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- INABA, T, et al.
(författare)
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Pharmacogenetics in clinical pharmacology and toxicology
- 1995
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Ingår i: Canadian journal of physiology and pharmacology. - : Canadian Science Publishing. - 0008-4212 .- 1205-7541. ; 73:3, s. 331-338
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Tidskriftsartikel (refereegranskat)abstract
- An international symposium entitled Pharmacogenetics in clinical pharmacology and toxicology: a tribute to Werner Kalow was held in Toronto, Ontario, July 20, 1994. This subject was particularly important to discuss in the presence of Werner Kalow, 77 years young, who is considered as one of the grandfathers of this unique combination of medical research fields. It has become increasingly appreciated that dozens of human drug metabolism polymorphisms exist. The interindividual variabilities in drug metabolism discussed at this symposium do not represent small differences such as 50% or 3-fold but, rather, represent 10- to greater than 1000-fold differences. When attributed to a single gene, dramatic differences can be seen among family members, just as blue and brown eyes can occur in siblings. These differences can result in acute drug toxicity. In addition, there are chronic effects: over one's lifetime, striking differences in the metabolism of drugs, occupationally hazardous chemicals, and other environmental pollutants can lead to interindividual differences in the buildup of DNA damage (e.g., mutations, chromosomal breaks, rearrangements) leading to toxicity and tumor initiation, as well as leading to a buildup in nongenotoxic signals (signal transduction pathways without DNA damage) important for toxicity, tumor promotion, and tumor progression. The human UDP glucuronosyltransferase (UGT superfamily is known to comprise more than 10 genes in humans, and probably in other mammalian species. Breakthroughs in UGT gene mutations responsible for the Crigler-Najjar syndrome and Gilbert's disease have recently been reported. The human cytochrome P450 termed CYP3A4 is a major P450 enzyme in the liver and gastrointestinal tract, and the full impact of the CYP3A4 polymorphism has yet to be fully appreciated. CYP3A4 metabolism of cyclosporin A, commonly prescribed to organ transplant recipients, the induction of CYP3A4 by rifampicin, and inhibition of CYP3A4 metabolism by erythromycin or ketoconazole are now quite well understood. The field of ethnopharmacology, or pharmacoanthropology, has recently emerged, pioneered at least in part by Kalow. Differences in debrisoquine–sparteine metabolism, S-mephenytoin hydroxylation, diazepam clearance, and omeprazole clearance in various Caucasian and Oriental subpopulations in a number of countries have been extensively reported. After a number of inconclusive studies, it has now been shown unequivocally that the human S-mephenytoin 4′-hydroxylase polymorphism represents at least two distinct mutations (one involving a splice site) in the CYP2C19 gene. Finally, the implications and clinical significance of a number of human polymorphisms (CYP2D6, CYP2C19, N-acetylation (NAT2), S-methylation by thiopurine methyltransferase (TPMT), and ester hydrolysis by plasma cholinesterase) were carefully reviewed at this symposium.Key words: pharmacology, toxicology, drug metabolism, pharmacogenetic polymorphism.
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- Romagnoni, A, et al.
(författare)
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Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
- 2019
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 10351-
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Tidskriftsartikel (refereegranskat)abstract
- Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers.
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- Young, WJ, et al.
(författare)
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Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease
- 2023
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 14:1, s. 1411-
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Tidskriftsartikel (refereegranskat)abstract
- The 3-dimensional spatial and 2-dimensional frontal QRS-T angles are measures derived from the vectorcardiogram. They are independent risk predictors for arrhythmia, but the underlying biology is unknown. Using multi-ancestry genome-wide association studies we identify 61 (58 previously unreported) loci for the spatial QRS-T angle (N = 118,780) and 11 for the frontal QRS-T angle (N = 159,715). Seven out of the 61 spatial QRS-T angle loci have not been reported for other electrocardiographic measures. Enrichments are observed in pathways related to cardiac and vascular development, muscle contraction, and hypertrophy. Pairwise genome-wide association studies with classical ECG traits identify shared genetic influences with PR interval and QRS duration. Phenome-wide scanning indicate associations with atrial fibrillation, atrioventricular block and arterial embolism and genetically determined QRS-T angle measures are associated with fascicular and bundle branch block (and also atrioventricular block for the frontal QRS-T angle). We identify potential biology involved in the QRS-T angle and their genetic relationships with cardiovascular traits and diseases, may inform future research and risk prediction.
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