Genes with de novo mutations are shared by four neuropsychiatric disorders discovered from NPdenovo database.
Genes with de novo mutations are shared by four neuropsychiatric disorders discovered from NPdenovo database.
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从 NPdenovo 数据库中发现的四种神经精神疾病共有具有从头突变的基因
DOI：
10.1038/mp.2015.40
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发表时间：
2016-02
影响因子：
11
通讯作者：
Wu J
中科院分区：
文献类型：
--
作者：
Li J;Cai T;Jiang Y;Chen H;He X;Chen C;Li X;Shao Q;Ran X;Li Z;Xia K;Liu C;Sun ZS;Wu J
目前，许多关于神经精神疾病的研究已经利用大规模的基于trio的全外显子组测序（WES）和全基因组测序（WGS）来鉴定许多从头突变（DNM）。在这里，我们从WES/WGS的36项研究中检索了17 104个DNM，来自4种神经精神疾病的3555个三重奏：自闭症谱系障碍，癫痫性脑病，智力残疾和精神分裂症，以及未受影响的兄弟姐妹（对照）。在排除非外显子变异后，我们集中在3334个外显子DNM上，以评估它们与这些疾病的相关性。我们的研究结果显示，与对照组相比，所有四种疾病的先证者中DNM的患病率更高（P< 1.3× 10− 7）。DNM频率升高主要是由功能丧失/有害的单核苷酸变异和移码插入缺失（即极端突变，P< 4.5× 10− 5）。通过对这些“极端”突变的广泛注释，我们优先考虑了这四种疾病中的764个候选基因。基因本体论、microRNA靶标和转录因子靶标的联合分析揭示了神经精神疾病病理学中候选基因的共同生物学过程和非编码调控元件。此外，加权基因共表达网络分析人类皮层特异性新皮层表达数据显示，候选基因收敛于8个具有特定层富集和生物过程特征的共享模块。此外，我们发现53个候选基因与一种以上的疾病相关（P< 0.000001），这表明这些疾病可能有共同的遗传病因。特别是，SCN 2A基因的DNM经常发生在所有四种疾病中。最后，我们构建了一个免费的NPdenovo数据库，它提供了一个全面的目录中确定的DNMs神经精神疾病。
Currently, many studies on neuropsychiatric disorders have utilized massive trio-based whole-exome sequencing (WES) and whole-genome sequencing (WGS) to identify numerous de novo mutations (DNMs). Here, we retrieved 17 104 DNMs from 3555 trios across four neuropsychiatric disorders: autism spectrum disorder, epileptic encephalopathy, intellectual disability and schizophrenia, in addition to unaffected siblings (control), from 36 studies by WES/WGS. After eliminating non-exonic variants, we focused on 3334 exonic DNMs for evaluation of their association with these diseases. Our results revealed a higher prevalence of DNMs in the probands of all four disorders compared with the one in the controls (P< 1.3× 10− 7). The elevated DNM frequency is dominated by loss-of-function/deleterious single-nucleotide variants and frameshift indels (that is, extreme mutations, P< 4.5× 10− 5). With extensive annotation of these ‘extreme’mutations, we prioritized 764 candidate genes in these four disorders. A combined analysis of Gene Ontology, microRNA targets and transcription factor targets revealed shared biological process and non-coding regulatory elements of candidate genes in the pathology of neuropsychiatric disorders. In addition, weighted gene co-expression network analysis of human laminar-specific neocortical expression data showed that candidate genes are convergent on eight shared modules with specific layer enrichment and biological process features. Furthermore, we identified that 53 candidate genes are associated with more than one disorder (P< 0.000001), suggesting a possibly shared genetic etiology underlying these disorders. Particularly, DNMs of the SCN2A gene are frequently occurred across all four disorders. Finally, we constructed a freely available NPdenovo database, which provides a comprehensive catalog of the DNMs identified in neuropsychiatric disorders.