Parental SIRT1 Overexpression Attenuate Metabolic Disorders Due to Maternal High-Fat Feeding.
Long The NguyenSonia SaadHui ChenCarol A PollockPublished in: International journal of molecular sciences (2020)
Maternal obesity can contribute to the development of obesity and related metabolic disorders in progeny. Sirtuin (SIRT)1, an essential regulator of metabolism and stress responses, has recently emerged as an important modifying factor of developmental programming. In this study, to elucidate the effects of parental SIRT1 overexpression on offspring mechanism, four experimental groups were included: (1) Chow-fed wild-type (WT)-dam × Chow-fed WT-sire; (2) High-fat diet (HFD)-fed WT-dam × Chow-fed WT-sire; (3) HFD-fed hemizygous SIRT1-transgenic (Tg)-dam × Chow-fed WT-sire; and (4) HFD-fed WT dam × Chow-fed Tg-sire. Our results indicate that Tg breeders had lower body weight and fat mass compared to WT counterparts and gave birth to WT offspring with reductions in body weight, adiposity and hyperlipidaemia compared to those born of WT parents. Maternal SIRT1 overexpression also reversed glucose intolerance, and normalised abnormal fat morphology and the expression of dysregulated lipid metabolism markers, including SIRT1. Despite having persistent hepatic steatosis, offspring born to Tg parents showed an improved balance of hepatic glucose/lipid metabolic markers, as well as reduced levels of inflammatory markers and TGF-β/Smad3 fibrotic signalling. Collectively, the data suggest that parental SIRT1 overexpression can ameliorate adverse metabolic programming effects by maternal obesity.
Keyphrases
- high fat diet
- insulin resistance
- adipose tissue
- body weight
- oxidative stress
- metabolic syndrome
- ischemia reperfusion injury
- birth weight
- weight gain
- type diabetes
- cell proliferation
- high fat diet induced
- transcription factor
- weight loss
- gestational age
- pregnancy outcomes
- transforming growth factor
- fatty acid
- machine learning
- low birth weight
- epithelial mesenchymal transition
- electronic health record
- poor prognosis
- preterm infants
- blood glucose
- body mass index
- blood pressure
- long non coding rna
- deep learning
- physical activity
- big data
- idiopathic pulmonary fibrosis