Potential genetic causes of heterogeneity of treatment effects.
Nongenetic biologic and lifestyle-related factors, including age, sex, hepatic/renal function, diet/exercise practices, illness severity, smoking, and alcohol consumption habits can account for the heterogeneity of treatment effects (HTE). However, even when these factors are taken into account, considerable variation remains unexplained and could potentially be attributable to genetic differences between patients. Drug response may be dictated by variation in genes involved in both pharmacokinetic (PK) (absorption, distribution, metabolism, excretion [ADME]) and pharmacodynamic (PD) (receptors, ion channels, enzymes, immune system) pathways. Functional variants of the ADME genes can result in patients being poor, intermediate, efficient, or ultrarapid metabolizers of specific agents, thereby affecting efficacy and/or susceptibility to adverse drug reaction and necessitating individualized dosing. A well-documented example of ADME gene variation is the debrisoquine polymorphism, which is characterized by markedly different metabolism of numerous commonly prescribed drugs based on variants of the cytochrome P450 2D6 gene. Variants of genes regulating PD pathways cause altering of drug target pathways, which may affect efficacy in a more pronounced manner. Examples of gene variants affecting PD pathways include those coding for dopamine metabolism, synthesis, and transport. These gene variants may act independently, in combination with each other, and/or in combination with PK genes to affect drug response, for example to antipsychotic medications. Increased understanding of a patient's genotype and its corresponding effect on drug response would be useful to the practicing clinician in choosing an effective drug and in optimizing the dose in a timely manner.
Goldstein
David B
DB
Center for Population Genomics and Pharmacogenetics, Duke Institute for Genome Sciences and Policy, Duke University, Durham, North Carolina 27710, USA. d.goldstein@duke.edu
Need
Anna C
AC
Singh
Rinki
R
Sisodiya
Sanjay M
SM
D000293:Adolescent; D000328:Adult; D000367:Age Factors; D002986:Clinical Trials as Topic; D003072:Cognition Disorders / Q000139:chemically induced* / Q000453:epidemiology; D004305:Dose-Response Relationship, Drug; D004827:Epilepsy / Q000175:diagnosis / Q000188:drug therapy* / Q000235:genetics*; D005260:Female; D005632:Fructose / Q000009:adverse effects / Q000031:analogs & derivatives* / Q000493:pharmacokinetics / Q000627:therapeutic use; D005828:Genetics, Population; D006801:Humans; D008297:Male; D008875:Middle Aged; D010597:Pharmacogenetics; D018570:Risk Assessment; D012737:Sex Factors; D000077236:Topiramate; D016896:Treatment Outcome
D000077236:Topiramate; D005632:Fructose