Transition to a Western Diet and Cardiometabolic Risk Biomarkers Derived from the Microbiome

Despite recent emergence of gut microbiota as a novel factor influencing obesity and related metabolic disorders such as diabetes and cardiovascular disease, very little is known about the role of long-term diet on microbially mediated disease risk. The primary reasons for this lack of understanding are: (1) lack of high quality, long-term diet data in combination with microbiome data; (2) lack of data in populations undergoing rapid changes in environments and outcomes, with enough variability to create a range of exposures; and (3) insufficient use of complex statistical models to allow examination of each piece of the time-dependent, complex system. The China Health and Nutrition Survey (CHNS), an NIH-funded study of more than 15,000 individuals followed over 25 years, provides high-quality longitudinal data and captures the transition from traditional to Western diet in parallel with urbanization and emergence of obesity and cardiovascular disease during the past two decades. These data will be used to generate insights that would not be obtainable in studies with participants who consume only a Westernized diet. Using sophisticated statistical models, the research team will examine whether information on gut microbiota composition along with data on the plasma metabolome can predict markers of cardiometabolic disease (body mass index, central adiposity, diabetes and inflammation), allowing implication of the microbiota in disease pathways. Fecal samples are collected from adult CHNS participants aged 30-65 at the 2015 exam. In a subsample from two neighboring Southern provinces -- one actively urbanizing and one already urbanized -- varying in current (and long-term change) in Western diet, microbial sequences in the 16S V3-V4 region (n=1,000) will be generated and the remaining fecal samples will be stored. We will select a subsample with 16S data who have consumed a traditional diet over the 25 years (n=400) and conduct plasma metabolomics of the host. In the CHNS subsample with microbiota plus metabolome (n=400) data, we will collect replicate blood and fecal samples in CHNS2017 to derive 16S and plasma metabolomics data to assess two-year changes (2015-2017) in diet, gut microbiota, plasma metabolites and in markers of cardiometabolic disease. We will examine whether gut microbiota and plasma metabolites differ depending upon when, within the 25-year period, diet changes occur, and if they are associated with health outcomes. In our longitudinal subsample we will examine changes in markers of Western diet in relation to concurrent changes in microbial diversity and community composition, and metabolites. We first use a series of standard regression models and then high dimensional regression analysis with variable selection and validation to build predictive models. We capitalize on an established and well-characterized, large cohort with far greater variability in diet and microbial communities than studies in cohorts on only Western diets. The project will substantially transform current understanding of the intersection of diet, gut microbiota, host metabolism and cardiometabolic disease.

Principal Investigator: Penny Gordon-Larsen

CPC Fellow Investigator: Barry M. Popkin

Other Investigators: Annie Green Howard, Huijun Wang, Anthony Fodor, Fang Xiaodong

Funding Source: NIH NIDDK

Grant Number: R01DK104371

Funding Period: 9/17/2015 - 6/30/2019

Primary Research Area: Population Health

Affiliated Research Project:

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