Development and application of meta-analysis in environmental health research

The Adverse Outcome Pathway (AOP) framework is a foundational approach in environmental pollutant research, encompassing the detrimental effects of pollutants across biological levels from molecules to populations. Toxicogenomics (TGx), which integrates omics technologies with toxicology, plays a crucial role in AOPs by elucidating the relationships between chemical exposure, molecular initiating events (MIEs), and key events (KEs) across various biological levels using animal and cell model-based data. However, since some MIEs (e.g. changes in specific enzyme activities or receptor binding/activation) cannot be confirmed by omics data alone, TGx data must be integrated with classical enzymatic assays, receptor function analyses, and related methods when constructing AOPs to ensure comprehensive, accurate identification of MIEs and their associated KEs. Epidemiology examines the links between environmental exposures, KEs and adverse outcomes (AOs) in human populations, contributing to the understanding of population-level disease outcomes. With the advent of big data, both epidemiology and TGx studies have generated substantial datasets. To synthesize these extensive data resources, meta-analysis emerges as a robust tool, effectively integrating environmental epidemiology and TGx data to provide a coherent and strong evidence base, revealing the correlative and causative relationships between environmental pollutants and human health outcomes. This review focuses on the role of meta-analysis in environmental health research, particularly on integrating environmental health epidemiology and TGx data. Additionally, we explore the challenges in applying meta-analysis and discuss future directions. Our aim is to provide researchers with a comprehensive understanding of meta-analysis methods and processes in environmental health research, encouraging wider adoption and further development of this analytical approach.