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Alcohol use disorder (AUD) is a complex genetic disorder characterized by problems arising from excessive alcohol consumption. Identifying functional genetic variations that contribute to risk for AUD is a major goal. Alternative splicing of RNA mediates the flow of genetic information from DNA to gene expression and expands proteome diversity. We asked whether alternative splicing could be a risk factor for AUD. Herein, we used a Mendelian randomization (MR)-based approach to identify skipped exons (the predominant splicing event in brain) that contribute to AUD risk. Genotypes and RNA-seq data from the CommonMind Consortium were used as the training dataset to develop predictive models linking individual genotypes to exon skipping in the prefrontal cortex. We applied these models to data from the Collaborative Studies on Genetics of Alcoholism to examine the association between the imputed cis-regulated splicing outcome and the AUD-related traits. We identified 27 exon skipping events that were predicted to affect AUD risk; six of these were replicated in the Australian Twin-family Study of Alcohol Use Disorder. Their host genes are DRC1, ELOVL7, LINC00665, NSUN4, SRRM2 and TBC1D5. The genes downstream of these splicing events are enriched in neuroimmune pathways. The MR-inferred impacts of the ELOVL7 skipped exon on AUD risk was further supported in four additional large-scale genome-wide association studies. Additionally, this exon contributed to changes of gray matter volumes in multiple brain regions, including the visual cortex known to be involved in AUD. In conclusion, this study provides strong evidence that RNA alternative splicing impacts the susceptibility to AUD and adds new information on AUD-relevant genes and pathways. Our framework is also applicable to other types of splicing events and to other complex genetic disorders.

BACKGROUND Genome-wide association studies (GWAS) of alcohol dependence (AD) and related phenotypes have identified multiple loci, but the functional variants underlying the loci have in most cases not been identified. Noncoding variants can influence phenotype by affecting gene expression; for example, variants in the 3' untranslated regions (3'UTR) can affect gene expression posttranscriptionally. METHODS We adapted a high-throughput assay known as PASSPORT-seq (parallel assessment of polymorphisms in miRNA target sites by sequencing) to identify among variants associated with AD and related phenotypes those that cause differential expression in neuronal cell lines. Based upon meta-analyses of alcohol-related traits in African American and European Americans in the Collaborative Study on the Genetics of Alcoholism, we tested 296 single nucleotide polymorphisms (SNPs with meta-analysis p values ≤ 0.001) that were located in 3'UTRs. RESULTS We identified 60 SNPs that affected gene expression (false discovery rate [FDR]

Genome-wide association studies (GWAS) of complex traits, such as alcohol use disorders (AUD), usually identify variants in non-coding regions and cannot by themselves distinguish whether the associated variants are functional or in linkage disequilibrium with the functional variants. Transcriptome studies can identify genes whose expression differs between alcoholics and controls. To test which variants associated with AUD may cause expression differences, we integrated data from deep RNA-seq and GWAS of four postmortem brain regions from 30 subjects with AUD and 30 controls to analyze allele-specific expression (ASE). We identified 88 genes with differential ASE in subjects with AUD compared to controls. Next, to test one potential mechanism contributing to the differential ASE, we analyzed single nucleotide polymorphisms (SNPs) in the 3′ untranslated regions (3′UTR) of these genes. Of the 88 genes with differential ASE, 61 genes contained 437 SNPs in the 3′UTR with at least one heterozygote among the subjects studied. Using a modified PASSPORT-seq (parallel assessment of polymorphisms in miRNA target-sites by sequencing) assay, we identified 25 SNPs that affected RNA levels in a consistent manner in two neuroblastoma cell lines, SH-SY5Y and SK-N-BE(2). Many of these SNPs are in binding sites of miRNAs and RNA-binding proteins, indicating that these SNPs are likely causal variants of AUD-associated differential ASE. In sum, we demonstrate that a combination of computational and experimental approaches provides a powerful strategy to uncover functionally relevant variants associated with the risk for AUD.

Transcriptome studies can identify genes whose expression differs between alcoholics and controls. To test which variants associated with alcohol use disorder (AUDs) may cause expression differences, we integrated deep RNA-seq and genome-wide association studies (GWAS) data from four postmortem brain regions of 30 AUDs subjects and 30 controls (social/non-drinkers) and analyzed allele-specific expression (ASE). We identified 90 genes with differential ASE in subjects with AUDs compared to controls. Of these, 61 genes contained 437 single nucleotide polymorphisms (SNPs) in the 3’ untranslated regions (3’UTR) with at least one heterozygote among the subjects studied. Using a modified PASSPORT-seq (parallel assessment of polymorphisms in miRNA target-sites by sequencing) assay, we identified 25 SNPs that showed affected RNA levels in a consistent manner in two neuroblastoma cell lines, SH-SY5Y and SK-N-BE(2). Many of these are in binding sites of miRNAs and RNA binding proteins, indicating that these SNPs are likely causal variants of AUD-associated differential ASE.

Obesity is associated with the higher risk of breast cancer in postmenopausal women. The leptin signaling pathway is recognized to primarily regulate energy balance and associated with breast cancer. Furthermore, the estrogen signaling pathway plays a critical role in breast carcinogenesis. In this review, we discuss how obesity is linked to breast cancer via cross-talk of leptin and estrogen pathways.