» Articles » PMID: 38834756

Circadian Rhythm Analysis Using Wearable-based Accelerometry As a Digital Biomarker of Aging and Healthspan

Overview
Journal NPJ Digit Med
Date 2024 Jun 4
PMID 38834756
Authors
Affiliations
Soon will be listed here.
Abstract

Recognizing the pivotal role of circadian rhythm in the human aging process and its scalability through wearables, we introduce CosinorAge, a digital biomarker of aging developed from wearable-derived circadian rhythmicity from 80,000 midlife and older adults in the UK and US. A one-year increase in CosinorAge corresponded to 8-12% higher all-cause and cause-specific mortality risks and 3-14% increased prospective incidences of age-related diseases. CosinorAge also captured a non-linear decline in resilience and physical functioning, evidenced by an 8-33% reduction in self-rated health and a 3-23% decline in health-related quality of life score, adjusting for covariates and multiple testing. The associations were robust in sensitivity analyses and external validation using an independent cohort from a disparate geographical region using a different wearable device. Moreover, we illustrated a heterogeneous impact of circadian parameters associated with biological aging, with young (<45 years) and fast agers experiencing a substantially delayed acrophase with a 25-minute difference in peak timing compared to slow agers, diminishing to a 7-minute difference in older adults (>65 years). We demonstrated a significant enhancement in the predictive performance when integrating circadian rhythmicity in the estimation of biological aging over physical activity. Our findings underscore CosinorAge's potential as a scalable, economic, and digital solution for promoting healthy longevity, elucidating the critical and multifaceted circadian rhythmicity in aging processes. Consequently, our research contributes to advancing preventive measures in digital medicine.

Citing Articles

Wearables in Chronomedicine and Interpretation of Circadian Health.

Gubin D, Weinert D, Stefani O, Otsuka K, Borisenkov M, Cornelissen G Diagnostics (Basel). 2025; 15(3).

PMID: 39941257 PMC: 11816745. DOI: 10.3390/diagnostics15030327.

References
1.
Xu Y, Wang X, Belsky D, McCall W, Liu Y, Su S . Blunted Rest-Activity Circadian Rhythm Is Associated With Increased Rate of Biological Aging: An Analysis of NHANES 2011-2014. J Gerontol A Biol Sci Med Sci. 2022; 78(3):407-413. PMC: 9977247. DOI: 10.1093/gerona/glac199. View

2.
Uno H, Cai T, Pencina M, DAgostino R, Wei L . On the C-statistics for evaluating overall adequacy of risk prediction procedures with censored survival data. Stat Med. 2011; 30(10):1105-17. PMC: 3079915. DOI: 10.1002/sim.4154. View

3.
Aubourg T, Demongeot J, Vuillerme N . Novel statistical approach for assessing the persistence of the circadian rhythms of social activity from telephone call detail records in older adults. Sci Rep. 2020; 10(1):21464. PMC: 7722744. DOI: 10.1038/s41598-020-77795-4. View

4.
Murabito J, Zhao Q, Larson M, Rong J, Lin H, Benjamin E . Measures of Biologic Age in a Community Sample Predict Mortality and Age-Related Disease: The Framingham Offspring Study. J Gerontol A Biol Sci Med Sci. 2017; 73(6):757-762. PMC: 5946832. DOI: 10.1093/gerona/glx144. View

5.
Doherty A, Jackson D, Hammerla N, Plotz T, Olivier P, Granat M . Large Scale Population Assessment of Physical Activity Using Wrist Worn Accelerometers: The UK Biobank Study. PLoS One. 2017; 12(2):e0169649. PMC: 5287488. DOI: 10.1371/journal.pone.0169649. View