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This summary is machine-generated.

Understanding environmental exposures is key to health, but data is complex. Developing semantic standards with ontologies is crucial for analyzing the external exposome and its impact on health outcomes.

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Area of Science:

  • Environmental Health
  • Bioinformatics
  • Ontology Engineering

Background:

  • Individual health results from a complex interplay of genetics and environmental exposures.
  • Genetics account for only about 10% of health conditions, highlighting the critical role of environmental factors and gene-environment interactions.
  • Systematic exploration of the external exposome is essential for understanding disease causes and prevention, yet data heterogeneity poses significant challenges.

Purpose of the Study:

  • To review existing ontologies for the external exposome.
  • To identify limitations in current external exposome ontologies.
  • To advocate for ontology-driven semantic standards to address data heterogeneity in exposome research.

Main Methods:

  • Conducted a systematic review of existing ontologies relevant to the external exposome.
  • Analyzed identified ontologies for their coverage of spatiotemporal characteristics and integration with conceptual frameworks like the socioecological model and social determinants of health.

Main Results:

  • Identified only four relevant ontologies for the external exposome.
  • Found that existing ontologies often neglect spatiotemporal data characteristics.
  • Observed that current ontologies are typically developed in isolation from broader health frameworks.

Conclusions:

  • Ontology-driven semantic standards are essential for harmonizing heterogeneous external exposome data.
  • Future health outcomes research requires integrating multi-domain and multi-scale data (genome, phenome, exposome) with diverse conceptual frameworks.
  • Addressing limitations in current ontologies is vital for advancing exposome science and its application in public health.