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- Ahmed, Fozia
(author)
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Estrogen and its receptors in adipose tissue from women and men : Associations with age, adiposity and type 2 diabetes
- 2024
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Doctoral thesis (other academic/artistic)abstract
- Obesity and its complications, such as insulin resistance and type 2 diabetes (T2D), are leading causes of morbidity and mortality globally. Adipose tissue is important for whole-body homeostasis, functioning as an energy storage reservoir and an endocrine organ. Estrogens mediate their effects through estrogen receptor alpha (ESR1) and beta (ESR2) and contribute to sex and menopause-related differences in body fat distribution. Moreover, estrogens can be produced from androgens in the adipose tissue by the enzyme aromatase. The overall aim of this thesis was to investigate the role of estrogen and estrogen signalling in human adipose tissue and their association with age, adiposity, and insulin resistance. In Paper I, we assessed ESR1 and ESR2 gene expression in subcutaneous adipose tissue (SAT) from pre- and postmenopausal women, and investigated the effects of estradiol on adipocyte glucose uptake. We found that ESR2 gene expression was higher in postmenopausal women than premenopausal women. Moreover, in late, but not pre- or early postmenopausal women, estradiol incubation reduced basal and insulin-stimulated glucose uptake, which corresponded to an increase in ESR2 gene expression levels. The inhibiting effect of estradiol on adipocyte glucose uptake was prevented using an ESR2 antagonist. Subsequently, in Paper II we assessed the role of ESR2 in SAT lipid and glucose metabolism and preadipocyte differentiation. ESR2 expression in SAT was inversely correlated with markers of central adiposity and positively correlated with markers of lipid accumulation. Moreover, ESR2 knockdown impaired subcutaneous preadipocyte differentiation and glucose utilization. In Paper III, we focused on adipocyte lipolysis in women, which is regulated, in part, by catecholamines. OCT3, which mediates catecholamine transport into adipocytes, where they can be degraded, was increased in SAT with age, and higher in postmenopausal women than premenopausal women. Moreover, its expression was negatively associated with markers of insulin resistance and ex vivo lipolysis. Estradiol incubation of SAT downregulated OCT3 gene expression, which may explain lower OCT3 gene expression in premenopausal compared to postmenopausal women. In Paper IV, we focused on the role of aromatase and estradiol in SAT from men. We found that aromatase expression was higher in SAT from men with obesity and T2D compared to subjects without obesity and T2D, respectively, and was positively associated with markers of central obesity and markers of insulin resistance. Contrastingly, ESR1 expression in SAT was lower in men with obesity and T2D compared to subjects without obesity and T2D, respectively, and negatively associated with markers of obesity and insulin resistance. ESR2 expression was higher in SAT from men with T2D compared to men without T2D. Estradiol reduced insulin-stimulated glucose uptake, however, neither testosterone, nor aromatase inhibition, altered adipocyte glucose uptake. In this thesis, we found that estrogen has important metabolic effects in adipose tissue, including regulating lipid accumulation, glucose uptake capacity, and catecholamine transport. Overall, our findings suggest that estrogen and estrogen receptors may have an important role in age-, menopausal- and sex-dependent differences in body fat distribution, and may serve as potential targets for the prevention and treatment obesity and insulin resistance.
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- Herrgårdh, Tilda, et al.
(author)
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A multi-scale digital twin for adiposity-driven insulin resistance in humans : diet and drug effects
- 2023
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In: Diabetology & Metabolic Syndrome. - : BioMed Central (BMC). - 1758-5996. ; 15:1
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Journal article (peer-reviewed)abstract
- BACKGROUND: The increased prevalence of insulin resistance is one of the major health risks in society today. Insulin resistance involves both short-term dynamics, such as altered meal responses, and long-term dynamics, such as the development of type 2 diabetes. Insulin resistance also occurs on different physiological levels, ranging from disease phenotypes to organ-organ communication and intracellular signaling. To better understand the progression of insulin resistance, an analysis method is needed that can combine different timescales and physiological levels. One such method is digital twins, consisting of combined mechanistic mathematical models. We have previously developed a model for short-term glucose homeostasis and intracellular insulin signaling, and there exist long-term weight regulation models. Herein, we combine these models into a first interconnected digital twin for the progression of insulin resistance in humans.METHODS: The model is based on ordinary differential equations representing biochemical and physiological processes, in which unknown parameters were fitted to data using a MATLAB toolbox. RESULTS: The interconnected twin correctly predicts independent data from a weight increase study, both for weight-changes, fasting plasma insulin and glucose levels, and intracellular insulin signaling. Similarly, the model can predict independent weight-change data in a weight loss study with the weight loss drug topiramate. The model can also predict non-measured variables.CONCLUSIONS: The model presented herein constitutes the basis for a new digital twin technology, which in the future could be used to aid medical pedagogy and increase motivation and compliance and thus aid in the prevention and treatment of insulin resistance.
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