BackgroundThe sequence of events leading to the development of insulin resistance (IR) as well as the underlying pathophysiological mechanisms are incompletely understood. As reductionist approaches have been largely unsuccessful in providing an understanding of the pathogenesis of IR, there is a need for an integrative, time-resolved approach to elucidate the development of the disease.Methodology/Principal FindingsMale ApoE3Leiden transgenic mice exhibiting a humanized lipid metabolism were fed a high-fat diet (HFD) for 0, 1, 6, 9, or 12 weeks. Development of IR was monitored in individual mice over time by performing glucose tolerance tests and measuring specific biomarkers in plasma, and hyperinsulinemic-euglycemic clamp analysis to assess IR in a tissue-specific manner. To elucidate the dynamics and tissue-specificity of metabolic and inflammatory processes key to IR development, a time-resolved systems analysis of gene expression and metabolite levels in liver, white adipose tissue (WAT), and muscle was performed. During HFD feeding, the mice became increasingly obese and showed a gradual increase in glucose intolerance. IR became first manifest in liver (week 6) and then in WAT (week 12), while skeletal muscle remained insulin-sensitive. Microarray analysis showed rapid upregulation of carbohydrate (only liver) and lipid metabolism genes (liver, WAT). Metabolomics revealed significant changes in the ratio of saturated to polyunsaturated fatty acids (liver, WAT, plasma) and in the concentrations of glucose, gluconeogenesis and Krebs cycle metabolites, and branched amino acids (liver). HFD evoked an early hepatic inflammatory response which then gradually declined to near baseline. By contrast, inflammation in WAT increased over time, reaching highest values in week 12. In skeletal muscle, carbohydrate metabolism, lipid metabolism, and inflammation was gradually suppressed with HFD.Conclusions/SignificanceHFD-induced IR is a time- and tissue-dependent process that starts in liver and proceeds in WAT. IR development is paralleled by tissue-specific gene expression changes, metabolic adjustments, changes in lipid composition, and inflammatory responses in liver and WAT involving p65-NFkB and SOCS3. The alterations in skeletal muscle are largely opposite to those in liver and WAT.

Abstract-Chronic inflammation in white adipose tissue (WAT) is positively associated with obesity, insulin resistance (IR) and the development of type 2 diabetes. The proinflammatory cytokine MIF (macrophage migration inhibitory factor) is an essential, upstream component of the inflammatory cascade. This study examines whether MIF is required for the development of obesity, IR, glucose intolerance, and atherosclerosis in the LDL receptor-deficient (Ldlr littermates are protected. MIF deficiency does not affect obesity and lipid risk factors but specifically reduces inflammation in WAT and liver, as reflected by lower plasma serum amyloid A and fibrinogen levels at baseline and under inflammatory conditions. Conversely, MIF stimulates the in vivo expression of human C-reactive protein, an inflammation marker and risk factor of IR and cardiovascular disease. In WAT, MIF deficiency reduces nuclear c-Jun levels and improves insulin sensitivity; MIF deficiency also reduces macrophage accumulation in WAT and blunts the expression of two proteins that regulate macrophage infiltration (intercellular adhesion molecule-1, CD44). Mechanistic parallels to WAT were observed in aorta, where the absence of MIF reduces monocyte adhesion, macrophage lesion content, and atherosclerotic lesion size. These data highlight the physiological importance of chronic inflammation in development of IR and atherosclerosis and suggest that MIF is a potential therapeutic target for reducing the inflammatory component of metabolic and cardiovascular disorders. Key Words: inflammation Ⅲ cytokines Ⅲ atherosclerosis Ⅲ insulin resistance Ⅲ C-reactive protein T he intertwined medical problems of obesity, glucose intolerance, type 2 diabetes (T2D), dyslipidemia, and atherosclerosis form the most serious threats to public health worldwide. Insulin resistance (IR) is an integral feature of the medical sequelae that are collectively referred to as the metabolic syndrome. 1 Decreased insulin sensitivity is the underlying defect in Ͼ90% of patients with T2D, and it is also considered to be a major pathological mechanism for the associated development of cardiovascular disease. 2 Recent human and animal studies have established both correlative and causative links between IR and chronic inflammation, in particular within adipose tissue. 3,4 For example, C-reactive protein (CRP), which is a serum marker of systemic inflammation, is independently related to insulin insensitivity and highly predictive for progression to overt T2D. 5 Mechanistic studies that have evaluated the impact of blocking specific inflammatory control points, such as c-Jun N-terminal kinase (JNK)1, 6 support the concept that the persistent activation of proinflammatory transcription factors (eg, c-Jun) in critical metabolic sites (adipose and liver tissue) may underlie the development of IR. When chronically inflamed, these tissues release proinflammatory molecules, including cytokines, acute-phase reactants, and procoagulant factors (eg, interleukin [IL]-6, serum amyloid A [SAA]...

Systems biology aims to understand the nonlinear interactions of multiple biomolecular components that characterize a living organism. One important aspect of systems biology approaches is to identify the biological pathways or networks that connect the differing elements of a system, and examine how they evolve with temporal and environmental changes. The utility of this method becomes clear when applied to multifactorial diseases with complex etiologies, such as inflammatory-related diseases, herein exemplified by atherosclerosis. In this paper, the initial studies in this discipline are reviewed and examined within the context of the development of the field. In addition, several different software tools are briefly described and a novel application for the KEGG database suite called KegArray is presented. This tool is designed for mapping the results of high-throughput omics studies, including transcriptomics, proteomics and metabolomics data, onto interactive KEGG metabolic pathways. The utility of KegArray is demonstrated using a combined transcriptomics and lipidomics dataset from a published study designed to examine the potential of cholesterol in the diet to influence the inflammatory component in the development of atherosclerosis. These data were mapped onto the KEGG PATHWAY database, with a low cholesterol diet affecting 60 distinct biochemical pathways and a high cholesterol exposure affecting 76 biochemical pathways. A total of 77 pathways were differentially affected between low and high cholesterol diets. The KEGG pathways "Biosynthesis of unsaturated fatty acids" and "Sphingolipid metabolism" evidenced multiple changes in gene/lipid levels between low and high cholesterol treatment, and are discussed in detail. Taken together, this paper provides a brief introduction to systems biology and the applications of pathway mapping to the study of cardiovascular disease, as well as a summary of available tools. Current limitations and future visions of this emerging field are discussed, with the conclusion that combining knowledge from biological pathways and high-throughput omics data will move clinical medicine one step further to individualize medical diagnosis and treatment.

High intakes of vegetable protein from gluten may have beneficial effects on cardiovascular disease risk by reducing oxidized LDL, serum triacylglycerol, and uric acid. Further studies are required to assess the longer-term effects on renal function.