Role of sleep quality in the acceleration of biological aging and its potential for preventive interaction on air pollution insults: Findings from the UK Biobank cohort

  1. Xu Gao
  2. Ninghao Huang
  3. Xinbiao Guo
  4. Tao Huang

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Abstract

Sleep has been associated with aging and relevant health outcomes, but the causal relationship remains inconclusive. In this study, we investigated the associations of sleep behaviors with biological ages (BAs) among 363,886 middle and elderly adults from UK Biobank. Sleep index (0 [worst]–6 [best]) of each participant was retrieved from the following six sleep behaviors: snoring, chronotype, daytime sleepiness, sleep duration, insomnia, and difficulties in getting up. Two BAs, the KDM‐biological age and PhenoAge, were estimated by corresponding algorithms based on clinical traits, and their residual discrepancies with chronological age were defined as the age accelerations (AAs). We first observed negative associations between the sleep index and the two AAs, and demonstrated that the change of AAs could be the consequence of sleep quality using Mendelian randomization with genetic risk scores of sleep index and BAs. Particularly, a one‐unit increase in sleep index was associated with 0.104‐ and 0.119‐year decreases in KDM‐biological AA and PhenoAge acceleration, respectively. Air pollution is another key driver of aging. We further observed significant independent and joint effects of sleep and air pollution (PM 2.5 and NO 2 ) on AAs. Sleep quality also showed a modifying effect on the associations of elevated PM 2.5 and NO 2  levels with accelerated AAs. For instance, an interquartile range increase in PM 2.5  level was associated with 0.009‐, 0.044‐, and 0.074‐year increase in PhenoAge acceleration among people with high (5–6), medium (3–4), and low (0–2) sleep index, respectively. Our findings elucidate that better sleep quality could lessen accelerated biological aging resulting from air pollution.

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  1. Version published to 10.1111/acel.13610
  2. ScreenIT

    SciScore for 10.1101/2021.08.27.457922: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIRB: UK Biobank research has approval from the North West Multicenter Research Ethical Committee.
    Consent: All participants provided written informed consent for the study.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    SAS version 9.4 TS1M5 (SAS Institute Inc.
    SAS Institute
    suggested: (Statistical Analysis System, RRID:SCR_008567)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Several limitations are notable when interpreting the results. First, UK Biobank is a volunteer cohort, and participants are likely healthier than the general population, which may limit the effect of sleep on BAs in our analysis as their AAs are expected to be lower than the general population theoretically. Furthermore, the measurement bias of air pollution must be noted. The air pollution data we used were mostly only a single measurement of the annual average outdoor air pollution level in 2010 since home addresses of the participants are unavailable during follow-up. Because the initial assessment visit of UK Biobank was from 2006 to 2010, we were unable to determine the lag or short-term (<1 month) effects of air pollution on both sleep and BAs. Also, as most individuals spend a large amount of time indoors, individual exposure to all forms of air pollution may differ from that indicated by the ambient outdoor levels we used. Additionally, self-reported sleep data was used in our analyses, misclassification of sleep behaviors was therefore inevitable. However, such bias may attenuate our findings toward the null and underestimate the effects we observed. Meanwhile, our sleep index dichotomized six sleep behaviors for simplicity but did not include all sleep behaviors or take the changes of sleep behaviors before and after the survey into consideration, which may cause residual bias to some extents. Last, participants in this study were mostly of European descent, which ...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  3. Version published to 10.1101/2021.08.27.457922v1 on bioRxiv