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Evaluating the evidence for macrophage presence in skeletal muscle and its relation to insulin resistance in obese mice and humans: a systematic review protocol.

ABSTRACT: The current global rates of obesity and type 2 diabetes are staggering. In order to implement effective management strategies, it is imperative to understand the mechanisms of obesity-induced insulin resistance and diabetes. Macrophage infiltration and inflammation of the adipose tissue in obesity is a well-established paradigm, yet the role of macrophages in muscle inflammation, insulin resistance and diabetes is not adequately studied. In this systematic review, we will examine the evidence for the presence of macrophages in skeletal muscle of obese humans and mice, and will assess the association between muscle macrophages and insulin resistance. We will identify published studies that address muscle macrophage content and phenotype, and its association with insulin resistance. We will search MEDLINE/PubMed, EMBASE, and Web of Science for eligible studies. Grey literature will be searched in ProQuest. Quality assessment will be conducted using the Systematic Review Centre for Laboratory Animal Experimentation risk of bias Tool for animal studies.The findings of this systematic review will shed light on immune-metabolic crosstalk in obesity, and allow the consideration of targeted therapies to modulate muscle macrophages in the treatment and prevention of diabetes. The review will be published in a peer-reviewed journal and presented at conferences.

SUBMITTER: Bhatt M

PROVIDER: S-EPMC5549391 | biostudies-other | 2017 Aug

REPOSITORIES: biostudies-other

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Project description:The obese people with abnormal BMI are predisposed to insulin resistance and diabetes. At the same time, human subjects with obesity and high BMI that are otherwise insulin sensitive are an interesting group to study the underlying gene expression patterns which provide them with such protective phenotype. Objective: Insulin resistance (IR) is one of the earliest predictors of type 2 diabetes. However, diagnosis of IR is limited. High fat fed mouse models provide key insights into IR. We hypothesized that early features of IR are associated with persistent changes in gene expression (GE) and endeavoured to (a) develop novel methods for improving signal:noise in analysis of human GE using mouse models; (b) identify a GE motif that accurately diagnoses IR in humans; and (c) identify novel biology associated with IR in humans. Methods: We integrated human muscle GE data with longitudinal mouse GE data and developed an unbiased three-level cross-species analysis platform (single-gene, gene-set and networks) to generate a gene expression motif (GEM) indicative of IR. A logistic regression classification model validated GEM in 3 independent human datasets (n =115). Results: This GEM of 93 genes substantially improved diagnosis of IR compared to routine clinical measures across multiple independent datasets. Individuals misclassified by GEM possessed other metabolic features raising the possibility that they represent a separate metabolic subclass. The GEM was enriched in pathways previously implicated in insulin action and revealed novel associations between β-catenin and Jak1 and IR. Functional analyses using small molecule inhibitors showed an important role for these proteins in insulin action. Conclusions: This study shows that systems approaches for identifying molecular signatures provides a powerful way to stratify individuals into discrete metabolic groups. Moreover, we speculate that the β-catenin pathway may represent a novel biomarker for IR in humans that warrant future investigation.

Project description:The obese people with abnormal BMI are predisposed to insulin resistance and diabetes. At the same time, human subjects with obesity and high BMI that are otherwise insulin sensitive are an interesting group to study the underlying gene expression patterns which provide them with such protective phenotype. Objective: Insulin resistance (IR) is one of the earliest predictors of type 2 diabetes. However, diagnosis of IR is limited. High fat fed mouse models provide key insights into IR. We hypothesized that early features of IR are associated with persistent changes in gene expression (GE) and endeavoured to (a) develop novel methods for improving signal:noise in analysis of human GE using mouse models; (b) identify a GE motif that accurately diagnoses IR in humans; and (c) identify novel biology associated with IR in humans. Methods: We integrated human muscle GE data with longitudinal mouse GE data and developed an unbiased three-level cross-species analysis platform (single-gene, gene-set and networks) to generate a gene expression motif (GEM) indicative of IR. A logistic regression classification model validated GEM in 3 independent human datasets (n =115). Results: This GEM of 93 genes substantially improved diagnosis of IR compared to routine clinical measures across multiple independent datasets. Individuals misclassified by GEM possessed other metabolic features raising the possibility that they represent a separate metabolic subclass. The GEM was enriched in pathways previously implicated in insulin action and revealed novel associations between Î²-catenin and Jak1 and IR. Functional analyses using small molecule inhibitors showed an important role for these proteins in insulin action. Conclusions: This study shows that systems approaches for identifying molecular signatures provides a powerful way to stratify individuals into discrete metabolic groups. Moreover, we speculate that the Î²-catenin pathway may represent a novel biomarker for IR in humans that warrant future investigation. Gene expression from muscle biopsies of Lean, Obese insulin sensitive (OIS), Obese insulin resistant (OIR) and obese T2D patients (T2D) were compared for differential expression between the groups (n=7 in each group)

Project description:ContextObesity is associated with insulin-resistance (IR), the key feature of type 2 diabetes. Although chronic low-grade inflammation has been identified as a central effector of IR development, it has never been investigated simultaneously at systemic level and locally in skeletal muscle and adipose tissue in obese humans characterized for their insulin sensitivity.ObjectivesWe compared metabolic parameters and inflammation at systemic and tissue levels in normal-weight and obese subjects with different insulin sensitivity to better understand the mechanisms involved in IR development.Methods30 post-menopausal women were classified as normal-weight insulin-sensitive (controls, CT) and obese (grade I) insulin-sensitive (OIS) or insulin-resistant (OIR) according to their body mass index and homeostasis model assessment of IR index. They underwent a hyperinsulinemic-euglycemic clamp, blood sampling, skeletal muscle and subcutaneous adipose tissue biopsies, an activity questionnaire and a self-administrated dietary recall. We analyzed insulin sensitivity, inflammation and IR-related parameters at the systemic level. In tissues, insulin response was assessed by P-Akt/Akt expression and inflammation by macrophage infiltration as well as cytokines and IκBα expression.ResultsSystemic levels of lipids, adipokines, inflammatory cytokines, and lipopolysaccharides were equivalent between OIS and OIR subjects. In subcutaneous adipose tissue, the number of anti-inflammatory macrophages was higher in OIR than in CT and OIS and was associated with higher IL-6 level. Insulin induced Akt phosphorylation to the same extent in CT, OIS and OIR. In skeletal muscle, we could not detect any inflammation even though IκBα expression was lower in OIR compared to CT. However, while P-Akt/Akt level increased following insulin stimulation in CT and OIS, it remained unchanged in OIR.ConclusionOur results show that systemic IR occurs without any change in systemic and tissues inflammation. We identified a muscle defect in insulin response as an early mechanism of IR development in grade I obese post-menopausal women.

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Evaluating the evidence for macrophage presence in skeletal muscle and its relation to insulin resistance in obese mice and humans: a systematic review protocol.

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