【广东会GDH基因检测】使用网络模型揭示精神疾病的发病机制

中国神经病基因检测公司排名详解

讨化神经科疾病个性化药物研究路径做了备注《Genes (Basel)》在. 2021 Jul 20;12(7):1101.发表了一篇题目为《使用网络模型揭示精神疾病的发病机制》肿瘤靶向药物治疗基因检测临床研究文章。该研究由Yanning Zuo, Don Wei, Carissa Zhu, Ormina Naveed, Weizhe Hong, Xia Yang等完成。促进了肿瘤的正确治疗与个性化用药的发展，进一步强调了基因信息检测与分析的重要性。

神经疾病遗传阻断及正确治疗临床研究内容关键词：

精神科心理科疾病用药指导基因检测临床应用结果

精神疾病是一种复杂的脑部疾病，具有高度的遗传异质性，影响着全世界数百万人。尽管精神遗传学取得了进展，但精神疾病的潜在致病机制在很大程度上仍然难以捉摸，这阻碍了新的合理疗法的发展。越来越多的证据表明，复杂疾病的遗传学可以通过全基因视角来观察，这涉及在高度互连的网络中对基因进行背景化。因此，应用基于网络的多组学整合方法可以为精神疾病的病理生理学提供新的视角。在这篇综述中，我们首先概述了精神遗传学的贼新进展，并强调了将分子关联转化为机制见解方面的差距。然后，我们概述了网络方法，并回顾了网络方法在精神疾病研究中的先前应用。贼后，我们描述了这种方法在多组织、多组学方法中的潜力，并总结了采用多种网络方法的未来方向。多组学；网络建模；精神疾病；系统生物学。

神经及精神疾病及其并发征、合并征国际数据库描述：

Psychiatric disorders are complex brain disorders with a high degree of genetic heterogeneity, affecting millions of people worldwide. Despite advances in psychiatric genetics, the underlying pathogenic mechanisms of psychiatric disorders are still largely elusive, which impedes the development of novel rational therapies. There has been accumulating evidence suggesting that the genetics of complex disorders can be viewed through an omnigenic lens, which involves contextualizing genes in highly interconnected networks. Thus, applying network-based multi-omics integration methods could cast new light on the pathophysiology of psychiatric disorders. In this review, we first provide an overview of the recent advances in psychiatric genetics and highlight gaps in translating molecular associations into mechanistic insights. We then present an overview of network methodologies and review previous applications of network methods in the study of psychiatric disorders. Lastly, we describe the potential of such methodologies within a multi-tissue, multi-omics approach, and summarize the future directions in adopting diverse network approaches.Keywords: integrative genomics; multi-omics; network modeling; psychiatric disorders; systems biology.