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

TL;DR

A new method called Taxonomy3 finds additional genetic signals in rheumatoid arthritis, offering new drug discovery opportunities.

Contribution

Taxonomy3, a novel mathematical approach, uncovers new genetic signals in rheumatoid arthritis beyond conventional GWAS.

Findings

Taxonomy3 identified novel genetic signals in rheumatoid arthritis not detected by traditional GWAS.

Follow-up studies confirmed the method's ability to reveal tractable drug targets with genetic support.

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.

Figures