Digital phenotyping by consumer wearables identifies sleep-associated markers of cardiovascular disease risk and biological aging.

Autor: Teo JX; 1SingHealth Duke-NUS Institute of Precision Medicine, National Heart Centre Singapore, Singapore, Singapore., Davila S; 1SingHealth Duke-NUS Institute of Precision Medicine, National Heart Centre Singapore, Singapore, Singapore.; 2Cardiovascular and Metabolic Disorders Program, Duke-NUS Medical School, Singapore, Singapore., Yang C; 3National Heart Research Institute Singapore, National Heart Centre, Singapore, Singapore., Hii AA; 3National Heart Research Institute Singapore, National Heart Centre, Singapore, Singapore., Pua CJ; 3National Heart Research Institute Singapore, National Heart Centre, Singapore, Singapore., Yap J; 4Department of Cardiology, National Heart Centre, Singapore, Singapore., Tan SY; 4Department of Cardiology, National Heart Centre, Singapore, Singapore., Sahlén A; 4Department of Cardiology, National Heart Centre, Singapore, Singapore.; 5Department of Medicine, Karolinska Institutet, Karolinska, Sweden., Chin CW; 4Department of Cardiology, National Heart Centre, Singapore, Singapore., Teh BT; 1SingHealth Duke-NUS Institute of Precision Medicine, National Heart Centre Singapore, Singapore, Singapore.; 6Cancer and Stem Biology Program, Duke-NUS Medical School, Singapore, Singapore.; 7Laboratory of Cancer Epigenome, Division of Medical Sciences, National Cancer Centre, Singapore, Singapore.; 8Institute of Molecular and Cell Biology, Agency for Science, Technology and Research, Singapore, Singapore.; 9Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore., Rozen SG; 1SingHealth Duke-NUS Institute of Precision Medicine, National Heart Centre Singapore, Singapore, Singapore.; 6Cancer and Stem Biology Program, Duke-NUS Medical School, Singapore, Singapore.; 10Centre for Computational Biology, Duke-NUS Medical School, Singapore, Singapore., Cook SA; 1SingHealth Duke-NUS Institute of Precision Medicine, National Heart Centre Singapore, Singapore, Singapore.; 2Cardiovascular and Metabolic Disorders Program, Duke-NUS Medical School, Singapore, Singapore.; 3National Heart Research Institute Singapore, National Heart Centre, Singapore, Singapore.; 11National Heart and Lung Institute, Imperial College London, London, UK.; 12MRC Clinical Sciences Centre, Imperial College London, London, UK., Yeo KK; 4Department of Cardiology, National Heart Centre, Singapore, Singapore., Tan P; 1SingHealth Duke-NUS Institute of Precision Medicine, National Heart Centre Singapore, Singapore, Singapore.; 6Cancer and Stem Biology Program, Duke-NUS Medical School, Singapore, Singapore.; 9Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore.; 13Biomedical Research Council, Agency for Science, Technology and Research, Singapore, Singapore., Lim WK; 1SingHealth Duke-NUS Institute of Precision Medicine, National Heart Centre Singapore, Singapore, Singapore.; 6Cancer and Stem Biology Program, Duke-NUS Medical School, Singapore, Singapore.
Jazyk: angličtina
Zdroj: Communications biology [Commun Biol] 2019 Oct 04; Vol. 2, pp. 361. Date of Electronic Publication: 2019 Oct 04 (Print Publication: 2019).
DOI: 10.1038/s42003-019-0605-1
Abstrakt: Sleep is associated with various health outcomes. Despite their growing adoption, the potential for consumer wearables to contribute sleep metrics to sleep-related biomedical research remains largely uncharacterized. Here we analyzed sleep tracking data, along with questionnaire responses and multi-modal phenotypic data generated from 482 normal volunteers. First, we compared wearable-derived and self-reported sleep metrics, particularly total sleep time (TST) and sleep efficiency (SE). We then identified demographic, socioeconomic and lifestyle factors associated with wearable-derived TST; they included age, gender, occupation and alcohol consumption. Multi-modal phenotypic data analysis showed that wearable-derived TST and SE were associated with cardiovascular disease risk markers such as body mass index and waist circumference, whereas self-reported measures were not. Using wearable-derived TST, we showed that insufficient sleep was associated with premature telomere attrition. Our study highlights the potential for sleep metrics from consumer wearables to provide novel insights into data generated from population cohort studies.
Competing Interests: Competing interestsThe authors declare no competing interests.
(© The Author(s) 2019.)
Databáze: MEDLINE
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