Human Genetics of Nicotine Addiction

描述（由申请人提供）：大约1/3的美国人口年龄超过 吸烟，这种行为对死亡率和发病率有巨大影响。而约35%的 吸烟者每年尝试戒烟，只有3%的人成功戒烟。尼古丁的原因 成瘾可能包括各种遗传和非遗传因素。基因组学研究进展 技术和计算机分析程序使发现复杂性状的易感基因成为可能。发现导致尼古丁成瘾风险的基因将加速未来有效治疗和预防的努力。该项目的主要优势包括大样本量和互补的遗传设计（同胞对连锁，系谱连锁和关联研究）。我们建议对1000个同胞对和20个犹他州大家庭进行基因组扫描，以提供足够的力量来检测易感基因座。此外，我们将测试与候选基因中的单核苷酸多态性（SNP）的关联。候选基因将根据小鼠微阵列分析中尼古丁暴露后的位置连锁证据、强生理学原理和表达改变来选择。通过确定来自犹他州人群的其他重度吸烟者、轻度吸烟者和非吸烟者，对来自正在进行的犹他州肺部健康研究和正在进行的威斯康星州尼古丁依赖研究的重度吸烟者现有充分表征的样本进行补充。除其他表型评估外，还将对受试者进行尼古丁依赖和戒断的最新评估。结构建模将用于数据简化，以定义遗传分析的表型因子。该项目利用了人类遗传学系现有的重测序、基因分型和分析能力。

DESCRIPTION (provided by applicant): Approximately 1/3 of the US population over the age of 15 smokes, a behavior that has enormous impact on mortality and morbidity. While about 35% of smokers annually try to quit, only 3% successfully overcome their addiction. Causes of nicotine addiction likely include a variety of genetic and non-genetic factors. Recent advances in genomic technologies and computerized analysis programs have made it possible to discover susceptibility genes for complex traits. The discovery of genes that contribute to the risk of nicotine addiction will accelerate future efforts toward effective treatment and prevention. Major strengths of this project include the large sample size and the complementary genetic designs (sib-pair linkage, pedigree linkage,and association studies). We propose to carry out genomic scans on 1000 sibling pairs and 20 large Utah families in order to provide ample power to detect susceptibility loci. In addition, we will test for association with single nucleotide polymorphisms (SNPs) in candidate genes. Candidate genes will be chosen based on positional linkage evidence, strong physiological rationale, and altered expression after nicotine exposure in mouse microarray analysis. Existing well-characterized samples of heavy smokers from ongoing Lung Health Studies in Utah and ongoing nicotine dependence studies in Wisconsin will be supplemented by ascertainment of additional heavy smokers, light smokers, and non-smokers from the Utah population. Subjects will be given state-of-the-art assessments of nicotine dependence and withdrawal, in addition to other phenotype assessments. Structural modeling will be used for data reduction to define phenotypic factors for genetic analysis. This project takes advantage of existing resequencing, genotyping and analytic capabilities in the Department of Human Genetics.