What is GAINs?

Applying our technology to genome-wide association study ("GWAS") data

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We have developed a new and unique capability based upon our network biology expertise and technology.

By using our proprietary platform technology to analyse GWAS data we can provide a way to bridge the gap between genetic susceptibility and disease mechanism.

Such analysis can identify potential intervention strategies, therapies and diagnostics.

Our novel methods uncover actionable insights from GWAS data


 

What is GWAS data?

GWAS is a population genetics technique that identifies variants in single nucleotide pairs ("SNPs") whose frequencies vary with disease traits.

As a data source, GWAS bridges genotype to phenotype. It can reveal 'natural' experiments in humans. It is is only functional -omics data available for some dissues/tissues. It is therefore a very valuable data source. However, the path from GWAS to disease biology is not straightforward. 

Despite the huge financial investment and the volume of data generated from GWAS very little has been delivered in terms of actionable understanding. 


 

GAINs addresses multiple failings in current GWAS analysis:

- A tight linkage between individual DNA variability and disease causation has not emerged: Network biology provides one way to integrate polygenic influences in a mechanistic way

- Hypertension, diabetes, cardiovascular disease, depression, many cancers and obesity are linked to hundreds of gene variants that even collectively do not explain the full variance of a disease: Network integration via GAINs analysis can detect evidence for disease mechanism driven by multiple variants

- Many if not most gene variants uncovered do not map on to a plausible biological mechanism: Our GAINs analysis of variants clearly maps to plausible biological mechanisms

- GWAS has failed to find actionable relationships between polymorphisms and disease: GAINs analysis applied to GWAS data has enabled the identification of actionable insights by using network biology to link polymorphisms to disease.

 


How and why GAINs works

 

GAINS process.png GAINs brings clarity to GWAS data and generates actionable insight

 

Application of GAINs to Parkinson's Disease

We have analysed GWAS data from patients and confirmed the centrality of pathophysiology known to be associated with Parkinson's Disease.

We have uncovered mechanistic insights completely new to the condition.

The output is immediately amenable to both network-driven and classic target-driven drug discovery.

We are seeking collaboration partners to exploit the potential of this innovative technology in all complex diseases.