A system model of the effects of exercise on plasma Interleukin-6 dynamics in healthy individuals: Role of skeletal muscle and adipose tissue

Glucagon-like peptide-1 and interleukin-6 interaction in response to physical exercise: An in-silico model in the framework of immunometabolism

BACKGROUND AND OBJECTIVE

Glucagon-like peptide 1 (GLP-1) is classically identified as an incretin hormone, secreted in response to nutrient ingestion and able to enhance glucose-stimulated insulin secretion. However, other stimuli, such as physical exercise, may enhance GLP-1 plasma levels, and this exercise-induced GLP-1 secretion is mediated by interleukin-6 (IL-6), a cytokine secreted by contracting skeletal muscle. The aim of the study is to propose a mathematical model of IL-6-induced GLP-1 secretion and kinetics in response to physical exercise of moderate intensity.

METHODS

The model includes the GLP-1 subsystem (with two pools: gut and plasma) and the IL-6 subsystem (again with two pools: skeletal muscle and plasma); it provides a parameter of possible clinical relevance representing the sensitivity of GLP-1 to IL-6 (k0). The model was validated on mean IL-6 and GLP-1 data derived from the scientific literature and on a total of 100 virtual subjects.

RESULTS

Model validation provided mean residuals between 0.0051 and 0.5493 pg⋅mL-1 for IL-6 (in view of concentration values ranging from 0.8405 to 3.9718 pg⋅mL-1) and between 0.0133 and 4.1540 pmol⋅L-1 for GLP-1 (in view of concentration values ranging from 0.9387 to 17.9714 pmol⋅L-1); a positive significant linear correlation (r = 0.85, p<0.001) was found between k0 and the ratio between areas under GLP-1 and IL-6 curve, over the virtual subjects.

CONCLUSIONS

The model accurately captures IL-6-induced GLP-1 kinetics in response to physical exercise.

Experimental-analytical approach to assessing mechanosensitive cartilage blood marker kinetics in healthy adults: dose-response relationship and interrelationship of nine candidate markers

Purpose: To determine the suitability of selected blood biomarkers of articular cartilage as mechanosensitive markers and to investigate the dose-response relationship between ambulatory load magnitude and marker kinetics in response to load. 

Methods: Serum samples were collected from 24 healthy volunteers before and at three time points after a 30-minute walking stress test performed on three test days. In each experimental session, one of three ambulatory loads was applied: 100% body weight (BW); 80%BW; 120%BW. Serum concentrations of COMP, MMP-3, MMP-9, ADAMTS-4, PRG-4, CPII, C2C and IL-6 were assessed using commercial enzyme-linked immunosorbent assays. A two-stage analytical approach was used to determine the suitability of a biomarker by testing the response to the stress test (criterion I) and the dose-response relationship between ambulatory load magnitude and biomarker kinetics (criterion II). 

Results. COMP, MMP-3 and IL-6 at all three time points after, MMP-9 at 30 and 60 minutes after, and ADAMTS-4 and CPII at immediately after the stress test showed an average response to load or an inter-individual variation in response to load of up to 25% of pre-test levels. The relation to load magnitude on average or an inter-individual variation in this relationship was up to 8% from load level to load level. There was a positive correlation for the slopes of the change-load relationship between COMP and MMP-3, and a negative correlation for the slopes between COMP, MMP-3 and IL-6 with MMP-9, and COMP with IL6. 

Conclusions: COMP, MMP-3, IL-6, MMP-9, and ADAMTS-4 warrant further investigation in the context of articular cartilage mechanosensitivity and its role in joint degeneration and OA. While COMP seems to be able to reflect a rapid response, MMP-3 seems to reflect a slightly longer lasting, but probably also more distinct response. MMP-3 showed also the strongest association with the magnitude of load.

Emulating complex simulations by machine learning methods

BACKGROUND

The aim of the present paper is to construct an emulator of a complex biological system simulator using a machine learning approach. More specifically, the simulator is a patient-specific model that integrates metabolic, nutritional, and lifestyle data to predict the metabolic and inflammatory processes underlying the development of type-2 diabetes in absence of familiarity. Given the very high incidence of type-2 diabetes, the implementation of this predictive model on mobile devices could provide a useful instrument to assess the risk of the disease for aware individuals. The high computational cost of the developed model, being a mixture of agent-based and ordinary differential equations and providing a dynamic multivariate output, makes the simulator executable only on powerful workstations but not on mobile devices. Hence the need to implement an emulator with a reduced computational cost that can be executed on mobile devices to provide real-time self-monitoring.

RESULTS

Similarly to our previous work, we propose an emulator based on a machine learning algorithm but here we consider a different approach which turn out to have better performances, indeed in terms of root mean square error we have an improvement of two order magnitude. We tested the proposed emulator on samples containing different number of simulated trajectories, and it turned out that the fitted trajectories are able to predict with high accuracy the entire dynamics of the simulator output variables. We apply the emulator to control the level of inflammation while leveraging on the nutritional input.

CONCLUSION

The proposed emulator can be implemented and executed on mobile health devices to perform quick-and-easy self-monitoring assessments.

Experimental-analytical approach to assessing mechanosensitive cartilage blood marker kinetics in healthy adults: dose-response relationship and interrelationship of nine candidate markers

Purpose: To determine the suitability of selected blood biomarkers of articular cartilage as mechanosensitive markers and to investigate the dose-response relationship between ambulatory load magnitude and marker kinetics in response to load.  Methods: Serum samples were collected from 24 healthy volunteers before and at three time points after a 30-minute walking stress test performed on three test days. In each experimental session, one of three ambulatory loads was applied: 100% body weight (BW); 80%BW; 120%BW. Serum concentrations of COMP, MMP-3, MMP-9, ADAMTS-4, PRG-4, CPII, C2C and IL-6 were assessed using commercial enzyme-linked immunosorbent assays. A two-stage analytical approach was used to determine the suitability of a biomarker by testing the response to the stress test (criterion I) and the dose-response relationship between ambulatory load magnitude and biomarker kinetics (criterion II).  Results. COMP, MMP-3 and IL-6 at all three time points after, MMP-9 at 30 and 60 minutes after, and ADAMTS-4 and CPII at immediately after the stress test showed an average response to load or an inter-individual variation in response to load of up to 25% of pre-test levels. The relation to load magnitude on average or an inter-individual variation in this relationship was up to 8% from load level to load level. There was a positive correlation for the slopes of the change-load relationship between COMP and MMP-3, and a negative correlation for the slopes between COMP, MMP-3 and IL-6 with MMP-9, and COMP with IL6.  Conclusions: COMP, MMP-3, IL-6, MMP-9, and ADAMTS-4 warrant further investigation in the context of articular cartilage mechanosensitivity and its role in joint degeneration and OA. While COMP seems to be able to reflect a rapid response, MMP-3 seems to reflect a slightly longer lasting, but probably also more distinct response. MMP-3 showed also the strongest association with the magnitude of load.

Interleukin-6 mediated exercise-induced alleviation of adiposity and hepatic steatosis in mice

INTRODUCTION

Exercise training has been shown to be the most effective strategy to combat obesity and non-alcoholic fatty liver disease. However, exercise promotes loss of adipose tissue mass and improves obesity-related hepatic steatosis through mechanisms that remain obscure.

RESEARCH DESIGN AND METHODS

To study the role of interleukin-6 (IL-6) in high-fat diet (HFD)-induced adiposity and hepatic steatosis during treadmill running, IL-6 knockout (IL-6 KO) mice and wild-type (WT) mice were randomly divided into lean, obese (fed a HFD) and trained obese groups (fed a HFD and exercise trained).

RESULTS

After 20 weeks of HFD feeding and 8 weeks of treadmill running, we found that exercise obviously reduced HFD-induced body weight gain, inhibited visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) expansion and almost completely reversed obesity-related intrahepatic fat accumulation in WT mice. However, IL-6 knockout (IL-6 KO) mice are refractory to the benefits of treadmill training on body weight, VAT and SAT mass elevation, and hepatic steatosis. Moreover, a panel of lipolytic-related and thermogenic-related genes, including ATGL, HSL and PGC-1α, was upregulated in the VAT and SAT of WT mice that received exercise training compared with untrained mice, which was not observed in IL-6 KO mice. In addition, exercise training resulted in a significant inhibition of hepatic peroxisome proliferator-activated receptor gamma (PPAR-γ) expression in WT mice, and these effects were not noted in IL-6 KO mice.

CONCLUSION

These results revealed that IL-6 is involved in the prevention of obesity and hepatic fat accumulation during exercise training. The mechanisms underlying these antiobesity effects may be associated with enhanced lipolysis and thermogenesis in white adipose tissue. The improvement in hepatic steatosis by exercise training may benefit from the marked inhibition of PPAR-γ expression by IL-6.

Potential predictors of type-2 diabetes risk: machine learning, synthetic data and wearable health devices

BACKGROUND

The aim of a recent research project was the investigation of the mechanisms involved in the onset of type 2 diabetes in the absence of familiarity. This has led to the development of a computational model that recapitulates the aetiology of the disease and simulates the immunological and metabolic alterations linked to type-2 diabetes subjected to clinical, physiological, and behavioural features of prototypical human individuals.

RESULTS

We analysed the time course of 46,170 virtual subjects, experiencing different lifestyle conditions. We then set up a statistical model able to recapitulate the simulated outcomes.

CONCLUSIONS

The resulting machine learning model adequately predicts the synthetic dataset and can, therefore, be used as a computationally-cheaper version of the detailed mathematical model, ready to be implemented on mobile devices to allow self-assessment by informed and aware individuals. The computational model used to generate the dataset of this work is available as a web-service at the following address: http://kraken.iac.rm.cnr.it/T2DM .

Exercise-induced immune system response: Anti-inflammatory status on peripheral and central organs

A wide array of molecular pathways has been investigated during the past decade in order to understand the mechanisms by which the practice of physical exercise promotes neuroprotection and reduces the risk of developing communicable and non-communicable chronic diseases. While a single session of physical exercise may represent a challenge for cell homeostasis, repeated physical exercise sessions will improve immunosurveillance and immunocompetence. Additionally, immune cells from the central nervous system will acquire an anti-inflammatory phenotype, protecting central functions from age-induced cognitive decline. This review highlights the exercise-induced anti-inflammatory effect on the prevention or treatment of common chronic clinical and experimental settings. It also suggests the use of pterins in biological fluids as sensitive biomarkers to follow the anti-inflammatory effect of physical exercise.

Effects of Aerobic Exercise Protocol on Genes Related to Insulin Resistance and Inflammation in the Pancreas of ob/ob Mice with NAFLD

Purpose

To evaluate the effect of 8 weeks of aerobic training on insulin resistance and inflammatory response in obese mice (ob/ob) with NAFLD.

Materials and Methods

Male ob/ob mice were randomly divided into sedentary (n=7) and trained (n=7) groups. Aerobic training consisted of 5 weekly sessions, 60 min per session at 60% of the maximum speed of the running test. Hepatic and pancreatic samples were collected to evaluate histological features and gene expression associated with insulin resistance and inflammatory response after 8-week experiment protocol. RNA was performed by TRIzol^®. PCR experiments were performed using the Rotor-Gene RG-3000. Parametric data were assessed by t-test, one-way ANOVA and Bonferroni test for multiple comparisons. Non-parametric data were assessed by the Mann-Whitney tests with Dunn's post-test of multiple comparisons. Histological analysis was assessed by chi-square test with Fisher's exact test. Significant variables were considered when p<0.05. All the analyses were performed by GraphPad Prism V6.0 software (GraphPad Software Inc.).

Results

Reductions in bodyweight (p = 0.008), weight evolution (p = 0.03), food intake (p <0.0001) and fat content were observed in trained group. Moreover, the trained group showed better results in peak velocity (p=0.03) physical effort tolerance (p=0.006) and distance (p=0.01). Gene expression showed differences in IL-10 (p=0.03) and GLUT-2 (p=0.03) in hepatic analysis, between groups. Pancreatic gene expression showed difference between groups in IRS-2 (p=0.004), GLUT-2 (p=0.03) and IL-10 (p=0.008) analysis. Also, the trained group showed lower values for interlobular fat and inflammatory infiltrate in histological analysis when compared to sedentary animals.

Conclusion

An 8-week physical training protocol was able to attenuate bodyweight gain, food intake and generate positive effects on gene expression related to insulin resistance and inflammation in both liver and pancreas of ob/ob mice.

Inflammatory cytokines IL-6 and TNF-α in patients with hip fracture

Mortality and remaining bedridden following the hip fracture surgery are not rare. We tried to measure the levels of inflammatory markers tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6) following the hip fracture surgery and compare their levels with controls. We aimed to show a relationship between the levels of these markers and post-operative mortality and walking capability.

INTRODUCTION

Osteoporosis is a condition, causing the hip fractures in the elderly. Hip fractures have a high rate of overall mortality up to 30% following the incident. Cytokines such as IL-6 and TNF-α are suggested to play a role in bone resorption and, thus, in the etiology of osteoporosis.

METHODS

Plasma levels of IL-6 and TNF-α were measured pre-operatively and on the first and second days after the surgery in 40 Turkish hip fracture patients. The levels of these cytokines were compared with 40 Turkish age-matched healthy controls. The levels of these cytokines were compared between the deceased and surviving patients, as well as the existence of walking capability following the surgery.

RESULTS

Significantly higher IL-6 levels were shown on the first and second days after the surgery (p = 0.005; p = 0.01, respectively). The overall death rate of our study group within the 2-year follow-up time was found to be 35%. No statistical significance was found in the means of 2-year follow-up mortality between the patients. Presence of walking capability did not differ between the patients, as well.

CONCLUSION

We demonstrated an association between IL-6 levels and hip fracture in our study group following the surgery. We also suggest that TNF-α and IL-6 levels are not related to the occurrence of death and walking capability after the surgery. However, these findings need further functional and clinical confirmation.

Modeling the Effect of High Calorie Diet on the Interplay between Adipose Tissue, Inflammation, and Diabetes

BACKGROUND

Type 2 diabetes (T2D) is a chronic metabolic disease potentially leading to serious widespread tissue damage. Human organism develops T2D when the glucose-insulin control is broken for reasons that are not fully understood but have been demonstrated to be linked to the emergence of a chronic inflammation. Indeed such low-level chronic inflammation affects the pancreatic production of insulin and triggers the development of insulin resistance, eventually leading to an impaired control of the blood glucose concentration. On the contrary, it is well-known that obesity and inflammation are strongly correlated.

AIM

In this study, we investigate in silico the effect of overfeeding on the adipose tissue and the consequent set up of an inflammatory state. We model the emergence of the inflammation as the result of adipose mass increase which, in turn, is a direct consequence of a prolonged excess of high calorie intake.

RESULTS

The model reproduces the fat accumulation due to excessive caloric intake observed in two clinical studies. Moreover, while showing consistent weight gains over long periods of time, it reveals a drift of the macrophage population toward the proinflammatory phenotype, thus confirming its association with fatness.

Personalizing physical exercise in a computational model of fuel homeostasis

The beneficial effects of physical activity for the prevention and management of several chronic diseases are widely recognized. Mathematical modeling of the effects of physical exercise in body metabolism and in particular its influence on the control of glucose homeostasis is of primary importance in the development of eHealth monitoring devices for a personalized medicine. Nonetheless, to date only a few mathematical models have been aiming at this specific purpose. We have developed a whole-body computational model of the effects on metabolic homeostasis of a bout of physical exercise. Built upon an existing model, it allows to detail better both subjects' characteristics and physical exercise, thus determining to a greater extent the dynamics of the hormones and the metabolites considered.