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PMID: 19525886 Published · ppublish English Journal Article Research Support, N.I.H., Extramural

A systems biology network model for genetic association studies of nicotine addiction and treatment.

Pharmacogenetics and genomics ·Vol. 19 ·No. 7 ·2009-07-00 ·Pages 538-51

Thomas PD, Mi H, Swan GE, Lerman C, Benowitz N, Tyndale RF, Bergen AW, Conti DV, Pharmacogenetics of Nicotine Addiction and Treatment Consortium

Abstract

Interpreting genome-scale genetic association data, particularly for complex diseases and phenotypes, requires extensive use of prior knowledge across a broad range of potential biological and environmental influences, spanning many scientific subdisciplines. We suggest that known or hypothesized disease risk factors, and causal mechanisms, can be represented using an ontology, a computational specification of a set of concepts and the relations between them. We have integrated the expertise of multiple investigators in nicotine pharmacokinetics and pharmacodynamics, nicotine dependence, and clinical smoking cessation outcomes, and represented this knowledge in an ontology-based network model. Our model spans multiple scales, from molecules, genes and cellular pathways, to complex behavioral phenotypes and even environmental factors. To leverage previous and ongoing work in the field of ontology development, we adopt, expand upon and relate elements from existing ontologies whenever possible. We discuss several applications of our ontology: to support interdisciplinary research by graphically representing a complex scientific theory, to facilitate meta-analysis across different studies, to highlight potential interactions, and to support statistical analysis and causal modeling. We demonstrate that our ontology can focus hypothesis testing on areas supported by current theory. We describe how an ontology-based computational representation can be applied to disease risk factors and mechanisms, enabling the use of prior knowledge in large-scale genetic association studies in general. In specific, we have developed an initial Smoking Behavior Risk Ontology to support studies related to the pharmacogenetics of nicotine addiction and treatment.

MeSH Terms
Databases, Genetic Genetic Predisposition to Disease Humans Liver/metabolism Models, Genetic Phenotype Reproducibility of Results Smoking/genetics Systems Biology Tobacco Use Disorder/genetics,therapy
Authors & Affiliations
9 authors, click to expand affiliations / ORCID
Thomas Paul D
Evolutionary Systems Biology, Artificial Intelligence Center, SRI International, Menlo Park, CA 94025, USA. paul.thomas@sri.com
Mi Huaiyu
Swan Gary E
Lerman Caryn
Benowitz Neal
Tyndale Rachel F
Bergen Andrew W
Conti David V
Pharmacogenetics of Nicotine Addiction and Treatment Consortium
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Article Info
Journal
Pharmacogenetics and genomics
Abbr.
Pharmacogenet Genomics
ISSN
1744-6872
DOI
10.1097/FPC.0b013e32832e2ced
Email
paul.thomas@sri.com
Published
2009-07-00
Pages
538-51
Language
English
Region
United States
NLM ID
101231005
PMCID
PMC6485245
Subset
IM
Grants
NIDA NIH HHS · U01 DA020830 · United States
External Links
PubMed source DOI: 10.1097/FPC.0b013e32832e2ced PMC Full Text View journal details
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