Association between Gut Microbiota and Metabolic Health and Obesity Status in Cats

Obesity is a major public health concern in both humans and animals, leading to several metabolic complications. Recent human studies have classified obesity into two phenotypes, metabolically healthy (MHO) and metabolically unhealthy (MUO) obesity based on cardiovascular and metabolic risk factors. MHO cases lack these risk factors and are protected from metabolic complications of obesity, whereas MUO cases exhibit the opposite characteristics. Moreover, recent studies have highlighted the possible role of the gut microbiome in determining metabolic health of obese individuals. However, studies on the association between the gut microbiome and obesity and metabolic abnormalities in cats are limited. Therefore, we aimed to examine the association between metabolic health phenotypes and gut microbiota composition and diversity in obese cats. We investigated hormone and serum biochemistry parameters and composition of the gut microbiota in non-obese (NO), MHO, and MUO groups. The abundances of Bifidobacteriaceae, Coriobacteriaceae, and Veillonellaceae were significantly higher in the obese versus NO group, showing a positive correlation with body mass index. The abundance of Ruminococcaceae was significantly higher in the MUO versus NO group, showing a positive correlation with triglyceride and total cholesterol levels. However, obesity, whether MHO or MUO, had only a minimal impact on fecal microbiota. Therefore, further studies are warranted to investigate whether gut microbiota could be a beneficial tool for the treatment or management of this condition.

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Publication Details

Journal
Animals
Published
2024-08-30
DOI
https://doi.org/10.3390/ani14172524
Citations
7
Primary Topic
Gut microbiota and health
Type
article
Field-Weighted Citation Impact
1.64

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article

Association between Gut Microbiota and Metabolic Health and Obesity Status in Cats

Kyu-Duk Yeon, Jung-Hyun Kim, Sun-Myung Kim
7 citations
Animals
Gut microbiota and health
1.64
article

Association between Gut Microbiota and Metabolic Health and Obesity Status in Cats

Kyu-Duk Yeon, Jung-Hyun Kim, Sun-Myung Kim
article en
7 citations

Abstract

Obesity is a major public health concern in both humans and animals, leading to several metabolic complications. Recent human studies have classified obesity into two phenotypes, metabolically healthy (MHO) and metabolically unhealthy (MUO) obesity based on cardiovascular and metabolic risk factors. MHO cases lack these risk factors and are protected from metabolic complications of obesity, whereas MUO cases exhibit the opposite characteristics. Moreover, recent studies have highlighted the possible role of the gut microbiome in determining metabolic health of obese individuals. However, studies on the association between the gut microbiome and obesity and metabolic abnormalities in cats are limited. Therefore, we aimed to examine the association between metabolic health phenotypes and gut microbiota composition and diversity in obese cats. We investigated hormone and serum biochemistry parameters and composition of the gut microbiota in non-obese (NO), MHO, and MUO groups. The abundances of Bifidobacteriaceae, Coriobacteriaceae, and Veillonellaceae were significantly higher in the obese versus NO group, showing a positive correlation with body mass index. The abundance of Ruminococcaceae was significantly higher in the MUO versus NO group, showing a positive correlation with triglyceride and total cholesterol levels. However, obesity, whether MHO or MUO, had only a minimal impact on fecal microbiota. Therefore, further studies are warranted to investigate whether gut microbiota could be a beneficial tool for the treatment or management of this condition.

AnimalsVol. 14(17)
Konkuk University (KR)
Konkuk University
Good health and well-being
Openalex Percentile: Top 16%
Gut microbiota and health
1.64
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Association between Gut Microbiota and Metabolic Health and Obesity Status in Cats — Kyu-Duk Yeon, Jung-Hyun Kim, et al. · Animals (2024) | TGRS Research Map | TGRS