Abstract TU151: The independent and joint effects of toxic elements on cardiovascular disease risk: A case-control study in the ELSA-Brasil cohort.

Introduction: Toxic metal exposures have been linked to cardiovascular diseases (CVD), yet most studies are cross-sectional and single-exposure focused. We investigated the independent and joint effects of arsenic (As), cadmium (Cd), lead (Pb), and mercury (Hg) on incident CVD in a large prospective cohort, using advanced mixture modeling and multi-media biomarker (MMB) assessments. Methods: We conducted a nested case-control study within the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) cohort, including 176 incident CVD cases and 7,810 controls. Baseline serum and urine samples were analyzed for toxic metals. We used conditional logistic regression to investigate associations between toxic metal levels and incident CVD risk. Mixture effects were assessed using quantile g-computation (QGC), weighted quantile sum (WQS) regression, and MMB modeling. Results: Higher urinary levels of Hg (OR: 1.82; 95% CI: 1.19-2.80) was associated with increased CVD risk. No consistent associations were found for serum metals. Urinary metal mixtures showed robust positive associations with CVD in both QGC and WQS models. MMB analyses identified urinary Hg as the strongest contributor to CVD risk across all modeling techniques. Nonlinear relationships were observed for urinary Cd and Hg. Conclusions: Urinary levels of Hg, and heavy metals as a mixture were associated with higher CVD risk. These findings support the use of advanced exposure modeling and call for greater attention to environmental metal exposures, particularly in low- and middle-income countries.