Metabolically healthy obesity: Facts and fantasies

Although obesity is typically associated with metabolic dysfunction and cardiometabolic diseases, some people with obesity are protected from many of the adverse metabolic effects of excess body fat and are considered metabolically healthy. However, there is no universally accepted definition of metabolically healthy obesity (MHO). Most studies define MHO as having either 0, 1, or 2 metabolic syndrome components, whereas many others define MHO using the homeostasis model assessment of insulin resistance (HOMA-IR). Therefore, numerous people reported as having MHO are not metabolically healthy, but simply have fewer metabolic abnormalities than those with metabolically unhealthy obesity (MUO). Nonetheless, a small subset of people with obesity have a normal HOMA-IR and no metabolic syndrome components. The mechanism(s) responsible for the divergent effects of obesity on metabolic health is not clear, but studies conducted in rodent models suggest that differences in adipose tissue biology in response to weight gain can cause or prevent systemic metabolic dysfunction. In this article, we review the definition, stability over time, and clinical outcomes of MHO, and discuss the potential factors that could explain differences in metabolic health in people with MHO and MUO - specifically, modifiable lifestyle factors and adipose tissue biology. Better understanding of the factors that distinguish people with MHO and MUO can produce new insights into mechanism(s) responsible for obesity-related metabolic dysfunction and disease

Differences in glucose control, insulin sensitivity, and body composition between metabolically healthy and unhealthy people with obesity

Poster presented at the 2017 Health Sciences Research Day which was organized and sponsored by the University of Missouri School of Medicine Research Council and held on November 9, 2017.Obesity is a significant risk factor for cardiometabolic complications, including type 2 diabetes and cardiovascular disease. However, approximately 25% of individuals with obesity are seemingly protected from these complications (Wildman et al. Arch Intern Med, 168, 1617-24, 2008). The purpose of this study was to provide a careful characterization of body composition and metabolic function in people who are: (i) lean and metabolically normal (MNL); (ii) obese and metabolically-normal (MN)); and (iii) obese and metabolically-abnormal (MAO). (Introduction & study aims) Although the glycemic responses of MNL individuals demonstrate a "metabolically healthy" state, more rigorous measures of insulin sensitivity show insulin resistance in this population, demonstrating people with MNO are insulin-resistant with respect to glucose metabolism but are able to maintain normal glycemic control by increased insulin secretion. Adipose tissue distribution is a marker of metabolic health in people with obesity, as greater intra-abdominal adipose tissue volume and intrahepatic triglyceride content are associated with metabolic dysfunction

β Cell function and plasma insulin clearance in people with obesity and different glycemic status

BackgroundIt is unclear how excess adiposity and insulin resistance affect β cell function, insulin secretion, and insulin clearance in people with obesity.MethodsWe used a hyperinsulinemic-euglycemic clamp procedure and a modified oral glucose tolerance test to evaluate the interrelationships among obesity, insulin sensitivity, insulin kinetics, and glycemic status in 5 groups of individuals: normoglycemic lean and obese individuals with (a) normal fasting glucose and normal glucose tolerance (Ob-NFG-NGT), (b) NFG and impaired glucose tolerance (Ob-NFG-IGT), (c) impaired fasting glucose and IGT (Ob-IFG-IGT), or (d) type 2 diabetes (Ob-T2D).ResultsGlucose-stimulated insulin secretion (GSIS), an assessment of β cell function, was greater in the Ob-NFG-NGT and Ob-NFG-IGT groups than in the lean group, even when insulin sensitivity was matched in the obese and lean groups. Insulin sensitivity, not GSIS, was decreased in the Ob-NFG-IGT group compared with the Ob-NFG-NGT group, whereas GSIS, not insulin sensitivity, was decreased in the Ob-IFG-IGT and Ob-T2D groups compared with the Ob-NFG-NGT and Ob-NFG-IGT groups. Insulin clearance was directly related to insulin sensitivity and inversely related to the postprandial increase in insulin secretion and plasma insulin concentration.ConclusionIncreased adiposity per se, not insulin resistance, enhanced insulin secretion in people with obesity. The obesity-induced increase in insulin secretion, in conjunction with a decrease in insulin clearance, sufficiently raised the plasma insulin concentrations needed to maintain normoglycemia in individuals with moderate, but not severe, insulin resistance. A deterioration in β cell function, not a decrease in insulin sensitivity, was a determinant of IFG and ultimately leads to T2D.CLINICAL TRIALS REGISTRATIONClinicalTrials.gov NCT02706262, NCT04131166, and NCT01977560.FUNDINGNIH (P30 DK056341, P30 DK020579, and UL1 TR000448); American Diabetes Association (1-18-ICTS-119); Longer Life Foundation; Pershing Square Foundation; and Washington University-Centene ARCH Personalized Medicine Initiative (P19-00559)

Statistics of soliton-bearing systems with additive noise

We present a consistent method to calculate the probability distribution of soliton parameters in systems with additive noise. Even though a weak noise is considered, we are interested in probabilities of large fluctuations (generally non-Gaussian) which are beyond perturbation theory. Our method is a further development of the instanton formalism (method of optimal fluctuation) based on a saddle-point approximation in the path integral. We first solve a fundamental problem of soliton statistics governing by noisy Nonlinear Schr\"odinger Equation (NSE). We then apply our method to optical soliton transmission systems using signal control elements (filters, amplitude and phase modulators).Comment: 4 pages. Submitted to PR

Towards multireference equivalents of the G2 and G3 methods

The effect of replacing the standard single-determinant reference wave functions in variants of G2 and G3 theory by multireference (MR) wave functions based on a full-valence complete active space has been investigated. Twelve methods of this type have been introduced and comparisons, based on a slightly reduced G2-1 test set, are made both internally and with the equivalent single-reference methods. We use CASPT2 as the standard MR-MP2 method and MRCl+Q as the higher correlation procedure in these calculations. We find that MR-G2(MP2,SVP), MR-G2(MP2), and MR-G3(MP2) perform comparably with their single-reference analogs, G2(MP2,SVP), G2(MP2), and G3(MP2), with mean absolute deviations (MADs) from the experimental data of 1.41, 1.54, and 1.23 kcal mol−1, compared with 1.60, 1.59, and 1.19 kcal mol−1, respectively. The additivity assumptions in the MR-Gn methods have been tested by carrying out MR-G2/MRCI+Q and MR-G3/MRCI+Q calculations, which correspond to large-basis-set MRCI+Q+ZPVE+HLC calculations. These give MADs of 1.84 and 1.58 kcal mol−1, respectively, i.e., the agreement with experiment is somewhat worse than that obtained with the MR-G2(MP2) and MR-G3(MP2) methods. In a third series of calculations, we have examined pure MP2 and MR-MP2 analogs of the G2 and G3 procedures by carrying out large-basis-set MP2 and CASPT2(+ZPVE+HLC) calculations. The resultant methods, which we denote G2/MP2, G3/MP2, MR-G2/MP2, and MR-G3/MP2, give MADs of 4.19, 3.36, 2.01, and 1.66 kcal mol−1, respectively. Finally, we have examined the effect of using MCQDPT2 in place of CASPT2 in five of our MR-Gn procedures, and find that there is a small but consistent deterioration in performance. Our calculations suggest that the MR-G3(MP2) and MR-G3/MP2 procedures may be useful in situations where a multireference approach is desirable.The authors would also like to thank the National Science Foundation International Division for providing travel funds to ~M.S.G. and M.A.F.! and the National Science Foundation Chemistry Division for supporting the research

Effect of dietary n‐3 PUFA supplementation on the muscle transcriptome in older adults

Dietary fish oil‐derived n‐3 PUFA supplementation can increase muscle mass, reduce oxygen demand during physical activity, and improve physical function (muscle strength and power, and endurance) in people. The results from several studies conducted in animals suggest that the anabolic and performance‐enhancing effects of n‐3 PUFA are at least in part transcriptionally regulated. The effect of n‐3 PUFA therapy on the muscle transcriptome in people is unknown. In this study, we used muscle biopsy samples collected during a recently completed randomized controlled trial that found that n‐3 PUFA therapy increased muscle mass and function in older adults to provide a comprehensive assessment of the effect of n‐3 PUFA therapy on the skeletal muscle gene expression profile in these people. Using the microarray technique, we found that several pathways involved in regulating mitochondrial function and extracellular matrix organization were increased and pathways related to calpain‐ and ubiquitin‐mediated proteolysis and inhibition of the key anabolic regulator mTOR were decreased by n‐3 PUFA therapy. However, the effect of n‐3 PUFA therapy on the expression of individual genes involved in regulating mitochondrial function and muscle growth, assessed by quantitative RT‐PCR, was very small. These data suggest that n‐3 PUFA therapy results in small but coordinated changes in the muscle transcriptome that may help explain the n‐3 PUFA‐induced improvements in muscle mass and function