Smartwatch-Derived Biomarkers Signal Pace of Biological Aging
4 affiliations
- 1Center for Advanced Surgical & Interventional Technology (CASIT), Department of Surgery, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA
- 2Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA
- 3Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA
- 4Department of Psychiatry and Behavioral Health, Hackensack Meridian School of Medicine, Nutley, NJ 07110, USA
Abstract
Background:: Biological aging varies substantially among individuals of the same chronological age, yet biological aging biomarkers require biospecimen collection and laboratory processing, limiting scalability for repeated monitoring.
Objective:: This study evaluated whether consumer smartwatch-derived digital biomarkers are associated with the pace of biological aging, quantified using DunedinPACE, a biomarker that measures biological aging rates.
Methods:: Baseline data were analyzed from the Healthy Minds for Life study within the Precision Aging Network. Among 1305 enrolled participants, 621 community-dwelling adults aged 50–79 years had both DunedinPACE and smartwatch data available. Smartwatch-derived biomarkers were grouped into mobility, cardiorespiratory physiology, sleep, and physiological stress domains. Associations with DunedinPACE were examined using Spearman correlations and adjusted linear regression models.
Results:: Significant associations were observed across all four domains. Daily step count showed the strongest mobility-domain association with DunedinPACE (r = −0.25, p < 0.01). Mean sleep peripheral oxygen saturation showed the strongest sleep-domain association (r = −0.22, p < 0.01). Resting heart rate showed the strongest physiological stress-domain association (r = 0.24, p < 0.01). Adjusted regression models supported these findings, with lower daily mobility, poorer sleep oxygenation and efficiency, greater wake after sleep onset, and higher resting heart rate showing the most consistent associations with higher DunedinPACE values.
Conclusions:: Smartwatch-derived biomarkers captured a multidomain profile of accelerated biological aging characterized by lower mobility, poorer sleep health, and elevated physiological stress. Consumer wearables can provide low-burden, real-world indicators of biological vulnerability, although longitudinal studies are needed before clinical use.
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BibTeX
@article{khandan2026smartwatchderived,
title = {{Smartwatch-Derived Biomarkers Signal Pace of Biological Aging}},
author = {Aminreza Khandan and Jian Sun and Sofi Majidi and Mohammad Dehghan Rouzi and Sona Mahrokhi Khoushehmehr and Helen Lavretsky and Gary W. Small and Linda M. Ercoli and Bijan Najafi},
journal = {Digital health and innovation},
year = {2026},
month = jul,
doi = {10.3390/dhi1010005},
url = {https://europepmc.org/article/PMC/PMC13727975},
note = {CC BY},
}
RIS
TY - JOUR
TI - Smartwatch-Derived Biomarkers Signal Pace of Biological Aging
AU - Aminreza Khandan
AU - Jian Sun
AU - Sofi Majidi
AU - Mohammad Dehghan Rouzi
AU - Sona Mahrokhi Khoushehmehr
AU - Helen Lavretsky
AU - Gary W. Small
AU - Linda M. Ercoli
AU - Bijan Najafi
PY - 2026
DA - 2026/07/09
JO - Digital health and innovation
DO - 10.3390/dhi1010005
UR - https://europepmc.org/article/PMC/PMC13727975
AB - Background:: Biological aging varies substantially among individuals of the same chronological age, yet biological aging biomarkers require biospecimen collection and laboratory processing, limiting scalability for repeated monitoring. Objective:: This study evaluated whether consumer smartwatch-derived digital biomarkers are associated with the pace of biological aging, quantified using DunedinPACE, a biomarker that measures biological aging rates. Methods:: Baseline data were analyzed from the Healthy Minds for Life study within the Precision Aging Network. Among 1305 enrolled participants, 621 community-dwelling adults aged 50–79 years had both DunedinPACE and smartwatch data available. Smartwatch-derived biomarkers were grouped into mobility, cardiorespiratory physiology, sleep, and physiological stress domains. Associations with DunedinPACE were examined using Spearman correlations and adjusted linear regression models. Results:: Significant associations were observed across all four domains. Daily step count showed the strongest mobility-domain association with DunedinPACE (r = −0.25, p < 0.01). Mean sleep peripheral oxygen saturation showed the strongest sleep-domain association (r = −0.22, p < 0.01). Resting heart rate showed the strongest physiological stress-domain association (r = 0.24, p < 0.01). Adjusted regression models supported these findings, with lower daily mobility, poorer sleep oxygenation and efficiency, greater wake after sleep onset, and higher resting heart rate showing the most consistent associations with higher DunedinPACE values. Conclusions:: Smartwatch-derived biomarkers captured a multidomain profile of accelerated biological aging characterized by lower mobility, poorer sleep health, and elevated physiological stress. Consumer wearables can provide low-burden, real-world indicators of biological vulnerability, although longitudinal studies are needed before clinical use.
SN - 3042-9315
ER -