"family": "Nies", "given": "Anne T", "initials": "AT", "orcid": "0000-0001-6862-0730", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/45f66a44d87e4b57bde4b609bbdb86a0.json"}}, {"family": "Lauschke", "given": "Volker M", "initials": "VM", "orcid": "0000-0002-1140-6204", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/82048d4da61547d08aa9d2bb3bae12dd.json"}}], "type": "journal article", "published": "2026-05-00", "journal": {"title": "Clin Transl Sci", "issn": "1752-8062", "volume": "19", "issue": "5", "pages": "e70592", "issn-l": null}, "abstract": "Genetic variants in drug transporter genes shape the interindividual variability in drug response. However, their functional interpretation has remained limited due to the substrate dependence of variant effects. Existing predictors are substrate-agnostic and cannot capture how a single amino acid change differentially affects transport across drugs. Here, we present the substrate-specific effect predictor (SSEP), the first model to predict transporter variant effects in a substrate-dependent manner. SSEP integrates curated in vitro uptake assays with deep mutational scanning data, leveraging multiscale features extracted from modeled variant-substrate complexes. Based on a feed-forward deep neural network architecture, SSEP provides quantitative, substrate-specific activity scores that correlate with experimental uptake data (Spearman's \u03c1 = 0.64) across multiple transporter families (OCT1, MATE, CNT, and OATP) and substrate classes (biguanides, tetraethylammonium, selective serotonin agonists, sympathomimetics and opiates). In benchmarking analyses, SSEP showed higher concordance (Kruskal-Wallis p = 1.11 \u00d7 10-41) with experimental uptake than commonly used substrate-agnostic predictors. Application of SSEP on UK Biobank data revealed that OCT1 (SLC22A1) variant burden weighted by metformin-specific SSEP scores was significantly associated with maintenance dose (\u03b2 = 30 mg/day per unit increase in predicted functional burden; p = 0.033), whereas substrate-agnostic weights showed no association (p = 0.78). Together, these results show that SSEP enables quantitative, drug-specific prediction of transporter variant effects, thereby improving the identification of clinically relevant transporter variants in population-scale data.", "doi": "10.1111/cts.70592", "pmid": "42104208", "labels": {"DDLS Fellow": null, "Yitian Zhou": null}, "xrefs": [{"db": "pmc", "key": "PMC13156069"}], "notes": [], "created": "2026-11-06T09:38:33.937Z", "modified": "2026-11-06T09:38:34.131Z"}, {"entity": "publication", "iuid": "adc7ca17f8dd46b692854c6e6d9841bb", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/adc7ca17f8dd46b692854c6e6d9841bb.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/adc7ca17f8dd46b692854c6e6d9841bb"}}, "title": "Substrate-specificity of pharmacogenomic variability - clinical relevance and emerging predictive strategies.", "authors": [{"family": "Zhou", "given": "Yitian", "initials": "Y", "orcid": "0000-0003-3066-5444", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d.json"}}, {"family": "Park", "given": "Yoomi", "initials": "Y", "orcid": "0000-0003-3070-938X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a7d4b85b74a44cdd803c4d336947cf7c.json"}}, {"family": "Lauschke", "given": "Volker M", "initials": "VM", "orcid": "0000-0002-1140-6204", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/82048d4da61547d08aa9d2bb3bae12dd.json"}}], "type": "journal article", "published": "2026-03-00", "journal": {"title": "Expert Opin Drug Metab Toxicol", "issn": "1744-7607", "volume": "22", "issue": "3", "pages": "201-215", "issn-l": null}, "abstract": "Genetic variation in drug-metabolizing enzymes and transporters contributes to interindividual differences in drug efficacy and toxicity. While current pharmacogenomic practice typically assigns fixed functional categories to variant alleles, accumulating evidence shows that many variant alleles exert substrate-specific effects.\n\nWe here summarize the current evidence for substrate-dependent functional variability across key pharmacogenes, including CYP2D6, CYP2C8, CYP2C9 and multiple uptake and efflux transporters, based on both experimental in vitro approaches and clinical pharmacokinetic analyses. We further evaluate the performance of existing computational variant-effect predictors and outline emerging structural, sequence-based, and representation-learning strategies for the prediction of substrate-specificity. Particular focus is placed on methodological gaps that currently prevent the prediction of substrate-specific effects and on the evolving technological landscape that may enable such capabilities.\n\nSubstrate specificity of pharmacogenetic variations is clinically relevant and insufficiently captured by current functional annotations and prediction tools. We believe that new strategies based on integrative multimodal frameworks that combine structural descriptors, protein language-model embeddings, ligand features and high-quality experimental data have the potential to capture substrate-specific variant effects in the near future. These advances will provide exciting new opportunities to systematically evaluate variant function, which will benefit both drug development and precision medicine.", "doi": "10.1080/17425255.2026.2654466", "pmid": "41914879", "labels": {"DDLS Fellow": null, "Yitian Zhou": null}, "xrefs": [], "notes": [], "created": "2026-11-06T09:37:49.255Z", "modified": "2026-11-06T09:37:49.375Z"}, {"entity": "publication", "iuid": "ac580aabc9cd4ad0a35c5d1bde9d60ca", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/ac580aabc9cd4ad0a35c5d1bde9d60ca.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/ac580aabc9cd4ad0a35c5d1bde9d60ca"}}, "title": "Integration of germline pharmacogenomic burden to predict fluoropyrimidine-related toxicity - A secondary analysis of the PREPARE trial.", "authors": [{"family": "De Mattia", "given": "Elena", "initials": "E", "orcid": "0000-0003-4948-8767", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/e8a9a17bfbf04ae4bc963b8e9dd96991.json"}}, {"family": "Park", "given": "Yoomi", "initials": "Y"}, {"family": "Peruzzi", "given": "Elena", "initials": "E"}, {"family": "Zhou", "given": "Yitian", "initials": "Y", "orcid": "0000-0003-3066-5444", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d.json"}}, {"family": "Roncato", "given": "Rossana", "initials": "R"}, {"family": "Polesel", "given": "Jerry", "initials": "J", "orcid": "0000-0001-9381-1520", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d222504eecb241b3824cad86688aff8b.json"}}, {"family": "Scarabel", "given": "Lucia", "initials": "L"}, {"family": "Schwab", "given": "Matthias", "initials": "M", "orcid": "0000-0002-9984-075X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a671991e1b85463e8a7bbad2e29fb1bd.json"}}, {"family": "Guchelaar", "given": "Henk-Jan", "initials": "HJ"}, {"family": "Swen", "given": "Jesse Joachim", "initials": "JJ"}, {"family": "Spina", "given": "Michele", "initials": "M"}, {"family": "Puglisi", "given": "Fabio", "initials": "F", "orcid": "0000-0003-0573-4938", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/17e87f4beb62427fb1155ca71a3c1388.json"}}, {"family": "Toffoli", "given": "Giuseppe", "initials": "G"}, {"family": "Lauschke", "given": "Volker M", "initials": "VM", "orcid": "0000-0002-1140-6204", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/82048d4da61547d08aa9d2bb3bae12dd.json"}}, {"family": "Cecchin", "given": "Erika", "initials": "E", "orcid": "0000-0001-7517-7490", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/3018f538ff124402b050b2e8e6b8f5e0.json"}}], "type": "journal article", "published": "2025-11-00", "journal": {"title": "Oncogene", "issn": "1476-5594", "volume": "44", "issue": "45", "pages": "4352-4362", "issn-l": "0950-9232"}, "abstract": "Testing for four dihydropyrimidine dehydrogenase (DPYD) variants (DPYD*2 A, DPYD*13, c.2846 A > T, DPYD-HapB3) is currently implemented in clinical practice to prevent fluoropyrimidines (FLs) related toxicity but with limited sensitivity. This study aimed to identify novel genetic factors in FL-related genes to enhance risk prediction using data from the PREPARE trial (NCT03093818). Two hundred seventy-four patients receiving FL-based chemotherapy with severe toxicity were sequenced for 60 candidate genes. Gene and pathway-level association analyses focusing mainly on rare variants were performed using dedicated statistical tests, including gene-wise variant burden (GVB) analysis. DPYD germline variant burden beyond the four routinely tested markers emerged to contribute to toxicity, indicating that rarer genetic variants could help in refining the optimal FL dosage (p < 0.1). Functional rare variant burden in ABCB5, PARP1, ENOSF1, CYP3A4 and nuclear receptors pathway impacted on toxicity risk (p < 0.05 in at least one statistical test). GVB analysis confirmed ABCB5 as a significant risk gene and highlighted ABCC4, HNF4A, and XRCC3 as additional candidates. A predictive model combining genetic burden scores with clinical variables improved the identification of high-risk patients (sensitivity=0.71, specificity=0.74, accuracy=0.73). This study indicated a paradigm shift from population to individual-level arguing for an extension of testing beyond the four DPYD currently considered variants to predict FL-related toxicity.", "doi": "10.1038/s41388-025-03587-7", "pmid": "40999005", "labels": {"DDLS Fellow": null, "Yitian Zhou": null}, "xrefs": [{"db": "pii", "key": "10.1038/s41388-025-03587-7"}], "notes": [], "created": "2026-11-06T09:37:33.874Z", "modified": "2026-11-06T09:37:34.147Z"}, {"entity": "publication", "iuid": "0fe64330690f45409059e8835d02e368", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/0fe64330690f45409059e8835d02e368.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/0fe64330690f45409059e8835d02e368"}}, "title": "Improved Prediction of CYP2D6 Catalyzed Drug Metabolism by Taking Variant Substrate Specificities and Novel Polymorphic Haplotypes into Account.", "authors": [{"family": "Johansson", "given": "Inger", "initials": "I", "orcid": "0000-0001-6646-4551", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2d3cf9c647a04b8f8b47a73bf0084729.json"}}, {"family": "Xanthopoulou", "given": "Emmanouella M", "initials": "EM", "orcid": "0009-0002-6208-1136", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8fee0f48839642079d7777505af681e0.json"}}, {"family": "Zhou", "given": "Yitian", "initials": "Y", "orcid": "0000-0003-3066-5444", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d.json"}}, {"family": "Sanchez-Spitman", "given": "Anabel", "initials": "A", "orcid": "0000-0003-2073-5648", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8b5a1ab273194f1c9b29248c464763e4.json"}}, {"family": "van der Lee", "given": "Maaike", "initials": "M", "orcid": "0000-0003-3344-6896", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/fa3fcdf5bd124ee78464b97acfd868db.json"}}, {"family": "Wollmann", "given": "Birgit M", "initials": "BM", "orcid": "0000-0001-7261-275X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/27a447ec9bb4471a8da776a3035b9775.json"}}, {"family": "St\u00f8rset", "given": "Elisabet", "initials": "E", "orcid": "0000-0002-2662-8504", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/f346f014e12e48d8be53967689fd9bca.json"}}, {"family": "Swen", "given": "Jesse J", "initials": "JJ", "orcid": "0000-0002-3965-5552", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a424f88f5c654f288a0c2d1d24696f28.json"}}, {"family": "Guchelaar", "given": "Henk-Jan", "initials": "HJ", "orcid": "0000-0002-7085-1383", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/64e116247dd5441486ad6da3a6ca688e.json"}}, {"family": "Molden", "given": "Espen", "initials": "E", "orcid": "0000-0001-6190-2751", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/e80709de306e45d79cf4619be67b2c49.json"}}, {"family": "Jukic", "given": "Marin M", "initials": "MM", "orcid": "0000-0002-5296-4245", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a97e34d5c125464aaf98b866a3f9f985.json"}}, {"family": "Ingelman-Sundberg", "given": "Magnus", "initials": "M", "orcid": "0000-0002-7255-9079", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cd15df22405f4055a6d81fcf89604f85.json"}}], "type": "journal article", "published": "2025-07-00", "journal": {"title": "Clin. Pharmacol. Ther.", "issn": "1532-6535", "volume": "118", "issue": "1", "pages": "218-231", "issn-l": "0009-9236"}, "abstract": "The polymorphic CYP2D6 enzyme plays a pivotal role in the metabolism of approximately 25% of clinically prescribed drugs. However, the impact of specific genetic variants on the interindividual variability in CYP2D6-mediated drug metabolism remains insufficiently quantified. This translational study sought to address this gap by analyzing the genotypes and phenotypes of patients in two large clinical cohorts, focusing on the metabolism of the CYP2D6 substrates risperidone and desmethyltamoxifen. The analysis incorporated novel polymorphic haplotypes and substrate-specific differences among the CYP2D6.1, CYP2D6.2, and CYP2D6.35 enzyme variants. The study revealed that CYP2D6.2 and CYP2D6.35 exhibit reduced metabolic capacity for these substrates, both in vivo and in an in vitro expression model. This was evidenced by decreased catalytic turnover (Kcat), decreased substrate affinity, and altered substrate docking. Furthermore, novel polymorphic haplotypes on the CYP2D6*1, CYP2D6*2, and CYP2D6*35 backgrounds were identified, each associated with a 30-40% increase in CYP2D6 activity. Incorporating these findings into prediction equations significantly improved the genetic prediction accuracy (R2) for CYP2D6-mediated metabolism of desmethyltamoxifen from 59% to 71% and risperidone, also metabolized by CYP3A4, from 42% to 46%. These results highlight the importance of accounting for drug-specific interactions with enzyme variants and integrating distinct polymorphic haplotypes into CYP pharmacogenomic models and guidelines for better translation into clinical practice.", "doi": "10.1002/cpt.3680", "pmid": "40261922", "labels": {"DDLS Fellow": null, "Yitian Zhou": null}, "xrefs": [{"db": "pmc", "key": "PMC12166262"}, {"db": "PDB", "key": "3TBG"}], "notes": [], "created": "2026-11-06T09:36:39.632Z", "modified": "2026-11-06T09:36:40.291Z"}, {"entity": "publication", "iuid": "38c9c8560f404b6da6e8cce401b8312d", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/38c9c8560f404b6da6e8cce401b8312d.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/38c9c8560f404b6da6e8cce401b8312d"}}, "title": "Evaluating the synergistic use of advanced liver models and AI for the prediction of drug-induced liver injury.", "authors": [{"family": "Zhou", "given": "Yitian", "initials": "Y", "orcid": "0000-0003-3066-5444", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d.json"}}, {"family": "Zhong", "given": "Yi", "initials": "Y"}, {"family": "Lauschke", "given": "Volker M", "initials": "VM", "orcid": "0000-0002-1140-6204", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/82048d4da61547d08aa9d2bb3bae12dd.json"}}], "type": "journal article", "published": "2025-05-00", "journal": {"title": "Expert Opin Drug Metab Toxicol", "issn": "1744-7607", "volume": "21", "issue": "5", "pages": "563-577", "issn-l": null}, "abstract": "Drug-induced liver injury (DILI) is a leading cause of acute liver failure. Hepatotoxicity typically occurs only in a subset of individuals after prolonged exposure and constitutes a major risk factor for the termination of drug development projects.\n\nWe provide an overview of available human liver models for DILI research and discuss how they have been used to aid in early risk assessments and to mitigate the risk of project closures due to DILI in clinical stages. We summarize the different data that can be provided by such models and illustrate how these diverse data types can be interfaced with machine learning strategies to improve predictions of liver safety liabilities.\n\nAdvanced human liver models closely mimic human liver phenotypes and functions for many weeks, allowing for the recapitulation of hepatotoxicity events in vitro. Integration of the biochemical, histological, and toxicogenomic output data from these models with physicochemical compound properties using different machine learning architectures holds promise to enhance preclinical DILI predictions. However, to realize this aim, it is important to benchmark the available liver models on test sets of DILI positive and negative compounds and to carefully annotate and share the resulting data.", "doi": "10.1080/17425255.2025.2461484", "pmid": "39893552", "labels": {"DDLS Fellow": null, "Yitian Zhou": null}, "xrefs": [], "notes": [], "created": "2026-11-06T09:36:07.841Z", "modified": "2026-11-06T09:36:07.898Z"}, {"entity": "publication", "iuid": "7c5bb11d578346848bf6848280124929", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/7c5bb11d578346848bf6848280124929.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/7c5bb11d578346848bf6848280124929"}}, "title": "Molecular docking to investigate HLA-associated idiosyncratic drug reactions.", "authors": [{"family": "Li", "given": "Kejun", "initials": "K"}, {"family": "Lauschke", "given": "Volker M", "initials": "VM", "orcid": "0000-0002-1140-6204", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/82048d4da61547d08aa9d2bb3bae12dd.json"}}, {"family": "Zhou", "given": "Yitian", "initials": "Y", "orcid": "0000-0003-3066-5444", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d.json"}}], "type": "journal article", "published": "2025-02-00", "journal": {"title": "Drug Metab Rev", "issn": "1097-9883", "volume": "57", "issue": "1", "pages": "67-90", "issn-l": null}, "abstract": "Idiosyncratic drug reactions (IDRs) pose severe threats to patient health. Unlike conventionally dose-dependent side effects, they are unpredictable and more frequently manifest as life-threatening conditions, such as severe cutaneous adverse reactions (SCARs) and drug-induced liver injury (DILI). Some HLA alleles, such as HLA-B*57:01, HLA-B*15:02, and HLA-B*58:01, are known risk factors for adverse reactions induced by multiple drugs. However, the structural basis underlying most HLA-associated adverse events remains poorly understood. This review summarizes the application of molecular docking to reveal the mechanisms of IDR-related HLA associations, covering studies using this technique to examine drug-HLA binding pockets and identify key binding residues. We provide a comprehensive overview of risk HLA alleles associated with IDRs, followed by a discussion of the utility and limitations of commonly used molecular docking tools in simulating complex molecular interactions within the HLA binding pocket. Through examples, including the binding of abacavir and flucloxacillin to HLA-B*57:01, carbamazepine to HLA-B*15:02, and allopurinol to HLA-B*58:01, we demonstrate how docking analyses can provide insights into the drug and HLA allele-specificity of adverse events. Furthermore, the use of molecular docking to screen drugs with unknown IDR liability is examined, targeting either multiple HLA variants or a single specific variant. Despite multiple challenges, molecular docking presents a promising toolkit for investigating drug-HLA interactions and understanding IDR mechanisms, with significant implications for preemptive HLA typing and safer drug development.", "doi": "10.1080/03602532.2025.2453521", "pmid": "39811883", "labels": {"DDLS Fellow": null, "Yitian Zhou": null}, "xrefs": [], "notes": [], "created": "2026-11-06T09:35:05.016Z", "modified": "2026-11-06T09:35:05.043Z"}, {"entity": "publication", "iuid": "b8e28bb7e0924bc890d6b2c2d625a78c", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/b8e28bb7e0924bc890d6b2c2d625a78c.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/b8e28bb7e0924bc890d6b2c2d625a78c"}}, "title": "PharmFreq: a comprehensive atlas of ethnogeographic allelic variation in clinically important pharmacogenes.", "authors": [{"family": "Tremmel", "given": "Roman", "initials": "R", "orcid": "0000-0003-1564-0433", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5dcfb9d17c9340d69ea2c5fcbd06aeec.json"}}, {"family": "Zhou", "given": "Yitian", "initials": "Y", "orcid": "0000-0003-3066-5444", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d.json"}}, {"family": "Camara", "given": "Mahamadou D", "initials": "MD"}, {"family": "Laarif", "given": "Sofiene", "initials": "S"}, {"family": "Eliasson", "given": "Erik", "initials": "E"}, {"family": "Lauschke", "given": "Volker M", "initials": "VM", "orcid": "0000-0002-1140-6204", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/82048d4da61547d08aa9d2bb3bae12dd.json"}}], "type": "journal article", "published": "2025-01-06", "journal": {"title": "Nucleic Acids Res.", "issn": "1362-4962", "volume": "53", "issue": "D1", "pages": "D1498-D1509", "issn-l": "0305-1048"}, "abstract": "Genetic polymorphisms in drug metabolizing enzymes, drug transporters as well as in genes encoding the human major histocompatibility complex contribute to inter-individual differences in drug efficacy and safety. The extent, pattern and complexity of such pharmacogenetic variation differ drastically across human populations. Here, we present PharmFreq, a global repository of pharmacogenetic frequency information that aggregates frequency data of 658 allelic variants from over 10 million individuals collected from >1200 studies across 144 countries. Most investigations were conducted in East Asian and European populations, accounting for 29.4 and 26.6% of all studies, respectively. We find that the number of studies per country and aggregated cohort size correlated significantly with population size (R = 0.55, P= 3*10-9) and country gross domestic product (R = 0.43, P= 2*10-6) with overall population coverage varying between 5% in Estonia to < 0.001% in many countries in Sub-Saharan Africa and Asia. All frequency data are openly accessible via a web-based interactive dashboard at pharmfreq.com that facilitates the exploration, visualization and analysis of country- and population-specific data and their inferred phenotypic consequences. PharmFreq thus presents a comprehensive, freely available resource for pharmacogenetic variant frequencies that can inform about ethnogeographic pharmacogenomic diversity and reveal important inequities that help to focus future research efforts into underrepresented populations.", "doi": "10.1093/nar/gkae1016", "pmid": "39540424", "labels": {"DDLS Fellow": null, "Yitian Zhou": null}, "xrefs": [{"db": "pmc", "key": "PMC11701539"}, {"db": "pii", "key": "7900193"}], "notes": [], "created": "2026-11-06T09:35:20.571Z", "modified": "2026-11-06T09:35:20.615Z"}, {"entity": "publication", "iuid": "9269f05ff3fb42129ab5f563d6b3c90a", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/9269f05ff3fb42129ab5f563d6b3c90a.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/9269f05ff3fb42129ab5f563d6b3c90a"}}, "title": "APF2: an improved ensemble method for pharmacogenomic variant effect prediction.", "authors": [{"family": "Zhou", "given": "Yitian", "initials": "Y", "orcid": "0000-0003-3066-5444", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d.json"}}, {"family": "Pirmann", "given": "Sebastian", "initials": "S"}, {"family": "Lauschke", "given": "Volker M", "initials": "VM", "orcid": "0000-0002-1140-6204", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/82048d4da61547d08aa9d2bb3bae12dd.json"}}], "type": "journal article", "published": "2024-05-27", "journal": {"title": "Pharmacogenomics J.", "issn": "1473-1150", "volume": "24", "issue": "3", "pages": "17", "issn-l": "1470-269X"}, "abstract": "Lack of efficacy or adverse drug response are common phenomena in pharmacological therapy causing considerable morbidity and mortality. It is estimated that 20-30% of this variability in drug response stems from variations in genes encoding drug targets or factors involved in drug disposition. Leveraging such pharmacogenomic information for the preemptive identification of patients who would benefit from dose adjustments or alternative medications thus constitutes an important frontier of precision medicine. Computational methods can be used to predict the functional effects of variant of unknown significance. However, their performance on pharmacogenomic variant data has been lackluster. To overcome this limitation, we previously developed an ensemble classifier, termed APF, specifically designed for pharmacogenomic variant prediction. Here, we aimed to further improve predictions by leveraging recent key advances in the prediction of protein folding based on deep neural networks. Benchmarking of 28 variant effect predictors on 530 pharmacogenetic missense variants revealed that structural predictions using AlphaMissense were most specific, whereas APF exhibited the most balanced performance. We then developed a new tool, APF2, by optimizing algorithm parametrization of the top performing algorithms for pharmacogenomic variations and aggregating their predictions into a unified ensemble score. Importantly, APF2 provides quantitative variant effect estimates that correlate well with experimental results (R2 = 0.91, p = 0.003) and predicts the functional impact of pharmacogenomic variants with higher accuracy than previous methods, particularly for clinically relevant variations with actionable pharmacogenomic guidelines. We furthermore demonstrate better performance (92% accuracy) on an independent test set of 146 variants across 61 pharmacogenes not used for model training or validation. Application of APF2 to population-scale sequencing data from over 800,000 individuals revealed drastic ethnogeographic differences with important implications for pharmacotherapy. We thus think that APF2 holds the potential to improve the translation of genetic information into pharmacogenetic recommendations, thereby facilitating the use of Next-Generation Sequencing data for stratified medicine.", "doi": "10.1038/s41397-024-00338-x", "pmid": "38802404", "labels": {"DDLS Fellow": null, "Yitian Zhou": null}, "xrefs": [{"db": "pmc", "key": "PMC11129946"}, {"db": "pii", "key": "10.1038/s41397-024-00338-x"}], "notes": [], "created": "2026-11-06T09:34:32.270Z", "modified": "2026-11-06T09:34:32.308Z"}, {"entity": "publication", "iuid": "3443089d81bd49a8a7eec732f4872957", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/3443089d81bd49a8a7eec732f4872957.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/3443089d81bd49a8a7eec732f4872957"}}, "title": "Population-specific variations in KCNH2 predispose patients to delayed ventricular repolarization upon dihydroartemisinin-piperaquine therapy.", "authors": [{"family": "Camara", "given": "Mahamadou D", "initials": "MD"}, {"family": "Zhou", "given": "Yitian", "initials": "Y", "orcid": "0000-0003-3066-5444", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d.json"}}, {"family": "Dara", "given": "Antoine", "initials": "A"}, {"family": "T\u00e9k\u00e9t\u00e9", "given": "Mamadou M", "initials": "MM"}, {"family": "N\u00f3brega de Sousa", "given": "Ta\u00eds", "initials": "T"}, {"family": "Sissoko", "given": "S\u00e9kou", "initials": "S"}, {"family": "Demb\u00e9l\u00e9", "given": "Laurent", "initials": "L", "orcid": "0000-0001-9087-8439", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0967a7d993b84fa785bb0d5d2a999512.json"}}, {"family": "Ouologuem", "given": "Nouhoun", "initials": "N"}, {"family": "Hamidou Togo", "given": "Amadou", "initials": "A"}, {"family": "Alhousseini", "given": "Mohamed L", "initials": "ML"}, {"family": "Fofana", "given": "Bakary", "initials": "B"}, {"family": "Sagara", "given": "Issaka", "initials": "I"}, {"family": "Djimde", "given": "Abdoulaye A", "initials": "AA"}, {"family": "Gil", "given": "Pedro J", "initials": "PJ"}, {"family": "Lauschke", "given": "Volker M", "initials": "VM", "orcid": "0000-0002-1140-6204", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/82048d4da61547d08aa9d2bb3bae12dd.json"}}], "type": "journal article", "published": "2024-05-02", "journal": {"title": "Antimicrob. Agents Chemother.", "issn": "1098-6596", "volume": "68", "issue": "5", "pages": "e0139023", "issn-l": "0066-4804"}, "abstract": "Dihydroartemisinin-piperaquine is efficacious for the treatment of uncomplicated malaria and its use is increasing globally. Despite the positive results in fighting malaria, inhibition of the Kv11.1 channel (hERG; encoded by the KCNH2 gene) by piperaquine has raised concerns about cardiac safety. Whether genetic factors could modulate the risk of piperaquine-mediated QT prolongations remained unclear. Here, we first profiled the genetic landscape of KCNH2 variability using data from 141,614 individuals. Overall, we found 1,007 exonic variants distributed over the entire gene body, 555 of which were missense. By optimizing the gene-specific parametrization of 16 partly orthogonal computational algorithms, we developed a KCNH2-specific ensemble classifier that identified a total of 116 putatively deleterious missense variations. To evaluate the clinical relevance of KCNH2 variability, we then sequenced 293 Malian patients with uncomplicated malaria and identified 13 variations within the voltage sensing and pore domains of Kv11.1 that directly interact with channel blockers. Cross-referencing of genetic and electrocardiographic data before and after piperaquine exposure revealed that carriers of two common variants, rs1805121 and rs41314375, experienced significantly higher QT prolongations (\u0394QTc of 41.8 ms and 61 ms, respectively, vs 14.4 ms in controls) with more than 50% of carriers having increases in QTc >30 ms. Furthermore, we identified three carriers of rare population-specific variations who experienced clinically relevant delayed ventricular repolarization. Combined, our results map population-scale genetic variability of KCNH2 and identify genetic biomarkers for piperaquine-induced QT prolongation that could help to flag at-risk patients and optimize efficacy and adherence to antimalarial therapy.", "doi": "10.1128/aac.01390-23", "pmid": "38546223", "labels": {"DDLS Fellow": null, "Yitian Zhou": null}, "xrefs": [{"db": "pmc", "key": "PMC11064487"}], "notes": [], "created": "2026-11-06T09:34:17.741Z", "modified": "2026-11-06T09:34:17.851Z"}, {"entity": "publication", "iuid": "858729ee9cfb4009a538aaec77d3177c", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/858729ee9cfb4009a538aaec77d3177c.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/858729ee9cfb4009a538aaec77d3177c"}}, "title": "Next-generation sequencing in pharmacogenomics - fit for clinical decision support?", "authors": [{"family": "Zhou", "given": "Yitian", "initials": "Y", "orcid": "0000-0003-3066-5444", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d.json"}}, {"family": "Lauschke", "given": "Volker M", "initials": "VM", "orcid": "0000-0002-1140-6204", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/82048d4da61547d08aa9d2bb3bae12dd.json"}}], "type": "journal article", "published": "2024-03-00", "journal": {"title": "Expert Rev Clin Pharmacol", "issn": "1751-2441", "volume": "17", "issue": "3", "pages": "213-223", "issn-l": null}, "abstract": "The technological advances of sequencing methods during the past 20 years have fuelled the generation of large amounts of sequencing data that comprise common variations, as well as millions of rare and personal variants that would not be identified by conventional genotyping. While comprehensive sequencing is technically feasible, its clinical utility for guiding personalized treatment decisions remains controversial.\n\nWe discuss the opportunities and challenges of comprehensive sequencing compared to targeted genotyping for pharmacogenomic applications. Current pharmacogenomic sequencing panels are heterogeneous and clinical actionability of the included genes is not a major focus. We provide a current overview and critical discussion of how current studies utilize sequencing data either retrospectively from biobanks, databases or repurposed diagnostic sequencing, or prospectively using pharmacogenomic sequencing.\n\nWhile sequencing-based pharmacogenomics has provided important insights into genetic variations underlying the safety and efficacy of a multitude pharmacological treatments, important hurdles for the clinical implementation of pharmacogenomic sequencing remain. We identify gaps in the interpretation of pharmacogenetic variants, technical challenges pertaining to complex loci and variant phasing, as well as unclear cost-effectiveness and incomplete reimbursement. It is critical to address these challenges in order to realize the promising prospects of pharmacogenomic sequencing.", "doi": "10.1080/17512433.2024.2307418", "pmid": "38247431", "labels": {"DDLS Fellow": null, "Yitian Zhou": null}, "xrefs": [], "notes": [], "created": "2026-11-06T09:33:47.044Z", "modified": "2026-11-06T09:33:47.103Z"}, {"entity": "publication", "iuid": "28a34a109dc24e86a66f6d9edaed4d04", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/28a34a109dc24e86a66f6d9edaed4d04.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/28a34a109dc24e86a66f6d9edaed4d04"}}, "title": "Cross-Ancestry Genome-Wide Association Study Defines the Extended CYP2D6 Locus as the Principal Genetic Determinant of Endoxifen Plasma Concentrations.", "authors": [{"family": "Khor", "given": "Chiea Chuen", "initials": "CC"}, {"family": "Winter", "given": "Stefan", "initials": "S"}, {"family": "Sutiman", "given": "Natalia", "initials": "N"}, {"family": "M\u00fcrdter", "given": "Thomas E", "initials": "TE"}, {"family": "Chen", "given": "Sylvia", "initials": "S", "orcid": "0000-0002-0445-6502", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5310f9983f7c447b8ccd17d80cb2d4a3.json"}}, {"family": "Lim", "given": "Joanne Siok Liu", "initials": "JSL"}, {"family": "Li", "given": "Zheng", "initials": "Z", "orcid": "0000-0002-7060-2213", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a014baeffa7c4317af45a704a24d17c9.json"}}, {"family": "Li", "given": "Jingmei", "initials": "J", "orcid": "0000-0001-8587-7511", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/6027dea1185b4a00a77a6bca138eab20.json"}}, {"family": "Sim", "given": "Kar Seng", "initials": "KS", "orcid": "0000-0002-3822-7759", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/7f1c9943279444bfad3e051f04296a71.json"}}, {"family": "Ganchev", "given": "Boian", "initials": "B"}, {"family": "Eccles", "given": "Diana", "initials": "D"}, {"family": "Eccles", "given": "Bryony", "initials": "B"}, {"family": "Tapper", "given": "William", "initials": "W"}, {"family": "Zgheib", "given": "Nathalie K", "initials": "NK", "orcid": "0000-0002-0571-768X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/191f804995e74a6d91b2c3a150be69ee.json"}}, {"family": "Tfayli", "given": "Arafat", "initials": "A"}, {"family": "Ng", "given": "Raymond Chee Hui", "initials": "RCH"}, {"family": "Yap", "given": "Yoon Sim", "initials": "YS"}, {"family": "Lim", "given": "Elaine", "initials": "E"}, {"family": "Wong", "given": "Mabel", "initials": "M"}, {"family": "Wong", "given": "Nan Soon", "initials": "NS"}, {"family": "Ang", "given": "Peter Cher Siang", "initials": "PCS"}, {"family": "Dent", "given": "Rebecca", "initials": "R"}, {"family": "Tremmel", "given": "Roman", "initials": "R", "orcid": "0000-0003-1564-0433", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5dcfb9d17c9340d69ea2c5fcbd06aeec.json"}}, {"family": "Klein", "given": "Kathrin", "initials": "K"}, {"family": "Schaeffeler", "given": "Elke", "initials": "E"}, {"family": "Zhou", "given": "Yitian", "initials": "Y", "orcid": "0000-0003-3066-5444", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d.json"}}, {"family": "Lauschke", "given": "Volker M", "initials": "VM", "orcid": "0000-0002-1140-6204", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/82048d4da61547d08aa9d2bb3bae12dd.json"}}, {"family": "Eichelbaum", "given": "Michel", "initials": "M"}, {"family": "Schwab", "given": "Matthias", "initials": "M", "orcid": "0000-0002-9984-075X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a671991e1b85463e8a7bbad2e29fb1bd.json"}}, {"family": "Brauch", "given": "Hiltrud B", "initials": "HB", "orcid": "0000-0001-7531-2736", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d50df7befe8b45989a8b81d3051004b5.json"}}, {"family": "Chowbay", "given": "Balram", "initials": "B", "orcid": "0000-0003-4775-9877", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a4b56e6cd97f40cd88668603d7c510f6.json"}}, {"family": "Schroth", "given": "Werner", "initials": "W", "orcid": "0000-0003-1412-4592", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/30be50cbd1474b8ebe8a0b31c5b47c91.json"}}], "type": "journal article", "published": "2023-03-00", "journal": {"title": "Clin. Pharmacol. Ther.", "issn": "1532-6535", "volume": "113", "issue": "3", "pages": "712-723", "issn-l": "0009-9236"}, "abstract": "The therapeutic efficacy of tamoxifen is predominantly mediated by its active metabolites 4-hydroxy-tamoxifen and endoxifen, whose formation is catalyzed by the polymorphic cytochrome P450 2D6 (CYP2D6). Yet, known CYP2D6 polymorphisms only partially determine metabolite concentrations in vivo. We performed the first cross-ancestry genome-wide association study with well-characterized patients of European, Middle-Eastern, and Asian descent (n = 497) to identify genetic factors impacting active and parent metabolite formation. Genome-wide significant variants were functionally evaluated in an independent liver cohort (n = 149) and in silico. Metabolite prediction models were validated in two independent European breast cancer cohorts (n = 287, n = 189). Within a single 1-megabase (Mb) region of chromosome 22q13 encompassing the CYP2D6 gene, 589 variants were significantly associated with tamoxifen metabolite concentrations, particularly endoxifen and metabolic ratio (MR) endoxifen/N-desmethyltamoxifen (minimal P = 5.4E-35 and 2.5E-65, respectively). Previously suggested other loci were not confirmed. Functional analyses revealed 66% of associated, mostly intergenic variants to be significantly correlated with hepatic CYP2D6 activity or expression (\u03c1 = 0.35 to -0.52), and six hotspot regions in the extended 22q13 locus impacting gene regulatory function. Machine learning models based on hotspot variants (n = 12) plus CYP2D6 activity score (AS) increased the explained variability (~ 9%) compared with AS alone, explaining up to 49% (median R2 ) and 72% of the variability in endoxifen and MR endoxifen/N-desmethyltamoxifen, respectively. Our findings suggest that the extended CYP2D6 locus at 22q13 is the principal genetic determinant of endoxifen plasma concentration. Long-distance haplotypes connecting CYP2D6 with adjacent regulatory sites and nongenetic factors may account for the unexplained portion of variability.", "doi": "10.1002/cpt.2846", "pmid": "36629403", "labels": {"DDLS Fellow": null, "Yitian Zhou": null}, "xrefs": [], "notes": [], "created": "2026-11-06T09:32:58.404Z", "modified": "2026-11-06T09:32:59.085Z"}, {"entity": "publication", "iuid": "2ece0b0aca9f4fcb9fb92d2ad2faf45f", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/2ece0b0aca9f4fcb9fb92d2ad2faf45f.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/2ece0b0aca9f4fcb9fb92d2ad2faf45f"}}, "title": "A paradigm shift in pharmacogenomics: From candidate polymorphisms to comprehensive sequencing.", "authors": [{"family": "Zhou", "given": "Yitian", "initials": "Y", "orcid": "0000-0003-3066-5444", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d.json"}}, {"family": "Koutsilieri", "given": "Stefania", "initials": "S", "orcid": "0000-0001-7067-0139", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d8891ce92ab74a22b46d7069bdd93ae6.json"}}, {"family": "Eliasson", "given": "Erik", "initials": "E"}, {"family": "Lauschke", "given": "Volker M", "initials": "VM", "orcid": "0000-0002-1140-6204", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/82048d4da61547d08aa9d2bb3bae12dd.json"}}], "type": "journal article", "published": "2022-12-00", "journal": {"title": "Basic Clin. Pharmacol. Toxicol.", "issn": "1742-7843", "volume": "131", "issue": "6", "pages": "452-464", "issn-l": "1742-7835"}, "abstract": "Genetic factors have long been recognized as important determinants of interindividual variability in drug efficacy and toxicity. However, despite the increasing number of established gene-drug associations, candidate polymorphisms can only explain a fraction of the genetically encoded functional variability in drug disposition. Advancements in genetic profiling methods now allow to analyse the landscape of human pharmacogenetic variations comprehensively, which opens new opportunities to identify novel factors that could explain the \"missing heritability.\" Here, we provide an updated overview of the landscape of pharmacogenomic variability based on recent analyses of population-scale sequencing projects. We then summarize the current state-of-the-art how the functional consequences of variants with unknown effects can be quantitatively estimated while discussing challenges and peculiarities that are specific to pharmacogenes. In the last sections, we discuss the importance of considering ethnogeographic diversity to provide equitable benefits of pharmacogenomics and summarize current roadblocks for the implementation of sequencing-based guidance of clinical decision-making. Based on the current state of the field, we conclude that testing is likely to gradually shift from the interrogation of selected candidate polymorphisms to comprehensive sequencing, which allows to consider the full spectrum of pharmacogenomic variations for a true personalization of genomic prescribing.", "doi": "10.1111/bcpt.13779", "pmid": "35971800", "labels": {"DDLS Fellow": null, "Yitian Zhou": null}, "xrefs": [{"db": "pmc", "key": "PMC9805052"}], "notes": [], "created": "2026-11-06T09:31:25.634Z", "modified": "2026-11-06T09:31:25.737Z"}, {"entity": "publication", "iuid": "e644f5af270b466a80538c9399583441", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/e644f5af270b466a80538c9399583441.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/e644f5af270b466a80538c9399583441"}}, "title": "The genetic landscape of major drug metabolizing cytochrome P450 genes-an updated analysis of population-scale sequencing data.", "authors": [{"family": "Zhou", "given": "Yitian", "initials": "Y", "orcid": "0000-0003-3066-5444", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d.json"}}, {"family": "Lauschke", "given": "Volker M", "initials": "VM", "orcid": "0000-0002-1140-6204", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/82048d4da61547d08aa9d2bb3bae12dd.json"}}], "type": "journal article", "published": "2022-12-00", "journal": {"title": "Pharmacogenomics J.", "issn": "1473-1150", "volume": "22", "issue": "5-6", "pages": "284-293", "issn-l": "1470-269X"}, "abstract": "Genes encoding cytochrome P450 enzymes (CYPs) are extremely polymorphic and multiple CYP variants constitute clinically relevant biomarkers for the guidance of drug selection and dosing. We previously reported the distribution of the most relevant CYP alleles using population-scale sequencing data. Here, we update these findings by making use of the increasing wealth of data, incorporating whole exome and whole genome sequencing data from 141,614 unrelated individuals across 12 human populations. We furthermore extend our previous studies by systematically considering also uncharacterized rare alleles and reveal that they contribute between 1.5% and 17.5% to the overall genetically encoded functional variability. By using established guidelines, we aggregate and translate the available sequencing data into population-specific patterns of metabolizer phenotypes. Combined, the presented data refine the worldwide landscape of ethnogeographic variability in CYP genes and aspire to provide a relevant resource for the optimization of population-specific genotyping strategies and precision public health.", "doi": "10.1038/s41397-022-00288-2", "pmid": "36068297", "labels": {"DDLS Fellow": null, "Yitian Zhou": null}, "xrefs": [{"db": "pmc", "key": "PMC9674520"}, {"db": "pii", "key": "10.1038/s41397-022-00288-2"}], "notes": [], "created": "2026-11-06T09:31:41.394Z", "modified": "2026-11-06T09:31:41.424Z"}, {"entity": "publication", "iuid": "983d6da6473f40dc885eda005b5c305e", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/983d6da6473f40dc885eda005b5c305e.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/983d6da6473f40dc885eda005b5c305e"}}, "title": "Cardiovascular Pharmacogenomics: An Update on Clinical Studies of Antithrombotic Drugs in Brazilian Patients.", "authors": [{"family": "Hirata", "given": "Thiago Dominguez Crespo", "initials": "TDC", "orcid": "0000-0002-3967-8121", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/58db0530c2634d4d98071dc5efda5a72.json"}}, {"family": "Dagli-Hernandez", "given": "Carolina", "initials": "C", "orcid": "0000-0003-2109-9399", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5c6619ab558c440eb79443baf981a0ac.json"}}, {"family": "Genvigir", "given": "Fabiana Dalla Vecchia", "initials": "FDV", "orcid": "0000-0002-7112-2879", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/eef08459787949a5a525ced75df26850.json"}}, {"family": "Lauschke", "given": "Volker Martin", "initials": "VM", "orcid": "0000-0002-1140-6204", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/82048d4da61547d08aa9d2bb3bae12dd.json"}}, {"family": "Zhou", "given": "Yitian", "initials": "Y", "orcid": "0000-0003-3066-5444", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d.json"}}, {"family": "Hirata", "given": "Mario Hiroyuki", "initials": "MH", "orcid": "0000-0002-9521-7979", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a7ac75c0d8474b49a5aba090c51e52fc.json"}}, {"family": "Hirata", "given": "Rosario Dominguez Crespo", "initials": "RDC", "orcid": "0000-0003-3073-5967", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/6412e946f63f466cace0bfd930d374c7.json"}}], "type": "journal article", "published": "2021-11-00", "journal": {"title": "Mol Diagn Ther", "issn": "1179-2000", "volume": "25", "issue": "6", "pages": "735-755", "issn-l": null}, "abstract": "Anticoagulant and antiplatelet drugs effectively prevent thrombotic events in patients with cardiovascular diseases, ischemic stroke, peripheral vascular diseases, and other thromboembolic diseases. However, genetic and non-genetic factors affect the response to antithrombotic therapy and can increase the risk of adverse events. This narrative review discusses pharmacogenomic studies on antithrombotic drugs commonly prescribed in Brazil. Multiple Brazilian studies assessed the impact of pharmacokinetic (PK) and pharmacodynamic (PD) gene variants on warfarin response. The reduced function alleles CYP2C9*2 and CYP2C9*3, and VKORC1 rs9923231 (c.-1639G>A) are associated with increased sensitivity to warfarin and a low dose requirement to prevent bleeding episodes, whereas CYP4F2 rs2108622 (p.Val433Met) carriers have higher dose requirements (warfarin resistance). These deleterious variants and non-genetic factors (age, gender, body weight, co-administered drugs, food interactions, and others) account for up to 63% of the warfarin dose variability. Few pharmacogenomics studies have explored antiplatelet drugs in Brazilian cohorts, finding associations between CYP2C19*2, PON1 rs662 and ABCC3 rs757421 genotypes and platelet responsiveness or clopidogrel PK in subjects with coronary artery disease (CAD) or acute coronary syndrome (ACS), whereas ITGB3 contributes to aspirin PK but not platelet responsiveness in diabetic patients. Brazilian guidelines on anticoagulants and antiplatelets recommend the use of a platelet aggregation test or genotyping only in selected cases of ACS subjects without ST-segment elevation taking clopidogrel, and also suggest CYP2C9 and VKORC1 genotyping before starting warfarin therapy to assess the risk of bleeding episodes or warfarin resistance.", "doi": "10.1007/s40291-021-00549-z", "pmid": "34357562", "labels": {"DDLS Fellow": null, "Yitian Zhou": null}, "xrefs": [{"db": "pii", "key": "10.1007/s40291-021-00549-z"}], "notes": [], "created": "2026-11-06T09:27:25.681Z", "modified": "2026-11-06T09:27:26.027Z"}, {"entity": "publication", "iuid": "0b81a745fadc4c0290088434d799cfe1", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/0b81a745fadc4c0290088434d799cfe1.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/0b81a745fadc4c0290088434d799cfe1"}}, "title": "Rare genetic variability in human drug target genes modulates drug response and can guide precision medicine.", "authors": [{"family": "Zhou", "given": "Yitian", "initials": "Y", "orcid": "0000-0003-3066-5444", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d.json"}}, {"family": "Arribas", "given": "Gabriel Herras", "initials": "GH", "orcid": "0000-0001-8067-7764", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c7a40eec7f3640d5923fca506e379c3c.json"}}, {"family": "Turku", "given": "Ainoleena", "initials": "A", "orcid": "0000-0003-0959-7221", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/80fbb027505240eaaebf4153df67a47f.json"}}, {"family": "J\u00fcrgenson", "given": "Tuuli", "initials": "T"}, {"family": "Mkrtchian", "given": "Souren", "initials": "S", "orcid": "0000-0001-9801-2736", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/4f0178b0c4ad4bfab16b512fce21b119.json"}}, {"family": "Krebs", "given": "Kristi", "initials": "K", "orcid": "0000-0003-0494-2751", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/1b98e04677d64206a83cab1c1328d936.json"}}, {"family": "Wang", "given": "Yi", "initials": "Y", "orcid": "0000-0002-3676-9183", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a03091d5222a409ba70c5fe26ac5455f.json"}}, {"family": "Svobodova", "given": "Barbora", "initials": "B", "orcid": "0000-0001-8099-089X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c58cb8dce631456d8a500ba4193c8b84.json"}}, {"family": "Milani", "given": "Lili", "initials": "L", "orcid": "0000-0002-5323-3102", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/e92d1400307a42f3a8baffc008996d1b.json"}}, {"family": "Schulte", "given": "Gunnar", "initials": "G", "orcid": "0000-0002-2700-7013", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5ca48082cc934a8494ac50e756be0f3e.json"}}, {"family": "Korabecny", "given": "Jan", "initials": "J", "orcid": "0000-0001-6977-7596", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5d8ccabb54834566ac9e298119a28484.json"}}, {"family": "Gastaldello", "given": "Stefano", "initials": "S", "orcid": "0000-0001-7369-8452", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/ad2f016a7270481b8085475e22441815.json"}}, {"family": "Lauschke", "given": "Volker M", "initials": "VM", "orcid": "0000-0002-1140-6204", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/82048d4da61547d08aa9d2bb3bae12dd.json"}}], "type": "journal article", "published": "2021-09-03", "journal": {"title": "Sci Adv", "issn": "2375-2548", "volume": "7", "issue": "36", "pages": "eabi6856", "issn-l": "2375-2548"}, "abstract": "Interindividual variability in drug response constitutes a major concern in pharmacotherapy. While polymorphisms in genes involved in drug disposition have been extensively studied, drug target variability remains underappreciated. By mapping the genomic variability of all human drug target genes onto high-resolution crystal structures of drug target complexes, we identified 1094 variants localized within 6 \u00c5 of drug-binding pockets and directly affecting their geometry, topology, or physicochemical properties. We experimentally show that binding site variants affect pharmacodynamics with marked drug- and variant-specific differences. In addition, we demonstrate that a common BCHE variant confers resistance to tacrine and rivastigmine, which can be overcome by the use of derivatives based on squaric acid scaffolds or tryptophan conjugation. These findings underscore the importance of genetic drug target variability and demonstrate that integration of genomic data and structural information can inform personalized drug selection and genetically guided drug development to overcome resistance.", "doi": "10.1126/sciadv.abi6856", "pmid": "34516913", "labels": {"DDLS Fellow": null, "Yitian Zhou": null}, "xrefs": [{"db": "pmc", "key": "PMC8442892"}], "notes": [], "created": "2026-11-06T09:27:07.941Z", "modified": "2026-11-06T09:27:08.312Z"}, {"entity": "publication", "iuid": "31fbdaf4ecbc4365bfb9e950ce15844b", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/31fbdaf4ecbc4365bfb9e950ce15844b.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/31fbdaf4ecbc4365bfb9e950ce15844b"}}, "title": "Population-scale predictions of DPD and TPMT phenotypes using a quantitative pharmacogene-specific ensemble classifier.", "authors": [{"family": "Zhou", "given": "Yitian", "initials": "Y", "orcid": "0000-0003-3066-5444", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4e92db79d554ad283927ad7e6e54e8d.json"}}, {"family": "Dagli Hernandez", "given": "Carolina", "initials": "C", "orcid": "0000-0003-2109-9399", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5c6619ab558c440eb79443baf981a0ac.json"}}, {"family": "Lauschke", "given": "Volker M", "initials": "VM", "orcid": "0000-0002-1140-6204", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/82048d4da61547d08aa9d2bb3bae12dd.json"}}], "type": "journal article", "published": "2020-12-00", "journal": {"title": "Br. J. Cancer", "issn": "1532-1827", "volume": "123", "issue": "12", "pages": "1782-1789", "issn-l": "0007-0920"}, "abstract": "Inter-individual differences in dihydropyrimidine dehydrogenase (DPYD encoding DPD) and thiopurine S-methyltransferase (TPMT) activity are important predictors for fluoropyrimidine and thiopurine toxicity. While several variants in these genes are known to decrease enzyme activities, many additional genetic variations with unclear functional consequences have been identified, complicating informed clinical decision-making in the respective carriers.\n\nWe used a novel pharmacogenetically trained ensemble classifier to analyse DPYD and TPMT genetic variability based on sequencing data from 138,842 individuals across eight populations.\n\nThe algorithm accurately predicted in vivo consequences of DPYD and TPMT variants (accuracy 91.4% compared to 95.3% in vitro). Further analysis showed high genetic complexity of DPD deficiency, advocating for sequencing-based DPYD profiling, whereas genotyping of four variants in TPMT was sufficient to explain >95% of phenotypic TPMT variability. Lastly, we provided population-scale profiles of ethnogeographic variability in DPD and TPMT phenotypes, and revealed striking interethnic differences in frequency and genetic constitution of DPD and TPMT deficiency.\n\nThese results provide the most comprehensive data set of DPYD and TPMT variability published to date with important implications for population-adjusted genetic profiling strategies of fluoropyrimidine and thiopurine risk factors and precision public health.", "doi": "10.1038/s41416-020-01084-0", "pmid": "32973300", "labels": {"DDLS Fellow": null, "Yitian Zhou": null}, "xrefs": [{"db": "pmc", "key": "PMC7722893"}, {"db": "pii", "key": "10.1038/s41416-020-01084-0"}], "notes": [], "created": "2026-11-06T09:25:20.232Z", "modified": "2026-11-06T09:25:20.378Z"}]}