MicroRNAs (miRNAs) are a large family of small non-coding RNAs which negatively control gene expression at both the mRNA and protein levels. The number of miRNAs identified is growing rapidly and approximately one-third is expressed in the brain where they have been shown to affect neuronal differentiation, synaptosomal complex localization and synapse plasticity, all functions thought to be disrupted in schizophrenia. Here we investigated the expression of 667 miRNAs (miRBase v.13) in the prefrontal cortex of individuals with schizophrenia (SZ, N=35) and bipolar disorder (BP, N=35) using a real-time PCR-based Taqman Low Density Array (TLDA). After extensive QC steps, 441 miRNAs were included in the final analyses. At a FDR of 10%, 22 miRNAs were identified as being differentially expressed between cases and controls, 7 dysregulated in SZ and 15 in BP. Using in silico target gene prediction programs, the 22miRNAs were found to target brain specific genes contained within networks overrepresented for neurodevelopment, behavior, and SZ and BP disease development. In an initial attempt to corroborate some of these predictions, we investigated the extent of correlation between the expressions of hsa-mir-34a, -132 and -212 and their predicted gene targets. mRNA expression of tyrosine hydroxylase (TH), phosphogluconate dehydrogenase (PGD) and metabotropic glutamate receptor 3 (GRM3) was measured in the SMRI sample. Hsa-miR-132 and -212 were negatively correlated with TH (p=0.0001 and 0.0017) and with PGD (p=0.0054 and 0.017, respectively).

Alcohol consumption is known to lead to gene expression changes in the brain. After performing weighted gene co-expression network analyses (WGCNA) on genome-wide mRNA and microRNA (miRNA) expression in Nucleus Accumbens (NAc) of subjects with alcohol dependence (AD; N = 18) and of matched controls (N = 18), six mRNA and three miRNA modules significantly correlated with AD were identified (Bonferoni-adj. p≤ 0.05). Cell-type-specific transcriptome analyses revealed two of the mRNA modules to be enriched for neuronal specific marker genes and downregulated in AD, whereas the remaining four mRNA modules were enriched for astrocyte and microglial specific marker genes and upregulated in AD. Gene set enrichment analysis demonstrated that neuronal specific modules were enriched for genes involved in oxidative phosphorylation, mitochondrial dysfunction and MAPK signaling. Glial-specific modules were predominantly enriched for genes involved in processes related to immune functions, i.e. cytokine signaling (all adj. p≤ 0.05). In mRNA and miRNA modules, 461 and 25 candidate hub genes were identified, respectively. In contrast to the expected biological functions of miRNAs, correlation analyses between mRNA and miRNA hub genes revealed a higher number of positive than negative correlations (χ2 test p≤ 0.0001). Integration of hub gene expression with genome-wide genotypic data resulted in 591 mRNA cis-eQTLs and 62 miRNA cis-eQTLs. mRNA cis-eQTLs were significantly enriched for AD diagnosis and AD symptom counts (adj. p = 0.014 and p = 0.024, respectively) in AD GWAS signals in a large, independent genetic sample from the Collaborative Study on Genetics of Alcohol (COGA). In conclusion, our study identified putative gene network hubs coordinating mRNA and miRNA co-expression changes in the NAc of AD subjects, and our genetic (cis-eQTL) analysis provides novel insights into the etiological mechanisms of AD.

Nicotinic acetylcholine receptors bind to nicotine and initiate the physiological and pharmacological responses to tobacco smoking. In this report, we studied the association of α5 and α3 subunits with nicotine dependence and with the symptoms of alcohol and cannabis abuse and dependence in two independent epidemiological samples (n = 815 and 1,121, respectively). In this study, seven single nucleotide polymorphisms were genotyped in the CHRNA5 and CHRNA3 genes. In both samples, we found that the same alleles of rs16969968 (P = 0.0068 and 0.0028) and rs1051730 (P = 0.0237 and 0.0039) were significantly associated with the scores of Fagerström test for nicotine dependence (FTND). In the analyses of the symptoms of abuse/dependence of alcohol and cannabis, we found that rs16969968 and rs1051730 were significantly associated with the symptoms of alcohol abuse or dependence (P = 0.0072 and 0.0057) in the combined sample, but the associated alleles were the opposite of that of FTND. No association with cannabis abuse/ dependence was found. These results suggested that the α5 and α3 subunits play a significant role in both nicotine dependence and alcohol abuse/dependence. However, the opposite effects with nicotine dependence and alcohol abuse/dependence were puzzling and future studies are necessary to resolve this issue.

MicroRNAs (miRNAs) are small non-coding RNAs that mainly function as negative regulators of gene expression (Lai, 2002) and have been shown to be involved in schizophrenia etiology through genetic and expression studies (Burmistrova et al., 2007; Hansen et al., 2007a; Perkins et al., 2007; Beveridge et al., 2010; Kim et al., 2010). In a mega analysis of genome-wide association study (GWAS) of schizophrenia (SZ) and bipolar disorders (BP), a polymorphism (rs1625579) located in the primary transcript of a miRNA gene, hsa-miR-137, was reported to be strongly associated with SZ. Four SZ loci (CACNA1C, TCF4, CSMD1, C10orf26) achieving genome-wide significance in the same study were predicted and later experimentally validated (Kwon et al., 2011) as hsa-miR-137 targets. Here, using in silico, cellular and luciferase based approaches we also provide evidence that another well replicated candidate schizophrenia gene, ZNF804A, is also target for hsa-miR-137.

Context The endogenous cannabinoid system has been implicated in drug addiction in animal models. The cannabinoid receptor 1 (CNR1) gene is 1 of the 2 receptors expressed in the brain. It has been reported to be associated with alcoholism and multiple drug abuse and dependence. Objective To test the hypothesis that the CNR1 gene is associated with nicotine dependence. Design Genotype-phenotype association study. Ten single-nucleotide polymorphisms were genotyped in the CNR1 gene in 2 independent samples. For the first sample (n=688), a 3-group case-control design was used to test allele association with smoking initiation and nicotine dependence. For the second sample (n = 961), association was assessed with scores from the Fagerström Test for Nicotine Dependence (FTND). Settings Population samples selected from the Mid-Atlantic Twin Registry. Participants White patients aged 18 to 65 years who met the criteria of inclusion. Main Outcome Measures Fagerström Tolerance Questionnaire and FTND scores. Results Significant single-marker and haplotype associations were found in both samples, and the associations were female specific. Haplotype 1-1-2 of markers rs2023239-rs12720071-rs806368 was associated with nicotine dependence and FTND score in the 2 samples (P<.001 and P = .009, respectively). Conclusion Variants and haplotypes in the CNR1 gene may alter the risk for nicotine dependence, and the associations are likely sex specific.

Background Alcohol Dependence (AD) shows evidence for genetic liability, but genes influencing risk remain largely unidentified. Methods We conducted a genomewide association study in 706 related AD cases and 1748 unscreened population controls from Ireland. We sought replication in 15,496 samples of European descent. We used model organisms to assess the role of orthologous genes in ethanol response behaviors. We tested one primate-specific gene for expression differences in case/control post-mortem brain tissue. Results We detected significant association in COL6A3 and suggestive association in two previously implicated loci, KLF12 and RYR3. None of these signals are significant in replication. A suggestive signal in the long noncoding RNA LOC339975 is significant in case:control meta-analysis, but not in a population sample. Knockdown of a COL6A3 ortholog in C. elegans reduced ethanol sensitivity. Col6a3 expression correlated with handling-induced convulsions in mice. Loss of function of the KLF12 ortholog in C. elegans impaired development of acute functional tolerance. Klf12 expression correlated with locomotor activation following ethanol injection in mice. Loss of function of the RYR3 ortholog reduced ethanol sensitivity in C. elegans and rapid tolerance in Drosophila. The ryanodine receptor antagonist dantrolene reduced motivation to self-administer ethanol in rats. Expression of LOC339975 does not differ between cases and controls but is reduced in carriers of the associated rs11726136 allele in nucleus accumbens. Conclusions We detect association between AD and COL6A3, KLF12, RYR3 and LOC339975. Despite non-replication of COL6A3, KLF12 and RYR3 signals, orthologs of these genes influence behavioral response to ethanol in model organisms, suggesting potential involvement in human ethanol response and AD liability. The associated LOC339975 allele may influence gene expression in human nucleus accumbens. Although the functions of long noncoding RNAs are poorly understood, there is mounting evidence implicating these genes in multiple brain functions and disorders.

Deep sequencing has become a popular tool for novel miRNA detection but its data must be viewed carefully as the state of the field is still undeveloped. Using three different programs, miRDeep (v1, 2), miRanalyzer and DSAP, we have analyzed seven data sets (six biological and one simulated) to provide a critical evaluation of the programs performance. We selected these software based on their popularity and overall approach toward the detection of novel and known miRNAs using deep-sequencing data. The program comparisons suggest that, despite differing stringency levels they all identify a similar set of known and novel predictions. Comparisons between the first and second version of miRDeep suggest that the stringency level of each of these programs may, in fact, be a result of the algorithm used to map the reads to the target. Different stringency levels are likely to affect the number of possible novel candidates for functional verification, causing undue strain on resources and time. With that in mind, we propose that an intersection across multiple programs be taken, especially if considering novel candidates that will be targeted for additional analysis. Using this approach, we identify and performed initial validation of 12 novel predictions in our in-house data with real-time PCR, six of which have been previously unreported.

Family-based and genome-wide association studies (GWAS) of alcohol dependence (AD) have reported numerous associated variants. The clinical validity of these variants for predicting AD compared to family history information has not been reported. Using the Collaborative Study on the Genetics of Alcoholism (COGA) and the Study of Addiction: Genes and Environment (SAGE) GWAS samples, we examined the aggregate impact of multiple single nucleotide polymorphisms (SNPs) on risk prediction. We created genetic sum scores by adding risk alleles associated in discovery samples, and then tested the scores for their ability to discriminate between cases and controls in validation samples. Genetic sum scores were assessed separately for SNPs associated with AD in candidate gene studies and SNPs from GWAS analyses that met varying p-value thresholds. Candidate gene sum scores did not exhibit significant predictive accuracy. Family history was a better classifier of case-control status, with a significant area under the receiver operating characteristic curve (AUC) of 0.686 in COGA and 0.614 in SAGE. SNPs that met less stringent p-value thresholds of 0.01 to 0.50 in GWAS analyses yielded significant AUC estimates, ranging from mean estimates of 0.549 for SNPs with p < 0.01 to 0.565 for SNPs with p < 0.50. This study suggests that SNPs currently have limited clinical utility, but there is potential for enhanced predictive ability with better understanding of the large number of variants that might contribute to risk.