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基因分析——自闭症和癌症共享基因的通路和特征。

GeneAnalytics Pathways and Profiling of Shared Autism and Cancer Genes.

机构信息

Departments of Psychiatry, Behavioral Sciences & Pediatrics, University of Kansas Medical Center, Kansas City, KS 66160, USA.

出版信息

Int J Mol Sci. 2019 Mar 7;20(5):1166. doi: 10.3390/ijms20051166.

Abstract

Recent research revealed that autism spectrum disorders (ASD) and cancer may share common genetic architecture, with evidence first reported with the gene. There are approximately 800 autism genes and 3500 genes associated with cancer. The VarElect phenotype program was chosen to identify genes jointly associated with both conditions based on genomic information stored in GeneCards. In total, 138 overlapping genes were then profiled with GeneAnalytics, an analysis pathway enrichment tool utilizing existing gene datasets to identify shared pathways, mechanisms, and phenotypes. Profiling the shared gene data identified seven significantly associated diseases of 2310 matched disease entities with factors implicated in shared pathology of ASD and cancer. These included 371 super-pathways of 455 matched entities reflecting major cell-signaling pathways and metabolic disturbances (e.g., CREB, AKT, GPCR); 153 gene ontology (GO) biological processes of 226 matched processes; 41 GO molecular functions of 78 matched functions; and 145 phenotypes of 232 matched phenotypes. The entries were scored and ranked using a matching algorithm that takes into consideration genomic expression, sequencing, and microarray datasets with cell or tissue specificity. Shared mechanisms may lead to the identification of a common pathology and a better understanding of causation with potential treatment options to lessen the severity of ASD-related symptoms in those affected.

摘要

最近的研究表明,自闭症谱系障碍(ASD)和癌症可能具有共同的遗传结构,首先报道的证据是 基因。大约有 800 个自闭症基因和 3500 个与癌症相关的基因。选择 VarElect 表型程序来根据存储在 GeneCards 中的基因组信息识别与两种情况都相关的基因。然后,使用 GeneAnalytics 对 138 个重叠基因进行分析,这是一种利用现有基因数据集识别共享途径、机制和表型的分析途径富集工具。对共享基因数据进行分析,确定了与 ASD 和癌症共同病理相关的七个显著相关疾病,涉及 2310 个匹配疾病实体的因素。其中包括 371 个超级途径(455 个匹配实体),反映了主要的细胞信号通路和代谢紊乱(例如,CREB、AKT、GPCR);226 个匹配过程的 153 个基因本体论(GO)生物学过程;78 个匹配功能的 41 个 GO 分子功能;232 个匹配表型的 145 个表型。使用考虑基因组表达、测序和具有细胞或组织特异性的微阵列数据集的匹配算法对条目进行评分和排名。共享机制可能导致共同病理学的识别,并更好地理解因果关系,从而为减轻受影响者与 ASD 相关症状的严重程度提供潜在的治疗选择。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9a/6429377/d0939e2818f4/ijms-20-01166-g001.jpg

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