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Klein, Teri E

0000-0001-5527-6475

Mayo Clinic

Department of Biomedical Data Science and Medicine (BMIR), Stanford University, Stanford, California, USA.

Citations 10

Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for Thiopurine Dosing Based on TPMT and NUDT15 Genotypes: 2025 Update
Maillard, M., Schwab, Matthias, Whirl-Carrillo, Michelle, Moyer, AM , Suarez‐Kurtz, Guilherme , Pui, CH, Stein, C Michael, Klein, Teri E. , Spahn, Claire , Kwon, Sooyeon, Boer, Nanne K de, Ahmad, Tariq, Antillon-Klussmann, Federico Guillermo, Caudle, Kelly E. , Yeoh, Allen E J, Schmiegelow, K., Yang, Jun J, Schwab, Matthias , Maillard, Maud , Maillard, Maud , Schwab, Matthias , Whirl-Carrillo, Michelle , Caudle, Kelly E , Kato, Motohiro , Klein, Teri E , Whirl‐Carrillo, Michelle , Stein, C. Michael, Hartono, Juanda Leo , Ahmad, Tariq , Antillon‐Klussmann, Federico Guillermo, Kato, Motohiro , Yeoh, Allen Eng Juh

Clinical Pharmacology & Therapeutics | January 31, 2026 | Volume: 119 | Issue: 4 | Pages: 916-927

10.1002/cpt.70209 Get It

Thiopurine methyltransferase (TPMT) and Nudix hydrolase 15 (NUDT15) are key enzymes that catabolize thiopurines. Decreased or no‐function alleles in TPMT and NUDT15 are associated with reduced or no enzyme activity and predictive of pronounced adverse effects, including severe myelosuppression, that may occur among individuals treated with standard doses of thiopurines. Genetic variants in these genes are present in all world populations; however, their frequency varies by ancestry. In this updated guideline, we provide recommendations for adjusting starting doses of mercaptopurine, thioguanine, and azathioprine based on TPMT and NUDT15 genotypes, including for individuals with variants in both genes (updates on www.clinpgx.org ).
Integrating Pharmacogenomics into the Broader Construct of Genomic Medicine: Efforts by the ClinGen Pharmacogenomics Working Group (PGxWG)
Gong, Li , Klein, Clarissa , Caudle, Kelly E. , Moyer, Ann M. , Klein, Teri E. , (PGxWG), ClinGen Pharmacogenomics Working Group, Ashcraft, Kristine , Bernhardt, Brooke, Blaxwell, Burns C, Bly, Zo, Cody, Neal, Tredici, Andria L. Del , Gregornik, David , Hart, Jennifer, Hoffman, James M. , Landrum, Melissa , Langlais, Kristofor K., Lee, M T M, Li, Rongling, McLeod, Howard L. , Monte, Andrew A. , Naik, Hetanshi , Obeng, Aniwaa Owusu , Ramos, Erin M. , Ren, Zhaoxia , Ritchie, Marylyn D. , Scherer, Steven E. , Shaaban, Sherin, Swen, Jesse J. , McIntyre, Joanne, Merritt, Keren, Wright, Matt W. , Klein, Teri E , Scott, Stuart A. , Whirl‐Carrillo, Michelle , (PGxWG), ClinGen Pharmacogenomics Working Group, Aminkeng, Folefac , Amr, Sami S , Cipriani, Amber , Dandara, Collet , Empey, Philip E. , Fieg, Elizabeth L. , Gaedigk, Andrea , Harrison, Steven M. , Hunter, Jessica Ezzell , Iwuchukwu, Otito Frances , Malheiro, Adriana , Morales, Joannella , Oni‐Orisan, Akinyemi , Rogers, Sara , Wagner, Alex H. , Woodahl, Erica L , McIntyre, Joanne, Merritt, Keren

Clinical Chemistry | January 3, 2025 | Volume: 71 | Issue: 1 | Pages: 36-44

10.1093/clinchem/hvae181 Get It

Abstract Pharmacogenomics (PGx) is focused on the relationship between an individual's genetic makeup and their response to medications, with the overarching aim of guiding prescribing decisions to improve drug efficacy and reduce adverse events. The PGx and genomic medicine communities have worked independently for over 2 decades, developing separate standards and terminology, making implementation of PGx across all areas of genomic medicine difficult. To address this issue, the Clinical Genome Resource (ClinGen) Pharmacogenomics Working Group (PGxWG) was established by the National Institutes of Health (NIH)-funded ClinGen to initially create frameworks for evaluating gene–drug response clinical validity and actionability aligned with the ClinGen frameworks for evaluating monogenic gene–disease relationships, and a framework for classifying germline PGx variants similar to the American College of Medical Genetics (ACMG) and Association of Molecular Pathology (AMP) system for interpretation of disease-causing variants. These frameworks will leverage decades of work from well-established PGx resources facilitating buy-in among PGx stakeholders. In this report, we describe the background and major activities of the ClinGen PGxWG, and how this initiative will facilitate the critical inclusion of PGx into the larger context of genomic medicine.
PharmVar Tutorial on CYP2D6 Structural Variation Testing and Recommendations on Reporting
Turner, Amy , Nofziger, Charity , Ramey-Hartung, Bronwyn , Ly, Reynold C. , Bousman, Chad , Agúndez, José A. G. , Sangkuhl, Katrin , Whirl‐Carrillo, Michelle , Dunnenberger, Henry M. , Ruaño, Gualberto , Kennedy, Martin A. , Phillips, Michael S. , Klein, Teri E. , Moyer, Ann M. , Turner, Amy J , Ramey, Bronwyn E , Bousman, Chad A , Vanoni, Simone , Dunnenberger, Henry M , Ruaño, Gualberto , Kennedy, Martin A , Phillips, Michael S , Hachad, Houda , Klein, Teri E , Moyer, AM , Gaedigk, Andrea , Whirl-Carrillo, Michelle , Agúndez, José A G , Hachad, Houda , Gaedigk, Andrea

Clinical Pharmacology & Therapeutics | September 5, 2023 | Volume: 114 | Issue: 6 | Pages: 1220-1237

10.1002/cpt.3044 Get It

The Pharmacogene Variation Consortium (PharmVar) provides nomenclature for the highly polymorphic human CYP2D6 gene locus and a comprehensive summary of structural variation. CYP2D6 contributes to the metabolism of numerous drugs and, thus, genetic variation in its gene impacts drug efficacy and safety. To accurately predict a patient's CYP2D6 phenotype, testing must include structural variants including gene deletions, duplications, hybrid genes, and combinations thereof. This tutorial offers a comprehensive overview of CYP2D6 structural variation, terms, and definitions, a review of methods suitable for their detection and characterization, and practical examples to address the lack of standards to describe CYP2D6 structural variants or any other pharmacogene. This PharmVar tutorial offers practical guidance on how to detect the many, often complex, structural variants, as well as recommends terms and definitions for clinical and research reporting. Uniform reporting is not only essential for electronic health record‐keeping but also for accurate translation of a patient's genotype into phenotype which is typically utilized to guide drug therapy.
Clinical Pharmacogenetics Implementation Consortium Guideline (CPIC) for CYP2C9 and Nonsteroidal Anti‐Inflammatory Drugs
Theken, Katherine N. , Lee, Craig R. , Gong, Li , Caudle, Kelly E. , Formea, Christine M. , Klein, Teri E. , Agúndez, José A. G. , Großer, Tilo , Agúndez, José A G , Klein, Teri E , Gaedigk, Andrea

Clinical Pharmacology & Therapeutics | March 19, 2020 | Volume: 108 | Issue: 2 | Pages: 191-200

10.1002/cpt.1830 Get It

Nonsteroidal anti‐inflammatory drugs (NSAIDs) are among the most commonly used analgesics due to their lack of addictive potential. However, NSAIDs have the potential to cause serious gastrointestinal, renal, and cardiovascular adverse events. CYP2C9 polymorphisms influence metabolism and clearance of several drugs in this class, thereby affecting drug exposure and potentially safety. We summarize evidence from the published literature supporting these associations and provide therapeutic recommendations for NSAIDs based on CYP2C9 genotype (updates at www.cpicpgx.org ).
PharmVar GeneFocus: CYP2D6
Nofziger, Charity , Turner, Amy , Whirl‐Carrillo, Michelle , Agúndez, José A. G. , Black, John L. , Dunnenberger, Henry M. , Ruaño, Gualberto , Kennedy, Martin A. , Hachad, Houda , Klein, Teri E. , Turner, Amy J , Whirl-Carrillo, Michelle , Agúndez, José A G , Black, John L , Dunnenberger, Henry M , Kennedy, Martin A , Hachad, Houda , Gaedigk, Andrea , Klein, Teri E , Sangkuhl, Katrin , Phillips, Michael , Gaedigk, Andrea

Clinical Pharmacology & Therapeutics | September 23, 2019 | Volume: 107 | Issue: 1 | Pages: 154-170

10.1002/cpt.1643 Get It

The Pharmacogene Variation Consortium (PharmVar) provides nomenclature for the highly polymorphic human CYP2D6 gene locus. CYP2D6 genetic variation impacts the metabolism of numerous drugs and, thus, can impact drug efficacy and safety. This GeneFocus provides a comprehensive overview and summary of CYP2D6 genetic variation and describes how the information provided by PharmVar is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC).
Clinical Pharmacogenetics Implementation Consortium Guideline for Thiopurine Dosing Based on TPMT and N
Relling, Mary V. , Schwab, Matthias , Whirl‐Carrillo, Michelle , Suarez‐Kurtz, Guilherme , Pui, Ching‐Hon, Stein, Charles, Moyer, Ann M. , Evans, William E. , Klein, Teri E. , Antillon‐Klussmann, Federico Guillermo, Caudle, Kelly E. , Yeoh, Allen Eng Juh , Antillón‐Klussmann, Federico , Yang, Jun J.J. , Whirl-Carrillo, Michelle , Klein, Teri E , Yeoh, Allen E J , Pui, Ching-Hon , Kato, Motohiro , Schmiegelow, Kjeld , Schwab, Matthias

Clinical Pharmacology & Therapeutics | November 17, 2018 | Volume: 105 | Issue: 5 | Pages: 1095-1105

10.1002/cpt.1304 Get It

Thiopurine methyltransferase (TPMT) activity exhibits a monogenic codominant inheritance and catabolizes thiopurines. TPMT variant alleles are associated with low enzyme activity and pronounced pharmacologic effects of thiopurines. Loss‐of‐function alleles in the NUDT15 gene are common in Asians and Hispanics and reduce the degradation of active thiopurine nucleotide metabolites, also predisposing to myelosuppression. We provide recommendations for adjusting starting doses of azathioprine, mercaptopurine, and thioguanine based on TPMT and NUDT15 genotypes (updates on www.cpicpgx.org ).
The Pharmacogenomics Research Network Translational Pharmacogenetics Program: Outcomes and Metrics of Pharmacogenetic Implementations Across Diverse Healthcare Systems
Luzum, Jasmine A. , Pakyz, R E, Elsey, AR, Haidar, Cyrine E. , Peterson, JF, Whirl‐Carrillo, Michelle , Handelman, SK, Palmer, Kathleen , Pulley, JM, Beller, Michael, Schildcrout, JS, Field, JR, Weitzel, KW, Cooper‐DeHoff, RM, Cavallari, Larisa H. , O'Donnell, PH, Altman, Russ B. , Pereira, Naveen L. , Ratain, MJ, Roden, DM, Embi, PJ, Klein, Teri E. , Johnson, JA, Relling, MV, Wang, L, Weinshilboum, RM, Freimuth, Robert R. , Johnson, Julie A. , Peterson, Josh F. , Schildcrout, Jonathan S. , Elsey, Amanda R., Peterson, JF, Weitzel, KW, Cooper-DeHoff, RM, Ratain, Mark J. , Roden, DM, Sadée, Wolfgang , Relling, Mary V. , Shuldiner, Alan R. , Schildcrout, Jonathan S , Whirl-Carrillo, Michelle , Freimuth, Robert R , Peterson, Josh F , Cavallari, Larisa H , Luzum, Jasmine A , Klein, Teri E

Clinical Pharmacology & Therapeutics | January 16, 2017 | Volume: 102 | Issue: 3 | Pages: 502-510

10.1002/cpt.630 Get It

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.
Developing knowledge resources to support precision medicine: principles from the Clinical Pharmacogenetics Implementation Consortium (CPIC)
Hoffman, James M. , Dunnenberger, Henry M. , Hicks, J. Kevin , Caudle, Kelly E. , Whirl‐Carrillo, Michelle , Freimuth, Robert R. , Klein, Teri E. , Peterson, Josh F. , Williams, Marc S , Whirl-Carrillo, Michelle , Dunnenberger, Henry M , Freimuth, Robert R , Peterson, Josh F , Klein, Teri E

Journal of the American Medical Informatics Association | March 30, 2016 | Volume: 23 | Issue: 4 | Pages: 796-801

10.1093/jamia/ocw027 Get It

Abstract To move beyond a select few genes/drugs, the successful adoption of pharmacogenomics into routine clinical care requires a curated and machine-readable database of pharmacogenomic knowledge suitable for use in an electronic health record (EHR) with clinical decision support (CDS). Recognizing that EHR vendors do not yet provide a standard set of CDS functions for pharmacogenetics, the Clinical Pharmacogenetics Implementation Consortium (CPIC) Informatics Working Group is developing and systematically incorporating a set of EHR-agnostic implementation resources into all CPIC guidelines. These resources illustrate how to integrate pharmacogenomic test results in clinical information systems with CDS to facilitate the use of patient genomic data at the point of care. Based on our collective experience creating existing CPIC resources and implementing pharmacogenomics at our practice sites, we outline principles to define the key features of future knowledge bases and discuss the importance of these knowledge resources for pharmacogenomics and ultimately precision medicine.
Pharmacogenetic allele nomenclature: International workgroup recommendations for test result reporting
Kalman, LV, Agúndez, JAG, Appell, Malin Lindqvist , Black, J.H., Bell, GC, Boukouvala, Sotiria , Bruckner, Carsten, Bruford, Elspeth A. , Caudle, KE, Coulthard, SA, Daly, Ann K. , Tredici, AL Del, Dunnen, Johan T. den , Drozda, Katarzyna, Everts, Robin E. , Flockhart, David A., Freimuth, Robert R. , Hachad, Houda , Hartshorne, Toinette, Ingelman‐Sundberg, Magnus , Klein, Teri E. , Lauschke, Volker M. , Maglott, DR, McLeod, HL, McMillin, GA, Ua, Meyer, Dj, Müller, Nickerson, D. A., Oetting, WS , Pacanowski, MA, Vm, Pratt, Relling, MV, Roberts, Angharad M. , Ws, Rubinstein, Sangkuhl, Katrin , Schwab, Matthias , Scott, Stuart A. , Sim, SC, Thirumaran, RK, Toji, LH, Tyndale, Rachel F. , Schaik, RHN van, Whirl‐Carrillo, Michelle , Yeo, K. L. B., Zanger, UM, Agúndez, José A. G. , Müller, Daniel J. , Agúndez, JAG, Gaedigk, Andrea , Relling, Mary V. , Toji, Lorraine H., Whirl-Carrillo, Michelle , Agúndez, José A G , Hachad, Houda , Müller, Daniel J , Tyndale, Rachel F , Freimuth, Robert R , Klein, Teri E , Scott, Stuart A , Schwab, Matthias

Clinical Pharmacology & Therapeutics | October 20, 2015 | Volume: 99 | Issue: 2 | Pages: 172-185

10.1002/cpt.280 Get It

This article provides nomenclature recommendations developed by an international workgroup to increase transparency and standardization of pharmacogenetic (PGx) result reporting. Presently, sequence variants identified by PGx tests are described using different nomenclature systems. In addition, PGx analysis may detect different sets of variants for each gene, which can affect interpretation of results. This practice has caused confusion and may thereby impede the adoption of clinical PGx testing. Standardization is critical to move PGx forward.
Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for CYP2D6 and CYP2C19 Genotypes and Dosing of Selective Serotonin Reuptake Inhibitors
Hicks, J K, Bishop, JR, Dj, Müller, Leckband, SG, Leeder, JS, Graham, RL, Chiulli, DL, LLerena, Adrián , Skaar, TC, Scott, Stuart A. , Stingl, Julia , Klein, Teri E. , Caudle, KE, Leeder, J. Steven , Müller, Daniel J. , Sangkuhl, Katrin , Ji, Yuan , Skaar, T.C., Gaedigk, Andrea , LLerena, Adrián , Müller, Daniel J , Klein, Teri E , Scott, Stuart A

Clinical Pharmacology & Therapeutics | May 13, 2015 | Volume: 98 | Issue: 2 | Pages: 127-134

10.1002/cpt.147 Get It

Selective serotonin reuptake inhibitors (SSRIs) are primary treatment options for major depressive and anxiety disorders. CYP2D6 and CYP2C19 polymorphisms can influence the metabolism of SSRIs, thereby affecting drug efficacy and safety. We summarize evidence from the published literature supporting these associations and provide dosing recommendations for fluvoxamine, paroxetine, citalopram, escitalopram, and sertraline based on CYP2D6 and/or CYP2C19 genotype (updates at www.pharmgkb.org ).