Amyotrophic lateral sclerosis (ALS) is a rapidly progressive and fatal neurodegenerative disease with no cure and limited treatment options. Its biological causes remain poorly understood, largely due to the heterogeneity of the disease and the fragmented nature of available datasets. The Longitude Prize on ALS is a global 5-year challenge designed to accelerate the discovery of new therapeutic targets by using advanced AI and integrative analysis across large-scale genetic, molecular, neuroimaging, and clinical data.
To support this effort, we seek access to UK Biobank genomic, multi-omic, imaging, and clinical data. These data will be integrated with complementary ALS datasets (Project MinE, Answer ALS, ALS Compute) to create the most comprehensive resource assembled to date. Combining UK Biobank data with these disease-focused cohorts will substantially enhance statistical power, biological resolution, and the ability to detect subtle but meaningful disease mechanisms.
Our research aims to address three core health-related questions:
1) Which genetic variants and biological pathways contribute to ALS susceptibility, progression, and survival?
2) Can distinct ALS subtypes be identified through shared genomic, molecular, or clinical signatures?
3) Which genes, proteins, or molecular pathways represent promising therapeutic targets, and how can AI help prioritise them?
Key objectives include:
* Identifying genetic variants and molecular signatures associated with ALS mechanisms.
* Mapping disease-relevant pathways and cellular processes using integrative AI-driven analyses.
* Discovering and prioritising high-potential therapeutic targets suitable for downstream validation.
* Supporting precision medicine by characterising ALS subgroups with distinct biological profiles.
This work will generate new insights into ALS pathogenesis, provide a foundation for improved therapeutic development, and directly benefit the global ALS research community.