The Biostatistical and Analytic Core (BAC) will provide advanced statistical and analytic support for all experimental projects within the Program Project Grant (PPG) and will be instrumental for achieving the overall aim of quantifying the relative contributions of sleep loss and circadian disruption on metabolism in healthy older people. To achieve this overall aim, the BAC will analyze data collected in the proposed PPG, as well as data across studies from the proposed, current, and previous PPGs and other studies conducted in the same facilities by PPG investigators. The integrative power of the PPG will therefore enable the BAC to extend the work of the individual experimental Projects by using data from multiple projects. This integration will allow more powerful and detailed statistical analyses, as well as cross-experiment analyses and comparisons that will enable stronger conclusions to be made about the effects of sleep loss and circadian disruption on physiology, metabolism and autonomic function in humans and rodents. The BAC specific aims are: (SA1) To conduct the primary and secondary statistical analyses for each of the individual projects within the PPG using state-of-the-art statistical and analytic methods for evaluating the specific aims of each individual project;(SA2 and SAS) To quantify the effects of sleep loss and circadian disruption, their interaction, and recovery from these exposures on various metrics of metabolism (SA2) and autonomic function (SAS) by using longitudinal analyses and by analyzing and comparing data across different experimental protocols. Analytic and statistical methods - along with the bio-mathematical models developed by the Analytic Cores within previous PPGs - have been used to design and to analyze most experiments in the Brigham and Women's Hospital (BWH) Division of Sleep Medicine (DSM). New methods are required because of the longitudinal, correlated, and frequently non-normal distributions of the data collected. Appropriate statistical and modeling techniques determine whether an intervention has a significant effect, and to enable extraction of additional information from previously collected data. Therefore, the BAC will support and greatly extend the results of the PPG experimental work.
The BAC will provide biostatistical support to all projects, will apply analytic and statistical techniques to the complex, longitudinal, and frequently non-normally distributed and correlated data sets. By integrating data from multiple experiments, the BAC will quantify the relative contributions of sleep loss and circadian disruption on metabolism and autonomic function in older people and rodents.
|Markt, Sarah C; Valdimarsdottir, Unnur A; Shui, Irene M et al. (2015) Circadian clock genes and risk of fatal prostate cancer. Cancer Causes Control 26:25-33|
|Balasubramanian, Ravikumar; Cohen, Daniel A; Klerman, Elizabeth B et al. (2014) Absence of central circadian pacemaker abnormalities in humans with loss of function mutation in prokineticin 2. J Clin Endocrinol Metab 99:E561-6|
|Dean 2nd, Dennis A; Adler, Gail K; Nguyen, David P et al. (2014) Biological time series analysis using a context free language: applicability to pulsatile hormone data. PLoS One 9:e104087|
|Hsieh, Wan-Hsin; Escobar, Carolina; Yugay, Tatiana et al. (2014) Simulated shift work in rats perturbs multiscale regulation of locomotor activity. J R Soc Interface 11:|
|Lim, Andrew S P; Ellison, Brian A; Wang, Joshua L et al. (2014) Sleep is related to neuron numbers in the ventrolateral preoptic/intermediate nucleus in older adults with and without Alzheimer's disease. Brain 137:2847-61|
|Lee, Jung Hie; Kim, Seong Jae; Lee, Se Yong et al. (2014) Reliability and validity of the Korean version of Morningness-Eveningness Questionnaire in adults aged 20-39 years. Chronobiol Int 31:479-86|
|Faghih, Rose T; Dahleh, Munther A; Adler, Gail K et al. (2014) Deconvolution of serum cortisol levels by using compressed sensing. PLoS One 9:e85204|
|Phillips, A J K; Fulcher, B D; Robinson, P A et al. (2013) Mammalian rest/activity patterns explained by physiologically based modeling. PLoS Comput Biol 9:e1003213|
|Breslow, Emily R; Phillips, Andrew J K; Huang, Jean M et al. (2013) A mathematical model of the circadian phase-shifting effects of exogenous melatonin. J Biol Rhythms 28:79-89|
|Phillips, A J K; Robinson, P A; Klerman, E B (2013) Arousal state feedback as a potential physiological generator of the ultradian REM/NREM sleep cycle. J Theor Biol 319:75-87|
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