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Principal Investigator
Name
Qian Xiao
Degrees
PhD, MPH
Institution
The University of Texas Health Science Center at Houston
Position Title
Assistant Professor
Email
About this CDAS Project
Study
IDATA (Learn more about this study)
Project ID
IDATA-37
Initial CDAS Request Approval
Jul 17, 2020
Title
Studying the association between diurnal rhythms of eating-fasting and rest-activity behaviors and oral microbiome.
Summary
Influenced by both the internal clock and environmental cues, many human behaviors exhibit a 24-hour rhythmic pattern. The most prominent examples of human diurnal behaviors are the rest-activity and eating-fasting cycles, and growing evidence suggests that disruptions of diurnal behaviors are important risk factors for cardiometabolic conditions, cancer and cognitive decline in the aging population. More recently, research showed that there is an intimate relationship between circadian rhythms, diurnal behaviors, and the microbiome: Several studies found that human gut and oral microbiome exhibit considerable circadian oscillations in microbial composition and functions. In addition, gut microbiome has been shown to correlate with various aspects of sleep, and there is strong evidence suggesting a bidirectional relationship between sleep and microbiome. Moreover, time-restricted feeding studies showed that meal timing may affect gut microbiome, which may in turn influence host metabolism and have an impact on metabolic dysfunction. Although these findings are intriguing and support a role of circadian rhythms in microbiome structure and function, there are limited studies on how natural variations in diurnal behaviors under free-living conditions are related to microbiome characteristics.

Traditionally, studies of rest-activity and eating-fasting behaviors focused on conventional measures of individual components such as caloric intake, dietary quality, physical activity duration and volume, length of sedentary behavior, and sleep duration and quality. These measures ignore the timing aspect of the behaviors and are inadequate to capture the overall patterns of multiple behaviors that are often correlated with each other. There is a need for an integrated approach to comprehensively assess the rhythmic profiles and interrelationships of diurnal behaviors in human populations, and examine their relationships with health and disease outcomes. Our previous work in the Interactive Diet and Activity Tracking in AARP (IDATA) study have defined multiple circadian parameters to characterize the eating-fasting cycle. We have found that meal timing variables are significantly associated with overweight and obesity. Specifically, eating early in the morning was associated with lower odds of overweight and obesity, while late night eating was associated with higher odds. We also found that the duration and timing of overnight fasting are associated with obesity. We are currently expanding this line of research by 1) characterizing rest-activity rhythms using actigraphy data; and 2) developing statistical methods to examine the joined profiles of eating-fasting and rest-activity in relation to health indicators.

In this study, we propose to investigate characteristics of the eating-fasting and rest-activity cycles in relation to oral microbiome in the IDATA. Currently, an approved and active study is aimed at obtaining oral microbiome data using multiple samples from more than 900 IDATA participants. The study will allow us to examine both average patterns and daily temporal variation (morning vs. evening) in oral microbiota, and investigate their associations with diurnal behavior patterns.
Aims

Aim 1 Investigate characteristics of the eating-fasting and rest-activity cycles in relation to microbial diversity, including alpha diversity (observed species, Shannon index, and Faith’s PD), beta diversity (Bray-Curtis, unweighted UniFrac, and weighted UniFrac), and presence/absence of a specific taxon).

Aim 2 Investigate characteristics of the eating-fasting and rest-activity cycles in relation to difference in microbial diversity between morning and evening measures.

Collaborators

Christian Abnet (NCI, DCEG)
Yukiko Yano (NCI, DCEG)