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

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作者
Justyna Kozlowska [1 ]
Neil Humphryes-Kirilov [1 ]
Anastasia Pavlovets [1 ]
Martin Connolly [1 ]
Zhana Kuncheva [1 ]
Jonathan Horner [1 ]
Ana Sousa Manso [1 ]
Clare Murray [1 ]
J. Craig Fox [1 ]
Alun McCarthy [1 ]
机构
[1] C4X Discovery Ltd,
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10.1038/s41598-024-64970-0
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摘要
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.
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