Exploratory untargeted metabolomics analysis reveals differences in metabolite profiles in pregnant people exposed vs. unexposed to E-cigarettes secondhand in the NYU children's health and environment study.

INTRODUCTION

Secondhand exposure to e-cigarettes represents a potential population health risk given e-cigarette's prevalence and their unknown health effects, particularly among vulnerable populations such as pregnant people.

OBJECTIVES

To explore metabolomic differences between pregnant people exposed vs. not exposed to secondhand e-cigarette aeresols, to identify possible biomarkers of exposure and metabolic pathways perturbed by e-cigarettes.

METHODS

Exposed participants (n = 19) from the NYU Children's Health and Environment Study were matched to unexposed participants (n = 57) at a 1:3 ratio on age, hospital of recruitment, and race/ethnicity. Early-pregnancy urine samples were analyzed via an untargeted metabolomics platform using reverse-phase liquid chromatography mass-spectrometry. Feature-exposure associations were estimated using conditional logistic regression to adjust for matching factors. A sensitivity analysis was conducted adjusting for secondhand tobacco exposure.

RESULTS

Among features enriched in the exposed group were flavonoids and flavor-related compounds including homoeriodictyol and naringenin-7-O-beta-D-glucuronide, 3-acetomidocoumarin, and guaiacol pentosylglucoside; synthetic drugs such as the endocannabinoid AM1172 and the stimulant alpha-PVP; and metabolites associated with lipid metabolism, including 2,4-undecadiene-8,10-diynoic acid isobutylamide, palmitamide, glycerol trihexanoate, and tetradecyl phosphonate. Among features negatively associated with exposure were xanthines.

CONCLUSION

This study is the first untargeted metabolomics study investigating metabolomic markers of e-cigarette exposure, including secondhand exposure, in a pregnant cohort. Despite this study's small size and exploratory nature, the results of this work suggest that flavoring components could be biomarkers for e-cigarette exposure, and that co-exposure to e-cigarettes and other drugs may be prevalent.