Sleep chart of biological ageing clocks in middle and late life.
Level 3 - non-randomized controlled study
Observational cohort analysis with survival models, mediation, and Mendelian randomization using UK Biobank data.
PubMed 42129562 · doi:10.1038/s41586-026-10524-5
What was done
The authors developed a 'Sleep Chart' evaluating the association between self-reported sleep duration and 23 biological aging clocks derived from in vivo imaging, plasma proteomics, and metabolomics across nine organ and brain systems in UK Biobank participants aged 37 to 84 years. They examined incident systemic disease risk, all-cause mortality, mediation pathways for late-life depression, genetic correlations, and Mendelian randomization for reverse causality.
What was found
A systemic U-shaped association was found between sleep duration and biological age gaps across all nine body/brain systems and three omics technologies. The lowest biological age gaps were observed at sleep durations between 6.4 and 7.8 hours, varying by organ and sex. Short (<6 h) and long (>8 h) sleep durations were associated with higher risks of systemic conditions (including depression and diabetes) and all-cause mortality compared to 6–8 hours. Aging clocks partially mediated the association between long sleep and late-life depression, whereas short sleep demonstrated a more direct relationship. Mendelian randomization did not show strong evidence that disease causally alters sleep, but could not completely rule out reverse causality. Exact numerical risk estimates were not reported in the abstract.
Why it matters
This study maps sleep duration against multi-system, multi-omics biological aging clocks, demonstrating that deviation from ~7 hours of sleep is linked to accelerated biological aging across multiple distinct organ systems.
Limits
Sleep duration was self-reported rather than objectively measured by actigraphy or polysomnography. Exact sample size and quantitative effect sizes (hazard ratios, confidence intervals) are omitted from the abstract. Despite Mendelian randomization analyses, residual confounding and reverse causality cannot be entirely excluded.