Automated feature extraction from population wearable device data identified novel loci associated with sleep and circadian rhythms

Abstract

Wearable devices have been increasingly used in research to provide continuous physical activity monitoring, but how to effectively extract features remains challenging for researchers. To analyze the generated actigraphy data in large-scale population studies, we developed computationally efficient methods to derive sleep and activity features through a Hidden Markov Model-based sleep/wake identification algorithm, and circadian rhythm features through a Penalized Multi-band Learning approach adapted from machine learning. Unsupervised feature extraction is useful when labeled data are unavailable, especially in large-scale population studies. We applied these two methods to the UK Biobank wearable device data and used the derived sleep and circadian features as phenotypes in genome-wide association studies. We identified 53 genetic loci with p<5×10 −8 including genes known to be associated with sleep disorders and circadian rhythms as well as novel loci associated with Body Mass Index, mental diseases and neurological disorders, which suggest shared genetic factors of sleep and circadian rhythms with physical and mental health. Further cross-tissue enrichment analysis highlights the important role of the central nervous system and the shared genetic architecture with metabolism-related traits and the metabolic system. Our study demonstrates the effectiveness of our unsupervised methods for wearable device data when additional training data cannot be easily acquired, and our study further expands the application of wearable devices in population studies and genetic studies to provide novel biological insights.

CARE: a novel wearable-derived feature linking circadian amplitude to human cognitive functions

“…The genome-wide significant locus was found to be associated with common executive functions [39], intelligence [40], and educational attainment [41]. Furthermore, results from the single-tissue and cross-tissue transcriptome-wide association analyses further confirmed the CARE's strong biological basis and highlighted the important role of circadian rhythms on the central nervous system, which is in line with previous findings from the other UK Biobank studies [60].…”

The Association between Circadian Syndrome and Frailty in US adults: a cross-sectional study of NHANES Data from 2007 to 2018

“…Hoyos et al noted marked circadian dysregulation in elderly patients with depression [ 29 ]. These psychological states can lead to reduced activity, nutritional imbalances, and other health complications, thereby fostering frailty.Lastly, CircS is closely associated with circadian rhythm disruption[ 25 , 30 ], defined as abnormalities in the biological clock’s variables over a 24-hour cycle [ 31 , 32 ]. Studies have shown that circadian rhythms are primarily regulated by the major biological clocks in the suprachiasmatic nucleus (SCN) of the hypothalamus [ 33 ].…”

Insights about circadian clock in glioma: From molecular pathways to therapeutic drugs

“…The circadian rhythm is an essential cyclic oscillation system generated by the endogenous circadian clock 11,12 . Essentially all mammalian organisms have developed circadian rhythms in order to synchronize social and physiological capabilities with explicit periodicity 13,14 .…”

“…10 The circadian rhythm is an essential cyclic oscillation system generated by the endogenous circadian clock. 11,12 Essentially all mammalian organisms have developed circadian rhythms in order to synchronize social and physiological capabilities with explicit periodicity. 13,14 The control center of this circadian rhythm is located in the suprachiasmatic nucleus (SCN) of the hypothalamus, which regulates the rhythm production of various physiological functions.…”