Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
BMC Genomics. 2012;13 Suppl 8(Suppl 8):S16. doi: 10.1186/1471-2164-13-S8-S16. Epub 2012 Dec 17.
A variety of species and experimental designs have been used to study genetic influences on alcohol dependence, ethanol response, and related traits. Integration of these heterogeneous data can be used to produce a ranked target gene list for additional investigation.
In this study, we performed a unique multi-species evidence-based data integration using three microarray experiments in mice or humans that generated an initial alcohol dependence (AD) related genes list, human linkage and association results, and gene sets implicated in C. elegans and Drosophila. We then used permutation and false discovery rate (FDR) analyses on the genome-wide association studies (GWAS) dataset from the Collaborative Study on the Genetics of Alcoholism (COGA) to evaluate the ranking results and weighting matrices. We found one weighting score matrix could increase FDR based q-values for a list of 47 genes with a score greater than 2. Our follow up functional enrichment tests revealed these genes were primarily involved in brain responses to ethanol and neural adaptations occurring with alcoholism.
These results, along with our experimental validation of specific genes in mice, C. elegans and Drosophila, suggest that a cross-species evidence-based approach is useful to identify candidate genes contributing to alcoholism.
为了研究遗传对酒精依赖、乙醇反应和相关特征的影响，已经使用了多种物种和实验设计。整合这些异质数据可用于生成经过排序的候选基因列表，以供进一步研究。
在这项研究中，我们使用三种微阵列实验在小鼠或人类中进行了独特的基于多物种证据的数据整合，这些实验生成了一个初始的酒精依赖（AD）相关基因列表、人类连锁和关联结果，以及与秀丽隐杆线虫和果蝇相关的基因集。然后，我们使用全基因组关联研究（GWAS）数据集的置换和错误发现率（FDR）分析，对合作酒精遗传研究（COGA）中的协作研究进行评估，以评估排名结果和加权矩阵。我们发现，一个加权评分矩阵可以提高 FDR 基于 q 值的评分大于 2 的 47 个基因列表。我们的后续功能富集测试表明，这些基因主要涉及大脑对乙醇的反应和与酒精中毒相关的神经适应。
这些结果，以及我们在小鼠、秀丽隐杆线虫和果蝇中对特定基因的实验验证，表明跨物种基于证据的方法可用于鉴定导致酒精中毒的候选基因。
