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Delabays B, Trajanoska K, Walonoski J, Mooser V. Cardiovascular Pharmacogenetics: From Discovery of Genetic Association to Clinical Adoption of Derived Test. Pharmacol Rev 2024; 76:791-827. [PMID: 39122647 DOI: 10.1124/pharmrev.123.000750] [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: 07/29/2023] [Revised: 04/24/2024] [Accepted: 05/28/2024] [Indexed: 08/12/2024] Open
Abstract
Recent breakthroughs in human genetics and in information technologies have markedly expanded our understanding at the molecular level of the response to drugs, i.e., pharmacogenetics (PGx), across therapy areas. This review is restricted to PGx for cardiovascular (CV) drugs. First, we examined the PGx information in the labels approved by regulatory agencies in Europe, Japan, and North America and related recommendations from expert panels. Out of 221 marketed CV drugs, 36 had PGx information in their labels approved by one or more agencies. The level of annotations and recommendations varied markedly between agencies and expert panels. Clopidogrel is the only CV drug with consistent PGx recommendation (i.e., "actionable"). This situation prompted us to dissect the steps from discovery of a PGx association to clinical translation. We found 101 genome-wide association studies that investigated the response to CV drugs or drug classes. These studies reported significant associations for 48 PGx traits mapping to 306 genes. Six of these 306 genes are mentioned in the corresponding PGx labels or recommendations for CV drugs. Genomic analyses also highlighted the wide between-population differences in risk allele frequencies and the individual load of actionable PGx variants. Given the high attrition rate and the long road to clinical translation, additional work is warranted to identify and validate PGx variants for more CV drugs across diverse populations and to demonstrate the utility of PGx testing. To that end, pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond. SIGNIFICANCE STATEMENT: Despite spectacular breakthroughs in human molecular genetics and information technologies, consistent evidence supporting PGx testing in the cardiovascular area is limited to a few drugs. Additional work is warranted to discover and validate new PGx markers and demonstrate their utility. Pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond.
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Affiliation(s)
- Benoît Delabays
- Canada Excellence Research Chair in Genomic Medicine, Victor Phillip Dahdaleh Institute of Genomic Medicine, Department of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC, Canada (B.D., K.T., V.M.); and Medeloop Inc., Palo Alto, California, and Montreal, QC, Canada (J.W.)
| | - Katerina Trajanoska
- Canada Excellence Research Chair in Genomic Medicine, Victor Phillip Dahdaleh Institute of Genomic Medicine, Department of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC, Canada (B.D., K.T., V.M.); and Medeloop Inc., Palo Alto, California, and Montreal, QC, Canada (J.W.)
| | - Joshua Walonoski
- Canada Excellence Research Chair in Genomic Medicine, Victor Phillip Dahdaleh Institute of Genomic Medicine, Department of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC, Canada (B.D., K.T., V.M.); and Medeloop Inc., Palo Alto, California, and Montreal, QC, Canada (J.W.)
| | - Vincent Mooser
- Canada Excellence Research Chair in Genomic Medicine, Victor Phillip Dahdaleh Institute of Genomic Medicine, Department of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC, Canada (B.D., K.T., V.M.); and Medeloop Inc., Palo Alto, California, and Montreal, QC, Canada (J.W.)
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2
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John S, Klumsathian S, Own‐eium P, Eu‐ahsunthornwattana J, Sura T, Dejsuphong D, Sritara P, Vathesatogkit P, Thongchompoo N, Thabthimthong W, Teerakulkittipong N, Chantratita W, Sukasem C. A comprehensive Thai pharmacogenomics database (TPGxD-1): Phenotype prediction and variants identification in 942 whole-genome sequencing data. Clin Transl Sci 2024; 17:e13830. [PMID: 38853370 PMCID: PMC11163017 DOI: 10.1111/cts.13830] [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: 01/23/2024] [Revised: 04/21/2024] [Accepted: 04/27/2024] [Indexed: 06/11/2024] Open
Abstract
Computational methods analyze genomic data to identify genetic variants linked to drug responses, thereby guiding personalized medicine. This study analyzed 942 whole-genome sequences from the Electricity Generating Authority of Thailand (EGAT) cohort to establish a population-specific pharmacogenomic database (TPGxD-1) in the Thai population. Sentieon (version 201808.08) implemented the GATK best workflow practice for variant calling. We then annotated variant call format (VCF) files using Golden Helix VarSeq 2.5.0 and employed Stargazer v2.0.2 for star allele analysis. The analysis of 63 very important pharmacogenes (VIPGx) reveals 85,566 variants, including 13,532 novel discoveries. Notably, we identified 464 known PGx variants and 275 clinically relevant novel variants. The phenotypic prediction of 15 VIPGx demonstrated a varied metabolic profile for the Thai population. Genes like CYP2C9 (9%), CYP3A5 (45.2%), CYP2B6 (9.4%), NUDT15 (15%), CYP2D6 (47%) and CYP2C19 (43%) showed a high number of intermediate metabolizers; CYP3A5 (41%), and CYP2C19 (9.9%) showed more poor metabolizers. CYP1A2 (52.7%) and CYP2B6 (7.6%) were found to have a higher number of ultra-metabolizers. The functional prediction of the remaining 10 VIPGx genes reveals a high frequency of decreased functional alleles in SULT1A1 (12%), NAT2 (84%), and G6PD (12%). SLCO1B1 reports 20% poor functional alleles, while PTGIS (42%), SLCO1B1 (4%), and TPMT (5.96%) showed increased functional alleles. This study discovered new variants and alleles in the 63 VIPGx genes among the Thai population, offering insights into advancing clinical pharmacogenomics (PGx). However, further validation is needed using other computational and genotyping methods.
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Affiliation(s)
- Shobana John
- Division of Pharmacogenomics and Personalized Medicine, Department of Pathology, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
- Laboratory for Pharmacogenomics, Somdech Phra Debaratana Medical Center (SDMC)Ramathibodi HospitalBangkokThailand
| | - Sommon Klumsathian
- Center for Medical Genomics, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
| | - Paravee Own‐eium
- Center for Medical Genomics, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
| | | | - Thanyachai Sura
- Division of Medical Genetics and Molecular Medicine, Department of Internal Medicine, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
| | - Donniphat Dejsuphong
- Program in Translational Medicine, Chakri Naruebodindra Medical Institute, Faculty of Medicine Ramathobodi HospitalMahidol UniversityBang PhliSamutprakarnThailand
| | - Piyamitr Sritara
- Department of Medicine, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
| | - Prin Vathesatogkit
- Department of Medicine, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
| | - Nartthawee Thongchompoo
- Center for Medical Genomics, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
| | - Wiphaporn Thabthimthong
- Center for Medical Genomics, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
| | - Nuttinee Teerakulkittipong
- Department of Pharmacology and Biopharmaceutical Sciences, Faculty of Pharmaceutical SciencesBurapha UniversityChonburiThailand
| | - Wasun Chantratita
- Center for Medical Genomics, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
| | - Chonlaphat Sukasem
- Division of Pharmacogenomics and Personalized Medicine, Department of Pathology, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
- Laboratory for Pharmacogenomics, Somdech Phra Debaratana Medical Center (SDMC)Ramathibodi HospitalBangkokThailand
- Department of Pharmacology and Biopharmaceutical Sciences, Faculty of Pharmaceutical SciencesBurapha UniversityChonburiThailand
- Department of Pharmacology and Therapeutics, MRC Centre for Drug Safety Science, Institute of Systems, Molecular and Integrative BiologyUniversity of LiverpoolLiverpoolUK
- Pharmacogenomics and Precision MedicineThe Preventive Genomics & Family Check‐up Services Center, Bumrungrad International HospitalBangkokThailand
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3
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Kanegusuku ALG, Chan CW, O'Donnell PH, Yeo KTJ. Implementation of pharmacogenomics testing for precision medicine. Crit Rev Clin Lab Sci 2024; 61:89-106. [PMID: 37776898 DOI: 10.1080/10408363.2023.2255279] [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: 01/31/2023] [Accepted: 08/31/2023] [Indexed: 10/02/2023]
Abstract
Great strides have been made in the past decade to lower barriers to clinical pharmacogenomics implementation. Nevertheless, PGx consultation prior to prescribing therapeutics is not yet mainstream. This review addresses the current climate surrounding PGx implementation, focusing primarily on strategies for implementation at academic institutions, particularly at The University of Chicago, and provides an up-to-date guide of resources supporting the development of PGx programs. Remaining challenges and recent strategies for overcoming these challenges to implementation are discussed.
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Affiliation(s)
| | - Clarence W Chan
- Departments of Pathology, The University of Chicago, Chicago, IL, USA
| | - Peter H O'Donnell
- Department of Medicine, The University of Chicago, Chicago, IL, USA
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, USA
| | - Kiang-Teck J Yeo
- Departments of Pathology, The University of Chicago, Chicago, IL, USA
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, USA
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Li LJ, Legeay S, Gagnon AL, Frigon MP, Tessier L, Tremblay K. Moving towards the implementation of pharmacogenetic testing in Quebec. Front Genet 2024; 14:1295963. [PMID: 38234998 PMCID: PMC10791884 DOI: 10.3389/fgene.2023.1295963] [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: 09/17/2023] [Accepted: 12/11/2023] [Indexed: 01/19/2024] Open
Abstract
Clinical implementation of pharmacogenetics (PGx) into routine care will elevate the current paradigm of treatment decisions. However, while PGx tests are increasingly becoming reliable and affordable, several barriers have limited their widespread usage in Canada. Globally, over ninety successful PGx implementors can serve as models. The purpose of this paper is to outline the PGx implementation barriers documented in Quebec (Canada) to suggest efficient solutions based on existing PGx clinics and propose an adapted clinical implementation model. We conclude that the province of Quebec is ready to implement PGx.
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Affiliation(s)
- Ling Jing Li
- Centre Intégré Universitaire de Santé et de Services Sociaux Du Saguenay-Lac-Saint-Jean (Chicoutimi University Hospital), Research Center, Saguenay, QC, Canada
- Medicine Department, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Saguenay, QC, Canada
| | - Samuel Legeay
- Centre Intégré Universitaire de Santé et de Services Sociaux Du Saguenay-Lac-Saint-Jean (Chicoutimi University Hospital), Research Center, Saguenay, QC, Canada
- Medicine Department, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Saguenay, QC, Canada
- University Angers, [CHU Angers], Inserm, CNRS, MINT, Angers, France
| | - Ann-Lorie Gagnon
- Centre Intégré Universitaire de Santé et de Services Sociaux Du Saguenay-Lac-Saint-Jean (Chicoutimi University Hospital), Research Center, Saguenay, QC, Canada
| | - Marie-Pier Frigon
- Centre Intégré Universitaire de Santé et de Services Sociaux Du Saguenay-Lac-Saint-Jean (Chicoutimi University Hospital), Research Center, Saguenay, QC, Canada
- Pediatrics Department, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Laurence Tessier
- Centre Intégré Universitaire de Santé et de Services Sociaux Du Saguenay-Lac-Saint-Jean (Chicoutimi University Hospital), Research Center, Saguenay, QC, Canada
- Pharmacology-Physiology Department, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Saguenay, QC, Canada
| | - Karine Tremblay
- Centre Intégré Universitaire de Santé et de Services Sociaux Du Saguenay-Lac-Saint-Jean (Chicoutimi University Hospital), Research Center, Saguenay, QC, Canada
- Pharmacology-Physiology Department, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Saguenay, QC, Canada
- Centre de Recherche Du Centre Hospitalier Universitaire de Sherbrooke (CR-CHUS), Sherbrooke, QC, Canada
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Deserranno K, Tilleman L, Rubben K, Deforce D, Van Nieuwerburgh F. Targeted haplotyping in pharmacogenomics using Oxford Nanopore Technologies' adaptive sampling. Front Pharmacol 2023; 14:1286764. [PMID: 38026945 PMCID: PMC10679755 DOI: 10.3389/fphar.2023.1286764] [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: 08/31/2023] [Accepted: 10/30/2023] [Indexed: 12/01/2023] Open
Abstract
Pharmacogenomics (PGx) studies the impact of interindividual genomic variation on drug response, allowing the opportunity to tailor the dosing regimen for each patient. Current targeted PGx testing platforms are mainly based on microarray, polymerase chain reaction, or short-read sequencing. Despite demonstrating great value for the identification of single nucleotide variants (SNVs) and insertion/deletions (INDELs), these assays do not permit identification of large structural variants, nor do they allow unambiguous haplotype phasing for star-allele assignment. Here, we used Oxford Nanopore Technologies' adaptive sampling to enrich a panel of 1,036 genes with well-documented PGx relevance extracted from the Pharmacogenomics Knowledge Base (PharmGKB). By evaluating concordance with existing truth sets, we demonstrate accurate variant and star-allele calling for five Genome in a Bottle reference samples. We show that up to three samples can be multiplexed on one PromethION flow cell without a significant drop in variant calling performance, resulting in 99.35% and 99.84% recall and precision for the targeted variants, respectively. This work advances the use of nanopore sequencing in clinical PGx settings.
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Affiliation(s)
| | | | | | | | - Filip Van Nieuwerburgh
- Laboratory of Pharmaceutical Biotechnology, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium
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Zheng P, Mo L, Zhao B, Li L, Cen B, Xu Z, Li Y. Pharmaceutical care model in precision medicine in China. FARMACIA HOSPITALARIA 2023; 47:T218-T223. [PMID: 37598018 DOI: 10.1016/j.farma.2023.07.004] [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: 11/27/2022] [Revised: 04/12/2023] [Accepted: 04/13/2023] [Indexed: 08/21/2023] Open
Abstract
Pharmacy service is to provide individualized pharmaceutical care for patients, which should follow the current evidence-based pharmacy, and constantly verify the evidence and then produce new evidence. In pharmaceutical care, differences are often found in the efficacy and adverse reactions of drugs among individuals, even within individuals, which are closely related to patients' genetics, liver and kidney functions, disease states, and drug interactions. Back in the 1980s, therapeutic drug monitoring (TDM) has been applied to routinely monitor the blood drug concentration of patients taking antiepileptic drugs or immunosuppressants after transplantation to provide individualized dosage recommendations and accumulate a large amount of pharmacokinetic (PK)/pharmacodynamic (PD) data. As individualized pharmaceutical care proceeds, the concept of precision medicine was introduced into pharmacy services in combination with evidence-based pharmacy, PK/PD theories, and big data to further promote the TDM technology and drugs, and carry out pharmacogenomics analysis. The TDM and pharmacogenomics have been applied gradually to the fields of antimicrobial, antitumor, and antipsychotic drugs and immunosuppressants. Based on the concept of precision pharmacy, we adopted approaches including PK/PD, quantitative pharmacology, population pharmacokinetics, and big data machine learning to provide more personalized pharmacy services, which is mainly for special patients, such as critical patients, patients with interaction risk of multiple drugs, patients with liver and renal insufficiency, pregnant women, children, and elderly patients. As the service pattern of precision pharmacy has been constructed and constantly improved, better evidence in clinical practice will be produced to provide patients with better precision pharmacy service.
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Affiliation(s)
- Ping Zheng
- Unidad de Farmacia Clínica, Hospital Nanfang, Universidad Médica del Sur, Guangzhou, China
| | - Liqian Mo
- Unidad de Farmacia Clínica, Hospital Nanfang, Universidad Médica del Sur, Guangzhou, China
| | - Boxin Zhao
- Unidad de Farmacia Clínica, Hospital Nanfang, Universidad Médica del Sur, Guangzhou, China
| | - Liren Li
- Unidad de Farmacia Clínica, Hospital Nanfang, Universidad Médica del Sur, Guangzhou, China
| | - Baihong Cen
- Unidad de Farmacia Clínica, Hospital Nanfang, Universidad Médica del Sur, Guangzhou, China
| | - Zhongyuan Xu
- Unidad de Farmacia Clínica, Hospital Nanfang, Universidad Médica del Sur, Guangzhou, China.
| | - Yilei Li
- Unidad de Farmacia Clínica, Hospital Nanfang, Universidad Médica del Sur, Guangzhou, China
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7
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Zheng P, Mo L, Zhao B, Li L, Cen B, Xu Z, Li Y. Pharmaceutical care model in precision medicine in China. FARMACIA HOSPITALARIA 2023; 47:218-223. [PMID: 37248115 DOI: 10.1016/j.farma.2023.04.005] [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: 11/27/2022] [Revised: 04/12/2023] [Accepted: 04/13/2023] [Indexed: 05/31/2023] Open
Abstract
Pharmacy service is to provide individualized pharmaceutical care for patients, which should follow the current evidence-based pharmacy, and constantly verify the evidence and then produce new evidence. In pharmaceutical care, differences are often found in the efficacy and adverse reactions of drugs among individuals, even within individuals, which are closely related to patient's genetics, liver and kidney functions, disease states, and drug interactions. Back in the 1980s, therapeutic drug monitoring (TDM) has been applied to routinely monitor the blood drug concentration of patients taking antiepileptic drugs or immunosuppressants after transplantation to provide individualized dosage recommendations and accumulate a large amount of pharmacokinetic (PK)/pharmacodynamic (PD) data. As individualized pharmaceutical care proceeds, the concept of precision medicine was introduced into pharmacy services in combination with evidence-based pharmacy, PK/PD theories and big data to further promote the TDM technology and drugs, and carry out pharmacogenomics analysis. The TDM and pharmacogenomics have been applied gradually to the fields of antimicrobial, antitumor and antipsychotic drugs and immunosuppressants. Based on the concept of precision pharmacy, we adpoted approaches including PK/PD, quantitative pharmacology, population pharmacokinetics, and big data machine learning to provide more personalized pharmacy services, which is mainly for special patients, such as critical patients, patients with interaction risk of multiple drugs, patients with liver and renal insufficiency, pregnant women, children and elderly patients. As the service pattern of precision pharmacy has been constructed and constantly improved, better evidence in clinical practice will be produced to provide patients with better precision pharmacy service.
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Affiliation(s)
- Ping Zheng
- Clinical Pharmacy Center, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhou Avenue North, Guangzhou City, Guangdong Province, China
| | - Liqian Mo
- Clinical Pharmacy Center, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhou Avenue North, Guangzhou City, Guangdong Province, China
| | - Boxin Zhao
- Clinical Pharmacy Center, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhou Avenue North, Guangzhou City, Guangdong Province, China
| | - Liren Li
- Clinical Pharmacy Center, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhou Avenue North, Guangzhou City, Guangdong Province, China
| | - Baihong Cen
- Clinical Pharmacy Center, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhou Avenue North, Guangzhou City, Guangdong Province, China
| | - Zhongyuan Xu
- Clinical Pharmacy Center, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhou Avenue North, Guangzhou City, Guangdong Province, China.
| | - Yilei Li
- Clinical Pharmacy Center, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhou Avenue North, Guangzhou City, Guangdong Province, China.
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Gentile G, De Luca O, Del Casale A, Salerno G, Simmaco M, Borro M. Frequencies of Combined Dysfunction of Cytochromes P450 2C9, 2C19, and 2D6 in an Italian Cohort: Suggestions for a More Appropriate Medication Prescribing Process. Int J Mol Sci 2023; 24:12696. [PMID: 37628884 PMCID: PMC10454797 DOI: 10.3390/ijms241612696] [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: 07/03/2023] [Revised: 08/07/2023] [Accepted: 08/10/2023] [Indexed: 08/27/2023] Open
Abstract
Improper drug prescription is a main cause of both drug-related harms (inefficacy and toxicity) and ineffective spending and waste of the healthcare system's resources. Nowadays, strategies to support an improved, informed prescription process may benefit from the adequate use of pharmacogenomic testing. Using next-generation sequencing, we analyzed the genomic profile for three major cytochromes P450 (CYP2C9, CYP2C19, CYP2D6) and studied the frequencies of dysfunctional isozymes (e.g., poor, intermediate, or rapid/ultra-rapid metabolizers) in a cohort of 298 Italian subjects. We found just 14.8% of subjects with a fully normal set of cytochromes, whereas 26.5% of subjects had combined cytochrome dysfunction (more than one isozyme involved). As improper drug prescription is more frequent, and more burdening, in polytreated patients, since drug-drug interactions also cause patient harm, we discuss the potential benefits of a more comprehensive PGX testing approach to support informed drug selection in such patients.
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Affiliation(s)
- Giovanna Gentile
- Department of Neurosciences, Mental Health and Sensory Organs (NESMOS), Sapienza University, Via di Grottarossa 1035/1039, 00189 Rome, Italy; (G.G.); (G.S.); (M.S.)
- Laboratory of Clinical Biochemistry, Advanced Molecular Diagnostic Unit, Sant’Andrea University Hospital, Via di Grottarossa 1035/1039, 00189 Rome, Italy
| | - Ottavia De Luca
- Laboratory of Clinical Biochemistry, Advanced Molecular Diagnostic Unit, Sant’Andrea University Hospital, Via di Grottarossa 1035/1039, 00189 Rome, Italy
| | - Antonio Del Casale
- Department of Dynamic and Clinical Psychology and Health Studies, Faculty of Medicine and Psychology, Sapienza University of Rome, 00189 Roma, Italy;
- Unit of Psychiatry, Sant’Andrea University Hospital, Via di Grottarossa 1035/1039, 00189 Rome, Italy
| | - Gerardo Salerno
- Department of Neurosciences, Mental Health and Sensory Organs (NESMOS), Sapienza University, Via di Grottarossa 1035/1039, 00189 Rome, Italy; (G.G.); (G.S.); (M.S.)
- Laboratory of Clinical Biochemistry, Advanced Molecular Diagnostic Unit, Sant’Andrea University Hospital, Via di Grottarossa 1035/1039, 00189 Rome, Italy
| | - Maurizio Simmaco
- Department of Neurosciences, Mental Health and Sensory Organs (NESMOS), Sapienza University, Via di Grottarossa 1035/1039, 00189 Rome, Italy; (G.G.); (G.S.); (M.S.)
- Laboratory of Clinical Biochemistry, Advanced Molecular Diagnostic Unit, Sant’Andrea University Hospital, Via di Grottarossa 1035/1039, 00189 Rome, Italy
| | - Marina Borro
- Department of Neurosciences, Mental Health and Sensory Organs (NESMOS), Sapienza University, Via di Grottarossa 1035/1039, 00189 Rome, Italy; (G.G.); (G.S.); (M.S.)
- Laboratory of Clinical Biochemistry, Advanced Molecular Diagnostic Unit, Sant’Andrea University Hospital, Via di Grottarossa 1035/1039, 00189 Rome, Italy
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Zeuli JD, Rivera CG, Wright JA, Kasten MJ, Mahmood M, Ragan AK, Rizza SA, Temesgen Z, Vergidis P, Wilson JW, Cummins NW. Pharmacogenomic panel testing provides insight and enhances medication management in people with HIV. AIDS 2023; 37:1525-1533. [PMID: 37199600 DOI: 10.1097/qad.0000000000003598] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
OBJECTIVE Our study aimed to assess the impact of pharmacogenomic panel testing in people with HIV (PWH). DESIGN Prospective, observational intervention assessment. METHODS One hundred PWH were provided a comprehensive pharmacogenomic panel during routine care visits within the HIV specialty clinic of a large academic medical center. The panel determined the presence of specific genetic variants that could predict response or toxicity to commonly prescribed antiretroviral therapy (ART) and non-ART medications. An HIV specialty pharmacist reviewed the results with participants and the care team. The pharmacist (1) recommended clinically actionable interventions based on the participants' current drug therapy, (2) assessed for genetic explanations for prior medication failures, adverse effects, or intolerances, and (3) advised on potential future clinically actionable care interventions based on individual genetic phenotypes. RESULTS Ninety-six participants (median age 53 years, 74% white, 84% men, 89% viral load <50 copies/ml) completed panel testing, yielding 682 clinically relevant pharmacogenomic results (133 major, 549 mild-moderate). Ninety participants (89 on ART) completed follow-up visits with 65 (72%) receiving clinical recommendations based on current medication profiles. Of the 105 clinical recommendations, 70% advised additional monitoring for efficacy or toxicity, and 10% advised alteration of drug therapy. Panel results offered explanation for prior ART inefficacy in one participant and ART intolerance in 29%. Genetic explanation for non-ART toxicity was seen in 21% of participants, with genetic contributors to inefficacy of non-ART therapy identified in 39% of participants. CONCLUSION Preliminary data in a small cohort of PWH demonstrates benefit of routine pharmacogenomic panel testing.
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Affiliation(s)
- John D Zeuli
- Department of Pharmacy
- Section of Infectious Diseases
| | | | - Jessica A Wright
- Department of Pharmacy
- Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota, USA
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Montrasio C, Cheli S, Clementi E. Pharmacogenetic Practice of Anticancer Drugs: Multiple Approaches for an Accurate and Comprehensive Genotyping. Pharmgenomics Pers Med 2023; 16:739-746. [PMID: 37534027 PMCID: PMC10390719 DOI: 10.2147/pgpm.s412430] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 06/19/2023] [Indexed: 08/04/2023] Open
Abstract
The application of pharmacogenetics in oncology is part of the routine clinical practice. In particular, genotyping of dihydropyrimidine dehydrogenase (DPYD) and UDP-glucuronosyltransferase (UGT1A1) is crucial to manage the treatment of patients taking fluoropyrimidines and irinotecan. The unique approach of our laboratory to the pharmacogenetic diagnostic service in oncology is to combine two real-time PCR methods, LightSNiP assay (TIB MOLBIOL), and more recently FRET (Fluorescent Resonance Energy Transfer) probes technology (Nuclear Laser Medicine), plus TaqMan assay (Thermo Fisher) for the confirmation of the presence of variant alleles on DNA from a second extraction. We found that both the FRET and LightSNiP assays, where detection occurs by melting curve analysis, offer an advantage over the competing TaqMan technology. Whereas unexpected genetic variants may be missed using a mutation-specific TaqMan assay, the information thus obtained can be useful to adjust the therapy in case of unexpected post-treatment toxicity. The combination of TaqMan and FRET assays helped us to achieve more accurate genotyping and a correct result for the patient. The added value of the DPYD FRET assay is the possibility of detecting, with the same amplification profile of the polymorphisms detailed in the guidelines, also the c.2194G>A (*6 rs1801160), cited in the recommendations as a variant to be investigated in case of severe toxicity. Regarding the UGT1A1 (TA)n promoter polymorphism (rs3064744), the distinctive and positive feature of the FRET assay is to allow clearly identifying all those potential variant alleles, including the (TA)5 and (TA)8 alleles, that are frequent in African Americans. Our clinical practice emphasizes the importance of not only rapid and easy-to-use assays, such as the new FRET ones, but also of accurate and comprehensive genotyping for good pharmacogenetic diagnostic activity.
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Affiliation(s)
- Cristina Montrasio
- Unit of Clinical Pharmacology, ASST Fatebenefratelli Sacco, L. Sacco University Hospital, Milan, Italy
| | - Stefania Cheli
- Unit of Clinical Pharmacology, ASST Fatebenefratelli Sacco, L. Sacco University Hospital, Milan, Italy
| | - Emilio Clementi
- Clinical Pharmacology Unit, Department of Biomedical and Clinical Sciences, L. Sacco University Hospital, Università degli Studi di Milano, Milan, Italy
- Scientific Institute IRCCS Eugenio Medea, Bosisio Parini, Italy
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Tafazoli A, Mikros J, Khaghani F, Alimardani M, Rafigh M, Hemmati M, Siamoglou S, Golińska AK, Kamiński KA, Niemira M, Miltyk W, Patrinos GP. Pharmacovariome scanning using whole pharmacogene resequencing coupled with deep computational analysis and machine learning for clinical pharmacogenomics. Hum Genomics 2023; 17:62. [PMID: 37452347 PMCID: PMC10347842 DOI: 10.1186/s40246-023-00508-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 07/03/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND This pilot study aims to identify and functionally assess pharmacovariants in whole exome sequencing data. While detection of known variants has benefited from pharmacogenomic-dedicated bioinformatics tools before, in this paper we have tested novel deep computational analysis in addition to artificial intelligence as possible approaches for functional analysis of unknown markers within less studied drug-related genes. METHODS Pharmacovariants from 1800 drug-related genes from 100 WES data files underwent (a) deep computational analysis by eight bioinformatic algorithms (overall containing 23 tools) and (b) random forest (RF) classifier as the machine learning (ML) approach separately. ML model efficiency was calculated by internal and external cross-validation during recursive feature elimination. Protein modelling was also performed for predicted highly damaging variants with lower frequencies. Genotype-phenotype correlations were implemented for top selected variants in terms of highest possibility of being damaging. RESULTS Five deleterious pharmacovariants in the RYR1, POLG, ANXA11, CCNH, and CDH23 genes identified in step (a) and subsequent analysis displayed high impact on drug-related phenotypes. Also, the utilization of recursive feature elimination achieved a subset of 175 malfunction pharmacovariants in 135 drug-related genes that were used by the RF model with fivefold internal cross-validation, resulting in an area under the curve of 0.9736842 with an average accuracy of 0.9818 (95% CI: 0.89, 0.99) on predicting whether a carrying individuals will develop adverse drug reactions or not. However, the external cross-validation of the same model indicated a possible false positive result when dealing with a low number of observations, as only 60 important variants in 49 genes were displayed, giving an AUC of 0.5384848 with an average accuracy of 0.9512 (95% CI: 0.83, 0.99). CONCLUSION While there are some technologies for functionally assess not-interpreted pharmacovariants, there is still an essential need for the development of tools, methods, and algorithms which are able to provide a functional prediction for every single pharmacovariant in both large-scale datasets and small cohorts. Our approaches may bring new insights for choosing the right computational assessment algorithms out of high throughput DNA sequencing data from small cohorts to be used for personalized drug therapy implementation.
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Affiliation(s)
- Alireza Tafazoli
- Department of Analysis and Bioanalysis of Medicines, Faculty of Pharmacy With the Division of Laboratory Medicine, Medical University of Bialystok, 15-089, Białystok, Poland
- Laboratory of Pharmacogenomics, Department of Molecular Neuropharmacology, Maj Institute of Pharmacology Polish Academy of Sciences, Kraków, Poland
| | - John Mikros
- Laboratory of Pharmacogenomics and Individualized Therapy, Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece
| | - Faeze Khaghani
- Department of Pharmaceutical Biotechnology, School of Pharmacy, Guilan University of Medical Sciences, Rasht, Iran
| | - Maliheh Alimardani
- Department of Medical Genetics and Molecular Medicine, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Mahboobeh Rafigh
- Medical Genetics Research Center, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Mahboobeh Hemmati
- Department of Medical Genetics and Molecular Medicine, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Stavroula Siamoglou
- Laboratory of Pharmacogenomics and Individualized Therapy, Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece
| | | | - Karol A Kamiński
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Białystok, Poland
- Department of Cardiology, Medical University of Bialystok, Białystok, Poland
| | - Magdalena Niemira
- Clinical Research Centre, Medical University of Bialystok, Białystok, Poland
| | - Wojciech Miltyk
- Department of Analysis and Bioanalysis of Medicines, Faculty of Pharmacy With the Division of Laboratory Medicine, Medical University of Bialystok, 15-089, Białystok, Poland.
| | - George P Patrinos
- Laboratory of Pharmacogenomics and Individualized Therapy, Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece.
- Zayed Center for Health Sciences, United Arab Emirates University, Al-Ain, United Arab Emirates.
- Department of Genetics and Genomics, College of Medicine and Health Sciences, United Arab Emirates University, Al-Ain, United Arab Emirates.
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Shugg T, Ly RC, Osei W, Rowe EJ, Granfield CA, Lynnes TC, Medeiros EB, Hodge JC, Breman AM, Schneider BP, Sahinalp SC, Numanagić I, Salisbury BA, Bray SM, Ratcliff R, Skaar TC. Computational pharmacogenotype extraction from clinical next-generation sequencing. Front Oncol 2023; 13:1199741. [PMID: 37469403 PMCID: PMC10352904 DOI: 10.3389/fonc.2023.1199741] [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: 04/03/2023] [Accepted: 05/22/2023] [Indexed: 07/21/2023] Open
Abstract
Background Next-generation sequencing (NGS), including whole genome sequencing (WGS) and whole exome sequencing (WES), is increasingly being used for clinic care. While NGS data have the potential to be repurposed to support clinical pharmacogenomics (PGx), current computational approaches have not been widely validated using clinical data. In this study, we assessed the accuracy of the Aldy computational method to extract PGx genotypes from WGS and WES data for 14 and 13 major pharmacogenes, respectively. Methods Germline DNA was isolated from whole blood samples collected for 264 patients seen at our institutional molecular solid tumor board. DNA was used for panel-based genotyping within our institutional Clinical Laboratory Improvement Amendments- (CLIA-) certified PGx laboratory. DNA was also sent to other CLIA-certified commercial laboratories for clinical WGS or WES. Aldy v3.3 and v4.4 were used to extract PGx genotypes from these NGS data, and results were compared to the panel-based genotyping reference standard that contained 45 star allele-defining variants within CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP4F2, DPYD, G6PD, NUDT15, SLCO1B1, TPMT, and VKORC1. Results Mean WGS read depth was >30x for all variant regions except for G6PD (average read depth was 29 reads), and mean WES read depth was >30x for all variant regions. For 94 patients with WGS, Aldy v3.3 diplotype calls were concordant with those from the genotyping reference standard in 99.5% of cases when excluding diplotypes with additional major star alleles not tested by targeted genotyping, ambiguous phasing, and CYP2D6 hybrid alleles. Aldy v3.3 identified 15 additional clinically actionable star alleles not covered by genotyping within CYP2B6, CYP2C19, DPYD, SLCO1B1, and NUDT15. Within the WGS cohort, Aldy v4.4 diplotype calls were concordant with those from genotyping in 99.7% of cases. When excluding patients with CYP2D6 copy number variation, all Aldy v4.4 diplotype calls except for one CYP3A4 diplotype call were concordant with genotyping for 161 patients in the WES cohort. Conclusion Aldy v3.3 and v4.4 called diplotypes for major pharmacogenes from clinical WES and WGS data with >99% accuracy. These findings support the use of Aldy to repurpose clinical NGS data to inform clinical PGx.
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Affiliation(s)
- Tyler Shugg
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Reynold C. Ly
- Division of Diagnostic Genetics and Genomics, Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Wilberforce Osei
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Elizabeth J. Rowe
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Caitlin A. Granfield
- Division of Diagnostic Genetics and Genomics, Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Ty C. Lynnes
- Division of Diagnostic Genetics and Genomics, Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Elizabeth B. Medeiros
- Division of Diagnostic Genetics and Genomics, Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Jennelle C. Hodge
- Division of Diagnostic Genetics and Genomics, Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Amy M. Breman
- Division of Diagnostic Genetics and Genomics, Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Bryan P. Schneider
- Division of Hematology/Oncology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States
| | - S. Cenk Sahinalp
- Center for Cancer Research, National Cancer Institute, National Institute of Health, Bethesda, MD, United States
| | - Ibrahim Numanagić
- Department of Computer Science, University of Victoria, Victoria, BC, Canada
| | | | | | | | - Todd C. Skaar
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States
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13
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Maslarinou A, Manolopoulos VG, Ragia G. Pharmacogenomic-guided dosing of fluoropyrimidines beyond DPYD: time for a polygenic algorithm? Front Pharmacol 2023; 14:1184523. [PMID: 37256234 PMCID: PMC10226670 DOI: 10.3389/fphar.2023.1184523] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Accepted: 04/19/2023] [Indexed: 06/01/2023] Open
Abstract
Fluoropyrimidines are chemotherapeutic agents widely used for the treatment of various solid tumors. Commonly prescribed FPs include 5-fluorouracil (5-FU) and its oral prodrugs capecitabine (CAP) and tegafur. Bioconversion of 5-FU prodrugs to 5-FU and subsequent metabolic activation of 5-FU are required for the formation of fluorodeoxyuridine triphosphate (FdUTP) and fluorouridine triphosphate, the active nucleotides through which 5-FU exerts its antimetabolite actions. A significant proportion of FP-treated patients develop severe or life-threatening, even fatal, toxicity. It is well known that FP-induced toxicity is governed by genetic factors, with dihydropyrimidine dehydrogenase (DPYD), the rate limiting enzyme in 5-FU catabolism, being currently the cornerstone of FP pharmacogenomics. DPYD-based dosing guidelines exist to guide FP chemotherapy suggesting significant dose reductions in DPYD defective patients. Accumulated evidence shows that additional variations in other genes implicated in FP pharmacokinetics and pharmacodynamics increase risk for FP toxicity, therefore taking into account more gene variations in FP dosing guidelines holds promise to improve FP pharmacotherapy. In this review we describe the current knowledge on pharmacogenomics of FP-related genes, beyond DPYD, focusing on FP toxicity risk and genetic effects on FP dose reductions. We propose that in the future, FP dosing guidelines may be expanded to include a broader ethnicity-based genetic panel as well as gene*gene and gender*gene interactions towards safer FP prescription.
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Affiliation(s)
- Anthi Maslarinou
- Laboratory of Pharmacology, Medical School, Democritus University of Thrace, Alexandroupolis, Greece
- Individualised Medicine and Pharmacological Research Solutions Center, Alexandroupolis, Greece
| | - Vangelis G. Manolopoulos
- Laboratory of Pharmacology, Medical School, Democritus University of Thrace, Alexandroupolis, Greece
- Individualised Medicine and Pharmacological Research Solutions Center, Alexandroupolis, Greece
- Clinical Pharmacology Unit, Academic General Hospital of Alexandroupolis, Alexandroupolis, Greece
| | - Georgia Ragia
- Laboratory of Pharmacology, Medical School, Democritus University of Thrace, Alexandroupolis, Greece
- Individualised Medicine and Pharmacological Research Solutions Center, Alexandroupolis, Greece
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14
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Pharmacokinetic Markers of Clinical Outcomes in Severe Mental Illness: A Systematic Review. Int J Mol Sci 2023; 24:ijms24054776. [PMID: 36902205 PMCID: PMC10003720 DOI: 10.3390/ijms24054776] [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: 01/13/2023] [Revised: 02/20/2023] [Accepted: 02/27/2023] [Indexed: 03/06/2023] Open
Abstract
The term severe mental illness (SMI) encompasses those psychiatric disorders exerting the highest clinical burden and socio-economic impact on the affected individuals and their communities. Pharmacogenomic (PGx) approaches hold great promise in personalizing treatment selection and clinical outcomes, possibly reducing the burden of SMI. Here, we sought to review the literature in the field, focusing on PGx testing and particularly on pharmacokinetic markers. We performed a systematic review on PUBMED/Medline, Web of Science, and Scopus. The last search was performed on the 17 September 2022, and further augmented with a comprehensive pearl-growing strategy. In total, 1979 records were screened, and after duplicate removal, 587 unique records were screened by at least 2 independent reviewers. Ultimately, forty-two articles were included in the qualitative analysis, eleven randomized controlled trials and thirty-one nonrandomized studies. The observed lack of standardization in PGx tests, population selection, and tested outcomes limit the overall interpretation of the available evidence. A growing body of evidence suggests that PGx testing might be cost-effective in specific settings and may modestly improve clinical outcomes. More efforts need to be directed toward improving PGx standardization, knowledge for all stakeholders, and clinical practice guidelines for screening recommendations.
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15
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Ibañez-Lligoña M, Colomer-Castell S, González-Sánchez A, Gregori J, Campos C, Garcia-Cehic D, Andrés C, Piñana M, Pumarola T, Rodríguez-Frias F, Antón A, Quer J. Bioinformatic Tools for NGS-Based Metagenomics to Improve the Clinical Diagnosis of Emerging, Re-Emerging and New Viruses. Viruses 2023; 15:v15020587. [PMID: 36851800 PMCID: PMC9965957 DOI: 10.3390/v15020587] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 02/16/2023] [Accepted: 02/17/2023] [Indexed: 02/24/2023] Open
Abstract
Epidemics and pandemics have occurred since the beginning of time, resulting in millions of deaths. Many such disease outbreaks are caused by viruses. Some viruses, particularly RNA viruses, are characterized by their high genetic variability, and this can affect certain phenotypic features: tropism, antigenicity, and susceptibility to antiviral drugs, vaccines, and the host immune response. The best strategy to face the emergence of new infectious genomes is prompt identification. However, currently available diagnostic tests are often limited for detecting new agents. High-throughput next-generation sequencing technologies based on metagenomics may be the solution to detect new infectious genomes and properly diagnose certain diseases. Metagenomic techniques enable the identification and characterization of disease-causing agents, but they require a large amount of genetic material and involve complex bioinformatic analyses. A wide variety of analytical tools can be used in the quality control and pre-processing of metagenomic data, filtering of untargeted sequences, assembly and quality control of reads, and taxonomic profiling of sequences to identify new viruses and ones that have been sequenced and uploaded to dedicated databases. Although there have been huge advances in the field of metagenomics, there is still a lack of consensus about which of the various approaches should be used for specific data analysis tasks. In this review, we provide some background on the study of viral infections, describe the contribution of metagenomics to this field, and place special emphasis on the bioinformatic tools (with their capabilities and limitations) available for use in metagenomic analyses of viral pathogens.
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Affiliation(s)
- Marta Ibañez-Lligoña
- Liver Diseases-Viral Hepatitis, Liver Unit, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Av. Monforte de Lemos, 3-5, 28029 Madrid, Spain
- Biochemistry and Molecular Biology Department, Universitat Autònoma de Barcelona (UAB), Campus de la UAB, Plaça Cívica, 08193 Bellaterra, Spain
| | - Sergi Colomer-Castell
- Liver Diseases-Viral Hepatitis, Liver Unit, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Av. Monforte de Lemos, 3-5, 28029 Madrid, Spain
- Biochemistry and Molecular Biology Department, Universitat Autònoma de Barcelona (UAB), Campus de la UAB, Plaça Cívica, 08193 Bellaterra, Spain
| | - Alejandra González-Sánchez
- Microbiology Department, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
| | - Josep Gregori
- Liver Diseases-Viral Hepatitis, Liver Unit, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
| | - Carolina Campos
- Liver Diseases-Viral Hepatitis, Liver Unit, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Av. Monforte de Lemos, 3-5, 28029 Madrid, Spain
- Biochemistry and Molecular Biology Department, Universitat Autònoma de Barcelona (UAB), Campus de la UAB, Plaça Cívica, 08193 Bellaterra, Spain
| | - Damir Garcia-Cehic
- Liver Diseases-Viral Hepatitis, Liver Unit, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Av. Monforte de Lemos, 3-5, 28029 Madrid, Spain
| | - Cristina Andrés
- Microbiology Department, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
| | - Maria Piñana
- Microbiology Department, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
| | - Tomàs Pumarola
- Microbiology Department, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
- Microbiology Department, Universitat Autònoma de Barcelona (UAB), Campus de la UAB, Plaça Cívica, 08193 Bellaterra, Spain
| | - Francisco Rodríguez-Frias
- Liver Diseases-Viral Hepatitis, Liver Unit, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Av. Monforte de Lemos, 3-5, 28029 Madrid, Spain
- Department of Basic Sciences, Universitat Internacional de Catalunya, Sant Cugat del Vallès, 08195 Barcelona, Spain
| | - Andrés Antón
- Microbiology Department, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
- Microbiology Department, Universitat Autònoma de Barcelona (UAB), Campus de la UAB, Plaça Cívica, 08193 Bellaterra, Spain
| | - Josep Quer
- Liver Diseases-Viral Hepatitis, Liver Unit, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Av. Monforte de Lemos, 3-5, 28029 Madrid, Spain
- Biochemistry and Molecular Biology Department, Universitat Autònoma de Barcelona (UAB), Campus de la UAB, Plaça Cívica, 08193 Bellaterra, Spain
- Correspondence:
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16
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Liu Y, Lin Z, Chen Q, Chen Q, Sang L, Wang Y, Shi L, Guo L, Yu Y. PAnno: A pharmacogenomics annotation tool for clinical genomic testing. Front Pharmacol 2023; 14:1008330. [PMID: 36778023 PMCID: PMC9909284 DOI: 10.3389/fphar.2023.1008330] [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: 07/31/2022] [Accepted: 01/16/2023] [Indexed: 01/27/2023] Open
Abstract
Introduction: Next-generation sequencing (NGS) technologies have been widely used in clinical genomic testing for drug response phenotypes. However, the inherent limitations of short reads make accurate inference of diplotypes still challenging, which may reduce the effectiveness of genotype-guided drug therapy. Methods: An automated Pharmacogenomics Annotation tool (PAnno) was implemented, which reports prescribing recommendations and phenotypes by parsing the germline variant call format (VCF) file from NGS and the population to which the individual belongs. Results: A ranking model dedicated to inferring diplotypes, developed based on the allele (haplotype) definition and population allele frequency, was introduced in PAnno. The predictive performance was validated in comparison with four similar tools using the consensus diplotype data of the Genetic Testing Reference Materials Coordination Program (GeT-RM) as ground truth. An annotation method was proposed to summarize prescribing recommendations and classify drugs into avoid use, use with caution, and routine use, following the recommendations of the Clinical Pharmacogenetics Implementation Consortium (CPIC), etc. It further predicts phenotypes of specific drugs in terms of toxicity, dosage, efficacy, and metabolism by integrating the high-confidence clinical annotations in the Pharmacogenomics Knowledgebase (PharmGKB). PAnno is available at https://github.com/PreMedKB/PAnno. Discussion: PAnno provides an end-to-end clinical pharmacogenomics decision support solution by resolving, annotating, and reporting germline variants.
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Affiliation(s)
- Yaqing Liu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Zipeng Lin
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Qingwang Chen
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Qiaochu Chen
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Leqing Sang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Yunjin Wang
- Department of Breast Surgery, Precision Cancer Medicine Center, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Shanghai, China,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Leming Shi
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Li Guo
- State Key Laboratory of Multiphase Complex Systems, Institute of Process Engineering, Chinese Academy of Sciences, Beijing, China,School of Chemical Engineering, University of Chinese Academy of Sciences, Beijing, China,*Correspondence: Li Guo, ; Ying Yu,
| | - Ying Yu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, China,*Correspondence: Li Guo, ; Ying Yu,
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17
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Zhou Y, Lauschke VM. Challenges Related to the Use of Next-Generation Sequencing for the Optimization of Drug Therapy. Handb Exp Pharmacol 2023; 280:237-260. [PMID: 35792943 DOI: 10.1007/164_2022_596] [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: 06/15/2023]
Abstract
Over the last decade, next-generation sequencing (NGS) methods have become increasingly used in various areas of human genomics. In routine clinical care, their use is already implemented in oncology to profile the mutational landscape of a tumor, as well as in rare disease diagnostics. However, its utilization in pharmacogenomics is largely lacking behind. Recent population-scale genome data has revealed that human pharmacogenes carry a plethora of rare genetic variations that are not interrogated by conventional array-based profiling methods and it is estimated that these variants could explain around 30% of the genetically encoded functional pharmacogenetic variability.To interpret the impact of such variants on drug response a multitude of computational tools have been developed, but, while there have been major advancements, it remains to be shown whether their accuracy is sufficient to improve personalized pharmacogenetic recommendations in robust trials. In addition, conventional short-read sequencing methods face difficulties in the interrogation of complex pharmacogenes and high NGS test costs require stringent evaluations of cost-effectiveness to decide about reimbursement by national healthcare programs. Here, we illustrate current challenges and discuss future directions toward the clinical implementation of NGS to inform genotype-guided decision-making.
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Affiliation(s)
- Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.
- University of Tuebingen, Tuebingen, Germany.
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18
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Graansma LJ, Zhai Q, Busscher L, Menafra R, van den Berg RR, Kloet SL, van der Lee M. From gene to dose: Long-read sequencing and *-allele tools to refine phenotype predictions of CYP2C19. Front Pharmacol 2023; 14:1076574. [PMID: 36937863 PMCID: PMC10014917 DOI: 10.3389/fphar.2023.1076574] [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: 10/21/2022] [Accepted: 01/31/2023] [Indexed: 03/06/2023] Open
Abstract
Background: Inter-individual differences in drug response based on genetic variations can lead to drug toxicity and treatment inefficacy. A large part of this variability is caused by genetic variants in pharmacogenes. Unfortunately, the Single Nucleotide Variant arrays currently used in clinical pharmacogenomic (PGx) testing are unable to detect all genetic variability in these genes. Long-read sequencing, on the other hand, has been shown to be able to resolve complex (pharmaco) genes. In this study we aimed to assess the value of long-read sequencing for research and clinical PGx focusing on the important and highly polymorphic CYP2C19 gene. Methods and Results: With a capture-based long-read sequencing panel we were able to characterize the entire region and assign variants to their allele of origin (phasing), resulting in the identification of 813 unique variants in 37 samples. To assess the clinical utility of this data we have compared the performance of three different *-allele tools (Aldy, PharmCat and PharmaKU) which are specifically designed to assign haplotypes to pharmacogenes based on all input variants. Conclusion: We conclude that long-read sequencing can improve our ability to characterize the CYP2C19 locus, help to identify novel haplotypes and that *-allele tools are a useful asset in phenotype prediction. Ultimately, this approach could help to better predict an individual's drug response and improve therapy outcomes. However, the added value in clinical PGx might currently be limited.
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Affiliation(s)
- Lonneke J. Graansma
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, Netherlands
| | - Qinglian Zhai
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, Netherlands
| | - Loes Busscher
- Leiden Genome Technology Center, Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
| | - Roberta Menafra
- Leiden Genome Technology Center, Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
| | - Redmar R. van den Berg
- Leiden Genome Technology Center, Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
| | - Susan L. Kloet
- Leiden Genome Technology Center, Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
| | - Maaike van der Lee
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, Netherlands
- *Correspondence: Maaike van der Lee,
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Tafazoli A, van der Lee M, Swen JJ, Zeller A, Wawrusiewicz-Kurylonek N, Mei H, Vorderman RHP, Konopko K, Zankiewicz A, Miltyk W. Development of an extensive workflow for comprehensive clinical pharmacogenomic profiling: lessons from a pilot study on 100 whole exome sequencing data. THE PHARMACOGENOMICS JOURNAL 2022; 22:276-283. [PMID: 35963939 PMCID: PMC9674517 DOI: 10.1038/s41397-022-00286-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 07/20/2022] [Accepted: 07/25/2022] [Indexed: 06/15/2023]
Abstract
This pilot study is aimed at implementing an approach for comprehensive clinical pharmacogenomics (PGx) profiling. Fifty patients with cardiovascular diseases and 50 healthy individuals underwent whole-exome sequencing. Data on 1800 PGx genes were extracted and analyzed through deep filtration separately. Theoretical drug induced phenoconversion was assessed for the patients, using sequence2script. In total, 4539 rare variants (including 115 damaging non-synonymous) were identified. Four publicly available PGx bioinformatics algorithms to assign PGx haplotypes were applied to nine selected very important pharmacogenes (VIP) and revealed a 45-70% concordance rate. To ensure availability of the results at point-of-care, actionable variants were stored in a web-hosted database and PGx-cards were developed for quick access and handed to the study subjects. While a comprehensive clinical PGx profile could be successfully extracted from WES data, available tools to interpret these data demonstrated inconsistencies that complicate clinical application.
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Affiliation(s)
- Alireza Tafazoli
- Department of Analysis and Bioanalysis of Medicines, Faculty of Pharmacy with the Division of Laboratory Medicine, Medical University of Bialystok, 15-089, Bialystok, Poland
- Clinical Research Centre, University Hospital of Bialystok, 15-276, Bialystok, Poland
| | - Maaike van der Lee
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Jesse J Swen
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Anna Zeller
- Clinical Research Centre, University Hospital of Bialystok, 15-276, Bialystok, Poland
| | | | - Hailiang Mei
- Sequencing Analysis Support Core, Department of Biomedical Data Sciences, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Ruben H P Vorderman
- Sequencing Analysis Support Core, Department of Biomedical Data Sciences, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Krzysztof Konopko
- Department of Photonics, Electronics, and Lighting Technology, Faculty of Electrical Engineering, Bialystok University of Technology, 15-351, Bialystok, Poland
| | - Andrzej Zankiewicz
- Department of Photonics, Electronics, and Lighting Technology, Faculty of Electrical Engineering, Bialystok University of Technology, 15-351, Bialystok, Poland
| | - Wojciech Miltyk
- Department of Analysis and Bioanalysis of Medicines, Faculty of Pharmacy with the Division of Laboratory Medicine, Medical University of Bialystok, 15-089, Bialystok, Poland.
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Alhaddad ZA, AlMousa HA, Younis NS. Pharmacists' Knowledge, and Insights in Implementing Pharmacogenomics in Saudi Arabia. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:10073. [PMID: 36011723 PMCID: PMC9407761 DOI: 10.3390/ijerph191610073] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 08/05/2022] [Accepted: 08/11/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Pharmacogenomics (PGx) and personalized medicine embrace the potential to optimize drug treatment and improve the patient's quality of life. Pharmacists' roles include contributing to genetic testing, patient counseling, and pharmacotherapies selection for superior treatment outcomes. The aim of this study is to assess the pharmacists' knowledge, insight, and self-confidence toward PGx testing, identify their future preferred education patterns, and determine the barriers to pharmacogenomic testing implementation. METHOD A cross-sectional study was conducted using a previously validated questionnaire among pharmacists working in the Kingdom of Saudi Arabia (KSA). The questionnaire was designed in seven major categories, consisting of 26 questions. RESULTS A total of 671 pharmacists participated in this survey. As for knowledge, only 29.8% of pharmacists had good knowledge regarding PGx, while 42.9% had poor knowledge levels. Respectable PGx knowledge was significantly higher among outpatient dispensing pharmacists (33.6%; p = 0.049) and among pharmacists who had completed PGx testing-related training or education (40.3%; p = 0.001). Considering perception, it was positive among 50% of pharmacists and negative among 19.8%. With regard to self-confidence, it was high among 39.2% of male pharmacists (p = 0.042), among 43% of clinical pharmacists (p = 0.006), and among 44.8% of pharmacists who had extra credentials (p = 0.001). The utmost favored continuing-education learning approaches were workshops or seminars. The barriers to the implementation of PGx testing included a lack of testing devices, clinical guidelines, training or education, and personnel. CONCLUSION The present study revealed that pharmacists in KSA had inadequate knowledge and understanding of PGx. Nevertheless, the majority established that PGx is a valuable tool for augmenting drug efficacy and safety.
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Silver A, Lazarin GA, Silver M, Miller M, Jansen M, Wechsberg C, Dekanek E, Grossfeld S, Herpel T, Gunatilake D, Bisignano A, Jaremko M. Technical Performance of a 430-Gene Preventative Genomics Assay to Identify Multiple Variant Types Associated with Adult-Onset Monogenic Conditions, Susceptibility Loci, and Pharmacogenetic Insights. J Pers Med 2022; 12:667. [PMID: 35629091 PMCID: PMC9147210 DOI: 10.3390/jpm12050667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 04/08/2022] [Accepted: 04/19/2022] [Indexed: 11/16/2022] Open
Abstract
DNA-based screening in individuals without known risk factors potentially identifies those who may benefit from genetic counseling, early medical interventions, and/or avoidance of late or missed diagnoses. While not currently in widespread usage, technological advances in genetic analysis overcome barriers to access by enabling less labor-intensive and more cost-efficient means to discover variants of clinical importance. This study describes the technical validation of a 430-gene next-generation sequencing based assay, GeneCompassTM, indicated for the screening of healthy individuals in the areas of actionable health risks, pharmaceutical drug response, and wellness traits. The test includes genes associated with Mendelian disorders and genetic susceptibility loci, encompassing 14 clinical areas and pharmacogenetic variants. The custom-designed target enrichment capture and bioinformatics pipelines interrogate multiple variant types, including single nucleotide variants, insertions/deletions (indels), copy number variants, and functional haplotypes (star alleles), including tandem alleles and structural variants. Validation was performed against reference DNA from three sources: 1000 Genomes Project (n = 3), Coriell biobank (n = 105), and previously molecularly characterized biological specimens: blood (n = 15) and saliva (n = 11). Analytical sensitivity and specificity for single nucleotide variants (SNVs) were 97.57% and 99.99%, respectively, and for indels were 74.57% and 97.34%, respectively. This study demonstrates the validity of an NGS assay for genetic screening and the broadening of access to preventative genomics.
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Affiliation(s)
- Ari Silver
- Phosphorus, Inc., 1140 Broadway, 12th Floor, New York, NY 10001, USA; (G.A.L.); (M.S.); (M.M.); (M.J.); (C.W.); (E.D.); (S.G.); (T.H.); (D.G.); (A.B.); (M.J.)
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The Potential Application of Extracellular Vesicles from Liquid Biopsies for Determination of Pharmacogene Expression. Pharmaceuticals (Basel) 2022; 15:ph15020252. [PMID: 35215364 PMCID: PMC8879428 DOI: 10.3390/ph15020252] [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: 01/27/2022] [Revised: 02/15/2022] [Accepted: 02/17/2022] [Indexed: 02/04/2023] Open
Abstract
Pharmacogenomics (PGx) entails the study of heritability of drug response. This may include both variability in genes related to pharmacokinetics (drug absorption, distribution, metabolism and excretion) and pharmacodynamics (e.g., drug receptors or signaling pathways). Individualizing drug therapy taking into account the genetic profile of the patient has the potential to make drug therapy safer and more effective. Currently, this approach relies on the determination of genetic variants in pharmacogenes by genotyping. However, it is widely acknowledged that large variability in gene expression is attributed to non-structural genetic variants. Therefore, at least from a theoretical viewpoint individualizing drug therapy based upon expression of pharmacogenes rather than on genotype may be advantageous but has been difficult to implement in the clinical setting. Extracellular vesicles (EVs) are lipid encapsulated structures that contain cargo such as lipids, nucleic acids and proteins. Since their cargo is tissue- and cell-specific they can be used to determine the expression of pharmacogenes in the liver. In this review, we describe methods of EV isolation and the potential of EVs isolated from liquid biopsies as a tool to determine the expression of pharmacogenes for use in personalized medicine.
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