Combinatorial Pharmacogenetics

Combinatorial pharmacogenetics seeks to characterize genetic variations that affect reactions to potentially toxic agents within the complex metabolic networks of the human body. Polymorphic drug-metabolizing enzymes are likely to represent some of the most common inheritable risk factors associated with common 'disease' phenotypes, such as adverse drug reactions. The relatively high concordance between polymorphisms in drug-metabolizing enzymes and clinical phenotypes indicates that research into this class of polymorphisms could benefit patients in the near future. Characterization of other genes affecting drug disposition (absorption, distribution, metabolism and elimination) will further enhance this process. As with most questions concerning biological systems, the complexity arises out of the combinatorial magnitude of all the possible interactions and pathways. The high-dimensionality of the resulting analysis problem will often overwhelm traditional analysis methods. Novel analysis techniques, such as multifactor dimensionality reduction, offer viable options for evaluating such data.

[1]  A pharmacogenetic analysis of the effects of tetrahydrocannabinol (delta 9THC) on brain gamma glutamyl transpeptidase. , 1985, Neurobehavioral toxicology and teratology.

[2]  D. Mccormick Sequence the Human Genome , 1986, Bio/Technology.

[3]  David W. Hosmer,et al.  Applied Logistic Regression , 1991 .

[4]  J. Concato,et al.  The Risk of Determining Risk with Multivariable Models , 1993, Annals of Internal Medicine.

[5]  S. Wrighton,et al.  Isolation and characterization of human liver cytochrome P450 2C19: correlation between 2C19 and S-mephenytoin 4'-hydroxylation. , 1993, Archives of biochemistry and biophysics.

[6]  G R Wilkinson,et al.  The major genetic defect responsible for the polymorphism of S-mephenytoin metabolism in humans. , 1994, The Journal of biological chemistry.

[7]  G R Wilkinson,et al.  Identification of a new genetic defect responsible for the polymorphism of (S)-mephenytoin metabolism in Japanese. , 1994, Molecular pharmacology.

[8]  P. Good,et al.  Permutation Tests: A Practical Guide to Resampling Methods for Testing Hypotheses , 1995 .

[9]  J. Concato,et al.  A simulation study of the number of events per variable in logistic regression analysis. , 1996, Journal of clinical epidemiology.

[10]  L. Pennypacker,et al.  Phenytoin Toxicity in an Older Patient with Slow Metabolism and Atypical Presentation , 1998, Pharmacotherapy.

[11]  M. Ratain,et al.  Genetic predisposition to the metabolism of irinotecan (CPT-11). Role of uridine diphosphate glucuronosyltransferase isoform 1A1 in the glucuronidation of its active metabolite (SN-38) in human liver microsomes. , 1998, The Journal of clinical investigation.

[12]  W. W. Bullen,et al.  Development and validation of a high-performance liquid chromatography tandem mass spectrometry assay for atorvastatin, ortho-hydroxy atorvastatin, and para-hydroxy atorvastatin in human, dog, and rat plasma , 1999, Journal of the American Society for Mass Spectrometry.

[13]  Z. Ouyang,et al.  Quantitation of the acid and lactone forms of atorvastatin and its biotransformation products in human serum by high-performance liquid chromatography with electrospray tandem mass spectrometry. , 1999, Rapid communications in mass spectrometry : RCM.

[14]  M. Wade,et al.  Epistasis and the Evolutionary Process , 2000 .

[15]  N. Venketasubramanian,et al.  Elimination of phenytoin in toxic overdose , 2000, Clinical Neurology and Neurosurgery.

[16]  H. Saka,et al.  Polymorphisms of UDP-glucuronosyltransferase gene and irinotecan toxicity: a pharmacogenetic analysis. , 2000, Cancer research.

[17]  H. Yamazaki,et al.  Formation of a dihydroxy metabolite of phenytoin in human liver microsomes/cytosol: roles of cytochromes P450 2C9, 2C19, and 3A4. , 2000, Drug metabolism and disposition: the biological fate of chemicals.

[18]  O. Pelkonen,et al.  Interindividual variability in human drug metabolism , 2001 .

[19]  W. Weber,et al.  The legacy of pharmacogenetics and potential applications. , 2001, Mutation research.

[20]  U. Brinkmann,et al.  The predictive value of MDR1, CYP2C9, and CYP2C19 polymorphisms for phenytoin plasma levels , 2001, The Pharmacogenomics Journal.

[21]  M. I. Ngelman-Sundber Pharmacogenetics: an opportunity for a safer and more efficient pharmacotherapy , 2001 .

[22]  C. Ioannides Enzyme Systems that Metabolise Drugs and Other Xenobiotics , 2001 .

[23]  J. H. Moore,et al.  Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer. , 2001, American journal of human genetics.

[24]  J. Ott,et al.  Trimming, weighting, and grouping SNPs in human case-control association studies. , 2001, Genome research.

[25]  J. V. Moran,et al.  Initial sequencing and analysis of the human genome. , 2001, Nature.

[26]  David L Veenstra,et al.  Association between CYP2C9 genetic variants and anticoagulation-related outcomes during warfarin therapy. , 2002, JAMA.

[27]  J. L. Le Gall,et al.  HFE based re-evaluation of heterozygous hemochromatosis. , 2002, American journal of medical genetics.

[28]  R. Subramanian,et al.  Effects of fibrates on metabolism of statins in human hepatocytes. , 2002, Drug metabolism and disposition: the biological fate of chemicals.

[29]  B. Aizenstein,et al.  Characterization of cytochrome P450 2D6 alleles using the Invader system. , 2002, BioTechniques.

[30]  R. Schilsky,et al.  UGT1A1*28 polymorphism as a determinant of irinotecan disposition and toxicity , 2002, The Pharmacogenomics Journal.

[31]  B. Ma,et al.  Mechanistic studies on metabolic interactions between gemfibrozil and statins. , 2002, The Journal of pharmacology and experimental therapeutics.

[32]  E. Spina,et al.  Influence of CYP2C9 and CYP2C19 genetic polymorphisms on warfarin maintenance dose and metabolic clearance , 2002, Clinical pharmacology and therapeutics.

[33]  M. Davidson Controversy surrounding the safety of cerivastatin , 2002, Expert opinion on drug safety.

[34]  Scott M. Williams,et al.  New strategies for identifying gene-gene interactions in hypertension , 2002, Annals of medicine.

[35]  Jason H. Moore,et al.  An application of conditional logistic regression and multifactor dimensionality reduction for detecting gene-gene Interactions on risk of myocardial infarction: The importance of model validation , 2004, BMC Bioinformatics.

[36]  Ivan Bratko,et al.  Attribute Interactions in Medical Data Analysis , 2003, AIME.

[37]  Jason H. Moore,et al.  Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions , 2003, Bioinform..

[38]  Jason H. Moore,et al.  Power of multifactor dimensionality reduction for detecting gene‐gene interactions in the presence of genotyping error, missing data, phenocopy, and genetic heterogeneity , 2003, Genetic epidemiology.

[39]  Jason H. Moore,et al.  The Ubiquitous Nature of Epistasis in Determining Susceptibility to Common Human Diseases , 2003, Human Heredity.

[40]  Ivan Bratko,et al.  Quantifying and Visualizing Attribute Interactions: An Approach Based on Entropy , 2003 .

[41]  Yuichi Sugiyama,et al.  Polymorphisms of OATP‐C (SLC21A6) and OAT3 (SLC22A8) genes: Consequences for pravastatin pharmacokinetics , 2003, Clinical pharmacology and therapeutics.

[42]  J Licinio,et al.  Pharmacogenetics of antidepressants and antipsychotics: the contribution of allelic variations to the phenotype of drug response , 2004, Molecular Psychiatry.

[43]  A. Khvorova,et al.  Identification of the gene for vitamin K epoxide reductase , 2004, Nature.

[44]  Ai-Young Lee,et al.  Genetic polymorphism of cytochrome P450 2C9 in diphenylhydantoin-induced cutaneous adverse drug reactions , 2004, European Journal of Clinical Pharmacology.

[45]  Steffen Bauer,et al.  Evidence for Inverse Effects of OATP‐C (SLC21A6) *5 and *1b Haplotypes on Pravastatin Kinetics , 2004, Clinical pharmacology and therapeutics.

[46]  Howard L McLeod,et al.  Use of pharmacogenetics and clinical factors to predict the maintenance dose of warfarin , 2003, Thrombosis and Haemostasis.

[47]  Jason H. Moore,et al.  Ideal discrimination of discrete clinical endpoints using multilocus genotypes , 2004, Silico Biol..

[48]  Andreas Fregin,et al.  Mutations in VKORC1 cause warfarin resistance and multiple coagulation factor deficiency type 2 , 2004, Nature.

[49]  M. Caldwell,et al.  Relative impact of covariates in prescribing warfarin according to CYP2C9 genotype. , 2004, Pharmacogenetics.

[50]  Paul D. Martin,et al.  The effect of gemfibrozil on the pharmacokinetics of rosuvastatin , 2004, Clinical pharmacology and therapeutics.

[51]  D. Ruppert The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2004 .

[52]  Chih-Chuan Chen,et al.  Dosage Recommendation of Phenytoin for Patients with Epilepsy with Different CYP2C9/CYP2C19 Polymorphisms , 2004, Therapeutic drug monitoring.

[53]  I. Ieiri,et al.  Association of pharmacokinetic (CYP2C9) and pharmacodynamic (factors II, VII, IX, and X; proteins S and C; and gamma-glutamyl carboxylase) gene variants with warfarin sensitivity. , 2003, Blood.

[54]  Y. Sugiyama,et al.  Gemfibrozil and Its Glucuronide Inhibit the Organic Anion Transporting Polypeptide 2 (OATP2/OATP1B1:SLC21A6)-Mediated Hepatic Uptake and CYP2C8-Mediated Metabolism of Cerivastatin: Analysis of the Mechanism of the Clinically Relevant Drug-Drug Interaction between Cerivastatin and Gemfibrozil , 2004, Journal of Pharmacology and Experimental Therapeutics.

[55]  G. Anderson Pharmacogenetics and enzyme induction/inhibition properties of antiepileptic drugs , 2004, Neurology.

[56]  Jonathan L Haines,et al.  Genetics, statistics and human disease: analytical retooling for complexity. , 2004, Trends in genetics : TIG.

[57]  Jason H Moore,et al.  Computational analysis of gene-gene interactions using multifactor dimensionality reduction , 2004, Expert review of molecular diagnostics.

[58]  Marylyn D Ritchie,et al.  Renin-Angiotensin System Gene Polymorphisms and Atrial Fibrillation , 2004, Circulation.

[59]  Ian H. Witten,et al.  Data mining in bioinformatics using Weka , 2004, Bioinform..

[60]  Jason H. Moore,et al.  STUDENTJAMA. The challenges of whole-genome approaches to common diseases. , 2004, JAMA.

[61]  P. Lord,et al.  Genomics and Drug Toxicity , 2004, Science.

[62]  O. Wallerman,et al.  Warfarin sensitivity related to CYP2C9, CYP3A5, ABCB1 (MDR1) and other factors , 2004, The Pharmacogenomics Journal.

[63]  William Shannon,et al.  Detecting epistatic interactions contributing to quantitative traits , 2004, Genetic epidemiology.

[64]  Harlan M Krumholz,et al.  Reporting of model validation procedures in human studies of genetic interactions. , 2004, Nutrition.

[65]  Marylyn D. Ritchie,et al.  Multilocus Analysis of Hypertension: A Hierarchical Approach , 2004, Human Heredity.

[66]  Serge Batalov,et al.  Susceptibility and modifier genes in Portuguese transthyretin V30M amyloid polyneuropathy: complexity in a single-gene disease. , 2005, Human molecular genetics.

[67]  Russell A Wilke,et al.  Relative impact of CYP3A genotype and concomitant medication on the severity of atorvastatin-induced muscle damage , 2005, Pharmacogenetics and genomics.

[68]  Jason H. Moore,et al.  A global view of epistasis , 2005, Nature Genetics.

[69]  Marylyn D Ritchie,et al.  Pacific Symposium on Biocomputing--computational approaches for pharmacogenomics. , 2005, Pharmacogenomics.

[70]  M. Reilly,et al.  MDR and PRP: A Comparison of Methods for High-Order Genotype-Phenotype Associations , 2005, Human Heredity.

[71]  Lin He,et al.  An association study of the N-methyl-D-aspartate receptor NR1 subunit gene (GRIN1) and NR2B subunit gene (GRIN2B) in schizophrenia with universal DNA microarray , 2005, European Journal of Human Genetics.

[72]  Scott M. Williams,et al.  Traversing the conceptual divide between biological and statistical epistasis: systems biology and a more modern synthesis. , 2005, BioEssays : news and reviews in molecular, cellular and developmental biology.

[73]  R. Wilke,et al.  Cytochrome P450 gene-based drug prescribing and factors impacting translation into routine clinical practice. , 2005, Personalized medicine.

[74]  Todd Holden,et al.  A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility. , 2006, Journal of theoretical biology.