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Nutr Metab Cardiovasc Dis. 2013 Mar;23(3):160-8. doi: 10.1016/j.numecd.2012.09.002. Epub 2012 Nov 10.

The role of gut microbiota in human obesity: recent findings and future perspectives.

Author information

1
Human Nutrition and Eating Disorders Research Center, Department of Public Health, Neuroscience, Experimental and Forensic Medicine, University of Pavia, Via A. Bassi 21, I-27100, Pavia, Italy. anna.tagliabue@unipv.it

Abstract

AIMS:

In recent years, gut microbiota have gained a growing interest as an environmental factor that may affect the predisposition toward adiposity. In this review, we describe and discuss the research that has focused on the involvement of gut microbiota in human obesity. We also summarize the current knowledge concerning the health effects of the composition of gut microbiota, acquired using the most recent methodological approaches, and the potential influence of gut microbiota on adiposity, as revealed by animal studies.

DATA SYNTHESIS:

Original research studies that were published in English or French until December 2011 were selected through a computer-assisted literature search. The studies conducted to date show that there are differences in the gut microbiota between obese and normal-weight experimental animals. There is also evidence that a high-fat diet may induce changes in gut microbiota in animal models regardless of the presence of obesity. In humans, obesity has been associated with reduced bacterial diversity and an altered representation of bacterial species, but the identified differences are not homogeneous among the studies.

CONCLUSIONS:

The question remains as to whether changes in the intestinal microbial community are one of the environmental causes of overweight and obesity or if they are a consequence of obesity, specifically of the unbalanced diet that often accompanies the development of excess weight gain. In the future, larger studies on the potential role of intestinal microbiota in human obesity should be conducted at the species level using standardized analytical techniques and taking all of the possible confounding variables into account.

PMID:
23149072
DOI:
10.1016/j.numecd.2012.09.002
[Indexed for MEDLINE]

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