Association Study of Gene Polymorphisms in GABA, Serotonin, Dopamine, and Alcohol Metabolism Pathways with Alcohol Dependence in Taiwanese Han Men.

BACKGROUND: The roles of GABA, serotonin, dopamine, and alcohol metabolism pathways in alcohol dependence (AD) are evident from animal models and human studies. Aims of this study were to investigate associations between genes in the 4 pathways and AD. METHODS: Male subjects from 2 independent samples of Taiwanese Han descent, a family sample of 179 trios and a case-control sample of 262 AD cases and 273 normal controls, were included in this study. The Schedules for Clinical Assessment in Neuropsychiatry was used for phenotype assessment of AD. We genotyped 282 single nucleotide polymorphisms (SNPs) located in 61 candidate genes involving alcohol metabolism, serotonin, and GABA systems among the family sample and replicated the top hits in the case-control sample. RESULTS: Fifteen SNPs located in 10 genes showed signals of associations (FBAT test p < 0.05) with AD in the family sample. Three SNPs, rs1229984 in ADH1B, rs671 in ALDH2, and rs2000292 in HTR1B, were significantly replicated in the case-control sample (p = 5.87 × 10(-14) , 5.12 × 10(-14) , and 0.0051, respectively). In the combined meta-analysis, these 3 SNPs and 1 additional SNP, rs698 in ADH1C, showed significant association after correcting for multiple comparisons, and rs1229984 and rs671 showed the strongest association (p < 10(-16) ). Logistic regression conditioning on rs1229984 and rs671 in the case-control sample showed that rs2000292 in HTR1B remained nominally significant. CONCLUSIONS: Genes in alcohol metabolism pathway, especially ADH1B and ALDH2, conferred the major genetic risk for AD in Taiwanese Han population. Some genes in GABA and serotonin pathways showed nominal association with AD.

Incorporating significant amino acid pairs and protein domains to predict RNA splicing-related proteins with functional roles.

Machinery of pre-mRNA splicing is carried out through the interaction of RNA sequence elements and a variety of RNA splicing-related proteins (SRPs) (e.g. spliceosome and splicing factors). Alternative splicing, which is an important post-transcriptional regulation in eukaryotes, gives rise to multiple mature mRNA isoforms, which encodes proteins with functional diversities. However, the regulation of RNA splicing is not yet fully elucidated, partly because SRPs have not yet been exhaustively identified and the experimental identification is labor-intensive. Therefore, we are motivated to design a new method for identifying SRPs with their functional roles in the regulation of RNA splicing. The experimentally verified SRPs were manually curated from research articles. According to the functional annotation of Splicing Related Gene Database, the collected SRPs were further categorized into four functional groups including small nuclear Ribonucleoprotein, Splicing Factor, Splicing Regulation Factor and Novel Spliceosome Protein. The composition of amino acid pairs indicates that there are remarkable differences among four functional groups of SRPs. Then, support vector machines (SVMs) were utilized to learn the predictive models for identifying SRPs as well as their functional roles. The cross-validation evaluation presents that the SVM models trained with significant amino acid pairs and functional domains could provide a better predictive performance. In addition, the independent testing demonstrates that the proposed method could accurately identify SRPs in mammals/plants as well as effectively distinguish between SRPs and RNA-binding proteins. This investigation provides a practical means to identifying potential SRPs and a perspective for exploring the regulation of RNA splicing.