Exercise and Esr1 Control Mitochondrial Content and Function to Regulate Adiposity

Mechanisms that underlie adipose tissue remodeling to enhance metabolic health in response to exercise training remain inadequately understood. PURPOSE: We utilized mouse genetics and human GWAS to determine the impact of exercise training on mitochondrial DNA copy number, and interrogate the relationship between Esr1 and adipose tissue health. METHODS: We performed RNAseq on adipose tissue from 100 strains of inbred mice following exercise training and determined mitochondrial content by qPCR. We performed deep phenotyping of mice harboring conditional Esr1 overexpression selectively in adipose tissue. Adipose specific Esr1 overexpression and control mice were fed a high fat diet and placed in metabolic chambers to interrogate the effects of Esr1 on whole body metabolism. RESULTS: We determined that exercise training significantly increased adipose tissue mtDNA content in mouse and man and that increased mitochondrial content correlated with reduced adiposity. Adipocyte health was associated with increased expression of transcripts involved in mitochondrial cristae formation including OPA1, Polg1, and Dnm1l. Since Esr1 is a transcription factor negatively associated with adipose tissue mass, and since deletion of Esr1 disrupts mitochondrial function and reduces expression of Polg1, OPA1, and Dnm1l, we interrogated in impact of conditional Esr1 overexpression on mitochondrial function and adipose tissue health. Adipocyte-specific Esr1 overexpression increased expression of mitochondrial gene targets, increased mtDNA copy number and mitochondrial respiration, and enhanced whole body energy expenditure of animals challenged by high fat diet feeding. Adipocyte-specific Esr1 overexpression protected mice against HFD-induced obesity. CONCLUSION: Exercise promotes remodeling of adipose tissue mitochondria and is associated with fat mass reduction. Overexpression of Esr1 drives a similar adipose tissue remodeling and weight loss as exercise training, and protects against adipose tissue weight gain in the context of overnutrition. These data suggest that exercise responsive transcripts in adipose tissue can be selectively targeted to enhance weight loss and improve metabolic health

Breaking Patterns of Environmentally Influenced Disease for Health Risk Reduction: Immune Perspectives

Diseases rarely, if ever, occur in isolation. Instead, most represent part of a more complex web or “pattern� of conditions that are connected via underlying biological mechanisms and processes, emerge across a lifetime, and have been identified with the aid of large medical databases. Objective We have described how an understanding of patterns of disease may be used to develop new strategies for reducing the prevalence and risk of major immune-based illnesses and diseases influenced by environmental stimuli. Findings Examples of recently defined patterns of diseases that begin in childhood include not only metabolic syndrome, with its characteristics of inflammatory dysregulation, but also allergic, autoimmune, recurrent infection, and other inflammatory patterns of disease. The recent identification of major immune-based disease patterns beginning in childhood suggests that the immune system may play an even more important role in determining health status and health care needs across a lifetime than was previously understood. Conclusions Focusing on patterns of disease, as opposed to individual conditions, offers two important venues for environmental health risk reduction. First, prevention of developmental immunotoxicity and pediatric immune dysfunction can be used to act against multiple diseases. Second, pattern-based treatment of entryway diseases can be tailored with the aim of disrupting the entire disease pattern and reducing the risk of later-life illnesses connected to underlying immune dysfunction. Disease-pattern–based evaluation, prevention, and treatment will require a change from the current approach for both immune safety testing and pediatric disease management

Tissue-selective estrogen complexes with bazedoxifene prevent metabolic dysfunction in female mice

Pairing the selective estrogen receptor modulator bazedoxifene (BZA) with estrogen as a tissue-selective estrogen complex (TSEC) is a novel menopausal therapy. We investigated estrogen, BZA and TSEC effects in preventing diabetisity in ovariectomized mice during high-fat feeding. Estrogen, BZA or TSEC prevented fat accumulation in adipose tissue, liver and skeletal muscle, and improved insulin resistance and glucose intolerance without stimulating uterine growth. Estrogen, BZA and TSEC improved energy homeostasis by increasing lipid oxidation and energy expenditure, and promoted insulin action by enhancing insulin-stimulated glucose disposal and suppressing hepatic glucose production. While estrogen improved metabolic homeostasis, at least partially, by increasing hepatic production of FGF21, BZA increased hepatic expression of Sirtuin1, PPARα and AMPK activity. The metabolic benefits of BZA were lost in estrogen receptor-α deficient mice. Thus, BZA alone or in TSEC produces metabolic signals of fasting and caloric restriction and improves energy and glucose homeostasis in female mice

Insulin Resistance and Altered Systemic Glucose Metabolism in Mice Lacking Nur77

OBJECTIVE: Nur77 is an orphan nuclear receptor with pleotropic functions. Previous studies have identified Nur77 as a transcriptional regulator of glucose utilization genes in skeletal muscle and gluconeogenesis in liver. However, the net functional impact of these pathways is unknown. To examine the consequence of Nur77 signaling for glucose metabolism in vivo, we challenged Nur77 null mice with high-fat feeding. RESEARCH DESIGN AND METHODS: Wild-type and Nur77 null mice were fed a high-fat diet (60% calories from fat) for 3 months. We determined glucose tolerance, tissue-specific insulin sensitivity, oxygen consumption, muscle and liver lipid content, muscle insulin signaling, and expression of glucose and lipid metabolism genes. RESULTS: Mice with genetic deletion of Nur77 exhibited increased susceptibility to diet-induced obesity and insulin resistance. Hyperinsulinemic-euglycemic clamp studies revealed greater high-fat diet–induced insulin resistance in both skeletal muscle and liver of Nur77 null mice compared with controls. Loss of Nur77 expression in skeletal muscle impaired insulin signaling and markedly reduced GLUT4 protein expression. Muscles lacking Nur77 also exhibited increased triglyceride content and accumulation of multiple even-chained acylcarnitine species. In the liver, Nur77 deletion led to hepatic steatosis and enhanced expression of lipogenic genes, likely reflecting the lipogenic effect of hyperinsulinemia. CONCLUSIONS: Collectively, these data demonstrate that loss of Nur77 influences systemic glucose metabolism and highlight the physiological contribution of muscle Nur77 to this regulatory pathway.National Institutes of Health (HD-00850, DK-081683-01, DK-30425, HL030568); American Diabetes Associatio

A statistical framework to evaluate virtual screening

<p>Abstract</p> <p>Background</p> <p>Receiver operating characteristic (ROC) curve is widely used to evaluate virtual screening (VS) studies. However, the method fails to address the "early recognition" problem specific to VS. Although many other metrics, such as RIE, BEDROC, and pROC that emphasize "early recognition" have been proposed, there are no rigorous statistical guidelines for determining the thresholds and performing significance tests. Also no comparisons have been made between these metrics under a statistical framework to better understand their performances.</p> <p>Results</p> <p>We have proposed a statistical framework to evaluate VS studies by which the threshold to determine whether a ranking method is better than random ranking can be derived by bootstrap simulations and 2 ranking methods can be compared by permutation test. We found that different metrics emphasize "early recognition" differently. BEDROC and RIE are 2 statistically equivalent metrics. Our newly proposed metric SLR is superior to pROC. Through extensive simulations, we observed a "seesaw effect" – overemphasizing early recognition reduces the statistical power of a metric to detect true early recognitions.</p> <p>Conclusion</p> <p>The statistical framework developed and tested by us is applicable to any other metric as well, even if their exact distribution is unknown. Under this framework, a threshold can be easily selected according to a pre-specified type I error rate and statistical comparisons between 2 ranking methods becomes possible. The theoretical null distribution of SLR metric is available so that the threshold of SLR can be exactly determined without resorting to bootstrap simulations, which makes it easy to use in practical virtual screening studies.</p

Role of Central Nervous System Glucagon-Like Peptide-1 Receptors in Enteric Glucose Sensing

OBJECTIVE—Ingested glucose is detected by specialized sensors in the enteric/hepatoportal vein, which send neural signals to the brain, which in turn regulates key peripheral tissues. Hence, impairment in the control of enteric-neural glucose sensing could contribute to disordered glucose homeostasis. The aim of this study was to determine the cells in the brain targeted by the activation of the enteric glucose-sensing system

Sarcopenia Exacerbates Obesity-Associated Insulin Resistance and Dysglycemia: Findings from the National Health and Nutrition Examination Survey III

Sarcopenia often co-exists with obesity, and may have additive effects on insulin resistance. Sarcopenic obese individuals could be at increased risk for type 2 diabetes. We performed a study to determine whether sarcopenia is associated with impairment in insulin sensitivity and glucose homeostasis in obese and non-obese individuals.We performed a cross-sectional analysis of National Health and Nutrition Examination Survey III data utilizing subjects of 20 years or older, non-pregnant (N = 14,528). Sarcopenia was identified from bioelectrical impedance measurement of muscle mass. Obesity was identified from body mass index. Outcomes were homeostasis model assessment of insulin resistance (HOMA IR), glycosylated hemoglobin level (HbA1C), and prevalence of pre-diabetes (6.0≤ HbA1C<6.5 and not on medication) and type 2 diabetes. Covariates in multiple regression were age, educational level, ethnicity and sex.Sarcopenia was associated with insulin resistance in non-obese (HOMA IR ratio 1.39, 95% confidence interval (CI) 1.26 to 1.52) and obese individuals (HOMA-IR ratio 1.16, 95% CI 1.12 to 1.18). Sarcopenia was associated with dysglycemia in obese individuals (HbA1C ratio 1.021, 95% CI 1.011 to 1.043) but not in non-obese individuals. Associations were stronger in those under 60 years of age. We acknowledge that the cross-sectional study design limits our ability to draw causal inferences.Sarcopenia, independent of obesity, is associated with adverse glucose metabolism, and the association is strongest in individuals under 60 years of age, which suggests that low muscle mass may be an early predictor of diabetes susceptibility. Given the increasing prevalence of obesity, further research is urgently needed to develop interventions to prevent sarcopenic obesity and its metabolic consequences

VDA, a Method of Choosing a Better Algorithm with Fewer Validations

The multitude of bioinformatics algorithms designed for performing a particular computational task presents end-users with the problem of selecting the most appropriate computational tool for analyzing their biological data. The choice of the best available method is often based on expensive experimental validation of the results. We propose an approach to design validation sets for method comparison and performance assessment that are effective in terms of cost and discrimination power