Work

Linking Place-Based Exposures and Genomics to understand Human Phenotypes

Year: 2026

Type: preprint

Abstract: Evidence that the environment has a greater impact on health than genomics alone is driving a need to understand exposure impacts and their interactions at scale. Geospatially tagged exposure data, such as for weather, climate and pollution, along with social factors associated with neighbourhoods such as distance to healthcare or community-wide socioeconomic status, can be used to build a picture of an individual's exposure conditions over time. Referred to as “place-based” exposures, these data, often collected by governmental agencies, provide opportunities to retrospectively explore environmental exposure impacts on human cohorts. This requires longitudinal location data from cohort participants (commonly residential address history) to build a clear picture of exposure histories and associations with phenotypes at the relevant latency. However, this raises concerns regarding confidentiality as a person's residential location is often not shareable as it is personal data and the linked, place-based data can potentially identify individuals within research datasets. This creates challenges in linking genomics and health data to relevant place-based exposure information. In addition, a lack of standards for representing exposures linked to cohort participants prevents cross-comparison and reproducible data analysis. This results in missed opportunities to understand exposure-genome impacts accurately and at scale. We call for the development of community-led standards to enable accurate exposure-genome-phenome analysis.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.21877290