Addiction molecular genetics: 639,401 SNP whole genome association identifies many “cell adhesion” genes

Liu, Qingrong; Drgon, Tomás; Johnson, Catherine; Walther, Donna; Hess, Judith; Uhl, George R.

doi:10.1002/ajmg.b.30436

Cited by 148 publications

(207 citation statements)

References 32 publications

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“…SNPs in VMAT2 and KCNMA1 have been shown to be associated with alcoholism and the endophenotype of subjective responses to ethanol (Lin et al, 2005;Schuckit et al, 2005). Also located at 83 cM is CTNNA3 (catenin alpha 3) which was recently identified in genomewide association studies of substance dependence vulnerability and nicotine dependence (Bierut et al, 2007;Liu et al, 2006).…”

Section: Discussionmentioning

confidence: 99%

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Linkage scan for quantitative traits identifies new regions of interest for substance dependence in the Collaborative Study on the Genetics of Alcoholism (COGA) sample

Agrawal

Hinrichs

Dunn

et al. 2008

Drug and Alcohol Dependence

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Dependence on alcohol and illicit drugs frequently co-occur. Results from a number of twin studies suggest that heritable influences on alcohol dependence and drug dependence may substantially overlap. Using large, genetically informative pedigrees from the Collaborative Study on the Genetics of Alcoholism (COGA), we performed quantitative linkage analyses using a panel of 1717 SNPs. Genome-wide linkage analyses were conducted for quantitative measures of DSM-IV alcohol

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Section: Discussionmentioning

confidence: 99%

“…Subsequently, these authors conducted genome-wide association analyses using 639,401 SNPs in pooled samples to identify a number of cell-adhesion genes (e.g. CNTN4, CNTN5, CNTN6: Contactin genes) associated with a general vulnerability to substance abuse/dependence (Liu et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Linkage scan for quantitative traits identifies new regions of interest for substance dependence in the Collaborative Study on the Genetics of Alcoholism (COGA) sample

Agrawal

Hinrichs

Dunn

et al. 2008

Drug and Alcohol Dependence

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“…Each DNA pool was assessed on four sets of four arrays, two from "100k" and two from "500k" Affymetrix microarray sets. Importantly, the methods used for these samples revealed r = 0.95 correlations between pooled and individual genotyping in extensive validation studies that are reported in detail in ref [68]. Data for each SNP thus provided a score that reflected a continuous percentage of its two alleles in hetero-and homozygotes in each pool.…”

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confidence: 94%

“…Another approach relies on identifying the numbers of nominally-positive SNPs that lie in genes nominated by an initial dataset. We begin here with the set of genes identified in [68], which were initially identified on the basis of strong support from clustered, reproducibly-positive SNPs in European-and African American samples from NIDA with more modest levels of support from 100k SNP genome wide association datasets from JGIDA methamphetamine-dependence and COGA alcoholdependence samples.Current availability of data based on 520,000 -630,000 autosomal SNPs from these samples, our ability to move these datasets to the more-complete build 36.1 of the NCBI human genome assembly and the availability of data from other samples listed above The genes that we identify in this way are involved in cell adhesion, enzymatic activities, protein translation, trafficking and degradation; transcriptional regulation, receptor, ion channel and transport processes, disease processes, cell structures and other functions (Table I). Most are expressed in the brain.…”

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confidence: 99%

“Higher order” addiction molecular genetics: Convergent data from genome-wide association in humans and mice

Uhl

Drgon

Johnson

et al. 2008

Biochemical Pharmacology

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Family, adoption and twin data each support substantial heritability for addictions. Most of this heritable influence is not substance-specific. The overlapping genetic vulnerability for developing dependence on a variety of addictive substances suggests large roles for "higher order" pharamacogenomics in addiction molecular genetics. We and others have now completed genomewide association (GWA) studies of DNAs from individuals with dependence on a variety of addictive substances vs appropriate controls. Recently reported replicated GWA observations identify a number of genes based on comparisons between controls and European-American and African-American polysubstance abusers. Here we review the convergence between these results and data that compares control samples and a) alcohol dependent European Americans, b) methamphetamine dependent Asians and c) nicotine dependent samples from European backgrounds. We also compare these human data to quantitative trait locus (QTL) results from studies of addiction-related phenotypes in mice that focus on alcohol, methamphetamine and barbiturates. These comparisons support a genetic architecture built from largely-polygenic contributions of common allelic variants to dependence on a variety of legal and illegal substances. Many of the gene variants identified in this way are likely to alter specification and maintenance of neuronal connections. KeywordsAssociation genome scanning; substance dependence; microarray; pooled; neuronal connections * To whom correspondence should be addressed at: Molecular Neurobiology, Box 5180, Baltimore, MD 21224 phone: (410) 550-2843 x 146, fax: (410) 550-1535, guhl@intra.nida.nih.gov. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. NIH Public Access A. Studies of human addiction vulnerabilitiesVulnerability to addictions is a complex trait with strong genetic influences that are largely shared by abusers of different legal and illegal addictive substances [1][2][3][4]. This conclusion comes from family, adoption and twin studies. Family studies clearly document that first degree relative (eg sibs) of addicts display greater risk for developing substance dependence than more distant relatives [1,5]. Adoption studies consistently find greater similarities between substance abuse phenotypes with biological relatives than with adoptive family members [1]. In twin studies, differences in concordance between genetically identical and fraternal twins also support heritability for vulnerability to addictions [3,[6][7][8][9][10][11][12]. Twin data allows quantitation of the amount, about 50%, of ad...

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“…Recently, NPAS3 was also identified as one of a number genes associated with genetic vulnerability to addiction. 15 The NPAS3 cytogenetic findings suggest that structural disruption of one allele can give rise to highly penetrant and dominantly inherited psychiatric illness. This implies the possibility that such mutations would give rise to positive linkage findings.…”

Section: Introductionmentioning

confidence: 99%

Interacting haplotypes at the NPAS3 locus alter risk of schizophrenia and bipolar disorder

et al. 2008

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The neuronal PAS domain 3 (NPAS3) gene encodes a neuronal transcription factor that is implicated in psychiatric disorders by the identification of a human chromosomal translocation associated with schizophrenia and a mouse knockout model with behavioural and hippocampal neurogenesis defects. To determine its contribution to the risk of psychiatric illness in the general population, we genotyped 70 single-nucleotide polymorphisms across the NPAS3 gene in 368 individuals with bipolar disorder, 386 individuals with schizophrenia and 455 controls. Modestly significant single-marker and global and individual haplotypes were identified in four discrete regions of the gene. The presence of both risk and protective haplotypes at each of these four regions indicated locus and allelic heterogeneity within NPAS3 and suggested a model whereby interactions between variants across the gene might contribute to susceptibility to illness. This was supported by predicting the most likely haplotype for each individual at each associated region and then calculating an NPAS3-mediated 'net genetic load' value. This value differed significantly from controls for both bipolar disorder (P = 0.0000010) and schizophrenia (P = 0.0000012). Logistic regression analysis also confirmed the combinatorial action of the four associated regions on disease risk. In addition, sensitivity/specificity plots showed that the extremes of the genetic loading distribution possess the greatest predictive power-a feature suggesting multiplicative allele interaction. These data add to recent evidence that the combinatorial analysis of a number of relatively small effect size haplotypes may have significant power to predict an individual's risk of a complex genetic disorder such as psychiatric illness.

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Addiction molecular genetics: 639,401 SNP whole genome association identifies many “cell adhesion” genes

Cited by 148 publications

References 32 publications

Linkage scan for quantitative traits identifies new regions of interest for substance dependence in the Collaborative Study on the Genetics of Alcoholism (COGA) sample

Linkage scan for quantitative traits identifies new regions of interest for substance dependence in the Collaborative Study on the Genetics of Alcoholism (COGA) sample

“Higher order” addiction molecular genetics: Convergent data from genome-wide association in humans and mice

Interacting haplotypes at the NPAS3 locus alter risk of schizophrenia and bipolar disorder

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