Toward Capturing the Exposome: Biomarker Variability and Co-exposure Patterns in the Shared Environment

摘要

Background: Variation in exposure levels in the population is dependent on time, location, and sex. One specific factor that may influence exposure co-variations is shared household; specifically, covariation of exposures may be influenced by both shared household (shared environment) and unique environment of the individuals (not attributable to shared household). Objective: We aimed to examine the influence of shared household in correlation of endocrine disrupting chemical (EDC) exposures systematically in couples living together. Methods: We leveraged a cohort with 501 couples and measured 128 serum and urinary EDCs from 13 different classes and estimated 1) sex-specific difference between genders; 2) variance explained by shared household; and 3) Spearman's rank correlation coefficient (r_s) for females, males, and couples. Results: After accounting for household, sex only influenced some biomarkers of the exposome, such as polyfluoroalkyl substances. On the other hand, shared household explained less than 20% of the total variance in 11 EDC classes. A "dense" correlational co-occurrence of the exposome was observed in males and females separately, especially among the persistent organic EDCs (e.g. polychlorinated biphenyls). For both females and males, within-class correlations of persistent organic EDCs had an absolute median r_s ranging between 0.29 to 0.45. In contrast, all classes had that below 0.21 in couples. Conclusions: Chemical co-exposure patterns, especially for persistent organic EDCs, can be dense, but similar in males versus females separately. However, although individuals spend a significant time at home, shared environment generally only accounted for less than 20% of the co-variation in levels of all markers of the exposome, and understanding the individual co-exposure patterns is a necessary step to capture the variations. In addition, the correlations between exposures have analytical implications for environment-wide association analyses.