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The intersection of pharmacology, imaging, and genetics in the development of personalized medicine.

ABSTRACT: We currently rely on large randomized controlled trials and meta-analyses to make clinical decisions; this places us at a risk of discarding subgroup or individually specific treatment options owing to their failure to prove efficacious across entire populations. There is a new era emerging in personalized medicine that will focus on individual differences that are not evident phenomenologically. Much research is directed towards identifying genes, endophenotypes, and biomarkers of disease that will facilitate diagnosis and predict treatment outcome. We are at the threshold of being able to predict treatment response, primarily through genetics and neuroimaging. In this review we discuss the most promising markers of treatment response and adverse effects emerging from the areas of pharmacogenetics and neuroimaging in depression and schizophrenia.

SUBMITTER: Gerretsen P

PROVIDER: S-EPMC3181934 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature

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The intersection of pharmacology, imaging, and genetics in the development of personalized medicine.

Gerretsen Philip P Müller Daniel J DJ Tiwari Arun A Mamo David D Pollock Bruce G BG

Dialogues in clinical neuroscience 20090101 4

We currently rely on large randomized controlled trials and meta-analyses to make clinical decisions; this places us at a risk of discarding subgroup or individually specific treatment options owing to their failure to prove efficacious across entire populations. There is a new era emerging in personalized medicine that will focus on individual differences that are not evident phenomenologically. Much research is directed towards identifying genes, endophenotypes, and biomarkers of disease that ...[more]

PMID: 20135894

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Project description:BackgroundThere is currently much interest in pharmacogenetics: determining variation in genes that regulate drug effects, with a particular emphasis on improving drug safety and efficacy. The ability to determine such variation motivates the application of personalized drug therapies that utilize a patient's genetic makeup to determine a safe and effective drug at the correct dose. To ascertain whether a genotype-guided drug therapy improves patient care, a personalized medicine intervention may be evaluated within the framework of a randomized controlled trial. The statistical design of this type of personalized medicine intervention requires special considerations: the distribution of relevant allelic variants in the study population; and whether the pharmacogenetic intervention is equally effective across subpopulations defined by allelic variants.MethodsThe statistical design of the Clarification of Optimal Anticoagulation through Genetics (COAG) trial serves as an illustrative example of a personalized medicine intervention that uses each subject's genotype information. The COAG trial is a multicenter, double blind, randomized clinical trial that will compare two approaches to initiation of warfarin therapy: genotype-guided dosing, the initiation of warfarin therapy based on algorithms using clinical information and genotypes for polymorphisms in CYP2C9 and VKORC1; and clinical-guided dosing, the initiation of warfarin therapy based on algorithms using only clinical information.ResultsWe determine an absolute minimum detectable difference of 5.49% based on an assumed 60% population prevalence of zero or multiple genetic variants in either CYP2C9 or VKORC1 and an assumed 15% relative effectiveness of genotype-guided warfarin initiation for those with zero or multiple genetic variants. Thus we calculate a sample size of 1238 to achieve a power level of 80% for the primary outcome. We show that reasonable departures from these assumptions may decrease statistical power to 65%.ConclusionsIn a personalized medicine intervention, the minimum detectable difference used in sample size calculations is not a known quantity, but rather an unknown quantity that depends on the genetic makeup of the subjects enrolled. Given the possible sensitivity of sample size and power calculations to these key assumptions, we recommend that they be monitored during the conduct of a personalized medicine intervention.Trial registrationclinicaltrials.gov: NCT00839657.

Project description:Development of addiction to alcohol or other substances can be attributed in part to exposure-dependent modifications at synaptic efficacy leading to an organism which functions at an altered homeostatic setpoint. Genetic factors may also influence setpoints and the stability of the homeostatic system of an organism. Quantitative genetic analysis of voluntary alcohol drinking, and mapping of the involved genes in the quasi-congenic Recombinant QTL Introgression strain system, identified Eac2 as a Quantitative Trait Locus (QTL) on mouse chromosome 6 which explained 18% of the variance with an effect size of 2.09 g/kg/day alcohol consumption, and Grm7 as a quantitative trait gene underlying Eac2 [Vadasz et al. in Neurochem Res 32:1099-1112, 100, Genomics 90:690-702, 102]. In earlier studies, the product of Grm7 mGluR7, a G protein-coupled receptor, has been implicated in stress systems [Mitsukawa et al. in Proc Natl Acad Sci USA 102:18712-18717, 63], anxiety-like behaviors [Cryan et al. in Eur J Neurosci 17:2409-2417, 14], memory [Holscher et al. in Learn Mem 12:450-455, 26], and psychiatric disorders (e.g., [Mick et al. in Am J Med Genet B Neuropsychiatr Genet 147B:1412-1418, 61; Ohtsuki et al. in Schizophr Res 101:9-16, 72; Pergadia et al. in Paper presented at the 38th Annual Meeting of the Behavior Genetics Association, Louisville, Kentucky, USA, 76]. Here, in experiments with mice, we show that (1) Grm7 knockout mice express increased alcohol consumption, (2) sub-congenic, and congenic mice carrying a Grm7 variant characterized by higher Grm7 mRNA drink less alcohol, and show a tendency for higher circadian dark phase motor activity in a wheel running paradigm, respectively, and (3) there are significant genetic differences in Grm7 mRNA abundance in the mouse brain between congenic and background mice identifying brain areas whose function is implicated in addiction related processes. We hypothesize that metabotropic glutamate receptors may function as regulators of homeostasis, and Grm7 (mGluR7) is involved in multiple processes (including stress, circadian activity, reward control, memory, etc.) which interact with substance use and the development of addiction. In conclusion, we suggest that mGluR7 is a significant new therapeutic target in addiction and related neurobehavioral disorders.

Dataset Information

The intersection of pharmacology, imaging, and genetics in the development of personalized medicine.

Publications

The intersection of pharmacology, imaging, and genetics in the development of personalized medicine.

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