Disrupting rhythms: diet-induced obesity impairs diurnal rhythms in metabolic tissues

Mouse Models of Obesity to Study the Tumor-Immune Microenvironment

Obesity is associated with chronic, low-grade systemic inflammation and leads to changes in the immune microenvironment of various tissues. As a result, obesity is associated with increased risk of cancer and a worse prognosis in patients. Given the prevalence of obesity worldwide, understanding the fundamental biology governing the relationship between obesity and cancer is critical. In this chapter, we describe preclinical models of obesity that can be combined with standard tumor models and techniques to study the tumor-immune microenvironment. We also discuss important considerations when planning experiments involving these models.

Clock Genes, Inflammation and the Immune System-Implications for Diabetes, Obesity and Neurodegenerative Diseases

Inflammation is a common feature of several diseases, including obesity, diabetes and neurodegenerative disorders. Circadian clock genes are expressed and oscillate in many cell types such as macrophages, neurons and pancreatic β cells. During inflammation, these endogenous clocks control the temporal gating of cytokine production, the antioxidant response, chemokine attraction and insulin secretion, among other processes. Deletion of clock genes in macrophages or brain-resident cells induces a higher production of inflammatory cytokines and chemokines, and this is often accompanied by an increased oxidative stress. In the context of obesity and diabetes, a high-fat diet disrupts the function of clock genes in macrophages and in pancreatic β cells, contributing to inflammation and systemic insulin resistance. Recently, it has been shown that the administration of natural and synthetic ligands or pharmacological enhancers of the circadian clock function can selectively regulate the production and release of pro-inflammatory cytokines and improve the metabolic function in vitro and in vivo. Thus, a better understanding of the circadian regulation of the immune system could have important implications for the management of metabolic and neurodegenerative diseases.

Obesity alters the peripheral circadian clock in the aorta and microcirculation

OBJECTIVE

Perturbation of daily rhythm increases cardiovascular risk. The aim of this study was to determine whether obesity alters circadian gene expression and microvascular function in lean mice and obese (db/db) mice.

METHODS

Mice were subjected to normal LD or DD to alter circadian rhythm. Metabolic parameters and microvascular vasoreactivity were evaluated. Array studies were conducted in the am and pm cycles to assess the rhythmicity of the entire genomics. Rhythmic expression of specific clock genes (Bmal1, Clock, Npas2, Per1, Per2, and Cry1), clock output genes (dbp), and vascular relaxation-related genes (eNOS, GTPCH1) were assessed.

RESULTS

Obesity was associated with metabolic dysfunction and impaired endothelial dilation in the microvasculature. Circadian rhythm of gene expression was suppressed 80% in both macro- and microcirculations of obese mice. Circadian disruption with DD increased fasting serum glucose and HbA1c in obese but not lean mice. Endothelium-dependent dilation was attenuated in obese mice and in lean mice subjected to DD. Rhythmic expression of per1 and dbp was depressed in obesity. Expression of eNOS expression was suppressed and GTPCH1 lost rhythmic expression both in obesity and by constant darkness.

CONCLUSION

These results suggest that obesity reduces circadian gene expression in concert with impaired endothelial function. The causal relationship remains to be determined.

Functional Module Analysis for Gene Coexpression Networks with Network Integration

Network has been a general tool for studying the complex interactions between different genes, proteins, and other small molecules. Module as a fundamental property of many biological networks has been widely studied and many computational methods have been proposed to identify the modules in an individual network. However, in many cases, a single network is insufficient for module analysis due to the noise in the data or the tuning of parameters when building the biological network. The availability of a large amount of biological networks makes network integration study possible. By integrating such networks, more informative modules for some specific disease can be derived from the networks constructed from different tissues, and consistent factors for different diseases can be inferred. In this paper, we have developed an effective method for module identification from multiple networks under different conditions. The problem is formulated as an optimization model, which combines the module identification in each individual network and alignment of the modules from different networks together. An approximation algorithm based on eigenvector computation is proposed. Our method outperforms the existing methods, especially when the underlying modules in multiple networks are different in simulation studies. We also applied our method to two groups of gene coexpression networks for humans, which include one for three different cancers, and one for three tissues from the morbidly obese patients. We identified 13 modules with three complete subgraphs, and 11 modules with two complete subgraphs, respectively. The modules were validated through Gene Ontology enrichment and KEGG pathway enrichment analysis. We also showed that the main functions of most modules for the corresponding disease have been addressed by other researchers, which may provide the theoretical basis for further studying the modules experimentally.

Branched-chain amino acids in metabolic signalling and insulin resistance

Branched-chain amino acids (BCAAs) are important nutrient signals that have direct and indirect effects. Frequently, BCAAs have been reported to mediate antiobesity effects, especially in rodent models. However, circulating levels of BCAAs tend to be increased in individuals with obesity and are associated with worse metabolic health and future insulin resistance or type 2 diabetes mellitus (T2DM). A hypothesized mechanism linking increased levels of BCAAs and T2DM involves leucine-mediated activation of the mammalian target of rapamycin complex 1 (mTORC1), which results in uncoupling of insulin signalling at an early stage. A BCAA dysmetabolism model proposes that the accumulation of mitotoxic metabolites (and not BCAAs per se) promotes β-cell mitochondrial dysfunction, stress signalling and apoptosis associated with T2DM. Alternatively, insulin resistance might promote aminoacidaemia by increasing the protein degradation that insulin normally suppresses, and/or by eliciting an impairment of efficient BCAA oxidative metabolism in some tissues. Whether and how impaired BCAA metabolism might occur in obesity is discussed in this Review. Research on the role of individual and model-dependent differences in BCAA metabolism is needed, as several genes (BCKDHA, PPM1K, IVD and KLF15) have been designated as candidate genes for obesity and/or T2DM in humans, and distinct phenotypes of tissue-specific branched chain ketoacid dehydrogenase complex activity have been detected in animal models of obesity and T2DM.

How to fix a broken clock

Fortunate are those who rise out of bed to greet the morning light well rested with the energy and enthusiasm to drive a productive day. Others, however, depend on hypnotics for sleep and require stimulants to awaken lethargic bodies. Sleep/wake disruption is a common occurrence in healthy individuals throughout their lifespan and is also a comorbid condition to many diseases (neurodegenerative) and psychiatric disorders (depression and bipolar). There is growing concern that chronic disruption of the sleep/wake cycle contributes to more serious conditions including diabetes (type 2), cardiovascular disease, and cancer. A poorly functioning circadian system resulting in misalignments in the timing of clocks throughout the body may be at the root of the problem for many people. In this article we discuss environmental (light therapy) and lifestyle changes (scheduled meals, exercise, and sleep) as interventions to help fix a broken clock. We also discuss the challenges and potential for future development of pharmacological treatments to manipulate this key biological system.