Genetics of Alcoholism

Purpose of Review We review the search for genetic variants that affect the risk for alcohol dependence and alcohol consumption. Recent Findings Variations in genes affecting alcohol metabolism (ADH1B, ALDH2) are protective against both alcohol dependence and excessive consumption, but different variants are found in different populations. There are different patterns of risk variants for alcohol dependence vs. consumption. Variants for alcohol dependence, but not consumption, are associated with risk for other psychiatric illnesses. Summary ADH1B and ALDH2 strongly affect both consumption and dependence. Variations in many other genes affect both consumption and dependence—or one or the other of these traits—but individual effect sizes are small. Evidence for other specific genes that affect dependence is not yet strong. Most current knowledge derives from studies of European-ancestry populations, and large studies of carefully phenotyped subjects from different populations are needed to understand the genetic contributions to alcohol consumption and alcohol use disorders

A Genome-Wide Association Study of Cocaine Use Disorder Accounting for Phenotypic Heterogeneity and Gene–Environment Interaction

Background: Phenotypic heterogeneity and complicated gene-environment interplay in etiology are among the primary factors that hinder the identification of genetic variants associated with cocaine use disorder. Methods: To detect novel genetic variants associated with cocaine use disorder, we derived disease traits with reduced phenotypic heterogeneity using cluster analysis of a study sample (n = 9965). We then used these traits in genome-wide association tests, performed separately for 2070 African Americans and 1570 European Americans, using a new mixed model that accounted for the moderating effects of 5 childhood environmental factors. We used an independent sample (918 African Americans, 1382 European Americans) for replication. Results: The cluster analysis yielded 5 cocaine use disorder subtypes, of which subtypes 4 (n = 3258) and 5 (n = 1916) comprised heavy cocaine users, had high heritability estimates (h2 = 0.66 and 0.64, respectively) and were used in association tests. Seven of the 13 identified genetic loci in the discovery phase were available in the replication sample. In African Americans, rs114492924 (discovery p = 1.23 x E-8), a single nucleotide polymorphism in LINC01411, was replicated in the replication sample (p = 3.63 x E-3). In a meta-analysis that combined the discovery and replication results, 3 loci in African Americans were significant genome-wide: rs10188036 in TRAK2 (p = 2.95 x E-8), del 1:15511771 in TMEM51 = 9.11 x E-10) and rs149843442 near LPHN2 (p = 3.50 x E-8). Limitations: Lack of data prevented us from replicating 6 of the 13 identified loci. Conclusion: Our results demonstrate the importance of considering phenotypic heterogeneity and gene-environment interplay in detecting genetic variations that contribute to cocaine use disorder, because new genetic loci have been identified using our novel analytic method

NIH Public Access Author Manuscript Biol Psychiatry. Author manuscript; available in PMC 2011 January 1.

Published in final edited form as

Characterization of a likelihood based method and effects of markers informativeness in evaluation of admixture and population group assignment

BACKGROUND: Detection and evaluation of population stratification are crucial issues in the conduct of genetic association studies. Statistical approaches useful for understanding these issues have been proposed; these methods rely on information gained from genotyping sets of markers that reflect population ancestry. Before using these methods, a set of markers informative for differentiating population genetic substructure (PGS) is necessary. We have previously evaluated the performance of a Bayesian clustering method implemented in the software STRUCTURE in detecting PGS with a particular informative marker set. In this study, we implemented a likelihood based method (LBM) in evaluating the informativeness of the same selected marker panel, with respect to assessing potential for stratification in samples of European Americans (EAs) and African Americans (AAs), that are known to be admixed. LBM calculates the probability of a set of genotypes based on observations in a reference population with known specific allele frequencies for each marker, assuming Hardy Weinberg equilibrium (HWE) for each marker and linkage equilibrium among markers. RESULTS: In EAs, the assignment accuracy by LBM exceeded 99% using the most efficient marker FY, and reached perfect assignment accuracy using the 10 most efficient markers excluding FY. In AAs, the assignment accuracy reached 96.4% using FY, and >95% when using at least the 9 most efficient markers. The comparison of the observed and reference allele frequencies (which were derived from previous publications and public databases) shows that allele frequencies observed in EAs matched the reference group more accurately than allele frequencies observed in AAs. As a result, the LBM performed better in EAs than AAs, as might be expected given the dependence of LBMs on prior knowledge of allele frequencies. Performance was not dependent on sample size. CONCLUSION: The performance of the LBM depends on the efficiency and number of markers, and depends greatly on how representative the available reference allele frequencies are for those of the population being assigned. This method is of value when the parental population is known and relevant allele frequencies are available

Variation at APOE and STH loci and Alzheimer's disease

BACKGROUND: The apolipoprotein E (APOE) and tau proteins play important roles in the pathological development of Alzheimer's disease (AD). Many studies have shown an association between the APOE gene and AD. Association between AD and the newly discovered saitohin (STH) gene, nested within the intron of the tau gene, has been reported. The present study aimed to elucidate the association between APOE and AD, and between STH and AD in our sample. METHODS: The functional polymorphisms, rs429358 and rs7412, in the APOE gene (which together define the ε2, ε3, and ε4 alleles), and the Q7R SNP in the STH gene, were genotyped in 369 patients with AD and 289 healthy European-Americans. The associations between these two genes and AD were analyzed in a case-control design. RESULTS: Consistent with previously reported results, the frequencies of the APOE ε4 allele, ε4/ε4 genotype and ε3/ε4 genotype were significantly higher in AD cases than controls; the ε4/ε4 genotype frequency was significantly higher in early-onset AD (EOAD) than late-onset AD (LOAD); the frequencies of the ε2 allele, ε3 allele, ε3/ε3 genotype and ε2/ε3 genotype were significantly lower in AD cases than controls. Positive likelihood ratios (LRs(+)) of APOE alleles and genotypes increased in a linear trend with the number of ε4 alleles and decreased in a linear trend with the number of ε2 or ε3 alleles. There was no significant difference in the STH allele and genotype frequency distributions between AD cases and controls. CONCLUSION: This study confirmed that the ε4 allele is a dose-response risk factor for AD and the ε4/ε4 genotype was associated with a significantly earlier age of onset. Moreover, we found that the ε2 allele was a dose-response protective factor for AD and the ε3 allele exerted a weaker dose-response protective effect for risk of AD compared with ε2. In a clinical setting, APOE genotyping could offer additional biological evidence of whether a subject may develop AD, but it is not robust enough to serve as an independent screening or predictive test in the diagnosis of AD. STH variation was not significantly associated with AD in our sample

Evaluating the role of a galanin enhancer genotype on a range of metabolic, depressive and addictive phenotypes

Funded by •ERC. Grant Number: 284167 •NIH. Grant Number: 1RO1DK0921127-01 •NWO. Grant Numbers: 463-06-001, 451-04-034Peer reviewedPublisher PD