Article

Genome-wide association studies identify genetic loci related to alcohol consumption in Korean men

Department of Foods and Nutrition, College of Natural Sciences, Kookmin University, Seoul, Republic of Korea.
American Journal of Clinical Nutrition (Impact Factor: 6.92). 03/2011; 93(4):809-16. DOI: 10.3945/ajcn.110.001776
Source: PubMed

ABSTRACT Genome-wide association (GWA) studies regarding the quantitative trait of alcohol consumption are limited.
The objective of the study was to explore genetic loci associated with the amount of alcohol consumed.
We conducted a GWA study with discovery data on single nucleotide polymorphisms (SNPs) for 1721 Korean male drinkers aged 40-69 y who were included in an urban population-based cohort. Another sample that comprised 1113 male drinkers who were from an independent cohort enrolled in a rural area served as a resource for replication. At baseline (18 June 2001 through 29 January 2003), members of both cohorts provided information on average daily alcohol consumptions, and their DNA samples were collected for genotyping.
We tested 315,914 SNPs of discovery data by using multivariate linear regression analysis adjusted for age and smoking, and 12 SNPs on chromosome 12q24 had genome-wide significant associations with alcohol consumption; adjusted P values by using Bonferroni correction were 1.6 × 10(-5) through 5.8 × 10(-46). We observed most SNPs in intronic regions and showed that the genes that harbor SNPs were C12orf51, CCDC63, MYL2, OAS3, CUX2, and RPH3A. In particular, signals in or near C12orf51, CCDC63, and MYL2 were successfully replicated in the test for 317,951 SNPs; rs2074356 in C12orf51 was in high linkage disequilibrium with SNPs in ALDH2, but other SNPs were not.
In a GWA study, we identified loci and alleles highly associated with alcohol consumption. The findings suggest the need for further investigations on the genetic propensity for drinking excessive amounts of alcohol.

0 Followers
 · 
147 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Metabolic syndrome (MetS) is a complex disorder related to insulin resistance, obesity, and inflammation. Genetic and environmental factors also contribute to the development of MetS, and through genome-wide association studies (GWASs), important susceptibility loci have been identified. However, GWASs focus more on individual single-nucleotide polymorphisms (SNPs), explaining only a small portion of genetic heritability. To overcome this limitation, pathway analyses are being applied to GWAS datasets. The aim of this study is to elucidate the biological pathways involved in the pathogenesis of MetS through pathway analysis. Cohort data from the Korea Associated Resource (KARE) was used for analysis, which include 8,842 individuals (age, 52.2 ± 8.9 years; body mass index, 24.6 ± 3.2 kg/m2). A total of 312,121 autosomal SNPs were obtained after quality control. Pathway analysis was conducted using Meta-analysis Gene-Set Enrichment of Variant Associations (MAGENTA) to discover the biological pathways associated with MetS. In the discovery phase, SNPs from chromosome 12, including rs11066280, rs2074356, and rs12229654, were associated with MetS (p < 5 × 10-6), and rs11066280 satisfied the Bonferroni-corrected cutoff (unadjusted p < 1.38 × 10-7, Bonferroni-adjusted p < 0.05). Through pathway analysis, biological pathways, including electron carrier activity, signaling by platelet-derived growth factor (PDGF), the mitogen-activated protein kinase kinase kinase cascade, PDGF binding, peroxisome proliferator-activated receptor (PPAR) signaling, and DNA repair, were associated with MetS. Through pathway analysis of MetS, pathways related with PDGF, mitogen-activated protein kinase, and PPAR signaling, as well as nucleic acid binding, protein secretion, and DNA repair, were identified. Further studies will be needed to clarify the genetic pathogenesis leading to MetS.
    12/2014; 12(4):195. DOI:10.5808/GI.2014.12.4.195
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: It is well-known that alcohol consumption is associated with stroke risk as well as with aldehyde dehydrogenase 2 gene (ALDH2) polymorphisms. However, it is unclear whether ALDH2 polymorphisms are associated with stroke risk independent of alcohol consumption and whether such association is modified by sex. We evaluated sex-specific associations of a common ALDH2 polymorphism and alcohol consumption with stroke risk in a Korean population. We conducted a prospective cohort study involving 8,465 men and women, aged 40-69 years and free of stroke between June, 2001 and January, 2003, and followed for the development of stroke. We identified new cases of stroke, which were self-reported or ascertained from vital registration data. Based on genome-wide association data, we selected a single-nucleotide polymorphism (rs2074356), which shows high linkage disequilibrium with the functional polymorphism of ALDH2. We conducted Cox proportional hazards regression analysis considering potential risk factors collected from a baseline questionnaire. Over the median follow-up of 8 years, 121 cases of stroke were identified. Carrying the wild-type allele of the ALDH2 polymorphism increased stroke risk among men. The multivariate hazard ratio [95% confidence interval] of stroke was 2.02 [1.03-3.99] for the wild-type allele compared with the mutant alleles, but the association was attenuated after controlling for alcohol consumption. Combinations of the wild-type allele and other risk factors of stroke, such as old age, diabetes mellitus, and habitual snoring, synergistically increased the risk among men. Among women, however, the ALDH2 polymorphism was not associated with stroke risk. The prospective cohort study showed a significant association between a common ALDH2 polymorphism and stroke risk in Korean men, but not in Korean women, and also demonstrated that men with genetic disadvantages gain more risk when having risk factors of stroke. Thus, these men may need to make more concerted efforts to control modifiable risk factors of stroke.
    Nutrition research and practice 02/2015; 9(1):79-86. DOI:10.4162/nrp.2015.9.1.79 · 1.13 Impact Factor
  • Source
    Diabetes & metabolism journal 12/2014; 38(6):484-6. DOI:10.4093/dmj.2014.38.6.484