Genome-Wide Association Study of Copy Number Variants Suggests LTBP1 and FGD4 Are Important for Alcohol Drinking

Pei, Yu‐Fang; Zhang, Lei; Yang, Tie‐Lin; Han, Yingying; Hai, Rong; Ran, Shu; Tian, Qinglong; Shen, Hui; Li, Jian Jian; Zhu, Xinyao; Luο, Xingguang; Deng, Hong−Wen

doi:10.1371/journal.pone.0030860

Cited by 15 publications

(11 citation statements)

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“…A 95% Bayesian credible interval was calculated for all meta-mQTLs and these intervals were input into the UCSC LinkOver tool to map the mouse (mm9) genome location to the human (hg19) genomic location (http://genome.ucsc.edu/cgi-bin/hgLiftOver). Various alcohol related phenotype GWAS [42], [43], [44], [45], [46] were examined for any associated SNPs residing within the syntenic region of the mQTLs. Knowledge-based searches on these syntenic regions were used for comparative genomics.…”

Section: Methodsmentioning

confidence: 99%

Whole Brain and Brain Regional Coexpression Network Interactions Associated with Predisposition to Alcohol Consumption

et al. 2013

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To identify brain transcriptional networks that may predispose an animal to consume alcohol, we used weighted gene coexpression network analysis (WGCNA). Candidate coexpression modules are those with an eigengene expression level that correlates significantly with the level of alcohol consumption across a panel of BXD recombinant inbred mouse strains, and that share a genomic region that regulates the module transcript expression levels (mQTL) with a genomic region that regulates alcohol consumption (bQTL). To address a controversy regarding utility of gene expression profiles from whole brain, vs specific brain regions, as indicators of the relationship of gene expression to phenotype, we compared candidate coexpression modules from whole brain gene expression data (gathered with Affymetrix 430 v2 arrays in the Colorado laboratories) and from gene expression data from 6 brain regions (nucleus accumbens (NA); prefrontal cortex (PFC); ventral tegmental area (VTA); striatum (ST); hippocampus (HP); cerebellum (CB)) available from GeneNetwork. The candidate modules were used to construct candidate eigengene networks across brain regions, resulting in three “meta-modules”, composed of candidate modules from two or more brain regions (NA, PFC, ST, VTA) and whole brain. To mitigate the potential influence of chromosomal location of transcripts and cis-eQTLs in linkage disequilibrium, we calculated a semi-partial correlation of the transcripts in the meta-modules with alcohol consumption conditional on the transcripts' cis-eQTLs. The function of transcripts that retained the correlation with the phenotype after correction for the strong genetic influence, implicates processes of protein metabolism in the ER and Golgi as influencing susceptibility to variation in alcohol consumption. Integration of these data with human GWAS provides further information on the function of polymorphisms associated with alcohol-related traits.

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Section: Methodsmentioning

confidence: 99%

Whole Brain and Brain Regional Coexpression Network Interactions Associated with Predisposition to Alcohol Consumption

et al. 2013

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“…For example, we reported that 754,259 (75%) among one million SNPs were significantly (p<10 −8 ) different in allele frequency between European-Americans and African-Americans; and the minor alleles ( f <0.5) of 157,718 (16%) SNPs in European-Americans were the major alleles ( f >0.5) in African-Americans, and vice versa [see Supplemental Materials and Methods by Zuo et al (Zuo et al, 2012)]. Suppose the causal allele of a putative disease-causal variant is a minor allele, it is expected that the risk allele of a marker in complete linkage disequilibrium (LD) with this causal allele would be a minor allele too, although this minor allele may be in opposite phases between European-Americans and African-Americans if this marker is among those 157,718 SNPs (Pei et al, 2012, Zuo et al, 2012). The combined effects of the same allele of such a marker (i.e., rare in one population but common in another) across these two populations by meta-analysis will be neutralized, which results in information loss.…”

Section: Introductionmentioning

confidence: 99%

A New Genomewide Association Meta-Analysis of Alcohol Dependence

Zuo

Tan

Zhang

et al. 2015

Alcohol Clin Exp Res

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Background Conventional meta-analysis based on genetic markers may be less powerful for heterogeneous samples. In the present study, we introduced a new meta-analysis for four genome-wide association studies on alcohol dependence that integrated the information of putative causal variants. Methods A total of 12,481 subjects in four independent cohorts were analyzed, including one European-American cohort (1,409 cases with alcohol dependence and 1,518 controls), one European-Australian cohort (a total of 6,438 family subjects with 1,645 probands), one African-American cohort from SAGE+COGA (681 cases and 508 controls) and one African-American cohort from Yale (1429 cases and 498 controls). The genome-wide association analysis was conducted for each cohort, and then a new meta-analysis was performed to derive the combined p values. cis-eQTL analysis of each risk variant in human tissues and RNA expression analysis of each risk gene in rat brain served as functional validation. Results In meta-analysis of European-American and European-Australian cohorts, we found 10 top-ranked SNPs (p<10−6) that were associated with alcohol dependence. They included 6 at SERINC2 (3.1×10−8≤p≤9.6×10−8), 1 at STK40 (p=1.3×10−7), 2 at KIAA0040 (3.3×10−7≤p≤5.2×10−7) and 1 at IPO11 (p=6.9×10−7). In meta-analysis of two African-American cohorts, we found 2 top-ranked SNPs including 1 at SLC6A11 (p=2.7×10−7) and 1 at CBLN2 (p=7.4×10−7). In meta-analysis of all four cohorts, we found 2 top-ranked SNPs in PTP4A1-PHF3 locus (6.0×10−7≤p≤7.2×10−7). In an African-American cohort only, we found 1 top-ranked SNP at PLD1 (p=8.3×10−7; OR=1.56). Many risk SNPs had positive cis-eQTL signals and all these risk genes except KIAA0040 were found to express in both rat and mouse brains. Conclusions We found multiple genes that were significantly or suggestively associated with alcohol dependence. They are among the most appropriate for follow-up as contributors to risk for alcohol dependence.

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“…194 In addition to the single SNP-based GWAS for AD and alcohol-related phenotypes, one genomewide gene set-based analysis 153 and three genomewide studies of copy number variants (CNVs) have been published to date (Table 4). 151,166,169 CNVs are a form of structural variation in which large regions of the genome are duplicated or deleted. CNVs, which are often rare, have been shown to explain a proportion of the risk for schizophrenia and autism.…”

Section: Gwas Of Ad or Symptoms Of Admentioning

confidence: 99%

The genetics of alcohol dependence

Rietschel

Treutlein

2012

Annals of the New York Academy of Sciences

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Alcohol consumption dates back to the Neolithic period, and alcohol dependence contributes substantially to the current global burden of disease. Despite this, optimal therapies and preventive strategies are lacking. Formal genetic studies of alcohol dependence have shown that genetic factors play as large a role in disease etiology as environmental factors. Molecular genetic studies may identify causal factors and facilitate the development of novel preventive and therapeutic approaches. Whereas earlier studies involved the use of linkage- and candidate-gene approaches, recent years have witnessed the introduction of genome-wide association studies (GWAS). The present review provides a brief overview of the findings of formal genetic studies, summarizes the results of earlier molecular-genetic investigations, and presents a detailed overview of all published GWAS in the field of alcohol dependence research. To date, few genome-wide significant findings have been reported. However, through the polygenic approach, GWAS have both confirmed the existence of a multitude of novel risk genes and indicated interesting new candidates.

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Genome-Wide Association Study of Copy Number Variants Suggests LTBP1 and FGD4 Are Important for Alcohol Drinking

Cited by 15 publications

References 50 publications

Whole Brain and Brain Regional Coexpression Network Interactions Associated with Predisposition to Alcohol Consumption

Whole Brain and Brain Regional Coexpression Network Interactions Associated with Predisposition to Alcohol Consumption

A New Genomewide Association Meta-Analysis of Alcohol Dependence

The genetics of alcohol dependence

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