Identification of genes whose variants contribute to nicotine dependence would have an enormous impact on the understanding and treatment for this common and intractable problem that represents one of the most important risk factors for numerous diseases. We propose to target for re-phenotyping a subset of the 30,000 Icelanders who have already answered smoking screening questionnaires. These 30,000 individuals have already been genotyped with a genome-wide linkage set of 1000 microsatellite markers and can be leveraged for this study. We propose to re-phenotype enough of this cohort to obtain at least 1000 individuals who have moderate to severe nicotine dependence according to a standard scale and who cluster into hundreds of extended families using our nationwide genealogy database. We will also collect at least two-thousand individuals who have smoked before but who did not become nicotine dependent to serve as non-dependent controls or first degree relatives of the affecteds. A large phenotype database will include data from Fagerstrom questionnaires and SSAGAII interviews to carefully define nicotine dependence and its co-morbidities. We will map loci for nicotine dependence through fully multipoint allele sharing linkage analysis that does not assume a particular inheritance model. Significant linkage peaks with high information content will be ultrafine-mapped with hundreds of markers to define the underlying LD structure. The regions will be assessed in a case-control analysis to look for significant haplotype association to nicotine dependence. Genes found in Iceland using this approach will be tested for their impact in outside populations already collected by our US co-investigators and advisory committee members. The extensive phenotype data on the nicotine dependent patients and relatives will be used in more careful genotype-phenotype correlations as a way to understand their role in nicotine dependence and its co-morbidities.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Research Project (R01)
Project #
5R01DA017932-04
Application #
7426956
Study Section
Mammalian Genetics Study Section (MGN)
Program Officer
Pollock, Jonathan D
Project Start
2005-08-01
Project End
2010-01-21
Budget Start
2008-05-01
Budget End
2010-01-21
Support Year
4
Fiscal Year
2008
Total Cost
$1,109,442
Indirect Cost
Name
Decode Genetics, Inc.
Department
Type
DUNS #
132219176
City
Reykjavik
State
Country
Iceland
Zip Code
IS101
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