Abstract
BACKGROUND: Serum neurofilament light chain (sNfL) has demonstrate significant clinical value in quantifying neuronal injury. Concurrently, extensive evidence has linked metal exposure to neurotoxic effects. However, the potential association between metal exposure and circulating sNfL levels remains uninvestigated in population-based study. OBJECTIVE: We applied a novel unsupervised clustering method (k-medoids) incorporating blood metals concentrations to stratify the general U. S. population into different exposure profiles to investigate the association between metal exposure and sNfL levels. METHODS: We analyzed data from the 2013-2014 NHANES cycle, and 513 participants were included in this study. Multivariate regression model, Bayesian kernel regression (BKMR) and quantile g-computation (QGC) were used to assess the relationship between individual and mixed metal exposure and sNfL. RESULTS: Multivariate regression revealed a significant positive association between blood cadmium concentrations and elevated sNfL levels in the overall population (β = 0.115, 95%CI: 0.039-0.190, p = 0.003). Through exposure pattern recognition using unsupervised k-medoids clustering, participants were stratified into distinct exposure subgroups: a high-exposure cluster (n = 326) and a low-exposure (n = 187) reference group. BKMR modeling within the high-exposure group identified cadmium as the dominant contributor to sNfL elevation, with stronger effects in male participants (β = 0.201, 95%CI: 0.087-0.315) and individuals with BMI > 25 kg/m(2) (β = 0.178, 95%CI: 0.062-0.294). CONCLUSION: This study provides systematic evidence that blood cadmium concentration can be used as the predominant driver of early neuronal injury, as objectively quantified through sNfL biomarker.