| 1. |
- Voight, Benjamin F, et al.
(författare)
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Plasma HDL cholesterol and risk of myocardial infarction : a mendelian randomisation study
- 2012
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Ingår i: The Lancet. - 0140-6736 .- 1474-547X. ; 380:9841, s. 572-580
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: High plasma HDL cholesterol is associated with reduced risk of myocardial infarction, but whether this association is causal is unclear. Exploiting the fact that genotypes are randomly assigned at meiosis, are independent of non-genetic confounding, and are unmodified by disease processes, mendelian randomisation can be used to test the hypothesis that the association of a plasma biomarker with disease is causal.METHODS: We performed two mendelian randomisation analyses. First, we used as an instrument a single nucleotide polymorphism (SNP) in the endothelial lipase gene (LIPG Asn396Ser) and tested this SNP in 20 studies (20,913 myocardial infarction cases, 95,407 controls). Second, we used as an instrument a genetic score consisting of 14 common SNPs that exclusively associate with HDL cholesterol and tested this score in up to 12,482 cases of myocardial infarction and 41,331 controls. As a positive control, we also tested a genetic score of 13 common SNPs exclusively associated with LDL cholesterol.FINDINGS: Carriers of the LIPG 396Ser allele (2·6% frequency) had higher HDL cholesterol (0·14 mmol/L higher, p=8×10(-13)) but similar levels of other lipid and non-lipid risk factors for myocardial infarction compared with non-carriers. This difference in HDL cholesterol is expected to decrease risk of myocardial infarction by 13% (odds ratio [OR] 0·87, 95% CI 0·84-0·91). However, we noted that the 396Ser allele was not associated with risk of myocardial infarction (OR 0·99, 95% CI 0·88-1·11, p=0·85). From observational epidemiology, an increase of 1 SD in HDL cholesterol was associated with reduced risk of myocardial infarction (OR 0·62, 95% CI 0·58-0·66). However, a 1 SD increase in HDL cholesterol due to genetic score was not associated with risk of myocardial infarction (OR 0·93, 95% CI 0·68-1·26, p=0·63). For LDL cholesterol, the estimate from observational epidemiology (a 1 SD increase in LDL cholesterol associated with OR 1·54, 95% CI 1·45-1·63) was concordant with that from genetic score (OR 2·13, 95% CI 1·69-2·69, p=2×10(-10)).INTERPRETATION: Some genetic mechanisms that raise plasma HDL cholesterol do not seem to lower risk of myocardial infarction. These data challenge the concept that raising of plasma HDL cholesterol will uniformly translate into reductions in risk of myocardial infarction.
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| 2. |
- Swen, JesseJ, et al.
(författare)
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A 12-gene pharmacogenetic panel to prevent adverse drug reactions : an open-label, multicentre, controlled, cluster-randomised crossover implementation study
- 2023
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Ingår i: The Lancet. - : Elsevier. - 0140-6736 .- 1474-547X. ; 401:10374, s. 347-356
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Tidskriftsartikel (refereegranskat)abstract
- Background: The benefit of pharmacogenetic testing before starting drug therapy has been well documented for several single gene-drug combinations. However, the clinical utility of a pre-emptive genotyping strategy using a pharmacogenetic panel has not been rigorously assessed.Methods: We conducted an open-label, multicentre, controlled, cluster-randomised, crossover implementation study of a 12-gene pharmacogenetic panel in 18 hospitals, nine community health centres, and 28 community pharmacies in seven European countries (Austria, Greece, Italy, the Netherlands, Slovenia, Spain, and the UK). Patients aged 18 years or older receiving a first prescription for a drug clinically recommended in the guidelines of the Dutch Pharmacogenetics Working Group (ie, the index drug) as part of routine care were eligible for inclusion. Exclusion criteria included previous genetic testing for a gene relevant to the index drug, a planned duration of treatment of less than 7 consecutive days, and severe renal or liver insufficiency. All patients gave written informed consent before taking part in the study. Participants were genotyped for 50 germline variants in 12 genes, and those with an actionable variant (ie, a drug-gene interaction test result for which the Dutch Pharmacogenetics Working Group [DPWG] recommended a change to standard-of-care drug treatment) were treated according to DPWG recommendations. Patients in the control group received standard treatment. To prepare clinicians for pre-emptive pharmacogenetic testing, local teams were educated during a site-initiation visit and online educational material was made available. The primary outcome was the occurrence of clinically relevant adverse drug reactions within the 12-week follow-up period. Analyses were irrespective of patient adherence to the DPWG guidelines. The primary analysis was done using a gatekeeping analysis, in which outcomes in people with an actionable drug-gene interaction in the study group versus the control group were compared, and only if the difference was statistically significant was an analysis done that included all of the patients in the study. Outcomes were compared between the study and control groups, both for patients with an actionable drug-gene interaction test result (ie, a result for which the DPWG recommended a change to standard-of-care drug treatment) and for all patients who received at least one dose of index drug. The safety analysis included all participants who received at least one dose of a study drug. This study is registered with ClinicalTrials.gov, NCT03093818 and is closed to new participants.Findings: Between March 7, 2017, and June 30, 2020, 41 696 patients were assessed for eligibility and 6944 (51.4 % female, 48.6% male; 97.7% self-reported European, Mediterranean, or Middle Eastern ethnicity) were enrolled and assigned to receive genotype-guided drug treatment (n=3342) or standard care (n=3602). 99 patients (52 [1.6%] of the study group and 47 [1.3%] of the control group) withdrew consent after group assignment. 652 participants (367 [11.0%] in the study group and 285 [7.9%] in the control group) were lost to follow-up. In patients with an actionable test result for the index drug (n=1558), a clinically relevant adverse drug reaction occurred in 152 (21 center dot 0%) of 725 patients in the study group and 231 (27.7%) of 833 patients in the control group (odds ratio [OR] 0 center dot 70 [95% CI 0 center dot 54-0 center dot 91]; p=0.0075), whereas for all patients, the incidence was 628 (21.5%) of 2923 patients in the study group and 934 (28. 6%) of 3270 patients in the control group (OR 0.70 [95% CI 0.61-0.79]; p <0.0001).Interpretation: Genotype-guided treatment using a 12-gene pharmacogenetic panel significantly reduced the incidence of clinically relevant adverse drug reactions and was feasible across diverse European health-care system organisations and settings. Large-scale implementation could help to make drug therapy increasingly safe.
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| 3. |
- van der Wouden, Cathelijne H., et al.
(författare)
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Generating evidence for precision medicine : considerations made by the Ubiquitous Pharmacogenomics Consortium when designing and operationalizing the PREPARE study
- 2020
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Ingår i: Pharmacogenetics & Genomics. - 1744-6872 .- 1744-6880. ; 30:6, s. 131-144
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Tidskriftsartikel (refereegranskat)abstract
- Objectives Pharmacogenetic panel-based testing represents a new model for precision medicine. A sufficiently powered prospective study assessing the (cost-)effectiveness of a panel-based pharmacogenomics approach to guide pharmacotherapy is lacking. Therefore, the Ubiquitous Pharmacogenomics Consortium initiated the PREemptive Pharmacogenomic testing for prevention of Adverse drug Reactions (PREPARE) study. Here, we provide an overview of considerations made to mitigate multiple methodological challenges that emerged during the design.Methods An evaluation of considerations made when designing the PREPARE study across six domains: study aims and design, primary endpoint definition and collection of adverse drug events, inclusion and exclusion criteria, target population, pharmacogenomics intervention strategy, and statistical analyses.Results Challenges and respective solutions included: (1) defining and operationalizing a composite primary endpoint enabling measurement of the anticipated effect, by including only severe, causal, and drug genotype-associated adverse drug reactions; (2) avoiding overrepresentation of frequently prescribed drugs within the patient sample while maintaining external validity, by capping drugs of enrolment; (3) designing the pharmacogenomics intervention strategy to be applicable across ethnicities and healthcare settings; and (4) designing a statistical analysis plan to avoid dilution of effect by initially excluding patients without a gene–drug interaction in a gatekeeping analysis.Conclusion Our design considerations will enable quantification of the collective clinical utility of a panel of pharmacogenomics-markers within one trial as a proof-of-concept for pharmacogenomics-guided pharmacotherapy across multiple actionable gene–drug interactions. These considerations may prove useful to other investigators aiming to generate evidence for precision medicine.
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