Modified Dark Matter in Galaxies and Galaxy Clusters

Modified Dark Matter (MDM) is a phenomenological model of dark matter, inspired by gravitational thermodynamics, that naturally accounts for the universal acceleration constant observed in galactic rotation curve data; a critical acceleration related to the cosmological constant, $\Lambda$, appears as a phenomenological manifestation of MDM. We show that the resulting mass profiles, which are sensitve to $\Lambda$, are consistent with observations at the galactic and galaxy cluster scales. Our results suggest that dark matter mass profiles contain information about the cosmological constant in a non-trivial way.Comment: To be published in the Proceedings of the Bahamas Advanced Study Institute and Conferences (BASIC

Variation in extracellular matrix genes is associated with weight regain after weight loss in a sex-specific manner

The extracellular matrix (ECM) of adipocytes is important for body weight regulation. Here, we investigated whether genetic variation in ECM-related genes is associated with weight regain among participants of the European DiOGenes study. Overweight and obese subjects (n = 469, 310 females, 159 males) were on an 8-week low-calorie diet with a 6-month follow-up. Body weight was measured before and after the diet, and after follow-up. Weight maintenance scores (WMS, regained weight as percentage of lost weight) were calculated based on the weight data. Genotype data were retrieved for 2903 SNPs corresponding to 124 ECM-related genes. Regression analyses provided us with six significant SNPs associated with the WMS in males: 3 SNPs in the POSTN gene and a SNP in the LAMB1, COL23A1, and FBLN5 genes. For females, 1 SNP was found in the FN1 gene. The risk of weight regain was increased by: the C/C genotype for POSTN in a co-dominant model (OR 8.25, 95 % CI 2.85-23.88) and the T/C-C/C genotype in a dominant model (OR 4.88, 95 % CI 2.35-10.16); the A/A genotype for LAMB1 both in a co-dominant model (OR 18.43, 95 % CI 2.35-144.63) and in a recessive model (OR 16.36, 95 % CI 2.14-124.9); the G/A genotype for COL23A1 in a co-dominant model (OR 3.94, 95 % CI 1.28-12.10), or the A-allele in a dominant model (OR 2.86, 95 % CI 1.10-7.49); the A/A genotype for FBLN5 in a co-dominant model (OR 13.00, 95 % CI 1.61-104.81); and the A/A genotype for FN1 in a recessive model (OR 2.81, 95 % CI 1.40-5.63). Concluding, variants of ECM genes are associated with weight regain after weight loss in a sex-specific manner

Diet Composition, Glucose Homeostasis, and Weight Regain in the YoYo Study

Based on several randomized clinical trials, it has been suggested that baseline glucose homeostasis interacts with the influence of diet composition on weight loss and weight loss maintenance. In this secondary analysis of the YoYo study, a study investigating predictors of weight loss maintenance, we tested the hypothesis that (self-selected) dietary carbohydrate and/or fibre intake interact with the glucose homeostasis parameters for weight loss maintenance. Sixty-one overweight or obese individuals lost around 10 kg of body weight on an energy-restricted diet and were then followed for 9 months. During this period, participants were advised to maintain their body weight and eat a healthy diet without further recommendations on calorie intake or diet composition. Contrary to our hypothesis, carbohydrate intake showed no positive association with weight regain after weight loss, and no interaction with baseline fasting glucose concentration was found. There was a non-significant negative association between fibre intake and weight regain (B = −0.274, standard error (SE) 0.158, p = 0.090), but again, no interaction with fasting plasma glucose was found. In conclusion, the data from the YoYo study do not support a role for baseline glucose homeostasis in determining the association between self-reported carbohydrate and/or fibre intake and weight regain after weight loss

Plasma levels of triglycerides and IL6 are associated with weight regain and fat mass expansion

CONTEXT: Long-term weight loss (WL) maintenance is the biggest challenge for overweight and obesity because of the almost unavoidable phenomenon of partial or even total weight regain (WR) after WL. OBJECTIVE: In the present study we investigated the relations of (the changes of) adipocyte size and other risk biomarkers with WR during the follow-up of the Yoyo dietary intervention. METHODS: In this randomized controlled study, 48 overweight/obese participants underwent a very-low-calorie diet to lose weight, followed by a weight-stable period of 4 weeks and a follow-up period of 9 months. Anthropometric measurements, adipocyte volume of abdominal subcutaneous adipose tissue, and plasma metabolic parameters (free fatty acids [FFAs], triglycerides [TGs], total cholesterol, glucose, insulin, homeostasis model assessment of insulin resistance [HOMA-IR], interleukin 6 [IL-6], angiotensin-converting enzyme [ACE] activity, retinol binding protein 4 [RBP4]) at the beginning and the end of follow-up were analyzed. RESULTS: Our results show that changes of TGs, IL-6, HOMA-IR, and ACE are significantly positively correlated with WR. Multiple linear regression analysis shows that only TG and IL-6 changes remained significantly correlated with WR and increased body fat mass. Moreover, the change in HOMA-IR was tightly correlated with the change in TGs. Surprisingly, change in adipocyte volume during follow-up was not correlated with WR nor with other factors, but positive correlations between adipocyte volume and HOMA-IR were found at the beginning and end of the follow-up. CONCLUSION: These results suggest that TGs and IL-6 are independently linked to WR via separate mechanisms, and that HOMA-IR and adipocyte volume may indirectly link to WR through the change of plasma TGs

Plasma levels of triglycerides and IL6 are associated with weight regain and fat mass expansion

Context Long-term weight loss (WL) maintenance is the biggest challenge for overweight and obesity because of the almost unavoidable phenomenon of partial or even total weight regain (WR) after WL. Objective In the present study we investigated the relations of (the changes of) adipocyte size and other risk biomarkers with WR during the follow-up of the Yoyo dietary intervention. Methods In this randomized controlled study, 48 overweight/obese participants underwent a very-low-calorie diet to lose weight, followed by a weight-stable period of 4 weeks and a follow-up period of 9 months. Anthropometric measurements, adipocyte volume of abdominal subcutaneous adipose tissue, and plasma metabolic parameters (free fatty acids [FFAs], triglycerides [TGs], total cholesterol, glucose, insulin, homeostasis model assessment of insulin resistance [HOMA-IR], interleukin 6 [IL-6], angiotensin-converting enzyme [ACE] activity, retinol binding protein 4 [RBP4]) at the beginning and the end of follow-up were analyzed. Results Our results show that changes of TGs, IL-6, HOMA-IR, and ACE are significantly positively correlated with WR. Multiple linear regression analysis shows that only TG and IL-6 changes remained significantly correlated with WR and increased body fat mass. Moreover, the change in HOMA-IR was tightly correlated with the change in TGs. Surprisingly, change in adipocyte volume during follow-up was not correlated with WR nor with other factors, but positive correlations between adipocyte volume and HOMA-IR were found at the beginning and end of the follow-up. Conclusion These results suggest that TGs and IL-6 are independently linked to WR via separate mechanisms, and that HOMA-IR and adipocyte volume may indirectly link to WR through the change of plasma TGs

Profiling cellular processes in adipose tissue during weight loss using time series gene expression

Obesity is a global epidemic identified as a major risk factor for multiple chronic diseases and, consequently, diet-induced weight loss is used to counter obesity. The adipose tissue is the primary tissue affected in diet-induced weight loss, yet the underlying molecular mechanisms and changes are not completely deciphered. In this study, we present a network biology analysis workflow which enables the profiling of the cellular processes affected by weight loss in the subcutaneous adipose tissue. Time series gene expression data from a dietary intervention dataset with two diets was analysed. Differentially expressed genes were used to generate co-expression networks using a method that capitalises on the repeat measurements in the data and finds correlations between gene expression changes over time. Using the network analysis tool Cytoscape, an overlap network of conserved components in the co-expression networks was constructed, clustered on topology to find densely correlated genes, and analysed using Gene Ontology enrichment analysis. We found five clusters involved in key metabolic processes, but also adipose tissue development and tissue remodelling processes were enriched. In conclusion, we present a flexible network biology workflow for finding important processes and relevant genes associated with weight loss, using a time series co-expression network approach that is robust towards the high inter-individual variation in humans

A computational model of postprandial adipose tissue lipid metabolism derived using human arteriovenous stable isotope tracer data

\u3cp\u3eGiven the association of disturbances in non-esterified fatty acid (NEFA) metabolism with the development of Type 2 Diabetes and Non-Alcoholic Fatty Liver Disease, computational models of glucose-insulin dynamics have been extended to account for the interplay with NEFA. In this study, we use arteriovenous measurement across the subcutaneous adipose tissue during a mixed meal challenge test to evaluate the performance and underlying assumptions of three existing models of adipose tissue metabolism and construct a new, refined model of adipose tissue metabolism. Our model introduces new terms, explicitly accounting for the conversion of glucose to glyceraldehye-3-phosphate, the postprandial influx of glycerol into the adipose tissue, and several physiologically relevant delays in insulin signalling in order to better describe the measured adipose tissues fluxes. We then applied our refined model to human adipose tissue flux data collected before and after a diet intervention as part of the Yoyo study, to quantify the effects of caloric restriction on postprandial adipose tissue metabolism. Significant increases were observed in the model parameters describing the rate of uptake and release of both glycerol and NEFA. Additionally, decreases in the model's delay in insulin signalling parameters indicates there is an improvement in adipose tissue insulin sensitivity following caloric restriction.\u3c/p\u3

A computational model of postprandial adipose tissue lipid metabolism derived using human arteriovenous stable isotope tracer data

Given the association of disturbances in non-esterified fatty acid (NEFA) metabolism with the development of Type 2 Diabetes and Non-Alcoholic Fatty Liver Disease, computational models of glucose-insulin dynamics have been extended to account for the interplay with NEFA. In this study, we use arteriovenous measurement across the subcutaneous adipose tissue during a mixed meal challenge test to evaluate the performance and underlying assumptions of three existing models of adipose tissue metabolism and construct a new, refined model of adipose tissue metabolism. Our model introduces new terms, explicitly accounting for the conversion of glucose to glyceraldehye-3-phosphate, the postprandial influx of glycerol into the adipose tissue, and several physiologically relevant delays in insulin signalling in order to better describe the measured adipose tissues fluxes. We then applied our refined model to human adipose tissue flux data collected before and after a diet intervention as part of the Yoyo study, to quantify the effects of caloric restriction on postprandial adipose tissue metabolism. Significant increases were observed in the model parameters describing the rate of uptake and release of both glycerol and NEFA. Additionally, decreases in the model’s delay in insulin signalling parameters indicates there is an improvement in adipose tissue insulin sensitivity following caloric restriction.</p