The 103,200-arm Acceleration Dataset in the UK Biobank Revealed a Landscape of Human Sleep Phenotypes

Overview

Journal Proc Natl Acad Sci U S A

Specialty Science

Date 2022 Mar 18

PMID 35302893

Authors

Machiko Katori

Shoi Shi

Koji L Ode

Yasuhiro Tomita

Hiroki R Ueda

Affiliations

Soon will be listed here.

Abstract

SignificanceHuman sleep phenotypes are diversified by genetic and environmental factors, and a quantitative classification of sleep phenotypes would lead to the advancement of biomedical mechanisms underlying human sleep diversity. To achieve that, a pipeline of data analysis, including a state-of-the-art sleep/wake classification algorithm, the uniform manifold approximation and projection (UMAP) dimension reduction method, and the density-based spatial clustering of applications with noise (DBSCAN) clustering method, was applied to the 100,000-arm acceleration dataset. This revealed 16 clusters, including seven different insomnia-like phenotypes. This kind of quantitative pipeline of sleep analysis is expected to promote data-based diagnosis of sleep disorders and psychiatric disorders that tend to be complicated by sleep disorders.

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