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全面的文献数据挖掘分析揭示了与自闭症谱系障碍功能相关的广泛遗传网络。

Comprehensive literature data-mining analysis reveals a broad genetic network functionally associated with autism spectrum disorder.

机构信息

Department of Magnetic Resonance Imaging, Shanxi Province People's Hospital, Taiyuan, Shanxi 030001, P.R China.

Department of Genomics Research, Elsevier R&D Solutions, Elsevier Inc., Rockville, MD 20852, USA.

出版信息

Int J Mol Med. 2018 Nov;42(5):2353-2362. doi: 10.3892/ijmm.2018.3845. Epub 2018 Aug 28.

Abstract

Previous studies have indicated that genetic factors are the predominate cause of Autism spectrum disorder (ASD). Nevertheless, to the best of our knowledge, to date no systematic study has summarized these data and provided an objective, complete list of genes with demonstrated associations with ASD. The present study included a literature data mining analysis of >2,064 articles including publications from January 2000 to April 2016, which identified 488 ASD target genes. Gene set enrichment analysis (GSEA), sub‑network enrichment analysis (SNEA) and network connectivity analysis (NCA) were conducted to assess the functional profile and pathogenic significance of these genes. A total of 2 literature metrics were proposed to prioritize the curated ASD genes with specific significance. This approach resulted in the development of an ASD genetic database. Subsequent analysis indicated that 391 of the 488 genes were enriched in 97 biological pathways (P<1x10‑8), demonstrating significant functional associations with each other. The majority of these curated ASD genes also serve significant roles in the pathogenesis of other neuropsychiatric disorders. These results suggest that the genetic causes of ASD are within a large network composed of functionally‑associated genes. The genetic database, together with the metric scores developed in the present study, provides a basis for future biological/genetic modeling in the field.

摘要

先前的研究表明,遗传因素是自闭症谱系障碍(ASD)的主要原因。然而,据我们所知,迄今为止,尚无系统的研究对这些数据进行总结,并提供一份具有 ASD 关联的客观、完整的基因列表。本研究对 2000 年 1 月至 2016 年 4 月期间发表的超过 2064 篇文章进行了文献数据挖掘分析,确定了 488 个 ASD 靶基因。进行了基因集富集分析(GSEA)、子网络富集分析(SNEA)和网络连通性分析(NCA),以评估这些基因的功能特征和发病意义。提出了 2 种文献指标来优先考虑具有特定意义的经过验证的 ASD 基因。这种方法开发了一个 ASD 遗传数据库。随后的分析表明,在 488 个基因中,有 391 个基因富集在 97 个生物途径中(P<1x10-8),彼此之间存在显著的功能关联。这些经过验证的 ASD 基因中的大多数在其他神经精神疾病的发病机制中也具有重要作用。这些结果表明,ASD 的遗传原因存在于一个由功能相关基因组成的大网络中。遗传数据库以及本研究中开发的指标评分,为该领域未来的生物/遗传建模提供了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/38d0/6192781/31ae54872190/IJMM-42-05-2353-g00.jpg

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