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. 2024 Oct:17:100585.
doi: 10.1016/j.envadv.2024.100585. Epub 2024 Sep 17.

Per-and polyfluoroalkyl substances and disrupted sleep: mediating roles of proteins

Shiwen Li  1 , Jesse A Goodrich  1 , Jiawen Carmen Chen  1 , Elizabeth Costello  1 , Emily Beglarian  1 , Jiawen Liao  1 , Tanya L Alderete  2 , Damaskini Valvi  3 , Brittney O Baumert  1 , Sarah Rock  1 , Sandrah P Eckel  1 , Rob McConnell  1 , Frank D Gilliland  1 , Zhanghua Chen  1 , David V Conti  1 , Lida Chatzi  1 , Max Aung  1
Affiliations

Per-and polyfluoroalkyl substances and disrupted sleep: mediating roles of proteins

Shiwen Li et al. Environ Adv. 2024 Oct.

Abstract

Background: Per-and polyfluoroalkyl substances (PFAS) contamination may disrupt sleep through disrupted metabolic and immune functions. The study aims to investigate the association and potential mechanism between PFAS and sleep.

Methods: We included 136 young adults recruited between 2014-2018 and 76 were re-assessed between 2020-2022. Additional 8 participants only had complete data between 2020-2022. Plasma PFAS (PFOS, PFOA, PFHxS, PFHpS, PFPeS, PFNA, PFDA) were measured at both visits using liquid-chromatography high-resolution mass spectrometry. Plasma proteins were measured by Olink® Explore 384 Cardiometabolic and Inflammation Panel I. Sleep duration was self-reported at both visits along with follow-up sleep disturbance and sleep-related impairment using validated instruments. We utilized multiple linear regression to explore the association between individual PFAS (in tertile) and these sleep outcomes. PFAS associated with sleep outcomes were subjected to computational toxicology analysis using the Comparative Toxicogenomics Database and Toxicology in the 21st Century database to identify potential genetic links between them. Mediation analysis using proteomic data was then performed to confirm the findings from computational toxicology analysis.

Results: At baseline, one tertile increase in PFDA was associated with 0.39 (95 % CI: 0.05, 0.73) hours of shorter nightly sleep duration, and, at follow-up, PFHxS and PFOA were associated with 0.39 (95 % CI: 0.05, 0.72) and 0.32 (95 % CI: 0.01, 0.63) hours shorter sleep duration, respectively. One tertile increase in PFOS exposure was associated with a 2.99-point increase in sleep disturbance scores (95 % CI: 0.67, 5.31) and a 3.35-point increase in sleep-related impairment scores (95 % CI: 0.51, 6.20). Computational toxicology and mediation analyses identified potential mediating roles for several proteins in the PFAS-sleep associations, including 11-beta-dehydrogenase isozyme 1 (HSD11B1), cathepsin B (CTSB) and several immune system-related proteins.

Conclusion: Future large scale epidemiological and mechanistic studies should confirm our findings and test effect measure modification of the associations by age.

Keywords: PFAS; Proteomics; Sleep.

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Conflict of interest statement

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1.
Fig. 1.
Analytic workflow.
Fig. 2.
Fig. 2.
Point estimates and 95 % confidence interval of the mean difference in nightly sleep duration (hours) per tertile increase in PFAS measured baseline (A) or follow-up (B). *We controlled baseline covariates (race/ethnicity, sex, parental education, age, physical activity, cigarette smoking, alcohol drinking, HEI) when assessing outcomes measured at baseline, and time-fixed covariates (race/ethnicity, sex, parental education) and covariates (age, physical activity, cigarette smoking, alcohol drinking, HEI) measured at follow-up for outcomes measured at follow-up. We additionally controlled the time to follow-up visits when assessing sleep outcomes measured at follow-up.
Fig. 3.
Fig. 3.
Point estimates and 95 % confidence intervals of the odds ratio of insufficient sleep (less than 7 h) per tertile increase in PFAS measured baseline (A) or follow-up (B). *We controlled baseline covariates (race/ethnicity, sex, parental education, age, physical activity, cigarette smoking, alcohol drinking, HEI) when assessing outcomes measured at baseline, and time-fixed covariates (race/ethnicity, sex, parental education) and covariates (age, physical activity, cigarette smoking, alcohol drinking, HEI) measured at follow-up for outcomes measured at follow-up. We additionally controlled the time to follow-up visits when assessing sleep outcomes measured at follow-up.
Fig. 4.
Fig. 4.
Point estimates and 95% confidence intervals of mean difference in sleep disturbance (A) and sleep-related impairment scores (B) per tertile increase in PFAS at follow-up. *We controlled time-fixed covariates (race/ethnicity, sex, parental education) and covariates (age, physical activity, cigarette smoking, alcohol drinking, HEI) measured at follow-up for outcomes measured at follow-up.
Fig. 5.
Fig. 5.
Screening of potential genetic target shared by PFAS identified in the epidemiological study and sleep-wake disorder in the comparative toxicogenomics database (CTD).
Fig. 6.
Fig. 6.
Toxicity of selected PFAS by cell type labeled with assay target. *Each point represents individual assay and is labeled with its assay target **Activity level is measured using the point-of-departure method to describe the toxicity of the PFAS (value range of log10(M)*(−1))
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