New Genetic Insights in Rheumatoid Arthritis using Taxonomy3(R), a Novel method for Analysing Human Genetic Data
Kozlowska, J.; Humphryes-Kirilov, N.; Pavlovets, A.; Connolly, M.; Kuncheva, Z.; Horner, J.; Sousa Manso, A.; Murray, C.; Fox, J. C.; McCarthy, A.
Show 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 used to analyse 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 a new method Taxonomy3(R) for analysing genetic datasets based on novel mathematics. When applied to a previously published rheumatoid arthritis GWAS dataset, Taxonomy3(R) 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.