A Cross-Sectional Study of Obesity Effects on the Metabolomic Profile of a Leptin-Resistant Swine Model.

Iberian pig metabolic syndrome metabolite profile metabolomics obesity

Journal

Metabolites
ISSN: 2218-1989
Titre abrégé: Metabolites
Pays: Switzerland
ID NLM: 101578790

Informations de publication

Date de publication:
05 Mar 2020
Historique:
received: 06 02 2020
revised: 25 02 2020
accepted: 03 03 2020
entrez: 11 3 2020
pubmed: 11 3 2020
medline: 11 3 2020
Statut: epublish

Résumé

Identifying metabolite signatures associated with obesity and related diseases might represent a valuable preventive and therapeutic tool to predict subjects at risk, establish an accurate prognosis, and monitor treatment success. The current cross-sectional study is aimed to evaluate the metabolite profile of diet-induced obesity in a porcine model of leptin resistance. Six Iberian female pigs prone to develop obesity (OB) were ad libitum fed a fat-enriched diet (HFD) for 82 days. Five lean Iberian sows (CON) in a maintenance diet served as controls. At the end of the dietary treatments, all animals were sacrificed, and plasma, liver, and muscle samples were immediately collected for nuclear magnetic resonance analysis. In plasma, signals corresponding to betaine, glycerophosphocholine/phosphocholine, glycine, and glutamate were decreased; and the valine signal was increased in OB sows compared to controls. Similarly, the betaine signal was decreased in the liver. No differences were detected in muscle. The observed metabolite changes suggest alterations in branched chain amino-acid metabolism and the methionine-homocysteine cycle, which have been previously associated with obesity-related diseases and type 2 diabetes in human observational studies. The current study supports the utilization of the leptin resistant Iberian pig for further interventional research in the field.

Identifiants

pubmed: 32150837
pii: metabo10030089
doi: 10.3390/metabo10030089
pmc: PMC7143848
pii:
doi:

Types de publication

Journal Article

Langues

eng

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Auteurs

M Victoria Sanz-Fernandez (MV)

Subdirección General de Investigación y Tecnología-Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (SGIT-INIA), 28040 Madrid, Spain.

Laura Torres-Rovira (L)

Subdirección General de Investigación y Tecnología-Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (SGIT-INIA), 28040 Madrid, Spain.

Jose L Pesantez-Pacheco (JL)

Subdirección General de Investigación y Tecnología-Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (SGIT-INIA), 28040 Madrid, Spain.
School of Veterinary Medicine and Zootechnics, Faculty of Agricultural Sciences, University of Cuenca, 010220 Cuenca, Ecuador.

Marta Vazquez-Gomez (M)

Faculty of Veterinary Medicine, Universidad Complutense de Madrid (UCM), 28040 Madrid, Spain.

Consolacion Garcia-Contreras (C)

Subdirección General de Investigación y Tecnología-Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (SGIT-INIA), 28040 Madrid, Spain.

Susana Astiz (S)

Subdirección General de Investigación y Tecnología-Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (SGIT-INIA), 28040 Madrid, Spain.

Antonio Gonzalez-Bulnes (A)

Subdirección General de Investigación y Tecnología-Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (SGIT-INIA), 28040 Madrid, Spain.
Faculty of Veterinary Medicine, Universidad Complutense de Madrid (UCM), 28040 Madrid, Spain.

Classifications MeSH