Toward capturing the exposome variability: Household co-exposure patterns in the LIFE Study Jake Chung Feb 2017

Questions 1. Is it possible to characterize the density of correlations of environmental exposures? 2. How are the correlations of exposures driven by shared environment (e.g., within household) vs. the individual? Aims 1. Explore the co-exposure patterns of chemical biomarkers in couples 2. Examine the influence of familial relatedness in correlation of exposures

Main findings Comparing females and males: 1. Highly similar co-exposure patterns between the male and female groups 2. Higher within-class Spearman correlations for persistent organic chemicals (PCBs, PBDEs, organochlorine pesticides) than other classes (abs. median rs: 0.25 - 0.5 vs 0.05 - 0.25) Comparing couples to above: 1. Abs. median rs of all chemical classes are lower 2. Most significant drop for persistent organics with abs. median rs in range of 0.1 - 0.25 3. In addition, interquartile ranges of correlation of all chemical classes are lower

Design 501 pairs of couples 128 serum and urinary biomarkers In 13 different chemical classes Persistent organics, non-persistent organics, and metals etc

Biomarkers measured in this study

Method 1. Load multiply imputed chemical data to R (provided by NICHD) 2. Obtain residuals from regressing chemicals against covariates (serum total lipids or urine creatinine) Linear model: scale(log10(biomarker+1)) ~ scale(covariate) Adjusted for total lipids: PBDEs, PCBs, OCPs Adjusted for creatinine: phytoestrogen, phthalates, phenols, parabens, paracetamols, metals, metalloid Unadjusted: PFASs, cotinine, blood metals 3. Calculate rs matrices with the residuals for males, females and couples Get final rs estimates by averaging across imputed frames (Rubin’s method) Get final p values from permutation tests

Two generally positively correlated clusters 1) PCBs, OCPs, and PFASs 2) phytoestrogens, phthalates, phenols, anti-microbials, paracetamols, urine metals and metalloids Left: females; Right: males. Interactive plots: https://www.ocf.berkeley.edu/~mkchung/corr/021517/

Similar co-exposure patterns between females and males (red line represents perfect agreement)

Similar density curves between females and males

Weaker co-exposure patterns in couples! Females Males Interactive plots: https://www.ocf.berkeley.edu/~mkchung/corr/021517/

Female chemicals are weak predictors to the chemicals in male

Persistent organic chemicals have higher within-class correlations Left: females; Right: males. Higher resolution plots: https://www.ocf.berkeley.edu/~mkchung/corr/021517/

Lower within-class correlations in couples Females Males

Interpretation Co-exposure patterns of biomarkers were found in: Both between and within chemical classes With stronger within-class correlation for persistent organic chemicals (PCBs, PBDEs, OCPs) Analytical challenges for exposome-wide association study: p value correction, multicollinearity Damping of correlations in couple group Chemical correlations were weaker in the couples than females and males, especially for persistent organics Non-home environment could be a significant source of exposure variability? Conditions to use indoor dust as surrogate of exposure assessment?

Higher PBDEs correlations within family members Young children (2-8 years old; N = 67) Parents of young children (<55 years old; N = 90), Older adults (≥55 years old; N = 59)