The carbohydrate-insulin model: a physiological perspective on the obesity pandemic.
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ABSTRACT:
SUBMITTER: Ludwig DS
PROVIDER: S-EPMC8634575 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Despite intensive research, the causes of the obesity epidemic remain incompletely understood and conventional calorie-restricted diets continue to lack long-term efficacy. According to the carbohydrate-insulin model (CIM) of obesity, recent increases in the consumption of processed, high-glycemic-load carbohydrates produce hormonal changes that promote calorie deposition in adipose tissue, exacerbate hunger, and lower energy expenditure. Basic and genetic research provides mechanistic evidence in support of the CIM. In animals, dietary composition has been clearly demonstrated to affect metabolism and body composition, independently of calorie intake, consistent with CIM predictions. Meta-analyses of behavioral trials report greater weight loss with reduced-glycemic load vs low-fat diets, though these studies characteristically suffer from poor long-term compliance. Feeding studies have lacked the rigor and duration to test the CIM, but the longest such studies tend to show metabolic advantages for low-glycemic load vs low-fat diets. Beyond the type and amount of carbohydrate consumed, the CIM provides a conceptual framework for understanding how many dietary and nondietary exposures might alter hormones, metabolism, and adipocyte biology in ways that could predispose to obesity. Pending definitive studies, the principles of a low-glycemic load diet offer a practical alternative to the conventional focus on dietary fat and calorie restriction.
| S-EPMC6082688 | biostudies-literature
Project description:BACKGROUND:A fundamental precept of the carbohydrate-insulin model of obesity is that insulin secretion drives weight gain. However, fasting hyperinsulinemia can also be driven by obesity-induced insulin resistance. We used genetic variation to isolate and estimate the potentially causal effect of insulin secretion on body weight. METHODS:Genetic instruments of variation of insulin secretion [assessed as insulin concentration 30 min after oral glucose (insulin-30)] were used to estimate the causal relationship between increased insulin secretion and body mass index (BMI), using bidirectional Mendelian randomization analysis of genome-wide association studies. Data sources included summary results from the largest published metaanalyses of predominantly European ancestry for insulin secretion (n = 26037) and BMI (n = 322154), as well as individual-level data from the UK Biobank (n = 138541). Data from the Cardiology and Metabolic Patient Cohort study at Massachusetts General Hospital (n = 1675) were used to validate genetic associations with insulin secretion and to test the observational association of insulin secretion and BMI. RESULTS:Higher genetically determined insulin-30 was strongly associated with higher BMI (? = 0.098, P = 2.2 × 10-21), consistent with a causal role in obesity. Similar positive associations were noted in sensitivity analyses using other genetic variants as instrumental variables. By contrast, higher genetically determined BMI was not associated with insulin-30. CONCLUSIONS:Mendelian randomization analyses provide evidence for a causal relationship of glucose-stimulated insulin secretion on body weight, consistent with the carbohydrate-insulin model of obesity.
| S-EPMC5937525 | biostudies-literature
Project description:BACKGROUND: Sensitivity to obesity is highly variable in humans, and rats fed a high fat diet (HFD) are used as a model of this inhomogeneity. Energy expenditure components (basal metabolism, thermic effect of feeding, activity) and variations in substrate partitioning are possible factors underlying the variability. Unfortunately, in rats as in humans, results have often been inconclusive and measurements usually made after obesity onset, obscuring if metabolism was a cause or consequence. Additionally, the role of high carbohydrate diet (HCD) has seldom been studied. METHODOLOGY/FINDINGS: Rats (n=24) were fed for 3 weeks on HCD and then 3 weeks on HFD. Body composition was tracked by MRI and compared to energy expenditure components measured prior to obesity. RESULTS: 1) under HFD, as expected, by adiposity rats were variable enough to be separable into relatively fat resistant (FR) and sensitive (FS) groups, 2) under HCD, and again by adiposity, rats were also variable enough to be separable into carbohydrate resistant (CR) and sensitive (CS) groups, the normal body weight of CS rats hiding viscerally-biased fat accumulation, 3) HCD adiposity sensitivity was not related to that under HFD, and both HCD and HFD adiposity sensitivities were not related to energy expenditure components (BMR, TEF, activity cost), and 4) only carbohydrate to fat partitioning in response to an HCD test meal was related to HCD-induced adiposity. CONCLUSIONS/SIGNIFICANCE: The rat model of human obesity is based on substantial variance in adiposity gains under HFD (FR/FS model). Here, since we also found this phenomenon under HCD, where it was also linked to an identifiable metabolic difference, we should consider the existence of another model: the carbohydrate resistant (CR) or sensitive (CS) rat. This new model is potentially complementary to the FR/FS model due to relatively greater visceral fat accumulation on a low fat high carbohydrate diet.
| S-EPMC3728328 | biostudies-literature
Project description:Nowadays, obesity and being overweight are among the major global health concerns. Many, diet-related diseases impose high tangible and intangible costs, and threaten the sustainability of health-care systems worldwide. In this study, we model, at the macroeconomic level, the impact of energy intake from different types of carbohydrates on the population's BMI (body mass index). We proceed in three steps. First, we develop a framework to analyse both the consumption choices between simple and complex carbohydrates and the effects of these choices on people health conditions. Second, we collect figures for 185 countries (over the period 2012-2014) regarding the shares of simple (sugar and sweetener) and complex (cereal) carbohydrates in each country's total dietary energy supply. Third, we use regression techniques to: (1) estimate the impact of these shares on the country's prevalence of obesity and being overweight; (2) compute for each country an indicator of dietary pattern based on the ratio between simple and complex carbohydrates, weighted by their estimated effects on the prevalence of obesity and being overweight; and (3) measure the elasticity of the prevalence of obesity and being overweight with respect to changes in both carbohydrate dietary pattern and income per capita. We find that unhealthy eating habits and the associated prevalence of excessive body fat accumulation tend to behave as a 'normal good' in low, medium- and high-HDI (Human Development Index) countries, but as an 'inferior good' in very high-HDI countries.
| S-EPMC5664675 | biostudies-literature
Project description:Adipocytes are key regulators of human metabolism, and their dysfunction in insulin signaling is central to metabolic diseases including type II diabetes mellitus (T2D). However, the progression of insulin resistance into T2D is still poorly understood. This limited understanding is due, in part, to the dearth of suitable models of insulin signaling in human adipocytes. Traditionally, adipocyte models fail to recapitulate in vivo insulin signaling, possibly due to exposure to supraphysiological nutrient and hormone conditions. We developed a protocol for hPSC-derived adipocytes that uses physiological nutrient conditions to produce a potent insulin response comparable to in vivo adipocytes. After systematic optimization, this protocol allows robust insulin-stimulated glucose uptake and transcriptional insulin response. Furthermore, exposure of sensitized adipocytes to physiological hyperinsulinemia dampens insulin-stimulated glucose uptake and dysregulates insulin-responsive transcription. Overall, our methodology provides a novel platform for the mechanistic study of insulin signaling and resistance using human pluripotent stem cell-derived adipocytes.
2022-06-17 | GSE201908 | GEO
Project description:Considering the immense challenge of preventing obesity, the time has come to reconceptualise the way we study the obesity development in childhood. The developmental cascade model offers a longitudinal framework to elucidate the way cumulative consequences and spreading effects of risk and protective factors, across and within biopsychosocial spheres and phases of development, can propel individuals towards obesity. In this article, we use a theory-driven model-building approach and a scoping review that included 310 published studies to propose a developmental cascade model of paediatric obesity. The proposed model provides a basis for testing hypothesised cascades with multiple intervening variables and complex longitudinal processes. Moreover, the model informs future research by resolving seemingly contradictory findings on pathways to obesity previously thought to be distinct (low self-esteem, consuming sugary foods, and poor sleep cause obesity) that are actually processes working together over time (low self-esteem causes consumption of sugary foods which disrupts sleep quality and contributes to obesity). The findings of such inquiries can aid in identifying the timing and specific targets of preventive interventions across and within developmental phases. The implications of such a cascade model of paediatric obesity for health psychology and developmental and prevention sciences are discussed.
| S-EPMC6324843 | biostudies-literature
Project description:Adipocytes are key regulators of human metabolism, and their dysfunction in insulin signaling is central to metabolic diseases including type II diabetes mellitus (T2D). However, the progression of insulin resistance into T2D is still poorly understood. This limited understanding is due, in part, to the dearth of suitable models of insulin signaling in human adipocytes. Traditionally, adipocyte models fail to recapitulate in vivo insulin signaling, possibly due to exposure to supraphysiological nutrient and hormone conditions. We developed a protocol for human pluripotent stem cell-derived adipocytes that uses physiological nutrient conditions to produce a potent insulin response comparable to in vivo adipocytes. After systematic optimization, this protocol allows robust insulin-stimulated glucose uptake and transcriptional insulin response. Furthermore, exposure of sensitized adipocytes to physiological hyperinsulinemia dampens insulin-stimulated glucose uptake and dysregulates insulin-responsive transcription. Overall, our methodology provides a novel platform for the mechanistic study of insulin signaling and resistance using human pluripotent stem cell-derived adipocytes.
| S-EPMC9205586 | biostudies-literature
Project description:Significance: Growth of distinctive blood vessels of granulation tissue is a central step in the post-developmental tissue remodeling. Even though lymphangiogenesis is a part of the regeneration process, the significance of the controlled restoration of lymphatic vessels has only recently been recognized. Recent Advances: Identification of lymphatic markers and growth factors paved the way for the exploration of the roles of lymphatic vessels in health and disease. Emerging pro-lymphangiogenic therapies use vascular endothelial growth factor (VEGF)-C to combat fluid retention disorders such as lymphedema and to enhance the local healing process. Critical Issues: The relevance of recently identified lymphatic functions awaits verification by their association with pathologic conditions. Further, despite a century of research, the complete etiology of secondary lymphedema, a fluid retention disorder directly linked to the lymphatic function, is not understood. Finally, the specificity of pro-lymphangiogenic therapy depends on VEGF-C transfection efficiency, dose exposure, and the age of the subject, factors that are difficult to standardize in a heterogeneous human population. Future Directions: Further research should reveal the role of lymphatic circulation in internal organs and connect its impairment with human diseases. Pro-lymphangiogenic therapies that aim at the acceleration of tissue healing should focus on the controlled administration of VEGF-C to increase their capillary specificity, whereas regeneration of collecting vessels might benefit from balanced maturation and differentiation of pre-existing lymphatics. Unique features of pre-nodal lymphatics, fault tolerance and functional hyperplasia of capillaries, may find applications outreaching traditional pro-lymphangiogenic therapies, such as immunomodulation or enhancement of subcutaneous grafting.
| S-EPMC6032671 | biostudies-other
Project description:MYC, a key member of the Myc-proto-oncogene family, is a universal transcription amplifier that regulates almost every physiological process in a cell including cell cycle, proliferation, metabolism, differentiation, and apoptosis. MYC interacts with several cofactors, chromatin modifiers, and regulators to direct gene expression. MYC levels are tightly regulated, and deregulation of MYC has been associated with numerous diseases including cancer. Understanding the comprehensive biology of MYC under physiological conditions is an utmost necessity to demark biological functions of MYC from its pathological functions. Here we review the recent advances in biological mechanisms, functions, and regulation of MYC. We also emphasize the role of MYC as a global transcription amplifier.
| S-EPMC10627926 | biostudies-literature
Project description:ObjectiveMultiple daily injections (MDI) therapy is the most common treatment for type 1 diabetes (T1D), consisting of long-acting insulin to cover fasting conditions and rapid-acting insulin to cover meals. Titration of long-acting insulin is needed to achieve satisfactory glycemia but is challenging due to inter-and intra-individual metabolic variability. In this work, a novel titration algorithm for long-acting insulin leveraging continuous glucose monitoring (CGM) and smart insulin pens (SIP) data is proposed.MethodsThe algorithm is based on a glucoregulatory model that describes insulin and meal effects on blood glucose fluctuations. The model is individualized on patient's data and used to extract the theoretical glucose curve in fasting conditions; the individualization step does not require any carbohydrate records. A cost function is employed to search for the optimal long-acting insulin dose to achieve the desired glycemic target in the fasting state. The algorithm was tested in two virtual studies performed within a validated T1D simulation platform, deploying different levels of metabolic variability (nominal and variance). The performance of the method was compared to that achieved with two published titration algorithms based on self-measured blood glucose (SMBG) records. The sensitivity of the algorithm to carbohydrate records was also analyzed.ResultsThe proposed method outperformed SMBG-based methods in terms of reduction of exposure to hypoglycemia, especially during the night period (0 am-6 am). In the variance scenario, during the night, an improvement in the time in the target glycemic range (70-180 mg/dL) from 69.0% to 86.4% and a decrease in the time in hypoglycemia (<70 mg/dL) from 10.7% to 2.6% was observed. Robustness analysis showed that the method performance is non-sensitive to carbohydrate records.ConclusionThe use of CGM and SIP in people with T1D using MDI therapy has the potential to inform smart insulin titration algorithms that improve glycemic control. Clinical studies in real-world settings are warranted to further test the proposed titration algorithm.SignificanceThis algorithm is a step towards a decision support system that improves glycemic control and potentially the quality of life, in a population of individuals with T1D who cannot benefit from the artificial pancreas system.
| S-EPMC8785345 | biostudies-literature