archives@tulane.edu / Background:
Human Biological Aging (BA) estimates are developed by human to better capture the gradual increase in the vulnerability of the aging body than chronological age. Human sleep dimensions have been suggested to be associated with human health indicators including cardiometabolic function, cognitive function and mortality. The objective of this study was to examine indicators of BA and their predictive validity using Klemera and Doubal’s Method (KDM), and Physiological Dysregulation Method (PDM) for quantifying BA, as well as to explore if phenotypical and genetic associations between sleep variables and BA estimates exist, using the Bogalusa Heart Study (BHS) – a community-based, cohort study.
Method:
In order to estimate BA, nineteen biomarkers were selected. Training datasets were from NHANES. The target dataset included 1,034 BHS subjects assessed between 2013-2016. Training was done separately for male and female, black and white participants. KDM and Mahalanobis Distance (DM) based PDM methods were used. Cognitive and physical performance testing were used to examine predictive validity.
The association between three sleep dimension variables and BA estimates were explored using 953 black and white BHS 2013-2016 subjects. Sleep duration in hours, chronotype scores and social jetlag in hours were the independent variables. BA estimates were the dependent variables.
Genotyping information from the BHS 2013-2016 were included (n=646) for genetic association. Related SNPs on morning chronotype were used to compute a genetic risk score (GRS) for BHS participants. Association between chronotype GRS and chronotype phenotype were explored.
Multivariate linear regression was used for all association analyses.
Results:
BA estimates were calculated using both the KDM and PDM methods. Linear regression showed that PDM BA estimates were associated with lower cognitive function physical performance tests. The effect sizes of all associations between PDM BA estimates and performance tests were of greater magnitude than between KDM estimates and performance tests. Short sleep duration and evening chronotype was associated with larger PDM BA estimates. Morning chronotype GRS was not associated with morning chronotype phenotype among BHS participants.
Conclusion:
PDM BA estimates are robust measures of biological aging in black and white men and women enrolled in the BHS. Insufficient sleep duration and evening chronotype may advance biological aging, regardless of gender, race and CA. We did not find association between morning chronotype GRS and morning chronotype phenotype. PDM BA estimates should be recommended for future aging studies using data from BHS participants. / 1 / Xunming Sun
| Identifer | oai:union.ndltd.org:TULANE/oai:http://digitallibrary.tulane.edu/:tulane_122473 |
| Date | January 2021 |
| Contributors | Sun, Xunming (author), Gustat, Jeanette (Thesis advisor), Bazzano, Lydia (Thesis advisor), Kelly, Tanika (Thesis advisor), Tang, Wan (Thesis advisor), School of Medicine Interdisciplinary Program of Aging (Degree granting institution) |
| Publisher | Tulane University |
| Source Sets | Tulane University |
| Language | English |
| Detected Language | English |
| Type | Text |
| Format | electronic, pages: 133 |
| Rights | No embargo, Copyright is in accordance with U.S. Copyright law. |
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