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Johnson L, Youssef E, O'Shea J, Thornley T, Gallagher J, Ledwidge M, Ryan C. Estimating the prevalence of potential and actionable drug-gene interactions in Irish primary care: A cross-sectional study. Br J Clin Pharmacol 2024. [PMID: 38864275 DOI: 10.1111/bcp.16122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 04/03/2024] [Accepted: 04/13/2024] [Indexed: 06/13/2024] Open
Abstract
AIMS Pharmacogenetics (PGx) is increasingly recognized as a strategy for medicines optimisation and prevention of adverse drug reactions. According to guidelines produced by the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Dutch Pharmacogenetic Working Group (DPWG), most medicines with drug-gene interactions (DGIs) are prescribed in primary care. This study aimed to estimate the prevalence of potential and actionable DGIs involving all medicines dispensed in Irish primary care. METHODS Dispensings of 46 drugs to General Medical Services (GMS) patients in the Health Service Executive Primary Care Reimbursement Service Irish pharmacy claims database from 01 January 2021 to 31 December 2021 were analysed to estimate the national prevalence of total dispensings and incidence of first-time dispensings of drugs with potential DGIs according to the CPIC and/or DPWG guidelines. Phenotype frequency data from the UK Biobank and the CPIC were used to estimate the incidence of actionable DGIs. RESULTS One in five dispensings (12 443 637 of 62 754 498, 19.8%) were medicines with potential DGIs, 1 878 255 of these dispensed for the first time. On application of phenotype frequencies and linked guideline based therapeutic recommendations, 2 349 055 potential DGIs (18.9%) required action, such as monitoring and guarding against maximum dose, drug or dose change. One in five (369 700, 19.7%) first-time dispensings required action, with 139 169 (7.4%) requiring a change in prescribing. Antidepressants, weak opioids and statins were most commonly identified as having actionable DGIs. CONCLUSIONS This study estimated a high prevalence of DGIs in primary care in Ireland, identifying the need and opportunity to optimize drug therapy through PGx testing.
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Affiliation(s)
- L Johnson
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - E Youssef
- Faculty of Health, Science, Social Care & Education, Kingston University, London, UK
| | - J O'Shea
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - T Thornley
- School of Pharmacy, University of Nottingham, Nottingham, UK
| | - J Gallagher
- School of Medicine, University College Dublin, Dublin, Ireland
| | - M Ledwidge
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- School of Medicine, University College Dublin, Dublin, Ireland
| | - C Ryan
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
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2
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Hahn M, Frantz AM, Eckert A, Reif A. [Barriers for Implementation of PGx Testing in Psychiatric Hospitals in Germany: Results of the FACT-PGx Study]. FORTSCHRITTE DER NEUROLOGIE-PSYCHIATRIE 2024; 92:221-229. [PMID: 37130546 DOI: 10.1055/a-2060-0694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
OBJECTIVE The FACT-PGx study was conducted to analyze barriers to implementation of pharmacogenetic testing in psychiatric hospitals in Germany and to propose solutions for its faster and easier implementation in all hospitals. METHODS 104 patients (50% female) were genotyped and participated in the study. 67 completed a survey. To analyze the correlation between continuous data (age) of the survey, the wilcoxon rank test and for categorial data (education level, history of treatment and episodes), t-test was used. RESULTS No patient declined to be genotyped. 99% believed that genotyping could help to shorten their hospital stay. Patients >40 years of age and with higher educational levels were willing to pay for the PGx (p=0.009). On average, patients were willing to pay 117.42€ +/-140.49€ and to wait 15.83+/- 8.92 days for the results. Processes differed significantly between routine laboratory screening and PGx testing which could be a barrier for implementation. CONCLUSION Patients are not barriers to but enablers of an implementation of PGx. New process flows can be barriers, but can be overcome by optimization.
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Affiliation(s)
- Martina Hahn
- Klinik für Psychiatrie, Psychosomatik und Psychotherapie, Universitätsklinikum Frankfurt, Frankfurt am Main, Germany
- Klinik für psychische Gesundheit, varisano Klinikum Frankfurt Hoechst, Frankfurt, Germany
| | - Amelie Merle Frantz
- Klinik für Psychiatrie, Psychosomatik und Psychotherapie, Universitätsklinikum Frankfurt, Frankfurt am Main, Germany
| | - Andreas Eckert
- Klinik für Psychiatrie, Psychosomatik und Psychotherapie, Universitätsklinikum Frankfurt, Frankfurt am Main, Germany
| | - Andreas Reif
- Klinik für Psychiatrie, Psychosomatik und Psychotherapie, Universitätsklinikum Frankfurt, Frankfurt am Main, Germany
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Xu X, Li Y, Han T, Zhao Y, Wang X, Fu X, Mao H. The hidden dangers of short-term glucocorticoid use in children: A genomic analysis. Int Immunopharmacol 2024; 135:112323. [PMID: 38788448 DOI: 10.1016/j.intimp.2024.112323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 05/11/2024] [Accepted: 05/19/2024] [Indexed: 05/26/2024]
Abstract
OBJECTIVE Glucocorticoid (GC) administration has been associated with adverse drug reactions (ADRs) affecting multiple organ systems. While long-term use is widely recognized as a significant independent predictor of ADRs, it is important to note that even short-term use can lead to serious ADRs. The considerable inter-individual variability in ADRs occurrence may be influenced by genetic factors. This study, we present a case of a child who experienced significant weight gain and osteoporosis, following a brief administration of GC. METHODS To comprehensively investigate the underlying mechanisms, we conducted a genomic analysis utilizing the whole exome sequencing (WES) technique. This analysis encompassed the examination of phase I and phase II metabolism, influx transport, efflux transport, and drug targeting. Additionally, a comprehensive analysis was conducted on a cohort of 52,119 children to determine their ABCB1 rs1045642 genotype, and an additional 37,884 children were tested for their CYP3A5 rs776746 genotype. RESULTS The pharmacogenetic analysis unveiled the presence of a high-risk variant in ABCB1 rs1045642 and a slow metabolism variant in CYP3A5 rs776746, both of which have the potential to substantially contribute to ADRs. The findings of this study indicate that the prevalence of ABCB1 rs1045642 CT type among patients was 47.58%, with TT type accounting for 15.69 % and CC type accounting for 36.73 %. Furthermore, the distribution of CYP3A5 rs776746 CC genotype was observed in 50.54 % of individuals, while CT and TT genotypes were present in 41.15 % and 8.31 % of the population respectively. The distribution of ABCB1 and CYP3A5 genotypes among the pediatric population in China displays notable features. Specifically, for the ABCB1 rs1045642 genotype, less than 50 % of children exhibit intermediate metabotypes. Conversely, among children with the CYP3A5 rs776746 genotype, the predominant cause for enzyme activity is the slow metabolic type, accounting for up to 90 % of cases. CONCLUSIONS Consequently, it is imperative to thoroughly evaluate the impact of allele mutation on the effectiveness and safety of glucocorticoid drugs or other medications metabolized by the ABCB1 and CYP3A5, particularly in the context of Chinese pediatric patients.
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Affiliation(s)
- Xiaolin Xu
- Department of Immunity, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, China; Department of Pharmacy, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, China
| | - Yan Li
- Department of Immunity, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, China
| | - Tongxin Han
- Department of Immunity, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, China
| | - Yiming Zhao
- Department of Pharmacy, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, China
| | - Xiaoling Wang
- Department of Pharmacy, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, China
| | | | - Huawei Mao
- Department of Immunity, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, China; Ministry of Education Key Laboratory of Major Diseases in Children, Beijing 100045, China.
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Zeng S, Qing Q, Xu W, Yu S, Zheng M, Tan H, Peng J, Huang J. Personalized anesthesia and precision medicine: a comprehensive review of genetic factors, artificial intelligence, and patient-specific factors. Front Med (Lausanne) 2024; 11:1365524. [PMID: 38784235 PMCID: PMC11111965 DOI: 10.3389/fmed.2024.1365524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 04/22/2024] [Indexed: 05/25/2024] Open
Abstract
Precision medicine, characterized by the personalized integration of a patient's genetic blueprint and clinical history, represents a dynamic paradigm in healthcare evolution. The emerging field of personalized anesthesia is at the intersection of genetics and anesthesiology, where anesthetic care will be tailored to an individual's genetic make-up, comorbidities and patient-specific factors. Genomics and biomarkers can provide more accurate anesthetic protocols, while artificial intelligence can simplify anesthetic procedures and reduce anesthetic risks, and real-time monitoring tools can improve perioperative safety and efficacy. The aim of this paper is to present and summarize the applications of these related fields in anesthesiology by reviewing them, exploring the potential of advanced technologies in the implementation and development of personalized anesthesia, realizing the future integration of new technologies into clinical practice, and promoting multidisciplinary collaboration between anesthesiology and disciplines such as genomics and artificial intelligence.
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Affiliation(s)
- Shiyue Zeng
- Zhuzhou Clinical College, Jishou University, Jishou, China
| | - Qi Qing
- Zhuzhou Clinical College, Jishou University, Jishou, China
| | - Wei Xu
- Department of Anesthesiology, Zhuzhou Central Hospital, Zhuzhou, China
| | - Simeng Yu
- Zhuzhou Clinical College, Jishou University, Jishou, China
| | - Mingzhi Zheng
- Department of Anesthesiology, Zhuzhou Central Hospital, Zhuzhou, China
| | - Hongpei Tan
- Department of Radiology, Third Xiangya Hospital, Central South University, Changsha, China
| | - Junmin Peng
- Department of Anesthesiology, Zhuzhou Central Hospital, Zhuzhou, China
| | - Jing Huang
- Department of Anesthesiology, Zhuzhou Central Hospital, Zhuzhou, China
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5
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Sadler MC, Apostolov A, Cevallos C, Ribeiro DM, Altman RB, Kutalik Z. Leveraging large-scale biobank EHRs to enhance pharmacogenetics of cardiometabolic disease medications. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.06.24305415. [PMID: 38633781 PMCID: PMC11023668 DOI: 10.1101/2024.04.06.24305415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/19/2024]
Abstract
Electronic health records (EHRs) coupled with large-scale biobanks offer great promises to unravel the genetic underpinnings of treatment efficacy. However, medication-induced biomarker trajectories stemming from such records remain poorly studied. Here, we extract clinical and medication prescription data from EHRs and conduct GWAS and rare variant burden tests in the UK Biobank (discovery) and the All of Us program (replication) on ten cardiometabolic drug response outcomes including lipid response to statins, HbA1c response to metformin and blood pressure response to antihypertensives (N = 740-26,669). Our findings at genome-wide significance level recover previously reported pharmacogenetic signals and also include novel associations for lipid response to statins (N = 26,669) near LDLR and ZNF800. Importantly, these associations are treatment-specific and not associated with biomarker progression in medication-naive individuals. Furthermore, we demonstrate that individuals with higher genetically determined low-density and total cholesterol baseline levels experience increased absolute, albeit lower relative biomarker reduction following statin treatment. In summary, we systematically investigated the common and rare pharmacogenetic contribution to cardiometabolic drug response phenotypes in over 50,000 UK Biobank and All of Us participants with EHR and identified clinically relevant genetic predictors for improved personalized treatment strategies.
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Affiliation(s)
- Marie C. Sadler
- University Center for Primary Care and Public Health, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Alexander Apostolov
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Caterina Cevallos
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Diogo M. Ribeiro
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Russ B. Altman
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Zoltán Kutalik
- University Center for Primary Care and Public Health, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
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Calendo G, Kusic D, Madzo J, Gharani N, Scheinfeldt L. ursaPGx: a new R package to annotate pharmacogenetic star alleles using phased whole-genome sequencing data. FRONTIERS IN BIOINFORMATICS 2024; 4:1351620. [PMID: 38533129 PMCID: PMC10963438 DOI: 10.3389/fbinf.2024.1351620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 02/28/2024] [Indexed: 03/28/2024] Open
Abstract
Long-read sequencing technologies offer new opportunities to generate high-confidence phased whole-genome sequencing data for robust pharmacogenetic annotation. Here, we describe a new user-friendly R package, ursaPGx, designed to accept multi-sample phased whole-genome sequencing data VCF input files and output star allele annotations for pharmacogenes annotated in PharmVar.
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Affiliation(s)
- Gennaro Calendo
- Coriell Institute for Medical Research, Camden, NJ, United States
| | - Dara Kusic
- Coriell Institute for Medical Research, Camden, NJ, United States
| | - Jozef Madzo
- Coriell Institute for Medical Research, Camden, NJ, United States
- Cooper Medical School of Rowan University, Camden, NJ, United States
| | - Neda Gharani
- Coriell Institute for Medical Research, Camden, NJ, United States
- Gharani Consulting Limited, London, United Kingdom
| | - Laura Scheinfeldt
- Coriell Institute for Medical Research, Camden, NJ, United States
- Cooper Medical School of Rowan University, Camden, NJ, United States
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7
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Dolin RH, Shenvi E, Alvarez C, Barrows RC, Boxwala A, Lee B, Nathanson BH, Kleyner Y, Hagemann R, Hongsermeier T, Kapusnik-Uner J, Lakdawala A, Shalaby J. PillHarmonics: An Orchestrated Pharmacogenetics Medication Clinical Decision Support Service. Appl Clin Inform 2024; 15:378-387. [PMID: 38388174 PMCID: PMC11098593 DOI: 10.1055/a-2274-6763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 02/07/2024] [Indexed: 02/24/2024] Open
Abstract
OBJECTIVES Pharmacogenetics (PGx) is increasingly important in individualizing therapeutic management plans, but is often implemented apart from other types of medication clinical decision support (CDS). The lack of integration of PGx into existing CDS may result in incomplete interaction information, which may pose patient safety concerns. We sought to develop a cloud-based orchestrated medication CDS service that integrates PGx with a broad set of drug screening alerts and evaluate it through a clinician utility study. METHODS We developed the PillHarmonics service for implementation per the CDS Hooks protocol, algorithmically integrating a wide range of drug interaction knowledge using cloud-based screening services from First Databank (drug-drug/allergy/condition), PharmGKB (drug-gene), and locally curated content (drug-renal/hepatic/race). We performed a user study, presenting 13 clinicians and pharmacists with a prototype of the system's usage in synthetic patient scenarios. We collected feedback via a standard questionnaire and structured interview. RESULTS Clinician assessment of PillHarmonics via the Technology Acceptance Model questionnaire shows significant evidence of perceived utility. Thematic analysis of structured interviews revealed that aggregated knowledge, concise actionable summaries, and information accessibility were highly valued, and that clinicians would use the service in their practice. CONCLUSION Medication safety and optimizing efficacy of therapy regimens remain significant issues. A comprehensive medication CDS system that leverages patient clinical and genomic data to perform a wide range of interaction checking and presents a concise and holistic view of medication knowledge back to the clinician is feasible and perceived as highly valuable for more informed decision-making. Such a system can potentially address many of the challenges identified with current medication-related CDS.
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Affiliation(s)
| | - Edna Shenvi
- Elimu Informatics, El Cerrito, California, United States
| | - Carla Alvarez
- Elimu Informatics, El Cerrito, California, United States
| | | | - Aziz Boxwala
- Elimu Informatics, El Cerrito, California, United States
| | - Benson Lee
- College of Pharmacy, Touro University California, Vallejo, California, United States
| | | | - Yelena Kleyner
- Elimu Informatics, El Cerrito, California, United States
| | - Rachel Hagemann
- Independent Contractor, San Francisco, California, United States
| | | | | | | | - James Shalaby
- Elimu Informatics, El Cerrito, California, United States
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8
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Russell C, Campion M, Grove ME, Matsuda K, Klein TE, Ashley E, Naik H, Wheeler MT, Scott SA. Knowledge and attitudes on implementing cardiovascular pharmacogenomic testing. Clin Transl Sci 2024; 17:e13737. [PMID: 38421234 PMCID: PMC10903329 DOI: 10.1111/cts.13737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 12/22/2023] [Accepted: 01/23/2024] [Indexed: 03/02/2024] Open
Abstract
Pharmacogenomics has the potential to inform drug dosing and selection, reduce adverse events, and improve medication efficacy; however, provider knowledge of pharmacogenomic testing varies across provider types and specialties. Given that many actionable pharmacogenomic genes are implicated in cardiovascular medication response variability, this study aimed to evaluate cardiology providers' knowledge and attitudes on implementing clinical pharmacogenomic testing. Sixty-one providers responded to an online survey, including pharmacists (46%), physicians (31%), genetic counselors (15%), and nurses (8%). Most respondents (94%) reported previous genetics education; however, only 52% felt their genetics education prepared them to order a clinical pharmacogenomic test. In addition, most respondents (66%) were familiar with pharmacogenomics, with genetic counselors being most likely to be familiar (p < 0.001). Only 15% of respondents had previously ordered a clinical pharmacogenomic test and a total of 36% indicated they are likely to order a pharmacogenomic test in the future; however, the vast majority of respondents (89%) were interested in pharmacogenomic testing being incorporated into diagnostic cardiovascular genetic tests. Moreover, 84% of providers preferred pharmacogenomic panel testing compared to 16% who preferred single gene testing. Half of the providers reported being comfortable discussing pharmacogenomic results with their patients, but the majority (60%) expressed discomfort with the logistics of test ordering. Reported barriers to implementation included uncertainty about the clinical utility and difficulty choosing an appropriate test. Taken together, cardiology providers have moderate familiarity with pharmacogenomics and limited experience with test ordering; however, they are interested in incorporating pharmacogenomics into diagnostic genetic tests and ordering pharmacogenomic panels.
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Affiliation(s)
- Callan Russell
- Department of GeneticsStanford UniversityStanfordCaliforniaUSA
- Present address:
Northside HospitalAtlantaGeorgiaUSA
| | - MaryAnn Campion
- Department of GeneticsStanford UniversityStanfordCaliforniaUSA
| | - Megan E. Grove
- Clinical Genomics LaboratoryStanford MedicinePalo AltoCaliforniaUSA
- Present address:
Color HealthBurlingameCaliforniaUSA
| | - Kelly Matsuda
- Division of Pharmacy and CardiologyStanford Health CarePalo AltoCaliforniaUSA
| | - Teri E. Klein
- Department of Biomedical Data ScienceStanford UniversityStanfordCaliforniaUSA
| | - Euan Ashley
- Stanford Center for Inherited Cardiovascular DiseaseStanfordCaliforniaUSA
- Department of Medicine, Division of Cardiovascular MedicineStanford UniversityStanfordCaliforniaUSA
| | - Hetanshi Naik
- Department of GeneticsStanford UniversityStanfordCaliforniaUSA
| | - Matthew T. Wheeler
- Stanford Center for Inherited Cardiovascular DiseaseStanfordCaliforniaUSA
- Department of Medicine, Division of Cardiovascular MedicineStanford UniversityStanfordCaliforniaUSA
| | - Stuart A. Scott
- Clinical Genomics LaboratoryStanford MedicinePalo AltoCaliforniaUSA
- Department of PathologyStanford UniversityStanfordCaliforniaUSA
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9
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Kappel DB, Rees E, Fenner E, King A, Jansen J, Helthuis M, Owen MJ, O'Donovan MC, Walters JTR, Pardiñas AF. Rare variants in pharmacogenes influence clozapine metabolism in individuals with schizophrenia. Eur Neuropsychopharmacol 2024; 80:47-54. [PMID: 38310750 DOI: 10.1016/j.euroneuro.2023.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 12/14/2023] [Accepted: 12/18/2023] [Indexed: 02/06/2024]
Abstract
Clozapine is the only licensed medication for treatment-resistant schizophrenia (TRS). Few predictors for variation in response to clozapine have been identified, but clozapine metabolism is known to influence therapeutic response and adverse side effects. Here, we expand on genome-wide studies of clozapine metabolism, previously focused on common genetic variation, by analysing whole-exome sequencing data from 2062 individuals with schizophrenia taking clozapine in the UK. We investigated whether rare genomic variation in genes and gene sets involved in the clozapine metabolism pathway influences plasma concentrations of clozapine metabolites, assessed through the longitudinal analysis of 6585 pharmacokinetic assays. We observed a statistically significant association between the burden of rare damaging coding variants (MAF ≤ 1 %) in gene sets broadly related to drug pharmacokinetics and lower clozapine (β = -0.054, SE = 0.019, P-value = 0.005) concentrations in plasma. We estimate that the effects in clozapine plasma concentrations of a single damaging allele in this gene set are akin to reducing the clozapine dose by about 35 mg/day. The gene-based analysis identified rare variants in CYP1A2, which encodes the enzyme responsible for converting clozapine to norclozapine, as having the strongest effects of any gene on clozapine metabolism (β = 0.324, SE = 0.124, P = 0.009). Our findings support the hypothesis that rare genetic variants in known drug-metabolising enzymes and transporters can markedly influence clozapine plasma concentrations; these results suggest that pharmacogenomic efforts trying to predict clozapine metabolism and personalise drug therapy could benefit from the inclusion of rare damaging variants in pharmacogenes beyond those already identified and catalogued as PGx star alleles.
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Affiliation(s)
- Djenifer B Kappel
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Elliott Rees
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Eilidh Fenner
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Adrian King
- Magna Laboratories Ltd., Ross-on-Wye, United Kingdom
| | - John Jansen
- Leyden Delta B.V., Nijmegen, The Netherlands
| | | | - Michael J Owen
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Michael C O'Donovan
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - James T R Walters
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Antonio F Pardiñas
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom.
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10
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Gharani N, Calendo G, Kusic D, Madzo J, Scheinfeldt L. Star allele search: a pharmacogenetic annotation database and user-friendly search tool of publicly available 1000 Genomes Project biospecimens. BMC Genomics 2024; 25:116. [PMID: 38279110 PMCID: PMC10811916 DOI: 10.1186/s12864-024-09994-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 01/08/2024] [Indexed: 01/28/2024] Open
Abstract
Here we describe a new public pharmacogenetic (PGx) annotation database of a large (n = 3,202) and diverse biospecimen collection of 1000 Genomes Project cell lines and DNAs. The database is searchable with a user friendly, web-based tool ( www.coriell.org/StarAllele/Search ). This resource leverages existing whole genome sequencing data and PharmVar annotations to characterize *alleles for each biospecimen in the collection. This new tool is designed to facilitate in vitro functional characterization of *allele haplotypes and diplotypes as well as support clinical PGx assay development, validation, and implementation.
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Affiliation(s)
- N Gharani
- Coriell Institute for Medical Research, 403 Haddon Ave, Camden, NJ, 08103, USA
- Gharani Consulting Limited, 272 Regents Park Road, London, N3 3HN, UK
| | - G Calendo
- Coriell Institute for Medical Research, 403 Haddon Ave, Camden, NJ, 08103, USA
| | - D Kusic
- Coriell Institute for Medical Research, 403 Haddon Ave, Camden, NJ, 08103, USA
| | - J Madzo
- Coriell Institute for Medical Research, 403 Haddon Ave, Camden, NJ, 08103, USA
- Cooper Medical School of Rowan University, 401 South Broadway, Camden, NJ, 08103, USA
| | - L Scheinfeldt
- Coriell Institute for Medical Research, 403 Haddon Ave, Camden, NJ, 08103, USA.
- Cooper Medical School of Rowan University, 401 South Broadway, Camden, NJ, 08103, USA.
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Lemke LK, Cicali EJ, Williams R, Nguyen KA, Cavallari LH, Wiisanen K. Clinician Response to Pharmacogenetic Clinical Decision Support Alerts. Clin Pharmacol Ther 2023; 114:1350-1357. [PMID: 37716912 PMCID: PMC10726431 DOI: 10.1002/cpt.3051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 08/09/2023] [Indexed: 09/18/2023]
Abstract
The objective of this study was to characterize clinician response following standardization of pharmacogenetic (PGx) clinical decision support alerts at University of Florida (UF) Health. A retrospective analysis of all PGx alerts that fired at a tertiary academic medical center from August 2020 through May 2022 was performed. Alert acceptance rate was calculated and compared across six gene-drug pairs, patient care setting, and clinician specialty. The disposition of the triggering medication was compared with the alert response and evaluated for congruence. There were a total of 818 alerts included for analysis of alert response, 557 alerts included in acceptance rate calculations, and 392 alerts with sufficient information to assess clinical response. The overall acceptance rate was 63%. The alert response and clinical response were congruent for 47% of alerts. Alert response was influenced by the triggering gene-drug pair, clinician specialty, patient care setting, and specialty of the provider who initially ordered the PGx test. Clinical response was mostly incongruent with alert response. Alert acceptance is influenced by the triggering gene-drug pair, clinician specialty, and care setting. Alert response is not a reliable surrogate marker for clinical action. Any future research into the impact of clinical decision support (CDS) alerts should focus on clinical response rather than alert response. Given the reliance on CDS alerts to enhance uptake of PGx, it is worthwhile to further investigate their impact on prescribing and patient outcomes.
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Affiliation(s)
- Lauren K Lemke
- Pharmacotherapy and Translational Research, University of Florida, Gainesville, USA
| | - Emily J Cicali
- Pharmacotherapy and Translational Research, University of Florida, Gainesville, USA
| | - Roy Williams
- Pharmacotherapy and Translational Research, University of Florida, Gainesville, USA
| | - Khoa A Nguyen
- Pharmacotherapy and Translational Research, University of Florida, Gainesville, USA
| | - Larisa H Cavallari
- Pharmacotherapy and Translational Research, University of Florida, Gainesville, USA
| | - Kristin Wiisanen
- Pharmacotherapy and Translational Research, University of Florida, Gainesville, USA
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12
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Tippenhauer K, Philips M, Largiadèr C, Sariyar M. Using the PharmCAT tool for Pharmacogenetic clinical decision support. Brief Bioinform 2023; 25:bbad452. [PMID: 38055839 PMCID: PMC10699732 DOI: 10.1093/bib/bbad452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 10/25/2023] [Accepted: 11/11/2023] [Indexed: 12/08/2023] Open
Abstract
Here, we will provide our insights into the usage of PharmCAT as part of a pharmacogenetic clinical decision support pipeline, which addresses the challenges in mapping clinical dosing guidelines to variants to be extracted from genetic datasets. After a general outline of pharmacogenetics, we describe some features of PharmCAT and how we integrated it into a pharmacogenetic clinical decision support system within a clinical information system. We conclude with promising developments regarding future PharmCAT releases.
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Affiliation(s)
- Kevin Tippenhauer
- Bern University of Applied Sciences, Quellgasse 21, 2500 Biel, Switzerland
| | - Marwin Philips
- Bern University of Applied Sciences, Quellgasse 21, 2500 Biel, Switzerland
| | - Carlo Largiadèr
- Department of Clinical Chemistry at the Bern University Hospital, Bern, Switzerland
| | - Murat Sariyar
- Bern University of Applied Sciences, Quellgasse 21, 2500 Biel, Switzerland
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13
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Peruzzi E, Roncato R, De Mattia E, Bignucolo A, Swen JJ, Guchelaar HJ, Toffoli G, Cecchin E. Implementation of pre-emptive testing of a pharmacogenomic panel in clinical practice: Where do we stand? Br J Clin Pharmacol 2023. [PMID: 37926674 DOI: 10.1111/bcp.15956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 10/19/2023] [Accepted: 10/20/2023] [Indexed: 11/07/2023] Open
Abstract
Adverse drug reactions (ADRs) account for a large proportion of hospitalizations among adults and are more common in multimorbid patients, worsening clinical outcomes and burdening healthcare resources. Over the past decade, pharmacogenomics has been developed as a practical tool for optimizing treatment outcomes by mitigating the risk of ADRs. Some single-gene reactive tests are already used in clinical practice, including the DPYD test for fluoropyrimidines, which demonstrates how integrating pharmacogenomic data into routine care can improve patient safety in a cost-effective manner. The evolution from reactive single-gene testing to comprehensive pre-emptive genotyping panels holds great potential for refining drug prescribing practices. Several implementation projects have been conducted to test the feasibility of applying different genetic panels in clinical practice. Recently, the results of a large prospective randomized trial in Europe (the PREPARE study by Ubiquitous Pharmacogenomics consortium) have provided the first evidence that prospective application of a pre-emptive pharmacogenomic test panel in clinical practice, in seven European healthcare systems, is feasible and yielded a 30% reduction in the risk of developing clinically relevant toxicities. Nevertheless, some important questions remain unanswered and will hopefully be addressed by future dedicated studies. These issues include the cost-effectiveness of applying a pre-emptive genotyping panel, the role of multiple co-medications, the transferability of currently tested pharmacogenetic guidelines among patients of non-European origin and the impact of rare pharmacogenetic variants that are not detected by currently used genotyping approaches.
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Affiliation(s)
- Elena Peruzzi
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano, Istituti di Ricovero e Cura a Carattere Scientifico, Aviano, Italy
| | - Rossana Roncato
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano, Istituti di Ricovero e Cura a Carattere Scientifico, Aviano, Italy
- Department of Medicine, University of Udine, Udine, Italy
| | - Elena De Mattia
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano, Istituti di Ricovero e Cura a Carattere Scientifico, Aviano, Italy
| | - Alessia Bignucolo
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano, Istituti di Ricovero e Cura a Carattere Scientifico, Aviano, Italy
| | - Jesse J Swen
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - Henk-Jan Guchelaar
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - Giuseppe Toffoli
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano, Istituti di Ricovero e Cura a Carattere Scientifico, Aviano, Italy
| | - Erika Cecchin
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano, Istituti di Ricovero e Cura a Carattere Scientifico, Aviano, Italy
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14
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Kanji CR, Mbavha BT, Masimirembwa C, Thelingwani RS. Analytical validation of GenoPharm a clinical genotyping open array panel of 46 pharmacogenes inclusive of variants unique to people of African ancestry. PLoS One 2023; 18:e0292131. [PMID: 37788265 PMCID: PMC10547200 DOI: 10.1371/journal.pone.0292131] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 09/13/2023] [Indexed: 10/05/2023] Open
Abstract
Pharmacogenomic testing may be used to improve treatment outcomes and reduce the frequency of adverse drug reactions (ADRs). Population specific, targeted pharmacogenetics (PGx) panel-based testing methods enable sensitive, accurate and economical implementation of precision medicine. We evaluated the analytical performance of the GenoPharm® custom open array platform which evaluates 120 SNPs across 46 pharmacogenes. Using commercially available reference samples (Coriell Biorepository) and in-house extracted DNA, we assessed accuracy, precision, and linearity of GenoPharm®. We then used GenoPharm® on 218 samples from two Southern African black populations and determined allele and genotype frequencies for selected actionable variants. Across all assays, the GenoPharm® panel demonstrated 99.5% concordance with the Coriell reference samples, with 98.9% reproducibility. We observed high frequencies of key genetic variants in people of African ancestry: CYP2B6*6 (0.35), CYP2C9*8, *11 (0.13, 0.03), CYP2D6*17 (0.21) and *29 (0.11). GenoPharm® open array is therefore an accurate, reproducible and sensitive test that can be used for clinical pharmacogenetic testing and is inclusive of variants specific to the people of African ancestry.
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Affiliation(s)
- Comfort Ropafadzo Kanji
- Department of Genomic Medicine, African Institute of Biomedical Science and Technology (AiBST), Beatrice, Zimbabwe
- Department of Clinical Pharmacology, University of Zimbabwe (UZ), Harare, Zimbabwe
| | - Bianza Tinotenda Mbavha
- Department of Genomic Medicine, African Institute of Biomedical Science and Technology (AiBST), Beatrice, Zimbabwe
| | - Collen Masimirembwa
- Department of Genomic Medicine, African Institute of Biomedical Science and Technology (AiBST), Beatrice, Zimbabwe
| | - Roslyn Stella Thelingwani
- Department of Genomic Medicine, African Institute of Biomedical Science and Technology (AiBST), Beatrice, Zimbabwe
- CradleOmics, Harare, Zimbabwe
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15
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Tuv SS, Spigset O, Jensen E, Vethe NT, Nordal K. [New tool for interpreting pharmacogenetic analyses]. TIDSSKRIFT FOR DEN NORSKE LEGEFORENING 2023; 143:23-0496. [PMID: 37753760 DOI: 10.4045/tidsskr.23.0496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/28/2023] Open
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16
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Samarasinghe SR, Hoy W, Jadhao S, McMorran BJ, Guchelaar HJ, Nagaraj SH. The pharmacogenomic landscape of an Indigenous Australian population. Front Pharmacol 2023; 14:1180640. [PMID: 37284308 PMCID: PMC10241071 DOI: 10.3389/fphar.2023.1180640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 04/07/2023] [Indexed: 06/08/2023] Open
Abstract
Background: Population genomic studies of individuals of Indigenous ancestry have been extremely limited comprising <0.5% of participants in international genetic databases and genome-wide association studies, contributing to a "genomic gap" that limits their access to personalised medicine. While Indigenous Australians face a high burden of chronic disease and associated medication exposure, corresponding genomic and drug safety datasets are sorely lacking. Methods: To address this, we conducted a pharmacogenomic study of almost 500 individuals from a founder Indigenous Tiwi population. Whole genome sequencing was performed using short-read Illumina Novaseq6000 technology. We characterised the pharmacogenomics (PGx) landscape of this population by analysing sequencing results and associated pharmacological treatment data. Results: We observed that every individual in the cohort carry at least one actionable genotype and 77% of them carry at least three clinically actionable genotypes across 19 pharmacogenes. Overall, 41% of the Tiwi cohort were predicted to exhibit impaired CYP2D6 metabolism, with this frequency being much higher than that for other global populations. Over half of the population predicted an impaired CYP2C9, CYP2C19, and CYP2B6 metabolism with implications for the processing of commonly used analgesics, statins, anticoagulants, antiretrovirals, antidepressants, and antipsychotics. Moreover, we identified 31 potentially actionable novel variants within Very Important Pharmacogenes (VIPs), five of which were common among the Tiwi. We further detected important clinical implications for the drugs involved with cancer pharmacogenomics such as thiopurines and tamoxifen, immunosuppressants like tacrolimus and certain antivirals used in the hepatitis C treatment due to potential differences in their metabolic processing. Conclusion: The pharmacogenomic profiles generated in our study demonstrate the utility of pre-emptive PGx testing and have the potential to help guide the development and application of precision therapeutic strategies tailored to Tiwi Indigenous patients. Our research provides valuable insights on pre-emptive PGx testing and the feasibility of its use in ancestrally diverse populations, emphasizing the need for increased diversity and inclusivity in PGx investigations.
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Affiliation(s)
| | - Wendy Hoy
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Sudhir Jadhao
- Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - Brendan J McMorran
- John Curtin School of Medical Research, College of Health and Medicine, Australian National University, Canberra, ACT, Australia
| | - Henk-Jan Guchelaar
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, Netherlands
| | - Shivashankar H Nagaraj
- Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, QLD, Australia
- Translational Research Institute, Queensland University of Technology, Brisbane, QLD, Australia
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17
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Salas-Hernández A, Galleguillos M, Carrasco M, López-Cortés A, Redal MA, Fonseca-Mendoza D, Esperón P, González-Martínez F, Lares-Asseff I, Lazarowski A, Loera-Castañeda V, Remírez D, Martínez MF, Vargas R, Rios-Santos F, Macho A, Cayún JP, Perez GR, Gutierrez C, Cerpa LC, Leiva T, Calfunao S, Xajil L, Sandoval C, Suárez M, Gonzalez A, Echeverría-Garcés G, Sullón-Dextre L, Cordero-García E, Morales AR, Avendaño A, Sánchez E, Bastone LC, Lara C, Zuluaga-Arias P, Soler AM, Da Luz J, Burgueño-Rodríguez G, Vital M, Reyes-Reyes E, Huaccha A, Ariza YV, Tzul N, Rendón AL, Serrano R, Acosta L, Motta-Pardo A, Beltrán-Angarita L, Brand E, Jiménez MA, Hidalgo-Lozada GM, Romero-Prado MMJ, Escobar-Castro K, Umaña-Rivas M, Vivas JD, Lagos P, Martínez YB, Quesada S, Calfio C, Arias ML, Lavanderos MA, Cáceres DD, Salazar-Granara A, Varela NM, Quiñones LA. An updated examination of the perception of barriers for pharmacogenomics implementation and the usefulness of drug/gene pairs in Latin America and the Caribbean. Front Pharmacol 2023; 14:1175737. [PMID: 37251329 PMCID: PMC10213898 DOI: 10.3389/fphar.2023.1175737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 04/21/2023] [Indexed: 05/31/2023] Open
Abstract
Pharmacogenomics (PGx) is considered an emergent field in developing countries. Research on PGx in the Latin American and the Caribbean (LAC) region remains scarce, with limited information in some populations. Thus, extrapolations are complicated, especially in mixed populations. In this paper, we reviewed and analyzed pharmacogenomic knowledge among the LAC scientific and clinical community and examined barriers to clinical application. We performed a search for publications and clinical trials in the field worldwide and evaluated the contribution of LAC. Next, we conducted a regional structured survey that evaluated a list of 14 potential barriers to the clinical implementation of biomarkers based on their importance. In addition, a paired list of 54 genes/drugs was analyzed to determine an association between biomarkers and response to genomic medicine. This survey was compared to a previous survey performed in 2014 to assess progress in the region. The search results indicated that Latin American and Caribbean countries have contributed 3.44% of the total publications and 2.45% of the PGx-related clinical trials worldwide thus far. A total of 106 professionals from 17 countries answered the survey. Six major groups of barriers were identified. Despite the region's continuous efforts in the last decade, the primary barrier to PGx implementation in LAC remains the same, the "need for guidelines, processes, and protocols for the clinical application of pharmacogenetics/pharmacogenomics". Cost-effectiveness issues are considered critical factors in the region. Items related to the reluctance of clinicians are currently less relevant. Based on the survey results, the highest ranked (96%-99%) gene/drug pairs perceived as important were CYP2D6/tamoxifen, CYP3A5/tacrolimus, CYP2D6/opioids, DPYD/fluoropyrimidines, TMPT/thiopurines, CYP2D6/tricyclic antidepressants, CYP2C19/tricyclic antidepressants, NUDT15/thiopurines, CYP2B6/efavirenz, and CYP2C19/clopidogrel. In conclusion, although the global contribution of LAC countries remains low in the PGx field, a relevant improvement has been observed in the region. The perception of the usefulness of PGx tests in biomedical community has drastically changed, raising awareness among physicians, which suggests a promising future in the clinical applications of PGx in LAC.
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Affiliation(s)
- Aimeé Salas-Hernández
- Department of Pharmacology, Toxicology and Pharmaco-Dependence, Faculty of Pharmacy, University of Costa Rica, San Jose, Costa Rica
| | - Macarena Galleguillos
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
| | - Matías Carrasco
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
| | - Andrés López-Cortés
- Cancer Research Group (CRG), Faculty of Medicine, Universidad de Las Américas, Quito, Ecuador
| | - María Ana Redal
- Molecular Diagnostic Laboratory, Genetics Division, Faculty of Medicine, Hospital de Clínicas José de San Martín, University of Buenos Aires, Buenos Aires, Argentina
| | - Dora Fonseca-Mendoza
- Universidad del Rosario, School of Medicine and Health Sciences, Center for Research in Genetics and Genomics (CIGGUR), Institute of Translational Medicine (IMT), Bogotá, Colombia
| | - Patricia Esperón
- Molecular Genetic Unit, School of Chemistry, Universidad de la República, General Flores, CP 1800 2124, Montevideo, Uruguay
| | - Farith González-Martínez
- Toxicology and Public Health Research Laboratory, Department of Research, Faculty of Dentistry, University of Cartagena, Cartagena, Colombia
| | - Ismael Lares-Asseff
- Academy of Genomics and Laboratory of Pharmacogenomics and Molecular Biomedicine, Instituto Politécnico Nacional, CIIDIR-Unidad Durango, Durango, Mexico
| | - Alberto Lazarowski
- Instituto de Fisiopatología y Bioquímica Clínica (INFIBIOC), Facultad de Farmacia y Bioquímica, Universidad de Buenos Aires- Argentina, Buenos Aires, Argentina
| | - Verónica Loera-Castañeda
- Academy of Genomics and Laboratory of Pharmacogenomics and Molecular Biomedicine, Instituto Politécnico Nacional, CIIDIR-Unidad Durango, Durango, Mexico
| | | | - Matías F. Martínez
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
- Department of Pharmaceutical Sciences and Technology, Faculty of Chemical and Pharmaceutical Sciences, University of Chile, Santiago, Chile
| | - Rodrigo Vargas
- Department of Molecular Biology, Galileo University, Guatemala City, Guatemala
| | - Fabricio Rios-Santos
- Department of Health. Faculty of Medicine, Federal University of Mato Grosso (UFMT), Cuibá, Brazil
| | - Antonio Macho
- Morphology and Applied Immunology Research Center (NuPMIA), University of Brasilia (UnB), Brasília, Brazil
| | - Juan P. Cayún
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
| | - Germán R. Perez
- Department of Microbiology, Faculty of Biochemical and Pharmaceutical Sciences. National University of Rosario, Rosario, Argentina
| | - Carolina Gutierrez
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
| | - Leslie C. Cerpa
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
| | - Tamara Leiva
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
| | - Susan Calfunao
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
- Laboratory Pathological Anatomy, Hospital Luis Calvo Mackenna, Santiago, Chile
| | - Lesly Xajil
- Department of Research in Pharmacogenomics, Faculty of Chemical Sciences and Pharmacy, University of San Carlos de Guatemala, Guatemala, Guatemala
| | - Christopher Sandoval
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
- Clinical Laboratory Blood Biochemistry and Immunoassay Section, Hospital Clínico Félix Bulnes Cerda, Santiago, Chile
| | - Marcelo Suárez
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
- Pharmacy Service, Hospital UC-Christus, Santiago, Chile
| | | | | | | | - Eugenia Cordero-García
- Department of Pharmacology, Toxicology and Pharmaco-Dependence, Faculty of Pharmacy, University of Costa Rica, San Jose, Costa Rica
| | - Alexis R. Morales
- Department of Toxicology and Pharmacology, Faculty of Pharmacy and Bioanalisis, University of Los Andes, Merida, Venezuela
| | - Andrea Avendaño
- Department of Pediatrics, Medical Genetics Unity, Faculty of Medicine, University of Los Andes, Mérida, Venezuela
| | | | - Laura C. Bastone
- Laboratorio de Medicina Genómica, Gammalab, Grupo Gamma, Rosario, Argentina
| | - Cesar Lara
- Betesda La Alternativa Natural, San José, Costa Rica
| | | | - Ana María Soler
- Laboratorio de Genética Molecular Humana, Departamento de Ciencias Biológicas, Universidad de La República, Montevideo, Uruguay
| | - Julio Da Luz
- Laboratorio de Genética Molecular Humana, Departamento de Ciencias Biológicas, Universidad de La República, Montevideo, Uruguay
| | - Gabriela Burgueño-Rodríguez
- Laboratorio de Genética Molecular Humana, Departamento de Ciencias Biológicas, Universidad de La República, Montevideo, Uruguay
| | - Marcelo Vital
- Molecular Genetic Unit, School of Chemistry, Universidad de la República, General Flores 2124, Montevideo, Uruguay
| | - Elizabeth Reyes-Reyes
- Clinical Experimental Pharmacology Section, Teaching and Research Department, Institute of Oncology and Radiobiology, Havana, Cuba
| | | | - Yeimy V. Ariza
- Pharmaceutical Chemistry Program, El Bosque University, Bogotá, Colombia
| | - Naomi Tzul
- Drug Inspectorate Unit, Ministry of Health and Wellness, Belmopan, Belize
| | - Ana L. Rendón
- Department of Pharmaceutical Technology, National Autonomous University of Honduras, Tegucigalpa, Honduras
| | | | - Larissa Acosta
- Faculty of Biology, Chemistry and Pharmacy, Galileo University, Guatemala, Guatemala
| | - Angelo Motta-Pardo
- GENOBIDC, Faculty of Pharmacy and Biochemistry, Universidad Nacional Mayor de San Marcos (UNMSM), CIGBM, Faculty of Medicine, Universidad de San Martin de Porres (USMP), Lima, Peru
| | - Leonardo Beltrán-Angarita
- Faculty of Heath Sciences, Central Unit of Valle del Cauca, Tuluá, Colombia
- Chemistry School, Universidad Tecnológica de Pereira, Pereira, Colombia
| | - Erika Brand
- Postgraduate Department, Master’s Degree in Immunology, Universidad Cayetano Heredia, Lima, Perú
| | | | | | - Marina M. J. Romero-Prado
- Department of Physiology, Health Sciences University Center, University of Guadalajara, Guadalajara, Jalisco, Mexico
| | - Karla Escobar-Castro
- Laboratory of Histocompatibility and Immunogenetics, Department of Nephrology and Transplant, Hospital General San Juan de Dios, Guatemala, Guatemala
| | - Mariel Umaña-Rivas
- Department of Tropical Medicine, Faculty of Medicine, University of Brasília, Brasília, Brazil
| | - Juan D. Vivas
- Department of Clinical Pharmacology, Faculty of Medicine, University of La Sabana, Chía, Colombia
| | - Paola Lagos
- Recombinant Biopharmaceutical Laboratory, Department of Pharmacology, Faculty of Biological Sciences, University of Concepción, Concepción, Chile
| | - Yineth Ballén Martínez
- Medical Specialist in Epidemiology Clinical Pharmacology Teacher; Medical Scientific and Pharmacovigilance Advisor in the Pharmaceutical Industry, Bogotá, Colombia
| | - Sharleth Quesada
- Faculty of Pharmacy, University of Costa Rica, San Jose, Costa Rica
| | - Camila Calfio
- International Center for Biomedicine ICC, Santiago, Chile
| | - Maria L. Arias
- Tropical Diseases Research Center and Microbiology Faculty, University of Costa Rica, San José, Costa Rica
| | - María A. Lavanderos
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
| | - Dante D. Cáceres
- Environmental Health Programme, School of Public Health, Faculty of Medicine, University of Chile, Santiago, Chile
| | - Alberto Salazar-Granara
- Universidad de San Martín de Porres, Facultad de Medicina Humana, Centro de Investigación de Medicina Tradicional y Farmacología, Lima, Perú
| | - Nelson M. Varela
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
| | - Luis A. Quiñones
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
- Department of Pharmaceutical Sciences and Technology, Faculty of Chemical and Pharmaceutical Sciences, University of Chile, Santiago, Chile
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18
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Huang Q, Liao Y, Yu T, Lei W, Liang H, Wen J, Liu Q, Chen Y, Huang K, Jing L, Huang X, Liu Y, Yu X, Su K, Liu T, Yang L, Huang M. A retrospective analysis of preemptive pharmacogenomic testing in 22,918 individuals from China. J Clin Lab Anal 2023; 37:e24855. [PMID: 36916827 PMCID: PMC10098050 DOI: 10.1002/jcla.24855] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 01/11/2023] [Accepted: 02/13/2023] [Indexed: 03/16/2023] Open
Abstract
BACKGROUND Pharmacogenomics (PGx) examines the influence of genetic variation on drug responses. With more and more Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines published, PGx is gradually shifting from the reactive testing of single gene toward the preemptive testing of multiple genes. But the profile of PGx genes, especially for the intra-country diversity, is not well understood in China. METHODS We retrospectively collected preemptive PGx testing data of 22,918 participants from 20 provinces of China, analyzed frequencies of alleles, genotypes and phenotypes of pharmacogenes, predicted drug responses for each participant, and performed comparisons between different provinces. RESULTS AND CONCLUSION After analyzing 15 pharmacogenes from CPIC guidelines of 31 drugs, we found that 99.97% of individuals may have an atypical response to at least one drug; the participants carry actionable genotypes leading to atypical dosage recommendation for a median of eight drugs. Over 99% of the participants were recommended a decreased warfarin dose based on genetic factors. There were 20 drugs with high-risk ratios from 0.18% to 58.25%, in which clopidogrel showed the highest high-risk ratio. In addition, the high-risk ratio of rasburicase in GUANGDONG (risk ratio (RR) = 13.17, 95%CI:4.06-33.22, p < 0.001) and GUANGXI (RR = 23.44, 95%CI:8.83-52.85, p < 0.001) were significantly higher than that in all provinces. Furthermore, the diversity we observed among 20 provinces suggests that preemptive PGx testing in different geographical regions in China may need to pay more attention to specific genes. These results emphasize the importance of preemptive PGx testing and provide essential evidence for promoting clinical implementation in China.
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Affiliation(s)
- Quanfei Huang
- Institute of Clinical Pharmacology, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, China
| | - Yuwei Liao
- Precision Medical Lab Center, People's Hospital of Yangjiang, Yangjiang, China
| | - Tao Yu
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Wei Lei
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Hongfeng Liang
- Precision Medical Lab Center, People's Hospital of Yangjiang, Yangjiang, China
| | - Jianxin Wen
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Qing Liu
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Yu Chen
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Kaisheng Huang
- CapitalBio Technology Co. Ltd., Beijing, China.,Guangdong CapitalBio Medical Laboratory, Dongguan, China
| | - Lifang Jing
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Xiaoyan Huang
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Yuanru Liu
- CapitalBio Technology Co. Ltd., Beijing, China.,Guangdong CapitalBio Medical Laboratory, Dongguan, China
| | - Xiaokang Yu
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Kaichan Su
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Tengfei Liu
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Liye Yang
- Precision Medical Lab Center, People's Hospital of Yangjiang, Yangjiang, China
| | - Min Huang
- Institute of Clinical Pharmacology, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, China
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19
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Mostaid MS, Aziz MA, Maisha JA, Islam MS, Maruf AA. A review of pharmacogenetic studies in the Bangladeshi population. Drug Metab Pers Ther 2023:dmdi-2022-0194. [PMID: 36854045 DOI: 10.1515/dmpt-2022-0194] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Accepted: 01/25/2023] [Indexed: 03/02/2023]
Abstract
Pharmacogenetics (PGx)-guided prescribing is an evidence-based precision medicine strategy. Although the past two decades have reported significant advancements in both the quality and quantity of PGx research studies, they are seldom done in developing countries like Bangladesh. This review identified and summarized PGx studies conducted in the Bangladeshi population by searching PubMed and Google Scholar. Additionally, a quality evaluation of the identified studies was also carried out. Eleven PGx studies were identified that looked at the effects of genetic variants on blood thinners (CYP2C9, VKORC1, and ITGB3), cancer drugs (TPMT, MTHFR, DPYD, ERCC1, GSTP1, XPC, XRCC1, TP53, XPD, and ABCC4), statins (COQ2, CYP2D6, and CYP3A5), and prednisolone (ABCB1, CYP3A5, and NR3C1) in the Bangladeshi population. Most studies were of low to moderate quality. Although the identified studies demonstrated the potential for PGx testing, the limited PGx literature in the Bangladeshi population poses a significant challenge in the widespread implementation of PGx testing in Bangladesh.
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Affiliation(s)
- Md Shaki Mostaid
- Department of Pharmaceutical Sciences, North South University, Dhaka, Bangladesh
| | - Md Abdul Aziz
- Laboratory of Pharmacogenomics and Molecular Biology, Department of Pharmacy, Noakhali Science and Technology University, Noakhali, Bangladesh
| | - Jeba Atkia Maisha
- Department of Mathematics and Natural Sciences, Brac University, Dhaka, Bangladesh
| | - Mohammad Safiqul Islam
- Laboratory of Pharmacogenomics and Molecular Biology, Department of Pharmacy, Noakhali Science and Technology University, Noakhali, Bangladesh
| | - Abdullah Al Maruf
- The Mathison Centre for Mental Health Research & Education, Cumming School of Medicine, University of Calgary, Calgary, Canada
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20
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Targeted next-generation sequencing of genes involved in Warfarin Pharmacodynamics and pharmacokinetics pathways using the Saudi Warfarin Pharmacogenetic study (SWAP). THE PHARMACOGENOMICS JOURNAL 2023:10.1038/s41397-023-00300-3. [PMID: 36739459 DOI: 10.1038/s41397-023-00300-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 01/15/2023] [Accepted: 01/26/2023] [Indexed: 02/06/2023]
Abstract
BACKGROUND Warfarin is an oral anticoagulant commonly used for treatment and prophylaxis against thromboembolic events. Warfarins's narrow therapeutic index window is one of the main challenges in clinical practice; thus, it requires frequent monitoring and dose adjustment to maintain patients' therapeutic range. Warfarin dose variation and response are attributed to several inter-and intra-individuals factors, including genetic variants in enzymes involved in warfarin pharmacokinetics (PK) and pharmacodynamics (PD) pathways. Thus, we aim to utilize the next-generation sequencing (NGS) approach to identify rare and common genetic variants that might be associated with warfarin responsiveness. METHOD AND RESULTS A predesigned NGS panel that included 16 genes involved in Warfarin PK/PD pathways was used to sequence 786 patients from the Saudi Warfarin Pharmacogenetic Cohort (SWAP). Identified variants were annotated using several annotation tools to identify the pathogenicity and allele frequencies of these variants. We conducted variants-level association tests with warfarin dose. We identified 710 variants within the sequenced genes; 19% were novel variants, with the vast majority being scarce variants. The genetic association tests showed that VKORC1 (rs9923231, and rs61742245), CYP2C9 (rs98332238, rs9332172, rs1057910, rs9332230, rs1799853, rs1057911, and rs9332119), CYP2C19 (rs28399511, and rs3758581), and CYP2C8 (rs11572080 and rs10509681) were significantly associated with warfarin weekly dose. Our model included genetics, and non-genetic factors explained 40.1% of warfarin dose variation. CONCLUSION The study identifies novel variants associated with warfarin dose in the Saudi population. These variants are more likely to be population-specific variants, suggesting that population-specific studies should be conducted before adopting a universal warfarin genotype-guided dosing algorithm.
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21
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Application of Pharmacogenetics for the Use of Antiplatelet and Anticoagulant Drugs. CURRENT CARDIOVASCULAR RISK REPORTS 2023. [DOI: 10.1007/s12170-022-00713-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
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22
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Shivaram S, Gao H, Qin S, Liu D, Weinshilboum RM, Wang L. Cytochrome P450 Transcriptional Regulation by Testis-Specific Y-Encoded-Like Protein: Identification of Novel Upstream Transcription Factors. Drug Metab Dispos 2023; 51:1-7. [PMID: 36153008 PMCID: PMC9832376 DOI: 10.1124/dmd.122.000945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 07/05/2022] [Accepted: 07/05/2022] [Indexed: 01/14/2023] Open
Abstract
Cytochrome P450s (CYPs) display significant inter-individual variation in expression, much of which remains unexplained by known CYP single-nucleotide polymorphisms (SNPs). Testis-specific Y-encoded-like proteins (TSPYLs) are transcriptional regulators for several drug-metabolizing CYPs including CYP3A4 However, transcription factors (TFs) that might influence CYP expression through an effect on TSPYL expression are unknown. Therefore, we studied regulators of TSPYL expression in hepatic cell lines and their possible SNP-dependent variation. Specifically, we identified candidate TFs that might influence TSPYL expression using the ENCODE ChIPseq database. Subsequently, the expression of TSPYL1/2/4 as well as that of selected CYP targets for TSPYL regulation were assayed in hepatic cell lines before and after knockdown of TFs that might influence CYP expression through TSPYL-dependent mechanisms. Those results were confirmed by studies of TF binding to TSPYL1/2/4 gene promoter regions. In hepatic cell lines, knockdown of the REST and ZBTB7A TFs resulted in decreased TSPYL1 and TSPYL4 expression and increased CYP3A4 expression, changes reversed by TSPYL1/4 overexpression. Potential binding sites for REST and ZBTB7A on the promoters of TSPYL1 and TSPYL4 were confirmed by chromatin immunoprecipitation. Finally, common SNP variants in upstream binding sites on the TSPYL1/4 promoters were identified and luciferase reporter constructs confirmed SNP-dependent modulation of TSPYL1/4 gene transcription. In summary, we identified REST and ZBTB7A as regulators of the expression of TSPYL genes which themselves can contribute to regulation of CYP expression and-potentially-of drug metabolism. SNP-dependent modulation of TSPYL transcription may contribute to individual variation in both CYP expression and-downstream-drug response phenotypes. SIGNIFICANCE STATEMENT: Testis-specific Y-encoded-like proteins (TSPYLs) are transcriptional regulators of cytochrome P450 (CYP) gene expression. Here, we report that variation in TSPYL expression as a result of the effects of genetically regulated TSPYL transcription factors is an additional factor that could result in downstream variation in CYP expression and potentially, as a result, variation in drug biotransformation.
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Affiliation(s)
- Suganti Shivaram
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Therapeutics, Mayo Clinic, Rochester, Minnesota
| | - Huanyao Gao
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Therapeutics, Mayo Clinic, Rochester, Minnesota
| | - Sisi Qin
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Therapeutics, Mayo Clinic, Rochester, Minnesota
| | - Duan Liu
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Therapeutics, Mayo Clinic, Rochester, Minnesota
| | - Richard M Weinshilboum
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Therapeutics, Mayo Clinic, Rochester, Minnesota
| | - Liewei Wang
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Therapeutics, Mayo Clinic, Rochester, Minnesota
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23
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Bai H, Zhang X, Bush WS. Pharmacogenomic and Statistical Analysis. Methods Mol Biol 2023; 2629:305-330. [PMID: 36929083 DOI: 10.1007/978-1-0716-2986-4_14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
Genetic variants can alter response to drugs and other therapeutic interventions. The study of this phenomenon, called pharmacogenomics, is similar in many ways to other types of genetic studies but has distinct methodological and statistical considerations. Genetic variants involved in the processing of exogenous compounds exhibit great diversity and complexity, and the phenotypes studied in pharmacogenomics are also more complex than typical genetic studies. In this chapter, we review basic concepts in pharmacogenomic study designs, data generation techniques, statistical analysis approaches, and commonly used methods and briefly discuss the ultimate translation of findings to clinical care.
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Affiliation(s)
- Haimeng Bai
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
- Department of Nutrition, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Xueyi Zhang
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
| | - William S Bush
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA.
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24
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van der Wouden CH, Guchelaar HJ, Swen JJ. Precision Medicine Using Pharmacogenomic Panel-Testing: Current Status and Future Perspectives. Clin Lab Med 2022; 42:587-602. [PMID: 36368784 DOI: 10.1016/j.cll.2022.09.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Cathelijne H van der Wouden
- Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Albinusdreef 2, Leiden 2333ZA, The Netherlands; Leiden Network for Personalised Therapeutics, Leiden, The Netherlands
| | - Henk-Jan Guchelaar
- Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Albinusdreef 2, Leiden 2333ZA, The Netherlands; Leiden Network for Personalised Therapeutics, Leiden, The Netherlands
| | - Jesse J Swen
- Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Albinusdreef 2, Leiden 2333ZA, The Netherlands; Leiden Network for Personalised Therapeutics, Leiden, The Netherlands.
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25
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Zhou Y, Lauschke VM. The genetic landscape of major drug metabolizing cytochrome P450 genes-an updated analysis of population-scale sequencing data. THE PHARMACOGENOMICS JOURNAL 2022; 22:284-293. [PMID: 36068297 PMCID: PMC9674520 DOI: 10.1038/s41397-022-00288-2] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 08/05/2022] [Accepted: 08/19/2022] [Indexed: 06/15/2023]
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.
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Affiliation(s)
- Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77, Stockholm, Sweden
| | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77, Stockholm, Sweden.
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.
- University of Tuebingen, Tuebingen, Germany.
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26
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Morris SA, Alsaidi AT, Verbyla A, Cruz A, Macfarlane C, Bauer J, Patel JN. Cost Effectiveness of Pharmacogenetic Testing for Drugs with Clinical Pharmacogenetics Implementation Consortium (CPIC) Guidelines: A Systematic Review. Clin Pharmacol Ther 2022; 112:1318-1328. [PMID: 36149409 PMCID: PMC9828439 DOI: 10.1002/cpt.2754] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 09/17/2022] [Indexed: 01/31/2023]
Abstract
The objective of this study was to evaluate the evidence on cost-effectiveness of pharmacogenetic (PGx)-guided treatment for drugs with Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. A systematic review was conducted using multiple biomedical literature databases from inception to June 2021. Full articles comparing PGx-guided with nonguided treatment were included for data extraction. Quality of Health Economic Studies (QHES) was used to assess robustness of each study (0-100). Data are reported using descriptive statistics. Of 108 studies evaluating 39 drugs, 77 (71%) showed PGx testing was cost-effective (CE) (N = 48) or cost-saving (CS) (N = 29); 21 (20%) were not CE; 10 (9%) were uncertain. Clopidogrel had the most articles (N = 23), of which 22 demonstrated CE or CS, followed by warfarin (N = 16), of which 7 demonstrated CE or CS. Of 26 studies evaluating human leukocyte antigen (HLA) testing for abacavir (N = 8), allopurinol (N = 10), or carbamazepine/phenytoin (N = 8), 15 demonstrated CE or CS. Nine of 11 antidepressant articles demonstrated CE or CS. The median QHES score reflected high-quality studies (91; range 48-100). Most studies evaluating cost-effectiveness favored PGx testing. Limited data exist on cost-effectiveness of preemptive and multigene testing across disease states.
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Affiliation(s)
- Sarah A. Morris
- Department of Cancer Pharmacology and PharmacogenomicsLevine Cancer Institute, Atrium HealthCharlotteNorth CarolinaUSA
| | | | - Allison Verbyla
- Health Economics and Outcomes Research, Department of BiostatisticsLevine Cancer Institute, Atrium HealthCharlotteNorth CarolinaUSA
| | - Adilen Cruz
- Health Economics and Outcomes Research, Department of BiostatisticsLevine Cancer Institute, Atrium HealthCharlotteNorth CarolinaUSA
| | | | - Joseph Bauer
- Health Economics and Outcomes Research, Department of BiostatisticsLevine Cancer Institute, Atrium HealthCharlotteNorth CarolinaUSA
| | - Jai N. Patel
- Department of Cancer Pharmacology and PharmacogenomicsLevine Cancer Institute, Atrium HealthCharlotteNorth CarolinaUSA
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27
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Fragala MS, Shaman JA, Lorenz RA, Goldberg SE. Role of Pharmacogenomics in Comprehensive Medication Management: Considerations for Employers. Popul Health Manag 2022; 25:753-762. [PMID: 36301527 DOI: 10.1089/pop.2022.0075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Rising prescription costs, poor medication adherence, and safety issues pose persistent challenges to employer-sponsored health care plans and their beneficiaries. Comprehensive medication management (CMM), a patient-centered approach to medication optimization, enriched by pharmacogenomics (PGx), has been shown to improve the efficacy and safety of pharmaceutical regimens. This has contributed to improved health care outcomes, reduced costs of treatments, better adherence, shorter durations of treatment, and fewer adverse effects from drug therapy. Despite compelling clinical and economic evidence to justify the application of CMM guided by PGx, implementation in clinical settings remains sparse; notable barriers include limited physician adoption and health insurance coverage. Ultimately, these challenges may be overcome through comprehensive programs that include clinical decision support systems and education through employer-sponsored population health management channels to the benefit of the employees, employers, health care providers, and health care systems. This article discusses benefits, considerations, and barriers of scalable PGx-enriched CMM programs in the context of self-insured employers.
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28
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Verma SS, Keat K, Li B, Hoffecker G, Risman M, Sangkuhl K, Whirl-Carrillo M, Dudek S, Verma A, Klein TE, Ritchie MD, Tuteja S. Evaluating the frequency and the impact of pharmacogenetic alleles in an ancestrally diverse Biobank population. J Transl Med 2022; 20:550. [PMID: 36443877 PMCID: PMC9703665 DOI: 10.1186/s12967-022-03745-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 10/30/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Pharmacogenomics (PGx) aims to utilize a patient's genetic data to enable safer and more effective prescribing of medications. The Clinical Pharmacogenetics Implementation Consortium (CPIC) provides guidelines with strong evidence for 24 genes that affect 72 medications. Despite strong evidence linking PGx alleles to drug response, there is a large gap in the implementation and return of actionable pharmacogenetic findings to patients in standard clinical practice. In this study, we evaluated opportunities for genetically guided medication prescribing in a diverse health system and determined the frequencies of actionable PGx alleles in an ancestrally diverse biobank population. METHODS A retrospective analysis of the Penn Medicine electronic health records (EHRs), which includes ~ 3.3 million patients between 2012 and 2020, provides a snapshot of the trends in prescriptions for drugs with genotype-based prescribing guidelines ('CPIC level A or B') in the Penn Medicine health system. The Penn Medicine BioBank (PMBB) consists of a diverse group of 43,359 participants whose EHRs are linked to genome-wide SNP array and whole exome sequencing (WES) data. We used the Pharmacogenomics Clinical Annotation Tool (PharmCAT), to annotate PGx alleles from PMBB variant call format (VCF) files and identify samples with actionable PGx alleles. RESULTS We identified ~ 316.000 unique patients that were prescribed at least 2 drugs with CPIC Level A or B guidelines. Genetic analysis in PMBB identified that 98.9% of participants carry one or more PGx actionable alleles where treatment modification would be recommended. After linking the genetic data with prescription data from the EHR, 14.2% of participants (n = 6157) were prescribed medications that could be impacted by their genotype (as indicated by their PharmCAT report). For example, 856 participants received clopidogrel who carried CYP2C19 reduced function alleles, placing them at increased risk for major adverse cardiovascular events. When we stratified by genetic ancestry, we found disparities in PGx allele frequencies and clinical burden. Clopidogrel users of Asian ancestry in PMBB had significantly higher rates of CYP2C19 actionable alleles than European ancestry users of clopidrogrel (p < 0.0001, OR = 3.68). CONCLUSIONS Clinically actionable PGx alleles are highly prevalent in our health system and many patients were prescribed medications that could be affected by PGx alleles. These results illustrate the potential utility of preemptive genotyping for tailoring of medications and implementation of PGx into routine clinical care.
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Affiliation(s)
- Shefali S. Verma
- grid.25879.310000 0004 1936 8972Department of Pathology & Laboratory Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA USA
| | - Karl Keat
- grid.25879.310000 0004 1936 8972Genomics & Computational Biology PhD Program, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA USA
| | - Binglan Li
- grid.168010.e0000000419368956Department of Biomedical Data Science, Stanford University, Stanford, CA USA
| | - Glenda Hoffecker
- grid.25879.310000 0004 1936 8972Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA USA
| | - Marjorie Risman
- grid.25879.310000 0004 1936 8972Department of Genetics and Institute for Biomedical Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA USA
| | | | - Katrin Sangkuhl
- grid.168010.e0000000419368956Department of Biomedical Data Science, Stanford University, Stanford, CA USA
| | - Michelle Whirl-Carrillo
- grid.168010.e0000000419368956Department of Biomedical Data Science, Stanford University, Stanford, CA USA
| | - Scott Dudek
- grid.25879.310000 0004 1936 8972Department of Genetics and Institute for Biomedical Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA USA
| | - Anurag Verma
- grid.25879.310000 0004 1936 8972Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA USA
| | - Teri E. Klein
- grid.168010.e0000000419368956Department of Biomedical Data Science, Stanford University, Stanford, CA USA ,grid.168010.e0000000419368956Department of Biomedical Data Science and Medicine (BMIR), Stanford University, Stanford, CA USA
| | - Marylyn D. Ritchie
- grid.25879.310000 0004 1936 8972Department of Genetics and Institute for Biomedical Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA USA
| | - Sony Tuteja
- grid.25879.310000 0004 1936 8972Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA USA
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29
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Brutnell TP, Wang X, Bao J. Integrating pharmacogenomics into clinical trials of hearing disorders. THE JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2022; 152:2828. [PMID: 36456290 PMCID: PMC9648993 DOI: 10.1121/10.0015092] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 09/26/2022] [Accepted: 10/20/2022] [Indexed: 06/17/2023]
Abstract
In 2019, the U.S. Food and Drug Administration issued guidance to increase the efficiency of drug development and support precision medicine, including tailoring treatments to those patients who will benefit based on genetic variation even in the absence of a documented mechanism of action. Although multiple advancements have been made in the field of pharmacogenetics (PGx) for other disease conditions, there are no approved PGx guidelines in the treatment of hearing disorders. In studies of noise-induced hearing loss (NIHL), some progress has been made in the last several years associating genomic loci with susceptibility to noise damage. However, the power of such studies is limited as the underlying physiological responses may vary considerably among the patient populations. Here, we have summarized previous animal studies to argue that NIHL subtyping is a promising strategy to increase the granularity of audiological assessments. By coupling this enhanced phenotyping capability with genetic association studies, we suggest that drug efficacy will be better predicted, increasing the likelihood of success in clinical trials when populations are stratified based on genetic variation or designed with multidrug combinations to reach a broader segment of individuals suffering or at risk from NIHL.
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Affiliation(s)
| | - Xinwen Wang
- Department of Pharmaceutical Sciences, Northeast Ohio Medical University, Rootstown, Ohio 44272, USA
| | - Jianxin Bao
- Gateway Biotechnology, St. Louis, Missouri 63132, USA
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30
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Raymond M, Critchlow E, Rice SM, Wodoslawsky S, Berger SI, Hegde M, Empey PE, Al-Kouatly HB. Fetal pharmacogenomics: A promising addition to complex neonatal care. Mol Genet Metab 2022; 137:140-145. [PMID: 36029725 DOI: 10.1016/j.ymgme.2022.08.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 08/06/2022] [Accepted: 08/07/2022] [Indexed: 12/20/2022]
Abstract
OBJECTIVE Pharmacogenomics (PGx) characterizes genetic variation in medication response. 85-95% of the population carries actionable PGx variants. No prior studies have demonstrated the application and feasibility of PGx in prenatal testing. We assessed parental desire for PGx findings from fetal exome sequencing (ES), evaluated PGx variants, and reviewed implications for medically complex neonates. METHODS A prospective cohort undergoing ES for nonimmune hydrops fetalis were offered PGx results as a secondary finding. Seven pharmacogenes with Level A evidence, defined by Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines, were tested and reported to patients and referring providers. Medication administration records were reviewed. RESULTS Most participants (36/40, 90%) desired PGx testing. 32/36 (89%) had potentially actionable PGx diplotypes in six genes: CYP2C19 (20/36, 56%), CYP2C9 (16/36, 44%), CYP2D6 (10/36, 28%), SLCO1B1 (13/36, 36%), TPMT (6/36, 17%), UGT1A1 (4/36, 11%). 12/13 (92%) live births had PGx variants. Neonatal chart review indicated that three medications with CPIC Level A evidence were administered to four neonates. None of the patients received a medication that aligned with an actionable pharmacogenetic variant as defined by Level A CPIC guidance. CONCLUSION Most participants opted to receive PGx results. 89% had actionable variants, consistent with population estimates. Obtaining fetal PGx data is feasible for medically complex neonates. Further studies are needed for broad clinical application of PGx in fetuses with major congenital abnormalities. Our study demonstrates the potential of PGx as useful preemptive clinical information that could be obtained at the time of fetal exome sequencing for other indications. CLINICALTRIALS gov Registration: NCT03911531.
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Affiliation(s)
- Megan Raymond
- Department of Obstetrics and Gynecology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Elizabeth Critchlow
- Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA, USA
| | - Stephanie M Rice
- Department of Obstetrics and Gynecology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Sascha Wodoslawsky
- Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA, USA
| | - Seth I Berger
- Center for Genetic Medicine Research at Children's National, Washington, DC, USA
| | | | - Philip E Empey
- Department of Pharmacy and Therapeutics, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Huda B Al-Kouatly
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Thomas Jefferson University, Philadelphia, PA, USA.
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Abstract
Pharmacogenomics is increasingly important to guide objective, safe, and effective individualised prescribing. Personalised prescribing has revolutionised treatments in the past decade, allowing clinicians to maximise drug efficacy and minimise adverse effects based on a person’s genetic profile. Opioids, the gold standard for cancer pain relief, are among the commonest medications prescribed in palliative care practice. This narrative review examines the literature surrounding opioid pharmacogenomics and its applicability to the palliative care cancer population. There is currently limited intersection between the fields of palliative care and pharmacogenomics, but growing evidence presents a need to build linkages between the two disciplines. Pharmacogenomic evidence guiding opioid prescribing is currently available for codeine and tramadol, which relates to CYP2D6 gene variants. However, these medications are prescribed less commonly for pain in palliative care. Research is accelerating with other opioids, where oxycodone (CYP2D6) and methadone (CYP2B6, ABCB1) already have moderate evidence of an association in terms of drug metabolism and downstream analgesic response and side effects. OPRM1 and COMT are receiving increasing attention and have implications for all opioids, with changes in opioid dosage requirements observed but they have not yet been studied widely enough to be considered clinically actionable. Current evidence indicates that incorporation of pharmacogenomic testing into opioid prescribing practice should focus on the CYP2D6 gene and its actionable variants. Although opioid pharmacogenomic tests are not widely used in clinical practice, the progressively reducing costs and rapid turnover means greater accessibility and affordability to patients, and thus, clinicians will be increasingly asked to provide guidance in this area. The upsurge in pharmacogenomic research will likely discover more actionable gene variants to expand international guidelines to impact opioid prescribing. This rapidly expanding area requires consideration and monitoring by clinicians in order for key findings with clinical implications to be accessible, meaningfully interpretable and communicated.
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32
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Zhou Y, Tremmel R, Schaeffeler E, Schwab M, Lauschke VM. Challenges and opportunities associated with rare-variant pharmacogenomics. Trends Pharmacol Sci 2022; 43:852-865. [PMID: 36008164 DOI: 10.1016/j.tips.2022.07.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 06/15/2022] [Accepted: 07/29/2022] [Indexed: 12/26/2022]
Abstract
Recent advances in next-generation sequencing (NGS) have resulted in the identification of tens of thousands of rare pharmacogenetic variations with unknown functional effects. However, although such pharmacogenetic variations have been estimated to account for a considerable amount of the heritable variability in drug response and toxicity, accurate interpretation at the level of the individual patient remains challenging. We discuss emerging strategies and concepts to close this translational gap. We illustrate how massively parallel experimental assays, artificial intelligence (AI), and machine learning can synergize with population-scale biobank projects to facilitate the interpretation of NGS data to individualize clinical decision-making and personalized medicine.
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Affiliation(s)
- Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Roman Tremmel
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany; University of Tübingen, Tübingen, Germany
| | - Elke Schaeffeler
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany; University of Tübingen, Tübingen, Germany; Cluster of Excellence iFIT (EXC2180) Image-Guided and Functionally Instructed Tumor Therapies, University of Tübingen, Tübingen, Germany
| | - Matthias Schwab
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany; Cluster of Excellence iFIT (EXC2180) Image-Guided and Functionally Instructed Tumor Therapies, University of Tübingen, Tübingen, Germany; Department of Clinical Pharmacology, and Department of Biochemistry and Pharmacy, University of Tübingen, Tübingen, Germany
| | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden; Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany; University of Tübingen, Tübingen, Germany.
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Pépin MA, Otis AS, Tremblay Z, Boulé M, Lebel D, Major P, Lortie A, Pinchefsky E, Rossignol E, Carleton B, Bussières JF, Métras MÉ. Pharmacogenetic testing in pediatric neurology: a pragmatic study evaluating clinician and patient perceptions. Per Med 2022; 19:423-434. [PMID: 35830229 DOI: 10.2217/pme-2021-0150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Aim: To evaluate clinicians' and patients' perceptions of pharmacogenetic testing in a clinical setting. Materials & methods: This is a pragmatic mixed-method prospective observational study. Hospital pharmacists and neurologists participated in focus groups regarding pharmacogenetic testing; patients who received pharmacogenetic testing and their community pharmacists completed surveys to assess their perception of these tests. Results: Most study participants had a positive view of pharmacogenetic testing. Three major themes were identified from the focus groups: receptiveness to pharmacogenetic testing, pharmacogenetic test characteristics and integrating pharmacogenetic tests into practice. Conclusion: The views reported are encouraging for the eventual implementation of pharmacogenetics in practice. Local integration of these tests is an essential step to improve patient care through personalized medicine.
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Affiliation(s)
- Marie-Anne Pépin
- Pharmacy Practice Research Unit & Department of Pharmacy, CHU Sainte-Justine, Montréal, Québec, H3T 1C5, Canada
| | - Anne-Sophie Otis
- Pharmacy Practice Research Unit & Department of Pharmacy, CHU Sainte-Justine, Montréal, Québec, H3T 1C5, Canada
| | - Zoë Tremblay
- Pharmacy Practice Research Unit & Department of Pharmacy, CHU Sainte-Justine, Montréal, Québec, H3T 1C5, Canada
| | - Marianne Boulé
- Pharmacy Practice Research Unit & Department of Pharmacy, CHU Sainte-Justine, Montréal, Québec, H3T 1C5, Canada
| | - Denis Lebel
- Pharmacy Practice Research Unit & Department of Pharmacy, CHU Sainte-Justine, Montréal, Québec, H3T 1C5, Canada
| | - Philippe Major
- Research Center & Division of Neurology, Department of Pediatrics, CHU Sainte-Justine, Montréal, Québec, H3T 1C5, Canada.,Department of Neuroscience, Université de Montréal, Montréal, Québec, H3T 1J4, Canada.,Department of Pediatrics, Université de Montréal, Montréal, Québec, H3T 1J4, Canada
| | - Anne Lortie
- Research Center & Division of Neurology, Department of Pediatrics, CHU Sainte-Justine, Montréal, Québec, H3T 1C5, Canada.,Department of Neuroscience, Université de Montréal, Montréal, Québec, H3T 1J4, Canada.,Department of Pediatrics, Université de Montréal, Montréal, Québec, H3T 1J4, Canada
| | - Elana Pinchefsky
- Research Center & Division of Neurology, Department of Pediatrics, CHU Sainte-Justine, Montréal, Québec, H3T 1C5, Canada.,Department of Neuroscience, Université de Montréal, Montréal, Québec, H3T 1J4, Canada
| | - Elsa Rossignol
- Research Center & Division of Neurology, Department of Pediatrics, CHU Sainte-Justine, Montréal, Québec, H3T 1C5, Canada.,Department of Neuroscience, Université de Montréal, Montréal, Québec, H3T 1J4, Canada.,Department of Pediatrics, Université de Montréal, Montréal, Québec, H3T 1J4, Canada
| | - Bruce Carleton
- Professor & Division Head, Translational Therapeutics, Department of Pediatrics, University of British-Columbia, Vancouver, British-Columbia, H3T 1J4, Canada.,Director, Pharmaceutical Outcomes Programme, BC Children's Hospital, Vancouver, British-Columbia, V6H 3N1, Canada.,Investigator, BC Children's Hospital Research Institute, Vancouver, British-Columbia, V6H 3N1, Canada
| | - Jean-François Bussières
- Pharmacy Practice Research Unit & Department of Pharmacy, CHU Sainte-Justine, Montréal, Québec, H3T 1C5, Canada.,Clinical Professor, Faculty of Pharmacy, Université de Montréal, Montréal, Québec, H3T 1J4, Canada
| | - Marie-Élaine Métras
- Pharmacy Practice Research Unit & Department of Pharmacy, CHU Sainte-Justine, Montréal, Québec, H3T 1C5, Canada.,Clinical Professor, Faculty of Pharmacy, Université de Montréal, Montréal, Québec, H3T 1J4, Canada
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34
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Model systems and organisms for addressing inter- and intra-species variability in risk assessment. Regul Toxicol Pharmacol 2022; 132:105197. [DOI: 10.1016/j.yrtph.2022.105197] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 05/20/2022] [Accepted: 05/25/2022] [Indexed: 12/12/2022]
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Fracowiak J, Huebner T, Heß S, Roethlein C, Langner D, Schneider U, Falkenberg F, Scholl C, Linder R, Stingl J, Haenisch B, Steffens M. Evaluation of the EMPAR study population on the basis of metabolic phenotypes of selected pharmacogenes. THE PHARMACOGENOMICS JOURNAL 2022; 22:136-144. [PMID: 35102241 PMCID: PMC8975744 DOI: 10.1038/s41397-022-00268-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 12/16/2021] [Accepted: 01/12/2022] [Indexed: 06/14/2023]
Abstract
The impact of genetic variability of pharmacogenes as a possible risk factor for adverse drug reactions is elucidated in the EMPAR (Einfluss metabolischer Profile auf die Arzneimitteltherapiesicherheit in der Routineversorgung/English: influence of metabolic profiles on the safety of drug therapy in routine care) study. EMPAR evaluates possible associations of pharmacogenetically predicted metabolic profiles relevant for the metabolism of frequently prescribed cardiovascular drugs. Based on a German study population of 10,748 participants providing access to healthcare claims data and DNA samples for pharmacogenetic assessment, first analyses were performed and evaluated. The aim of this first evaluation was the characterization of the study population with regard to general parameters such as age, gender, comorbidity, and polypharmacy at baseline (baseline year) as well as important combinations of cardiovascular drugs with relevant genetic variants and predicted metabolic phenotypes. The study was registered in the German Clinical Trials Register (DRKS) on July 6, 2018 (DRKS00013909).
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Affiliation(s)
- Jochen Fracowiak
- Research Division, Federal Institute for Drugs and Medical Devices, Bonn, North Rhine-Westphalia, Germany
| | - Tatjana Huebner
- Research Division, Federal Institute for Drugs and Medical Devices, Bonn, North Rhine-Westphalia, Germany.
| | - Steffen Heß
- Research Division, Federal Institute for Drugs and Medical Devices, Bonn, North Rhine-Westphalia, Germany
| | - Christoph Roethlein
- German Center for Neurodegenerative Diseases (DZNE), Bonn, North Rhine-Westphalia, Germany
| | | | | | | | - Catharina Scholl
- Research Division, Federal Institute for Drugs and Medical Devices, Bonn, North Rhine-Westphalia, Germany
| | | | - Julia Stingl
- Institute for Clinical Pharmacology, RWTH Aachen University, Aachen, North Rhine-Westphalia, Germany
| | - Britta Haenisch
- Research Division, Federal Institute for Drugs and Medical Devices, Bonn, North Rhine-Westphalia, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, North Rhine-Westphalia, Germany
- Center for Translational Medicine, Medical Faculty, University of Bonn, Bonn, North Rhine-Westphalia, Germany
| | - Michael Steffens
- Research Division, Federal Institute for Drugs and Medical Devices, Bonn, North Rhine-Westphalia, Germany
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36
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Pharmacogenetic interventions to improve outcomes in patients with multimorbidity or prescribed polypharmacy: a systematic review. THE PHARMACOGENOMICS JOURNAL 2022; 22:89-99. [PMID: 35194175 PMCID: PMC8975737 DOI: 10.1038/s41397-021-00260-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 10/19/2021] [Accepted: 10/21/2021] [Indexed: 01/11/2023]
Abstract
Conventional medicines optimisation interventions in people with multimorbidity and polypharmacy are complex and yet limited; a more holistic and integrated approach to healthcare delivery is required. Pharmacogenetics has potential as a component of medicines optimisation. Studies involving multi-medicine pharmacogenetics in adults with multimorbidity or polypharmacy, reporting on outcomes derived from relevant core outcome sets, were included in this systematic review. Narrative synthesis was undertaken to summarise the data; meta-analysis was inappropriate due to study heterogeneity. Fifteen studies of diverse design and variable quality were included. A small, randomised study involving pharmacist-led medicines optimisation, including pharmacogenetics, suggests this approach could have significant benefits for patients and health systems. However, due to study design heterogeneity and the quality of the included studies, it is difficult to draw generalisable conclusions. Further pragmatic, robust pharmacogenetics studies in diverse, real-world patient populations, are required to establish the benefit of multi-medicine pharmacogenetic screening on patient outcomes.
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37
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Auwerx C, Sadler MC, Reymond A, Kutalik Z. From Pharmacogenetics to Pharmaco-Omics:Milestones and Future Directions. HGG ADVANCES 2022; 3:100100. [PMID: 35373152 PMCID: PMC8971318 DOI: 10.1016/j.xhgg.2022.100100] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
The origins of pharmacogenetics date back to the 1950s, when it was established that inter-individual differences in drug response are partially determined by genetic factors. Since then, pharmacogenetics has grown into its own field, motivated by the translation of identified gene-drug interactions into therapeutic applications. Despite numerous challenges ahead, our understanding of the human pharmacogenetic landscape has greatly improved thanks to the integration of tools originating from disciplines as diverse as biochemistry, molecular biology, statistics, and computer sciences. In this review, we discuss past, present, and future developments of pharmacogenetics methodology, focusing on three milestones: how early research established the genetic basis of drug responses, how technological progress made it possible to assess the full extent of pharmacological variants, and how multi-dimensional omics datasets can improve the identification, functional validation, and mechanistic understanding of the interplay between genes and drugs. We outline novel strategies to repurpose and integrate molecular and clinical data originating from biobanks to gain insights analogous to those obtained from randomized controlled trials. Emphasizing the importance of increased diversity, we envision future directions for the field that should pave the way to the clinical implementation of pharmacogenetics.
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38
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Identification of pharmacogenetic variants from large scale next generation sequencing data in the Saudi population. PLoS One 2022; 17:e0263137. [PMID: 35089958 PMCID: PMC8797234 DOI: 10.1371/journal.pone.0263137] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 01/12/2022] [Indexed: 11/19/2022] Open
Abstract
It is well documented that drug responses are related to Absorption, Distribution, Metabolism, and Excretion (ADME) characteristics of individual patients. Several studies have identified genetic variability in pharmacogenes, that are either directly responsible for or are associated with ADME, giving rise to individualized treatments. Our objective was to provide a comprehensive overview of pharmacogenetic variation in the Saudi population. We mined next generation sequencing (NGS) data from 11,889 unrelated Saudi nationals, to determine the presence and frequencies of known functional SNP variants in 8 clinically relevant pharmacogenes (CYP2C9, CYP2C19, CYP3A5, CYP4F2, VKORC1, DPYD, TPMT and NUDT15), recommended by the Clinical Pharmacogenetics Implementation Consortium (CPIC), and collectively identified 82 such star alleles. Functionally significant pharmacogenetic variants were prevalent especially in CYP genes (excluding CYP3A5), with 10-44.4% of variants predicted to be inactive or to have decreased activity. In CYP3A5, inactive alleles (87.5%) were the most common. Only 1.8%, 0.7% and 0.7% of NUDT15, TPMT and DPYD variants respectively, were predicted to affect gene activity. In contrast, VKORC1 was found functionally, to be highly polymorphic with 53.7% of Saudi individuals harboring variants predicted to result in decreased activity and 31.3% having variants leading to increased metabolic activity. Furthermore, among the 8 pharmacogenes studied, we detected six rare variants with an aggregated frequency of 1.1%, that among several other ethnicities, were uniquely found in Saudi population. Similarly, within our cohort, the 8 pharmacogenes yielded forty-six novel variants predicted to be deleterious. Based upon our findings, 99.2% of individuals from the Saudi population carry at least one actionable pharmacogenetic variant.
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39
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Lanillos J, Carcajona M, Maietta P, Alvarez S, Rodriguez-Antona C. Clinical pharmacogenetic analysis in 5,001 individuals with diagnostic Exome Sequencing data. NPJ Genom Med 2022; 7:12. [PMID: 35181665 PMCID: PMC8857256 DOI: 10.1038/s41525-022-00283-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 01/21/2022] [Indexed: 11/22/2022] Open
Abstract
Exome sequencing is utilized in routine clinical genetic diagnosis. The technical robustness of repurposing large-scale next-generation sequencing data for pharmacogenetics has been demonstrated, supporting the implementation of preemptive pharmacogenetic strategies based on adding clinical pharmacogenetic interpretation to exomes. However, a comprehensive study analyzing all actionable pharmacogenetic alleles contained in international guidelines and applied to diagnostic exome data has not been performed. Here, we carried out a systematic analysis based on 5001 Spanish or Latin American individuals with diagnostic exome data, either Whole Exome Sequencing (80%), or the so-called Clinical Exome Sequencing (20%) (60 Mb and 17 Mb, respectively), to provide with global and gene-specific clinical pharmacogenetic utility data. 788 pharmacogenetic alleles, distributed through 19 genes included in Clinical Pharmacogenetics Implementation Consortium guidelines were analyzed. We established that Whole Exome and Clinical Exome Sequencing performed similarly, and 280 alleles in 11 genes (CACNA1S, CYP2B6, CYP2C9, CYP4F2, DPYD, G6PD, NUDT15, RYR1, SLCO1B1, TPMT, and UGT1A1) could be used to inform of pharmacogenetic phenotypes that change drug prescription. Each individual carried in average 2.2 alleles and overall 95% (n = 4646) of the cohort could be informed of at least one actionable pharmacogenetic phenotype. Differences in variant allele frequency were observed among the populations studied and the corresponding gnomAD population for 7.9% of the variants. In addition, in the 11 selected genes we uncovered 197 novel variants, among which 27 were loss-of-function. In conclusion, we provide with the landscape of actionable pharmacogenetic information contained in diagnostic exomes, that can be used preemptively in the clinics.
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Affiliation(s)
- Javier Lanillos
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Programme, Spanish National Cancer Research Centre (CNIO), 28029, Madrid, Spain
| | | | | | | | - Cristina Rodriguez-Antona
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Programme, Spanish National Cancer Research Centre (CNIO), 28029, Madrid, Spain. .,Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Madrid, Spain.
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40
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Scionti F, Di Martino MT, Caracciolo D, Pensabene L, Tagliaferri P, Arbitrio M. Tools in Pharmacogenomics Biomarker Identification for Cancer Patients. Methods Mol Biol 2022; 2401:1-12. [PMID: 34902118 DOI: 10.1007/978-1-0716-1839-4_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The understanding of the biological differences which underlie the inter-individual variability in drug response improved the efficacy of cancer therapy in the era of precision medicine. In fact molecularly targeted drugs and immunotherapy represent a revolution in cancer treatment. The identification of genetic predictive and/or prognostic biomarkers linked to drug pharmacokinetics (PK) and pharmacodynamics (PD) is allowed by the development of high-throughput omics tools for detecting and understanding biological differences among individuals, in order to improve drug efficacy and minimize risk of toxicity. Personalized medicine in cancer treatment reduces costs of the healthcare system. Unfortunately, pharmacogenomics biomarkers discovery is influenced by complexity, need of high-quality evidence, and a validation process for regulatory purposes. This chapter is focused on the critic analysis of presently available pharmacogenomics tools for discovering or testing genetic polymorphic variants in drug metabolizing enzyme to be introduced in clinical practice for the prospective stratification of cancer patients.
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Affiliation(s)
- Francesca Scionti
- Institute for Biomedical Research and Innovation (IRIB), National Research Council (CNR), Messina, Italy
| | | | - Daniele Caracciolo
- Department of Experimental and Clinical Medicine, Magna Græcia University, Catanzaro, Italy
| | - Licia Pensabene
- Department of Medical and Surgical Sciences, Pediatric Unit, University "Magna Graecia" of Catanzaro, Catanzaro, Italy
| | | | - Mariamena Arbitrio
- Institute of Research and Biomedical Innovation (IRIB), National Research Council (CNR), Catanzaro, Italy.
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41
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Application of long-read sequencing to elucidate complex pharmacogenomic regions: a proof of principle. THE PHARMACOGENOMICS JOURNAL 2022; 22:75-81. [PMID: 34741133 PMCID: PMC8794781 DOI: 10.1038/s41397-021-00259-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
The use of pharmacogenomics in clinical practice is becoming standard of care. However, due to the complex genetic makeup of pharmacogenes, not all genetic variation is currently accounted for. Here, we show the utility of long-read sequencing to resolve complex pharmacogenes by analyzing a well-characterised sample. This data consists of long reads that were processed to resolve phased haploblocks. 73% of pharmacogenes were fully covered in one phased haploblock, including 9/15 genes that are 100% complex. Variant calling accuracy in the pharmacogenes was high, with 99.8% recall and 100% precision for SNVs and 98.7% precision and 98.0% recall for Indels. For the majority of gene-drug interactions in the DPWG and CPIC guidelines, the associated genes could be fully resolved (62% and 63% respectively). Together, these findings suggest that long-read sequencing data offers promising opportunities in elucidating complex pharmacogenes and haplotype phasing while maintaining accurate variant calling.
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Barker CIS, Groeneweg G, Maitland-van der Zee AH, Rieder MJ, Hawcutt DB, Hubbard TJ, Swen JJ, Carleton BC. Pharmacogenomic testing in paediatrics: clinical implementation strategies. Br J Clin Pharmacol 2021; 88:4297-4310. [PMID: 34907575 PMCID: PMC9544158 DOI: 10.1111/bcp.15181] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 10/22/2021] [Accepted: 11/09/2021] [Indexed: 11/27/2022] Open
Abstract
Pharmacogenomics (PGx) relates to the study of genetic factors determining variability in drug response. Implementing PGx testing in paediatric patients can enhance drug safety, helping to improve drug efficacy or reduce the risk of toxicity. Despite its clinical relevance, the implementation of PGx testing in paediatric practice to date has been variable and limited. As with most paediatric pharmacological studies, there are well‐recognised barriers to obtaining high‐quality PGx evidence, particularly when patient numbers may be small, and off‐label or unlicensed prescribing remains widespread. Furthermore, trials enrolling small numbers of children can rarely, in isolation, provide sufficient PGx evidence to change clinical practice, so extrapolation from larger PGx studies in adult patients, where scientifically sound, is essential. This review paper discusses the relevance of PGx to paediatrics and considers implementation strategies from a child health perspective. Examples are provided from Canada, the Netherlands and the UK, with consideration of the different healthcare systems and their distinct approaches to implementation, followed by future recommendations based on these cumulative experiences. Improving the evidence base demonstrating the clinical utility and cost‐effectiveness of paediatric PGx testing will be critical to drive implementation forwards. International, interdisciplinary collaborations will enhance paediatric data collation, interpretation and evidence curation, while also supporting dedicated paediatric PGx educational initiatives. PGx consortia and paediatric clinical research networks will continue to play a central role in the streamlined development of effective PGx implementation strategies to help optimise paediatric pharmacotherapy.
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Affiliation(s)
- Charlotte I S Barker
- Department of Medical & Molecular Genetics, King's College London, London, UK.,Department of Clinical Genetics, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Gabriella Groeneweg
- Division of Translational Therapeutics, Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada.,Pharmaceutical Outcomes Programme, BC Children's Hospital, Vancouver, British Columbia, Canada
| | - Anke H Maitland-van der Zee
- Respiratory Medicine/Pediatric Respiratory Medicine, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Michael J Rieder
- Departments of Paediatrics, Physiology and Pharmacology and Medicine, Western University, London, Ontario, Canada.,Molecular Medicine Group, Robarts Research Institute, London, Ontario, Canada
| | - Daniel B Hawcutt
- Department of Women's and Children's Health, University of Liverpool, Liverpool, UK.,NIHR Clinical Research Facility, Alder Hey Children's Hospital, Liverpool, UK
| | - Tim J Hubbard
- Department of Medical & Molecular Genetics, King's College London, London, UK.,Genomics England, London, UK
| | - Jesse J Swen
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, The Netherlands.,Leiden Network for Personalized Therapeutics, Leiden, The Netherlands
| | - Bruce C Carleton
- Division of Translational Therapeutics, Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada.,Pharmaceutical Outcomes Programme, BC Children's Hospital, Vancouver, British Columbia, Canada.,BC Children's Hospital Research Institute, Vancouver, British Columbia, Canada
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43
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Jameson A, Fylan B, Bristow GC, Sagoo GS, Dalton C, Cardno A, Sohal J, McLean SL. What Are the Barriers and Enablers to the Implementation of Pharmacogenetic Testing in Mental Health Care Settings? Front Genet 2021; 12:740216. [PMID: 34630531 PMCID: PMC8493030 DOI: 10.3389/fgene.2021.740216] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 08/30/2021] [Indexed: 01/29/2023] Open
Abstract
In psychiatry, the selection of antipsychotics and antidepressants is generally led by a trial-and-error approach. The prescribing of these medications is complicated by sub-optimal efficacy and high rates of adverse drug reactions (ADRs). These both contribute to poor levels of adherence. Pharmacogenetics (PGx) considers how genetic variation can influence an individual’s response to a drug. Pharmacogenetic testing is a tool that could aid clinicians when selecting psychotropic medications, as part of a more personalized approach to prescribing. This may improve the use of and adherence to these medications. Yet to date, the implementation of PGx in mental health environments in the United Kingdom has been slow. This review aims to identify the current barriers and enablers to the implementation of PGx in psychiatry and determine how this can be applied to the uptake of PGx by NHS mental health providers. A systematic searching strategy was developed, and searches were carried out on the PsychInfo, EmBase, and PubMed databases, yielding 11 appropriate papers. Common barriers to the implementation of PGx included cost, concerns over incorporation into current workflow and a lack of knowledge about PGx; whilst frequent enablers included optimism that PGx could lead to precision medicine, reduce ADRs and become a more routine part of psychiatric clinical care. The uptake of PGx in psychiatric care settings in the NHS should consider and overcome these barriers, while looking to capitalize on the enablers identified in this review.
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Affiliation(s)
- Adam Jameson
- Bradford District Care NHS Foundation Trust, Bradford, United Kingdom.,School of Pharmacy and Medical Sciences, University of Bradford, Bradford, United Kingdom.,Wolfson Centre for Applied Health Research, Bradford, United Kingdom
| | - Beth Fylan
- School of Pharmacy and Medical Sciences, University of Bradford, Bradford, United Kingdom.,Wolfson Centre for Applied Health Research, Bradford, United Kingdom.,Bradford Institute of Health Research, NIHR Yorkshire and Humber Patient Safety Translational Research Centre, Bradford, United Kingdom
| | - Greg C Bristow
- School of Pharmacy and Medical Sciences, University of Bradford, Bradford, United Kingdom
| | - Gurdeep S Sagoo
- Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds, Leeds, United Kingdom.,National Institute for Health Research Leeds in vitro Diagnostics Co-operative, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | - Caroline Dalton
- Biomolecular Sciences Research Centre, Sheffield Hallam University, Sheffield, United Kingdom
| | - Alastair Cardno
- Leeds Institute of Health Sciences, Faculty of Medicine and Health, University of Leeds, Leeds, United Kingdom
| | - Jaspreet Sohal
- Bradford District Care NHS Foundation Trust, Bradford, United Kingdom
| | - Samantha L McLean
- School of Pharmacy and Medical Sciences, University of Bradford, Bradford, United Kingdom.,Wolfson Centre for Applied Health Research, Bradford, United Kingdom
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44
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Clinical implementation of drug metabolizing gene-based therapeutic interventions worldwide. Hum Genet 2021; 141:1137-1157. [PMID: 34599365 DOI: 10.1007/s00439-021-02369-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 09/09/2021] [Indexed: 02/05/2023]
Abstract
Over the last few years, the field of pharmacogenomics has gained considerable momentum. The advances of new genomics and bioinformatics technologies propelled pharmacogenomics towards its implementation in the clinical setting. Since 2007, and especially the last-5 years, many studies have focused on the clinical implementation of pharmacogenomics while identifying obstacles and proposed strategies and approaches for overcoming them in the real world of primary care as well as outpatients and inpatients clinics. Here, we outline the recent pharmacogenomics clinical implementation projects and provide details of the study designs, including the most predominant and innovative, as well as clinical studies worldwide that focus on outpatients and inpatient clinics, and primary care. According to these studies, pharmacogenomics holds promise for improving patients' health in terms of efficacy and toxicity, as well as in their overall quality of life, while simultaneously can contribute to the minimization of healthcare expenditure.
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45
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David V, Fylan B, Bryant E, Smith H, Sagoo GS, Rattray M. An Analysis of Pharmacogenomic-Guided Pathways and Their Effect on Medication Changes and Hospital Admissions: A Systematic Review and Meta-Analysis. Front Genet 2021; 12:698148. [PMID: 34394187 PMCID: PMC8362615 DOI: 10.3389/fgene.2021.698148] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Accepted: 06/28/2021] [Indexed: 01/02/2023] Open
Abstract
Ninety-five percent of the population are estimated to carry at least one genetic variant that is discordant with at least one medication. Pharmacogenomic (PGx) testing has the potential to identify patients with genetic variants that puts them at risk of adverse drug reactions and sub-optimal therapy. Predicting a patient's response to medications could support the safe management of medications and reduce hospitalization. These benefits can only be realized if prescribing clinicians make the medication changes prompted by PGx test results. This review examines the current evidence on the impact PGx testing has on hospital admissions and whether it prompts medication changes. A systematic search was performed in three databases (Medline, CINAHL and EMBASE) to search all the relevant studies published up to the year 2020, comparing hospitalization rates and medication changes amongst PGx tested patients with patients receiving treatment-as-usual (TAU). Data extracted from full texts were narratively synthesized using a process model developed from the included studies, to derive themes associated to a suggested workflow for PGx-guided care and its expected benefit for medications optimization and hospitalization. A meta-analysis was undertaken on all the studies that report the number of PGx tested patients that had medication change(s) and the number of PGx tested patients that were hospitalized, compared to participants that received TAU. The search strategy identified 5 hospitalization themed studies and 5 medication change themed studies for analysis. The meta-analysis showed that medication changes occurred significantly more frequently in the PGx tested arm across 4 of 5 studies. Meta-analysis showed that all-cause hospitalization occurred significantly less frequently in the PGx tested arm than the TAU. The results show proof of concept for the use of PGx in prescribing that produces patient benefit. However, the review also highlights the opportunities and evidence gaps that are important when considering the introduction of PGx into health systems; namely patient involvement in PGx prescribing decisions, thus a better understanding of the perspective of patients and prescribers. We highlight the opportunities and evidence gaps that are important when considering the introduction of PGx into health systems.
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Affiliation(s)
- Victoria David
- Leeds Teaching Hospitals National Health Service (NHS) Trust, Leeds, United Kingdom.,School of Pharmacy and Medical Sciences, University of Bradford, Bradford, United Kingdom.,Wolfson Centre for Applied Health Research, Bradford, United Kingdom
| | - Beth Fylan
- School of Pharmacy and Medical Sciences, University of Bradford, Bradford, United Kingdom.,Wolfson Centre for Applied Health Research, Bradford, United Kingdom.,Yorkshire and Humber Patient Safety Translational Research Centre, Bradford Institute of Health Research, Bradford, United Kingdom
| | - Eleanor Bryant
- Wolfson Centre for Applied Health Research, Bradford, United Kingdom.,Division of Psychology in the School of Social Sciences, University of Bradford, Bradford, United Kingdom
| | - Heather Smith
- Leeds Teaching Hospitals National Health Service (NHS) Trust, Leeds, United Kingdom
| | - Gurdeep S Sagoo
- Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds, Leeds, United Kingdom.,National Institute for Health Research Leeds In Vitro Diagnostics Co-operative, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | - Marcus Rattray
- School of Pharmacy and Medical Sciences, University of Bradford, Bradford, United Kingdom.,Wolfson Centre for Applied Health Research, Bradford, United Kingdom
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46
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Hicks JK, El Rouby N, Ong HH, Schildcrout JS, Ramsey LB, Shi Y, Tang LA, Aquilante CL, Beitelshees AL, Blake KV, Cimino JJ, Davis BH, Empey PE, Kao DP, Lemkin DL, Limdi NA, Lipori GP, Rosenman MB, Skaar TC, Teal E, Tuteja S, Wiley LK, Williams H, Winterstein AG, Van Driest SL, Cavallari LH, Peterson JF. Opportunity for Genotype-Guided Prescribing Among Adult Patients in 11 US Health Systems. Clin Pharmacol Ther 2021; 110:179-188. [PMID: 33428770 PMCID: PMC8217370 DOI: 10.1002/cpt.2161] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 12/24/2020] [Indexed: 12/11/2022]
Abstract
The value of utilizing a multigene pharmacogenetic panel to tailor pharmacotherapy is contingent on the prevalence of prescribed medications with an actionable pharmacogenetic association. The Clinical Pharmacogenetics Implementation Consortium (CPIC) has categorized over 35 gene-drug pairs as "level A," for which there is sufficiently strong evidence to recommend that genetic information be used to guide drug prescribing. The opportunity to use genetic information to tailor pharmacotherapy among adult patients was determined by elucidating the exposure to CPIC level A drugs among 11 Implementing Genomics In Practice Network (IGNITE)-affiliated health systems across the US. Inpatient and/or outpatient electronic-prescribing data were collected between January 1, 2011 and December 31, 2016 for patients ≥ 18 years of age who had at least one medical encounter that was eligible for drug prescribing in a calendar year. A median of ~ 7.2 million adult patients was available for assessment of drug prescribing per year. From 2011 to 2016, the annual estimated prevalence of exposure to at least one CPIC level A drug prescribed to unique patients ranged between 15,719 (95% confidence interval (CI): 15,658-15,781) in 2011 to 17,335 (CI: 17,283-17,386) in 2016 per 100,000 patients. The estimated annual exposure to at least 2 drugs was above 7,200 per 100,000 patients in most years of the study, reaching an apex of 7,660 (CI: 7,632-7,687) per 100,000 patients in 2014. An estimated 4,748 per 100,000 prescribing events were potentially eligible for a genotype-guided intervention. Results from this study show that a significant portion of adults treated at medical institutions across the United States is exposed to medications for which genetic information, if available, should be used to guide prescribing.
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Affiliation(s)
- J. Kevin Hicks
- Department of Individualized Cancer Management, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Nihal El Rouby
- Department of Pharmacotherapy & Translational Research, University of Florida, Gainesville, FL
- James Winkle College of Pharmacy, University of Cincinnati, Cincinnati, OH
| | - Henry H. Ong
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN
| | | | - Laura B. Ramsey
- Department of Pediatrics, College of Medicine, University of Cincinnati, Divisions of Research in Patient Services and Clinical Pharmacology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
| | - Yaping Shi
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN
| | - Leigh Anne Tang
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
| | - Christina L. Aquilante
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado, Aurora, CO
| | | | | | - James J. Cimino
- Informatics Institute, University of Alabama at Birmingham, Birmingham, AL
| | - Brittney H. Davis
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL
| | - Philip E. Empey
- Department of Pharmacy & Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA
| | - David P. Kao
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
| | | | - Nita A. Limdi
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL
| | - Gloria P. Lipori
- University of Florida Health and University of Florida Health Sciences Center, Gainesville, FL
| | - Marc B. Rosenman
- Indiana University School of Medicine, Indianapolis, IN
- Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL
| | - Todd C. Skaar
- Indiana University School of Medicine, Indianapolis, IN
| | | | - Sony Tuteja
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Laura K. Wiley
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
| | | | - Almut G. Winterstein
- Department of Pharmaceutical Outcomes & Policy, University of Florida, Gainesville, FL
| | - Sara L. Van Driest
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Larisa H. Cavallari
- Department of Pharmacotherapy & Translational Research, University of Florida, Gainesville, FL
| | - Josh F. Peterson
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
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47
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Bishop JR, Huang RS, Brown JT, Mroz P, Johnson SG, Allen JD, Bielinski SJ, England J, Farley JF, Gregornik D, Giri J, Kroger C, Long SE, Luczak T, McGonagle EJ, Ma S, Matey ET, Mandic PK, Moyer AM, Nicholson WT, Petry N, Pawloski PA, Schlichte A, Schondelmeyer SW, Seifert RD, Speedie MK, Stenehjem D, Straka RJ, Wachtl J, Waring SC, Ness BV, Zierhut HA, Aliferis C, Wolf SM, McCarty CA, Jacobson PA. Pharmacogenomics education, research and clinical implementation in the state of Minnesota. Pharmacogenomics 2021; 22:681-691. [PMID: 34137665 DOI: 10.2217/pgs-2021-0058] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Several healthcare organizations across Minnesota have developed formal pharmacogenomic (PGx) clinical programs to increase drug safety and effectiveness. Healthcare professional and student education is strong and there are multiple opportunities in the state for learners to gain workforce skills and develop advanced competency in PGx. Implementation planning is occurring at several organizations and others have incorporated structured utilization of PGx into routine workflows. Laboratory-based and translational PGx research in Minnesota has driven important discoveries in several therapeutic areas. This article reviews the state of PGx activities in Minnesota including educational programs, research, national consortia involvement, technology, clinical implementation and utilization and reimbursement, and outlines the challenges and opportunities in equitable implementation of these advances.
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Affiliation(s)
- Jeffrey R Bishop
- Department of Experimental & Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA.,Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - R Stephanie Huang
- Department of Experimental & Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
| | - Jacob T Brown
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota College of Pharmacy, Duluth, MN 55812, USA
| | - Pawel Mroz
- Department of Laboratory Medicine & Pathology, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Steven G Johnson
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Josiah D Allen
- University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA.,Medigenics Consulting LLC, Minneapolis, MN 55407, USA
| | - Suzette J Bielinski
- Department of Quantitative Health Sciences, Division of Epidemiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Joel F Farley
- Department of Pharmaceutical Care & Health Systems, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
| | - David Gregornik
- Pharmacogenomics Program, Children's Minnesota, Minneapolis, MN 55407, USA
| | - Jyothsna Giri
- Mayo Clinic Center for Individualized Medicine, Mayo Clinic College of Medicine & Science, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Susie E Long
- MHealth Fairview. Acute Care Pharmacy Services, Minneapolis, MN 55455, USA
| | - Tiana Luczak
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota College of Pharmacy, Duluth, MN 55812, USA.,Essentia Health, Duluth, MN 55805, USA
| | - Erin J McGonagle
- Department of Experimental & Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
| | - Sisi Ma
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Eric T Matey
- Department of Pharmacy, Mayo Clinic College of Medicine & Science, Mayo Clinic, Rochester, MN 55905, USA
| | - Pinar K Mandic
- Department of Finance, University of Minnesota Carlson School of Management, Minneapolis, MN 55455, USA
| | - Ann M Moyer
- Department of Laboratory Medicine & Pathology, Mayo Clinic College of Medicine & Science, Mayo Clinic, Rochester, MN 55905, USA
| | - Wayne T Nicholson
- Department of Anesthesiology & Perioperative Medicine, Mayo Clinic College of Medicine & Science, Mayo Clinic, Rochester, MN 55905, USA
| | - Natasha Petry
- Sanford Health Imagenetics, Sioux Falls, SD 57105, USA.,Department of Pharmacy Practice, North Dakota State University College of Health Professions, Fargo, ND 58108, USA
| | | | | | - Stephen W Schondelmeyer
- Department of Pharmaceutical Care & Health Systems, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
| | - Randall D Seifert
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota College of Pharmacy, Duluth, MN 55812, USA
| | - Marilyn K Speedie
- Department of Medicinal Chemistry, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
| | - David Stenehjem
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota College of Pharmacy, Duluth, MN 55812, USA
| | - Robert J Straka
- Department of Experimental & Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
| | - Jason Wachtl
- Geritom Medical, Inc, Bloomington, MN 55438, USA
| | | | - Brian Van Ness
- Department of Genetics, Cell Biology & Development, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Heather A Zierhut
- Department of Genetics, Cell Biology & Development, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Constantin Aliferis
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Susan M Wolf
- Law School, Medical School, Consortium on Law & Values in Health, Environment & the Life Sciences, University of Minnesota, Minneapolis, MN 55455, USA
| | - Catherine A McCarty
- Department of Family Medicine & Biobehavioral Health, University of Minnesota Medical School, Duluth, MN 55812, USA
| | - Pamala A Jacobson
- Department of Experimental & Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
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48
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Zanardi R, Manfredi E, Montrasio C, Colombo C, Serretti A, Fabbri C. Pharmacogenetic-Guided Treatment of Depression: Real-World Clinical Applications, Challenges, and Perspectives. Clin Pharmacol Ther 2021; 110:573-581. [PMID: 34047355 DOI: 10.1002/cpt.2315] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Accepted: 05/20/2021] [Indexed: 12/12/2022]
Abstract
Depression is a leading cause of disability worldwide and, despite the availability of numerous antidepressants, the lack of standardized criteria to apply personalized prescription is still a major issue. Pharmacogenetic (PGx) markers in cytochrome P450 (CYP450) genes are already usable to guide antidepressant choice/titration according to clinical guidelines; they are an important step toward personalized psychiatry as they can reduce the time to identify an effective and tolerated treatment. Clinical application is still limited due to the financial and organizational challenges, but the number of services providing genotyping of pharmacogenes is increasing, with encouraging projections of cost-effectiveness. Critical aspects that emerged from the available studies are the importance of integration of genotyping results in electronic medical records, standardization, and regular updates of decision support systems, training and collaboration of different professionals, need of longer follow-ups to estimate cost-effectiveness, and importance of avoiding inequalities in access to genotyping. Diversities exist among the groups of patients to whom genotyping is offered (pre-emptive or reactive testing) and the type of clinical services (e.g., hospitals and primary care), currently without a consensus on which is the best approach. Future studies should aim to clarify these issues, as well as consider and compare PGx applications among different countries and healthcare systems. Finally, the extension of genotyping outside pharmacokinetic genes should be considered as a key step to improve the clinical impact of PGx, as this could significantly increase the variance explained in treatment outcomes.
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Affiliation(s)
- Raffaella Zanardi
- Department of Clinical Neurosciences, Mood Disorder Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Department of Clinical Neurosciences, University Vita-Salute San Raffaele, Milan, Italy
| | - Elena Manfredi
- Department of Clinical Neurosciences, University Vita-Salute San Raffaele, Milan, Italy
| | - Cristina Montrasio
- Unit of Clinical Pharmacology, ASST Fatebenefratelli Sacco University Hospital, Milan, Italy
| | - Cristina Colombo
- Department of Clinical Neurosciences, Mood Disorder Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Department of Clinical Neurosciences, University Vita-Salute San Raffaele, Milan, Italy
| | - Alessandro Serretti
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Chiara Fabbri
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.,Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
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49
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Implementation of Pharmacogenomics and Artificial Intelligence Tools for Chronic Disease Management in Primary Care Setting. J Pers Med 2021; 11:jpm11060443. [PMID: 34063850 PMCID: PMC8224063 DOI: 10.3390/jpm11060443] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 05/18/2021] [Accepted: 05/20/2021] [Indexed: 12/12/2022] Open
Abstract
Chronic disease management often requires use of multiple drug regimens that lead to polypharmacy challenges and suboptimal utilization of healthcare services. While the rising costs and healthcare utilization associated with polypharmacy and drug interactions have been well documented, effective tools to address these challenges remain elusive. Emerging evidence that proactive medication management, combined with pharmacogenomic testing, can lead to improved health outcomes and reduced cost burdens may help to address such gaps. In this report, we describe informatic and bioanalytic methodologies that integrate weak signals in symptoms and chief complaints with pharmacogenomic analysis of ~90 single nucleotide polymorphic variants, CYP2D6 copy number, and clinical pharmacokinetic profiles to monitor drug–gene pairs and drug–drug interactions for medications with significant pharmacogenomic profiles. The utility of the approach was validated in a virtual patient case showing detection of significant drug–gene and drug–drug interactions of clinical significance. This effort is being used to establish proof-of-concept for the creation of a regional database to track clinical outcomes in patients enrolled in a bioanalytically-informed medication management program. Our integrated informatic and bioanalytic platform can provide facile clinical decision support to inform and augment medication management in the primary care setting.
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50
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Lunenburg CATC, Thirstrup JP, Bybjerg-Grauholm J, Bækvad-Hansen M, Hougaard DM, Nordentoft M, Werge T, Børglum AD, Mors O, Mortensen PB, Gasse C. Pharmacogenetic genotype and phenotype frequencies in a large Danish population-based case-cohort sample. Transl Psychiatry 2021; 11:294. [PMID: 34006849 PMCID: PMC8131614 DOI: 10.1038/s41398-021-01417-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2021] [Revised: 04/20/2021] [Accepted: 05/04/2021] [Indexed: 12/23/2022] Open
Abstract
Pharmacogenetics aims to improve clinical care by studying the relationship between genetic variation and variable drug response. Large population-based datasets could improve our current understanding of pharmacogenetics from selected study populations. We provide real-world pharmacogenetic frequencies of genotypes and (combined) phenotypes of a large Danish population-based case-cohort sample (iPSYCH2012; data of the Integrative Psychiatric Research consortium). The genotyped sample consists of 77,684 individuals, of which 51,464 individuals had diagnoses of severe mental disorders (SMD case-cohort) and 26,220 were individuals randomly selected from the Danish population (population cohort). Array-based genotype data imputed to 8.4 million genetic variants was searched for a selected pharmacogenetic panel of 42 clinically relevant variants and a CYP2D6 gene deletion and duplication. We identified 19 of 42 variants. Minor allele frequencies (MAFs) were consistent with previously reported MAFs, and did not differ between SMD cases and population cohorts. Almost all individuals carried at least one genetic variant (> 99.9%) and 87% carried three or more genetic variants. When genotypes were translated into phenotypes, also > 99.9% of individuals had at least one divergent phenotype (i.e. divergent from the common phenotypes considered normal, e.g. extensive metabolizer). The high number of identified individuals with at least one pharmacogenetic variant or divergent phenotype indicates the importance of pharmacogenetic panel-based genotyping. Combined CYP2C19-CYP2D6 phenotypes revealed that 72.7% of individuals had divergent phenotypes for one or both enzymes. As CYP2D6 and CYP2C19 have an important role in the metabolism of psychotropic drugs, this indicates the relevance of pharmacogenetic testing specifically in individuals using psychotropic drugs.
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Affiliation(s)
- Carin A. T. C. Lunenburg
- grid.154185.c0000 0004 0512 597XDepartment of Affective Disorders, Aarhus University Hospital Psychiatry, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Janne P. Thirstrup
- grid.7048.b0000 0001 1956 2722Department of Biomedicine, Faculty of Health, Aarhus University, Aarhus, Denmark ,grid.452548.a0000 0000 9817 5300The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus/Copenhagen, Denmark ,grid.7048.b0000 0001 1956 2722Center for Genomics and Personalized Medicine, Aarhus University, Aarhus, Denmark
| | - Jonas Bybjerg-Grauholm
- grid.452548.a0000 0000 9817 5300The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus/Copenhagen, Denmark ,grid.6203.70000 0004 0417 4147Danish Center for Neonatal Screening, Statens Serum Institut, Copenhagen, Denmark
| | - Marie Bækvad-Hansen
- grid.6203.70000 0004 0417 4147Danish Center for Neonatal Screening, Statens Serum Institut, Copenhagen, Denmark
| | - David M. Hougaard
- grid.452548.a0000 0000 9817 5300The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus/Copenhagen, Denmark ,grid.6203.70000 0004 0417 4147Danish Center for Neonatal Screening, Statens Serum Institut, Copenhagen, Denmark
| | - Merete Nordentoft
- grid.452548.a0000 0000 9817 5300The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus/Copenhagen, Denmark ,grid.4973.90000 0004 0646 7373Mental Health Centre Copenhagen, Capital Region of Denmark, Copenhagen University Hospital, Copenhagen, Denmark
| | - Thomas Werge
- grid.452548.a0000 0000 9817 5300The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus/Copenhagen, Denmark ,grid.5254.60000 0001 0674 042XInstitute of Biological Psychiatry, Mental Health Services, Copenhagen University, Copenhagen, Denmark ,grid.5254.60000 0001 0674 042XDepartment of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark ,grid.5254.60000 0001 0674 042XLundbeck Foundation Center for GeoGenetics, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Anders D. Børglum
- grid.7048.b0000 0001 1956 2722Department of Biomedicine, Faculty of Health, Aarhus University, Aarhus, Denmark ,grid.452548.a0000 0000 9817 5300The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus/Copenhagen, Denmark ,grid.7048.b0000 0001 1956 2722Center for Genomics and Personalized Medicine, Aarhus University, Aarhus, Denmark
| | - Ole Mors
- grid.452548.a0000 0000 9817 5300The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus/Copenhagen, Denmark ,grid.154185.c0000 0004 0512 597XPsychosis Research Unit, Aarhus University Hospital Psychiatry, Aarhus, Denmark
| | - Preben B. Mortensen
- grid.452548.a0000 0000 9817 5300The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus/Copenhagen, Denmark ,grid.7048.b0000 0001 1956 2722NCRR National Centre for Register-Based Research, School of Business and Social Sciences, Aarhus University, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Centre for Integrated Register-based Research, CIRRAU, Aarhus University, Aarhus, Denmark
| | - Christiane Gasse
- Department of Affective Disorders, Aarhus University Hospital Psychiatry, Aarhus, Denmark. .,Department of Clinical Medicine, Aarhus University, Aarhus, Denmark. .,Psychosis Research Unit, Aarhus University Hospital Psychiatry, Aarhus, Denmark.
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