Uncovering hidden variance: pair-wise SNP analysis accounts for additional variance in nicotine dependence.

paper Cited Public

Authors: Culverhouse, Robert C; Saccone, Nancy L; Stitzel, Jerry A; Wang, Jen C; Steinbach, Joseph H; Goate, Alison M; Schwantes-An, Tae-Hwi; Grucza, Richard A; Stevens, Victoria L; Bierut, Laura J
Year: 2011
Journal: Human genetics
PMID: 21079997
DOI: 10.1007/s00439-010-0911-7
PMCID: PMC3030551

#	Section	Preview
0	Introduction	A key challenge for genetic analysis today is to account for the bulk of the phenotypic variance in…
1	Introduction	While all of these likely have some role in the “missing” genetic contribution to complex…
2	Introduction	There are a variety of definitions for epistasis, but a common hallmark is that the effect of one…
3	Introduction	In this study, we have taken a systematic approach to examine joint effects of variants marking the…
4	Introduction	Our goals in this study are to investigate the following questions: Can examining variants in the…
5	Materials and methods — Collaborative Genetic Study of Nicotine Dependence data	Individuals from the Collaborative Genetic Study of Nicotine Dependence (COGEND) used in these…
6	Materials and methods — Collaborative Genetic Study of Nicotine Dependence data	The SNPs examined in this study represent variants in 16 cholinergic nicotinic receptor genes, with…
7	Materials and methods — Collaborative Genetic Study of Nicotine Dependence data	All genotype data have undergone extensive quality control measures (Bierut et al. 2007; Saccone et…
8	Materials and methods — American Cancer Society data	A subset of individuals from the American Cancer Society (ACS) Cancer Prevention Study-II Nutrition…
9	Materials and methods — American Cancer Society data	rate available on each of the three questionnaires (<5 cigarettes/day in 1982 and 1992, <10…
10	Materials and methods — American Cancer Society data	SNPs genotyped in the ACS subjects included those in the neuronal nicotinic acetylcholine receptor…
11	Materials and methods — American Cancer Society data	Summary information about age and sex in the two datasets is given in Table 1.
12	Materials and methods — Joint analysis	A variety of methods can be used to investigate how multiple genetic variants contribute jointly to…
13	Materials and methods — Joint analysis	Intuitively, the RPM is a multi-locus ‘measured genotype’ (Boerwinkle et al. 1986) approach,…
14	Materials and methods — Joint analysis	a variety of simulated models (Marchini et al. 2005). We note that if the RPM model explains none of…
15	Materials and methods — Application of the RPM to the COGEND sample (Hypothesis generation)	Applying the RPM to the dichotomous nicotine dependence phenotype among smokers in COGEND allowed…
16	Materials and methods — Application of the RPM to the COGEND sample (Hypothesis generation)	Univariate and pair-wise RPM analyses were performed for the 127 nicotinic receptor SNPs that passed…
17	Materials and methods — Hypothesis testing	We took two approaches to further examine the joint effects identified by the RPM in the COGEND…
18	Materials and methods — Hypothesis testing — Logistic regression testing	All the top SNP-pairs identified by the RPM were evaluated using logistic regression to determine if…
19	Materials and methods — Hypothesis testing — Replication testing	Replication using independent data is the gold standard. For this, we used the ACS data that had the…

Name	Type
ACS Cancer Prevention Study-II Nutrition cohort local	cohort
ACS data local	cohort
African American	cohort
age	phenotype
American Community Survey	cohort
binary trait	phenotype
cancer	phenotype
cardiovascular disease	phenotype
CGASP local	cohort
Chinese	cohort
cholinergic nicotinic receptor subunit SNPs local	variant
chr15q25 local	gene
Chrna3	gene
Chrna4	gene
CHRNA5	gene
Chrnb2	gene
Chrnb4	gene
CHRN subunit gene variants local	variant
cigarettes	phenotype
COGEND	cohort
COGEND dataset local	cohort
complex diseases	phenotype
complex traits	phenotype
Consortium for the Genetic Analysis of Smoking Phenotypes (CGASP) local	cohort
copy number variant	variant
CYP2A6	gene
datasets	cohort
Detroit	cohort
diabetes	phenotype
dichotomous trait local	phenotype
efficiency of reproduction local	phenotype
European population	cohort
FTND-derived nicotine dependence phenotype local	phenotype
Gabbr1	gene
Gabbr2	gene
genetic data	drug
genetic variants	cohort
gross morphology local	phenotype
HapMap	cohort
heavy drinking	phenotype
heavy smoking phenotype local	phenotype
Heavy-smoking phenotype local	phenotype
heavy versus light smoking phenotype local	phenotype
hypertension	phenotype
Independent Dataset local	cohort
independent samples	cohort
infection	phenotype
Initial Dataset local	cohort
insertion/deletion	variant
inversion	variant
Koreans	cohort
light smokers	phenotype
light smoking phenotype local	phenotype
Light-smoking phenotype local	phenotype
longevity	phenotype
MAOA	gene
mesolimbic reward pathway local	anatomy
Meta-analysis of 76,972 subjects local	cohort
Minneapolis local	cohort
multi-locus genotype local	variant
neuronal nicotinic acetylcholine receptor genes local	gene
nicotine	drug
nicotine dependence	phenotype
nicotine receptor gene cluster local	gene
nicotinic receptor SNP local	variant
nicotinic receptor subunit genes local	gene
nicotinic receptor variants local	variant
Non-dependent smoking local	phenotype
obesity	phenotype
phenotype	phenotype
phenotypic variance	phenotype
Polymorphism	cohort
rare variant	cohort
replication sample	cohort
rs1051730	variant
rs1061730 local	variant
rs13277524	variant
rs1500948 local	variant
rs16969968	variant
rs1696998 local	variant
rs17483548 local	variant
rs2133965 local	variant
rs2292977 local	variant
rs2611603 local	variant
rs3743075 local	variant
rs3787138	variant
rs514743 local	variant
rs588765	variant
rs667282 local	variant
rs680244	variant
sex	phenotype
smoking	phenotype
smoking behavior	phenotype
smoking behaviors	phenotype
SNP	cohort
SNP in CHRNA5-CHRNA3-CHRNB4 cluster local	variant
SNP-pair local	variant
SNPs in cholinergic nicotinic receptor genes local	variant
St. Louis local	cohort
structural variant	cohort
Tobacco and Genetics Consortium	cohort
trait	phenotype
trait variance local	phenotype
translocation	variant
α5α3β4 cluster local	gene

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Uncovering hidden variance: pair-wise SNP analysis accounts for additional variance in nicotine dependence.

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