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Calibration of Toenail Metal Concentrations for Sample Mass Heterogeneity and Between-Batch Variability: The COMET

Roberto Pastor-Barriuso1,2, Enrique Gutiérrez-González3, Elena Varea-Jiménez1,4

  • 1National Center for Epidemiology, Carlos III Institute of Health (ISCIII), Madrid, Spain.

Environmental Health Perspectives
|March 7, 2025
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Summary

Toenail metal concentrations can now be accurately calibrated using a novel modeling approach that corrects for sample mass and laboratory batch variations. This method improves the reliability of toenail biomarkers in epidemiological studies for metal exposure assessment.

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Area of Science:

  • Environmental Health Sciences
  • Biomarker Development
  • Epidemiological Methods

Background:

  • Toenails serve as valuable biomarkers for long-term metal exposure in epidemiological research.
  • Accuracy of toenail metal analysis is often compromised by variations in sample mass and laboratory batch processing.

Purpose of the Study:

  • To introduce a novel statistical modeling approach for calibrating toenail metal concentrations.
  • To address systematic and random errors stemming from heterogeneous sample masses and laboratory batch variability.

Main Methods:

  • Developed a heteroscedastic spline mixed model to link sample mass and laboratory batch to metal concentrations.
  • The model accounts for mass-dependent bias, batch-specific random bias, and mass-related error variance heterogeneity.
  • Derived calibrated concentrations by removing extraneous variances and provided the R script COMET for implementation.

Main Results:

  • Sample mass and batch variability explained 26%-60% of the total variance in measured toenail metal concentrations across metals.
  • Calibrated concentrations revealed biased odds ratios in one-quarter of metal-cancer associations compared to uncalibrated data.
  • The COMET R script facilitates model fitting, variance component extraction, and concentration calibration.

Conclusions:

  • The proposed modeling approach effectively corrects toenail metal concentrations for sample mass and batch variability.
  • This methodology enhances the accuracy of toenail biomarkers for metal exposure assessment in epidemiological studies.
  • The model is adaptable for calibrating other biological specimens with similar sources of measurement error.