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通过 Taxonomy3 分析揭示类风湿关节炎的新遗传见解,以促进药物发现。

Unveiling new genetic insights in rheumatoid arthritis for drug discovery through Taxonomy3 analysis.

机构信息

C4X Discovery Ltd, Manchester One, 53 Portland Street, Manchester, M1 3LD, UK.

出版信息

Sci Rep. 2024 Jun 19;14(1):14153. doi: 10.1038/s41598-024-64970-0.

Abstract

Genetic support for a drug target has been shown to increase the probability of success in drug development, with the potential to reduce attrition in the pharmaceutical industry alongside discovering novel therapeutic targets. It is therefore important to maximise the detection of genetic associations that affect disease susceptibility. Conventional statistical methods such as genome-wide association studies (GWAS) only identify some of the genetic contribution to disease, so novel analytical approaches are required to extract additional insights. C4X Discovery has developed Taxonomy3, a unique method for analysing genetic datasets based on mathematics that is novel in drug discovery. When applied to a previously published rheumatoid arthritis GWAS dataset, Taxonomy3 identified many additional novel genetic signals associated with this autoimmune disease. Follow-up studies using tool compounds support the utility of the method in identifying novel biology and tractable drug targets with genetic support for further investigation.

摘要

遗传支持药物靶点已被证明可提高药物开发成功率,有望降低制药行业的淘汰率,并发现新的治疗靶点。因此,最大限度地提高对影响疾病易感性的遗传关联的检测非常重要。传统的统计方法,如全基因组关联研究(GWAS),只能识别出疾病遗传贡献的一部分,因此需要新的分析方法来提取更多的见解。C4X Discovery 开发了 Taxonomy3,这是一种基于数学的独特的遗传数据集分析方法,在药物发现中是新颖的。当应用于之前发表的类风湿关节炎 GWAS 数据集时,Taxonomy3 确定了许多与这种自身免疫性疾病相关的新的遗传信号。使用工具化合物的后续研究支持该方法在识别具有遗传支持的新生物学和可治疗药物靶点方面的效用,以便进一步研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7034/11186831/e65c321583ed/41598_2024_64970_Fig1_HTML.jpg

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