Sensitivity of Urinary Toxicant Co-Exposure Patterns to Demographic Adjustment and Marker Type: A Methodological
Basant K Puri1,2, Jean A Monro3
1Cambridge Advanced Research, Cambridge CB21, UK.
Toxics
|July 28, 2026
Summary
Principal component analysis (PCA) of environmental toxicant patterns in patients is sensitive to demographic adjustments and variable selection. Robust, stable exposure signatures were not identified, cautioning against interpreting transient patterns without validation.
Area of Science:
- Environmental Health
- Toxicology
- Biostatistics
Background:
- Patients with environmentally related conditions often have complex, multi-toxicant exposures.
- The stability of these toxicant patterns when adjusted for demographics is not well understood.
Purpose of the Study:
- To assess the sensitivity of principal component analysis (PCA) structures to demographic confounding and variable composition in patients with environmentally related conditions.
- To evaluate the stability of multivariate toxicant patterns under demographic adjustment.
Main Methods:
- Principal component analysis (PCA) was applied to nine urinary biomarkers from 551 patients.
- Analyses were performed on raw data and residuals adjusted for age and sex, using Varimax and Promax rotations.
- The impact of including both exposure and response variables was examined.
Main Results:
- The solvent/industrial toxicant cluster (xylene, styrene metabolites) showed the most stability across analyses.
- Component structures were sensitive to preprocessing, with herbicide (2,4-dichlorophenoxyacetic acid) clustering shifting after demographic adjustment.
- Mixing exposure and response variables (e.g., tiglylglycine) led to model violations (Heywood cases).
- Cumulative variance explained was modest (KMO ≈ 0.52), indicating weak inter-biomarker correlations.
Conclusions:
- PCA-derived toxicant patterns in heterogeneous clinical data are vulnerable to demographic confounding, variable selection, and marker type.
- The study does not support the identification of robust, demographically stable clustering patterns in this cohort.
- Caution is advised when interpreting transient clustering patterns as definitive exposure signatures without rigorous validation.
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