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Türkmen D, Bowden J, Masoli JAH, Melzer D, Pilling LC. SLCO1B1 Exome Sequencing and Statin Treatment Response in 64,000 UK Biobank Patients. Int J Mol Sci 2024; 25:4426. [PMID: 38674010 PMCID: PMC11050003 DOI: 10.3390/ijms25084426] [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: 03/21/2024] [Revised: 04/12/2024] [Accepted: 04/16/2024] [Indexed: 04/28/2024] Open
Abstract
The solute carrier organic anion transporter family member 1B1 (SLCO1B1) encodes the organic anion-transporting polypeptide 1B1 (OATP1B1 protein) that transports statins to liver cells. Common genetic variants in SLCO1B1, such as *5, cause altered systemic exposure to statins and therefore affect statin outcomes, with potential pharmacogenetic applications; yet, evidence is inconclusive. We studied common and rare SLCO1B1 variants in up to 64,000 patients from UK Biobank prescribed simvastatin or atorvastatin, combining whole-exome sequencing data with up to 25-year routine clinical records. We studied 51 predicted gain/loss-of-function variants affecting OATP1B1. Both SLCO1B1*5 alone and the SLCO1B1*15 haplotype increased LDL during treatment (beta*5 = 0.08 mmol/L, p = 6 × 10-8; beta*15 = 0.03 mmol/L, p = 3 × 10-4), as did the likelihood of discontinuing statin prescriptions (hazard ratio*5 = 1.12, p = 0.04; HR*15 = 1.05, p = 0.04). SLCO1B1*15 and SLCO1B1*20 increased the risk of General Practice (GP)-diagnosed muscle symptoms (HR*15 = 1.22, p = 0.003; HR*20 = 1.25, p = 0.01). We estimated that genotype-guided prescribing could potentially prevent 18% and 10% of GP-diagnosed muscle symptoms experienced by statin patients, with *15 and *20, respectively. The remaining common variants were not individually significant. Rare variants in SLCO1B1 increased LDL in statin users by up to 1.05 mmol/L, but replication is needed. We conclude that genotype-guided treatment could reduce GP-diagnosed muscle symptoms in statin patients; incorporating further SLCO1B1 variants into clinical prediction scores could improve LDL control and decrease adverse events, including discontinuation.
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Affiliation(s)
- Deniz Türkmen
- Epidemiology & Public Health Group, Department of Clinical & Biomedical Science, Faculty of Health & Life Sciences, University of Exeter, Exeter EX4 4QD, UK; (D.T.); (J.A.H.M.); (D.M.)
| | - Jack Bowden
- Exeter Diabetes Group (ExCEED), Department of Clinical & Biomedical Science, Faculty of Health & Life Sciences, University of Exeter, Exeter EX4 4QD, UK;
- Department of Genetics, Novo Nordisk Research Centre Oxford, Innovation Building, Old Road Campus, Oxford OX3 7BN, UK
| | - Jane A. H. Masoli
- Epidemiology & Public Health Group, Department of Clinical & Biomedical Science, Faculty of Health & Life Sciences, University of Exeter, Exeter EX4 4QD, UK; (D.T.); (J.A.H.M.); (D.M.)
- Department of Healthcare for Older People, Royal Devon University Healthcare NHS Foundation Trust, Exeter EX2 5DW, UK
| | - David Melzer
- Epidemiology & Public Health Group, Department of Clinical & Biomedical Science, Faculty of Health & Life Sciences, University of Exeter, Exeter EX4 4QD, UK; (D.T.); (J.A.H.M.); (D.M.)
| | - Luke C. Pilling
- Epidemiology & Public Health Group, Department of Clinical & Biomedical Science, Faculty of Health & Life Sciences, University of Exeter, Exeter EX4 4QD, UK; (D.T.); (J.A.H.M.); (D.M.)
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2
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Bigossi M, Maroteau C, Dawed AY, Taylor A, Srinivasan S, Melhem AL, Pearson ER, Pola R, Palmer CNA, Siddiqui MK. A gene risk score using missense variants in SLCO1B1 is associated with earlier onset statin intolerance. EUROPEAN HEART JOURNAL. CARDIOVASCULAR PHARMACOTHERAPY 2023; 9:536-545. [PMID: 37253618 PMCID: PMC10509567 DOI: 10.1093/ehjcvp/pvad040] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 04/13/2023] [Accepted: 05/29/2023] [Indexed: 06/01/2023]
Abstract
BACKGROUND AND AIMS The efficacy of statin therapy is hindered by intolerance to the therapy, leading to discontinuation. Variants in SLCO1B1, which encodes the hepatic transporter OATB1B1, influence statin pharmacokinetics, resulting in altered plasma concentrations of the drug and its metabolites. Current pharmacogenetic guidelines require sequencing of the SLCO1B1 gene, which is more expensive and less accessible than genotyping. In this study, we aimed to develop an easy, clinically implementable functional gene risk score (GRS) of common variants in SLCO1B1 to identify patients at risk of statin intolerance. METHODS AND RESULTS A GRS was developed from four common variants in SLCO1B1. In statin users from Tayside, Scotland, UK, those with a high-risk GRS had increased odds across three phenotypes of statin intolerance [general statin intolerance (GSI): ORGSI 2.42; 95% confidence interval (CI): 1.29-4.31, P = 0.003; statin-related myopathy: ORSRM 2.51; 95% CI: 1.28-4.53, P = 0.004; statin-related suspected rhabdomyolysis: ORSRSR 2.85; 95% CI: 1.03-6.65, P = 0.02]. In contrast, using the Val174Ala genotype alone or the recommended OATP1B1 functional phenotypes produced weaker and less reliable results. A meta-analysis with results from adjudicated cases of statin-induced myopathy in the PREDICTION-ADR Consortium confirmed these findings (ORVal174Ala 1.99; 95% CI: 1.01-3.95, P = 0.048; ORGRS 1.76; 95% CI: 1.16-2.69, P = 0.008). For those requiring high-dose statin therapy, the high-risk GRS was more consistently associated with the time to onset of statin intolerance amongst the three phenotypes compared with Val174Ala (GSI: HRVal174Ala 2.49; 95% CI: 1.09-5.68, P = 0.03; HRGRS 2.44; 95% CI: 1.46-4.08, P < 0.001). Finally, sequence kernel association testing confirmed that rare variants in SLCO1B1 are associated with the risk of intolerance (P = 0.02). CONCLUSION We provide evidence that a GRS based on four common SLCO1B1 variants provides an easily implemented genetic tool that is more reliable than the current recommended practice in estimating the risk and predicting early-onset statin intolerance.
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Affiliation(s)
- Margherita Bigossi
- Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, Division of Population Health & Genomics, School of Medicine, Ninewells Hospital & Medical School, University of Dundee, DundeeDD1 9SY, UK
- Section of Internal Medicine and Thromboembolic Diseases, Department of Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, L.go A. Gemelli 8, 00168 Rome, Italy
| | - Cyrielle Maroteau
- Human Genetics Centre of Excellence, Novo Nordisk Research Centre Oxford, Oxford OX3 7FZ, UK
| | - Adem Y Dawed
- Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, Division of Population Health & Genomics, School of Medicine, Ninewells Hospital & Medical School, University of Dundee, DundeeDD1 9SY, UK
| | - Alasdair Taylor
- Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, Division of Population Health & Genomics, School of Medicine, Ninewells Hospital & Medical School, University of Dundee, DundeeDD1 9SY, UK
| | - Sundararajan Srinivasan
- Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, Division of Population Health & Genomics, School of Medicine, Ninewells Hospital & Medical School, University of Dundee, DundeeDD1 9SY, UK
| | - Alaa’ Lufti Melhem
- Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, Division of Population Health & Genomics, School of Medicine, Ninewells Hospital & Medical School, University of Dundee, DundeeDD1 9SY, UK
| | - Ewan R Pearson
- Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, Division of Population Health & Genomics, School of Medicine, Ninewells Hospital & Medical School, University of Dundee, DundeeDD1 9SY, UK
| | - Roberto Pola
- Section of Internal Medicine and Thromboembolic Diseases, Department of Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, L.go A. Gemelli 8, 00168 Rome, Italy
| | - Colin N A Palmer
- Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, Division of Population Health & Genomics, School of Medicine, Ninewells Hospital & Medical School, University of Dundee, DundeeDD1 9SY, UK
| | - Moneeza K Siddiqui
- Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, Division of Population Health & Genomics, School of Medicine, Ninewells Hospital & Medical School, University of Dundee, DundeeDD1 9SY, UK
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3
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Lönnberg KI, Tornio A, Hirvensalo P, Keskitalo J, Mustaniemi AL, Kiiski JI, Filppula AM, Niemi M. Real-world pharmacogenetics of statin intolerance: effects of SLCO1B1, ABCG2 , and CYP2C9 variants. Pharmacogenet Genomics 2023; 33:153-160. [PMID: 37490620 PMCID: PMC10399933 DOI: 10.1097/fpc.0000000000000504] [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: 03/02/2023] [Accepted: 07/10/2023] [Indexed: 07/27/2023]
Abstract
OBJECTIVE The association of SLCO1B1 c.521T>C with simvastatin-induced muscle toxicity is well characterized. However, different statins are subject to metabolism and transport also by other proteins exhibiting clinically meaningful genetic variation. Our aim was to investigate associations of SLCO1B1 c.521T>C with intolerance to atorvastatin, fluvastatin, pravastatin, rosuvastatin, or simvastatin, those of ABCG2 c.421C>A with intolerance to atorvastatin, fluvastatin, or rosuvastatin, and that of CYP2C9*2 and *3 alleles with intolerance to fluvastatin. METHODS We studied the associations of these variants with statin intolerance in 2042 patients initiating statin therapy by combining genetic data from samples from the Helsinki Biobank to clinical chemistry and statin purchase data. RESULTS We confirmed the association of SLCO1B1 c.521C/C genotype with simvastatin intolerance both by using phenotype of switching initial statin to another as a marker of statin intolerance [hazard ratio (HR) 1.88, 95% confidence interval (CI) 1.08-3.25, P = 0.025] and statin switching along with creatine kinase measurement (HR 5.44, 95% CI 1.49-19.9, P = 0.011). No significant association was observed with atorvastatin and rosuvastatin. The sample sizes for fluvastatin and pravastatin were relatively small, but SLCO1B1 c.521T>C carriers had an increased risk of pravastatin intolerance defined by statin switching when compared to homozygous reference T/T genotype (HR 2.11, 95% CI 1.01-4.39, P = 0.047). CONCLUSION The current results can inform pharmacogenetic statin prescribing guidelines and show feasibility for the methodology to be used in larger future studies.
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Affiliation(s)
- K. Ivar Lönnberg
- Department of Clinical Pharmacology, University of Helsinki
- Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki
| | - Aleksi Tornio
- Department of Clinical Pharmacology, University of Helsinki
- Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki
- Integrative Physiology and Pharmacology, Institute of Biomedicine, University of Turku
- Unit of Clinical Pharmacology, Turku University Hospital, Turku
| | - Päivi Hirvensalo
- Department of Clinical Pharmacology, University of Helsinki
- Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki
| | - Jenni Keskitalo
- Department of Clinical Pharmacology, University of Helsinki
- Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki
- Department of Clinical Pharmacology, HUS Diagnostic Center, Helsinki University Hospital, Helsinki
| | - Anna-Liina Mustaniemi
- Department of Clinical Pharmacology, University of Helsinki
- Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki
| | - Johanna I. Kiiski
- Department of Clinical Pharmacology, University of Helsinki
- Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki
| | - Anne M. Filppula
- Department of Clinical Pharmacology, University of Helsinki
- Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki
- Pharmaceutical Science Laboratory Åbo Akademi University, Turku, Finland
| | - Mikko Niemi
- Department of Clinical Pharmacology, University of Helsinki
- Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki
- Department of Clinical Pharmacology, HUS Diagnostic Center, Helsinki University Hospital, Helsinki
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Oni-Orisan A, Tuteja S, Hoffecker G, Smith DM, Castrichini M, Crews KR, Murphy WA, Nguyen NHK, Huang Y, Lteif C, Friede KA, Tantisira K, Aminkeng F, Voora D, Cavallari LH, Whirl-Carrillo M, Duarte JD, Luzum JA. An Introductory Tutorial on Cardiovascular Pharmacogenetics for Healthcare Providers. Clin Pharmacol Ther 2023; 114:275-287. [PMID: 37303270 PMCID: PMC10406163 DOI: 10.1002/cpt.2957] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 05/17/2023] [Indexed: 06/13/2023]
Abstract
Pharmacogenetics can improve clinical outcomes by reducing adverse drug effects and enhancing therapeutic efficacy for commonly used drugs that treat a wide range of cardiovascular diseases. One of the major barriers to the clinical implementation of cardiovascular pharmacogenetics is limited education on this field for current healthcare providers and students. The abundance of pharmacogenetic literature underscores its promise, but it can also be challenging to learn such a wealth of information. Moreover, current clinical recommendations for cardiovascular pharmacogenetics can be confusing because they are outdated, incomplete, or inconsistent. A myriad of misconceptions about the promise and feasibility of cardiovascular pharmacogenetics among healthcare providers also has halted clinical implementation. Therefore, the main goal of this tutorial is to provide introductory education on the use of cardiovascular pharmacogenetics in clinical practice. The target audience is any healthcare provider (or student) with patients that use or have indications for cardiovascular drugs. This tutorial is organized into the following 6 steps: (1) understand basic concepts in pharmacogenetics; (2) gain foundational knowledge of cardiovascular pharmacogenetics; (3) learn the different organizations that release cardiovascular pharmacogenetic guidelines and recommendations; (4) know the current cardiovascular drugs/drug classes to focus on clinically and the supporting evidence; (5) discuss an example patient case of cardiovascular pharmacogenetics; and (6) develop an appreciation for emerging areas in cardiovascular pharmacogenetics. Ultimately, improved education among healthcare providers on cardiovascular pharmacogenetics will lead to a greater understanding for its potential in improving outcomes for a leading cause of morbidity and mortality.
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Affiliation(s)
- Akinyemi Oni-Orisan
- Department of Clinical Pharmacy, University of California San Francisco, San Francisco, California, USA
| | - Sony Tuteja
- Division of Translational Medicine and Human Genetics, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Glenda Hoffecker
- Division of Translational Medicine and Human Genetics, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - D. Max Smith
- MedStar Health, Columbia, Maryland, USA
- Department of Oncology, Georgetown University Medical Center, Washington, DC, USA
| | - Matteo Castrichini
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Kristine R. Crews
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, Tennessee, USA
| | - William A. Murphy
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Nam H. K. Nguyen
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - Yimei Huang
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - Christelle Lteif
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - Kevin A. Friede
- Division of Cardiology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Kelan Tantisira
- Division of Respiratory Medicine, Department of Pediatrics, University of California San Diego, San Diego, California, USA
| | - Folefac Aminkeng
- Departments of Medicine and Biomedical Informatics (DBMI), Yong Loo Lin School of Medicine, National University of Singapore, Singapore City, Singapore
- Centre for Precision Health (CPH), National University Health System (NUHS), Singapore City, Singapore
| | - Deepak Voora
- Precision Medicine Program, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Larisa H. Cavallari
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | | | - Julio D. Duarte
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - Jasmine A. Luzum
- Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, Michigan, USA
- Center for Individualized and Genomic Medicine Research, Henry Ford Health System, Detroit, Michigan, USA
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Yow HY, Hamzah S, Abdul Rahim N, Suppiah V. Pharmacogenomics of response to statin treatment and susceptibility to statin-induced adverse drug reactions in Asians: a scoping review. ASIAN BIOMED 2023; 17:95-114. [PMID: 37818163 PMCID: PMC10561688 DOI: 10.2478/abm-2023-0050] [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] [Indexed: 10/12/2023]
Abstract
Background Statins are the most widely used lipid-lowering agents for patients with hyperlipidemia. However, interindividual variations in efficacy and risk of adverse drug reactions to statin treatment have been widely reported. Ethnicity is well known to be one of the contributing factors to this variation, particularly among Asians. Objectives To identify genetic variants associated with statin treatment responses among Asian populations with a focus on four commonly prescribed statins: atorvastatin, rosuvastatin, simvastatin, and pravastatin. Methods A literature search was conducted in Medline and Embase databases. Studies published from 2008 to 2021 were included. The title and abstract of each article were screened by two reviewers and verified by another two reviewers. Data charted include information on authors, year of study, study population, statin studied, gene studied, study findings, and data of significant statistical value. Results A total of 35 articles were included from the 1,939 original studies related to treatment efficacy and 5 articles out of the 284 original studies related to adverse effects. Genetic variants in transmembrane transporters, cytochrome P450 isoenzymes, and apolipoproteins are the most extensively studied among Asian populations, with a main focus on ethnic Chinese. However, Asia consists of genetically different populations, and the results of this review indicated that there is a paucity of studies on other ethnic groups within Asia. Conclusions Considering the ethnicity of patients could provide a potential value to personalized medicine in statin therapy.
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Affiliation(s)
- Hui-Yin Yow
- Department of Pharmaceutical Life Sciences, Faculty of Pharmacy, Universiti Malaya, Kuala Lumpur50603, Malaysia
- School of Pharmacy, Faculty of Health and Medical Sciences, Taylor's University, Selangor47500, Malaysia
| | - Sharina Hamzah
- School of Pharmacy, Faculty of Health and Medical Sciences, Taylor's University, Selangor47500, Malaysia
- Medical Advancement for Better Quality of Life Impact Lab, Taylor's University, Selangor47500, Malaysia
| | - Nusaibah Abdul Rahim
- Department of Clinical Pharmacy and Pharmacy Practice, Faculty of Pharmacy, Universiti Malaya, Kuala Lumpur50603, Malaysia
| | - Vijayaprakash Suppiah
- Clinical and Health Sciences, University of South Australia, Adelaide, SA5001, Australia
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA5001, Australia
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Massmann A, Van Heukelom J, Green RC, Hajek C, Hickingbotham MR, Larson EA, Lu CY, Wu AC, Zoltick ES, Christensen KD, Schultz A. SLCO1B1 gene-based clinical decision support reduces statin-associated muscle symptoms risk with simvastatin. Pharmacogenomics 2023; 24:399-409. [PMID: 37232094 PMCID: PMC10242433 DOI: 10.2217/pgs-2023-0056] [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: 04/03/2023] [Accepted: 05/09/2023] [Indexed: 05/27/2023] Open
Abstract
Background: SLCO1B1 variants are known to be a strong predictor of statin-associated muscle symptoms (SAMS) risk with simvastatin. Methods: The authors conducted a retrospective chart review on 20,341 patients who had SLCO1B1 genotyping to quantify the uptake of clinical decision support (CDS) for genetic variants known to impact SAMS risk. Results: A total of 182 patients had 417 CDS alerts generated, and 150 of these patients (82.4%) received pharmacotherapy that did not increase risks for SAMS. Providers were more likely to cancel simvastatin orders in response to CDS alerts if genotyping had been done prior to the first simvastatin prescription than after (94.1% vs 28.5%, respectively; p < 0.001). Conclusion: CDS significantly reduces simvastatin prescribing at doses associated with SAMS.
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Affiliation(s)
- Amanda Massmann
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD 57069, USA
| | - Joel Van Heukelom
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD 57069, USA
| | - Robert C Green
- Department of Medicine, Brigham & Women's Hospital & Harvard Medical School, Boston, MA 02115, USA
- Ariadne Labs, Boston, MA 02215, USA
- Broad Institute of Harvard & MIT, Cambridge, MA 02142, USA
| | - Catherine Hajek
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Helix OpCo, LLC, San Mateo, CA 94401, USA
| | - Madison R Hickingbotham
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - Eric A Larson
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD 57069, USA
| | - Christine Y Lu
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
- Department of Population Medicine, Harvard Medical School, Boston, MA 02215, USA
| | - Ann Chen Wu
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
- Department of Population Medicine, Harvard Medical School, Boston, MA 02215, USA
| | - Emilie S Zoltick
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - Kurt D Christensen
- Broad Institute of Harvard & MIT, Cambridge, MA 02142, USA
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
- Department of Population Medicine, Harvard Medical School, Boston, MA 02215, USA
| | - April Schultz
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD 57069, USA
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7
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Ramsey LB, Gong L, Lee SB, Wagner JB, Zhou X, Sangkuhl K, Adams SM, Straka RJ, Empey PE, Boone EC, Klein TE, Niemi M, Gaedigk A. PharmVar GeneFocus: SLCO1B1. Clin Pharmacol Ther 2023; 113:782-793. [PMID: 35797228 PMCID: PMC10900141 DOI: 10.1002/cpt.2705] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 06/24/2022] [Indexed: 11/06/2022]
Abstract
The Pharmacogene Variation Consortium (PharmVar) is now providing star (*) allele nomenclature for the highly polymorphic human SLCO1B1 gene encoding the organic anion transporting polypeptide 1B1 (OATP1B1) drug transporter. Genetic variation within the SLCO1B1 gene locus impacts drug transport, which can lead to altered pharmacokinetic profiles of several commonly prescribed drugs. Variable OATP1B1 function is of particular importance regarding hepatic uptake of statins and the risk of statin-associated musculoskeletal symptoms. To introduce this important drug transporter gene into the PharmVar database and serve as a unified reference of haplotype variation moving forward, an international group of gene experts has performed an extensive review of all published SLCO1B1 star alleles. Previously published star alleles were self-assigned by authors and only loosely followed the star nomenclature system that was first developed for cytochrome P450 genes. This nomenclature system has been standardized by PharmVar and is now applied to other important pharmacogenes such as SLCO1B1. In addition, data from the 1000 Genomes Project and investigator-submitted data were utilized to confirm existing haplotypes, fill knowledge gaps, and/or define novel star alleles. The PharmVar-developed SLCO1B1 nomenclature has been incorporated by the Clinical Pharmacogenetics Implementation Consortium (CPIC) 2022 guideline on statin-associated musculoskeletal symptoms.
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Affiliation(s)
- Laura B Ramsey
- Divisions of Clinical Pharmacology and Research in Patient Services, Cincinnati Children's Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Li Gong
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA
| | - Seung-Been Lee
- Precision Medicine Institute, Macrogen Inc., Seoul, Korea
| | - Jonathan B Wagner
- Division of Clinical Pharmacology, Toxicology & Therapeutic Innovation, Children's Mercy Kansas City, Kansas City, Missouri, USA
- School of Medicine, University of Missouri-Kansas City, Kansas City, Missouri, USA
| | - Xujia Zhou
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California, USA
| | - Katrin Sangkuhl
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA
| | - Solomon M Adams
- School of Pharmacy, Shenandoah University, Fairfax, Virginia, USA
| | - Robert J Straka
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota, USA
| | - Philip E Empey
- School of Pharmacy and Institute for Precision Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Erin C Boone
- Division of Clinical Pharmacology, Toxicology & Therapeutic Innovation, Children's Mercy Kansas City, Kansas City, Missouri, USA
| | - Teri E Klein
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA
- Department of Medicine (BMIR), Stanford University, Stanford, California, USA
| | - Mikko Niemi
- Department of Clinical Pharmacology, University of Helsinki, Helsinki, Finland
- Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Clinical Pharmacology, HUS Diagnostic Center, Helsinki University Hospital, Helsinki, Finland
| | - Andrea Gaedigk
- Division of Clinical Pharmacology, Toxicology & Therapeutic Innovation, Children's Mercy Kansas City, Kansas City, Missouri, USA
- School of Medicine, University of Missouri-Kansas City, Kansas City, Missouri, USA
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8
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Tariq S, Goriparthi L, Ismail D, Kankeu Tonpouwo G, Thapa M, Khalid K, Cooper AC, Jean-Charles G. Correlates of Myopathy in Diabetic Patients Taking Statins. Cureus 2023; 15:e37708. [PMID: 37206522 PMCID: PMC10191392 DOI: 10.7759/cureus.37708] [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] [Accepted: 04/16/2023] [Indexed: 05/21/2023] Open
Abstract
Diabetes is one of the most common chronic ailments; its incidence has reached epidemic proportions in the 21st century. Diabetes significantly increases micro and macrovascular complications, which are effectively managed with statins. Therefore, statins' pharmacokinetics, pharmacodynamics, and pharmacogenetics have been extensively studied. Although statins act as a keystone in preventing cardiovascular complications, at the same time, they pose a threat to the quality of life of diabetics due to the resulting muscular side effects. This article summarizes the prevalence, clinical manifestations, pathophysiology, and risk factors of statin-induced myopathy in diabetic patients. Among the diverse predisposing risk factors, the primary variables identified for causing myopathy in diabetic patients include age, gender, ethnicity, duration and severity of illness, comorbid conditions, level of physical activity, alcohol use, cholecalciferol (vitamin D3) levels, type and dose of statins, and anti-diabetic drugs or other drugs used concomitantly. In addition, cardiovascular risk quotients also potentially impact diabetic patients making them more vulnerable to developing myopathy from statins. Therefore, this study highlights the importance of managing statin-associated myopathic side effects by providing consensus guidelines on diagnostic, monitoring, and treatment strategies. We also discussed statins' prognostic value in reducing cardiovascular events in diabetic individuals.
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Affiliation(s)
- Sara Tariq
- Internal Medicine, Mayo Hospital, Lahore, PAK
- Internal Medicine, JC (Jean-Charles) Medical Center, Orlando, USA
| | - Lakshmi Goriparthi
- General Surgery, Osmania Medical College, Hyderabad, IND
- Internal Medicine, JC (Jean-Charles) Medical Center, Orlando, USA
| | - Dina Ismail
- Internal Medicine, JC (Jean-Charles) Medical Center, Orlando, USA
- Family Medicine, University Hassan II of Casablanca Faculty of Medicine and Pharmacy, Casablanca, MAR
| | - Gauvain Kankeu Tonpouwo
- Internal Medicine, Faculty of Medicine, University of Lubumbashi, Plaine Tshombé, Lubumbashi, COD
| | - Milan Thapa
- Internal Medicine, Monmouth Medical Center, Long Branch, USA
| | - Khizer Khalid
- Internal Medicine, JC (Jean-Charles) Medical Center, Orlando, USA
| | | | - Gutteridge Jean-Charles
- Internal Medicine, AdventHealth Orlando Hospital, Orlando, USA
- Internal Medicine, JC (Jean-Charles) Medical Center, Orlando, USA
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9
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Jansen ME, Rigter T, Fleur TMC, Souverein PC, Verschuren WMM, Vijverberg SJ, Swen JJ, Rodenburg W, Cornel MC. Predictive Value of SLCO1B1 c.521T>C Polymorphism on Observed Changes in the Treatment of 1136 Statin-Users. Genes (Basel) 2023; 14:456. [PMID: 36833383 PMCID: PMC9957000 DOI: 10.3390/genes14020456] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 02/03/2023] [Accepted: 02/06/2023] [Indexed: 02/12/2023] Open
Abstract
Pharmacogenomic testing is a method to prevent adverse drug reactions. Pharmacogenomics could be relevant to optimize statin treatment, by identifying patients at high risk for adverse drug reactions. We aim to investigate the clinical validity and utility of pre-emptive pharmacogenomics screening in primary care, with SLCO1B1 c.521T>C as a risk factor for statin-induced adverse drug reactions. The focus was on changes in therapy as a proxy for adverse drug reactions observed in statin-users in a population-based Dutch cohort. In total, 1136 statin users were retrospectively genotyped for the SLCO1B1 c.521T>C polymorphism (rs4149056) and information on their statin dispensing was evaluated as cross-sectional research. Approximately half of the included participants discontinued or switched their statin treatment within three years. In our analyses, we could not confirm an association between the SLCO1B1 c.521T>C genotype and any change in statin therapy or arriving at a stable dose sooner in primary care. To be able to evaluate the predictive values of SLCO1B1 c.521T>C genotype on adverse drug reactions from statins, prospective data collection of actual adverse drug reactions and reasons to change statin treatment should be facilitated.
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Affiliation(s)
- Marleen E. Jansen
- Department of Clinical Genetics, Amsterdam Public Health Research Institute, Personalized Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Section Community Genetics, 1081 HV Amsterdam, The Netherlands
- Centre for Health Protection, National Institute for Public Health and the Environment, 3721 MA Bilthoven, The Netherlands
| | - Tessel Rigter
- Department of Clinical Genetics, Amsterdam Public Health Research Institute, Personalized Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Section Community Genetics, 1081 HV Amsterdam, The Netherlands
- Centre for Health Protection, National Institute for Public Health and the Environment, 3721 MA Bilthoven, The Netherlands
| | - Thom M. C. Fleur
- Department of Clinical Genetics, Amsterdam Public Health Research Institute, Personalized Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Section Community Genetics, 1081 HV Amsterdam, The Netherlands
- Division of Pharmacoepidemiology & Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, 3508 TB Utrecht, The Netherlands
| | - Patrick C. Souverein
- Division of Pharmacoepidemiology & Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, 3508 TB Utrecht, The Netherlands
| | - W. M. Monique Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, 3721 MA Bilthoven, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, 3508 GA Utrecht, The Netherlands
| | - Susanne J. Vijverberg
- Department of Pulmonary Medicine and Amsterdam Public Health Research Institute, Personalized Medicine, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands
| | - Jesse J. Swen
- Department of Clinical Pharmacy & Toxicology, Leiden University Medical Centre, 2300 RC Leiden, The Netherlands
| | - Wendy Rodenburg
- Centre for Health Protection, National Institute for Public Health and the Environment, 3721 MA Bilthoven, The Netherlands
| | - Martina C. Cornel
- Department of Clinical Genetics, Amsterdam Public Health Research Institute, Personalized Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Section Community Genetics, 1081 HV Amsterdam, The Netherlands
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10
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Siddiqui MK, Hall C, Cunningham SG, McCrimmon R, Morris A, Leese GP, Pearson ER. Using Data to Improve the Management of Diabetes: The Tayside Experience. Diabetes Care 2022; 45:2828-2837. [PMID: 36288800 DOI: 10.2337/dci22-0003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 07/12/2022] [Indexed: 02/03/2023]
Abstract
Tayside is a region in the East of Scotland and forms one of nine local government regions in the country. It is home to approximately 416,000 individuals who fall under the National Health Service (NHS) Tayside health board, which provides health care services to the population. In Tayside, Scotland, a comprehensive informatics network for diabetes care and research has been established for over 25 years. This has expanded more recently to a comprehensive Scotland-wide clinical care system, Scottish Care Information - Diabetes (SCI-Diabetes). This has enabled improved diabetes screening and integrated management of diabetic retinopathy, neuropathy, nephropathy, cardiovascular health, and other comorbidities. The regional health informatics network links all of these specialized services with comprehensive laboratory testing, prescribing records, general practitioner records, and hospitalization records. Not only do patients benefit from the seamless interconnectedness of these data, but also the Tayside bioresource has enabled considerable research opportunities and the creation of biobanks. In this article we describe how health informatics has been used to improve care of people with diabetes in Tayside and Scotland and, through anonymized data linkage, our understanding of the phenotypic and genotypic etiology of diabetes and associated complications and comorbidities.
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Affiliation(s)
- Moneeza K Siddiqui
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, U.K
| | - Christopher Hall
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, U.K
| | - Scott G Cunningham
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, U.K
| | - Rory McCrimmon
- Division of Systems Medicine, School of Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, U.K
| | - Andrew Morris
- Usher Institute, College of Medicine and Veterinary Medicine, Edinburgh, U.K
| | - Graham P Leese
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, U.K
| | - Ewan R Pearson
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, U.K
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11
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Božina T, Ganoci L, Karačić E, Šimičević L, Vrkić-Kirhmajer M, Klarica-Domjanović I, Križ T, Sertić Z, Božina N. ABCG2 and SLCO1B1 gene polymorphisms in the Croatian population. Ann Hum Biol 2022; 49:323-331. [PMID: 36382878 DOI: 10.1080/03014460.2022.2140826] [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: 11/17/2022]
Abstract
BACKGROUND Organic anion-transporting polypeptide 1B1 (OATP1B1) and the ATP-binding cassette subfamily G member 2, ABCG2, are important transporters involved in the transport of endogenous substrates and xenobiotics, including drugs. Genetic polymorphisms of these transporters have effect on transporter activity. There is significant interethnic variability in the frequency of allele variants. AIM To determined allele and genotype frequencies of ABCG2 and SLCO1B1 genes in Croatian populations of European descent. SUBJECTS AND METHODS A total of 905 subjects (482 women) were included. Genotyping for ABCG2 c.421C > A (rs2231142) and for SLCO1B1 c.521T > C (rs4149056), was performed by real-time polymerase chain reaction (PCR) using TaqMan® DME Genotyping Assays. RESULTS For ABCG2 c.421C > A, the frequency of CC, CA and AA genotypes was 81.4%, 17.8% and 0.8% respectively. The frequency of variant ABCG2 421 A allele was 9.7%. For SLCO1B1 c.521T > C, the frequency of TT, TC and CC genotypes was 61.7%, 34.8% and 3.5% respectively. The frequency of variant SLCO1B1 521 C allele was 20.9%. CONCLUSION The frequency of the ABCG2 and SLCO1B1 allelic variants and genotypes in the Croatian population is in accordance with other European populations. Pharmacogenetic analysis can serve to individualise drug therapy and minimise the risk of developing adverse drug reactions.
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Affiliation(s)
- Tamara Božina
- Department of Medical Chemistry, Biochemistry, and Clinical Chemistry, University of Zagreb School of Medicine, Zagreb, Croatia
| | - Lana Ganoci
- Division of Pharmacogenomics and Therapy Individualization, Department of Laboratory Diagnostics, University Hospital Centre Zagreb, Zagreb, Croatia
| | - Ena Karačić
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Livija Šimičević
- Division of Pharmacogenomics and Therapy Individualization, Department of Laboratory Diagnostics, University Hospital Centre Zagreb, Zagreb, Croatia
| | - Majda Vrkić-Kirhmajer
- Department of Cardiovascular Diseases Zagreb, University of Zagreb School of Medicine, University Hospital Centre Zagreb, Croatia
| | | | - Tena Križ
- Department of Ophthalmology, University Hospital Centre "Sestre milosrdnice", Zagreb, Croatia
| | - Zrinka Sertić
- Department of Emergency Medicine, University Hospital Centre Zagreb, Zagreb, Croatia
| | - Nada Božina
- Department of Pharmacology, University of Zagreb School of Medicine, Zagreb, Croatia
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12
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Shatnawi A, Kamran Z, Al-Share Q. Pharmacogenomics of lipid-lowering agents: the impact on efficacy and safety. Per Med 2022; 20:65-86. [DOI: 10.2217/pme-2022-0041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Hyperlipidemia is a significant risk factor for cardiovascular disease morbidity and mortality. The lipid-lowering drugs are considered the cornerstone of primary and secondary prevention of atherosclerotic cardiovascular disease. Unfortunately, the lack of efficacy and associated adverse effects, ranging from mild-to-moderate to potentially life-threatening, lead to therapy discontinuation. Numerous reports support the role of gene polymorphisms in drugs' pharmacokinetic parameters and their associated adverse reactions. Therefore, this study aims to understand the pharmacogenomics of lipid-lowering drugs and the impact of genetic variants of key genes on the drugs' efficacy and toxicity. Indeed, genetically guided lipid-lowering therapy enhances overall safety, improves drug adherence and achieves long-term therapy.
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Affiliation(s)
- Aymen Shatnawi
- Department of Drug Discovery & Biomedical Sciences, College of Pharmacy, Medical University of South Carolina, 70 President St., Room 402, Charleston, SC 29425, USA
| | - Zourayz Kamran
- Department of Pharmaceutical & Administrative Sciences, University of Charleston School of Pharmacy, 2300 MacCorkle Ave SE, Charleston, WV 25304, USA
| | - Qusai Al-Share
- Department of Clinical Pharmacy, Assistant Professor of Pharmacology & Therapeutics, Faculty of Pharmacy, Jordan University of Science & Technology, P.O. Box 3030, Irbid, 22110, Jordan
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13
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Sheikhy A, Fallahzadeh A, Aghaei Meybodi HR, Hasanzad M, Tajdini M, Hosseini K. Personalized medicine in cardiovascular disease: review of literature. J Diabetes Metab Disord 2021; 20:1793-1805. [PMID: 34900826 DOI: 10.1007/s40200-021-00840-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 06/18/2021] [Indexed: 12/13/2022]
Abstract
Purpose Personalized medicine (PM) is the concept of managing patients based on their characteristics, including genotypes. In the field of cardiology, advantages of PM could be found in the diagnosis and treatment of several conditions such as arrhythmias and cardiomyopathies; moreover, it may be beneficial to prevent adverse drug reactions (ADR) and select the best medication. Genetic background can help us in selecting effective treatments, appropriate dose requirements, and preventive strategies in individuals with particular genotypes. Method In this review, we provide examples of personalized medicine based on human genetics for the most used pharmaceutics in cardiology, including warfarin, clopidogrel, and statins. We also review cardiovascular diseases, including coronary artery disease, arrhythmia, and cardiomyopathies. Conclusion Genetic factors are as important as environmental factors and they should be tested and evaluated more in the future by improving in genetic testing tools. Supplementary Information The online version contains supplementary material available at 10.1007/s40200-021-00840-0.
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Affiliation(s)
- Ali Sheikhy
- Research Department, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Aida Fallahzadeh
- Research Department, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Hamid Reza Aghaei Meybodi
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mandana Hasanzad
- Personalized Medicine Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
- Medical Genomics Research Center, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Masih Tajdini
- Cardiology Department, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Kaveh Hosseini
- Cardiology Department, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
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14
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Kiage J, Venkatanarayan A, Roth M, Elam M. Atorvastatin-associated rhabdomyolysis in a patient with a novel variant of the SLCO1B1 gene: A case report. J Clin Lipidol 2021; 16:23-27. [PMID: 34887219 DOI: 10.1016/j.jacl.2021.11.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 11/15/2021] [Accepted: 11/16/2021] [Indexed: 11/19/2022]
Abstract
We report the case of an individual with severe hypercholesterolemia who experienced rhabdomyolysis with high dose atorvastatin. Genetic testing was undertaken to evaluate for suspected familial hypercholesterolemia (FH) and for the presence of gene variants associated with susceptibility to statin associated muscle disease. Genetic testing identified the presence of a potentially damaging variant of the hepatic xenobiotic transporter pump SLCO1B1, a single nucleotide variant (SNV) (rs77271279, c.481+1G>T) that disrupts the canonical donor splice motif. Although this variant has not previously been reported as associated with rhabdomyolysis and thus requires validation in population studies, it likely played a role in this patient's susceptibility to rhabdomyolysis based on functional assessment of the effect of this variant on SLCO1B1 protein function and given the known role of this transporter in statin uptake by the liver. The presence of this gene variant reinforced our decision to treat the patient's hypercholesterolemia with non-statin alternatives (PCSK9 inhibitor and ezetimibe). Genetic testing also identified the presence of a second SLCO1B1 gene variant, c.1200C>G (p.Phe400Leu, rs59113707) and homozygosity for an intron variant of the apolipoprotein(a) (LPA) gene (c.2604.138G>A intron variant, rs9457951) associated with increased Lp(a), a risk factor for atherosclerotic cardiovascular disease. Notably, all three variants are rare in persons of European descent but more frequent in African-Americans. These findings underscore the role of disabling mutations of the SLCO1B1 gene in statin myopathy and the need to validate these and other gene variants associated with statin myopathy in a population of patients with statin-associated muscle disease.
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Affiliation(s)
- James Kiage
- Veterans Affairs Medical Center, Memphis TN, United States; University of Tennessee Health Sciences Center, Memphis TN, United States
| | - Ajay Venkatanarayan
- Veterans Affairs Medical Center, Memphis TN, United States; University of Tennessee Health Sciences Center, Memphis TN, United States
| | | | - Marshall Elam
- Veterans Affairs Medical Center, Memphis TN, United States; University of Tennessee Health Sciences Center, Memphis TN, United States.
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15
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Melhem AL, Chourasia MK, Bigossi M, Maroteau C, Taylor A, Pola R, Dawed AY, Tornio A, Palmer CNA, Siddiqui MK. Common Statin Intolerance Variants in ABCB1 and LILRB5 Show Synergistic Effects on Statin Response: An Observational Study Using Electronic Health Records. Front Genet 2021; 12:713181. [PMID: 34659336 PMCID: PMC8517257 DOI: 10.3389/fgene.2021.713181] [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: 05/22/2021] [Accepted: 08/11/2021] [Indexed: 12/25/2022] Open
Abstract
Background: Statin intolerance impacts approximately 10% of statin users, with side effects ranging from mild myalgia to extreme intolerance resulting in myopathy and rhabdomyolysis. Statin intolerance results in poor adherence to therapy and can impact statin efficacy. Many genetic variants are associated with statin intolerance. The effect of these variants on statin efficacy has not been systematically explored. Methods: Using longitudinal electronic health records and genetic biobank data from Tayside, Scotland, we examined the effect of seven genetic variants with previously reported associations with simvastatin or atorvastatin intolerance on the outcome of statin response. Statin response was measured by the reduction achieved when comparing pre- and post-statin non-high-density lipoprotein-cholesterol (non-HDL-C). Post-treatment statin response was limited to non-HDL-C measured within 6months of therapy initiation. Univariate and multivariable linear regression models were used to assess the main and adjusted effect of the variants on statin efficacy. Results: Around 9,401 statin users met study inclusion criteria, of whom 8,843 were first prescribed simvastatin or atorvastatin. The average difference in post-treatment compared to pre-treatment non-HDL-cholesterol was 1.45 (±1.04) mmol/L. In adjusted analyses, only two variants, one in the gene ATP-binding cassette transporter B1 (ABCB1; rs1045642), and one in leukocyte immunoglobulin like receptor B5 (LILRB5; rs12975366), were associated with statin efficacy. In ABCB1, homozygous carriers of the C allele at rs1045642 had 0.06mmol/L better absolute reduction in non-HDL-cholesterol than carriers of the T allele (95% CI: 0.01, 0.1). In LILRB5 (rs12975366), carriers of the C allele had 0.04mmol/L better absolute reduction compared to those homozygous for the T allele (95% CI: 0.004, 0.08). When combined into a two-variant risk score, individuals with both the rs1045642-CC genotype and the rs12975366-TC or CC genotype had a 0.11mmol/L greater absolute reduction in non-HDL-cholesterol compared to those with rs1045642-TC or TT genotype and the rs12975366-TT genotype (95% CI: 0.05, 0.16; p<0.001). Conclusion: We report two genetic variants for statin adverse drug reactions (ADRs) that are associated with statin efficacy. While the ABCB1 variant has been shown to have an association with statin pharmacokinetics, no similar evidence for LILRB5 has been reported. These findings highlight the value of genetic testing to deliver precision therapeutics to statin users.
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Affiliation(s)
- Alaa' Lutfi Melhem
- Division of Population Health & Genomics, Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, School of Medicine, Ninewells Hospital & Medical School, University of Dundee, Dundee, United Kingdom
| | - Mehul Kumar Chourasia
- Division of Population Health & Genomics, Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, School of Medicine, Ninewells Hospital & Medical School, University of Dundee, Dundee, United Kingdom
| | - Margherita Bigossi
- Division of Population Health & Genomics, Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, School of Medicine, Ninewells Hospital & Medical School, University of Dundee, Dundee, United Kingdom.,Section of Internal Medicine and Thromboembolic Diseases, Department of Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Cyrielle Maroteau
- Division of Population Health & Genomics, Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, School of Medicine, Ninewells Hospital & Medical School, University of Dundee, Dundee, United Kingdom
| | - Alasdair Taylor
- Division of Population Health & Genomics, Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, School of Medicine, Ninewells Hospital & Medical School, University of Dundee, Dundee, United Kingdom
| | - Roberto Pola
- Section of Internal Medicine and Thromboembolic Diseases, Department of Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Adem Y Dawed
- Division of Population Health & Genomics, Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, School of Medicine, Ninewells Hospital & Medical School, University of Dundee, Dundee, United Kingdom
| | - Aleksi Tornio
- Division of Population Health & Genomics, Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, School of Medicine, Ninewells Hospital & Medical School, University of Dundee, Dundee, United Kingdom.,Integrative Physiology and Pharmacology Unit, Institute of Biomedicine, University of Turku, Turku, Finland
| | - Colin N A Palmer
- Division of Population Health & Genomics, Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, School of Medicine, Ninewells Hospital & Medical School, University of Dundee, Dundee, United Kingdom
| | - Moneeza K Siddiqui
- Division of Population Health & Genomics, Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, School of Medicine, Ninewells Hospital & Medical School, University of Dundee, Dundee, United Kingdom
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16
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Malki MA, Dawed AY, Haywood C, Doney A, Pearson ER. Utilizing Large Electronic Medical Record Data Sets to Identify Novel Drug-Gene Interactions for Commonly Used Drugs. Clin Pharmacol Ther 2021; 110:816-825. [PMID: 34213766 DOI: 10.1002/cpt.2352] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 06/07/2021] [Indexed: 01/03/2023]
Abstract
Real-world prescribing of drugs differs from the experimental systems, physiological-pharmacokinetic models, and clinical trials used in drug development and licensing, with drugs often used in patients with multiple comorbidities with resultant polypharmacy. The increasing availability of large biobanks linked to electronic healthcare records enables the potential to identify novel drug-gene interactions in large populations of patients. In this study we used three Scottish cohorts and UK Biobank to identify drug-gene interactions for the 50 most commonly used drugs and 162 variants in genes involved in drug pharmacokinetics. We defined two phenotypes based upon prescribing behavior-drug-stop or dose-decrease. Using this approach, we replicate 11 known drug-gene interactions including, for example, CYP2C9/CYP2C8 variants and sulfonylurea/thiazolidinedione prescribing and ABCB1/ABCG2 variants and statin prescribing. We identify eight novel associations after Bonferroni correction, three of which are replicated or validated in the UK Biobank or have other supporting results: The C-allele at rs4918758 in CYP2C9 was associated with a 25% (15-44%) lower odds of dose reduction of quinine, P = 1.6 × 10-5 ; the A-allele at rs9895420 in ABCC3 was associated with a 46% (24-62%) reduction in odds of dose reduction with doxazosin, P = 1.2 × 10-4 , and altered blood pressure response in the UK Biobank; the CYP2D6*2 variant was associated with a 30% (18-40%) reduction in odds of stopping ramipril treatment, P = 1.01 × 10-5 , with similar results seen for enalapril and lisinopril and with other CYP2D6 variants. This study highlights the scope of using large population bioresources linked to medical record data to explore drug-gene interactions at scale.
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Affiliation(s)
- Mustafa Adnan Malki
- Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK.,Clinical Pharmacy Department, College of Pharmacy, Umm Al-Qura University, Mecca, Saudi Arabia
| | - Adem Y Dawed
- Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Caroline Haywood
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Alex Doney
- Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Ewan R Pearson
- Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
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17
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Association between CYP3A5 Polymorphism and Statin-Induced Adverse Events: A Systemic Review and Meta-Analysis. J Pers Med 2021; 11:jpm11070677. [PMID: 34357144 PMCID: PMC8304457 DOI: 10.3390/jpm11070677] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 07/11/2021] [Accepted: 07/17/2021] [Indexed: 12/13/2022] Open
Abstract
Purpose: Cytochrome P450 (CYP) is involved in the metabolism of statins; CYP3A5 is the main enzyme responsible for lipophilic statin metabolism. However, the evidence of the association between CYP3A5*3 polymorphism and the risk of statin-induced adverse events remains unclear. Therefore, this study aimed to perform a systematic review and meta-analysis to investigate the relationship between the CYP3A5*3 polymorphism and the risk of statin-induced adverse events. Methods: The PubMed, Web of Science, and EMBASE databases were searched for qualified studies published until August 2020. Observational studies that included the association between statin-induced adverse events and the CYP3A5*3 polymorphism were reviewed. The odds ratios (ORs) and 95% confidence intervals (CIs) were evaluated to assess the strength of the relationship. The Mantel-Haenszel method was used to provide the pooled ORs. Heterogeneity was estimated with I2 statistics and publication bias was determined by Begg's and Egger's test of the funnel plot. Data analysis was performed using Review Manager (version 5.4) and R Studio (version 3.6). Results: In total, data from 8 studies involving 1614 patients were included in this meta-analysis. The CYP3A5*3 polymorphism was found to be associated with the risk of statin-induced adverse events (*3/*3 vs. *1/*1 + *1/*3: OR = 1.40, 95% CI = 1.08-1.82). For myopathy, the pooled OR was 1.30 (95% CI: 0.96-1.75). The subgroup analysis of statin-induced myopathy revealed a trend, which did not achieve statistical significance. Conclusions: This meta-analysis demonstrated that the CYP3A5*3 polymorphism affected statin-induced adverse event risk. Therefore, CYP3A5 genotyping may be useful to predict statin toxicity.
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18
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Ooi BNS, Raechell, Ying AF, Koh YZ, Jin Y, Yee SWL, Lee JHS, Chong SS, Tan JWC, Liu J, Lee CG, Drum CL. Robust Performance of Potentially Functional SNPs in Machine Learning Models for the Prediction of Atorvastatin-Induced Myalgia. Front Pharmacol 2021; 12:605764. [PMID: 33967749 PMCID: PMC8100589 DOI: 10.3389/fphar.2021.605764] [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: 09/13/2020] [Accepted: 03/08/2021] [Indexed: 12/20/2022] Open
Abstract
Statins can cause muscle symptoms resulting in poor adherence to therapy and increased cardiovascular risk. We hypothesize that combinations of potentially functional SNPs (pfSNPs), rather than individual SNPs, better predict myalgia in patients on atorvastatin. This study assesses the value of potentially functional single nucleotide polymorphisms (pfSNPs) and employs six machine learning algorithms to identify the combination of SNPs that best predict myalgia. Methods: Whole genome sequencing of 183 Chinese, Malay and Indian patients from Singapore was conducted to identify genetic variants associated with atorvastatin induced myalgia. To adjust for confounding factors, demographic and clinical characteristics were also examined for their association with myalgia. The top factor, sex, was then used as a covariate in the whole genome association analyses. Variants that were highly associated with myalgia from this and previous studies were extracted, assessed for potential functionality (pfSNPs) and incorporated into six machine learning models. Predictive performance of a combination of different models and inputs were compared using the average cross validation area under ROC curve (AUC). The minimum combination of SNPs to achieve maximum sensitivity and specificity as determined by AUC, that predict atorvastatin-induced myalgia in most, if not all the six machine learning models was determined. Results: Through whole genome association analyses using sex as a covariate, a larger proportion of pfSNPs compared to non-pf SNPs were found to be highly associated with myalgia. Although none of the individual SNPs achieved genome wide significance in univariate analyses, machine learning models identified a combination of 15 SNPs that predict myalgia with good predictive performance (AUC >0.9). SNPs within genes identified in this study significantly outperformed SNPs within genes previously reported to be associated with myalgia. pfSNPs were found to be more robust in predicting myalgia, outperforming non-pf SNPs in the majority of machine learning models tested. Conclusion: Combinations of pfSNPs that were consistently identified by different machine learning models to have high predictive performance have good potential to be clinically useful for predicting atorvastatin-induced myalgia once validated against an independent cohort of patients.
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Affiliation(s)
- Brandon N S Ooi
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Dundee, Singapore
| | - Raechell
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Dundee, Singapore
| | | | - Yong Zher Koh
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Dundee, Singapore
| | - Yu Jin
- Division of Cellular and Molecular Research, Humphrey Oei Institute of Cancer Research, National Cancer Centre Singapore, Singapore, Singapore
| | - Sherman W L Yee
- Department of Medicine, Yong Loo Lin School of Medicine, Cardiovascular Research Institute, National University of Singapore, Singapore, Singapore
| | | | - Samuel S Chong
- Department of Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Jack W C Tan
- Department of Cardiology, National Heart Centre Singapore, Singapore, Singapore
| | - Jianjun Liu
- Genome Institute of Singapore, Singapore, Singapore
| | - Caroline G Lee
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Dundee, Singapore.,Duke-NUS Graduate School, Singapore, Singapore.,Division of Cellular and Molecular Research, Humphrey Oei Institute of Cancer Research, National Cancer Centre Singapore, Singapore, Singapore.,NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, Singapore
| | - Chester L Drum
- Department of Medicine, Yong Loo Lin School of Medicine, Cardiovascular Research Institute, National University of Singapore, Singapore, Singapore.,Translational Laboratory in Genetic Medicine, Singapore, Singapore
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19
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Camerino GM, Tarantino N, Canfora I, De Bellis M, Musumeci O, Pierno S. Statin-Induced Myopathy: Translational Studies from Preclinical to Clinical Evidence. Int J Mol Sci 2021; 22:ijms22042070. [PMID: 33669797 PMCID: PMC7921957 DOI: 10.3390/ijms22042070] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 02/14/2021] [Accepted: 02/15/2021] [Indexed: 02/07/2023] Open
Abstract
Statins are the most prescribed and effective drugs to treat cardiovascular diseases (CVD). Nevertheless, these drugs can be responsible for skeletal muscle toxicity which leads to reduced compliance. The discontinuation of therapy increases the incidence of CVD. Thus, it is essential to assess the risk. In fact, many studies have been performed at preclinical and clinical level to investigate pathophysiological mechanisms and clinical implications of statin myotoxicity. Consequently, new toxicological aspects and new biomarkers have arisen. Indeed, these drugs may affect gene transcription and ion transport and contribute to muscle function impairment. Identifying a marker of toxicity is important to prevent or to cure statin induced myopathy while assuring the right therapy for hypercholesterolemia and counteracting CVD. In this review we focused on the mechanisms of muscle damage discovered in preclinical and clinical studies and highlighted the pathological situations in which statin therapy should be avoided. In this context, preventive or substitutive therapies should also be evaluated.
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Affiliation(s)
- Giulia Maria Camerino
- Section of Pharmacology, Department of Pharmacy and Drug Sciences, University of Bari “Aldo Moro”, 70125 Bari, Italy; (G.M.C.); (N.T.); (I.C.); (M.D.B.)
| | - Nancy Tarantino
- Section of Pharmacology, Department of Pharmacy and Drug Sciences, University of Bari “Aldo Moro”, 70125 Bari, Italy; (G.M.C.); (N.T.); (I.C.); (M.D.B.)
| | - Ileana Canfora
- Section of Pharmacology, Department of Pharmacy and Drug Sciences, University of Bari “Aldo Moro”, 70125 Bari, Italy; (G.M.C.); (N.T.); (I.C.); (M.D.B.)
| | - Michela De Bellis
- Section of Pharmacology, Department of Pharmacy and Drug Sciences, University of Bari “Aldo Moro”, 70125 Bari, Italy; (G.M.C.); (N.T.); (I.C.); (M.D.B.)
| | - Olimpia Musumeci
- Unit of Neurology and Neuromuscular Disorders, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, Italy;
| | - Sabata Pierno
- Section of Pharmacology, Department of Pharmacy and Drug Sciences, University of Bari “Aldo Moro”, 70125 Bari, Italy; (G.M.C.); (N.T.); (I.C.); (M.D.B.)
- Correspondence:
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20
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Turongkaravee S, Jittikoon J, Lukkunaprasit T, Sangroongruangsri S, Chaikledkaew U, Thakkinstian A. A systematic review and meta-analysis of genotype-based and individualized data analysis of SLCO1B1 gene and statin-induced myopathy. THE PHARMACOGENOMICS JOURNAL 2021; 21:296-307. [PMID: 33608664 PMCID: PMC8159730 DOI: 10.1038/s41397-021-00208-w] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Revised: 12/05/2020] [Accepted: 01/15/2021] [Indexed: 01/31/2023]
Abstract
This meta-analysis was conducted to determine the genotypic effects of rs4149056 and rs2306283 polymorphism in SLCO1B1 gene on myopathy in patients with statin. Studies were searched using multiple databases and selected following inclusion criteria. Two reviewers independently performed data extraction and assessments for risk of bias. Fixed-or-random-effect was applied to pool allele frequency/effects. Mixed-effect logit model was used to pool genotypic effects using individual patient data. Heterogeneity and publication bias were explored. Fourteen studies were pooled for rs4149056; the minor C allele frequency were 15% in Caucasians and 14% in Asians. Six studies were pooled for rs2306283; the minor G allele frequency was 34% in Caucasian and 75% in Asians. Genotypic effects of rs4149056 polymorphism in Caucasians indicated that statin users who carried CC and TC genotypes had a significantly higher risk of myopathy than those who carried TT genotype, with a pooled odds ratio (OR) of 2.9 (95% confidence interval, 1.59, 5.34) and 1.6 (1.20, 2.16), respectively. For subgroup analysis, CC and TC genotypes also suggested a higher risk of myopathy in simvastatin users [OR = 2.8 (1.17, 6.77) and OR = 1.8 (1.15, 2.77), respectively] and in atorvastatin users [OR = 4.0 (1.23, 12.63) and OR = 2.0 (1.11, 3.52), respectively] than those who carried TT genotype. There was no significant association between rs2306283 polymorphism and myopathy in Caucasians and Asians. There was no evidence of publication bias for both polymorphisms.
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Affiliation(s)
- Saowalak Turongkaravee
- grid.10223.320000 0004 1937 0490Social, Economic and Administrative Pharmacy (SEAP) Graduate Program, Faculty of Pharmacy, Mahidol University, Bangkok, Thailand
| | - Jiraphun Jittikoon
- grid.10223.320000 0004 1937 0490Department of Biochemistry, Faculty of Pharmacy, Mahidol University, Bangkok, Thailand
| | - Thitiya Lukkunaprasit
- grid.10223.320000 0004 1937 0490Department of Clinical Epidemiology and Biostatistics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Sermsiri Sangroongruangsri
- grid.10223.320000 0004 1937 0490Social and Administrative Pharmacy Division, Department of Pharmacy, Faculty of Pharmacy, Mahidol University, Bangkok, Thailand
| | - Usa Chaikledkaew
- grid.10223.320000 0004 1937 0490Social and Administrative Pharmacy Division, Department of Pharmacy, Faculty of Pharmacy, Mahidol University, Bangkok, Thailand ,grid.10223.320000 0004 1937 0490Mahidol University Health Technology Assessment (MUHTA) Graduate Program, Mahidol University, Bangkok, Thailand
| | - Ammarin Thakkinstian
- grid.10223.320000 0004 1937 0490Department of Clinical Epidemiology and Biostatistics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand ,grid.10223.320000 0004 1937 0490Mahidol University Health Technology Assessment (MUHTA) Graduate Program, Mahidol University, Bangkok, Thailand
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21
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Vassy JL, Gaziano JM, Green RC, Ferguson RE, Advani S, Miller SJ, Chun S, Hage AK, Seo SJ, Majahalme N, MacMullen L, Zimolzak AJ, Brunette CA. Effect of Pharmacogenetic Testing for Statin Myopathy Risk vs Usual Care on Blood Cholesterol: A Randomized Clinical Trial. JAMA Netw Open 2020; 3:e2027092. [PMID: 33270123 PMCID: PMC7716196 DOI: 10.1001/jamanetworkopen.2020.27092] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
IMPORTANCE Nonadherence to statin guidelines is common. The solute carrier organic anion transporter family member 1B1 (SLCO1B1) genotype is associated with simvastatin myopathy risk and is proposed for clinical implementation. The unintended harms of using pharmacogenetic information to guide pharmacotherapy remain a concern for some stakeholders. OBJECTIVE To determine the impact of delivering SLCO1B1 pharmacogenetic results to physicians on the effectiveness of atherosclerotic cardiovascular disease (ASCVD) prevention (measured by low-density lipoprotein cholesterol [LDL-C] levels) and concordance with prescribing guidelines for statin safety and effectiveness. DESIGN, SETTING, AND PARTICIPANTS This randomized clinical trial was performed from December 2015 to July 2019 at 8 primary care practices in the Veterans Affairs Boston Healthcare System. Participants included statin-naive patients with elevated ASCVD risk. Data analysis was performed from October 2019 to September 2020. INTERVENTIONS SLCO1B1 genotyping and results reporting to primary care physicians at baseline (intervention group) vs after 1 year (control group). MAIN OUTCOMES AND MEASURES The primary outcome was the 1-year change in LDL-C level. The secondary outcomes were 1-year concordance with American College of Cardiology-American Heart Association and Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for statin therapy and statin-associated muscle symptoms (SAMS). RESULTS Among 408 patients (mean [SD] age, 64.1 [7.8] years; 25 women [6.1%]), 193 were randomized to the intervention group and 215 were randomized to the control group. Overall, 120 participants (29%) had a SLCO1B1 genotype indicating increased simvastatin myopathy risk. Physicians offered statin therapy to 65 participants (33.7%) in the intervention group and 69 participants (32.1%) in the control group. Compared with patients whose physicians did not know their SLCO1B1 results at baseline, patients whose physicians received the results had noninferior reductions in LDL-C at 12 months (mean [SE] change in LDL-C, -1.1 [1.2] mg/dL in the intervention group and -2.2 [1.3] mg/dL in the control group; difference, -1.1 mg/dL; 90% CI, -4.1 to 1.8 mg/dL; P < .001 for noninferiority margin of 10 mg/dL). The proportion of patients with American College of Cardiology-American Heart Association guideline-concordant statin prescriptions in the intervention group was noninferior to that in the control group (12 patients [6.2%] vs 14 patients [6.5%]; difference, -0.003; 90% CI, -0.038 to 0.032; P < .001 for noninferiority margin of 15%). All patients in both groups were concordant with CPIC guidelines for safe statin prescribing. Physicians documented 2 and 3 cases of SAMS in the intervention and control groups, respectively, none of which was associated with a CPIC guideline-discordant prescription. Among patients with a decreased or poor SLCO1B1 transporter function genotype, simvastatin was prescribed to 1 patient in the control group but none in the intervention group. CONCLUSIONS AND RELEVANCE Clinical testing and reporting of SLCO1B1 results for statin myopathy risk did not result in poorer ASCVD prevention in a routine primary care setting and may have been associated with physicians avoiding simvastatin prescriptions for patients at genetic risk for SAMS. Such an absence of harm should reassure stakeholders contemplating the clinical use of available pharmacogenetic results. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT02871934.
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Affiliation(s)
- Jason L. Vassy
- VA Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Ariadne Labs, Boston, Massachusetts
| | - J. Michael Gaziano
- VA Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Robert C. Green
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Ariadne Labs, Boston, Massachusetts
| | - Ryan E. Ferguson
- VA Boston Healthcare System, Boston, Massachusetts
- Department of General Internal Medicine, Boston University School of Medicine, Boston, Massachusetts
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
| | | | | | - Sojeong Chun
- Massachusetts College of Pharmacy and Health Sciences, Boston
| | - Anthony K. Hage
- Massachusetts College of Pharmacy and Health Sciences, Boston
| | - Soo-Ji Seo
- Massachusetts College of Pharmacy and Health Sciences, Boston
| | | | | | - Andrew J. Zimolzak
- VA Boston Healthcare System, Boston, Massachusetts
- Baylor College of Medicine, Houston, Texas
- Michael E. DeBakey VA Medical Center, Houston, Texas
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22
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Rollinson V, Turner R, Pirmohamed M. Pharmacogenomics for Primary Care: An Overview. Genes (Basel) 2020; 11:E1337. [PMID: 33198260 PMCID: PMC7696803 DOI: 10.3390/genes11111337] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 11/02/2020] [Accepted: 11/04/2020] [Indexed: 12/11/2022] Open
Abstract
Most of the prescribing and dispensing of medicines happens in primary care. Pharmacogenomics (PGx) is the study and clinical application of the role of genetic variation on drug response. Mounting evidence suggests PGx can improve the safety and/or efficacy of several medications commonly prescribed in primary care. However, implementation of PGx has generally been limited to a relatively few academic hospital centres, with little adoption in primary care. Despite this, many primary healthcare providers are optimistic about the role of PGx in their future practice. The increasing prevalence of direct-to-consumer genetic testing and primary care PGx studies herald the plausible gradual introduction of PGx into primary care and highlight the changes needed for optimal translation. In this article, the potential utility of PGx in primary care will be explored and on-going barriers to implementation discussed. The evidence base of several drug-gene pairs relevant to primary care will be outlined with a focus on antidepressants, codeine and tramadol, statins, clopidogrel, warfarin, metoprolol and allopurinol. This review is intended to provide both a general introduction to PGx with a more in-depth overview of elements relevant to primary care.
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23
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Xiang Q, Zhang XD, Mu GY, Wang Z, Liu ZY, Xie QF, Hu K, Zhang Z, Ma LY, Jiang J, Cui YM. Correlation between single-nucleotide polymorphisms and statin-induced myopathy: a mixed-effects model meta-analysis. Eur J Clin Pharmacol 2020; 77:569-581. [PMID: 33150478 DOI: 10.1007/s00228-020-03029-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Accepted: 10/21/2020] [Indexed: 12/18/2022]
Abstract
PURPOSE A meta-analysis was performed to evaluate the correlation between single-nucleotide polymorphisms (SNPs) and risk of statin-induced myopathy (SIM). METHODS We retrieved the studies published on SIM until April 2019 from the PubMed, Embase, and Cochrane Library databases. We collected data from 32 studies that analyzed 10 SNPs in five genes and included 21,692 individuals and nine statins. RESULTS The analysis of the heterozygous (p = 0.017), homozygous (p = 0.002), dominant (p = 0.005), and recessive models (p = 0.009) of SLCO1B1 rs4149056 showed that this SNP increases the risk of SIM. Conversely, heterozygous (p = 0.048) and dominant models (p = 0.030) of SLCO1B1 rs4363657 demonstrated that this SNP is associated with a reduced risk of SIM. Moreover, an increased risk of SIM was predicted for carriers of the rs4149056 C allele among simvastatin-treated patients, whereas carriers of the GATM rs9806699 A allele among rosuvastatin-treated patients had a lower risk of SIM. CONCLUSION The meta-analysis revealed that the rs4149056 and rs4363657 SNPs in SLCO1B1 and the rs9806699 SNP in GATM are correlated with the risk of SIM.
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Affiliation(s)
- Qian Xiang
- Department of Pharmacy, Peking University First Hospital, Beijing, 100034, China
| | - Xiao-Dan Zhang
- Department of Pharmacy, Peking University First Hospital, Beijing, 100034, China
| | - Guang-Yan Mu
- Department of Pharmacy, Peking University First Hospital, Beijing, 100034, China
| | - Zhe Wang
- Department of Pharmacy, Peking University First Hospital, Beijing, 100034, China
| | - Zhi-Yan Liu
- Department of Pharmacy, Peking University First Hospital, Beijing, 100034, China
| | - Qiu-Fen Xie
- Department of Pharmacy, Peking University First Hospital, Beijing, 100034, China
| | - Kun Hu
- Department of Pharmacy, Peking University First Hospital, Beijing, 100034, China
| | - Zhuo Zhang
- Department of Pharmacy, Peking University First Hospital, Beijing, 100034, China
| | - Ling-Yue Ma
- Department of Pharmacy, Peking University First Hospital, Beijing, 100034, China
| | - Jie Jiang
- Department of Cardiology, Peking University First Hospital, Beijing, 100034, China
| | - Yi-Min Cui
- Department of Pharmacy, Peking University First Hospital, Beijing, 100034, China. .,, Beijing, China.
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24
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Kee PS, Chin PKL, Kennedy MA, Maggo SDS. Pharmacogenetics of Statin-Induced Myotoxicity. Front Genet 2020; 11:575678. [PMID: 33193687 PMCID: PMC7596698 DOI: 10.3389/fgene.2020.575678] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Accepted: 08/26/2020] [Indexed: 12/15/2022] Open
Abstract
Statins, a class of lipid-lowering medications, have been a keystone treatment in cardiovascular health. However, adverse effects associated with statin use impact patient adherence, leading to statin discontinuation. Statin-induced myotoxicity (SIM) is one of the most common adverse effects, prevalent across all ages, genders, and ethnicities. Although certain demographic cohorts carry a higher risk, the impaired quality of life attributed to SIM is significant. The pathogenesis of SIM remains to be fully elucidated, but it is clear that SIM is multifactorial. These factors include drug-drug interactions, renal or liver dysfunction, and genetics. Genetic-inferred risk for SIM was first reported by a landmark genome-wide association study, which reported a higher risk of SIM with a polymorphism in the SLCO1B1 gene. Since then, research associating genetic factors with SIM has expanded widely and has become one of the foci in the field of pharmacogenomics. This review provides an update on the genetic risk factors associated with SIM.
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Affiliation(s)
- Ping Siu Kee
- Gene Structure and Function Laboratory, Carney Centre for Pharmacogenomics, Department of Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand
| | | | - Martin A. Kennedy
- Gene Structure and Function Laboratory, Carney Centre for Pharmacogenomics, Department of Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand
| | - Simran D. S. Maggo
- Gene Structure and Function Laboratory, Carney Centre for Pharmacogenomics, Department of Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand
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25
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Turner RM, Radman I, Bozina N, Alfirevic A. Pharmacogenetics and statin-related myopathy: what do we know? Pharmacogenomics 2020; 21:821-825. [DOI: 10.2217/pgs-2020-0041] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Affiliation(s)
- Richard Myles Turner
- Department of Molecular & Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Block A, Waterhouse Building, 1–5 Brownlow Street, Liverpool, L69 3GL, UK
| | - Ivana Radman
- University Department of Ophthalmology, University Hospital Centre Sestre milosrdnice, Vinogradska cesta, 10000 Zagreb, Croatia
| | - Nada Bozina
- Department of Pharmacology, School of Medicine, University of Zagreb, Department of Laboratory Diagnostics, University Hospital Centre Zagreb, Kispaticeva 12, 10000 Zagreb, Croatia
| | - Ana Alfirevic
- Department of Molecular & Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Block A, Waterhouse Building, 1–5 Brownlow Street, Liverpool, L69 3GL, UK
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26
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Turner RM, Fontana V, Zhang JE, Carr D, Yin P, FitzGerald R, Morris AP, Pirmohamed M. A Genome-wide Association Study of Circulating Levels of Atorvastatin and Its Major Metabolites. Clin Pharmacol Ther 2020; 108:287-297. [PMID: 32128760 DOI: 10.1002/cpt.1820] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Accepted: 01/28/2020] [Indexed: 01/03/2023]
Abstract
Atorvastatin (ATV) is frequently prescribed and generally well tolerated, but can lead to myotoxicity, especially at higher doses. A genome-wide association study of circulating levels of ATV, 2-hydroxy (2-OH) ATV, ATV lactone (ATV L), and 2-OH ATV L was performed in 590 patients who had been hospitalized with a non-ST elevation acute coronary syndrome 1 month earlier and were on high-dose ATV (80 mg or 40 mg daily). The UGT1A locus (lead single nucleotide polymorphism, rs887829) was strongly associated with both increased 2-OH ATV/ATV (P = 7.25 × 10-16 ) and 2-OH ATV L/ATV L (P = 3.95 × 10-15 ) metabolic ratios. Moreover, rs45446698, which tags CYP3A7*1C, was nominally associated with increased 2-OH ATV/ATV (P = 6.18 × 10-7 ), and SLCO1B1 rs4149056 with increased ATV (P = 2.21 × 10-6 ) and 2-OH ATV (P = 1.09 × 10-6 ) levels. In a subset of these patients whose levels of ATV and metabolites had also been measured at 12 months after hospitalization (n = 149), all of these associations remained, except for 2-OH ATV and rs4149056 (P = 0.057). Clinically, rs4149056 was associated with increased muscular symptoms (odds ratio (OR) 3.97; 95% confidence interval (CI) 1.29-12.27; P = 0.016) and ATV intolerance (OR 1.55; 95% CI 1.09-2.19; P = 0.014) in patients (n = 870) primarily discharged on high-dose ATV. In summary, both novel and recognized genetic associations have been identified with circulating levels of ATV and its major metabolites. Further study is warranted to determine the clinical utility of genotyping rs4149056 in patients on high-dose ATV.
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Affiliation(s)
- Richard M Turner
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Vanessa Fontana
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Jieying E Zhang
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Daniel Carr
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Peng Yin
- Department of Biostatistics, University of Liverpool, Liverpool, UK.,Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, Shenzhen, China
| | - Richard FitzGerald
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Andrew P Morris
- Department of Biostatistics, University of Liverpool, Liverpool, UK.,Division of Musculoskeletal and Dermatological Sciences, University of Manchester, Manchester, UK
| | - Munir Pirmohamed
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK
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27
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The impact of statins on physical activity and exercise capacity: an overview of the evidence, mechanisms, and recommendations. Eur J Appl Physiol 2020; 120:1205-1225. [PMID: 32248287 DOI: 10.1007/s00421-020-04360-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2019] [Accepted: 03/24/2020] [Indexed: 12/16/2022]
Abstract
PURPOSE Statins are among the most widely prescribed medications worldwide. Considered the 'gold-standard' treatment for cardiovascular disease (CVD), statins inhibit HMG-CoA reductase to ultimately reduce serum LDL-cholesterol levels. Unfortunately, the main adverse event of statin use is the development of muscle-associated problems, referred to as SAMS (statin-associated muscle symptoms). While regular moderate physical activity also decreases CVD risk, there is apprehension that physical activity may induce and/or exacerbate SAMS. While much work has gone into identifying the epidemiology of SAMS, only recent research has focused on the extent to which these muscle symptoms are accompanied by functional declines. The purpose of this review is to provide an overview of possible mechanisms underlying SAMS and summarize current evidence regarding the relationship between statin treatment, physical activity, exercise capacity, and SAMS development. METHODS PubMed and Google Scholar databases were used to search the most relevant and up-to-date peer-reviewed research on the topic. RESULTS The mechanism(s) behind SAMS, including altered mitochondrial metabolism, reduced coenzyme Q10 levels, reduced vitamin D levels, impaired calcium homeostasis, elevated extracellular glutamate, and genetic polymorphisms, still lack consensus and remain up for debate. Our summation of the evidence leads us to suggest that the etiology of SAMS development is likely multifactorial. Our review also demonstrates that there is limited evidence for statins impairing exercise adaptations or reducing exercise capacity for the majority of the investigated populations. CONCLUSION The available evidence indicates that the benefits of engaging in physical activity while on statin medication largely outweigh the risks.
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28
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Al-Salameh A, Danchin N, Verstuyft C, Kotti S, Puymirat E, Ferrières J, Schiele F, Coste P, Lemesle G, Cayla G, Becquemont L, Simon T. Association between rs4149056 variant in SLCO1B1 and early discontinuation of statin after acute myocardial infarction. Pharmacogenomics 2020; 21:163-172. [DOI: 10.2217/pgs-2019-0109] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Data from two French surveys were used to analyze the association between in-hospital statin discontinuation and SLCO1B1 polymorphism (rs4149056) in patients with acute myocardial infarction. Using TaqMan allelic discrimination assay, 1674 and 1708 patients were genotyped for SLCO1B1 in 2005 and 2010, respectively. The association with in-hospital statin discontinuation was assessed after adjusting for confounding factors. In 2005, homozygosity for the reduced-function allele was associated with an increased risk of in-hospital statin discontinuation (OR: 3.68; p = 0.004) compared with the wild-type allele but this association disappeared in 2010. However, statin type and intensity-dose differed significantly between the surveys. SLCO1B1 polymorphism (rs4149056) does not seem to be a major determinant of early ‘in-hospital’ statin discontinuation after acute myocardial infarction.
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Affiliation(s)
- Abdallah Al-Salameh
- Clinical Research Center Paris-Sud, Bicêtre University Hospital, Assistance Publique-Hôpitaux de Paris (AP-HP), 78 rue du Général Leclerc, F-94270 Le Kremlin-Bicêtre, France
- Centre de Recherche en Epidémiologie et Santé des Populations (CESP), Faculté de Médecine – Université Paris-Sud, INSERM, Université Paris-Saclay, 94805, Villejuif, France
| | - Nicolas Danchin
- Department of Cardiology, Hôpital Européen Georges Pompidou, AP-HP, 75015 Paris, France
- Université Paris-Descartes, Paris, France
- FACT (French Alliance for Cardiovascular Trials), an F-CRIN Network, Paris, France
| | - Céline Verstuyft
- University Paris-Sud Faculty of Medicine, Pharmacology Department, Le Kremlin Bicêtre, France and Bicêtre University Hospital, AP-HP, Le Kremlin Bicêtre, France
| | - Salma Kotti
- Department of Clinical Pharmacology, Clinical Platform of Research of East of Paris (URC-EST-CRC-CRB), Hôpital Saint Antoine, AP-HP, Paris, France
| | - Etienne Puymirat
- Department of Cardiology, Hôpital Européen Georges Pompidou, AP-HP, 75015 Paris, France
- Université Paris-Descartes, Paris, France
| | - Jean Ferrières
- Department of Cardiology, Toulouse University Hospital, UMR1027, INSERM, 31059 Toulouse, France
| | - François Schiele
- Department of Cardiology, University Hospital Jean Minjoz, 25030 Besançon, France
| | - Pierre Coste
- Hôpital Cardiologique Haut Lévêque, University Hospital of Bordeaux, 33600 Pessac, France
| | - Gilles Lemesle
- Department of Cardiology, Lille Regional University Hospital, 59037 Lille, France
| | - Guillaume Cayla
- Department of Cardiology, Nîmes University Hospital, 30900 Nîmes, France
| | - Laurent Becquemont
- Clinical Research Center Paris-Sud, Bicêtre University Hospital, Assistance Publique-Hôpitaux de Paris (AP-HP), 78 rue du Général Leclerc, F-94270 Le Kremlin-Bicêtre, France
- Centre de Recherche en Epidémiologie et Santé des Populations (CESP), Faculté de Médecine – Université Paris-Sud, INSERM, Université Paris-Saclay, 94805, Villejuif, France
- University Paris-Sud Faculty of Medicine, Pharmacology Department, Le Kremlin Bicêtre, France and Bicêtre University Hospital, AP-HP, Le Kremlin Bicêtre, France
| | - Tabassome Simon
- FACT (French Alliance for Cardiovascular Trials), an F-CRIN Network, Paris, France
- Department of Clinical Pharmacology, Clinical Platform of Research of East of Paris (URC-EST-CRC-CRB), Hôpital Saint Antoine, AP-HP, Paris, France
- Sorbonne Université, Site Saint Antoine, Paris, France
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Turner RM, Pirmohamed M. Statin-Related Myotoxicity: A Comprehensive Review of Pharmacokinetic, Pharmacogenomic and Muscle Components. J Clin Med 2019; 9:jcm9010022. [PMID: 31861911 PMCID: PMC7019839 DOI: 10.3390/jcm9010022] [Citation(s) in RCA: 98] [Impact Index Per Article: 19.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 12/17/2019] [Accepted: 12/18/2019] [Indexed: 02/06/2023] Open
Abstract
Statins are a cornerstone in the pharmacological prevention of cardiovascular disease. Although generally well tolerated, a small subset of patients experience statin-related myotoxicity (SRM). SRM is heterogeneous in presentation; phenotypes include the relatively more common myalgias, infrequent myopathies, and rare rhabdomyolysis. Very rarely, statins induce an anti-HMGCR positive immune-mediated necrotizing myopathy. Diagnosing SRM in clinical practice can be challenging, particularly for mild SRM that is frequently due to alternative aetiologies and the nocebo effect. Nevertheless, SRM can directly harm patients and lead to statin discontinuation/non-adherence, which increases the risk of cardiovascular events. Several factors increase systemic statin exposure and predispose to SRM, including advanced age, concomitant medications, and the nonsynonymous variant, rs4149056, in SLCO1B1, which encodes the hepatic sinusoidal transporter, OATP1B1. Increased exposure of skeletal muscle to statins increases the risk of mitochondrial dysfunction, calcium signalling disruption, reduced prenylation, atrogin-1 mediated atrophy and pro-apoptotic signalling. Rare variants in several metabolic myopathy genes including CACNA1S, CPT2, LPIN1, PYGM and RYR1 increase myopathy/rhabdomyolysis risk following statin exposure. The immune system is implicated in both conventional statin intolerance/myotoxicity via LILRB5 rs12975366, and a strong association exists between HLA-DRB1*11:01 and anti-HMGCR positive myopathy. Epigenetic factors (miR-499-5p, miR-145) have also been implicated in statin myotoxicity. SRM remains a challenge to the safe and effective use of statins, although consensus strategies to manage SRM have been proposed. Further research is required, including stringent phenotyping of mild SRM through N-of-1 trials coupled to systems pharmacology omics- approaches to identify novel risk factors and provide mechanistic insight.
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30
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Malki MA, Pearson ER. Drug-drug-gene interactions and adverse drug reactions. THE PHARMACOGENOMICS JOURNAL 2019; 20:355-366. [PMID: 31792369 PMCID: PMC7253354 DOI: 10.1038/s41397-019-0122-0] [Citation(s) in RCA: 87] [Impact Index Per Article: 17.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Revised: 11/11/2019] [Accepted: 11/17/2019] [Indexed: 11/21/2022]
Abstract
The economic and health burden caused by adverse drug reactions has increased dramatically in the last few years. This is likely to be mediated by increasing polypharmacy, which increases the likelihood for drug–drug interactions. Tools utilized by healthcare practitioners to flag potential adverse drug reactions secondary to drug–drug interactions ignore individual genetic variation, which has the potential to markedly alter the severity of these interactions. To date there have been limited published studies on impact of genetic variation on drug–drug interactions. In this review, we establish a detailed classification for pharmacokinetic drug–drug–gene interactions, and give examples from the literature that support this approach. The increasing availability of real-world drug outcome data linked to genetic bioresources is likely to enable the discovery of previously unrecognized, clinically important drug–drug–gene interactions.
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Affiliation(s)
- Mustafa Adnan Malki
- Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Ewan Robert Pearson
- Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK.
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31
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Janssen L, Allard NAE, Saris CGJ, Keijer J, Hopman MTE, Timmers S. Muscle Toxicity of Drugs: When Drugs Turn Physiology into Pathophysiology. Physiol Rev 2019; 100:633-672. [PMID: 31751166 DOI: 10.1152/physrev.00002.2019] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Drugs are prescribed to manage or prevent symptoms and diseases, but may sometimes cause unexpected toxicity to muscles. The symptomatology and clinical manifestations of the myotoxic reaction can vary significantly between drugs and between patients on the same drug. This poses a challenge on how to recognize and prevent the occurrence of drug-induced muscle toxicity. The key to appropriate management of myotoxicity is prompt recognition that symptoms of patients may be drug related and to be aware that inter-individual differences in susceptibility to drug-induced toxicity exist. The most prevalent and well-documented drug class with unintended myotoxicity are the statins, but even today new classes of drugs with unintended myotoxicity are being discovered. This review will start off by explaining the principles of drug-induced myotoxicity and the different terminologies used to distinguish between grades of toxicity. The main part of the review will focus on the most important pathogenic mechanisms by which drugs can cause muscle toxicity, which will be exemplified by drugs with high risk of muscle toxicity. This will be done by providing information on key clinical and laboratory aspects, muscle electromyography patterns and biopsy results, and pathological mechanism and management for a specific drug from each pathogenic classification. In addition, rather new classes of drugs with unintended myotoxicity will be highlighted. Furthermore, we will explain why it is so difficult to diagnose drug-induced myotoxicity, and which tests can be used as a diagnostic aid. Lastly, a brief description will be given of how to manage and treat drug-induced myotoxicity.
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Affiliation(s)
- Lando Janssen
- Departments of Physiology, Hematology, and Neurology, Radboud University Medical Center, Nijmegen, The Netherlands; and Human and Animal Physiology, Wageningen University & Research, Wageningen, The Netherlands
| | - Neeltje A E Allard
- Departments of Physiology, Hematology, and Neurology, Radboud University Medical Center, Nijmegen, The Netherlands; and Human and Animal Physiology, Wageningen University & Research, Wageningen, The Netherlands
| | - Christiaan G J Saris
- Departments of Physiology, Hematology, and Neurology, Radboud University Medical Center, Nijmegen, The Netherlands; and Human and Animal Physiology, Wageningen University & Research, Wageningen, The Netherlands
| | - Jaap Keijer
- Departments of Physiology, Hematology, and Neurology, Radboud University Medical Center, Nijmegen, The Netherlands; and Human and Animal Physiology, Wageningen University & Research, Wageningen, The Netherlands
| | - Maria T E Hopman
- Departments of Physiology, Hematology, and Neurology, Radboud University Medical Center, Nijmegen, The Netherlands; and Human and Animal Physiology, Wageningen University & Research, Wageningen, The Netherlands
| | - Silvie Timmers
- Departments of Physiology, Hematology, and Neurology, Radboud University Medical Center, Nijmegen, The Netherlands; and Human and Animal Physiology, Wageningen University & Research, Wageningen, The Netherlands
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32
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Johnson D, Hughes D, Pirmohamed M, Jorgensen A. Evidence to Support Inclusion of Pharmacogenetic Biomarkers in Randomised Controlled Trials. J Pers Med 2019; 9:E42. [PMID: 31480618 PMCID: PMC6789450 DOI: 10.3390/jpm9030042] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 08/15/2019] [Accepted: 08/19/2019] [Indexed: 01/01/2023] Open
Abstract
Pharmacogenetics and biomarkers are becoming normalised as important technologies to improve drug efficacy rates, reduce the incidence of adverse drug reactions, and make informed choices for targeted therapies. However, their wider clinical implementation has been limited by a lack of robust evidence. Suitable evidence is required before a biomarker's clinical use, and also before its use in a clinical trial. We have undertaken a review of five pharmacogenetic biomarker-guided randomised controlled trials (RCTs) and evaluated the evidence used by these trials to justify biomarker inclusion. We assessed and quantified the evidence cited in published rationale papers, or where these were not available, obtained protocols from trial authors. Very different levels of evidence were provided by the trials. We used these observations to write recommendations for future justifications of biomarker use in RCTs and encourage regulatory authorities to write clear guidelines.
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Affiliation(s)
- Danielle Johnson
- Institute of Translational Medicine, Department of Biostatistics, University of Liverpool, Waterhouse Building, 1-5 Brownlow Street, Liverpool L69 3GL, UK.
| | - Dyfrig Hughes
- Centre for Health Economics and Medicines Evaluation, Bangor University, Ardudwy, Normal Site, Bangor LL57 2PZ, UK
| | - Munir Pirmohamed
- MRC Centre for Drug Safety Science and Wolfson Centre for Personalised Medicine, Institute of Translational Medicine, Waterhouse Building, 1-5 Brownlow Street, Liverpool L69 3GL, UK
| | - Andrea Jorgensen
- Institute of Translational Medicine, Department of Biostatistics, University of Liverpool, Waterhouse Building, 1-5 Brownlow Street, Liverpool L69 3GL, UK
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33
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Brunham LR, Baker S, Mammen A, Mancini GBJ, Rosenson RS. Role of genetics in the prediction of statin-associated muscle symptoms and optimization of statin use and adherence. Cardiovasc Res 2019; 114:1073-1081. [PMID: 29878063 DOI: 10.1093/cvr/cvy119] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2018] [Accepted: 05/31/2018] [Indexed: 12/20/2022] Open
Abstract
Statin therapy reduces cardiovascular events in patients with, or at risk of, atherosclerotic cardiovascular disease. However, statins are underutilized in patients for whom they are indicated and are frequently discontinued. Discontinuation may be the result of statin-associated muscle symptoms (SAMS), which encompass a broad spectrum of clinical phenotypes from myalgia to severe myopathy. As with many adverse drug reactions (ADRs), inter-individual variability in susceptibility to SAMS is due, at least in part, to differences in host genetics. The genetic basis for SAMS has been investigated in candidate gene studies, genome-wide association studies, and, more recently, studies of multi-omic networks, including at the transcriptome level. In this article, we provide a systematic review of the pharmacogenetic basis of SAMS, focusing on how an understanding of the genetic and molecular determinants of SAMS can be considered in a personalized approach to reduce the incidence of this ADR, optimize statin adherence, and reduce the risk for cardiovascular events.
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Affiliation(s)
- Liam R Brunham
- Department of Medicine, Centre for Heart Lung Innovation, University of British Columbia, St. Paul's Hospital, Rm 166 - 1081 Burrard St., Vancouver, British Columbia V6Z 1Y6, Canada.,Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Steven Baker
- Department of Medicine, Neuromuscular Disease Clinic, McMaster University, Hamilton, Ontario, Canada
| | - Andrew Mammen
- Muscle Disease Unit, National Institutes of Health, Bethesda, MD, USA
| | - G B John Mancini
- Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Robert S Rosenson
- Mount Sinai Heart, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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34
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Carr DF, Francis B, Jorgensen AL, Zhang E, Chinoy H, Heckbert SR, Bis JC, Brody JA, Floyd JS, Psaty BM, Molokhia M, Lapeyre-Mestre M, Conforti A, Alfirevic A, van Staa T, Pirmohamed M. Genomewide Association Study of Statin-Induced Myopathy in Patients Recruited Using the UK Clinical Practice Research Datalink. Clin Pharmacol Ther 2019; 106:1353-1361. [PMID: 31220337 PMCID: PMC6896237 DOI: 10.1002/cpt.1557] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Accepted: 05/24/2019] [Indexed: 12/27/2022]
Abstract
Statins can be associated with myopathy. We have undertaken a genomewide association study (GWAS) to discover and validate genetic risk factors for statin‐induced myopathy in a “real‐world” setting. One hundred thirty‐five patients with statin myopathy recruited via the UK Clinical Practice Research Datalink were genotyped using the Illumina OmniExpress Exome version 1.0 Bead Chip and compared with the Wellcome Trust Case‐Control Consortium (n = 2,501). Nominally statistically significant single nucleotide polymorphism (SNP) signals in the GWAS (P < 5 × 10−5) were further evaluated in several independent cohorts (comprising 332 cases and 449 drug‐tolerant controls). Only one (rs4149056/c.521C>T in the SLCO1B1 gene) SNP was genomewide significant in the severe myopathy (creatine kinase > 10 × upper limit of normal or rhabdomyolysis) group (P = 2.55 × 10−9; odds ratio 5.15; 95% confidence interval 3.13–8.45). The association with SLCO1B1 was present for several statins and replicated in the independent validation cohorts. The data highlight the role of SLCO1B1 c.521C>T SNP as a replicable genetic risk factor for statin myopathy. No other novel genetic risk factors with a similar effect size were identified.
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Affiliation(s)
- Daniel F Carr
- Wolfson Centre for Personalised Medicine, Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - Ben Francis
- Department of Biostatistics, Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - Andrea L Jorgensen
- Department of Biostatistics, Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - Eunice Zhang
- Wolfson Centre for Personalised Medicine, Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - Hector Chinoy
- Rheumatology Department, Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, Salford, UK.,NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
| | - Susan R Heckbert
- Cardiovascular Health Research Unit, Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, USA.,Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, USA.,Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - James S Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, USA.,Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, USA.,Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Mariam Molokhia
- School of Population Health and Environmental Sciences, King's College London, London, UK
| | | | | | - Ana Alfirevic
- Wolfson Centre for Personalised Medicine, Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - Tjeerd van Staa
- Health e-Research Centre, School of Health Sciences, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester, UK.,Faculty of Science, Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht University, Utrecht, The Netherlands
| | - Munir Pirmohamed
- Wolfson Centre for Personalised Medicine, Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK
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35
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Poller B, Woessner R, Barve A, Tillmann HC, Vemula J, Nica A, Elbast W, Schiller H, End P, Camenisch G, Weiss M. Fevipiprant has a low risk of influencing co-medication pharmacokinetics: Impact on simvastatin and rosuvastatin in different SLCO1B1 genotypes. Pulm Pharmacol Ther 2019; 57:101809. [PMID: 31195091 DOI: 10.1016/j.pupt.2019.101809] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 04/23/2019] [Accepted: 05/27/2019] [Indexed: 12/31/2022]
Abstract
Fevipiprant, a prostaglandin D2 receptor 2 antagonist, is in clinical development as a treatment for asthma. The goal of this study was to assess the potential of fevipiprant to cause drug-drug interactions (DDI) as a perpetrator, that is, by altering the pharmacokinetics (PK) of co-medications. In vitro drug interaction studies of clinically relevant drug metabolizing enzymes and transporters were conducted for fevipiprant and its acyl glucuronide (AG) metabolite. Comparison of Ki values with unbound systemic or portal vein steady-state plasma exposure of fevipiprant and its AG metabolite revealed the potential for inhibition of organic anion transporting polypeptide 1B1 (OATP1B1) transporters (R-value of 5.99), while other targets including cytochrome P450 enzymes were not, or only marginally, inhibited. Consequently, an open-label, two-part, two-period, single-sequence clinical study assessed the effect of fevipiprant 450 mg QD on the pharmacokinetics of simvastatin 20 mg and rosuvastatin 20 mg, two statins with different dependency in OATP1B1-mediated hepatic uptake, in healthy adult volunteers. The study also assessed the pharmacogenetics of the SLCO1B1 gene, which encodes OATP1B1. Clinically, fevipiprant 450 mg QD showed a low potential for interaction and increased the peak concentrations of simvastatin acid and rosuvastatin by 2.23- and 1.87-fold, respectively, with little or no impact on total exposure. Genotype analysis confirmed that SLCO1B1 genotype influences statin pharmacokinetics to a similar extent either with or without fevipiprant co-administration. In summary, fevipiprant at 450 mg QD has only minor liabilities as a perpetrator for DDI.
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Affiliation(s)
- Birk Poller
- Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Ralph Woessner
- Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Avantika Barve
- Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA
| | | | | | - Alexandra Nica
- Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Walid Elbast
- Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Hilmar Schiller
- Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Peter End
- Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Gian Camenisch
- Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Markus Weiss
- Novartis Institutes for Biomedical Research, Basel, Switzerland.
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36
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Streja E, Streja DA, Soohoo M, Kleine CE, Hsiung JT, Park C, Moradi H. Precision Medicine and Personalized Management of Lipoprotein and Lipid Disorders in Chronic and End-Stage Kidney Disease. Semin Nephrol 2019; 38:369-382. [PMID: 30082057 DOI: 10.1016/j.semnephrol.2018.05.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Precision medicine is an emerging field that calls for individualization of treatment strategies based on characteristics unique to each patient. In lipid management, current guidelines are driven mainly by clinical trial results that presently indicate that patients with non-dialysis-dependent chronic kidney disease (CKD) should be treated with a β-hydroxy β-methylglutaryl-CoA reductase inhibitor, also known as statin therapy. For patients with end-stage kidney disease (ESKD) being treated with hemodialysis, statin therapy has not been shown to successfully reduce poor outcomes in trials and therefore is not recommended. The two major guidelines dissent on whether statin therapy should be of moderate or high intensity in non-dialysis-dependent CKD patients, but often leave the prescribing clinician to make that decision. These decisions often are complicated by the increased concerns for adverse events such as myopathies in patients with advanced kidney disease and ESKD. In the future, there may be an opportunity to further identify CKD and ESKD patients who are more likely to benefit from lipid-modifying therapy as opposed to those who likely will suffer from its side effects using precision medicine tools. For now, data from genetics studies and subgroup analyses may provide insight for future research directions in this field and we review some of the work that has been published in this regard.
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Affiliation(s)
- Elani Streja
- Harold Simmons Center for Kidney Disease Research and Epidemiology, Division of Nephrology and Hypertension, University of California Irvine Medical Center, Orange, CA.; Nephrology Section, Tibor Rubin Veterans Affairs Medical Center, Long Beach, CA..
| | - Dan A Streja
- Division of Endocrinology, Diabetes and Metabolism, West Los Angeles VA Medical Center, Greater Los Angeles VA Healthcare System, Los Angeles, CA
| | - Melissa Soohoo
- Harold Simmons Center for Kidney Disease Research and Epidemiology, Division of Nephrology and Hypertension, University of California Irvine Medical Center, Orange, CA.; Nephrology Section, Tibor Rubin Veterans Affairs Medical Center, Long Beach, CA
| | - Carola-Ellen Kleine
- Harold Simmons Center for Kidney Disease Research and Epidemiology, Division of Nephrology and Hypertension, University of California Irvine Medical Center, Orange, CA.; Nephrology Section, Tibor Rubin Veterans Affairs Medical Center, Long Beach, CA
| | - Jui-Ting Hsiung
- Harold Simmons Center for Kidney Disease Research and Epidemiology, Division of Nephrology and Hypertension, University of California Irvine Medical Center, Orange, CA.; Nephrology Section, Tibor Rubin Veterans Affairs Medical Center, Long Beach, CA
| | - Christina Park
- Harold Simmons Center for Kidney Disease Research and Epidemiology, Division of Nephrology and Hypertension, University of California Irvine Medical Center, Orange, CA.; Nephrology Section, Tibor Rubin Veterans Affairs Medical Center, Long Beach, CA
| | - Hamid Moradi
- Harold Simmons Center for Kidney Disease Research and Epidemiology, Division of Nephrology and Hypertension, University of California Irvine Medical Center, Orange, CA.; Nephrology Section, Tibor Rubin Veterans Affairs Medical Center, Long Beach, CA
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37
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Hébert HL, Shepherd B, Milburn K, Veluchamy A, Meng W, Carr F, Donnelly LA, Tavendale R, Leese G, Colhoun HM, Dow E, Morris AD, Doney AS, Lang CC, Pearson ER, Smith BH, Palmer CNA. Cohort Profile: Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS). Int J Epidemiol 2019; 47:380-381j. [PMID: 29025058 PMCID: PMC5913637 DOI: 10.1093/ije/dyx140] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/07/2017] [Indexed: 12/25/2022] Open
Affiliation(s)
| | | | - Keith Milburn
- Health Informatics Centre Services, Ninewells Hospital & Medical School, University of Dundee, Dundee, UK
| | - Abirami Veluchamy
- Division of Population Health Sciences.,Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics
| | | | - Fiona Carr
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics
| | | | - Roger Tavendale
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics
| | - Graham Leese
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics
| | - Helen M Colhoun
- Division of Population Health Sciences.,Institute of Genetics & Molecular Medicine
| | - Ellie Dow
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics
| | - Andrew D Morris
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | | | - Chim C Lang
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics
| | - Ewan R Pearson
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics
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38
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Schwarz UI, Gulilat M, Kim RB. The Role of Next-Generation Sequencing in Pharmacogenetics and Pharmacogenomics. Cold Spring Harb Perspect Med 2019; 9:cshperspect.a033027. [PMID: 29844222 DOI: 10.1101/cshperspect.a033027] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Inherited genetic variations in pharmacogenetic loci are widely acknowledged as important determinants of phenotypic differences in drug response, and may be actionable in the clinic. However, recent studies suggest that a considerable number of novel rare variants in pharmacogenes likely contribute to a still unexplained fraction of the observed interindividual variability. Next-generation sequencing (NGS) represents a rapid, relatively inexpensive, large-scale DNA sequencing technology with potential relevance as a comprehensive pharmacogenetic genotyping platform to identify genetic variation related to drug therapy. However, many obstacles remain before the clinical use of NGS-based test results, including technical challenges, functional interpretation, and strict requirements for diagnostic tests. Advanced computational analyses, high-throughput screening methodologies, and generation of shared resources with cell-based and clinical information will facilitate the integration of NGS data into candidate genotyping approaches, likely enhancing future drug phenotype predictions in patients.
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Affiliation(s)
- Ute I Schwarz
- Division of Clinical Pharmacology, Department of Medicine, Western University, London, Ontario N6A 5A5, Canada.,Department of Physiology and Pharmacology, Western University, London, Ontario N6A 5A5, Canada
| | - Markus Gulilat
- Department of Physiology and Pharmacology, Western University, London, Ontario N6A 5A5, Canada
| | - Richard B Kim
- Division of Clinical Pharmacology, Department of Medicine, Western University, London, Ontario N6A 5A5, Canada.,Department of Physiology and Pharmacology, Western University, London, Ontario N6A 5A5, Canada
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39
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40
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Vassy JL, Brunette CA, Majahalme N, Advani S, MacMullen L, Hau C, Zimolzak AJ, Miller SJ. The Integrating Pharmacogenetics in Clinical Care (I-PICC) Study: Protocol for a point-of-care randomized controlled trial of statin pharmacogenetics in primary care. Contemp Clin Trials 2018; 75:40-50. [PMID: 30367991 PMCID: PMC8119226 DOI: 10.1016/j.cct.2018.10.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Revised: 10/04/2018] [Accepted: 10/16/2018] [Indexed: 01/08/2023]
Abstract
BACKGROUND The association between the SLCO1B1 rs4149056 variant and statin-associated muscle symptoms (SAMS) is well validated, but the clinical utility of its implementation in patient care is unknown. DESIGN The Integrating Pharmacogenetics in Clinical Care (I-PICC) Study is a pseudo-cluster randomized controlled trial of SLCO1B1 genotyping among statin-naïve primary care and women's health patients across the Veteran Affairs Boston Healthcare System. Eligible patients of enrolled primary care providers are aged 40-75 and have elevated risk of cardiovascular disease by American College of Cardiology/American Heart Association (ACC/AHA) guidelines. Patients give consent by telephone in advance of an upcoming appointment, but they are enrolled only if and when their provider co-signs an order for SLCO1B1 testing, performed on a blood sample already collected in clinical care. Enrolled patients are randomly allocated to have their providers receive results through the electronic health record at baseline (PGx + arm) versus after 12 months (PGx- arm). The primary outcome is the change in low-density lipoprotein cholesterol (LDL-C) after one year. Secondary outcomes are concordance with Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for simvastatin prescribing, concordance with ACC/AHA guidelines for statin use, and incidence of SAMS. With 408 patients, the study has >80% power to exclude a between-group LDL-C difference of 10 mg/dL (non-inferiority design) and to detect between-group differences of 15% in CPIC guideline concordance (superiority design). CONCLUSION The outcomes of the I-PICC Study will inform the clinical utility of preemptive SLCO1B1 testing in the routine practice of medicine, including its proposed benefits and unforeseen risks.
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Affiliation(s)
- Jason L Vassy
- VA Boston Healthcare System, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, USA.
| | | | | | | | | | - Cynthia Hau
- VA Boston Healthcare System, Boston, MA, USA
| | - Andrew J Zimolzak
- VA Boston Healthcare System, Boston, MA, USA; Boston University School of Medicine, Boston, MA, USA
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Evaluation of serum SLCO1B1 levels and genetic variants of SLCO1B1 rs4149056 and rs2306283 in patients with early and exudative age-related macular degeneration. Gene 2018; 676:139-145. [DOI: 10.1016/j.gene.2018.07.031] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Revised: 06/18/2018] [Accepted: 07/11/2018] [Indexed: 01/10/2023]
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Vassy JL, Chun S, Advani S, Ludin SA, Smith JG, Alligood EC. Impact of SLCO1B1 Pharmacogenetic Testing on Patient and Healthcare Outcomes: A Systematic Review. Clin Pharmacol Ther 2018; 106:360-373. [PMID: 30137643 DOI: 10.1002/cpt.1223] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Accepted: 08/14/2018] [Indexed: 12/22/2022]
Abstract
Demonstrated improvements in patient outcomes will facilitate the clinical implementation of pharmacogenetic testing. Using the association between solute carrier organic anion transporter family member 1B1 (SLCO1B1) and statin-associated muscle symptoms (SAMSs) as a model, we conducted a systematic review of patient outcomes after delivery of SLCO1B1 results. Using PubMed and Embase searches through December 19, 2017, we identified 37 eligible records reporting preliminary or final outcomes, including six studies delivering only SLCO1B1 results and five large healthcare system-based implementation projects of multipharmacogene panels. Two small trials have demonstrated at least short-term improvements in low-density lipoprotein cholesterol after SLCO1B1 testing among previously statin intolerant patients. Evidence from large implementation projects suggests that SLCO1B1 results may change prescribing patterns for some high-risk patients. No study has reported improvements in SAMSs or cardiovascular events or tracked the economic outcomes of SLCO1B1 testing. Ongoing studies should collect and report outcomes relevant to pharmacogenetics stakeholders.
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Affiliation(s)
- Jason L Vassy
- Veterans Affairs (VA) VA Boston Healthcare System, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA.,Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Sojeong Chun
- Veterans Affairs (VA) VA Boston Healthcare System, Boston, Massachusetts, USA.,Massachusetts College of Pharmacy and Health Sciences University, Boston, Massachusetts, USA
| | - Sanjay Advani
- Veterans Affairs (VA) VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Sophie A Ludin
- Veterans Affairs (VA) VA Boston Healthcare System, Boston, Massachusetts, USA.,Cornell University, Ithaca, New York, USA
| | - Jason G Smith
- Veterans Affairs (VA) VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Elaine C Alligood
- Veterans Affairs (VA) VA Boston Healthcare System, Boston, Massachusetts, USA
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Association between SLCO1B1 T521C polymorphism and risk of statin-induced myopathy: a meta-analysis. THE PHARMACOGENOMICS JOURNAL 2018; 18:721-729. [DOI: 10.1038/s41397-018-0054-0] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Revised: 07/20/2018] [Accepted: 08/10/2018] [Indexed: 12/22/2022]
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Peyser B, Perry EP, Singh K, Gill RD, Mehan MR, Haga SB, Musty MD, Milazzo NA, Savard D, Li YJ, Trujilio G, Voora D. Effects of Delivering
SLCO1B1
Pharmacogenetic Information in Randomized Trial and Observational Settings. CIRCULATION-GENOMIC AND PRECISION MEDICINE 2018; 11:e002228. [DOI: 10.1161/circgen.118.002228] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Bruce Peyser
- Department of Medicine (B.P., K.S., G.T., D.V.), Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC. United States (S.B.H., M.D.M., D.V.)
| | | | - Kavisha Singh
- Department of Medicine (B.P., K.S., G.T., D.V.), Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC. United States (S.B.H., M.D.M., D.V.)
| | | | | | - Susanne B. Haga
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC. United States (E.P.P., Y.-J.L.)
| | - Michael D. Musty
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC. United States (E.P.P., Y.-J.L.)
| | | | | | - Yi-Ju Li
- Air Force, Fairfield, CA (N.A.M., D.S.)
| | - Gloria Trujilio
- Department of Medicine (B.P., K.S., G.T., D.V.), Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC. United States (S.B.H., M.D.M., D.V.)
| | - Deepak Voora
- Department of Medicine (B.P., K.S., G.T., D.V.), Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC. United States (S.B.H., M.D.M., D.V.)
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC. United States (E.P.P., Y.-J.L.)
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Tuteja S, Rader DJ. SLCO1B1and Statin Therapy. CIRCULATION-GENOMIC AND PRECISION MEDICINE 2018; 11:e002320. [DOI: 10.1161/circgen.118.002320] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Sony Tuteja
- Division of Translational Medicine and Human Genetics, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia (S.T, D.J.R)
| | - Daniel J. Rader
- Division of Translational Medicine and Human Genetics, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia (S.T, D.J.R)
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia (D.J.R.)
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Zhong Z, Wu H, Li B, Li C, Liu Z, Yang M, Zhang Q, Zhong W, Zhao P. Analysis of SLCO1B1 and APOE genetic polymorphisms in a large ethnic Hakka population in southern China. J Clin Lab Anal 2018; 32:e22408. [PMID: 29424099 PMCID: PMC6817202 DOI: 10.1002/jcla.22408] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Accepted: 01/21/2018] [Indexed: 01/12/2023] Open
Abstract
OBJECTIVE Statins are the most widely used lipid-lowering drugs, which have a significant effect on the inhibition of cardiovascular disease. The efficacy and side effects of statins are associated with the polymorphisms of SLCO1B1 and APOE genes. The purpose of this study was to analyze the SLCO1B1 and APOE gene polymorphisms in the Hakka population of southern China. METHODS A total of 3249 subjects including 2019 males and 1230 females participated in this study. Polymerase chain reaction (PCR)-fluorescence probe technique for polymorphisms analysis and analyzed the genotypes frequencies of SLCO1B1 and APOE genes. RESULTS The frequencies of SLCO1B1 521T>C between men and women were statistically significant (SLCO1B1 521TT, χ2 = 8.431, P = .004; SLCO1B1 521TC, χ2 = 7.436, P = .007). The frequencies of haplotypes *1b/*1b (40.07%) and *1a/*1b (32.56%) of SLCO1B1 gene accounted for 72.63%, followed by *1b/*15(14.40%), *1a/*1a (5.82%), *1a/*15 (5.57%), *15/*15 (1.45%), and *1a/*5 (0.12%). The frequencies of haplotypes *1a/*15 and *1b/*1b of SLCO1B1 gene between men and women were statistically significant (*1a/*15, χ2 = 6.789, P = .009; *1b/*1b, χ2 = 3.998, P = .004). In this study, genotype ɛ3/ɛ3 accounted for 69.04%, followed by ɛ3/ɛ4 (16.19%), ɛ2/ɛ3 (11.60%), ɛ2/ɛ4 (1.35%), ɛ4/ɛ4 (1.08%), and ɛ2/ɛ2 (0.74%) in all subjects, in which ɛ3 had the greatest allele frequency (82.93%), followed by ɛ4 (9.85%) and ɛ2 (7.22%). We found that 47 subjects carrying the SLCO1B1 521 (CC) polymorphism who had not any myopathy caused by statins. CONCLUSIONS We analyzed the SLCO1B1 and APOE gene polymorphisms in the Hakka population of southern China. This study provides a reference for the individualized meditation for Hakka population in this area.
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Affiliation(s)
- Zhixiong Zhong
- Center for Cardiovascular DiseasesMeizhou People's Hospital (Huangtang Hospital)Meizhou Hospital Affiliated to Sun Yat‐sen UniversityMeizhouChina
- Clinical Core LaboratoryMeizhou People's Hospital (Huangtang Hospital)Meizhou Hospital Affiliated to Sun Yat‐sen UniversityMeizhouChina
| | - Heming Wu
- Clinical Core LaboratoryMeizhou People's Hospital (Huangtang Hospital)Meizhou Hospital Affiliated to Sun Yat‐sen UniversityMeizhouChina
- Center for Precision MedicineMeizhou People's Hospital (Huangtang Hospital)Meizhou Hospital Affiliated to Sun Yat‐sen UniversityMeizhouChina
| | - Bin Li
- Center for Cardiovascular DiseasesMeizhou People's Hospital (Huangtang Hospital)Meizhou Hospital Affiliated to Sun Yat‐sen UniversityMeizhouChina
- Clinical Core LaboratoryMeizhou People's Hospital (Huangtang Hospital)Meizhou Hospital Affiliated to Sun Yat‐sen UniversityMeizhouChina
| | - Cunren Li
- Center for Cardiovascular DiseasesMeizhou People's Hospital (Huangtang Hospital)Meizhou Hospital Affiliated to Sun Yat‐sen UniversityMeizhouChina
- Clinical Core LaboratoryMeizhou People's Hospital (Huangtang Hospital)Meizhou Hospital Affiliated to Sun Yat‐sen UniversityMeizhouChina
| | - Zhidong Liu
- Center for Cardiovascular DiseasesMeizhou People's Hospital (Huangtang Hospital)Meizhou Hospital Affiliated to Sun Yat‐sen UniversityMeizhouChina
- Clinical Core LaboratoryMeizhou People's Hospital (Huangtang Hospital)Meizhou Hospital Affiliated to Sun Yat‐sen UniversityMeizhouChina
| | - Min Yang
- Center for Cardiovascular DiseasesMeizhou People's Hospital (Huangtang Hospital)Meizhou Hospital Affiliated to Sun Yat‐sen UniversityMeizhouChina
- Clinical Core LaboratoryMeizhou People's Hospital (Huangtang Hospital)Meizhou Hospital Affiliated to Sun Yat‐sen UniversityMeizhouChina
| | - Qifeng Zhang
- Center for Cardiovascular DiseasesMeizhou People's Hospital (Huangtang Hospital)Meizhou Hospital Affiliated to Sun Yat‐sen UniversityMeizhouChina
- Clinical Core LaboratoryMeizhou People's Hospital (Huangtang Hospital)Meizhou Hospital Affiliated to Sun Yat‐sen UniversityMeizhouChina
| | - Wei Zhong
- Center for Cardiovascular DiseasesMeizhou People's Hospital (Huangtang Hospital)Meizhou Hospital Affiliated to Sun Yat‐sen UniversityMeizhouChina
- Clinical Core LaboratoryMeizhou People's Hospital (Huangtang Hospital)Meizhou Hospital Affiliated to Sun Yat‐sen UniversityMeizhouChina
| | - Pingsen Zhao
- Clinical Core LaboratoryMeizhou People's Hospital (Huangtang Hospital)Meizhou Hospital Affiliated to Sun Yat‐sen UniversityMeizhouChina
- Center for Precision MedicineMeizhou People's Hospital (Huangtang Hospital)Meizhou Hospital Affiliated to Sun Yat‐sen UniversityMeizhouChina
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Abstract
Considerable interindividual variability in response to cardiovascular pharmacotherapy exists with drug responses varying from being efficacious to inadequate to induce severe adverse events. Fueled by advancements and multidisciplinary collaboration across disciplines such as genetics, bioinformatics, and basic research, the vision of personalized medicine, rather than a one-size-fits-all approach, may be within reach. Pharmacogenetics offers the potential to optimize the benefit-risk profile of drugs by tailoring diagnostic and treatment strategies according to the individual patient. To date, a multitude of studies has tried to delineate the effects of gene-drug interactions for drugs commonly used to treat cardiovascular-related disease. The focus of this review is on how genetic variability may modify drug responsiveness and patient outcomes following therapy with commonly used cardiovascular drugs including clopidogrel, warfarin, statins, and β-blockers. Also included are examples of how genetic studies can be used to guide drug discovery and examples of how genetic information may be deployed in clinical decision making.
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Affiliation(s)
- Peter E Weeke
- Department of Cardiology, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Denmark.
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48
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Cano-Corres R, Candás-Estébanez B, Padró-Miquel A, Fanlo-Maresma M, Pintó X, Alía-Ramos P. Influence of 6 genetic variants on the efficacy of statins in patients with dyslipidemia. J Clin Lab Anal 2018; 32:e22566. [PMID: 29732606 DOI: 10.1002/jcla.22566] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Accepted: 04/12/2018] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Patients with dyslipidemia are often treated with statins to reduce lipids and hence cardiovascular risk, but treatment response is variable, partly due to genetic factors. METHODS We studied the influence of 6 gene variants (APOE c.526C > T (APOE2), APOE c.388T > C (APOE4), SLCO1B1 c.521T > C, CYP3A4 c.-392G > A, HMGCR c.1564-106A > G, and LPA c.3947 + 467T > C) on statin efficacy assessing 2 indicators: the percent reduction in total cholesterol (TC) and non-HDL cholesterol (non-HDL), as well as the achievement of therapeutic goals. The study was performed in a group of patients (n = 100) without previous pharmacological treatment. Multiple regression models were used to calculate the percentage of explanation in response variability added by every variant to a basal model constructed with significant nongenetic control variables. RESULTS The most influential variant was HMGCR c.1564-106A > G (rs3846662), and carriers showed a significantly lower reduction in TC and non-HDL. This variant is related to an alternative splicing involving exon 13, which is also regulated by lipid concentrations in patients without the variant. Concerning therapeutic goals, HMGCR c.1564-106A > G hindered the achievement of TC targets on patients. CONCLUSIONS The HMGCR c.1564-106A > G variant was associated with less statin efficacy to decrease cholesterol.
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Affiliation(s)
- Ruth Cano-Corres
- Clinical Laboratory, Biochemistry Department, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí I3PT, Universitat Autònoma de Barcelona, Sabadell, Spain
| | - Beatriz Candás-Estébanez
- Clinical Laboratory, Biochemistry and Molecular Genetics, Hospital Universitari de Bellvitge-IDIBELL, Barcelona, Spain
| | - Ariadna Padró-Miquel
- Clinical Laboratory, Biochemistry and Molecular Genetics, Hospital Universitari de Bellvitge-IDIBELL, Barcelona, Spain
| | - Marta Fanlo-Maresma
- Unidad de Lípidos y Riesgo Vascular, Servicio de Medicina Interna, Hospital Universitario de Bellvitge, CiberObn, Idibell, Barcelona, Spain
| | - Xavier Pintó
- Unidad de Lípidos y Riesgo Vascular, Servicio de Medicina Interna, Hospital Universitario de Bellvitge, CiberObn, Idibell, Barcelona, Spain
| | - Pedro Alía-Ramos
- Clinical Laboratory, Biochemistry and Molecular Genetics, Hospital Universitari de Bellvitge-IDIBELL, Barcelona, Spain
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Tornio A, Flynn R, Morant S, Velten E, Palmer CNA, MacDonald TM, Doney ASF. Investigating Real-World Clopidogrel Pharmacogenetics in Stroke Using a Bioresource Linked to Electronic Medical Records. Clin Pharmacol Ther 2018; 103:281-286. [PMID: 28653333 PMCID: PMC5813097 DOI: 10.1002/cpt.780] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2017] [Revised: 06/09/2017] [Accepted: 06/21/2017] [Indexed: 12/12/2022]
Abstract
Clopidogrel efficacy is influenced by genetic variation of cytochrome P450 (CYP)2C19, however, few studies have considered patients who have a stroke. We used electronic medical records (EMRs) linked to a bioresource to examine real-world implications of clopidogrel pharmacogenetics in stroke. Patients hospitalized for any arterial thrombo-occlusive (ATO) event who subsequently redeemed clopidogrel prescriptions in the community were entered into the study (n = 651). During 24-month follow-up, the primary endpoint of recurrent ATO or death occurred in 299 patients (46%). CYP2C19*2 loss-of-function allele carriers had an increased risk (hazard ratio (HR) = 1.29; 95% confidence interval (CI) = 1.04-1.59; P = 0.019). In the ischemic stroke subgroup (n = 94), the estimate of risk was greater (HR = 2.23; 95% CI = 1.17-4.24; P = 0.015), which was further supported by a meta-analysis of available studies. In conclusion, we have demonstrated the clinical impact of CYP2C19*2 on clopidogrel efficacy using a purely EMR approach. This suggests that the risk in the ischemic stroke population may be particularly high.
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Affiliation(s)
- Aleksi Tornio
- Division of Molecular & Clinical Medicine, School of MedicineUniversity of DundeeDundeeUK
| | - Rob Flynn
- Medicines Monitoring Unit, School of MedicineUniversity of DundeeDundeeUK
| | - Steve Morant
- Medicines Monitoring Unit, School of MedicineUniversity of DundeeDundeeUK
| | - Elena Velten
- Medicines Monitoring Unit, School of MedicineUniversity of DundeeDundeeUK
| | - Colin N. A. Palmer
- Division of Molecular & Clinical Medicine, School of MedicineUniversity of DundeeDundeeUK
| | | | - Alex S. F. Doney
- Medicines Monitoring Unit, School of MedicineUniversity of DundeeDundeeUK
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50
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K Siddiqui M, Maroteau C, Veluchamy A, Tornio A, Tavendale R, Carr F, Abelega NU, Carr D, Bloch K, Hallberg P, Yue QY, Pearson ER, Colhoun HM, Morris AD, Dow E, George J, Pirmohamed M, Ridker PM, Doney ASF, Alfirevic A, Wadelius M, Maitland-van der Zee AH, Chasman DI, Palmer CNA. A common missense variant of LILRB5 is associated with statin intolerance and myalgia. Eur Heart J 2017; 38:3569-3575. [PMID: 29020356 PMCID: PMC5837247 DOI: 10.1093/eurheartj/ehx467] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2017] [Revised: 05/26/2017] [Accepted: 07/24/2017] [Indexed: 12/11/2022] Open
Abstract
Aims A genetic variant in LILRB5 (leukocyte immunoglobulin-like receptor subfamily-B) (rs12975366: T > C: Asp247Gly) has been reported to be associated with lower creatine phosphokinase (CK) and lactate dehydrogenase (LDH) levels. Both biomarkers are released from injured muscle tissue, making this variant a potential candidate for susceptibility to muscle-related symptoms. We examined the association of this variant with statin intolerance ascertained from electronic medical records in the GoDARTS study. Methods and results In the GoDARTS cohort, the LILRB5 Asp247 variant was associated with statin intolerance (SI) phenotypes; one defined as having raised CK and being non-adherent to therapy [odds ratio (OR) 1.81; 95% confidence interval (CI): 1.34-2.45] and the other as being intolerant to the lowest approved dose of a statin before being switched to two or more other statins (OR 1.36; 95% CI: 1.07-1.73). Those homozygous for Asp247 had increased odds of developing both definitions of intolerance. Importantly the second definition did not rely on CK elevations. These results were replicated in adjudicated cases of statin-induced myopathy in the PREDICTION-ADR consortium (OR1.48; 95% CI: 1.05-2.10) and for the development of myalgia in the JUPITER randomized clinical trial of rosuvastatin (OR1.35, 95% CI: 1.10-1.68). A meta-analysis across the studies showed a consistent association between Asp247Gly and outcomes associated with SI (OR1.34; 95% CI: 1.16-1.54). Conclusion This study presents a novel immunogenetic factor associated with statin intolerance, an important risk factor for cardiovascular outcomes. The results suggest that true statin-induced myalgia and non-specific myalgia are distinct, with a potential role for the immune system in their development. We identify a genetic group that is more likely to be intolerant to their statins.
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Affiliation(s)
- Moneeza K Siddiqui
- Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, Division of Molecular & Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee DD19SY, UK
| | - Cyrielle Maroteau
- Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, Division of Molecular & Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee DD19SY, UK
| | - Abirami Veluchamy
- Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, Division of Molecular & Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee DD19SY, UK
| | - Aleksi Tornio
- Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, Division of Molecular & Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee DD19SY, UK
| | - Roger Tavendale
- Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, Division of Molecular & Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee DD19SY, UK
| | - Fiona Carr
- Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, Division of Molecular & Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee DD19SY, UK
| | - Ngu-Uma Abelega
- Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, Division of Molecular & Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee DD19SY, UK
| | - Dan Carr
- Institute of Translation Medicine, University of Liverpool, Liverpool L69 3BX, UK
| | - Katyrzyna Bloch
- Institute of Translation Medicine, University of Liverpool, Liverpool L69 3BX, UK
| | - Par Hallberg
- Department of Medical Sciences, Clinical Pharmacology and Science of Life Laboratory, Uppsala University, 751 85 Uppsala, Sweden
| | - Qun-Ying Yue
- Medical Products Agency, Dag Hammarskjölds väg 42, 75237 Uppsala, Sweden
| | - Ewan R Pearson
- Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, Division of Molecular & Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee DD19SY, UK
| | - Helen M Colhoun
- Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, Division of Molecular & Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee DD19SY, UK
- Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Andrew D Morris
- Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, Division of Molecular & Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee DD19SY, UK
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Eleanor Dow
- Ninewells Hospital and Medical School, Dundee DD19SY, UK
| | - Jacob George
- Ninewells Hospital and Medical School, Dundee DD19SY, UK
| | - Munir Pirmohamed
- Institute of Translation Medicine, University of Liverpool, Liverpool L69 3BX, UK
| | - Paul M Ridker
- Brigham and Women's Hospital, Department of Medicine, Preventive Medicine, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA
| | - Alex S F Doney
- Ninewells Hospital and Medical School, Dundee DD19SY, UK
| | - Ana Alfirevic
- Institute of Translation Medicine, University of Liverpool, Liverpool L69 3BX, UK
| | - Mia Wadelius
- Department of Medical Sciences, Clinical Pharmacology and Science of Life Laboratory, Uppsala University, 751 85 Uppsala, Sweden
| | - Anke-Hilse Maitland-van der Zee
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute of Pharmaceutical Sciences, Utrecht University, 3508 TB Utrecht, The Netherlands
- Department of Respiratory Medicine, Academic Medical Center, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Daniel I Chasman
- Brigham and Women's Hospital, Department of Medicine, Preventive Medicine, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA
| | - Colin N A Palmer
- Pat McPherson Centre for Pharmacogenetics & Pharmacogenomics, Division of Molecular & Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee DD19SY, UK
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