Genetic Epidemiology, Translational Neurogenomics, Psychiatric Genetics and Statistical Genetics Laboratories investigate the pattern of disease in families, particularly identical and non-identical twins, to assess the relative importance of genes and environment in a variety of important health problems.
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PMID
32805044
TITLE
Inference of causal relationships between sleep-related traits and 1,527 phenotypes using genetic data.
ABSTRACT
STUDY OBJECTIVE NlmCategory: OBJECTIVE
Sleep is essential for both physical and mental health, and there is a growing interest in understanding how different factors shape individual variation in sleep duration, quality and patterns, or confer risk for sleep disorders. The present study aimed to identify novel inferred causal relationships between sleep-related traits and other phenotypes, using a genetics-driven hypothesis-free approach not requiring longitudinal data.
METHODS NlmCategory: METHODS
Sleep is essential for both physical and mental health, and there is a growing interest in understanding how different factors shape individual variation in sleep duration, quality and patterns, or confer risk for sleep disorders. The present study aimed to identify novel inferred causal relationships between sleep-related traits and other phenotypes, using a genetics-driven hypothesis-free approach not requiring longitudinal data. We used summary-level statistics from genome-wide association studies and the latent causal variable (LCV) method to screen the phenome and infer causal relationships between seven sleep-related traits (insomnia, daytime dozing, easiness of getting up in the morning, snoring, sleep duration, napping, and morningness) and 1,527 other phenotypes.
RESULTS NlmCategory: RESULTS
Sleep is essential for both physical and mental health, and there is a growing interest in understanding how different factors shape individual variation in sleep duration, quality and patterns, or confer risk for sleep disorders. The present study aimed to identify novel inferred causal relationships between sleep-related traits and other phenotypes, using a genetics-driven hypothesis-free approach not requiring longitudinal data. We used summary-level statistics from genome-wide association studies and the latent causal variable (LCV) method to screen the phenome and infer causal relationships between seven sleep-related traits (insomnia, daytime dozing, easiness of getting up in the morning, snoring, sleep duration, napping, and morningness) and 1,527 other phenotypes. We identify 84 inferred causal relationships. Among other findings, connective tissue disorders increase insomnia risk and reduce sleep duration; depression-related traits increase insomnia and daytime dozing; insomnia, napping and snoring are affected by obesity and cardiometabolic traits and diseases; and working with asbestos, thinner, or glues may increase insomnia risk, possibly through an increased risk of respiratory disease or socio-economic related factors.
CONCLUSION NlmCategory: CONCLUSIONS
Sleep is essential for both physical and mental health, and there is a growing interest in understanding how different factors shape individual variation in sleep duration, quality and patterns, or confer risk for sleep disorders. The present study aimed to identify novel inferred causal relationships between sleep-related traits and other phenotypes, using a genetics-driven hypothesis-free approach not requiring longitudinal data. We used summary-level statistics from genome-wide association studies and the latent causal variable (LCV) method to screen the phenome and infer causal relationships between seven sleep-related traits (insomnia, daytime dozing, easiness of getting up in the morning, snoring, sleep duration, napping, and morningness) and 1,527 other phenotypes. We identify 84 inferred causal relationships. Among other findings, connective tissue disorders increase insomnia risk and reduce sleep duration; depression-related traits increase insomnia and daytime dozing; insomnia, napping and snoring are affected by obesity and cardiometabolic traits and diseases; and working with asbestos, thinner, or glues may increase insomnia risk, possibly through an increased risk of respiratory disease or socio-economic related factors. Overall, our results indicate that changes in sleep variables are predominantly the consequence, rather than the cause, of other underlying phenotypes and diseases. These insights could inform the design of future epidemiological and interventional studies in sleep medicine and research.
Sleep Research Society 2020. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.
DATE PUBLISHED
2020 Aug 17
HISTORY
PUBSTATUS PUBSTATUSDATE
received 2020/05/07
entrez 2020/08/18 06:00
pubmed 2020/08/18 06:00
medline 2020/08/18 06:00
AUTHORS
NAME COLLECTIVENAME LASTNAME FORENAME INITIALS AFFILIATION AFFILIATIONINFO
García-Marín LM García-Marín Luis M LM Faculty of Medicine, The University of Queensland, Brisbane QLD Australia.
Campos AI Campos Adrián I AI Faculty of Medicine, The University of Queensland, Brisbane QLD Australia.
Martin NG Martin Nicholas G NG Genetic Epidemiology Lab, QIMR Berghofer Medical Research Institute, Brisbane QLD Australia.
Cuéllar-Partida G Cuéllar-Partida Gabriel G Genetic Epidemiology Lab, QIMR Berghofer Medical Research Institute, Brisbane QLD Australia.
Rentería ME Rentería Miguel E ME Global Brain Health Institute, University of California, San Francisco, CA, USA.
INVESTIGATORS
JOURNAL
VOLUME:
ISSUE:
TITLE: Sleep
ISOABBREVIATION: Sleep
YEAR: 2020
MONTH: Aug
DAY: 17
MEDLINEDATE:
SEASON:
CITEDMEDIUM: Internet
ISSN: 1550-9109
ISSNTYPE: Electronic
MEDLINE JOURNAL
MEDLINETA: Sleep
COUNTRY: United States
ISSNLINKING: 0161-8105
NLMUNIQUEID: 7809084
PUBLICATION TYPE
PUBLICATIONTYPE TEXT
Journal Article
COMMENTS AND CORRECTIONS
GRANTS
GENERAL NOTE
KEYWORDS
KEYWORD
Sleep
causal inference
complex-traits
daytime dozing
epidemiology
genetics
insomnia
snoring
MESH HEADINGS
SUPPLEMENTARY MESH
GENE SYMBOLS
CHEMICALS
OTHER ID's