Urinary Paraben Concentrations and Associations with the Periconceptional Urinary Metabolome: Untargeted and Targeted Metabolomics Analyses of Participants from the Early Pregnancy Study

Background: Parabens, found in everyday items from personal care products to foods, are chemicals with endocrine-disrupting activity, which has been shown to influence reproductive function. Objectives: This study investigated whether urinary concentrations of methylparaben, propylparaben, or butylparaben were associated with the urinary metabolome during the periconceptional period, a critical window for female reproductive function. Changes to the periconceptional urinary metabolome could provide insights into the mechanisms by which parabens could impact fertility. Methods: Urinary paraben concentrations were measured in paired pre- and postconception urine samples from 42 participants in the Early Pregnancy Study, a prospective cohort of 221 women attempting to conceive. We performed untargeted and targeted metabolomics analyses using ultrahigh-performance liquid chromatography quadrupole time-of-flight mass spectrometry. We used principal component analysis, orthogonal partial least-squares discriminant analysis, and permutation testing, coupled with univariate statistical analyses, to find metabolites associated with paraben concentration at the two time points. Potential confounders were identified with a directed acyclic graph and used to adjust results with multivariable linear regression. Metabolites were identified using fragmentation data. Results: Seven metabolites were associated with paraben concentration (variable importance to projection score >1, false discovery rate–corrected q-value<0.1). We identified four diet-related metabolites to the Metabolomics Standards Initiative (MSI) certainty of identification level 2, including metabolites from smoke flavoring, grapes, and olive oil. One metabolite was identified to the class level only (MSI level 3). Two metabolites were unidentified (MSI level 4). After adjustment, three metabolites remained associated with methylparaben and propylparaben, two of which were diet-related. No metabolomic markers of endocrine disruption were associated with paraben concentrations. Discussion: This study identified novel relationships between urinary paraben concentrations and diet-related metabolites but not with metabolites on endocrine-disrupting pathways, as hypothesized. It demonstrates the feasibility of integrating untargeted metabolomics data with environmental exposure information and epidemiological adjustment for confounders. The findings underscore a potentially important connection between diet and paraben exposure, with applications to nutritional epidemiology and dietary exposure assessment. https://doi.org/10.1289/EHP12125


Table of Contents
Supplemental Material.ProteoWizard settings for conversion of .rawfiles to .mzMLfiles.
Table S1.Results of unsupervised PCA of metabolomics data from urine samples provided by 42 participants in the Early Pregnancy Study.
Table S2.Results of 200 random permutation tests (permutation by paraben concentration category), and difference between the original OPLS-DA R 2 and the R 2 calculated from the permutation test, from urine samples provided by 42 participants in the Early Pregnancy Study.
Table S3.Change in metabolite intensity associated with urinary paraben concentration and other covariates in multivariable linear regression models for 42 participants in the Early Pregnancy Study.
Table S4.Intensity of catechol sulfate and pregnenolone sulfate (specific gravity-adjusted, natural log transformed) across paraben concentration categories, stratified by sample time point, for 42 participants in the Early pregnancy Study.

Figure S3a.
Comparison of catechol sulfate intensity (specific gravity-adjusted, natural logtransformed) across paraben concentration categories, stratified by sample time point, for 42 participants in the Early Pregnancy Study.Data used to construct these figures can be found in Table S4.

Figure S3b
. Comparison of urinary pregnenolone sulfate intensity (specific gravity-adjusted, natural log-transformed) across paraben concentration categories, stratified by sample time point, for 42 participants in the Early Pregnancy Study.Data used to construct these figures can be found in Table S4.
Figure S3b.Comparison of urinary pregnenolone sulfate intensity (specific gravity-adjusted, natural log-transformed) across paraben concentration categories, stratified by sample time point, for 42 participants in the Early Pregnancy Study.Data used to construct these figures can be found in Table S5.

Figure S2a .
Figure S2a.PCA plots of HILIC data and urinary paraben concentration category, stratified by sample time point (conception cycle, early pregnancy).

Figure S2b .
Figure S2b.PCA plots of RPLC data and urinary paraben concentration category, stratified by sample time point (conception cycle, early pregnancy).

Figure
Figure S2a.PCA plots of HILIC data and urinary paraben concentration category, stratified by sample time point (conception cycle, early pregnancy)

Table S1 .
Days of the week represented in 84 pooled urine samples, each comprised of 3 daily specimens, from 42 participants in the Early Pregnancy Study

Table S2 .
Results of unsupervised PCA of metabolomics data from urine samples provided by 42 participants in the Early Pregnancy Study Note: R 2 indicates how much variance in the data is explained by the model, and Q 2 indicates the predictive ability of the model.For a visual representation of this table, please see FigureS2.PCA, principal components analysis; PC, principal component; HILIC, hydrophilic interaction chromatography; RPLC, reversed-phase liquid chromatography.

Table S3 .
Results of 200 random permutation tests (permutation by paraben concentration category), and difference between the original OPLS-DA R 2 and the R 2 calculated from the permutation test, from urine samples provided by 42 participants in the Early Pregnancy Study

HILIC data RPLC data Sample time point Paraben concentration comparison (n) Original R 2 Y Permuted R 2 Y Difference in R 2 Y a Permuted Q 2 Original R 2 Y Permuted R 2 Y Difference in R 2 Y a Permuted Q 2
The permutation test is used to cross-validate OPLS-DA results.It randomly assigns sample concentration category, correlating the Q 2 and R 2 Y of the original data with the distribution of Q 2 and R 2 Y after 200 iterations of random permutation by concentration category.R 2 Y indicates group separation by concentration category, and Q 2 indicates predictive performance of the model.If the difference between R 2 Y and Q 2 is >0.3, this suggests overfitting of the model.Permutation models with a Q 2 intercept close to or below 0 indicate poorly fitting models when concentration category is randomly assigned; in turn, this suggests that the original OPLS-DA model accurately assigns concentration category.Paraben concentration categories of low, medium, and high are defined in Table1.OPLS-DA, orthogonal partial least-squares discriminant analysis; HILIC, hydrophilic interaction chromatography; RPLC, reversed-phase liquid chromatography; L, low concentration category; M, medium concentration category; H, high concentration category.
Note:a Difference in R 2 Y = original R 2 Y − permuted R 2 Y

Table S4 .
Change in metabolite intensity associated with urinary paraben concentration and other covariates in multivariable linear regression models for 42 participants in the Early Pregnancy Study

Table S4 ,
continued.FiguresS2a and S2b.PCA plots of urinary paraben concentration category, stratified by sample time point (conception cycle, early pregnancy), in 42 women from the Early Pregnancy Study.FigureS2aincludes HILIC data, and FigureS2bincludes RPLC data.Data used to construct these figures can be found in TableS2.PCA, principal components analysis; PC, principal component; HILIC, hydrophilic interaction chromatography; RPLC, reversed-phase liquid chromatography; var, variance.