Associations of sleep and circadian phenotypes with COVID-19 susceptibility and hospitalization : an observational cohort study based on the UK Biobank and a two-sample Mendelian randomization study
© The Author(s) 2022. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissionsoup.com..
STUDY OBJECTIVES: Sleep and circadian phenotypes are associated with several diseases. The present study aimed to investigate whether sleep and circadian phenotypes were causally linked with coronavirus disease 2019 (COVID-19)-related outcomes.
METHODS: Habitual sleep duration, insomnia, excessive daytime sleepiness, daytime napping, and chronotype were selected as exposures. Key outcomes included positivity and hospitalization for COVID-19. In the observation cohort study, multivariable risk ratios (RRs) and their 95% confidence intervals (CIs) were calculated. Two-sample Mendelian randomization (MR) analyses were conducted to estimate the causal effects of the significant findings in the observation analyses. Odds ratios (ORs) and the corresponding 95% CIs were calculated and compared using the inverse variance weighting, weighted median, and MR-Egger methods.
RESULTS: In the UK Biobank cohort study, both often excessive daytime sleepiness and sometimes daytime napping were associated with hospitalized COVID-19 (excessive daytime sleepiness [often vs. never]: RR = 1.24, 95% CI = 1.02-1.5; daytime napping [sometimes vs. never]: RR = 1.12, 95% CI = 1.02-1.22). In addition, sometimes daytime napping was also associated with an increased risk of COVID-19 susceptibility (sometimes vs. never: RR = 1.04, 95% CI = 1.01-1.28). In the MR analyses, excessive daytime sleepiness was found to increase the risk of hospitalized COVID-19 (MR IVW method: OR = 4.53, 95% CI = 1.04-19.82), whereas little evidence supported a causal link between daytime napping and COVID-19 outcomes.
CONCLUSIONS: Observational and genetic evidence supports a potential causal link between excessive daytime sleepiness and an increased risk of COVID-19 hospitalization, suggesting that interventions targeting excessive daytime sleepiness symptoms might decrease severe COVID-19 rate.
| Errataetall: | |
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:45 |
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| Enthalten in: |
Sleep - 45(2022), 6 vom: 13. Juni |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Liu, Zheran [VerfasserIn] |
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| Links: |
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| Themen: |
COVID-19 |
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| Anmerkungen: |
Date Completed 14.06.2022 Date Revised 23.08.2022 published: Print CommentIn: Sleep. 2022 Jul 11;45(7):. - PMID 35567789 Citation Status MEDLINE |
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| doi: |
10.1093/sleep/zsac003 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM335689264 |
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| 100 | 1 | |a Liu, Zheran |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Associations of sleep and circadian phenotypes with COVID-19 susceptibility and hospitalization |b an observational cohort study based on the UK Biobank and a two-sample Mendelian randomization study |
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| 500 | |a published: Print | ||
| 500 | |a CommentIn: Sleep. 2022 Jul 11;45(7):. - PMID 35567789 | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © The Author(s) 2022. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissionsoup.com. | ||
| 520 | |a STUDY OBJECTIVES: Sleep and circadian phenotypes are associated with several diseases. The present study aimed to investigate whether sleep and circadian phenotypes were causally linked with coronavirus disease 2019 (COVID-19)-related outcomes | ||
| 520 | |a METHODS: Habitual sleep duration, insomnia, excessive daytime sleepiness, daytime napping, and chronotype were selected as exposures. Key outcomes included positivity and hospitalization for COVID-19. In the observation cohort study, multivariable risk ratios (RRs) and their 95% confidence intervals (CIs) were calculated. Two-sample Mendelian randomization (MR) analyses were conducted to estimate the causal effects of the significant findings in the observation analyses. Odds ratios (ORs) and the corresponding 95% CIs were calculated and compared using the inverse variance weighting, weighted median, and MR-Egger methods | ||
| 520 | |a RESULTS: In the UK Biobank cohort study, both often excessive daytime sleepiness and sometimes daytime napping were associated with hospitalized COVID-19 (excessive daytime sleepiness [often vs. never]: RR = 1.24, 95% CI = 1.02-1.5; daytime napping [sometimes vs. never]: RR = 1.12, 95% CI = 1.02-1.22). In addition, sometimes daytime napping was also associated with an increased risk of COVID-19 susceptibility (sometimes vs. never: RR = 1.04, 95% CI = 1.01-1.28). In the MR analyses, excessive daytime sleepiness was found to increase the risk of hospitalized COVID-19 (MR IVW method: OR = 4.53, 95% CI = 1.04-19.82), whereas little evidence supported a causal link between daytime napping and COVID-19 outcomes | ||
| 520 | |a CONCLUSIONS: Observational and genetic evidence supports a potential causal link between excessive daytime sleepiness and an increased risk of COVID-19 hospitalization, suggesting that interventions targeting excessive daytime sleepiness symptoms might decrease severe COVID-19 rate | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Observational Study | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a COVID-19 | |
| 650 | 4 | |a Mendelian randomization | |
| 650 | 4 | |a cohort study | |
| 650 | 4 | |a sleep | |
| 700 | 1 | |a Luo, Yaxin |e verfasserin |4 aut | |
| 700 | 1 | |a Su, Yonglin |e verfasserin |4 aut | |
| 700 | 1 | |a Wei, Zhigong |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Ruidan |e verfasserin |4 aut | |
| 700 | 1 | |a He, Ling |e verfasserin |4 aut | |
| 700 | 1 | |a Yang, Lianlian |e verfasserin |4 aut | |
| 700 | 1 | |a Pei, Yiyan |e verfasserin |4 aut | |
| 700 | 1 | |a Ren, Jianjun |e verfasserin |4 aut | |
| 700 | 1 | |a Peng, Xingchen |e verfasserin |4 aut | |
| 700 | 1 | |a Hu, Xiaolin |e verfasserin |4 aut | |
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