Multi-media biomarkers: Integrating information to improve lead exposure assessment.

ABSTRACT: Exposure assessment traditionally relies on biomarkers that measure chemical concentrations in individual biological media (i.e., blood, urine, etc.). However, chemicals distribute unevenly among different biological media; thus, each medium provides incomplete information about body burden. We propose that machine learning and statistical approaches can create integrated exposure estimates from multiple biomarker matrices that better represent the overall body burden, which we term multi-media biomarkers (MMBs). We measured lead (Pb) in blood, urine, hair and nails from 251 Italian adolescents aged 11-14 years from the Public Health Impact of Metals Exposure (PHIME) cohort. We derived aggregated MMBs from the four biomarkers and then tested their association with Wechsler Intelligence Sca

SUBMITTER: Levin-Schwartz Y 

PROVIDER: S-EPMC7167344 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature