Strengthening Causal Inference in Exposomics Research: Application of Genetic Data and Methods.

Area of Science:

• Environmental Health Sciences
• Genetics
• Epidemiology

Background:

• Exposome research measures environmental exposures but often lacks genetic data integration for robust causal inference.
• Heritability of many exposome-associated phenotypes highlights the need to incorporate genetic factors.

Purpose of the Study:

• To demonstrate how integrating genetic data strengthens causal inference in exposomics research.
• To address challenges in exposomics, including reverse causation, confounding, efficiency, replication, data integration, and tissue-specific effects.

Main Methods:

• Review and synthesis of methods integrating genetic data into exposomics study designs.
• Application of these methods to examples from biomarker and health behavior studies.

Main Results:

• Genetic data integration can address six key challenges in causal inference for exposomics.
• Technological and statistical advances facilitate this integration, requiring large sample sizes and data sharing.

Conclusions:

• Integrating genetic methods enhances causal inference in exposomics research.
• International collaboration and data sharing are crucial for advancing exposomics and understanding health effects across diverse populations and life courses.