ArticleHuman heredity2010
Using a pharmacokinetic model to relate an individual's susceptibility to alcohol dependence to genotypes.
Article in Human heredity, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- A unified mapping framework of multifaceted pharmacodynamic responses to hypertension interventions.Drug discovery today · 2019Review
- Mapping genes for drug chronotherapy.Drug discovery today · 2018Review
- Pharmacodynamic genome-wide association study identifies new responsive loci for glucocorticoid intervention in asthma.The pharmacogenomics journal · 2015Article
- Do polymorphisms in chemosensory genes matter for human ingestive behavior?Food quality and preference · 2013Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
BACKGROUND/
aimsPopulation-based studies have successfully identified genes affecting common diseases, but have not provided a molecular mechanism. We describe an approach for alcohol dependence connecting a mechanistic model at the molecular level with disease risk at the population level, and investigate how this model implies statistical gene-gene interactions that affect disease risk.
methodsWe develop a pharmacokinetic model describing how genetic variations in ADH1B, ADH1C, ADH7, ALDH2, and TAS2R38 affect consumption behavior, and alcohol and acetaldehyde levels over time in various tissues of individuals with a particular genotype to predict their susceptibility to alcohol dependence.
resultsWe show that there is good agreement between the observed genotype/haplotype frequencies and those predicted by the model among cases and controls. Based on this framework, we show that we expect to observe statistical interactions among these genes for a reasonably large sample size when logistic regression models are used to relate genotype effects and disease risk.
conclusionOur model exemplifies mechanistic modeling of how genes interact to influence an individual's susceptibility to alcohol dependence. We anticipate that this general approach could also be applied to study other diseases at the molecular level.
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