A Systems Biology Approach to Detect eQTLs Associated with miRNA and mRNA Co-expression Networks in the Nucleus Accumbens of Chronic Alcoholic Patients

Alcohol Dependence (AD) is a chronic substance use disorder with moderate heritability (60%). Linkage and genome-wide association studies (GWAS) have implicated a number of loci; however, the molecular mechanisms underlying AD are unclear. Advances in systems biology allow genome-wide expression data to be integrated with genetic data to detect expression quantitative trait loci (eQTL), polymorphisms that regulate gene expression levels, influence phenotypes and are significantly enriched among validated genetic signals for many commonly studied traits including AD. We integrated genome-wide mRNA and miRNA expression data with genotypic data from the nucleus accumbens (NAc), a major addiction-related brain region, of 36 subjects (18 AD cases, 18 matched controls). We applied weighted gene co-expression network analysis (WGCNA) to identify mRNA and miRNA gene co-expression modules significantly associated with AD. We identified six mRNA modules, two of which were downregulated in AD and were enriched for neuronal marker gene expression. The remaining four modules were upregulated in AD and enriched for astrocyte and microglial marker gene expressions. After performing gene set enrichment analysis (GSEA), we found that neuronal-specific modules enriched for oxidative phosphorylation, mitochondrial dysfunction and MAPK signaling pathways and glial-specific modules enriched for immune related processes, cell adhesion molecules and cell signaling pathways. WGCNA was also applied to miRNA data and identified two downregulated and one upregulated modules in AD. We intersected computationally predicted miRNA:mRNA interactions with miRNA and mRNA expression correlations to identify 481 significant (FDR\u3c0.10) miRNA:mRNA targeting pairs. Over half (54%) of the mRNAs were targeted cooperatively by more than one miRNA suggesting a potentially important cellular mechanism relevant to AD. After integrating our expression and genetic data we identified 591 significant mRNA and 68 significant miRNA cis-eQTLs (\u3c1 megabase) (FDR\u3c0.10). After querying against GWAS data from the Colaborative Study on Genetics of Alcohol and Study of Addiction: Gentics and Environment, eQTLs for neuronatin (NNAT; rs1780705), proteosome subunit type 5 (PSMB5; rs10137082), long non-coding RNA (PKI55; rs13392737), adaptor related protein complex 1 sigma one subunit (AP1S1; rs12079545) and translocation associate membrane protein 1 (TRAM1; rs13277972) were associated with AD or alcohol related phenotypes at p\u3c10-4