Article

Genome-wide association study of comorbid depressive syndrome and alcohol dependence

Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia 23298-0126, USA.
Psychiatric genetics (Impact Factor: 2.33). 11/2011; 22(1):31-41. DOI: 10.1097/YPG.0b013e32834acd07
Source: PubMed

ABSTRACT Depression and alcohol dependence (AD) are common psychiatric disorders that often co-occur. Both disorders are genetically influenced, with heritability estimates in the range of 35-60%. In addition, evidence from twin studies suggests that AD and depression are genetically correlated. Herein, we report results from a genome-wide association study of a comorbid phenotype, in which cases meet the Diagnostic and Statistical Manual of Mental Disorders-IV symptom threshold for major depressive symptomatology and the Diagnostic and Statistical Manual of Mental Disorders-IV criteria for AD.
Samples (N=467 cases and N=407 controls) were of European-American descent and were genotyped using the Illumina Human 1M BeadChip array.
Although no single-nucleotide polymorphism (SNP) meets genome-wide significance criteria, we identified 10 markers with P values less than 1 × 10(-5), seven of which are located in known genes, which have not been previously implicated in either disorder. Genes harboring SNPs yielding P values less than 1 × 10(-5) are functionally enriched for a number of gene ontology categories, notably several related to glutamatergic function. Investigation of expression localization using online resources suggests that these genes are expressed across a variety of tissues, including behaviorally relevant brain regions. Genes that have been previously associated with depression, AD, or other addiction-related phenotypes - such as CDH13, CSMD2, GRID1, and HTR1B - were implicated by nominally significant SNPs. Finally, the degree of overlap of significant SNPs between a comorbid phenotype and an AD-only phenotype is modest.
These results underscore the complex genomic influences on psychiatric phenotypes and suggest that a comorbid phenotype is partially influenced by genetic variants that do not affect AD alone.

0 Bookmarks
 · 
208 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: Of the two members of the δ subfamily of ionotropic glutamate receptors, GluD2 is exclusively expressed at parallel fiber-Purkinje cell (PF-PC) synapses in the cerebellum and regulates their structural and functional connectivity. However, little is known to date regarding cellular and synaptic expression of GluD1 and its role in synaptic circuit formation. In the present study, we investigated this issue by producing specific and sensitive histochemical probes for GluD1 and analyzing cerebellar synaptic circuits in GluD1-knock-out mice. GluD1 was widely expressed in the adult mouse brain, with high levels in higher brain regions, including the cerebral cortex, striatum, limbic regions (hippocampus, nucleus accumbens, lateral septum, bed nucleus stria terminalis, lateral habenula, and central nucleus of the amygdala), and cerebellar cortex. In the cerebellar cortex, GluD1 mRNA was expressed at the highest level in molecular layer interneurons and its immunoreactivity was concentrated at PF synapses on interneuron somata. In GluD1-knock-out mice, the density of PF synapses on interneuron somata was significantly reduced and the size and number of interneurons were significantly diminished. Therefore, GluD1 is common to GluD2 in expression at PF synapses, but distinct from GluD2 in neuronal expression in the cerebellar cortex; that is, GluD1 in interneurons and GluD2 in PCs. Furthermore, GluD1 regulates the connectivity of PF-interneuron synapses and promotes the differentiation and/or survival of molecular layer interneurons. These results suggest that GluD1 works in concert with GluD2 for the construction of cerebellar synaptic wiring through distinct neuronal and synaptic expressions and also their shared synapse-connecting function.
    The Journal of Neuroscience : The Official Journal of the Society for Neuroscience 05/2014; 34(22):7412-24. DOI:10.1523/JNEUROSCI.0628-14.2014 · 6.75 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Identifying replicable genetic variants for addiction has been extremely challenging. Besides the common difficulties with genome-wide association studies (GWAS), environmental factors are known to be critical to addiction, and comorbidity is widely observed. Despite the importance of environmental factors and comorbidity for addiction study, few GWAS analyses adequately considered them due to the limitations of the existing statistical methods. Although parametric methods have been developed to adjust for covariates in association analysis, difficulties arise when the traits are multivariate because there is no ready-to-use model for them. Recent nonparametric development includes U-statistics to measure the phenotype-genotype association weighted by a similarity score of covariates. However, it is not clear how to optimize the similarity score. Therefore, we propose a semiparametric method to measure the association adjusted by covariates. In our approach, the nonparametric U-statistic is adjusted by parametric estimates of propensity scores using the idea of inverse probability weighting. The new measurement is shown to be asymptotically unbiased under our null hypothesis while the previous nonweighted and weighted ones are not. Simulation results show that our test improves power as opposed to the nonweighted and two other weighted U-statistic methods, and it is particularly powerful for detecting gene-environment interactions. Finally, we apply our proposed test to the Study of Addiction: Genetics and Environment (SAGE) to identify genetic variants for addiction. Novel genetic variants are found from our analysis, which warrant further investigation in the future.
    Journal of the American Statistical Association 07/2014; 109(507). DOI:10.1080/01621459.2014.901223 · 2.11 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Objective To report the genome-wide significant and/or replicable risk variants for alcohol dependence and explore their potential biological functions.Methods We searched in PubMed for all genome-wide association studies (GWASs) of alcohol dependence. The following three types of the results were extracted: genome-wide significant associations in an individual sample, the combined samples, or the meta-analysis (p < 5 × 10−8); top-ranked associations in an individual sample (p < 10−5) that were nominally replicated in other samples (p < .05); and nominally replicable associations across at least three independent GWAS samples (p < .05). These results were meta-analyzed. cis-eQTLs in human, RNA expression in rat and mouse brains and bioinformatics properties of all of these risk variants were analyzed.ResultsThe variants located within the alcohol dehydrogenase (ADH) cluster were significantly associated with alcohol dependence at the genome-wide level (p < 5 × 10−8) in at least one sample. Some associations with the ADH cluster were replicable across six independent GWAS samples. The variants located within or near SERINC2, KIAA0040, MREG–PECR or PKNOX2 were significantly associated with alcohol dependence at the genome-wide level (p < 5 × 10−8) in meta-analysis or combined samples, and these associations were replicable across at least one sample. The associations with the variants within NRD1, GPD1L–CMTM8 or MAP3K9–PCNX were suggestive (5 × 10−8 < p < 10−5) in some samples, and nominally replicable in other samples. The associations with the variants at HTR7 and OPA3 were nominally replicable across at least three independent GWAS samples (10−5 < p < .05). Some risk variants at the ADH cluster, SERINC2, KIAA0040, NRD1, and HTR7 had potential biological functions.Conclusion The most robust risk locus was the ADH cluster. SERINC2, KIAA0040, NRD1, and HTR7 were also likely to play important roles in alcohol dependence. PKNOX2, MREG, PECR, GPD1L, CMTM8, MAP3K9, PCNX, and OPA3 might play less important roles in risk for alcohol dependence based on the function analysis. This conclusion will significantly contribute to the post-GWAS follow-up studies on alcohol dependence. (Am J Addict 2014;23:526–539)
    American Journal on Addictions 11/2014; 23(6). DOI:10.1111/j.1521-0391.2014.12147.x · 1.74 Impact Factor

Full-text (2 Sources)

Download
126 Downloads
Available from
Jun 3, 2014