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全基因组关联研究(GWAS)汇总数据和神经祖细胞药物诱导基因表达谱在精神科药物优先级分析中的应用。

Application of GWAS summary data and drug-induced gene expression profiles of neural progenitor cells in psychiatric drug prioritization analysis.

作者信息

Li Xiangyi, Xue Chao, Zhu Zheng, Yu Xuegao, Yang Qi, Cui Liqian, Li Miaoxin

机构信息

Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, Guangdong, China.

Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Guangzhou, 510080, Guangdong, China.

出版信息

Mol Psychiatry. 2025 Jan;30(1):111-121. doi: 10.1038/s41380-024-02660-z. Epub 2024 Jul 13.

DOI:10.1038/s41380-024-02660-z
PMID:39003413
Abstract

Common psychiatric disorders constitute one of the most substantial healthcare burdens worldwide. However, drug development in psychiatry remains hampered partially due to the lack of approaches to estimating drugs that can simultaneously modulate the expression of a nontrivial fraction of disease susceptibility genes. We proposed a new drug prioritization strategy under the framework of our previously proposed phenotype-associated tissues estimation approach (DESE) by investigating the drugs' selective perturbation effect on disease susceptibility genes. Based on the genome-wide association study summary data and drug-induced gene expression profiles of neural progenitor cells, we applied this strategy to prioritize candidate drugs for schizophrenia, depression and bipolar I disorder and identified several known therapeutic drugs among the top-ranked drug candidates. Also, our results revealed that the disease susceptibility genes involved in the selective gene perturbation analysis were enriched with many biologically sensible function terms and interacted with known therapeutic drugs. Our results suggested that selective gene perturbation analysis could be a promising starting point to prioritize biologically sensible drug candidates under the "one drug, multiple targets" paradigm for the drug development of common psychiatric disorders.

摘要

常见精神疾病是全球范围内最沉重的医疗负担之一。然而,精神病学领域的药物研发仍然受到一定阻碍,部分原因是缺乏能够同时调节相当一部分疾病易感基因表达的药物评估方法。我们在先前提出的表型相关组织估计方法(DESE)框架下,通过研究药物对疾病易感基因的选择性扰动效应,提出了一种新的药物优先排序策略。基于全基因组关联研究汇总数据和神经祖细胞的药物诱导基因表达谱,我们将该策略应用于精神分裂症、抑郁症和双相I型障碍的候选药物优先排序,并在排名靠前的候选药物中鉴定出几种已知的治疗药物。此外,我们的结果表明,参与选择性基因扰动分析的疾病易感基因富含许多具有生物学意义的功能术语,并与已知治疗药物相互作用。我们的结果表明,在常见精神疾病药物研发的“一药多靶”范式下,选择性基因扰动分析可能是优先选择具有生物学意义的候选药物的一个有前景的起点。

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本文引用的文献

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Drug targeting in psychiatric disorders - how to overcome the loss in translation?精神疾病的药物靶向治疗——如何克服转化中的损失?
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g:Profiler-interoperable web service for functional enrichment analysis and gene identifier mapping (2023 update).用于功能富集分析和基因标识符映射的可互操作网络服务(2023 更新)。
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Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis.
多民族全基因组关联分析确定类风湿关节炎的新遗传机制。
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Mapping genomic loci implicates genes and synaptic biology in schizophrenia.基因组定位研究提示精神分裂症的发病与基因及突触生物学有关。
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The Genetic Architecture of Depression in Individuals of East Asian Ancestry: A Genome-Wide Association Study.东亚裔人群抑郁症的遗传结构:全基因组关联研究。
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Evaluation of connectivity map shows limited reproducibility in drug repositioning.连通性映射评估显示药物重定位的重现性有限。
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Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology.对超过 40000 例双相情感障碍病例的全基因组关联研究为其潜在生物学机制提供了新的见解。
Nat Genet. 2021 Jun;53(6):817-829. doi: 10.1038/s41588-021-00857-4. Epub 2021 May 17.
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Exploiting the GTEx resources to decipher the mechanisms at GWAS loci.利用 GTEx 资源来破解 GWAS 位点的机制。
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