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对 16 种精神疾病和物质使用表型的遗传调控基因表达及共表达网络作用的分析。

An analysis of genetically regulated gene expression and the role of co-expression networks across 16 psychiatric and substance use phenotypes.

机构信息

Translational Neurogenomics Laboratory; QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.

Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.

出版信息

Eur J Hum Genet. 2022 May;30(5):560-566. doi: 10.1038/s41431-022-01037-6. Epub 2022 Feb 25.

Abstract

Genome-wide association studies (GWASs) have identified thousands of risk loci for psychiatric and substance use phenotypes, however the biological consequences of these loci remain largely unknown. We performed a transcriptome-wide association study of 10 psychiatric disorders and 6 substance use phenotypes (GWAS sample size range, N = 9725-807,553) using expression quantitative trait loci data from 532 prefrontal cortex samples. We estimated the correlation of genetically regulated expression between phenotype pairs, and compared the results with the genetic correlations. We identified 393 genes with at least one significant phenotype association, comprising 458 significant associations across 16 phenotypes. Overall, the transcriptomic correlations for phenotype pairs were significantly higher than the respective genetic correlations. For example, attention deficit hyperactivity disorder and autism spectrum disorder, both childhood developmental disorders, had significantly higher transcriptomic correlation (r = 0.84) than genetic correlation (r = 0.35). Finally, we tested the enrichment of phenotype-associated genes in gene co-expression networks built from human prefrontal cortex samples. Phenotype-associated genes were enriched in multiple gene co-expression modules and the implicated modules contained genes involved in mRNA splicing and glutamatergic receptors, among others. Together, our results highlight the utility of gene expression data in the understanding of functional gene mechanisms underlying psychiatric disorders and substance use phenotypes.

摘要

全基因组关联研究(GWAS)已经确定了数千个与精神疾病和物质使用表型相关的风险基因座,但这些基因座的生物学后果在很大程度上仍然未知。我们使用来自 532 个前额叶皮层样本的表达数量性状基因座数据,对 10 种精神疾病和 6 种物质使用表型进行了全转录组关联研究(GWAS 样本量范围,N=9725-807,553)。我们估计了表型对之间遗传调控表达的相关性,并将结果与遗传相关性进行了比较。我们确定了 393 个至少有一个显著表型关联的基因,包括 16 个表型中的 458 个显著关联。总体而言,表型对之间的转录组相关性明显高于各自的遗传相关性。例如,注意缺陷多动障碍和自闭症谱系障碍,这两种儿童发育障碍,其转录组相关性(r=0.84)明显高于遗传相关性(r=0.35)。最后,我们测试了表型相关基因在基于人类前额叶皮层样本构建的基因共表达网络中的富集情况。表型相关基因在多个基因共表达模块中富集,所涉及的模块包含涉及 mRNA 剪接和谷氨酸能受体的基因等。总之,我们的研究结果强调了基因表达数据在理解精神疾病和物质使用表型背后的功能基因机制方面的效用。

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