Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Inflammation, metaflammation and immunometabolic disorders

Abstract

Proper regulation and management of energy, substrate diversity and quantity, as well as macromolecular synthesis and breakdown processes, are fundamental to cellular and organismal survival and are paramount to health. Cellular and multicellular organization are defended by the immune response, a robust and critical system through which self is distinguished from non-self, pathogenic signals are recognized and eliminated, and tissue homeostasis is safeguarded. Many layers of evolutionarily conserved interactions occur between immune response and metabolism. Proper maintenance of this delicate balance is crucial for health and has important implications for many pathological states such as obesity, diabetes, and other chronic non-communicable diseases.

Main

The overwhelming frequency of metabolic diseases such as obesity and diabetes may be related to organismal design and the evolutionary constraints within which natural selection has acted throughout history. Some of the initial thoughts and considerations of this relationship have been described previously1. However, it is worth stressing that, in general, selective pressures in evolution do not favour the development of countermeasures against excess nutrients and energy, but rather select for phenotypes that ensure survival in the face of deficiencies. For example, while there seems to be no need to defend against obesity, a strong rationale can be envisioned to defend against starvation. The same argument could be made regarding sugar concentrations in body fluids; while hyperglycaemia is not an immediate threat to survival, hypoglycaemia is. Hence, organisms harbour strong and redundant pathways to seek food, favour energy efficiency and storage, produce glucose and prevent hypoglycaemia. While these features provide selective advantage in the context of supply limitations, with the removal of these selective pressures, they have now become a prominent liability expressed in the form of obesity and related metabolic diseases such as diabetes (Fig. 1).

Figure 1: Immunometabolic impact on health.
figure1

Chronic metabolic inflammation, metaflammation, in multiple organs is implicated in metabolic disease. In metabolic organs including the liver, brain, pancreas and adipose tissue, inflammatory cell action and interactions within the stromal components is an important determinant of maintenance of tissue homeostasis as well as metabolic disease pathogenesis. Owing to their proximity, immune cells may sense and react to changes in nutrient availability, and in turn influence the intrinsic metabolic action within neighbouring cells critical for metabolic homeostasis, for example by altering lipid metabolism or inhibiting glucose uptake. These tissues and mediators produced from them also cause systemic inflammatory responses and disrupt metabolic homeostasis. As a result, immunometabolic diseases often emerge as clusters and promote ageing, disability and premature death.

PowerPoint slide

So how do the interface of metabolism and immunity relate to this transformation? The evolutionary advantages of a strong defence system are obvious in protecting against pathogens, and as a strong immune response is dependent on energy sources, one can also argue that the integration of these systems and their cooperation in responding to fluctuations in the energy and nutrient environment would be highly advantageous. From this perspective, an intriguing way to think about this paradigm would be to envision immune mediators, such as cytokines, as metabolic hormones. In fact, this aspect of immunometabolism is extremely well-conserved among organisms and will be the main topic of discussion in this work. Infection-related metabolic alterations, as well as the metabolic and energetic programming of the immune response, are also critical components of immunometabolism that were recently reviewed elsewhere2 and will not be covered here.

I would also like to emphasize here the duration and scale of responses as key determinants of outcomes. In the setting of infection, a successful immune response is strong but often short-lived, resulting in elimination of the pathogen followed by termination of the response, and the organism lives. If the result is a failure, the organism dies. In this evolutionary framework, there is no host survival advantage to chronic inflammation or to a low-grade response incapable of pathogen elimination. These constraints that govern the outcomes of immune responses are described in a recent review by R. Medzhitov3. It has also been well-established that inflammation is essential for repair, remodelling, and even renewal of tissues, including those with critical metabolic function. These responses also need to be temporally and spatially regulated to maintain homeostasis, including metabolic homeostasis, otherwise they will be uniformly damaging when sustained. Hence, broad, potent or permanent interferences targeting immune resolution or activation may have unintended and adverse consequences for tissue health, and if these tissues and related functions are critical for metabolic homeostasis, for the metabolic health of the organism as well. Finally, it is discernible that such an ancient and critical response will present layers of specificity as well as redundancy, hence its experimental or therapeutic management requires thorough consideration beyond the targeting of individual components.

These considerations aside, the immunological aspect of metabolic regulation in a multicellular organism could be framed in its most fundamental form by examining a highly conserved relationship between a potent and pleiotropic immune mediator (tumour necrosis factor, TNF), a pathogen sensing system (the Toll-like receptors, TLRs), and a powerful metabolic hormone (insulin). While this paradigm emerged from the observations made in obese and diabetic rodent models and examination of metabolic consequences in genetic or other interventions that target TNF and subsequently TLRs, it is highly conserved throughout evolution. Importantly, this entire cascade and the central signalling nodes and mediators have now been demonstrated in Drosophila4. Hence, unequivocal evidence links TNF to insulin action and production as a mechanism of evolutionary adaptation that is captured during the more recent maladaptive state of chronic nutrient and energy surplus exemplified by obesity (the same is also applicable to TLRs). Using this simple and highly preserved framework, it is possible to incorporate many layers of complexity with numerous mediators, hormones, and signalling systems to explore immunometabolism (Fig. 2).

Figure 2: Evolutionary conservation of immune and metabolic pathway crosstalk.
figure2

a, The Drosophila fat body serves to both sense and store nutrients and defend against pathogens; over the course of evolution a similar structure in an ancient mammalian ancestor has given rise to the distinct metabolic and immune organs observed in modern mammals, including adipose tissue and liver. b, Crosstalk between immune and metabolic pathways is remarkably conserved from invertebrates to mammals. The principle framework of this relationship is defined by three integrated systems; Eiger (TNF) and its receptor Wengen, dILP (insulin) and its receptors, and the TLR signalling pathways. TNF and TLR signalling block insulin signalling or production through JNK activation and MyD88, from flies to humans, and blocking these pathways rescues metabolic defects, whereas activation results in abnormal metabolic homeostasis. This scheme implies that cytokines can act as metabolic hormones to provide adaptations to nutrient fluctuations; in more complex organisms they become a liability in the face of chronic nutrient and energy exposure, such as the case in obesity. A full list of mediators and signaling networks can be found in Supplemental Figure 1.

PowerPoint slide

Immunometabolic integration in invertebrates

The strong link between nutrient sensing and immune signalling is rooted in their common evolutionary origin. In Drosophila, for example, the fat body carries out liver, adipose, and immune functions1,4. The fat body is capable of sensing both infectious and metabolic disturbances, and studies of Drosophila have helped to illuminate highly conserved immunometabolic pathways discovered in mammals. Indeed, the fat body is the major producer of Eiger, the Drosophila orthologue of TNF5. Activation of Wengen (a TNF receptor) or TLR signalling results in inhibition of insulin action through JNK and MyD88 pathways converging on GSK3 and Foxo as targets6,7. Studies in humans and mammalian models have demonstrated that JNK kinase activity has an important upstream role in integrating inflammatory and metabolic function, and this is conserved in Drosophila, where JNK signalling regulates the expression of the lipocalin Nlaz, an orthologue of RBP4, antagonizing expression of Drosophila insulin-like peptide (Dilp) and insulin/IGF signalling6,8. As in mammals, exposure to dietary stress (overfeeding or a high-sugar diet) results in resistance to Dilp action in the fat body downstream of JNK activity9,10.

A very recent study provided a final and critical missing piece of evidence that demonstrates the highly evolutionarily conserved activity of TNF that is also central to metabolic disease, that is, diabetes in the fruit fly. Eiger (TNF), produced by fat cells, acts through Grindelwald (the second putative Drosophila TNF receptor) to control body size during substrate deprivation. Most importantly, reduction of Grindelwald in the fat body prevents the development of hyperglycaemia in the setting of a high sugar diet4. Taken together, these data reinforce a general model in which TNF and other immune mediators act as adipose-derived hormones (adipokines) that work to couple nutritional status to adaptive responses, and the misapplication of this system in the setting of chronic nutrient excess is a key underlying mechanism in the pathogenesis of metabolic disease, from flies to humans (Fig. 2). Similar lines of evidence are also emerging from work in other model organisms such as Caenorhabditis elegans and Danio rerio, demonstrating a high degree of evolutionary conservation and providing powerful platforms for mechanistic and interventional studies.

Components of immunometabolic interactions

Initial support for our understanding of the connection between obesity and metabolic disease came from the findings that macrophages secrete a molecule (TNF) that induces insulin resistance in adipocytes11, and that obesity was associated with increased expression of inflammatory mediators in adipose tissue and that this inflammation interfered with glucose metabolism12,13. Numerous interventional studies have since validated this postulate (complete references available at http://www.metaflammation.org). The demonstration of macrophage infiltration into the adipose tissue of obese mice was another important milestone14,15. Although immune cell infiltration into adipose tissue had been observed almost forty years earlier16,17, the potential contribution of these cells, or inflammation in general, to metabolic health or dysfunction was unappreciated at the time. The later studies were the basis for investigations into the possibility that adipose tissue macrophages act as direct modulators of metabolism, and led to work that showed that, in obesity, free fatty acid exposure promotes the polarization of adipose tissue resident macrophages towards a pro-inflammatory (M1-polarized) phenotype which can block insulin action18,19,20. Recent work has begun to unravel the molecular mechanisms that underlie these events, including the identification of epigenomic alterations that determine macrophage sensitivity to metabolically driven inflammatory (metaflammatory) signals21, and the discovery of additional macrophage-secreted products that attenuate insulin signalling22. Although I am unable to cover the topic in detail in this manuscript, it is important to note that subsequent work has demonstrated that many other immune cell types including dendritic cells, mast cells, eosinophils and lymphoid cells also contribute to metabolic tissue homeostasis and to the control of glucose metabolism. Furthermore, certain macrophage populations, as well as other resident immune cells, are also critical in tissue homeostasis and turnover of stromal constituents such as adipocytes, and hence the nature, amount, and activation state of these immune cells in the tissue environment is critical in determining their impact on systemic metabolism.

The inflammasome, a protein complex that enables maturation of the pro-inflammatory cytokines IL-1β and IL-18 by caspase-1-mediated cleavage, is an integral part of innate immunity. The role of the inflammasome in metabolic disease is firmly supported by a multitude of studies, which demonstrate that mice deficient in various inflammasome components as well as IL-1β or its receptor IL-1R1 are protected from diet-induced insulin resistance23,24. Treating rodent diabetic models with an inhibitor of IL-1 signalling or an antibody targeting IL-1β has also been shown to have metabolic benefits, including improved insulin sensitivity and improved β cell survival25. Finally, this pathway plays an important role in human diabetes25,26.

A danger signal that is released by the inflammasome is HMGB1, which is a ligand for the receptor for advanced glycation end products (RAGE). Neutralization of HMGB1 or deletion of its receptor results in reduced inflammation and weight gain and improved glucose tolerance in mouse models27,28. Notably, studies of inflammasome-driven release of HMGB1 demonstrated that the double-stranded-RNA-sensing kinase PKR is a critical mediator of inflammasome activity and metabolic regulation29. While one study observed that PKR is dispensable for inflammasome activation30, work from many other groups has since provided ample evidence linking PKR to inflammasome activity which in fact is responsive to cellular metabolic status31,32,33,34. Lastly, recent studies illustrated a remarkable possibility of activating PKR through endogenous double-stranded RNA signals in response to metabolic stress35, and it is possible that other endogenous ligands can also engage PKR in this manner. Since small nucleolar RNA production is also required for lipotoxicity36, PKR may directly sense endogenous messages related to the metabolic milieu and integrate them with innate immune responses to regulate systemic homeostasis. This postulate is consistent with the finding that there is a marked reduction in stress- and nutrient-induced JNK activation in the absence of PKR, resulting in protection against high-fat-diet-induced obesity, insulin resistance and diabetes in multiple studies (reviewed in ref. 37), although one study has not observed these effects38. On the other hand, PKR activity has been linked to pancreatic β cell failure and lipid-induced muscle insulin resistance in numerous other studies39,40,41.

Newly identified role for the adaptive immune system

Many recent studies have demonstrated that in addition to alterations to the innate immune system, obesity is also associated with increased activation of adaptive immunity. For example, there are shifts in the influx of T cells in the adipose tissue in obesity; increases in CD4+ and CD8+ T cells have been documented in obese humans and mice42. Conversely, regulatory T (Treg) cells in adipose tissue are positively associated with insulin sensitivity43,44, and induction or adoptive transfer of Treg cells improves glucose homeostasis in obese mice45. In line with this, mice deficient in adipose tissue Treg cells are also protected against age-related insulin resistance46. Notably, the beneficial effect of Treg cells requires expression of PPARγ, an important metabolic mediator, and genetic deletion of PPARγ in Treg cells is sufficient to prevent anti-diabetic actions of PPARγ agonists, providing yet another layer of evidence into the immunometabolic nature of type 2 diabetes47. B cells also accumulate in the adipose tissue of obese mice48, and in this setting they produce a more inflammatory repertoire of cytokines49. By contrast, the number of tolerance-promoting regulatory B cells in adipose tissue is decreased in models of obesity50, as are the number of anti-inflammatory type 1 natural killer T (NKT) cells51 and iNKT cells52. Most intriguingly, obesity triggers abnormal B cell function, which is reflected in the production of autoantibodies and pathological immunoglobulins48. While the relative contribution of the adaptive immune system activation to the pathologies of systemic glucose homeostasis in obesity remains incompletely understood, there are exciting potential opportunities in this area with translational possibilities.

Pleiotropism of hormones, cytokines and signalling networks

Altered production of many pro- or anti-inflammatory cytokines, adipokines and lipid mediators, as well as signalling through a plethora of immune receptors and intracellular mediators, has been observed in obesity and experimentally linked to metabolic pathology. These are too numerous to list here but a comprehensive compilation is presented in Supplementary Fig. 1 (extended version available at http://www.metaflammation.org). The signalling kinases are also numerous and include PKC, p38, ERK, JNK, IKK, JAK, AMPK, mTOR and PKR. The overwhelming majority of these signalling networks converge on metabolic hormone action, most critically on insulin and glucagon, but also several others. Careful studies have revealed that the actions of many classical inflammatory molecules are context-dependent and may vary on the basis of duration and dose of exposure as well as the production and target sites. Therefore, association studies and analysis of global single-gene-deletion models in mice may often not tell the whole (or even the accurate) story. One of the best examples of a molecule with such complex roles is IL-6, the circulating levels of which have been shown by many to be increased in the setting of obesity and to correlate with diabetes risk and metabolic syndrome. In line with this finding, IL-6 induces insulin resistance in various tissues and cell types, but acutely enhances insulin signalling in muscle. Accordingly, in some in vivo studies, blocking IL-6 action with a neutralizing antibody improves insulin sensitivity in obese mice, while other groups have shown that IL-6 interference does not alter insulin sensitivity, and the descriptions of Il6−/− mice are also greatly variable with both beneficial and detrimental effects (references available at http://www.metaflammation.org).

Analogous intricacies also exist in the studies of the effects of inflammatory signalling networks on metabolism. Although a large body of evidence supports a detrimental role on glucose metabolism for pathological IκB kinase (IKK) activation in multiple tissues, other approaches that promote or interfere with IKK activity have produced conflicting results. For example, blocking IKK action in the adipose tissue of mice, which was designed as a strategy to block the inflammatory response, in fact results in massive adipose tissue inflammation and metabolic deterioration related to the role of IKK activity in the resolution of inflammation53. IKK activation can also impinge upon endoplasmic reticulum (ER) function and the unfolded protein response (UPR)54. Importantly, beneficial metabolic effects of salicylates have been reported in mouse models of, and in humans with, metabolic disease, although the degree to which these effects are mediated through IKK signalling in humans and the impact on insulin action versus improved insulin secretion remains to be explored55,56. Similarly, while many independent studies in mice and humans support the conclusion that p38 activation is detrimental for metabolism, occasional reports suggest that it may have beneficial effects57,58. Conversely, the role of pathological JNK activation in obesity is an important benchmark in experimental studies evaluating immunometabolic phenotypes, and its detrimental impact on glucose homeostasis has been consistently and convincingly documented in many studies59,60. Numerous studies have also addressed the target cell types and tissues involved in this biology and the underlying mechanisms continue to be explored by many groups61,62. Regrettably it is not possible to examine these studies in detail here, but these differential findings underscore the limitations that may be encountered in efforts to study immunometabolic biology and to therapeutically target classical inflammatory pathways with an all-or-none or linear framework, wherein single molecules have context-dependent and pleiotropic functions, positive and negative, on both local and systemic inflammation and the metabolic outcomes. This is characteristic of not just immune mediators, but even metabolic hormones that modulate systemic glucose metabolism such as glucagon.

Metabolic inflammation was first described in adipose tissue, it presents the highest complexity at this site, and has been examined in detail with thousands of studies. However, it is critical to emphasize that adipose tissue is neither the sole site of metaflammation nor could it be assumed to be the only player in metabolic homeostasis or related pathologies. Obesity-related influx of immune cells occurs in many other tissues such as the hypothalamus, liver, muscle, pancreatic islets and the gut (Fig. 1). The immunometabolic program within each organ also includes stromal components and metabolic cells, such as adipocytes, hepatocytes and β cells. These cells not only control the energy and substrate fluxes into the immune effectors but also themselves produce many cytokines, chemotactic molecules and lipid mediators. Hence, the systemic impact of metabolic inflammation as well as the bidirectional interactions between immune and stromal components are critical considerations in determining physiological and pathological outcomes. Some examples are provided in other sections of this text.

Organelle dynamics and function in immunometabolism

A key question in understanding immunometabolic biology is whether mechanisms can be identified that integrate nutrient and immune responses and provide a broad framework for metabolic failure in the face of energy and nutrient excess. In the past ten years, work from many labs has shown that one of the key components of metabolic health involves organelle homeostasis, particularly in the ER. Fluctuations in nutrient supply and metabolic demand impair ER function and activate the UPR. Notably, elements of the UPR converge on many inflammatory pathways including JNK and IKK, the activation of which block insulin action as well as secretion and impair glucose homeostasis63,64. Furthermore, the link between UPR activation and inflammation was shown to be dependent on the pattern recognition receptors NOD1 and NOD2 (ref. 65), and the ER is a critical site for inflammasome activation66. ER function may more generally be an important factor in determining immune cell fate and function, including eosinophil differentiation, immunoglobulin production from B cells and IL-6 expression in macrophages67. Taken together, these findings strongly indicate that by modulating the state of the ER, metabolic stress can have a profound and direct impact on immune system function, and the ER may serve as key site where the information on the nutrient and energy status of the cell can be relayed to inflammatory pathways. Notably, it is also now clear that inflammation itself may impair ER function. In genetically obese mice, the increased production of nitric oxide leads to post-translational modifications of the UPR component IRE1, which impairs its ability to cleave XBP1 mRNA and initiate a pro-resolution program68. In general, proper activation of XBP1 is important for metabolic homeostasis in the liver, however it has been reported that lack of XBP1 in the liver can also be protective against insulin resistance69. Hence, the metabolic biology mediated by this branch of the UPR also exhibits a great deal of variation on the basis of the experimental system used, and it is likely that neither constitutive activation nor complete inhibition would result in successful long-term management of metabolism. These issues notwithstanding, it is clear that a chronic inflammatory environment is not conducive to maintaining a healthy equilibrium in the ER.

In most cells, organelle homeostasis does not occur in isolation, and the ER is not the only organelle exhibiting dysfunction in obesity. There is growing body of compelling evidence that obesity induces a state of mitochondrial dysfunction70. Many recent studies have provided insight into the mechanisms involved, and offered further support that mitochondrial dysfunction may be one of the critical events in the development of obesity-induced metabolic pathologies. In rodents, a high-fat diet leads to uncoupled respiration and oxidative stress in the liver, which contributes to pathologies in glucose metabolism71. In macrophages, increased ROS production promotes pro-inflammatory polarization and can lead to insulin resistance in vivo72,73. There is also evidence of reduced mitochondrial function in type 2 diabetic patients in adipose tissue74 and skeletal muscle75, although how alterations in mitochondrial function relate to glucose metabolism and insulin action is an area of active debate and exploration, which will not be covered in detail here. Notably, we now know that at least in liver, dysfunction of the ER and mitochondria are linked phenomena, as obesity induces abnormal connections and communication between these organelles, resulting in excess mitochondrial calcium accumulation, oxidative stress and dysfunction76. Relatedly, the ER-resident E3 ubiquitin ligase synoviolin controls the turnover of PGC-1β, thereby modulating mitochondrial respiration and energy expenditure, with consequences for body weight and metabolic regulation77. Furthermore, altered calcium signalling may be a generalized dysfunction that contributes to obesity-induced metabolic decline in many tissues and cell types (reviewed in ref. 78).

Nutrients and metabolites as fuel and signalling molecules

The concept that nutrients, particularly circulating lipids, have a role in determining insulin sensitivity dates from at least as early as the 1960s, when it was recognized that lipids and fatty acids reduced insulin-induced glucose uptake in isolated heart muscle79. This effect was subsequently shown systemically in animal models including rats and in humans80. Since then, it has become clear from studies in humans and animal models that lipid-induced insulin resistance and impaired glucose metabolism may also involve other mechanisms, including the activation of inflammatory pathways81,82,83,84. For example, the innate immune component TLR4 has been identified as a receptor for saturated and polyunsaturated fatty acids19,85,86, and although this sensing may occur indirectly, mice with loss of function of TLR4 are protected from the effects of diets high in saturated fat87,88. Deletion of the TLR adaptor molecule MyD88 in the central nervous system also protects mice from diet-induced insulin resistance89. Taken together, ample evidence supports the involvement of TLR signalling in metabolic control in multiple experimental models7,88.

Notably, other critical mechanisms may contribute to the role of lipid-induced insulin resistance independent of TLR signalling. For example, mice fed a high-fat diet exhibit changes in their serum, muscle and adipose tissue lipid profiles indicative of mitochondrial dysfunction, and incubating macrophages with these lipids drives expression of proinflammatory cytokines90,91. Furthermore, many cytokines also induce the production of ceramides, which themselves may have potent metabolic effects, as has been reviewed elsewhere92. Another line of evidence indicates that lipid-induced insulin resistance in skeletal muscle is associated with accumulation of fatty acyl-CoA and DAG, leading to activation of PKCθ, which blocks insulin action through IRS-1 serine phosphorylation and other mechanisms84,93. Similar results have also been observed in human studies94. However, the full extent of this pathway’s ability to mediate diet-induced insulin resistance is unclear, in part because animal models used to investigate the role of PKCθ in the development of insulin resistance have given rise to complex results95,96. Fatty-acid-induced activation of PKC as well as JNK in macrophages has also been linked to the production of inflammatory cytokines and promotion of muscle insulin resistance97. The interactions between direct mechanistic targets of these pathways, and how they are linked to metabolic pathologies is being explored, however it is clear that the DAG–PKC and the ceramide pathways are extremely promising avenues for further research with important implications for human metabolic disease. More research is necessary to fully understand whether these pathways are indeed separate from or an integrated part of the immunometabolic systems described here. As many lines of evidence demonstrate activity of signalling molecules such as PKC or JNK in both metabolic and immune responses, a model integrating these systems (see ref. 37) is likely to be most accurate (Fig. 3, references available at http://www.metaflammation.org). While it is not possible to cover the topic in further depth, it is important to note that there are also many lipids that play anti-inflammatory roles and produce metabolic benefits that have been identified98.

Figure 3: Convergence of key signalling molecules on both metabolic and inflammatory pathways and functional outcomes.
figure3

The integration of metabolic and inflammatory signalling occurs at multiple levels, including at the receptor, organelle, kinase pathways, and gene expression. Most signalling molecules have defined metabolic and immune functions. The three most heavily studied examples, PKC, JNK and IKK, can signal a multitude of immune (both innate and adaptive responses, resolution of inflammation) and metabolic (insulin, glucagon or FGF21 action, fatty acid and cholesterol metabolism, appetite regulation, and so on) responses. The examples are provided to illustrate the integrated immunometabolic capabilities of signalling molecules as a framework to illustrate their complex functional profiles. DAG, diacylgycerol; FFA, free fatty acids; H2S, hydrogen sulphide; LCA-CoA, long-chain acyl-CoAs; PGE2, prostaglandin E2; ROS, reactive oxygen species.

PowerPoint slide

Immunometabolic links in human studies

Studies of human subjects have long provided clues of the link between inflammatory signalling and metabolic disease. Indeed, as early as 1884 it was noted that patients with meningitis exhibit a transient diabetic syndrome, and a careful review of cases suggested that the frequency of diabetes was so high that a meningitis diagnosis might be missed and patients treated exclusively for their hyperglycaemia99. Since then, ample studies in human subjects have continued to underscore the potential role of immunity in diabetes in genetic, clinical, epidemiological and population studies (For some examples and references, see http://www.metaflammation.org).

Immune genes and metabolic phenotypes in GWAS

Some of the initial loci identified in genome-wide association studies (GWAS) linked to type 2 diabetes are implicated in the regulation of insulin secretion and insulin processing100,101, leading to the suggestion that relative susceptibility to β cell failure may be the dominant genetic contribution to diabetes risk102,103. Some have even suggested the initial scarcity of hits identified in established immune pathways may impugn the biological link between inflammation and diabetes susceptibility. While this may be the case, the volume of genetic evidence should not be interpreted as supporting or refuting the translatability to humans, and indeed careful examination reveals many immunological components genetically linked to metabolic phenotypes in humans. For example, fasting insulin and glucose levels were linked to PTPRJ, which is a regulator of T cell signalling104, and variants in ST6GAL1, which has a role in antigen production, have been linked to type 2 diabetes susceptibility105. A large-scale GWAS identified multiple loci with known roles in immunity as being susceptibility loci for type 2 diabetes, including MAEA, which has a role in macrophage maturation, CMIP, which is involved in T cell signalling, and WWOX, an oxidoreductase that mediates TNF-mediated apoptosis106. Similar links exist for JNK, GPR120, and others107,108. Most recently, two large-scale studies published in 2015 combined GWAS with ‘metabochip’ analysis to identify many immunological loci that are linked to metabolic traits109,110. In this work, waist–hip ratio is linked to MAP3K1, a part of the JNK pathway, MACROD1, a regulator of NFκB activation, NFE2L3 (also known as NRF3) which coordinates cellular stress responses, and the inflammasome component NLRP3 (ref. 110). In addition, this approach linked variants of IFNGR1, TLR4 and NLRC3 to body mass index109. However, since human genetic variability is estimated to contribute to a fraction of the heritability of complex traits, and many of the direct genetic hits are still being investigated for their causal impact on phenotypic outcomes, it is prudent to interpret both positive and negative results with caution. Integrated approaches including the analysis of chromatin states and global gene expression or metabolomic profiles in mouse models and in humans have also provided additional examples of the contribution of inflammation to metabolic phenotypes111,112. Taken together, these findings not only provide multiple layers of genetic support for the immunometabolic component of diabetes and obesity but also clearly demonstrate the broad similarities between model organisms and humans in this biology.

Emerging data from human trials

As we progress in our understanding of the molecular mechanisms that underlie the connections between obesity and metabolic disease, the ultimate goal is the development of successful translational approaches to treat patients or prevent disease. Biologics targeting classical inflammatory molecules including IL-1, IL-6 and TNF are already currently in clinical use for the treatment of rheumatoid arthritis, Crohn’s disease and other chronic inflammatory diseases, and assessment of these patients provides some insight into whether these approaches might have metabolic benefit in these populations. However, the results of these studies have been variable; for example in the case of TNF, while some have concluded that anti-TNF therapy reduces risk of diabetes or improves insulin sensitivity, others have not replicated these findings. The same is also true in small proof-of-principle studies in obese patients. However, large retrospective and meta-analysis studies have concluded that anti-TNF therapy improved insulin sensitivity or hyperglycaemia and importantly, reduced lifetime risk of diabetes113,114. Multiple studies have provided highly promising evidence that antagonizing IL-1 signalling improves insulin secretion and, in some patients, enhances insulin sensitivity26. A detailed analysis of the pros and cons of these trials was recently reported115. The limited success of these approaches targeting individual cytokines so far should not be considered endorsements or indictments of the proposed immune mechanisms; indeed successful immunological interventions have been extremely challenging even in diseases such as type 1 diabetes, where the immune mechanisms driving the pathology are well-established, and in others (such as Crohn’s and rheumatoid arthritis), anti-cytokine treatments only benefit a small fraction of the patients116. Overall, it is clear that TNF or IL-1 blockade have benefits, but better patient selection and precision is needed to realize the full translational potential of these approaches.

In addition to these well-established immunomodulatory strategies, which perhaps represent the ‘low-hanging fruit’ to be used for additional indications, the use of other anti-inflammatory molecules such as resolvins, ω-3 fatty acids, palmitoleate, or fatty acid-hydroxyl fatty acids provide extremely promising prospects for translational opportunities through lipid mediators or metabolism with encouraging leads98. There is also an exciting prospect related to erythropoietin (EPO), which has potent anti-inflammatory and tissue-protective effects, acting as a direct and indirect antagonist of TNF117. These actions of EPO are independent of its haematopoietic effects, and are signalled through an atypical heteromeric low-affinity receptor. Recently, a selective peptide agonist of this form of the receptor called ARA290 has been shown to be effective against obesity-induced inflammation and insulin resistance in mice118, and proof-of-principle studies in humans showed promising improvements in glucose control and dyslipidemia119. There is now a larger clinical trial planned to test the EPO receptor antagonist ARA290 (NCT01933529). Finally, it is important to note that essentially all existing anti-diabetic remedies, including metformin, thiozolidinediones, DPP4 inhibitors, incretin agonists, and even lifestyle interventions including exercise and caloric restriction, all exhibit anti-inflammatory activity120,121,122. Notably, statins reportedly exert pro-inflammatory action, such as stimulation of inflammasome activity, which may underlie the perplexing increase in diabetes risk identified in some studies with statin use123,124. While each one of these approaches presents pros and cons, especially in the complex multifactorial metabolic disease space, they all point to critical and causal involvement of abnormal immune response in metabolic pathologies. I am hopeful that there will be more refined and better stratified clinical studies116 and many additional approaches to clarify further the immune-metabolic basis of obesity and diabetes and its effective translation to human diseases (Box 1).

Challenges, caveats, and reflections

In this author’s opinion, the challenges remaining in this field can be identified in few distinct areas. How does metabolic inflammation start and at what point does it become detrimental? What are the unknown mechanisms that guard metabolic organs from nutritional, metabolic, or immune challenges to maintain homeostasis? What are the appropriate model systems and paths to translation to prevent or treat human disease? The current status of some of these issues is discussed throughout the text. Regarding the initiation of metaflammation, there are several interesting and emerging concepts, one of which is that dying adipocytes release toxic cargo including cell-free DNA, which engages immune effectors and initiates inflammatory responses125. A second compelling hypothesis is related to hypoxia, which is a ubiquitous feature of adipose tissue in obesity in experimental models and humans126. A third emerging concept is obesity-induced genotoxicity and related stress responses, particularly in the adipose tissue127. However, it is unclear whether these mechanisms occur in isolation, in a sequence or together, or whether they have relevance to other tissues where metabolic inflammation occurs, such as liver and pancreas. In particular, the inflammatory responses in the brain to metabolic stress have been observed both in mice and humans, with important metabolic consequences, but little is known about the mechanisms that trigger them128. Perhaps a promising avenue in this regard is the involvement of toxic lipids or metabolites and the targeting of inflammatory signalling networks, which may also include the production of endogenous RNA species. Finally, failure of organelles structurally and/or functionally may serve as a critical event in metabolic homeostasis, as well as in the initiation or propagation of metaflammation37,63. These are all exciting developments that have the potential to provide insight into new aspects of metabolism and the origin of the immunometabolic aetiology of obesity and diabetes.

Specific to inflammation, it is important to remember that intact inflammatory pathways are critical for the health of tissues and proper homeostasis, including the health of adipose tissue expansion in response to caloric excess129. An active immune system is required for acute responses and organismal maintenance, and thus integrity of the tissue function as well as metabolic homeostasis cannot be sustained without the immune response. Hence, general disruption of inflammatory pathways may not only compromise the ability to combat invaders but also result in tissue damage and even induce systemic inflammation through the disruption of repair and remodelling or by creating dysbiosis130,131. A thoughtful consideration of the implications of manipulating immune responses to treat chronic diseases is therefore warranted.

There is also tremendous redundancy in the pathways that support inflammation as well as its resolution, and this certainly is also the case in immunometabolic regulation (Supplementary Fig. 1, extended version available at http://www.metaflammation.org). This poses an important and unresolved question regarding how we design and interpret immunometabolic changes in genetic models, especially in inbred mouse strains. Just as a clinical study with a single subject may be informative but cannot be definitive or generalizable, genetic interventions in inbred strains have limitations in determining the efficacy or translatability of putative targets. Finally, in humans there is also tremendous inter-individual variability in the magnitude of the immune response, even exhibiting strong seasonal fluctuations132,133,134. Given these difficulties, and the need for therapeutic approaches that do not permanently interfere with entire branches of the immune system and are free of undesirable outcomes, translating our experimental insights into successful clinical interventions will require nuanced thinking, combinatorial approaches, and new experimental paradigms. A very promising approach is the use of outbred or even wild strains, such as in collaborative and diversity cross studies, and integrating genetic variation with other environmental modifiers to establish links with complex metabolic phenotypes and facilitate successful translation to human disease135,136.

References

  1. 1

    Hotamisligil, G. S. Inflammation and metabolic disorders. Nature 444, 860–867 (2006)

    ADS  CAS  PubMed  Google Scholar 

  2. 2

    Pearce, E. L. & Pearce, E. J. Metabolic pathways in immune cell activation and quiescence. Immunity 38, 633–643 (2013)

    CAS  PubMed  PubMed Central  Google Scholar 

  3. 3

    Kotas, M. E. & Medzhitov, R. Homeostasis, inflammation, and disease susceptibility. Cell 160, 816–827 (2015)

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4

    Agrawal, N. et al. The Drosophila TNF Eiger is an adipokine that acts on insulin-producing cells to mediate nutrient response. Cell Metab. 23, 675–684 (2016).An important study demonstrating the evolutionary conservation of the negative impact of TNF on insulin production, insulin action and glucose metabolism, and a demonstration of how cytokines can serve as metabolic hormones.

    CAS  PubMed  Google Scholar 

  5. 5

    Mabery, E. M. & Schneider, D. S. The Drosophila TNF ortholog Eiger is required in the fat body for a robust immune response. J. Innate Immun. 2, 371–378 (2010)

    CAS  PubMed  PubMed Central  Google Scholar 

  6. 6

    Wang, M. C., Bohmann, D. & Jasper, H. JNK extends life span and limits growth by antagonizing cellular and organism-wide responses to insulin signaling. Cell 121, 115–125 (2005)

    CAS  PubMed  Google Scholar 

  7. 7

    DiAngelo, J. R., Bland, M. L., Bambina, S., Cherry, S. & Birnbaum, M. J. The immune response attenuates growth and nutrient storage in Drosophila by reducing insulin signaling. Proc. Natl Acad. Sci. USA 106, 20853–20858 (2009)

    ADS  CAS  PubMed  Google Scholar 

  8. 8

    Hull-Thompson, J. et al. Control of metabolic homeostasis by stress signaling is mediated by the lipocalin NLaz. PLoS Genet. 5, e1000460 (2009)

    PubMed  PubMed Central  Google Scholar 

  9. 9

    Pasco, M. Y. & Léopold, P. High sugar-induced insulin resistance in Drosophila relies on the lipocalin Neural Lazarillo. PLoS One 7, e36583 (2012)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  10. 10

    Morris, S. N. et al. Development of diet-induced insulin resistance in adult Drosophila melanogaster. Biochim. Biophys. Acta 1822, 1230–1237 (2012)

    CAS  PubMed  PubMed Central  Google Scholar 

  11. 11

    Pekala, P., Kawakami, M., Vine, W., Lane, M. D. & Cerami, A. Studies of insulin resistance in adipocytes induced by macrophage mediator. J. Exp. Med. 157, 1360–1365 (1983).This important paper demonstrates that macrophages activated by LPS secrete products that block insulin action in adipocytes.

    CAS  PubMed  Google Scholar 

  12. 12

    Hotamisligil, G. S., Shargill, N. S. & Spiegelman, B. M. Adipose expression of tumor necrosis factor-alpha: direct role in obesity-linked insulin resistance. Science 259, 87–91 (1993)

    ADS  CAS  PubMed  Google Scholar 

  13. 13

    Uysal, K. T., Wiesbrock, S. M., Marino, M. W. & Hotamisligil, G. S. Protection from obesity-induced insulin resistance in mice lacking TNF-α function. Nature 389, 610–614 (1997)

    ADS  CAS  PubMed  Google Scholar 

  14. 14

    Xu, H. et al. Chronic inflammation in fat plays a crucial role in the development of obesity-related insulin resistance. J. Clin. Invest. 112, 1821–1830 (2003)

    CAS  PubMed  PubMed Central  Google Scholar 

  15. 15

    Weisberg, S. P. et al. Obesity is associated with macrophage accumulation in adipose tissue. J. Clin. Invest. 112, 1796–1808 (2003).Published simultaneously, these two important studies (refs 14 and 15 ) demonstrated macrophage infiltration into adipose tissue and relate this to metabolic deterioration.

    CAS  PubMed  PubMed Central  Google Scholar 

  16. 16

    Hausberger, F. X. Pathological changes in adipose tissue of obese mice. Anat. Rec. 154, 651–660 (1966)

    CAS  PubMed  Google Scholar 

  17. 17

    Hellman, B. Studies in obese-hyperglycemic mice. Ann. NY Acad. Sci. 131, 541–558 (1965)

    ADS  CAS  PubMed  Google Scholar 

  18. 18

    Lumeng, C. N., Bodzin, J. L. & Saltiel, A. R. Obesity induces a phenotypic switch in adipose tissue macrophage polarization. J. Clin. Invest. 117, 175–184 (2007)

    CAS  PubMed  PubMed Central  Google Scholar 

  19. 19

    Nguyen, M. T. et al. A subpopulation of macrophages infiltrates hypertrophic adipose tissue and is activated by free fatty acids via Toll-like receptors 2 and 4 and JNK-dependent pathways. J. Biol. Chem. 282, 35279–35292 (2007)

    CAS  PubMed  Google Scholar 

  20. 20

    Hevener, A. L. et al. Macrophage PPARg is required for normal skeletal muscle and hepatic insulin sensitivity and full antidiabetic effects of thiazolidinediones. J. Clin. Invest. 117, 1658–1669 (2007)

    CAS  PubMed  PubMed Central  Google Scholar 

  21. 21

    Fan, R. et al. Loss of the co-repressor GPS2 sensitizes macrophage activation upon metabolic stress induced by obesity and type 2 diabetes. Nat. Med. 22, 780–791 (2016)

    ADS  CAS  PubMed  Google Scholar 

  22. 22

    Li, P. et al. Hematopoietic-derived Galectin-3 causes cellular and systemic insulin resistance. Cell 167, 973–984.e12 (2016)

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 23

    Wen, H. et al. Fatty acid-induced NLRP3-ASC inflammasome activation interferes with insulin signaling. Nat. Immunol. 12, 408–415 (2011)

    CAS  PubMed  PubMed Central  Google Scholar 

  24. 24

    Stienstra, R. et al. The inflammasome-mediated caspase-1 activation controls adipocyte differentiation and insulin sensitivity. Cell Metab. 12, 593–605 (2010)

    CAS  PubMed  PubMed Central  Google Scholar 

  25. 25

    Herder, C., Dalmas, E., Böni-Schnetzler, M. & Donath, M. Y. The IL-1 pathway in type 2 diabetes and cardiovascular complications. Trends Endocrinol. Metab. 26, 551–563 (2015)

    CAS  PubMed  Google Scholar 

  26. 26

    Larsen, C. M. et al. Interleukin-1-receptor antagonist in type 2 diabetes mellitus. N. Engl. J. Med. 356, 1517–1526 (2007).A critical study demonstrating the benefits of blocking inflammation in humans with type 2 diabetes.

    CAS  PubMed  Google Scholar 

  27. 27

    Song, F. et al. RAGE regulates the metabolic and inflammatory response to high-fat feeding in mice. Diabetes 63, 1948–1965 (2014)

    CAS  PubMed  PubMed Central  Google Scholar 

  28. 28

    Montes, V. N. et al. Anti-HMGB1 antibody reduces weight gain in mice fed a high-fat diet. Nutr. Diabetes 5, e161 (2015)

    CAS  PubMed  PubMed Central  Google Scholar 

  29. 29

    Lu, B. et al. Novel role of PKR in inflammasome activation and HMGB1 release. Nature 488, 670–674 (2012)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  30. 30

    He, Y., Franchi, L. & Núñez, G. The protein kinase PKR is critical for LPS-induced iNOS production but dispensable for inflammasome activation in macrophages. Eur. J. Immunol. 43, 1147–1152 (2013)

    CAS  PubMed  PubMed Central  Google Scholar 

  31. 31

    Boriushkin, E., Wang, J. J., Li, J., Bhatta, M. & Zhang, S. X. p58IPK suppresses NLRP3 inflammasome activation and IL-1β production via inhibition of PKR in macrophages. Sci. Rep. 6, 25013 (2016)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  32. 32

    Li, W., Li, J., Sama, A. E. & Wang, H. Carbenoxolone blocks endotoxin-induced protein kinase R (PKR) activation and high mobility group Box 1 (HMGB1) release. Mol. Med. 19, 203–211 (2013)

    CAS  PubMed  PubMed Central  Google Scholar 

  33. 33

    Hett, E. C. et al. Chemical genetics reveals a kinase-independent role for protein kinase R in pyroptosis. Nat. Chem. Biol. 9, 398–405 (2013)

    CAS  PubMed  PubMed Central  Google Scholar 

  34. 34

    Xie, M. et al. PKM2-dependent glycolysis promotes NLRP3 and AIM2 inflammasome activation. Nat. Commun. 7, 13280 (2016).This study demonstrates the importance of PKR in inflammasome activation, and how cellular metabolism influences this activity.

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  35. 35

    Youssef, O. A. et al. Potential role for snoRNAs in PKR activation during metabolic stress. Proc. Natl Acad. Sci. USA 112, 5023–5028 (2015)

    ADS  CAS  PubMed  Google Scholar 

  36. 36

    Michel, C. I. et al. Small nucleolar RNAs U32a, U33, and U35a are critical mediators of metabolic stress. Cell Metab. 14, 33–44 (2011).A paper demonstrating the critical role of small nucleolar RNAs in mediating the detrimental effects of metabolic stress, particularly in response to lipids.

    CAS  PubMed  PubMed Central  Google Scholar 

  37. 37

    Fu, S., Watkins, S. M. & Hotamisligil, G. S. The role of endoplasmic reticulum in hepatic lipid homeostasis and stress signaling. Cell Metab. 15, 623–634 (2012)

    CAS  PubMed  Google Scholar 

  38. 38

    Lancaster, G. I. et al. PKR is not obligatory for high-fat diet-induced obesity and its associated metabolic and inflammatory complications. Nat. Commun. 7, 10626 (2016)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  39. 39

    Hage Hassan, R. et al. Sustained action of ceramide on the insulin signaling pathway in muscle cells: implication of the double-stranded RNA-activated protein kinase. J. Biol. Chem. 291, 3019–3029 (2016)

    PubMed  Google Scholar 

  40. 40

    Chen, S. S. et al. Activation of double-stranded RNA-dependent protein kinase inhibits proliferation of pancreatic β-cells. Biochem. Biophys. Res. Commun. 443, 814–820 (2014)

    CAS  PubMed  Google Scholar 

  41. 41

    Song, Y. et al. Activated PKR inhibits pancreatic β-cell proliferation through sumoylation-dependent stabilization of P53. Mol. Immunol. 68 (2 Pt A), 341–349 (2015)

    CAS  PubMed  Google Scholar 

  42. 42

    Yang, H. et al. Obesity increases the production of proinflammatory mediators from adipose tissue T cells and compromises TCR repertoire diversity: implications for systemic inflammation and insulin resistance. J. Immunol. 185, 1836–1845 (2010)

    CAS  PubMed  PubMed Central  Google Scholar 

  43. 43

    Feuerer, M. et al. Lean, but not obese, fat is enriched for a unique population of regulatory T cells that affect metabolic parameters. Nat. Med. 15, 930–939 (2009)

    CAS  PubMed  PubMed Central  Google Scholar 

  44. 44

    Winer, S. et al. Normalization of obesity-associated insulin resistance through immunotherapy. Nat. Med. 15, 921–929 (2009)

    CAS  PubMed  PubMed Central  Google Scholar 

  45. 45

    Ilan, Y. et al. Induction of regulatory T cells decreases adipose inflammation and alleviates insulin resistance in ob/ob mice. Proc. Natl Acad. Sci. USA 107, 9765–9770 (2010)

    ADS  CAS  PubMed  Google Scholar 

  46. 46

    Bapat, S. P. et al. Depletion of fat-resident Treg cells prevents age-associated insulin resistance. Nature 528, 137–141 (2015)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  47. 47

    Cipolletta, D. et al. PPAR-γ is a major driver of the accumulation and phenotype of adipose tissue Treg cells. Nature 486, 549–553 (2012).This paper demonstrates that an established anti-diabetic agent produces its anti-inflammatory and anti-diabetic effects through PPARγ n T reg cells.

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  48. 48

    Winer, D. A. et al. B cells promote insulin resistance through modulation of T cells and production of pathogenic IgG antibodies. Nat. Med. 17, 610–617 (2011)

    CAS  PubMed  PubMed Central  Google Scholar 

  49. 49

    DeFuria, J. et al. B cells promote inflammation in obesity and type 2 diabetes through regulation of T-cell function and an inflammatory cytokine profile. Proc. Natl Acad. Sci. USA 110, 5133–5138 (2013)

    ADS  CAS  PubMed  Google Scholar 

  50. 50

    Nishimura, S. et al. Adipose natural regulatory B cells negatively control adipose tissue inflammation. Cell Metab. 18, 759–766 (2013)

    CAS  PubMed  Google Scholar 

  51. 51

    Ji, Y. et al. Activation of natural killer T cells promotes M2 macrophage polarization in adipose tissue and improves systemic glucose tolerance via interleukin-4 (IL-4)/STAT6 protein signaling axis in obesity. J. Biol. Chem. 287, 13561–13571 (2012)

    CAS  PubMed  PubMed Central  Google Scholar 

  52. 52

    Lynch, L. Adipose invariant natural killer T cells. Immunology 142, 337–346 (2014)

    CAS  PubMed  PubMed Central  Google Scholar 

  53. 53

    Kwon, H. et al. Adipocyte-specific IKKβ signaling suppresses adipose tissue inflammation through an IL-13-dependent paracrine feedback pathway. Cell Reports 9, 1574–1583 (2014).This important paper demonstrates the anti-inflammatory activity of the IKK pathway, and shows that IKK activation is not equivalent to inflammation owing to its impact on resolution in the adipose tissue.

    CAS  PubMed  PubMed Central  Google Scholar 

  54. 54

    Zhang, X. et al. Hypothalamic IKKβ/NF-κB and ER stress link overnutrition to energy imbalance and obesity. Cell 135, 61–73 (2008)

    CAS  PubMed  PubMed Central  Google Scholar 

  55. 55

    Goldfine, A. B. et al. Salicylate (salsalate) in patients with type 2 diabetes: a randomized trial. Ann. Intern. Med. 159, 1–12 (2013)

    PubMed  PubMed Central  Google Scholar 

  56. 56

    Hundal, R. S. et al. Mechanism by which high-dose aspirin improves glucose metabolism in type 2 diabetes. J. Clin. Invest. 109, 1321–1326 (2002)

    CAS  PubMed  PubMed Central  Google Scholar 

  57. 57

    Gehart, H., Kumpf, S., Ittner, A. & Ricci, R. MAPK signalling in cellular metabolism: stress or wellness? EMBO Rep. 11, 834–840 (2010)

    CAS  PubMed  PubMed Central  Google Scholar 

  58. 58

    González-Terán, B. et al. p38γ and p38δ reprogram liver metabolism by modulating neutrophil infiltration. EMBO J. 35, 536–552 (2016)

    PubMed  PubMed Central  Google Scholar 

  59. 59

    Hirosumi, J. et al. A central role for JNK in obesity and insulin resistance. Nature 420, 333–336 (2002)

    ADS  CAS  PubMed  Google Scholar 

  60. 60

    Tuncman, G. et al. Functional in vivo interactions between JNK1 and JNK2 isoforms in obesity and insulin resistance. Proc. Natl Acad. Sci. USA 103, 10741–10746 (2006)

    ADS  CAS  PubMed  Google Scholar 

  61. 61

    Sabio, G. et al. A stress signaling pathway in adipose tissue regulates hepatic insulin resistance. Science 322, 1539–1543 (2008).This manuscript shows the pathological role of JNK activity in adipose tissue and demonstrates how this inflammatory input disrupts liver insulin action and glucose metabolism. This paper also addresses the role of JNK1 in macrophages.

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  62. 62

    Tsaousidou, E. et al. Distinct roles for JNK and IKK activation in Agouti-related peptide neurons in the development of obesity and insulin resistance. Cell Reports 9, 1495–1506 (2014)

    CAS  PubMed  Google Scholar 

  63. 63

    Hotamisligil, G. S. Endoplasmic reticulum stress and the inflammatory basis of metabolic disease. Cell 140, 900–917 (2010)

    CAS  PubMed  PubMed Central  Google Scholar 

  64. 64

    Zhang, K. & Kaufman, R. J. From endoplasmic-reticulum stress to the inflammatory response. Nature 454, 455–462 (2008)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  65. 65

    Keestra-Gounder, A. M. et al. NOD1 and NOD2 signalling links ER stress with inflammation. Nature 532, 394–397 (2016)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  66. 66

    Oslowski, C. M. et al. Thioredoxin-interacting protein mediates ER stress-induced β cell death through initiation of the inflammasome. Cell Metab. 16, 265–273 (2012)

    CAS  PubMed  PubMed Central  Google Scholar 

  67. 67

    Bettigole, S. E. & Glimcher, L. H. Endoplasmic reticulum stress in immunity. Annu. Rev. Immunol. 33, 107–138 (2015)

    CAS  PubMed  Google Scholar 

  68. 68

    Yang, L. et al. S-Nitrosylation links obesity-associated inflammation to endoplasmic reticulum dysfunction. Science 349, 500–506 (2015)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  69. 69

    Jurczak, M. J. et al. Dissociation of inositol-requiring enzyme (IRE1α)-mediated c-Jun N-terminal kinase activation from hepatic insulin resistance in conditional X-box-binding protein-1 (XBP1) knock-out mice. J. Biol. Chem. 287, 2558–2567 (2012)

    CAS  PubMed  Google Scholar 

  70. 70

    Turner, N. & Heilbronn, L. K. Is mitochondrial dysfunction a cause of insulin resistance? Trends Endocrinol. Metab. 19, 324–330 (2008)

    CAS  PubMed  Google Scholar 

  71. 71

    Morino, K., Petersen, K. F. & Shulman, G. I. Molecular mechanisms of insulin resistance in humans and their potential links with mitochondrial dysfunction. Diabetes 55 (Suppl 2), S9–S15 (2006)

    CAS  PubMed  PubMed Central  Google Scholar 

  72. 72

    Freemerman, A. J. et al. Metabolic reprogramming of macrophages: glucose transporter 1 (GLUT1)-mediated glucose metabolism drives a proinflammatory phenotype. J. Biol. Chem. 289, 7884–7896 (2014)

    CAS  PubMed  PubMed Central  Google Scholar 

  73. 73

    Miao, H. et al. Macrophage CGI-58 deficiency activates ROS-inflammasome pathway to promote insulin resistance in mice. Cell Reports 7, 223–235 (2014)

    CAS  PubMed  PubMed Central  Google Scholar 

  74. 74

    Bogacka, I., Xie, H., Bray, G. A. & Smith, S. R. Pioglitazone induces mitochondrial biogenesis in human subcutaneous adipose tissue in vivo. Diabetes 54, 1392–1399 (2005)

    CAS  PubMed  Google Scholar 

  75. 75

    Kelley, D. E., He, J., Menshikova, E. V. & Ritov, V. B. Dysfunction of mitochondria in human skeletal muscle in type 2 diabetes. Diabetes 51, 2944–2950 (2002)

    CAS  PubMed  Google Scholar 

  76. 76

    Arruda, A. P. et al. Chronic enrichment of hepatic endoplasmic reticulum-mitochondria contact leads to mitochondrial dysfunction in obesity. Nat. Med. 20, 1427–1435 (2014)

    CAS  PubMed  PubMed Central  Google Scholar 

  77. 77

    Fujita, H. et al. The E3 ligase synoviolin controls body weight and mitochondrial biogenesis through negative regulation of PGC-1β. EMBO J. 34, 1042–1055 (2015)

    CAS  PubMed  PubMed Central  Google Scholar 

  78. 78

    Arruda, A. P. & Hotamisligil, G. S. Calcium homeostasis and organelle function in the pathogenesis of obesity and diabetes. Cell Metab. 22, 381–397 (2015)

    CAS  PubMed  PubMed Central  Google Scholar 

  79. 79

    Randle, P. J., Garland, P. B., Hales, C. N. & Newsholme, E. A. The glucose fatty-acid cycle. Its role in insulin sensitivity and the metabolic disturbances of diabetes mellitus. Lancet 281, 785–789 (1963)

    Google Scholar 

  80. 80

    McGarry, J. D. Glucose-fatty acid interactions in health and disease. Am. J. Clin. Nutr. 67 (Suppl), 500S–504S (1998)

    CAS  PubMed  Google Scholar 

  81. 81

    Glass, C. K. & Olefsky, J. M. Inflammation and lipid signaling in the etiology of insulin resistance. Cell Metab. 15, 635–645 (2012)

    CAS  PubMed  PubMed Central  Google Scholar 

  82. 82

    Nguyen, M. T. et al. JNK and tumor necrosis factor-a mediate free fatty acid-induced insulin resistance in 3T3-L1 adipocytes. J. Biol. Chem. 280, 35361–35371 (2005). This paper demonstrates that FFAs induce insulin resistance in cells by activating inflammatory cascades involving JNK and IKK.

    CAS  PubMed  Google Scholar 

  83. 83

    Tynan, G. A. et al. Endogenous oils derived from human adipocytes are potent adjuvants that promote IL-1α-dependent inflammation. Diabetes 63, 2037–2050 (2014)

    CAS  PubMed  Google Scholar 

  84. 84

    Yu, C. et al. Mechanism by which fatty acids inhibit insulin activation of insulin receptor substrate-1 (IRS-1)-associated phosphatidylinositol 3-kinase activity in muscle. J. Biol. Chem. 277, 50230–50236 (2002)

    CAS  PubMed  Google Scholar 

  85. 85

    Lee, J. Y. et al. Reciprocal modulation of Toll-like receptor-4 signaling pathways involving MyD88 and phosphatidylinositol 3-kinase/AKT by saturated and polyunsaturated fatty acids. J. Biol. Chem. 278, 37041–37051 (2003)

    CAS  PubMed  Google Scholar 

  86. 86

    Huang, S. et al. Saturated fatty acids activate TLR-mediated proinflammatory signaling pathways. J. Lipid Res. 53, 2002–2013 (2012)

    CAS  PubMed  PubMed Central  Google Scholar 

  87. 87

    Davis, J. E., Gabler, N. K., Walker-Daniels, J. & Spurlock, M. E. Tlr-4 deficiency selectively protects against obesity induced by diets high in saturated fat. Obesity (Silver Spring) 16, 1248–1255 (2008)

    CAS  Google Scholar 

  88. 88

    Jin, C., Henao-Mejia, J. & Flavell, R. A. Innate immune receptors: key regulators of metabolic disease progression. Cell Metab. 17, 873–882 (2013)

    CAS  PubMed  Google Scholar 

  89. 89

    Kleinridders, A. et al. MyD88 signaling in the CNS is required for development of fatty acid-induced leptin resistance and diet-induced obesity. Cell Metab. 10, 249–259 (2009)

    CAS  PubMed  PubMed Central  Google Scholar 

  90. 90

    Sampey, B. P. et al. Metabolomic profiling reveals mitochondrial-derived lipid biomarkers that drive obesity-associated inflammation. PLoS One 7, e38812 (2012)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  91. 91

    Lim, J. et al. Diet-induced obesity, adipose inflammation, and metabolic dysfunction correlating with PAR2 expression are attenuated by PAR2 antagonism. FASEB J. 27, 4757–4767 (2013)

    ADS  CAS  PubMed  Google Scholar 

  92. 92

    Bikman, B. T. & Summers, S. A. Ceramides as modulators of cellular and whole-body metabolism. J. Clin. Invest. 121, 4222–4230 (2011)

    CAS  PubMed  PubMed Central  Google Scholar 

  93. 93

    Griffin, M. E. et al. Free fatty acid-induced insulin resistance is associated with activation of protein kinase C theta and alterations in the insulin signaling cascade. Diabetes 48, 1270–1274 (1999)

    CAS  PubMed  Google Scholar 

  94. 94

    Szendroedi, J. et al. Role of diacylglycerol activation of PKCθ in lipid-induced muscle insulin resistance in humans. Proc. Natl Acad. Sci. USA 111, 9597–9602 (2014).This study shows that in human subjects lipid-induced insulin resistance in muscle is associated with DAG–PKC activation.

    ADS  CAS  PubMed  Google Scholar 

  95. 95

    Kim, J. K. et al. PKC-θ knockout mice are protected from fat-induced insulin resistance. J. Clin. Invest. 114, 823–827 (2004)

    CAS  PubMed  PubMed Central  Google Scholar 

  96. 96

    Serra, C. et al. Transgenic mice with dominant negative PKC-theta in skeletal muscle: a new model of insulin resistance and obesity. J. Cell. Physiol. 196, 89–97 (2003)

    CAS  PubMed  Google Scholar 

  97. 97

    Kewalramani, G., Fink, L. N., Asadi, F. & Klip, A. Palmitate-activated macrophages confer insulin resistance to muscle cells by a mechanism involving protein kinase C θ and ε. PLoS One 6, e26947 (2011)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  98. 98

    Yilmaz, M., Claiborn, K. C. & Hotamisligil, G. S. De novo lipogenesis products and endogenous lipokines. Diabetes 65, 1800–1807 (2016)

    CAS  PubMed  PubMed Central  Google Scholar 

  99. 99

    Fox, M. J., Kuzma, J. F. & Washam, W. T. Transitory diabetic syndrome associated with meningococcic meningitis. Arch. Intern. Med. (Chic.) 79, 614–621 (1947)

    CAS  Google Scholar 

  100. 100

    Dimas, A. S. et al. Impact of type 2 diabetes susceptibility variants on quantitative glycemic traits reveals mechanistic heterogeneity. Diabetes 63, 2158–2171 (2014)

    CAS  PubMed  PubMed Central  Google Scholar 

  101. 101

    McCarthy, M. I. Genomics, type 2 diabetes, and obesity. N. Engl. J. Med. 363, 2339–2350 (2010)

    CAS  PubMed  Google Scholar 

  102. 102

    Florez, J. C. Newly identified loci highlight beta cell dysfunction as a key cause of type 2 diabetes: where are the insulin resistance genes? Diabetologia 51, 1100–1110 (2008)

    CAS  PubMed  Google Scholar 

  103. 103

    Jain, P. et al. Systems biology approach reveals genome to phenome correlation in type 2 diabetes. PLoS One 8, e53522 (2013)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  104. 104

    Manning, A. K. et al. A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance. Nat. Genet. 44, 659–669 (2012)

    CAS  PubMed  PubMed Central  Google Scholar 

  105. 105

    Kooner, J. S. et al. Genome-wide association study in individuals of South Asian ancestry identifies six new type 2 diabetes susceptibility loci. Nat. Genet. 43, 984–989 (2011)

    CAS  PubMed  PubMed Central  Google Scholar 

  106. 106

    Cho, Y. S. et al. Meta-analysis of genome-wide association studies identifies eight new loci for type 2 diabetes in east Asians. Nat. Genet. 44, 67–72 (2011)

    PubMed  PubMed Central  Google Scholar 

  107. 107

    Waeber, G. et al. The gene MAPK8IP1, encoding islet-brain-1, is a candidate for type 2 diabetes. Nat. Genet. 24, 291–295 (2000).This paper identifies a mutation in MAPK81P1 which causes constitutive JNK activation in humans leading to a Mendelian form of diabetes.

    CAS  PubMed  Google Scholar 

  108. 108

    Ichimura, A. et al. Dysfunction of lipid sensor GPR120 leads to obesity in both mouse and human. Nature 483, 350–354 (2012).This paper examines the role of GPR120, which was previously demonstrated by the Olefsky laboratory to be a lipid sensor critical for immunometabolism and diabetes, in human genetic studies.

    ADS  CAS  PubMed  Google Scholar 

  109. 109

    Locke, A. E. et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 518, 197–206 (2015)

    CAS  PubMed  PubMed Central  Google Scholar 

  110. 110

    Shungin, D. et al. New genetic loci link adipose and insulin biology to body fat distribution. Nature 518, 187–196 (2015)

    CAS  PubMed  PubMed Central  Google Scholar 

  111. 111

    Brown, A. E. et al. p38 MAPK activation upregulates proinflammatory pathways in skeletal muscle cells from insulin-resistant type 2 diabetic patients. Am. J. Physiol. Endocrinol. Metab. 308, E63–E70 (2015)

    CAS  PubMed  Google Scholar 

  112. 112

    Toubal, A., Treuter, E., Clément, K. & Venteclef, N. Genomic and epigenomic regulation of adipose tissue inflammation in obesity. Trends Endocrinol. Metab. 24, 625–634 (2013)

    CAS  PubMed  Google Scholar 

  113. 113

    Burska, A. N., Sakthiswary, R. & Sattar, N. Effects of tumour necrosis factor antagonists on insulin sensitivity/resistance in rheumatoid arthritis: a systematic review and meta-analysis. PLoS One 10, e0128889 (2015)

    PubMed  PubMed Central  Google Scholar 

  114. 114

    Solomon, D. H. et al. Association between disease-modifying antirheumatic drugs and diabetes risk in patients with rheumatoid arthritis and psoriasis. J. Am. Med. Assoc. 305, 2525–2531 (2011)

    CAS  Google Scholar 

  115. 115

    Donath, M. Y. Targeting inflammation in the treatment of type 2 diabetes: time to start. Nat. Rev. Drug Discov. 13, 465–476 (2014)

    CAS  PubMed  Google Scholar 

  116. 116

    Schork, N. J. Personalized medicine: time for one-person trials. Nature 520, 609–611 (2015)

    ADS  CAS  PubMed  Google Scholar 

  117. 117

    Cerami, A. TNF and EPO: major players in the innate immune response: their discovery. Ann. Rheum. Dis. 71 (Suppl 2), i55–i59 (2012)

    CAS  PubMed  Google Scholar 

  118. 118

    Collino, M. et al. A non-erythropoietic peptide derivative of erythropoietin decreases susceptibility to diet-induced insulin resistance in mice. Br. J. Pharmacol. 171, 5802–5815 (2014)

    CAS  PubMed  PubMed Central  Google Scholar 

  119. 119

    Brines, M. et al. ARA 290, a nonerythropoietic peptide engineered from erythropoietin, improves metabolic control and neuropathic symptoms in patients with type 2 diabetes. Mol. Med. 20, 658–666 (2015)

    PubMed  PubMed Central  Google Scholar 

  120. 120

    Kothari, V., Galdo, J. A. & Mathews, S. T. Hypoglycemic agents and potential anti-inflammatory activity. J. Inflamm. Res. 9, 27–38 (2016)

    CAS  PubMed  PubMed Central  Google Scholar 

  121. 121

    Scheen, A. J., Esser, N. & Paquot, N. Antidiabetic agents: potential anti-inflammatory activity beyond glucose control. Diabetes Metab. 41, 183–194 (2015)

    CAS  PubMed  Google Scholar 

  122. 122

    Lancaster, G. I. & Febbraio, M. A. The immunomodulating role of exercise in metabolic disease. Trends Immunol. 35, 262–269 (2014)

    CAS  PubMed  Google Scholar 

  123. 123

    Coward, W. R., Marei, A., Yang, A., Vasa-Nicotera, M. M. & Chow, S. C. Statin-induced proinflammatory response in mitogen-activated peripheral blood mononuclear cells through the activation of caspase-1 and IL-18 secretion in monocytes. J. Immunol. 176, 5284–5292 (2006)

    CAS  PubMed  Google Scholar 

  124. 124

    Henriksbo, B. D. et al. Fluvastatin causes NLRP3 inflammasome-mediated adipose insulin resistance. Diabetes 63, 3742–3747 (2014).This study demonstrates a direct link between a statin and inflammasome activation, showing a mechanism by which statins may act as pro-inflammatory agents.

    CAS  PubMed  Google Scholar 

  125. 125

    Nishimoto, S. et al. Obesity-induced DNA released from adipocytes stimulates chronic adipose tissue inflammation and insulin resistance. Sci. Adv. 2, e1501332 (2016)

    ADS  PubMed  PubMed Central  Google Scholar 

  126. 126

    Lefere, S. et al. Hypoxia-regulated mechanisms in the pathogenesis of obesity and non-alcoholic fatty liver disease. Cell. Mol. Life Sci. 73, 3419–3431 (2016)

    CAS  PubMed  Google Scholar 

  127. 127

    Minamino, T. et al. A crucial role for adipose tissue p53 in the regulation of insulin resistance. Nat. Med. 15, 1082–1087 (2009)

    CAS  PubMed  Google Scholar 

  128. 128

    Thaler, J. P. et al. Obesity is associated with hypothalamic injury in rodents and humans. J. Clin. Invest. 122, 153–162 (2012)

    CAS  PubMed  Google Scholar 

  129. 129

    Wernstedt Asterholm, I. et al. Adipocyte inflammation is essential for healthy adipose tissue expansion and remodeling. Cell Metab. 20, 103–118 (2014)

    CAS  PubMed  Google Scholar 

  130. 130

    Vereecke, L. et al. A20 controls intestinal homeostasis through cell-specific activities. Nat. Commun. 5, 5103 (2014)

    ADS  CAS  PubMed  Google Scholar 

  131. 131

    Yi, Z., Stunz, L. L. & Bishop, G. A. CD40-mediated maintenance of immune homeostasis in the adipose tissue microenvironment. Diabetes 63, 2751–2760 (2014)

    CAS  PubMed  PubMed Central  Google Scholar 

  132. 132

    Li, Y. et al. A functional genomics approach to understand variation in cytokine production in humans. Cell 167, 1099–1110.e14 (2016)

    CAS  PubMed  Google Scholar 

  133. 133

    ter Horst, R. et al. Host and environmental factors influencing individual human cytokine responses. Cell 167, 1111–1124.e13 (2016)

    CAS  PubMed  PubMed Central  Google Scholar 

  134. 134

    Schirmer, M. et al. Linking the human gut microbiome to inflammatory cytokine production capacity. Cell 167, 1125–1136.e8 (2016)

    CAS  PubMed  PubMed Central  Google Scholar 

  135. 135

    Bogue, M. A., Churchill, G. A. & Chesler, E. J. Collaborative cross and diversity outbred data resources in the Mouse Phenome Database. Mamm. Genome 26, 511–520 (2015)

    CAS  PubMed  PubMed Central  Google Scholar 

  136. 136

    Kebede, M. A. & Attie, A. D. Insights into obesity and diabetes at the intersection of mouse and human genetics. Trends Endocrinol. Metab. 25, 493–501 (2014)

    CAS  PubMed  PubMed Central  Google Scholar 

  137. 137

    Ouchi, N. et al. Sfrp5 is an anti-inflammatory adipokine that modulates metabolic dysfunction in obesity. Science 329, 454–457 (2010)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  138. 138

    Fuster, J. J. et al. Non-canonical Wnt signaling promotes obesity-induced adipose tissue inflammation and metabolic dysfunction independent of adipose tissue expansion. Diabetes 64, 1235–1248 (2015)

    CAS  PubMed  Google Scholar 

  139. 139

    Suzuki, K., Kumanogoh, A. & Kikutani, H. Semaphorins and their receptors in immune cell interactions. Nat. Immunol. 9, 17–23 (2008)

    CAS  PubMed  Google Scholar 

  140. 140

    Shimizu, I. et al. Semaphorin3E-induced inflammation contributes to insulin resistance in dietary obesity. Cell Metab. 18, 491–504 (2013).This study illustrates a new mechanism that couples adipocytes and immune cells and impairs systemic insulin action and glucose metabolism through TNF-mediated inflammatory signals.

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

I am grateful to all members of the Hotamisligil laboratory for helpful discussions, and especially G. Parlakgül for the initial preparation of figures, and K. Claiborn for discussions and invaluable editorial assistance. Work in the Hotamisligil laboratory is supported by grants from the National Institutes of Health (DK052539, HL125753, AI116901), the JDRF (2SRA-2016-147-Q-R), and sponsored research agreements from Union Chemique Belge and Servier.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Gökhan S. Hotamisligil.

Ethics declarations

Competing interests

The author declares no competing financial interests.

Additional information

Reviewer Information Nature thanks M. Febbraio and R. Kahn for their contribution to the peer review of this work.

Supplementary information

Supplementary Information

This file contains a Supplementary Table and Supplementary Figure 1. (PDF 1339 kb)

PowerPoint slides

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Hotamisligil, G. Inflammation, metaflammation and immunometabolic disorders. Nature 542, 177–185 (2017). https://doi.org/10.1038/nature21363

Download citation

Further reading

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing