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Published on: June 21, 2015
Urinary heavy metal and trace element mixtures in chronic kidney disease: associations and implications for potential
Sisi Xie1, Julien Vaucher1,2, Maïwenn Perrais3,4
1Department of Medicine, Internal Medicine, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland.
Introduction:
Chronic kidney disease (CKD) is a growing public health challenge, yet impaired kidney function may substantially alter urinary biomarker profiles, complicating their interpretation. We aimed to investigate the associations between urinary element concentrations and prevalent CKD, and to explore whether impaired kidney function and altered urinary excretion may contribute to reverse causality in the interpretation of urinary biomarkers.
Methods:
We conducted a cross-sectional analysis of urinary element mixtures and prevalent CKD among 6,192 adults (51.7% female; mean age 52.4 ± 10.7 years). Associations between urinary element concentrations and prevalent CKD were evaluated using logistic regression, restricted cubic spline models, and three mixture modeling approaches, including Bayesian kernel machine regression, weighted quantile sum regression, and quantile g-computation.
Results:
Participants with CKD exhibited lower urinary concentrations of selenium, molybdenum, cadmium, mercury, lead, and thallium, whereas urinary zinc concentrations were higher. Non-linear associations were observed for several elements. Across multiple mixture models, higher combined urinary element concentrations were consistently associated with lower odds of prevalent CKD. Cadmium, mercury, selenium, and thallium contributed most strongly to these inverse associations, whereas zinc showed a positive contribution.
Discussion:
These findings are unlikely to reflect protective effects and may instead reflect impaired urinary excretion resulting from kidney dysfunction. Our findings suggest that urinary elements in CKD reflect not only exposure but also disease-related alterations in renal excretory function. These findings highlight the potential for reverse causality when interpreting urinary elements as biomarkers or predictors of kidney outcomes.
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