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From Environmental Evidence to Biomarker Selection: A Structured Decision-Support Process for Human Biomonitoring
Elisa Bustaffa1, Cristina Aprea2, Alessandro Barbieri3
1Institute of Clinical Physiology, National Research Council (IFC-CNR), Via Moruzzi 1, 56124 Pisa, Italy.
This study outlines a structured approach for designing Human Biomonitoring (HBM) studies in complex contaminated environments. It details a multi-level biomarker strategy to assess health risks from environmental exposures.
Area of Science:
- Environmental Health Sciences
- Toxicology
- Biomarker Research
Background:
- Human Biomonitoring (HBM) assesses exposure to environmental contaminants and early biological changes.
- Complex contaminated sites require structured processes for exposure assessment and risk evaluation.
Purpose of the Study:
- To describe the methodological process for designing the INSINERGIA_RT HBM study in Tuscany, Italy.
- To present a structured approach for designing HBM studies in complex environmental settings.
- To integrate environmental, toxicological, epidemiological, and public health data for biomarker selection.
Main Methods:
- The study design integrated environmental evidence, toxicological knowledge, and epidemiological priorities.
- A hierarchical model organizes biomarkers reflecting biological response stages.
- A multi-level approach includes oxidative stress, inflammation, organ damage markers, and integrative indicators like telomere length and metabolomics.
Main Results:
- The manuscript presents a methodological framework, not biomonitoring results.
- The approach is illustrated by an ongoing HBM study in Livorno and Piombino.
- Biomarkers are categorized by biological response levels: upstream pathways, early effects, and cumulative responses.
Conclusions:
- The described structured approach can guide the design of HBM studies in complex contaminated areas.
- A multi-level, mechanistic biomarker strategy is proposed for comprehensive exposure and health risk assessment.
- The INSINERGIA_RT study design provides a practical example of applying this framework.
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