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Skeletal Muscle Inflammation: ambivalent roles in Exercise and Diabetes

Periodic Reporting for period 1 - SMILED (Skeletal Muscle Inflammation: ambivalent roles in Exercise and Diabetes)

Reporting period: 2016-05-01 to 2018-04-30

In Europe, 52 million people are living with diabetes and the world health organization estimates that it will be the 7th leading cause of death worldwide by 2030. Diabetes leads to severe complications such as cardiovascular events and certain forms of cancers and therefore constitutes an economic burden of unmanageable proportions. More than 90% of diabetic patients have type 2 diabetes (T2D), a complex multifactorial disease typically associated with obesity and sedentary lifestyle. Skeletal muscle is the major site of dietary glucose disposal and therefore a key player in the development of whole-body insulin resistance, the first step toward to the development of T2D. T2D is associated with chronic low-grade inflammation and muscle inflammation is emerging as a potential contributor to insulin resistance. Recent reports show that inflammatory immune cell numbers within muscle are elevated during obesity and I and others have demonstrated that muscle cells in vitro can mount inflammatory responses under metabolic challenges.
The overall aim of this proposal was to determine the interaction between inflammation and the metabolic response to exercise and T2D.
• Aim 1: Characterize and compare muscle inflammation in humans during exercise and T2D. Identify pathways specific to muscle which could be targetable to improve insulin sensitivity.
• Aim 2: Develop strategies to emulate diabetes and exercise in vitro and modulate inflammatory responses in order to improve insulin sensitivity or alleviate insulin resistance.
• Aim 3: Determine if and how skeletal muscle cells retain a memory of exercise or diabetes in vitro through epigenetic modifications and how this impacts on inflammation and insulin resistance.
Using biopsies, primary cells and publically available data, we characterized the gene response of human skeletal muscle to exercise and type 2 diabetes. A meta-analysis of 63 published exercise studies was performed and the database made public at www.metamex.eu. The statistical power from this approach allowed us to clearly separate the skeletal muscle response to acute versus chronic exercise training. Bioinformatics analyses revealed selective pathways activated by inactivity and various exercise types. This meta-analysis also shed light on the adverse response to exercise in metabolically impaired individuals. In parallel, we recruited type 2 diabetic volunteers who performed a single bout of aerobic exercise in the lab. We analyzed biopsies and plasma before and after the exercise and discovered that type 2 diabetic individuals had a selective inflammatory response not observed in control volunteers. The identification of this specific response has the potential to lead to specific inflammatory-based interventions to improve the response to exercise and metabolic parameters in metabolically impaired individuals.
In vitro, we developed models of “exercise in a dish” by contracting muscle with electrical pulse stimulation and models of “diabetes in a dish” by exposing cells to high levels of sugar or fat. These models allowed us to validate the data observed in human biopsies and more precisely define the molecular pathways involved. We discovered that cells grown in diabetes-like conditions or cells grown from type 2 diabetic individuals had an altered response to contraction, especially on inflammatory genes.
Overall, the data obtained during this MSCA fellowship expanded our understanding of the gene response of skeletal muscle to exercise and diabetes. We developed novel approaches like MetaMEx and advanced technologies and bioinformatics to identify novel targets. Many of these are currently under thorough examination for their potential as pharmacological interventions to enhance the benefits of exercise and improve metabolic health.
Using two complementary approaches, we precisely characterized the response of skeletal muscle to exercise in healthy and type 2 diabetic individuals. The first approach used bioinformatics and publically available date to generate the most comprehensive data base to date on skeletal muscle transcriptomic response to exercise and inactivity. This MetaMEx database allowed us to identify genes and pathways selectively altered in obese and/or type 2 diabetic individuals. The second approach was to recruit a well-controlled cohort of type 2 diabetic individuals and body weight matched healthy controls. They underwent a single bout of acute aerobic exercise and biopsy and blood were collected before and after exercise to analyze gene responses and cytokine levels. We identified a selective inflammatory response induced only in type 2 diabetic individuals after exercise.
Human skeletal muscle cells were collected from muscle biopsies and grown and differentiated into myotubes in vitro. We developed models of “exercise in a dish” by contracting muscle with electrical pulse stimulation and models of “diabetes in a dish” by exposing cells to high levels of sugar or fat. These models allowed us to validate the data observed in human biopsies and more precisely define the molecular pathways involved. We characterized the response to contraction in vitro vis a vis the exercise response in biopsies and found surprisingly very little overlap in the gene response, suggesting that contraction per se, in the absence of all the others elements of exercise (stress, blood flow, innervation, inflammation) only activates a limited number of genes. We also discovered that cells grown in diabetes-like conditions or cells grown from type 2 diabetic individuals had an altered response to contraction, especially on inflammatory genes.
Results were presented at national and international conferences (Swedish Strategic Research Program in Diabetes, European Association for the Study of Diabetes, Cell Symposium on Exercise Metabolism). Four original publications and 2 reviews are accepted or in preparation. My projects and scientific discoveries were posted on my personal website (www.nicopillon.com) Twitted (@NicoPillon) and the MetaMEx database distributed online (www.metamex.eu).
Our most striking result is the identification of a deregulated response of skeletal muscle to exercise in type 2 diabetic individuals. This has huge implications for metabolic health, since it opens new therapeutic perspectives targeting inflammatory pathways. The identification of new proteins sheds light on novel pharmacological targets to improve metabolic health. Overall, our discoveries might lead to improvements of the benefits of exercise in metabolically impaired individuals.
We went beyond the state of the art by designing a novel way to exploit publically available data. The MetaMEx analysis provides an innovative way to pool, compare and distribute all available exercise studies in a user-friendly way. Making sense of the massive amount of data generated every day in science is a challenge. Meta-analyses like MetaMEx will enhance the potential for future discoveries by increasing statistical power, promoting sharing of databases and scientific collaborations.
Summary of techniques and models used in the project and main outcomes