Genomic regions identified by overlapping clusters of nominally-positive SNPs from genome-wide studies of alcohol and illegal substance dependence.
paper
Primary
Public
- Authors
- Johnson, Catherine; Drgon, Tomas; Walther, Donna; Uhl, George R
- Year
- 2011
- Journal
- PloS one
- PMID
- 21818250
- DOI
- 10.1371/journal.pone.0019210
- PMCID
- PMC3144872
Declaring "replication" from results of genome wide association (GWA) studies is straightforward when major gene effects provide genome-wide significance for association of the same allele of the same SNP in each of multiple independent samples. However, such unambiguous replication is unlikely when phenotypes display polygenic genetic architecture, allelic heterogeneity, locus heterogeneity and when different samples display linkage disequilibria with different fine structures. We seek chromosomal regions that are tagged by clustered SNPs that display nominally-significant association in each of several independent samples. This approach provides one "nontemplate" approach to identifying overall replication of groups of GWA results in the face of difficult genetic architectures. We apply this strategy to 1 M SNP GWA results for dependence on: a) alcohol (including many individuals with dependence on other addictive substances) and b) at least one illegal substance (including many individuals dependent on alcohol). This approach provides high confidence in rejecting the null hypothesis that chance alone accounts for the extent to which clustered, nominally-significant SNPs from samples of the same racial/ethnic background identify the same sets of chromosomal regions. It identifies several genes that are also reported in other independent alcohol-dependence GWA datasets. There is more modest confidence in: a) identification of individual chromosomal regions and genes that are not also identified by data from other independent samples, b) the more modest overlap between results from samples of different racial/ethnic backgrounds and c) the extent to which any gene not identified herein is excluded, since the power of each of these individual samples is modest. Nevertheless, the strong overlap identified among the samples with similar racial/ethnic backgrounds supports contributions to individual differences in vulnerability to addictions that come from newer allelic variants that are common in subsets of current humans.
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| # | Section | Preview |
|---|---|---|
| 0 | Introduction | Genome wide association (GWA) is a method of choice for identifying genes whose variants influence… |
| 1 | Introduction | suggests that we may have identified many or even most of the loci at which we might expect… |
| 2 | Introduction | Vulnerability to heavy use and development of dependence on alcohol and/or an illegal abused… |
| 3 | Introduction | We have developed a “nontemplate” strategy that identifies overall replication of sets of genome… |
| 4 | Introduction | We now report application of this nontemplate strategy to identify overall replication of groups of… |
| 5 | Introduction | chromosomal regions with frequencies expected by chance. We note the more modest levels of… |
| 6 | Materials and Methods — Subjects, genotyping and assignment of nominal significance of dependent vs control allele frequencies in each sample — 1) dbGAP samples from the FSCD, COGA and COGEND studies | Genotypes from unrelated subjects who provided written consents and met DSM criteria for alcohol… |
| 7 | Materials and Methods — Subjects, genotyping and assignment of nominal significance of dependent vs control allele frequencies in each sample — 1) dbGAP samples from the FSCD, COGA and COGEND studies | dependence on alcohol. Controls, defined in dbGap variable phv00022939.v1.p1.c2 “final_type”,… |
| 8 | Materials and Methods — Subjects, genotyping and assignment of nominal significance of dependent vs control allele frequencies in each sample — 1) dbGAP samples from the FSCD, COGA and COGEND studies | Genotyping for these samples was performed using Illumina 1 M SNP arrays at the Center for Inherited… |
| 9 | Materials and Methods — Subjects, genotyping and assignment of nominal significance of dependent vs control allele frequencies in each sample — 2) NIDA/MNB samples | European-American and African-American research volunteers, largely non treatment seeking, came to… |
| 10 | Materials and Methods — Subjects, genotyping and assignment of nominal significance of dependent vs control allele frequencies in each sample — 2) NIDA/MNB samples | not explicitly describe studies using high densities of DNA markers, 3) allowed us to use methods… |
| 11 | Materials and Methods — Subjects, genotyping and assignment of nominal significance of dependent vs control allele frequencies in each sample — 3) Identification of chromosomal regions containing clusters of SNPs with nominally-significant case vs control differences in single or multiple samples | We performed analyses based on previously-defined criteria using datasets of approximately 1 million… |
| 12 | Materials and Methods — Subjects, genotyping and assignment of nominal significance of dependent vs control allele frequencies in each sample — 4) Monte Carlo methods for assignment of levels of significance to: a) the extent of clustering in each sample and b) the degree to which clustered nominally-positive SNPs from multiple independent samples identify the same chromosomal regions | Monte Carlo methods were used to assign empirical statistical probabilities to two null hypotheses,… |
| 13 | Materials and Methods — Subjects, genotyping and assignment of nominal significance of dependent vs control allele frequencies in each sample — 4) Monte Carlo methods for assignment of levels of significance to: a) the extent of clustering in each sample and b) the degree to which clustered nominally-positive SNPs from multiple independent samples identify the same chromosomal regions | We first tested the null hypothesis that chromosomal clustering of these nominally positive SNPs… |
| 14 | Materials and Methods — Subjects, genotyping and assignment of nominal significance of dependent vs control allele frequencies in each sample — 4) Monte Carlo methods for assignment of levels of significance to: a) the extent of clustering in each sample and b) the degree to which clustered nominally-positive SNPs from multiple independent samples identify the same chromosomal regions | list that corresponded to these randomly-assigned numbers were then queried for the extent to which… |
| 15 | Materials and Methods — Subjects, genotyping and assignment of nominal significance of dependent vs control allele frequencies in each sample — 4) Monte Carlo methods for assignment of levels of significance to: a) the extent of clustering in each sample and b) the degree to which clustered nominally-positive SNPs from multiple independent samples identify the same chromosomal regions | Monte Carlo methods were also used to assign empirical statistical probabilities to a second null… |
| 16 | Materials and Methods — Subjects, genotyping and assignment of nominal significance of dependent vs control allele frequencies in each sample — 4) Monte Carlo methods for assignment of levels of significance to: a) the extent of clustering in each sample and b) the degree to which clustered nominally-positive SNPs from multiple independent samples identify the same chromosomal regions | Secondary analysis of dbGAP data used permutation approaches as implemented in PLINK (v1.06)… |
| 17 | Materials and Methods — Subjects, genotyping and assignment of nominal significance of dependent vs control allele frequencies in each sample — 4) Monte Carlo methods for assignment of levels of significance to: a) the extent of clustering in each sample and b) the degree to which clustered nominally-positive SNPs from multiple independent samples identify the same chromosomal regions | To assess the power of our current approach we used current sample sizes and standard deviations,… |
| 18 | Results | As noted elsewhere [21], variation among the allele frequency estimates between pools from… |
| 19 | Results — European-American samples | For the dbGAP data from European-Americans, χ2 tests displayed p<0.05 for 49,843 autosomal Illumina… |
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| Name | Type |
|---|---|
| abilities to quit smoking local | phenotype |
| Ability to quit smoking | phenotype |
| Acute response to alcohol local | phenotype |
| addiction | phenotype |
| addiction phenotypes | phenotype |
| Addictive Substance local | drug |
| ADH1C | gene |
| adoption studies | cohort |
| Affymetrix | drug |
| Affymetrix 6.0 arrays local | drug |
| Affymetrix 6.0 SNPs local | variant |
| African American | cohort |
| African-American control subjects local | cohort |
| African American data local | cohort |
| African American dataset local | cohort |
| African-American dependent subjects local | cohort |
| African-Americans | cohort |
| alcohol | phenotype |
| alcohol dependence | phenotype |
| alcohol metabolism | phenotype |
| Asian | cohort |
| autosomal SNPs | cohort |
| bipolar disorder | phenotype |
| CADPS local | gene |
| case cohort | cohort |
| cases | cohort |
| case samples | cohort |
| CAST | gene |
| CDH13 | gene |
| CDH13 variant local | variant |
| Center for Inherited Disease Research (CIDR) local | cohort |
| chromosomal clustering local | phenotype |
| cigarettes | phenotype |
| cocaine | phenotype |
| COGEND | cohort |
| Collaborative Study on the Genetics of Alcoholism (COGA) | cohort |
| complex disorders | phenotype |
| control | cohort |
| controls | cohort |
| Control samples local | phenotype |
| control subjects | cohort |
| CSMD1 | gene |
| dbGaP | cohort |
| dbGAP African-Americans local | cohort |
| dbGAP European-Americans local | cohort |
| dbGAP European-American samples local | cohort |
| dbGAP individuals local | cohort |
| dbGAP samples | cohort |
| dbGAP study phs000092.v1.p1 local | cohort |
| dbGap variable phv00022939.v1.p1.c2 local | cohort |
| dependence | phenotype |
| disease | phenotype |
| disorder | phenotype |
| DSCAM local | gene |
| ERAP local | gene |
| European-American control subjects local | cohort |
| European-American dataset local | cohort |
| European-American dependent subjects local | cohort |
| European ancestry | cohort |
| European population | cohort |
| families | cohort |
| Family study of cocaine dependence (FSCD) local | cohort |
| FTND >4 local | phenotype |
| FTND score >4 local | phenotype |
| FTND scores >4 local | phenotype |
| full sample | cohort |
| functional allelic variant local | variant |
| GABA receptor gene cluster local | gene |
| gene | gene |
| genes | gene |
| Genome-wide association data local | cohort |
| GWA datasets | cohort |
| GWA study | cohort |
| heavy drinking | phenotype |
| Hispanic individuals | cohort |
| illegal behaviors | phenotype |
| Illegal substance use local | phenotype |
| illicit drug dependence | phenotype |
| illicit drug use | phenotype |
| Illumina 1 M SNP arrays local | drug |
| Illumina genotyping | drug |
| Illumina platform | drug |
| independent samples | cohort |
| linkage studies | cohort |
| marijuana | phenotype |
| marijuana dependence | phenotype |
| MNB local | cohort |
| MNB/NIDA European-American local | cohort |
| Modest substance use local | phenotype |
| Monte Carlo simulation local | cohort |
| Mtmr7 | gene |
| nicotine | drug |
| nicotine dependence | phenotype |
| NIDA | cohort |
| NIDA/MNB | cohort |
| NIDA/MNB African-American samples local | cohort |
| NIDA/MNB European American samples local | cohort |
| NIDA/MNB European-American samples local | cohort |
| NIDA/MNB pooled samples local | cohort |
| NIDA/MNB samples local | cohort |
| NIDA pooled samples local | cohort |
| NIDA samples local | cohort |
| nontemplate analyses local | drug |
| oligogenic loci local | gene |
| opioid | drug |
| opioid dependence | phenotype |
| PECR | gene |
| phenotype | phenotype |
| phenotypic differences | phenotype |
| physical abuse | phenotype |
| polygenic influences | cohort |
| polygenic influences local | phenotype |
| pseudopositive SNPs local | variant |
| samples | cohort |
| smoking | phenotype |
| SNP | cohort |
| SNP clusters local | variant |
| substance abuse | phenotype |
| substance use | phenotype |
| Treatment-seeking individuals local | phenotype |
| true positive SNPs local | variant |
| Twin cohort | cohort |
| UBASH3B local | gene |
| unspecified phenotype local | phenotype |
| variant | cohort |
| Vulnerability to Develop Dependence local | phenotype |
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