ENVHLTH-02: Climate-related exposures and the human exposome

Call goal: bring climate exposures (heat, air pollution, drought) into exposome research and show how they drive disease. Proposals must use long-term cohorts that link exposure data with medical and omics data and must apply AI/ML to the analysis.

What we contribute:

·       Methylation and transcriptomic exposure signatures, including epigenetic-ageing measures, as candidate exposome biomarkers.

·       Germline genetic susceptibility analysis to identify who is most vulnerable to climate exposures (gene-environment interaction).

·       Multi-omics integration linking genome, methylation and expression to biological pathways.

·       AI/ML pipelines for cohort-scale analysis of omics, exposure and real-world data.

·       Automated, FAIR-compliant data processing, ready for the IHEN Exposome Toolbox and Data Catalogue.

·       Long-read sequencing analysis that reads the genome and methylome from a single assay, reducing cost and sample use in large cohorts.

·       API-driven batch processing for cohort-scale sample volumes, integrated with partners' LIMS and data systems.

·       GDPR-aligned, EEA-hosted data handling under ISO/IEC 27001 and ISO 27799 for sensitive cohort data.

Why it strengthens the consortium: exposome consortia are usually led by environmental epidemiologists who hold exposure and cohort data but need molecular depth. Geneyx covers genome, methylation and RNA analysis plus the mandatory AI/ML activity in one partner, with automated pipelines that process cohort-scale samples reproducibly. This turns exposure-health associations into biological mechanisms and biomarkers, which the expected outcomes call for, and produces FAIR outputs ready for the IHEN toolbox and data catalogue, as the call requires.