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| 2. |
- Karlsson Sundbaum, Johanna, et al.
(författare)
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Genome-wide association study of liver enzyme elevation in rheumatoid arthritis patients starting methotrexate
- 2021
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Ingår i: Pharmacogenomics (London). - : Future Medicine Ltd. - 1462-2416 .- 1744-8042. ; 22:15, s. 973-982
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Tidskriftsartikel (refereegranskat)abstract
- Aim: To identify novel genetic variants predisposing to elevation of Alanine aminotransferase (ALT) in rheumatoid arthritis (RA) patients after initiation of methotrexate (MTX) treatment. Patients & methods: We performed genome-wide association studies in 198 RA patients starting MTX. Outcomes were maximum level of ALT and ALT >1.5-times the upper level of normal within the first 6 months of treatment. Results: RAVER2 (rs72675408) was significantly associated with maximum level of ALT (p = 4.36 × 10-8). This variant is in linkage disequilibrium with rs72675451, which is associated with differential expression of JAK1 and RAVER2. Conclusion: We found an association between ALT elevation and genetic variants that may regulate the expression of JAK1 and RAVER2. JAK1 encodes a janus kinase involved in the pathogenesis of RA.
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| 3. |
- Caudle, Kelly E, et al.
(författare)
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Incorporation of Pharmacogenomics into Routine Clinical Practice : the Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline Development Process
- 2014
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Ingår i: Current drug metabolism. - : Bentham Science Publishers Ltd.. - 1389-2002 .- 1875-5453. ; 15:2, s. 209-217
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Tidskriftsartikel (refereegranskat)abstract
- The Clinical Pharmacogenetics Implementation Consortium (CPIC) publishes genotype-based drug guidelines to help clinicians understand how available genetic test results could be used to optimize drug therapy. CPIC has focused initially on well-known examples of pharmacogenomic associations that have been implemented in selected clinical settings, publishing nine to date. Each CPIC guideline adheres to a standardized format and includes a standard system for grading levels of evidence linking genotypes to phenotypes and assigning a level of strength to each prescribing recommendation. CPIC guidelines contain the necessary information to help clinicians translate patient-specific diplotypes for each gene into clinical phenotypes or drug dosing groups. This paper reviews the development process of the CPIC guidelines and compares this process to the Institute of Medicine's Standards for Developing Trustworthy Clinical Practice Guidelines.
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| 4. |
- Dias, M M, et al.
(författare)
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The effect of the UGT1A1*28 allele on survival after irinotecan-based chemotherapy : a collaborative meta-analysis
- 2014
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Ingår i: The Pharmacogenomics Journal. - : Springer Science and Business Media LLC. - 1470-269X .- 1473-1150. ; 14:5, s. 424-431
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Tidskriftsartikel (refereegranskat)abstract
- To date, studies of irinotecan pharmacogenetics have mostly focused on the effect of the UGT1A1*28 allele on irinotecan-related toxicity. However, the clinical utility of routine UGT1A1*28 genotyping to pre-emptively adjust irinotecan dosage is dependent upon whether UGT1A1*28 also affects patient survival following irinotecan therapy. Previous observational studies evaluating the influence of UGT1A1*28 on survival have shown contradictory results. A systematic review and meta-analysis of both published and unpublished data were performed to summarize the available evidence of the relationship between the UGT1A1*28 allele and patient survival related to irinotecan therapy. Overall and progression-free survival meta-analysis data were available for 1524 patients and 1494 patients, respectively. The difference in the survival between patients of different UGT1A1*28 genotypes (homozygous, heterozygous or wild-type) who had received irinotecan was not found to be statistically significant. There was also no evidence of irinotecan dose, regimen or line of therapy having an impact on this association.
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| 5. |
- Eliasson, Erik, et al.
(författare)
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Farmakogenomik – individuell anpassning av läkemedel och dos : [Pharmacogenomics - a cornerstone of Precision Medicine. Genomic Medicine Sweden analyses genotypes associated with serious drug toxicity or therapeutic failure]
- 2021
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Ingår i: Läkartidningen. - : Läkartidningen Förlag AB. - 0023-7205 .- 1652-7518. ; 118
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Forskningsöversikt (refereegranskat)abstract
- Serious adverse drug reactions, drug intolerance, and lack of effect are major problems in healthcare. Pharmacogenomics is the part of precision medicine that aims to develop predictive risk markers in this respect and establish such testing in clinical practice. The nation-wide project Genomic Medicine Sweden (GMS) is undertaking large-scale sequencing to predict risk of drug toxicity and lack of efficacy in malignant diseases. The aim is to facilitate an improved, individualized treatment with increased patient safety. In addition to accurate genotyping, other technical or infrastructure-related aspects need to be considered for a successful implementation in healthcare, for example electronic accessibility and visibility of pharmacogenomic data of long-standing relevance for an individual's ongoing and future drug treatment.
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| 6. |
- Garwicz, Daniel, et al.
(författare)
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Farmakogenetisk analys kan avslöja risk för statinbiverkningar : [Pharmacogenetic analysis can predict adverse effects of statins]
- 2013
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Ingår i: Läkartidningen. - 0023-7205 .- 1652-7518. ; 110:19-20, s. 951-952
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Tidskriftsartikel (refereegranskat)abstract
- Mer än var tionde vuxen i Sverige behandlas med statiner. Muskelsvaghet, -trötthet och -värk är kända biverkningar. I sällsynta fall ses rabdomyolys, som kan leda till akut njursvikt och någon gång dödsfall. Statiners kemiska egenskaper och serumkoncentration påverkar risken för allvarliga biverkningar. Serumkoncentrationen beror på dos och på patientens förmåga att omsätta läkemedlet.Akademiska sjukhuset har som första svenska sjukhus infört analys av en genetisk variant (SLCO1B1*5) som kan förutsäga ökad risk för sällsynta, allvarliga muskelbiverkningar vid statinbehandling.
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| 7. |
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| 8. |
- Hamberg, Anna-Karin, et al.
(författare)
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Characterising variability in warfarin dose requirements in children using modelling and simulation
- 2013
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Ingår i: British Journal of Clinical Pharmacology. - : Wiley. - 0306-5251 .- 1365-2125. ; 78:1, s. 158-169
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Tidskriftsartikel (refereegranskat)abstract
- AIMS: Although genetic, clinical and demographic factors have been shown to explain approximately half of the inter-individual variability in warfarin dose requirement in adults, less is known about causes of dose variability in children. This study aimed to identify and quantify major genetic, clinical and demographic sources of warfarin dose variability in children using modelling and simulation.METHODS: Clinical, demographic and genetic data from 163 children with a median age of 6.3 years (range 0.06-18.9 years), covering over 183 years of warfarin therapy and 6445 INR observations were used to update and optimise a published adult pharmacometric warfarin model for use in children.RESULTS: Genotype effects in children were found to be comparable to what has been reported for adults, with CYP2C9 explaining up to a 4-fold difference in dose (CYP2C9 *1/*1 vs. *3/*3) and VKORC1 explaining up to a 2-fold difference in dose (VKORC1 G/G vs. A/A), respectively. The relationship between bodyweight and warfarin dose was non-linear, with a 3-fold difference in dose for a 4-fold difference in bodyweight. In addition, age, baseline and target INR, and time since initiation of therapy, but not CYP4F2 genotype, had a significant impact on typical warfarin dose requirements in children.CONCLUSIONS: The updated model provides quantitative estimates of major clinical, demographic and genetic factors impacting warfarin dose variability in children. With this new knowledge more individualised dosing regimens can be developed and prospectively evaluated in the pursuit of improving both efficacy and safety of warfarin therapy in children.
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| 9. |
- Hamberg, Anna-Karin, et al.
(författare)
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Pharmacogenetics-based warfarin dosing in children
- 2014
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Ingår i: Pharmacogenomics (London). - : Future Medicine Ltd. - 1462-2416 .- 1744-8042. ; 15:3, s. 361-374
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Forskningsöversikt (refereegranskat)abstract
- Clinical factors, demographic variables and variations in two genes, CYP2C9 and VKORC1, have been shown to contribute to the variability in warfarin dose requirements among adult patients. Less is known about their relative importance for dose variability in children. A few small studies have been reported, but the results have been conflicting, especially regarding the impact of genotypes. In this article, we critically review published pharmacogenetic-based prediction models for warfarin dosing in children, and present results from a head-to-head comparison of predictive performance in a distinct cohort of warfarin-treated children. Finally we discuss what properties a prediction model should have, and what knowledge gaps need to be filled, to improve warfarin therapy in children of all ages.
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| 10. |
- Horne, B D, et al.
(författare)
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Pharmacogenetic warfarin dose refinements remain significantly influenced by genetic factors after one week of therapy
- 2012
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Ingår i: Thrombosis and Haemostasis. - 0340-6245 .- 2567-689X. ; 107:2, s. 232-240
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Tidskriftsartikel (refereegranskat)abstract
- By guiding initial warfarin dose, pharmacogenetic (PGx) algorithms may improve the safety of warfarin initiation. However, once international normalised ratio (INR) response is known, the contribution of PGx to dose refinements is uncertain. This study sought to develop and validate clinical and PGx dosing algorithms for warfarin dose refinement on days 6-11 after therapy initiation. An international sample of 2,022 patients at 13 medical centres on three continents provided clinical, INR, and genetic data at treatment days 6-11 to predict therapeutic warfarin dose. Independent derivation and retrospective validation samples were composed by randomly dividing the population (80%/20%). Prior warfarin doses were weighted by their expected effect on S-warfarin concentrations using an exponential-decay pharmacokinetic model. The INR divided by that "effective" dose constituted a treatment response index . Treatment response index, age, amiodarone, body surface area, warfarin indication, and target INR were associated with dose in the derivation sample. A clinical algorithm based on these factors was remarkably accurate: in the retrospective validation cohort its R2 was 61.2% and median absolute error (MAE) was 5.0 mg/week. Accuracy and safety was confirmed in a prospective cohort (N=43). CYP2C9 variants and VKORC1-1639 G→A were significant dose predictors in both the derivation and validation samples. In the retrospective validation cohort, the PGx algorithm had: R2= 69.1% (p<0.05 vs. clinical algorithm), MAE= 4.7 mg/week. In conclusion, a pharmacogenetic warfarin dose-refinement algorithm based on clinical, INR, and genetic factors can explain at least 69.1% of therapeutic warfarin dose variability after about one week of therapy.
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