A recent study found that exposure to certain per- and polyfluoroalkyl substances may be associated with shorter sleep duration and increased sleep disturbance in young adults.

In the study, published in Environmental Advances, researchers provided new evidence linking these persistent environmental pollutants to adverse sleep outcomes. The cross-sectional and longitudinal study included 136 young adults (mean age = 19 years at baseline) recruited from the Southern California Children's Health Study between 2014 and 2018. A subset of 76 participants was reassessed between 2020 and 2022.

The study population was predominantly Hispanic (58%), with 67% having parents' education above high school. Participants slept on average 8.04 (standard deviation [SD] = 1.49) hours at baseline and 6.86 (SD = 1.16) hours at follow-up. The average sleep disturbance score at follow-up was 48.02 (SD = 7.44) and the average sleep impairment score was 50.36 (SD = 9.07).

Plasma concentrations of per- and polyfluoroalkyl substances (PFAS) were measured using liquid chromatography–high-resolution mass spectrometry. Seven PFAS were quantified: perfluorodecanoic acid (PFDA), perfluorononanoic acid (PFNA), perfluorohexane sulfonate (PFHxS), Perfluorooctane sulfonate (PFOS), perfluorooctanoate (PFOA), perfluoroheptane sulfonic acid (PFHpS), and perfluoropentane sulfonic acid (PFPeS).

Sleep outcomes included self-reported sleep duration at baseline and follow-up, as well as sleep disturbance and sleep-related impairment measured at follow-up using validated PROMIS instruments.

Multiple linear regression models assessed cross-sectional associations between PFAS exposures (in tertiles) and sleep outcomes, adjusting for relevant covariates. Longitudinal analysis employed generalized estimating equations to examine associations between baseline PFAS and sleep duration over time.

The researchers employed a multifaceted approach, combining epidemiologic analysis with computational toxicology and proteomics data to investigate potential mechanisms. Computational toxicology analysis utilized the Comparative Toxicogenomics Database and Toxicology in the 21st Century database to identify potential genetic links between PFAS and sleep disorders.

Among the key findings were:

• One tertile increase in PFDA at baseline was associated with 0.39 hours less nightly sleep (95% confidence interval [CI] = –0.73 to –0.05).
• At follow-up, PFHxS and PFOA were associated with 0.39 (95% CI = –0.72 to –0.05) and 0.32 (95% CI = –0.63 to –0.01) hours less sleep, respectively.
• PFOS was associated with higher sleep disturbance scores (β = 2.99, 95% CI = 0.67–5.31) and sleep-related impairment scores (β = 3.35, 95% CI = 0.51–6.20) at follow-up.
• PFOS was suggestively associated with insufficient sleep (< 7 hours) at follow-up (odds ratio [OR] = 2.25, 95% CI = 1.04–4.89, FDR-P value: .28).

The researchers identified several proteins that may mediate the relationship between PFAS and sleep outcomes:

• Corticosteroid 11-beta-dehydrogenase isozyme 1 (HSD11B1) mediated 37% of the total effect of PFOA on sleep duration at follow-up.
• Cathepsin B (CTSB) mediated the association between PFOS and sleep disturbance.
• Interleukin-6 receptor subunit beta (IL6ST), dickkopf-related protein 3 (DKK3), ectonucleoside triphosphate diphosphohydrolase 5 (ENTPD5), scavenger receptor cysteine-rich domain-containing group B protein (SSC4D), and tyrosine-protein kinase receptor (TYRO3) all mediated the association between PFOS and sleep-related impairment.

Computational toxicology analysis suggested that PFOS, PFOA, and PFDA may be linked to sleep-wake disorders through genes including IL1B, POMC, BHLHE41, and CHRNB2. These PFAS were also associated with GO terms related to circadian rhythm.

Toxicity screening indicated that PFDA, PFOA, and PFOS increased activity of the human Nrf2 transcriptional factor (a biomarker for oxidative stress) and decreased activity of the human estrogen receptor alpha transcriptional factor.

The study's strengths included its prospective design, multi-omics approach, and focus on young adults. Limitations included the relatively small sample size and potential for residual confounding.

The authors declared having no competing interests.