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The relationship between mixed exposure to blood metal and serum neurofilament light chain levels in the general U.S. population

An unsupervised clustering approach

Bibliographic Data

ID22075873
AuthorsJiyu Nie (Jinan University), Wen Lin (0000-0001-6155-7951, Guangdong Academy of Medical Sciences), Lin Wen (0000-0003-4921-6147), Zhentian Lai (Jinan University), Chuhang Lin (0009-0007-7324-2712, Jinan University), Haiyin Li (0000-0002-1242-8261, Jinan University), Jing Zhang (0000-0002-6431-9286, Jinan University), Shen Xie (0000-0002-7962-6975, Jinan University), Xiaosong Ben (0000-0003-1155-7202, Guangdong Academy of Medical Sciences, corresponding author), Chunxia Jing (0000-0001-7333-4181, Jinan University, corresponding author)
Year2025
Volume13
Pages1516879-1516879
Publication date2025-07-30
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2025.1516879
PMID40809763
OpenAlexW4412765882
LanguageEN
References cited45

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

Environmental health · Multivariate statistics · Population · Statistics · Aluminum toxicity and tolerance in plants and animals · Heavy Metal Exposure and Toxicity · Mathematics · Medicine · Occupational exposure and asthma · Internal Medicine

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