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Clin Gastroenterol Hepatol. 2019 Jan;17(2):218-230. doi: 10.1016/j.cgh.2018.09.017. Epub 2018 Sep 18.

Microbiome 101: Studying, Analyzing, and Interpreting Gut Microbiome Data for Clinicians.

Author information

1
Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, California.
2
Department of Pediatrics, University of California San Diego, La Jolla, California.
3
Scripps Institution of Oceanography, University of California San Diego, La Jolla, California.
4
Division of Biological Sciences, University of California San Diego, La Jolla, California.
5
Department of Medicine, University of California San Diego, La Jolla, California.
6
Department of Medicine, University of California San Diego, La Jolla, California; Center for Microbiome Innovation, University of California San Diego, La Jolla, California.
7
Center for Microbiome Innovation, University of California San Diego, La Jolla, California; Department of Computer Science and Engineering, University of California San Diego, La Jolla, California; California Institute of Telecommunications and Information Technology, University of California San Diego, La Jolla, California.
8
Center for Microbiome Innovation, University of California San Diego, La Jolla, California; Division of Gastroenterology, Veterans Administration San Diego Health System, La Jolla, California.
9
Department of Medicine, University of California San Diego, La Jolla, California; Center for Microbiome Innovation, University of California San Diego, La Jolla, California; Division of Gastroenterology, Veterans Administration San Diego Health System, La Jolla, California.
10
Department of Pediatrics, University of California San Diego, La Jolla, California; Center for Microbiome Innovation, University of California San Diego, La Jolla, California; Skaggs School of Pharmacy, University of California San Diego, La Jolla, California.
11
Department of Pediatrics, University of California San Diego, La Jolla, California; Center for Microbiome Innovation, University of California San Diego, La Jolla, California; Department of Computer Science and Engineering, University of California San Diego, La Jolla, California; Department of Bioengineering, University of California San Diego, La Jolla, California. Electronic address: robknight@ucsd.edu.

Abstract

Advances in technical capabilities for reading complex human microbiomes are leading to an explosion of microbiome research, leading in turn to intense interest among clinicians in applying these techniques to their patients. In this review, we discuss the content of the human microbiome, including intersubject and intrasubject variability, considerations of study design including important confounding factors, and different methods in the laboratory and on the computer to read the microbiome and its resulting gene products and metabolites. We highlight several common pitfalls for clinicians, including the expectation that an individual's microbiome will be stable, that diet can induce rapid changes that are large compared with the differences among subjects, that everyone has essentially the same core stool microbiome, and that different laboratory and computational methods will yield essentially the same results. We also highlight the current limitations and future promise of these techniques, with the expectation that an understanding of these considerations will help accelerate the path toward routine clinical application of these techniques developed in research settings.

KEYWORDS:

Clinician; Diagnosis; Gut Microbiome; Prognosis; Study Design

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