Genetic background and sex control the outcome of high-fat diet feeding in mice

The sharp increase in obesity prevalence worldwide is mainly attributable to changes in physical activity and eating behavior but the metabolic and clinical impacts of these obesogenic conditions vary between sexes and genetic backgrounds. This warrants personalized treatments of obesity and its com...

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Veröffentlicht in:iScience 2022-06, Vol.25 (6), p.104468-104468, Article 104468
Hauptverfasser: Bachmann, Alexis Maximilien, Morel, Jean-David, El Alam, Gaby, Rodríguez-López, Sandra, Imamura de lima, Tanes, Goeminne, Ludger J.E., Benegiamo, Giorgia, Loric, Sylvain, Conti, Marc, Sleiman, Maroun Bou, Auwerx, Johan
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Sprache:eng
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Zusammenfassung:The sharp increase in obesity prevalence worldwide is mainly attributable to changes in physical activity and eating behavior but the metabolic and clinical impacts of these obesogenic conditions vary between sexes and genetic backgrounds. This warrants personalized treatments of obesity and its complications, which require a thorough understanding of the diversity of metabolic responses to high-fat diet intake. By analyzing nine genetically diverse mouse strains, we show that much like humans, mice exhibit a huge variety of physiological and biochemical responses to high-fat diet. The strains exhibit various degrees of alterations in their phenotypic makeup. At the transcriptome level, we observe dysregulations of immunity, translation machinery, and mitochondrial genes. At the biochemical level, the enzymatic activity of mitochondrial complexes is affected. The diversity across mouse strains, diets, and sexes parallels that found in humans and supports the use of diverse mouse populations in future mechanistic or preclinical studies on metabolic dysfunctions. [Display omitted] •Strain- and sex-specific profile of metabolic dysfunction in mice•Liver mitochondrial complex activity in vivo associates with metabolic traits•Open data source for evaluating different mouse strains for metabolic disease•Interactive data exploration through an online application Obesity medicine; Biological sciences; Endocrinology
ISSN:2589-0042
2589-0042
DOI:10.1016/j.isci.2022.104468