Although a relationship between obesity and inflammation in fat has been previously observed, in most cases these inflammatory changes have been viewed as being secondary to obesity. Our data, comparing diabetes-prone B6 mouse and diabetes-resistant 129 mouse at 6 weeks of age, show alterations in the inflammatory process in adipose tissue even before differences in metabolic parameters can be detected. Thus, B6 mice exhibit increased expression of the T-cell chemokines SDF1α and CCL5/RANTES and an increased number of T-cells in the fat tissue. These differences are associated with higher IFNγ and CD80 levels in the B6 mice—both molecules are known to participate in T-cell function and activation (25
) (summarized in the model shown in ).
Schematic model illustrating the potential causes and consequences related to the different repertoire of immune cells in adipose tissue of B6 and 129 mice. Solid arrows, secretion; dashed arrows, migration; dotted arrows, migration/differentiation.
Recent work has shown that T-cells infiltrate into the visceral adipose tissue of obese animals and humans with type 2 diabetes, and this is followed by recruitment of macrophages and development of insulin resistance (26
). Based on these findings, a model for the role of T-cells in the pathogenesis of obesity and insulin resistance has been proposed in which increases in SDF1α and CCL5/RANTES levels in adipose tissue occur in response to an obesogenic environment and promote infiltration with T lymphocytes (29
). IFNγ derived from these T-cells then promotes MCP1 secretion by preadipocytes (and possibly other cell types), resulting in recruitment of macrophages that further contribute to insulin resistance by production of proinflammatory cytokines (29
Our study provides evidence to support a major impact of the genetic background of different mouse strains in the migration of T-cells to the adipose tissue, both in the basal state and in response to weight gain. In B6 mice, the number of T-cells in the adipose tissue correlates positively with the increase in adipose mass as a consequence of aging or HFD. By contrast, this response is practically absent in 129 mice despite a significant increase in adiposity in response to age or HFD. Thus, similar to mice with ablation of T-cells (27
), 129 mice develop only mild insulin resistance in response to obesity. To what extent aging and the composition of the diet impact the infiltration of T-cells into adipose tissue, in addition to the effects of weight gain, remain to be determined. It is clear though that insulin resistance in response to increased adiposity differ substantially between mouse strains, and this phenomenon is correlated with the migration of T-cell to the adipose tissue. Thus, inflammation in the adipose tissue does not always correlate with weight gain and is strongly dependent on the genetic background of the host. Similar differences dependent on genetic background are likely to occur in humans and contribute to differences in obesity-induced diabetes risk in different ethnic groups or even different individuals, allowing for some of the “fat-fit” phenotype.
Among other implications, these observations clearly impact the choice of models for metabolic studies, in particular when knockout mice are used. Knockout mice are often derived from the embryonic stem cells of 129 mice, and therefore, in many cases, studies are performed on mice on a pure 129 background or mixed 129/B6 background. In these cases, backcrossing to B6 mice for several generations usually potentiates the inflammatory and metabolic response of the model to environmental factors. However, it is not clear which of these backgrounds (B6, 129, or mixed) most closely mimic the human condition.
Other recent reports support our findings that metabolic disease traits can be associated with alterations of inflammatory gene expression networks in the adipose tissue and liver (30
). However, to our knowledge, no study has previously demonstrated a measurable difference in inflammation preceding any measurable phenotypic difference associated with metabolic diseases. The novelty of our study is that, by comparing young B6 and 129 animals using a sensitive computational approach, we can focus on factors that can potentially predispose to disease in a prospective manner and avoid findings that are mainly secondary to obesity or metabolic differences. Our investigation also examined differences between B6 and 129 mice in multiple organs, allowing us to conclude that inflammation in adipose tissue, and to a lesser extent in liver, but not in skeletal muscle or spleen, is associated with the predisposition to insulin resistance. In addition, our computational analysis was able to set forth hypotheses that led to subsequent biologic validation experiments which provided further insight into the components of the immune system that may contribute to metabolic diseases (i.e., T-cell recruitment).
In addition to inflammation, other phenomena have been shown to participate in the multifactorial pathophysiology of insulin resistance. Alterations in insulin receptor levels and insulin signaling through IRS-proteins (32
), induction of the unfolded protein response (33
) and oxidative stress pathways (34
), and changes in lipid (35
) and amino acid metabolism (36
) can all promote insulin resistance and contribute to the final phenotype. Many of these pathways act by producing post-translational modifications of signaling proteins, such as phosphorylation or alterations in compartmentalization, which would not be detected as changes at the gene expression level. In this regard it is worth noting that in addition to differences in inflammation, GNEA analysis was able to identify other gene sets differentially expressed between the mouse strains in adipose tissue at 6 weeks of age (supplementary Table S2), including networks related to signal transduction, protein secretion pathways, and glucose catabolism. Many of these pathways can interact with inflammatory pathways, and this crosstalk could represent an entry point to the manifestation of metabolic diseases. Thus, although changes in the immune response are definitely one of the factors that precedes and predicts the tendency of B6 mice to have greater insulin resistance than 129, it is unlikely that inflammation is the only predisposing risk factor associated with diabetes between these two mouse strains.
In summary, it has been proposed that type 2 diabetes and obesity are diseases associated with an immune system that cannot cope appropriately with environmental threats (37
). Based on this hypothesis, anti-inflammatory drugs, such as salicylates (40
) and interleukin-1 blockers (42
), have been used to improve glycemia in individuals with type 2 diabetes. In this study, we demonstrate that pre-existing differences in the inflammatory milieu in metabolically active tissues may represent an important component of the genetic background as a risk factor to metabolic diseases. Thus, inflammation cannot be viewed as only a mechanism that links susceptibility factors such as overfeeding, underactivity, aging, and stress to metabolic diseases—it may also link these pathologies to heritability. Our study indicates that inflammation is an important early variable in the metabolic response to environmental challenges and suggests several potential targets for intervention, including LBP, Ly86, SDF1α, CCL5/RANTES, and MCP1. This provides new strategies for reducing the epidemic of type 2 diabetes and metabolic diseases in spite of increasing obesity by attacking the variable genetic risk.