Epigenetic clocks suggest accelerated aging in patients with isolated REM Sleep Behavior Disorder

Sleep onset time as a mediator in the association between screen exposure and aging: a cross-sectional study

Excessive screen exposure has become a significant health concern. This study investigates the impact of screen time on aging in middle-aged and elderly populations. Healthy working adults over 45 years old in Shanghai, China, underwent general and ocular examinations. Questionnaires collected demographics, medical history, and screen exposure details. Aging was assessed using the retinal age gap, defined as the difference between the retinal age predicted by deep learning algorithms based on fundus images and chronological age. Pathway analysis tested the mediation effect of sleep duration and onset time on the relationship between screen usage and retinal age gap. The retinal age gap increased with longer screen exposure, from 0.49 ± 3.51 years in the lowest tertile to 5.13 ± 4.96 years in the highest tertile (Jonckheere-Terpstra test, p < 0.001). Each additional hour of screen exposure accelerated the retinal age gap by 0.087 years (95% CI, 0.027, 0.148, p = 0.005) in the fully adjusted linear model. Sleep onset time mediated the impact of screen usage on the retinal age gap (indirect effect, β = 0.11; 95% CI 0.04-0.24). The impact of screen usage in a light-off environment on the retinal age gap was fully mediated by sleep onset time (indirect effect, β = 0.22; 95% CI 0.07-0.38), with the proportion being 100%. Our study identified a correlation between excessive screen time and a wider retinal age gap in middle-aged and elderly individuals, likely due to delayed sleep onset. To mitigate the adverse effects on the retina and aging, it is important to limit screen usage and avoid screens before bedtime.

Deciphering the role of immune cell composition in epigenetic age acceleration: Insights from cell-type deconvolution applied to human blood epigenetic clocks

Aging is a significant risk factor for various human disorders, and DNA methylation clocks have emerged as powerful tools for estimating biological age and predicting health-related outcomes. Methylation data from blood DNA has been a focus of more recently developed DNA methylation clocks. However, the impact of immune cell composition on epigenetic age acceleration (EAA) remains unclear as only some clocks incorporate partial cell type composition information when analyzing EAA. We investigated associations of 12 immune cell types measured by cell-type deconvolution with EAA predicted by six widely-used DNA methylation clocks in data from >10,000 blood samples. We observed significant associations of immune cell composition with EAA for all six clocks tested. Across the clocks, nine or more of the 12 cell types tested exhibited significant associations with EAA. Higher memory lymphocyte subtype proportions were associated with increased EAA, and naïve lymphocyte subtypes were associated with decreased EAA. To demonstrate the potential confounding of EAA by immune cell composition, we applied EAA in rheumatoid arthritis. Our research maps immune cell type contributions to EAA in human blood and offers opportunities to adjust for immune cell composition in EAA studies to a significantly more granular level. Understanding associations of EAA with immune profiles has implications for the interpretation of epigenetic age and its relevance in aging and disease research. Our detailed map of immune cell type contributions serves as a resource for studies utilizing epigenetic clocks across diverse research fields, including aging-related diseases, precision medicine, and therapeutic interventions.

DNA Methylation Age Acceleration as a Potential Biomarker for Early Onset of Rapid Eye Movement Sleep Behavior Disorder

Rapid eye movement sleep behavior disorder (RBD) is the strongest prodromal marker for α-synucleinopathies. The Horvath DNA methylation age (DNAm-age) is an epigenetic clock reflecting biological aging. We found an association of DNAm-age acceleration with RBD age at onset at baseline (N = 162, B = -0.68, standard error [SE] = 0.12, p = 2.59e-08) and follow-up (n = 45, B = -1.07, SE = 0.21, p = 9.73e-06). The result remained similar after accounting for genetic risk factors (eg, RBD polygenic risk score). On average, RBD patients with faster versus slow/normal epigenetic aging had a 5.2-year earlier phenoconversion, and the Cox regression analysis revealed a trend toward significance (n = 53, hazard ratio = 1.05, 95% confidence interval = 0.99-1.11, p = 0.06). Our findings suggest that DNAm-age acceleration is a potential biomarker for earlier RBD onset. ANN NEUROL 2023.