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Previous studies have shown that the elevated levels of circulating branched-chain amino acids (BCAAs) are associated with the development of insulin resistance and its complications, including obesity, type 2 diabetes, cardiovascular disease and some cancers. However, animal models that can mimic the metabolic state of chronically elevated BCAAs in humans are rare. Therefore, the aim of this study was to establish the above animal model and analyse the metabolic changes associated with high BCAA levels. Sixteen 8-week-old Sprague–Dawley (SD) rats were randomly divided into two groups and given either a high fructose diet or a normal diet. BCAA levels as well as blood glucose and lipid levels were measured at different time points of feeding. The mRNA expression levels of two key enzymes of BCAA catabolism, ACAD (acyl-CoA dehydrogenase) and BCKDH (branched-chain α-keto acid dehydrogenase), were measured by qPCR, and the protein expression levels of these two enzymes were analysed by immunohistochemistry. Finally, the metabolite expression differences between the two groups were analysed by Q300 metabolomics technology. Our study confirms that defects in the catabolic pathways of BCAAs lead to increased levels of circulating BCAAs, resulting in disorders of glucose and lipid metabolism characterized by insulin resistance by affecting metabolic pathways associated with amino acids and bile acids.
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Background
Obesity and arterial stiffness are strongly associated with cardiovascular disease; however, their relationship remains controversial.
Methods
Body mass index was measured using anthropometric evaluation, and visceral fat area was calculated using an absorptiometry scan.
Results
The data of 5309 participants were collected from NHANES (National Health and Nutrition Examination Survey) (2011–2018). Based on the normal-weight normal visceral fat group that was considered as a reference, ePWV increased in all other groups, with the obese grade 2 visceral obesity group increasing the most by 26.35 cm/s (95% CI: 13.52, 39.18, P < 0.001), followed by normal-weight visceral obesity group 24.43 cm/s (95% CI: 1.88, 46.98, P = 0.035), which was even higher than obese grade 1 visceral obesity (β: 21.16, 95% CI: 9.24, 33.07, P = 0.001), obese grade 2 normal visceral fat group (β: 13.8; 95% CI: 0.10, 27.5, P = 0.048) and overweight visceral obesity group (β: 10.23; 95% CI: 1.89, 18.57, P = 0.018). For the 10-year cardiovascular risk, the obese grade 2 visceral obesity group had a 9.56-fold increase in compared with the control (OR: 10.56, 95% CI: 4.06, 27.51, P < 0.0001). Normal-weight visceral obesity, obese grade 1 visceral obesity, and overweight visceral obesity groups increased by 8.03-fold (OR: 9.03, 95% CI: 2.66, 30.69; P < 0.001), 7.91-fold (OR: 8.91, 95% CI: 3.82, 20.79, P < 0.001), and 7.28-fold (OR: 8.28, 95% CI: 3.19, 21.46, P < 0.001). The risk was lower in the normal visceral fat group. Except for the obese grade 2 normal visceral fat group, there was no significant difference in other groups.
Conclusions
Normal-weight visceral obesity was associated with higher arterial stiffness and 10-year cardiovascular risk.
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Institute of Epidemiology and Medical Biometry, ZIBMT, Ulm University, Ulm, Germany
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Institute of Epidemiology and Medical Biometry, ZIBMT, Ulm University, Ulm, Germany
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Objective
To investigate the frequency, treatment, and outcome of patients with diabetes due to severe insulin resistance syndromes (SIRS).
Research Design and Methods
Based on data from the multicenter prospective Diabetes Registry DPV, we analyzed diagnosis, treatment, and outcome of 636,777 patients with diabetes from 1995 to 2022.
Results
Diabetes due to SIRS was documented in 67 cases (62.7% females), 25 (37%) had lipodystrophies (LD) and 42 (63%) had congenital defects of insulin signaling. The relative frequency compared to type 1 diabetes (T1D) was about 1:2300. Median age at diabetes diagnosis in patients with SIRS was 14.8 years (interquartile range (IQR) 12.8–33.8).
A total of 38 patients with SIRS (57%) received insulin and 34 (51%) other antidiabetics, mostly metformin. As high as 16% of patients with LD were treated with fibrates. Three out of eight patients with generalized LD (37.5%) were treated with metreleptin and one patient with Rabson–Mendenhall syndrome was treated with recombinant insulin-like growth factor 1.
The median glycated hemoglobin level at follow-up was 7.1% (54 mmol/mol). Patients with LD had higher triglycerides than patients with T1D and T2D (P < 0.001 and P = 0.022, respectively), and also significantly higher liver enzymes and lower high-density lipoprotein cholesterol than patients with T1D (P < 0.001).
Patients with insulin receptor disorders were significantly less likely to be treated with antihypertensive medication than patients with T2D (P = 0.042), despite having similar levels of hypertension.
Conclusions
Diabetes due to SIRS is rarely diagnosed and should be suspected in lean children or young adults without classical T1D. Awareness of cardiovascular risk factors in these patients should be raised.
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Obesity is a major cause of type 2 diabetes. Transition from obesity to type 2 diabetes manifests in the dysregulation of hormones controlling glucose homeostasis and inflammation. As metabolism is a dynamic process that changes across 24 h, we assessed diurnal rhythmicity in a panel of 10 diabetes-related hormones. Plasma hormones were analysed every 2 h over 24 h in a controlled laboratory study with hourly isocaloric drinks during wake. To separate effects of body mass from type 2 diabetes, we recruited three groups of middle-aged men: an overweight (OW) group with type 2 diabetes and two control groups (lean and OW). Average daily concentrations of glucose, triacylglycerol and all the hormones except visfatin were significantly higher in the OW group compared to the lean group (P < 0.001). In type 2 diabetes, glucose, insulin, C-peptide, glucose-dependent insulinotropic peptide and glucagon-like peptide-1 increased further (P < 0.05), whereas triacylglycerol, ghrelin and plasminogen activator inhibitor-1 concentrations were significantly lower compared to the OW group (P < 0.001). Insulin, C-peptide, glucose-dependent insulinotropic peptide and leptin exhibited significant diurnal rhythms in all study groups (P < 0.05). Other hormones were only rhythmic in 1 or 2 groups. In every group, hormones associated with glucose regulation (insulin, C-peptide, glucose-dependent insulinotropic peptide, ghrelin and plasminogen activator inhibitor-1), triacylglycerol and glucose peaked in the afternoon, whereas glucagon and hormones associated with appetite and inflammation peaked at night. Thus being OW with or without type 2 diabetes significantly affected hormone concentrations but did not affect the timing of the hormonal rhythms.
Leicester Diabetes Centre, University of Leicester, Leicester General Hospital, Leicester, UK
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Centre for Physical Activity in Health and Disease, Brunel University London, Uxbridge, UK
Division of Sport, Health and Exercise Sciences, Department of Life Sciences, Brunel University London, Uxbridge, UK
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A single exercise session can affect appetite-regulating hormones and suppress appetite. The effects of short, regular physical activity breaks across the day on appetite are unclear. This study investigated the effects of breaking up sitting with high-intensity physical activity vs a single bout of moderate-intensity exercise and prolonged sitting on appetite control. In this randomised crossover trial, 14 sedentary, inactive adults (7 women) completed 3, 8-h experimental conditions: (i) prolonged sitting (SIT); (ii) 30 min of moderate-intensity exercise followed by prolonged sitting (EX-SIT), and (iii) sitting with 2 min 32 s of high-intensity physical activity every hour (SIT-ACT). Physical activity energy expenditure was matched between EX-SIT and SIT-ACT. Subjective appetite was measured every 30 min with acylated ghrelin and total peptide-YY (PYY) measured hourly in response to two standardised test meals. An ad libitum buffet meal was provided at the end of each condition. Based on linear mixed model analysis, total area under the curve for satisfaction was 16% higher (P = 0.021) and overall appetite was 11% lower during SIT-ACT vs EX-SIT (P = 0.018), with no differences between SIT-ACT and SIT. Time series analysis indicated that SIT-ACT reduced subjective appetite during the majority of the post-lunch period compared with SIT and EX-SIT, with some of these effects reversed earlier in the afternoon (P < 0.05). Total PYY and acylated ghrelin did not differ between conditions. Relative energy intake was 760 kJ lower during SIT-ACT vs SIT (P = 0.024). High-intensity physical activity breaks may be effective in acutely suppressing appetite; yet, appetite-regulating hormones may not explain such responses.
