Completed Genetics & Molecular Biology Brain & Nervous System

A systematic approach to understanding the biology underpinning GWAS hits.

In plain English

AI plain-English summary

Hundreds of DNA variants linked to common diseases sit in regulatory "control switches" that no one has systematically decoded. Genome-wide association studies (GWAS) have pinpointed thousands of risk locations across the genome, but the vast majority fall in non-coding regions that regulate gene activity rather than in genes themselves. Only a handful of these signals have been traced to a specific biological mechanism, leaving the rest as statistical clues without a functional explanation. This project brings together leaders in GWAS, gene regulation, and disease biology to build a systematic pipeline for turning those statistical hits into concrete biological understanding. The team will develop and apply methods to link regulatory elements to the genes they control, then test them across a series of diseases chosen to represent increasingly complex challenges. If successful, this work could transform how researchers interpret GWAS results, turning thousands of orphan signals into testable hypotheses about disease mechanisms. That deeper understanding of fundamental biology is the necessary foundation for future diagnostics, drug targets, or risk prediction tools—though the project itself is focused on building that foundation, not on immediate clinical applications.

View original technical description
Genome-wide association studies have been extraordinarily successful in identifying DNA sequence variants associated with human diseases and phenotypes, with thousands of risk-loci identified across hundreds of traits. Each of these loci has the potential to reveal novel insights into human biology which can in turn underpin future translational advances. However GWAS loci frequently lie within regulatory sequences which complicates efforts to deliver actionable biological insights. To date, ch aracterisation of the molecular basis of predisposition to specific traits and diseases has been limited to a handful of the many thousands of non-coding GWAS signals. This lack of successful follow-up has impeded the GWAS approach from realising its huge potential. Recently, there have been major advances in our understanding of the regulatory architecture of the human genome, and, in particular, in the development of techniques for assessing the relationships between regulatory elements and t he genes they control. This application seeks funding for international leaders in GWAS, human gene regulation, human disease, and statistical genetics to exploit these recent advances by developing a systematic approach to the functional follow-up of GWAS loci and applying this across a series of diseases selected to represent increasingly complex challenges to biological inference.

View the original record at the funder ↗

Researchers

Douglas Higgs (EPMC Awardee)

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Original classification

Strategic Award - Science

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