A meta-analysis of two genome-wide association studies identifies 3 new loci for alcohol dependence

Wang, Ke Sheng; Li, Xuefeng; Zhang, Qunyuan; Pan, Yue; Aragam, Nagesh; Zeng, Min

doi:10.1016/j.jpsychires.2011.06.005

Cited by 80 publications

(67 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the present study, we found genome-wide significant association signals (po5 Â 10 À7 together with FDRo0.05) for AD for three genes (KIAA0040, SERINC2 and HTR1A) in EAs. Two of these genes, that is, KIAA0040 and HTR1A, were also among the top-ranked genes in EAs in the prior study (Bierut et al, 2010); in addition, KIAA0040 as a risk gene for AD was confirmed by another GWAS meta-analysis for SAGE, COGA, and an Australian family sample (Wang et al, 2011). However, this was not previously replicated in AAs and not confirmed by functional studies.…”

Section: Discussionmentioning

confidence: 88%

Genome-Wide Association Study of Alcohol Dependence Implicates KIAA0040 on Chromosome 1q

Zuo

Gelernter

Zhang

et al. 2011

Neuropsychopharmacol

107

128

View full text Add to dashboard Cite

Previous studies using SAGE (the Study of Addiction: Genetics and Environment) and COGA (the Collaborative Study on the Genetics of Alcoholism) genome-wide association study (GWAS) data sets reported several risk loci for alcohol dependence (AD), which have not yet been well replicated independently or confirmed by functional studies. We combined these two data sets, now publicly available, to increase the study power, in order to identify replicable, functional, and significant risk regions for AD. A total of 4116 subjects (1409 European-American (EA) cases with AD, 1518 EA controls, 681 African-American (AA) cases, and 508 AA controls) underwent association analysis. An additional 443 subjects underwent expression quantitative trait locus (eQTL) analysis. Genome-wide association analysis was performed in EAs to identify significant risk genes. All available markers in the genome-wide significant risk genes were tested in AAs for associations with AD, and in six HapMap populations and two European samples for associations with gene expression levels. We identified a unique genome-wide significant geneFKIAA0040Fthat was enriched with many replicable risk SNPs for AD, all of which had significant cis-acting regulatory effects. The distributions of Àlog(p) values for SNP-disease and SNP-expression associations for all markers in the TNN-KIAA0040 region were consistent across EAs, AAs, and five HapMap populations (0.369prp0.824; 2.8 Â 10 À9 ppp0.032). The most significant SNPs in these populations were in high LD, concentrating in KIAA0040. Finally, expression of KIAA0040 was significantly (1.2 Â 10 À11 ppp1.5 Â 10 À6) associated with the expression of numerous genes in the neurotransmitter systems or metabolic pathways previously associated with AD. We concluded that KIAA0040 might harbor a causal variant for AD and thus might directly contribute to risk for this disorder. KIAA0040 might also contribute to the risk of AD via neurotransmitter systems or metabolic pathways that have previously been implicated in the pathophysiology of AD. Alternatively, KIAA0040 might regulate the risk via some interactions with flanking genes TNN and TNR. TNN is involved in neurite outgrowth and cell migration in hippocampal explants, and TNR is an extracellular matrix protein expressed primarily in the central nervous system.

show abstract

Section: Discussionmentioning

confidence: 88%

Genome-Wide Association Study of Alcohol Dependence Implicates KIAA0040 on Chromosome 1q

Zuo

Gelernter

Zhang

et al. 2011

Neuropsychopharmacol

107

128

View full text Add to dashboard Cite

show abstract

“…html) was used to assess control genotype data for conformity with Hardy-Weinberg equilibrium (HWE). To deal with population stratification, the principal-component analysis approach (Price et al 2006) in HelixTree was used to identify outlier individuals in the COGA sample (Wang et al 2011). The logistic regression adjusted for age and sex was performed for AWS as a binary trait for the COGA sample using PLINK v1.07 (Purcell et al 2007).…”

Section: Genome-wide Association Analysismentioning

confidence: 99%

“…Bierut et al (2010) analyzed 1 M Illumina Human SNPs from The Study of Addiction: ''Genetics and Environment'' (SAGE), and identified 15 SNPs associated with AD (p \ 10 -5 ); meanwhile, Edenberg et al (2010) identified 199 SNPs (p B 2.1 9 10 -4 ) using a GWA analysis of the Collaborative Study on the Genetics of Alcoholism (COGA) sample and a cluster of genes on chromosome 11, and confirmed genes including CPE, DNASE2B, SLC10A2, ARL6IP5, ID4, GATA4, SYNE1, and ADCY3. Lind et al (2010) conducted a pooling-based GWA study and metaanalysis using a case-control design while Wang et al (2011) performed a meta-analysis of AD using the COGA and SAGE samples. More recently, GWA studies have been conducted with alcohol consumption (Baik et al 2011;Kendler et al 2011;Schumann et al 2011), event-related brain oscillations (Zlojutro et al 2011), and quantitative consumption and diagnostic and quantitative dependence (Heath et al 2011).…”

Section: Introductionmentioning

confidence: 99%

Genome-wide association study identifies 5q21 and 9p24.1 (KDM4C) loci associated with alcohol withdrawal symptoms

Wang

Zhang³

et al. 2011

J Neural Transm

Self Cite

View full text Add to dashboard Cite

Several genome-wide association (GWA) studies of alcohol dependence (AD) and alcohol-related phenotypes have been conducted; however, little is known about genetic variants influencing alcohol withdrawal symptoms (AWS). We conducted the first GWA study of AWS using 461 cases of AD with AWS and 408 controls in Caucasian population in the Collaborative Study on the Genetics of Alcoholism (COGA) sample. Logistic regression analysis of AWS as a binary trait, adjusted for age and sex, was performed using PLINK. We identified 51 SNPs associated with AWS with p < 10(-4). The first best signal was rs770182 (p = 3.65 × 10(-6)) at 5q21 near EFNA5 gene which was replicated in the Australian twin-family study of 273 families (p = 0.0172). Furthermore, three SNPs (rs10975990, rs10758821 and rs1407862) within KDM4C gene at 9p24.1 showed p < 10(-4) (p = 7.15 × 10(-6), 2.79 × 10(-5) and 4.93 × 10(-5), respectively) in the COGA sample while one SNP rs12001158 within KDM4C with p = 1.97 × 10(-4) in the COGA sample was replicated in the family sample (p = 0.01). Haplotype analysis further supported the associations of single-marker analyses of KDM4C in the COGA sample. Moreover, two SNPs (rs2046593 and rs10497668) near FSIP2 at 2q32.1 with moderate associations with AWS in the COGA sample (p = 2.66 × 10(-4) and 9.48 × 10(-5), respectively) were replicated in the family sample (p = 0.0013 and 0.0162, respectively). In addition, several SNPs in GABRA1, GABRG1, and GABRG3 were associated with AWS (p < 10(-2)) in the COGA sample. In conclusion, we identified several loci associated with AWS. These findings offer the potential for new insights into the pathogenesis of AD and AWS.

show abstract

“…Means to circumvent this problem include meta-analyses of the literature and reanalyses of pre-existing original data, both of which increase statistical power. For example, Wang et al [166,167] combined data sets from the SAGE, the COGA and the OZALC GWAS [168,169,170] and identified several gene loci not reported in the initial publications (table 1, first part). In a very recent GWAS, Gelernter et al [171] included a total of 16,087 subjects, both newly recruited and from pre-existing samples.…”

Section: Genome-wide Association Studiesmentioning

confidence: 99%

“…For example, the KIAA0040 risk variant identified in a GWAS by Zuo et al [172] and replicated in the meta-analysis by Wang et al [167], encodes an HLA1-DR11-restricted T cell epitope with yet unknown function [178]. However, expression quantitative trait locus analysis has demonstrated that the expression of the KIAA0040 gene is associated with the expression of multiple other genes involved in neurotransmission, including several genes previously implicated in alcohol dependence and other psychiatric disorders, such as DRD2-TTC12, DRD3, HTR1B, GRM5 and OPRD1 [172].…”

Section: From Genes To Pathwaysmentioning

confidence: 99%

Genetics of Alcohol Dependence: A Review of Clinical Studies

Samochowiec

Puls

et al. 2014

Neuropsychobiology

View full text Add to dashboard Cite

Background/Aims: Alcohol dependence is a common severe psychiatric disorder with a multifactorial etiology. Since the completion of the human genome project and with the increased availability of high-throughput genotyping, multiple genetic risk factors for substance-related disorders, including alcohol dependence, have been identified, but not all results could be replicated. Methods: We systematically review the clinical literature on genetic risk factors for alcohol dependence and alcohol-related phenotypes, including candidate gene-based studies, linkage studies and genome-wide association studies (GWAS). Results: Irrespectively of the methodology employed, the most robust findings regarding genetic risk factors for alcohol dependence concern genetic variations that affect alcohol metabolism. GWAS confirm the importance of the alcohol dehydrogenase gene cluster on chromosome 4 in the genetic risk for alcohol dependence with multiple variants that exert a small, but cumulative influence. A single variant with strong influence on individual risk is the aldehyde dehydrogenase 2 ALDHD2*2 variant common in Asian populations. Other robust associations have been found with previously uncharacterized genes like KIAA0040, and such observations can lead to the identification of thus far unknown signaling pathways. Converging evidence also points to a role of glutamatergic, dopaminergic and serotonergic neurotransmitter signaling in the risk for alcohol dependence, but effects are small, and gene-environment interactions further increase the complexity. Conclusion: With few exceptions like ALDH2*2, the contribution of individual genetic variants to the risk for alcohol-related disorders is small. However, the concentration of risk variants within neurotransmitter signaling pathways may help to deepen our understanding of the underlying pathophysiology and thereby contribute to develop novel therapeutic strategies.

show abstract

A meta-analysis of two genome-wide association studies identifies 3 new loci for alcohol dependence

Cited by 80 publications

References 57 publications

Genome-Wide Association Study of Alcohol Dependence Implicates KIAA0040 on Chromosome 1q

Genome-Wide Association Study of Alcohol Dependence Implicates KIAA0040 on Chromosome 1q

Genome-wide association study identifies 5q21 and 9p24.1 (KDM4C) loci associated with alcohol withdrawal symptoms

Genetics of Alcohol Dependence: A Review of Clinical Studies

Contact Info

Product

Resources

About