Periodic Reporting for period 1 - SMILED (Skeletal Muscle Inflammation: ambivalent roles in Exercise and Diabetes)
Reporting period: 2016-05-01 to 2018-04-30
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.
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).
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.