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Adv Nutr. 2019 Jun 21. pii: nmz022. doi: 10.1093/advances/nmz022. [Epub ahead of print]

The Role of the Gut Microbiome in Predicting Response to Diet and the Development of Precision Nutrition Models-Part I: Overview of Current Methods.

Author information

1
Departments of Nutrition, Food Science and Technology, University of California, Davis, Davis, CA.
2
Food Science and Technology, University of California, Davis, Davis, CA.
3
Department of Biostatistics, University of Washington, Seattle, WA.
4
Obesity and Metabolism, Western Human Nutrition Research Center, Agricultural Research Service, USDA, Davis, CA.
5
Immunity and Disease Prevention, Western Human Nutrition Research Center, Agricultural Research Service, USDA, Davis, CA.

Abstract

Health care is increasingly focused on health at the individual level. In the rapidly evolving field of precision nutrition, researchers aim to identify how genetics, epigenetics, and the microbiome interact to shape an individual's response to diet. With this understanding, personalized responses can be predicted and dietary advice can be tailored to the individual. With the integration of these complex sources of data, an important aspect of precision nutrition research is the methodology used for studying interindividual variability in response to diet. This article stands as the first in a 2-part review of current research investigating the contribution of the gut microbiota to interindividual variability in response to diet. Part I reviews the methods used by researchers to design and carry out such studies as well as the statistical and bioinformatic methods used to analyze results. Part II reviews the findings of these studies, discusses gaps in our current knowledge, and summarizes directions for future research. Taken together, these reviews summarize the current state of knowledge and provide a foundation for future research on the role of the gut microbiome in precision nutrition.

KEYWORDS:

dietary response; effect modification; gut microbiome; interindividual variability; metabolism; methods; personalized nutrition; precision nutrition; prediction

PMID:
31225589
DOI:
10.1093/advances/nmz022

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