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Pre-Training Muscle Characteristics of Subjects Who Are Obese Determine How Well Exercise Training Will Improve Their Insulin Responsiveness.

ABSTRACT: Stuart, CA, Lee, ML, South, MA, Howell, MEA, Cartwright, BM, Ramsey, MW, and Stone, MH. Pre-training muscle characteristics of subjects who are obese determine how well exercise training will improve their insulin responsiveness. J Strength Cond Res 31(3): 798-808, 2017-Only half of prediabetic subjects who are obese who underwent exercise training without weight loss increased their insulin responsiveness. We hypothesized that those who improved their insulin responsiveness might have pretraining characteristics favoring a positive response to exercise training. Thirty nondiabetic subjects who were obese volunteered for 8 weeks of either strength training or endurance training. During training, subjects increased their caloric intake to prevent weight loss. Insulin responsiveness by euglycemic clamps and muscle fiber composition, and expression of muscle key biochemical pathways were quantified. Positive responders initially had 52% higher intermediate muscle fibers (fiber type IIa) with 27% lower slow-twitch fibers (type I) and 23% lower expression of muscle insulin receptors. Whether after weight training or stationary bike training, positive responders' fiber type shifted away from type I and type IIa fibers to an increased proportion of type IIx fibers (fast twitch). Muscle insulin receptor expression and glucose transporter type 4 (GLUT4) expression increased in all trained subjects, but these moderate changes did not consistently translate to improvement in whole-body insulin responsiveness. Exercise training of previously sedentary subjects who are obese can result in muscle remodeling and increased expression of key elements of the insulin pathway, but in the absence of weight loss, insulin sensitivity improvement was modest and limited to about half of the participants. Our data suggest rather than responders being more fit, they may have been less fit, only catching up to the other half of subjects who are obese whose insulin responsiveness did not increase beyond their pretraining baseline.

SUBMITTER: Stuart CA

PROVIDER: S-EPMC5195912 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Pre-Training Muscle Characteristics of Subjects Who Are Obese Determine How Well Exercise Training Will Improve Their Insulin Responsiveness.

Stuart Charles A CA Lee Michelle L ML South Mark A MA Howell Mary E A ME Cartwright Brian M BM Ramsey Michael W MW Stone Michael H MH

Journal of strength and conditioning research 20170301 3

Stuart, CA, Lee, ML, South, MA, Howell, MEA, Cartwright, BM, Ramsey, MW, and Stone, MH. Pre-training muscle characteristics of subjects who are obese determine how well exercise training will improve their insulin responsiveness. J Strength Cond Res 31(3): 798-808, 2017-Only half of prediabetic subjects who are obese who underwent exercise training without weight loss increased their insulin responsiveness. We hypothesized that those who improved their insulin responsiveness might have pretraini ...[more]

PMID: 27379957

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Project description:To examine the relationships between plasma and tissue markers of systemic and vascular inflammation and obesity and insulin resistance and determine the effects of aerobic exercise training plus weight loss (AEX+WL) and weight loss (WL) alone on these biomarkers.Prospective controlled study.Veterans Affairs Medical Center and University research setting.Overweight and obese sedentary postmenopausal women (N = 77).Six months, 3 d/wk AEX+WL (n = 37) or WL (n = 40).Total-body dual-energy X-ray absorptiometry, abdominal computed tomography, hyperinsulinemic-euglycemic clamps (a criterion standard method of assessing insulin sensitivity), adipose tissue biopsies (n = 28), and blood for homeostasis model assessment-insulin resistance, and soluble forms of intracellular adhesion molecule 1 (sICAM-1) and vascular cell adhesion molecule 1 (sVCAM-1), C-reactive protein (CRP), and serum amyloid A (SAA).Body weight (P < .001), percentage of fat (P < .001), visceral fat (P < .005), triglyceride levels (P < .001), and systolic blood pressure decreased comparably after WL and AEX+WL (P = .04). Maximal oxygen consumption increased 16% after AEX+WL (P < .001). Insulin resistance decreased in both groups (P = .005). Glucose utilization according to the clamp increased 10% (P = .04) with AEX+WL and 8% with WL (P = .07). AEX+WL decreased CRP by 29% (P < .001) and WL by 21% (P = .02). SAA levels decreased twice as much after AEX+WL (-19%, P = .02) as after WL (-9%, P = .08). Plasma sICAM-1 and sVCAM-1 levels did not change, but women with the greatest reduction in plasma sICAM-1 levels had the greatest reductions in fasting glucose (P = .02), insulin (P = .02), and insulin resistance (P = .004). Gluteal ICAM messenger ribonucleic acid levels decreased 27% after AEX+WL (P = .02) and did not change after WL.Obesity and insulin resistance worsen markers of systemic and vascular inflammation. A reduction in plasma sICAM-1 is important to improve insulin sensitivity. CRP, SAA, and tissue ICAM decrease with exercise and weight loss, suggesting that exercise training is a necessary component of lifestyle modification in obese postmenopausal women.

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)

Dataset Information

Pre-Training Muscle Characteristics of Subjects Who Are Obese Determine How Well Exercise Training Will Improve Their Insulin Responsiveness.

Publications

Pre-Training Muscle Characteristics of Subjects Who Are Obese Determine How Well Exercise Training Will Improve Their Insulin Responsiveness.

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