Insulin resistance, adipose depots and gut: Interactions and pathological implications

Digestive and Liver Disease 42 (2010) 310–319

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Insulin resistance, adipose depots and gut: Interactions and pathological implications Amalia Gastaldelli a,∗ , Andrea Natali b , Roberto Vettor c , Stefano Ginanni Corradini d a

Institute of Clinical Physiology, Stable Isotope Laboratory, CNR-National Research Council, Pisa, Italy Department of Internal Medicine, University of Pisa, Italy c Department of Medical and Surgical Sciences, University of Padova, Italy d Division of Gastroenterology, Department of Clinical Medicine, University “Sapienza” of Rome, Italy b

a r t i c l e

i n f o

Article history: Received 12 January 2010 Accepted 17 January 2010 Available online 2 March 2010 Keywords: Adipose tissue Gut microbiota Hepatic fat NAFLD Obesity

a b s t r a c t This review article focuses on the many metabolic actions of insulin at the level of muscle, liver and adipose tissue. In terms of pathogenetic mechanisms, the condition of insulin resistance is complex, as multiple genetic and environmental factors, among which an increasingly sedentary lifestyle associated with high-fat diet, mutually interact according to variable patterns in time in any given individual. It is well recognized that obesity (in particular abdominal obesity) favours the development of insulin resistance. Here we evaluate the impact of obesity and ectopic fat accumulation (visceral and hepatic) on insulin resistance at the level of different target organs, i.e., muscle, liver and adipose tissue. The roles of the gut and the liver, in particular of bile acids and gut microflora, are also discussed as possible determinants of energy balance and glucose metabolism. © 2010 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

1. Insulin resistance (IR): sites, mechanisms and measurements Insulin is an essential hormone produced by the beta cells of the pancreatic islets of Langerhans and secreted into the portal circulation mainly in response to plasma glucose concentration gradients. Before entering the systemic circulation, insulin is substantially (approximately 50%) cleared by the liver, which acts as a filter modulating its concentration. Insulin acts on metabolism of carbohydrates, lipids, protein, ions, and nucleic acids. IR is defined as an impairment in insulin action on glucose metabolism. Insulin sensitivity (the opposite of IR) quantifies the ability of insulin to control blood glucose concentration by stimulating glucose uptake (in peripheral tissue, mainly skeletal muscle) and suppressing its production (mainly in the liver). The liver is the principle determinant of glucose concentration in the fasting state. Fasting hyperglycemia is prevented as long as hepatic glucose production (HGP) is sensitive to insulin and/or beta cells are sensitive to small changes in plasma glucose. On the other hand, in the postprandial state, elevated glucose concentrations are determined mainly by both beta cell ability to produce insulin with the proper dynamics in response to large changes in

∗ Corresponding author. Tel.: +39 050 3152679; fax: +39 050 3152166. E-mail addresses: [email protected], [email protected] (A. Gastaldelli).

plasma glucose, and by peripheral tissue insulin sensitivity. In general, postprandial glycemia starts to increase long before hepatic autoregulation is lost, because its regulation is more complex. In the following paragraphs we will focus on the principal sites of IR. 1.1. Techniques to measure peripheral IR in humans The gold standard for the measurement of peripheral IR is the euglycemic hyperinsulinemic clamp technique [1]. The rate of glucose disposal (i.e., rate of exogenous glucose infusion) during the hyperinsulinemic phase of the study provides a measure of peripheral insulin sensitivity. Most often, studies are performed choosing an insulin infusion rate of 40 mU m−2 min−1 for 2 h to achieve a physiological level of serum insulin around 600 pmol/l (100 ␮U/ml). At this level of hyperinsulinemia, in normal healthy subjects endogenous (hepatic) glucose production is totally suppressed, and thus, estimation of glucose disposal is highly accurate. However, HGP may not be fully suppressed in patients with generalized and regional obesity or diabetes, at serum insulin concentrations of approximately 600 pmol/l, which may introduce an error in the estimation of glucose disposal. Under these conditions, simultaneous infusion of either radiolabelled or stable isotopes of glucose, which provides a measure of HGP during the fasting condition and during the hyperinsulinemic phase, is required (Table 1). Another test used is the intravenous glucose tolerance test (IVGTT) that consists in intravenous administration of a glucose bolus (300 mg/kg body wt within 2 min), and insulin infusion

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Table 1 Most common tests for the estimation of IR. Type of test

Estimation of peripheral IR

Estimation of hepatic IR

Incretin response

Length and difficulty of study

Number of blood samples

Euglycemic hyperinsulinemic clamp Intravenous glucose tolerance test (IVGTT) Oral glucose tolerance test (OGTT) Fasting values of insulin and glucose

Yes, as glucose disposal rate (M value) Yes, as SI from minimal model

Only if a glucose tracer is infused, as residual EGP Only if a glucose tracer is infused, as residual EGP Only if a glucose tracer is infused, as residual EGP HOMA, QUICKI

No

From 150 min (no tracer), to 300 min (with tracer) Requires Nurse + MD 180 min Requires Nurse + MD

8 samples

Yes

150 min Requires Nurse

5 samples

No

10 min Nurse

1 sample

Yes, from derived indexes (OGIS, Matsuda) HOMA, QUICKI

No

(approximately 13–20 mU/kg given over 5 min) from 20 to 25 min after administration of glucose. The entire exam lasts 180 min, it requires several plasma samples for the measurement of glucose and insulin concentration and the calculation of the insulin sensitivity is performed using the minimal model [2]. Given the difficulty in performing the euglycemic hyperinsulinemic clamp or the IVGTT, many indexes have been developed and validated against the clamp. Among the “basic” indexes are those that use fasting values of insulin (FPI) and glucose (FPG), like HOMA-IR [3] or the QUICKI [4]. The two indexes are similar; HOMA is an index of IR based on the product of insulin and glucose concentration (FPI × FPG/22.5). QUICKI is an index of insulin sensitivity and uses a log transformation of the product of insulin and glucose concentration (insulin sensitivity = 1/log(FPI × FPG)). Although they have been validated against the clamp, they are not good indexes to quantify IR in poorly controlled type 2 diabetes, since in these subjects there is a deterioration of beta cell function, with increased hyperglycemia as insulin secretion decreases. In addition, as discussed in the liver section, they are more closely related to liver insulin sensitivity. Other indexes have been derived from oral glucose tolerance test (OGTT). Among these the most used are the OGIS [5] and the Matsuda [6] index (Table 2). Both have been validated in diabetic and non-diabetic subjects against the euglycemic hyperinsulinemic clamp. They are very simple since they use glucose and insulin concentration measured during the 2 h following the ingestion of glucose (75 g). Many other indexes have been developed, including other parameters such as age, gender, and BMI, but these were either validated only in non-diabetic subjects, or they resulted less effective to the above two and are therefore less used [7].

27 samples

1.2. Mechanisms of IR in skeletal muscle Conventionally IR, as measured by these techniques refers to peripheral, i.e., skeletal muscle, glucose metabolism since muscle is quantitatively the major site of insulin-stimulated glucose uptake. In addition to muscle fibres, characteristics related to mitochondrial function and vascularization, one of the more relevant – and prevalent – causes of IR is an increased plasma free fatty acid (FFA) concentration (Fig. 1). Following Randle’s hypothesis [8], many studies have addressed the mechanistic link between lipid excess and IR. Certain predictions of the Randle’s cycle, namely, increased cellular citrate and glucose-6-phosphate levels and accelerated fat oxidation, have not been observed in experimental studies of human made insulin resistant by lipid infusions [9,10]. Additional effects of lipids may be required to explain the observed impairment in insulin sensitivity. Recently, a number of defects in intracellular insulin signalling have been described in type 2 diabetes and obesity, and in animal models of IR. Because certain lipid species are second messengers themselves, it is possible that increased tissue lipid availability may activate pathways that lead to attenuation of insulin signals. It has been observed that IR in skeletal muscle during FFA infusion arises when triglycerides start to accumulate inside muscle fibres [11] in excess of their oxidation. One of the major defects is in the impairment in insulin receptor substrate-1 (IRS1)-associated phosphatidyl inositol-3-kinase (PI-3K) activity. In fact, excessive storage of intramyocellular lipids may be associated with the accumulation of intracellular signalling molecules (i.e., ceramide, diacylglycerol, and protein kinase C, with the activation of the I␬␤-kinase (IKK-␤)/I␬␤-nuclear factor (NF)-␬␤ pathway)

Table 2 Simple indexes for the estimation of IR. Site of IR

INDEX

Type of Test

Type of subjects

Peripheral IR

OGIS

Peripheral IR

ISI (insulin sensitivity Index or Matsuda index)

Hepatic IR

Glucose production × FPI

Both diabetic and non-diabetic subjects Both diabetic and non-diabetic subjects Both diabetic and non-diabetic subjects

Hepatic IR

FPG × FPI HOMA 1/QUICKI

OGTT (120 or 180 min, 3 plasma samples for glucose and 2 plasma samples for insulin) OGTT (120 min, 5 plasma samples for glucose and insulin concentration) Glucose tracer infusion (120 min for non-diabetic, 180 min for diabetic subjects, 5 plasma samples for glucose and 1 for insulin concentration) Fasting state 1 Plasma samples for glucose and insulin concentration

Adipose tissue IR

Lipolysis × FPI

Glycerol tracer infusion

Adipose tissue IR

FFA × FPI

Fasting state 1 Plasma samples for FFA and insulin concentration

Both diabetic and non-diabetic subjects Both diabetic and non-diabetic subjects

FPG = fasting plasma glucose concentration. FPI = fasting plasma insulin concentration. FFAs = free fatty acids.

Both diabetic and non-diabetic subjects

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Fig. 1. Sites of insulin action and impairment due to the presence of IR (HGP, hepatic glucose production; VLDL, very low-density lipoprotein; FFAs, free fatty acids).

[12] that may feed back to inhibit PI-3K activity associated with IRS-1. 1.3. Adipose tissue IR Another important site of peripheral glucose uptake, and therefore of IR, is adipose tissue (Fig. 1). Triglycerides are synthesized inside the adipocyte by the reaction between three molecules of fatty acids and one molecule of glycerol-3-phosphate, which is derived from glucose since adipocytes lack the enzyme glycerol kinase (to convert glycerol into glycerol-3-phosphate). It is of note that peripheral glucose uptake measured with either the clamp, IVGTT technique or the indexes cannot distinguish between muscle and adipose tissue uptake (even if muscle is the major site of insulin-stimulated glucose uptake) but it indicates total glucose disposal. Besides promoting glucose uptake, insulin has two important roles at the level of adipose tissue: promoting fatty acids re-esterification into triglyceride, and also inhibiting triglyceride hydrolysis and release of FFA into the circulation (lipolysis). Impairment of insulin action at the level of adipose tissue results also in excess release of FFAs into the circulation. Several studies have shown that elevated FFA concentrations are linked with the onset of peripheral and hepatic IR [13,14] (Fig. 1). Elevated FFA and intracellular lipids appear to inhibit insulin signalling, leading to a reduction in insulin-stimulated muscle glucose transport that may be mediated by a decrease in GLUT-4 translocation [13]. The resulting suppression of muscle glucose transport leads to reduced muscle glycogen synthesis and glycolysis. In the liver, elevated FFA may contribute to hyperglycaemia by antagonizing the effects of insulin on endogenous glucose production. It has been shown that in healthy humans, acute and chronic lipid infusion determines peripheral and hepatic IR [13,15], induces hyperinsulinemia

by increasing both fasting and glucose-stimulated insulin secretion [15,16]. Since the fasting plasma insulin concentration is a strong inhibitory stimulus for lipolysis [17], an index of adipocyte IR can be calculated [18] as the product of the fasting lipolysis and insulin concentration (adipose IR index = lipolysis × FPI) (Fig. 2). However, this index requires the measurement of fasting lipolysis by infusing a glycerol tracer [18]. Alternatively, since FFA concentration is proportional to lipolysis, the adipose IR index can be calculated as FFA × FPI [19]. 1.4. Hepatic IR Other insulin sensitive organs can be the target of IR; among these the most important is the liver, which synthesizes and stores

Fig. 2. As insulin concentration increases, glucose production (HGP) and lipolysis decrease following a non-linear curve (Ref. [17]). Presence of hepatic and adipose tissue IR can be estimated in fasting state by the product of glucose or lipid flux and insulin concentration.

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glucose. In particular, insulin modulates HGP by inhibiting HGP during fasting and promoting glycogen synthesis during the postprandial state. Impairment in insulin action at the level of the liver is called hepatic IR. Endogenous glucose can be produced either from glycogenolysis or gluconeogenesis (GNG). During fasting, insulin acts in the liver mainly by reducing glycogenolysis [13,20], while during the postprandial state the effect is on both GNG and glycogenolysis [21]. Insulin-resistant subjects have increased fasting GNG compared to their lean counterparts [22], despite normal HGP. On the other hand, during the euglycemic hyperinsulinemic clamp the normal suppression of HGP is blunted in IR subjects, and the residual HGP is mainly due to unrestrained GNG [20]. This can be considered an early manifestation of hepatic IR. Hepatic IR has been found to exist in both obese non-diabetic and obese type 2 diabetic patients and is considered to be a dominant component in the pathogenesis of fasting hyperglycemia in type 2 diabetes [23]. It has been suggested that hepatic IR may be directly related to visceral adiposity, independent of total fat mass [19,24]. Hepatic IR is also a characteristic feature of subjects with non-alcoholic fatty liver [18,19]. Although the mechanisms of IR in the liver are imperfectly understood, a role for elevated plasma FFA has been postulated (Fig. 1). While raised FFA concentrations promote liver GNG [25], when plasma FFA were experimentally lowered in healthy volunteers changes in GNG mirrored the changes in plasma FFA, while glycogenolysis was inversely correlated with FFA concentrations [25]. Another possible mechanism is through the activity of phosphoenolpyruvate carboxykinase (PEPCK) that is thought to be the rate-limiting enzyme responsible for converting several gluconeogenic precursors in the gluconeogenic pathways. It has been shown that both a high-fat diet and high-sucrose diet increase GNG through an increase in PEPCK flux. So far, there is no gold standard method to measure hepatic IR. An index of hepatic IR can be obtained during euglycemic hyperinsulinemic clamp by infusing a glucose tracer and measuring the suppression of HGP. The main problem with this index is that, as previously mentioned, most clamp studies are performed with an insulin infusion rate of 40 mU m−2 min−1 , which induces full suppression of HGP in most non-diabetic subjects. It is therefore difficult to have a precise estimation of hepatic IR. A reasonable alternative is a low-dose (e.g., 10 mU m−2 min−1 ) insulin clamp coupled with tracer glucose infusion. A few indices have been derived using measurement at fasting. Fasting hepatic IR can be estimated from the product of endogenous glucose production and fasting plasma insulin (hepatic IR index = HGP × FPI) (Fig. 2, Table 2). The logic behind this calculation is as follows: (1) under basal conditions, the majority (∼85–90%) of HGP is derived from liver [26]; and (2) insulin is a potent inhibitor of HGP: even very small increments in the ambient insulin concentration exert a potent inhibitory effect on HGP [17]. Moreover, within the range of fasting plasma insulin concentrations that are observed in type 2 diabetic individuals (∼10–25 ␮U/ml), the increment in plasma insulin concentration is linearly related to the decline in HGP [17]. Therefore, the product of the basal rate of HGP and the simultaneously measured fasting plasma insulin concentration provides an index of hepatic IR (Fig. 2); this index of hepatic IR has been validated [27]. In non-diabetic obese subjects fasting HGP is lower than in lean controls when expressed per kg of total body weight, but similar when expressed per kg of lean body mass [28]. Thus, given their higher fasting insulin levels obese subjects are more insulin resistant at the level of the liver than lean controls. This index is not commonly used since HGP has to be measured by infusing radiolabelled or stable isotopes of glucose. Since HGP is the primary determinant of the fasting plasma glucose concentration [29], and the fasting plasma insulin concentration is the primary regulator of HGP [30], the product of fasting plasma glu-

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cose and FPI primarily reflects hepatic IR. Therefore, HOMA-IR [31] or the QUCKI [4], which are indexes derived from the product of the fasting plasma glucose and insulin concentrations, can be used to estimate fasting hepatic IR. 2. Role of the liver and the gut in the development of obesity and IR The gastro-intestinal system plays an important role in energy homeostasis. After the discovery of gastro-intestinal secreted hormones related to IR (e.g., GLP-1, GIP and ghrelin) the role of the gut in the development of IR has been of particular interest. Among the many ways in which both the liver and the gut control body weight, particular interest has been recently raised by the role played by bile acids (BAs) and by the gut microflora. BAs have been reported to inhibit diet-induced obesity and prevent the development of IR suggesting effects on energy homeostasis [32]. The intestinal flora has been proposed as an environmental factor involved in the control of body weight and regulation of IR. The mechanisms of weight gain and IR imply a role of the gut microbiota in promoting intestinal glucose absorption, energy extraction from non-digestible food component (short-chain fatty acids produced through fermentation) and a concomitant hyperglycemia and hyperinsulinemia, two key metabolic factors promoting lipogenesis [33]. 2.1. Bile acids, body weight control and IR While BAs have long been known to be essential in dietary lipid absorption, in recent years an important role for BAs as signalling molecules has emerged. BAs that activate mitogen-activated protein kinase pathways [34,35] are ligands for the G-protein-coupled receptor (GPCR) TGR5 [36,37] and activate nuclear hormone receptors such as farnesoid X receptor ␣ (FXR-␣) [38–40]. FXR-␣ regulates the enterohepatic recycling and biosynthesis of BAs by controlling the expression of genes such as the short heterodimer partner (SHP) [41,42] that inhibits the activity of other nuclear receptors. The FXR-a-mediated SHP induction also underlies the down-regulation of the hepatic fatty acid and triglyceride biosynthesis and very low-density lipoprotein production mediated by sterol regulatory element-binding protein 1c [43]. This indicates that BAs function beyond the control of BA homeostasis as general metabolic integrators. Watanabe et al. have recently shown that BAs induce energy expenditure by promoting intracellular thyroid hormone activation [44]. This conclusion was achieved by showing that the administration of BAs to mice increases energy expenditure in brown adipose tissue, preventing obesity and resistance to insulin. The mechanism underlying these novel metabolic effects of BAs is based on the induction of the cyclic-AMP-dependent thyroid hormone activating enzyme type 2 iodothyronine deiodinase (D2), which converts thyroxine (T4) into 3,5,3 -triiodothyronine (T3), thus giving rise to increased thyroid hormone activity. In fact, in vitro treatment of brown adipocytes and human skeletal myocytes with BA increases D2 activity and oxygen consumption and the BA induced D2 activation in vivo is lost in D2−/− mice [44]. The effects of BAs on energy expenditure are independent of FXR-a, and instead are mediated by increased cAMP production secondary to the binding of BAs with the G-protein-coupled receptor TGR5. Although the translation of this mechanism towards clinically exploitable strategies is still far off, TGR5 is emerging as a very promising target for metabolic control and energy homeostasis, thus allowing the potential unlinking of metabolism control from the diet. Ongoing research is aimed at finding BA derivatives or other compounds with selective TGR5 agonist action [45,46]. A further hypothetical role of the BA-stimulated TGR5 positive effect on body weight

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and IR could be through controlling glucagon-like protein 1 (GLP-1) production and insulin secretion. In fact, BAs have been shown to induce GLP-1 release from the intestinal enteroendocrine secretin tumor cell-1 (STC-1) cell line [47]. If these effects would translate to the in vivo situation, it is possible that BAs via their effects on GLP-1 release from L-cells in the intestine will decrease appetite, enhance insulin release from pancreatic ␤-cells, and delay gastric emptying [46]. 2.2. Gut microbiota, body weight control and IR Gut microbiota comprises about 10–100 trillions (1000 species) of bacteria, which are 10 times more than human cells. The human host and its gut microbiota share mutually beneficial (symbiotic) metabolic and genetic relationships. Recent evidence, primarily from investigations in animal models, suggests that bacteria that normally reside within the human gastro-intestinal tract, collectively referred to as the gut microbiota, affect nutrient acquisition and energy regulation [33]. The composition of gut microbiota has also been shown to differ in lean vs. obese mice and humans, with similar patterns in the two species. Backhed et al. elegantly provided experimental evidence that the presence of the gut microbiota affects the amount of energy extracted from the diet [48]. In fact, they have shown that young conventionally raised mice have a 40% higher body fat content and 47% higher gonadal fat content than germ-free mice even though they consumed less food than their germ-free counterparts. The distal gut microbiota from the normal mice was then transplanted into germ-free mice (a process known as conventionalization), resulting in a 60% increase in body fat within 2 weeks, again without any increase in food consumption. The increase in body fat was accompanied by IR, adipocyte hypertrophy, and increased levels of circulating leptin and glucose. Backhed et al. have also shed light on the mechanisms of energy regulation by the gut microbiota [48,49]. These mechanisms include fermentation of indigestible dietary polysaccharides to absorbable forms, intestinal absorption of monosaccharides and short-chain fatty acids with their subsequent conversion to fat within the liver, and regulation of host genes at different levels that promote deposition of fat in lipocytes. In particular: (1) hepatic lipogenesis is increased by carbohydrate response element-binding protein (ChREBP) and liver sterol response element-binding protein type-1 (SREBP-1) overexpression; (2) FFA release from serum lipoprotein-associated triacylglycerols with consequent muscle and adipose tissue entry is increased by suppression of intestinal fasting-induced adipocyte factor (Fiaf), a physiological inhibitor of serum lipoprotein lipase activity; (3) mitochondrial fatty acid oxidation is reduced in muscles and in the liver by suppression of the activity of adenosine monophosphate-activated protein kinase. Thus, gut microbiota is able to affect both sides of the energy balance equation: energy harvest from dietary substances (Fiaf) and energy expense and storing. The qualitative composition of gut microbiota is also relevant to weight control and IR. Metagenomic studies demonstrated that certain mixes of gut microbiota may protect or predispose the host to obesity [50]. Microbiota may also regulate host genes that promote deposition of absorbed fat into adipocytes. Gut microbiota was shown to suppress intestinal fasting-induced adipocyte factor (Fiaf) that decreases fat storage by inhibiting lipoprotein lipase while promoting release of fatty acids, resulting in increased storage of calories as fat. In contrast, lean germ-free mice had elevated levels of Fiaf with reduced body fat deposition, even when fed a high-fat, high-sugar diet [49]. Therefore, the gut microbiota can influence both sides of the energy equation, modulating the efficiency of energy intake, storage or expenditure [50]. A further mechanism by which gut microbiota could influence the development of obesity is low-grade chronic systemic inflammation due to gram-negative

bacterial lipopolysaccharide (LPS) [51]. LPS is a strong inducer of inflammatory response and is involved in the release of several cytokines that are key factors triggering IR. Cani et al. showed in mice that a high-fat diet increases endotoxemia and affects bacterial populations which are predominant in the intestine, favouring an increase in the gram-negative to gram-positive ratio [51]. In addition, they found that chronic metabolic endotoxemia induces obesity, IR, and diabetes by triggering the expression of inflammatory cytokines via a CD14-dependent mechanism. Human studies have provided indirect support for these findings. Treatment of humans with polymyxin B, an antibiotic that specifically targets gram-negative organisms, was shown to reduce LPS expression and hepatic steatosis [52] and patients with type 2 diabetes had higher LPS levels than did a well-matched group of controls without diabetes [53]. Turnbaugh et al. showed that the distal gut microbiota of genetically obese leptin-deficient (ob/ob) mice, as compared to that of their lean (ob/+ and +/+) litter mates, contained genes encoding enzymes for the breakdown of otherwise indigestible dietary polysaccharides and more end products of fermentation (e.g., acetate and butyrate) and fewer calories were present in the faeces of obese mice [54]. The capacity of the composition of the gut microbiota in determining weight can be transmitted by transferring the gut microbiota of obese ob/ob mice to lean germ-free mice, while the effect of transferring the gut microbiota of lean mice was inferior. Ley et al. found that the ob/ob mice had 50% fewer Bacteroidetes and correspondingly more Firmicutes (the two major Bacteria phyla of gut microbiota) than their lean littermates, independently of differences in food consumption [55], and the same proportion was found in the gut microbiota of obese humans as compared to lean controls [56]. After weight-loss program, with either a fat-restricted or carbohydrate-restricted low-calorie diet, the relative proportion of Bacteroidetes increased, while Firmicutes decreased, in proportion to percentage of lost weight and independently of changes in dietary caloric content. Beside Bacteroidetes and Firmicutes, that are the dominant microbial organisms, in the gut there are also methanogenic Archaea that improve the efficiency of polysaccharide fermentation by preventing the formation of hydrogen and other reaction end products. In contrast, the formation of methane creates energy unavailable for uptake by animals. Samuel and Gordon found that cocolonization of germ-free mice with Methanobrevibacter smithii and Bacteroides thetaiotaomicron (a common colonic bacteria highly efficient in glycan metabolism), allowed otherwise indigestible sugars to be metabolized and harvested as additional energy, increased the efficiency of energy extraction from dietary polysaccharides and increased the amount of host adiposity more than did colonization with each organism alone [57]. These findings not only suggest a contribution of Archaea to digestive health but also show that interactions among microorganisms in the gut have a role in host energy homeostasis. A final proof that overweight is associated with gut microflora regards its composition in infancy. Kalliomäki et al. prospectively followed children from birth to age 7 years. Children who were at normal weight at age 7 years had higher numbers of bifidobacteria in fecal samples collected at ages 6 and 12 months and lower numbers of Staphylococcus aureus compared to overweight-obese [58]. This study is very important because it represents the first demonstration that, in humans, differences in intestinal microbiota may precede the development of overweight. Fig. 3 summarizes the possible mechanisms by which the gut microbial community can contribute to obesity. These results suggest that differences exist between gut microbiota of obese and lean subjects, indicating that manipulation of gut microbiota may represent a novel approach for regulating energy balance in obese people, although proper diet and exercise remain

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Fig. 3. Mechanisms by which the intestinal microbiota may contribute to obesity. AMPK = adenosine monophosphate-activated protein kinase; ChREBP = carbohydrate response element-binding protein; Fiaf = fasting-induced adipocyte factor; LPL = lipoprotein lipase; LPS = lipopolysaccharide; SREBP-1 = sterol response element-binding protein type-1.

the best ways to prevent and treat overweight and obesity. However, additional work is needed to investigate the cause–effect relationship between obesity and gut microbiota and to clarify the following issues: (1) whether the relatively small changes in energy extraction, which can be induced by qualitative changes of gut microflora, contribute to clinically meaningful differences in weight; (2) whether differences in gut microbiota in obese vs. lean people are the cause or the result of obesity; (3) identification of environmental and genetic factors that determine the distinctive characteristics of individual microbiota; (4) clinical trials assessing the efficacy of prebiotics and probiotics (the latter needing also proof of safety) should include intestinal microbiota evaluation before and after therapy. 3. Fat depots, IR and liver disease It has been shown that is not obesity per se but rather preferential fat accumulation in the abdominal area that is associated with IR [59–62]. Accumulation of fat in insulin sensitive organs results in lipid-induced dysfunction referred to as lipotoxicity [59,61]. Thus, considerable insight into the link between ectopic fat and IR has been gained from studies of adipose tissue distribution. 3.1. Adipose tissue and IR Adipose tissue plays a central role in the management of systemic energy stores as well as in many other processes [62,63]. This is in part due to its capacity not only to store triglycerides but also to secrete many proteins that have a major impact on energy homeostasis [62] (Fig. 4). A dysregulation of both processes leads to profound changes in insulin sensitivity at the level of the whole organism, but in particular of single organ [61]. Adipose tissue can hold only a certain amount of fat, and if excessively loaded, there is a spillover or redistribution of lipid to ectopic sites, including liver

and skeletal muscle (Fig. 1). In support of this, hepatic steatosis is frequently observed in individuals with the metabolic syndrome [61,64]. Non-alcoholic fatty liver disease (NAFLD) has a prevalence of 57–74% in obese individuals [65], and it is the most common cause of abnormal liver function tests in the United States. The ectopic triglyceride deposition in non-adipose tissue, such as liver and skeletal muscle and also the heart, has deleterious effects [61]. There is both tissue damage (lipotoxicity) and the development of IR. A vast body of research has focused on identifying specific defects in insulin action, which impair insulin-mediated glucose uptake under conditions of excess lipid availability. Many studies have related lipid excess to muscle IR, implying a cause–effect relationship between the two. White adipose tissue secretes several hormones, particularly leptin and adiponectin, and a variety of other protein signals: the adipocytokines [66]. They include proteins involved in the regulation of energy balance, lipid and glucose metabolism as well as inflammation, angiogenesis, vascular and blood pressure regulation [66]. In addition, a number of lesions in insulin signal transduction have recently been described in human, animal, and cell-based studies and, since several lipids are signalling molecules, it has been proposed that increased lipid availability, by activation of inhibitory signalling pathways, leads to attenuation of insulin action (Fig. 4). Several adipocyte-derived factors have been shown to contribute to systemic IR. One of these is adiponectin, which has been shown to correlate negatively with glucose, insulin, triglyceride levels and body mass index, and positively with high-density lipoprotein–cholesterol levels and insulin-stimulated glucose disposal [63,67]. Despite the fact that adiponectin is secreted from adipose tissue, circulating adiponectin levels are lower in obese individuals than in lean individuals, due to its strong association with insulin sensitivity [66,68]. Adiponectin increases insulin sensitivity by increasing tissue fat oxidation, resulting in reduced

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Fig. 4. Failure of storage function of the adipose tissue is associated with adipose tissue IR, increased lipolysis which determines peripheral lipotoxicity, mitochondrial damage, release of pro-inflammatory adipokines, macrophage infiltration.

circulating FFA levels and reduced intracellular triglyceride contents in liver and muscle [69] and by promoting adipose tissue glucose uptake [70]. A recent study has shown that transgenic ob/ob mice overexpressing adiponectin, despite becoming morbidly obese, had reduced triglyceride levels in the liver and muscle, which in turn contributed to improved systemic insulin sensitivity [71]. Thus, it has been proposed that the preferential storage of triglycerides in adipose tissue is mediated by adiponectin [71]. Another factor that has been shown to contribute to IR in obesity is the increased levels of adipocyte-derived FFAs. According to Randle’s hypothesis [8], excessive FFA release induces IR by inhibiting skeletal muscle glucose uptake and glycogen synthesis. An increased supply of FFA also results in increased FFA uptake, oxidation and re-esterification in muscle [25]. In fact, increased intramuscular triglyceride concentrations have been reported in insulin-resistant obese individuals in reciprocal relation to the rate of insulin-stimulated glucose metabolism [11,72–75]. An impairment of glucose oxidation can occur in the presence of increased lipid oxidation, due to the inhibition of pyruvate dehydrogenase by lipid-derived acetyl-CoA, which leads to feedback resulting in reduced glucose uptake [8,25]. However, it cannot be excluded that excess FFA could modulate fat tissue and skeletal muscle gene expression and thus influence fuel partitioning [76]. Abdominal obesity, rather than general obesity, is now recognized as a risk factor for the development of diabetes [77], cardiovascular diseases [78,79] and also for the risk of death [78–80]. Excess abdominal fat accumulation, both visceral and hepatic, has been associated with abnormalities in glucose and lipid metabolism [61]. In particular, both increased visceral and intrahepatic fat content have been associated with hepatic IR [18,81,82]. In contrast, subcutaneous adipose tissue does not appear to be associated with adverse metabolic consequences and may even be protective. In the next two paragraphs we will describe how visceral and hepatic fat are related to IR. 3.2. Visceral fat and IR Visceral adipose tissue (VAT) has been found to be strongly associated with both hepatic [19,83] and muscular [61,83,84] IR and fat

deposition [19,85]. It has been hypothesized that visceral adiposity could result in hepatic IR via a ‘portal’ effect of FFA and glycerol released from increased omental fat [86,87]. VAT is a labile fat depot where lipolysis is less suppressible by insulin, maybe because of a change in the affinity of intra-abdominal fat tissue for catecholamines or insulin that result in increased lipolysis. Preferential influx of FFA (and other molecules produced by VAT) via the portal circulation to the liver could induce or augment hepatic IR, in particular by enhancing GNG (“portal hypothesis”) [62,86,87]. This hypothesis was in part confirmed by recent studies that showed that obese subjects have an increased release of FFA and glycerol into the portal circulation [88]. Moreover, gluconeogenic flux is increased in proportion to visceral fat, fasting plasma FFA and glucose concentrations [84] and surgical removal of visceral fat in mice reverses hepatic IR [81]. However, a recent study has shown that in obese subjects IR is related more to the presence of hepatic steatosis, rather than visceral fat accumulation [89]. Obese subjects matched for hepatic steatosis (13%) but with either low or high VAT (0.7 kg vs. 1.8 kg) have similar degrees of IR at the level of all organs. On the other hand, when matched per VAT, subjects with hepatic steatosis had impaired suppression of HGP and lipolysis and reduced peripheral glucose uptake [89]. Omental and mesenteric adipose tissue are recognized as depots strongly associated also with IR in skeletal muscle [90,91], but the causes are not clear. Despite the fact that visceral fat lipolysis is less suppressible by insulin, the total amount of VAT rarely exceeds 10% of total body fat even in obese subjects [92]. It is therefore difficult to imagine that FFA released from visceral depots can directly affect muscle glucose metabolism. Rather, visceral fat releases adipokines which could be implicated in skeletal muscle IR [63,71,90] although in vivo secretion rates of most adipokines from VAT are probably not greater than the secretion rates from subcutaneous adipose tissue [93] (Fig. 4). Subjects with preferential visceral fat accumulation have increased circulating values of adipocytokines involved in inflammation (IL-1␤, IL-6, IL-8, IL-10, TNF␣ and TGF-␤) and acutephase response (serum amyloid A, PAI-1) [66,93]. For this reason it has been hypothesized that visceral obesity and inflammation within white adipose tissue may be a crucial step contributing to the emergence of IR, type 2 diabetes and atherosclerosis [90,91].

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3.3. Hepatic fat and IR The last decade has witnessed an epidemic increase in the incidence of NAFLD, which includes both hepatic steatosis and steatohepatitis [94,95]. Both obesity and diabetes, two conditions associated with IR, are important risk factors for the development of fatty liver [94,95]. So it is not surprising to find that subjects with NAFLD are highly insulin resistant at the level of: (1) muscle, since they exhibit reduced glucose uptake [18,89]; (2) liver, since they show impaired suppression of HGP [18,19,89,95], and (3) adipose tissue, since they exhibit high lipolytic rates and increased circulating FFA [18,19,89,96]. IR in NAFLD is a primary defect independent of obesity and/or diabetes, as recently shown in non-obese, non-diabetic subjects with NAFLD [18]. The presence of diabetes worsens the problem, since these subjects tend to accumulate more abdominal fat (both hepatic and visceral), which is strictly correlated to the degree of both peripheral and hepatic IR [19]. Several hypotheses have been postulated to explain IR in subjects with NAFLD. There is general agreement that these subjects have increased lipolysis and high circulating FFA levels [18,96], and tracer studies have shown that both hepatic and total lipid oxidation are not reduced, but rather increased [18,96]. Elevated secretion of VLDL is also observed in these subjects [89,97]. The increased availability of FFA to the liver may be multifactorial depending on increased release of fatty acids from adipocytes, excess lipid content in the diet or increased de novo lipogenesis (DNL), i.e., endogenous synthesis of FFA in the liver [98] (Fig. 1). Increased VLDL-TG is due mainly to non-systemic FFA, i.e., presumably derived from lipolysis of intrahepatic triglyceride, hepatic lipolysis of circulating triglyceride, and de novo hepatic fatty acid synthesis [89]. It has been demonstrated that animals administered with high-fat feeding show both hepatic steatosis and impaired suppression of HGP, while in humans, hypocaloric, low fat diets decrease hepatocellular lipid levels by 40–80% [99]. Thus, it has been postulated that preferential influx of FFA via the portal circulation is a relevant determinant of hepatic lipid accumulation. High splanchnic lipid flux is observed not only after high-fat meals but also during fasting conditions in subjects with predominantly abdominal obesity [88]. Accordingly, visceral fat accumulation has been associated with NAFLD, since a strong correlation exists between visceral and liver fat content [19,95]. Animal and human studies indicate that VAT is the major source of the increased FFA flow to the liver and even if visceral fat has been associated with hepatic IR [19,95] this is probably not the only cause [89]. DNL may be another important source of hepatic FFA [98]. While the contribution of DNL during fasting is rather small (around 5%) in normal subjects, in patients with NAFLD DNL is elevated, with rates around 25% [98]. IR state and the chronic inflammatory profile frequently go together with NAFLD or NASH and visceral obesity. Studies in animal models and in human subjects suggest a role of adipocytokines and hormones released by adipose tissue, particularly VAT, but this is far from being fully elucidated. Adiponectin, which promotes hepatic fatty acid oxidation, may protect against NAFLD. In fact, plasma adiponectin is significantly lower in NAFLD patients and is associated with increased hepatic fat and IR [100,101]. Since adiponectin, besides improving glucose and lipid metabolism, inhibits the expression of several pro-inflammatory cytokines including TNF␣ [102], low levels of adiponectin are associated with hyperexpression of inflammatory factors, that not only favours hepatic triglyceride accumulation, but also its progression towards inflammation and fibrosis. TNF␣ promotes lipolysis, increases FFA flux and together with IL-6 is responsible for mitochondrial dysfunction [102]. Leptin is also involved in the accumulation of hepatic triglyceride through the regulation of fat and its distribution and modulation of hepatic oxidation. Leptin also plays a

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multifunctional role in inflammation, acting as a pro-inflammatory stimulus [103]. A suggested mechanism for the accumulation of hepatic triglyceride could therefore be a resistance to leptin action independently of IR. 4. Summary and conclusions The etiology of IR is not simple, as multiple genetic and environmental factors are involved, in particular, sedentary life style and high-fat diet. It is well recognized that ectopic fat accumulation, rather than general obesity, is a characteristic feature of subjects with IR. Studies in humans and animals have shown that abdominal (i.e., visceral and hepatic) fat is strongly associated with the presence and the development of IR. Subjects with abdominal obesity are more insulin resistant at the level of muscle and liver, showing reduced peripheral glucose disposal and increased HGP and GNG and often have fatty liver disease. In these subjects insulin action is impaired also at the level of adipose tissue, with increased release of FFA into the circulation that contributes to ectopic fat accumulation and lipotoxicity. Among several factors associated with the development of IR we have evaluated the role of BAs and intestinal microflora. BAs inhibit diet-induced obesity, regulate and prevent the development of IR suggesting effects on energy homeostasis. The intestinal flora has been proposed as an environmental factor involved in the control of body weight and regulation of IR. The mechanisms of weight gain and IR imply a role of the gut microbiota in promoting intestinal glucose absorption, energy extraction from non-digestible food component (short-chain fatty acids produced through the fermentation) and a concomitant higher glycemia and insulinemia. In conclusion, IR is a multi-organ dysfunction that can degenerate. A change in lifestyle and diet should be suggested in patients with IR to prevent the development of hepatic and cardiovascular diseases and/or diabetes. Conflict of interest statement The authors declare that they have no conflict of interest as regards the present manuscript. References [1] DeFronzo RA, Tobin JD, Andres R. Glucose clamp technique: a method for quantifying insulin secretion and resistance. Am J Physiol 1979;237:E214–23. [2] Bergman RN, Ider YZ, Bowden CR, et al. Quantitative estimation of insulin sensitivity. Am J Physiol 1979;236:E667–77. [3] Wallace TM, Levy JC, Matthews DR. Use and abuse of homa modeling. Diabetes Care 2004;27:1487–95. [4] Quon MJ. Quicki is a useful and accurate index of insulin sensitivity. J Clin Endocrinol Metab 2002;87:949–51. [5] Mari A, Pacini G, Murphy E, et al. A model-based method for assessing insulin sensitivity from the oral glucose tolerance test. Diabetes Care 2001;24:539–48. [6] Matsuda M, DeFronzo RA. Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care 1999;22:1462–70. [7] Mari A, Pacini G, Brazzale AR, et al. Comparative evaluation of simple insulin sensitivity methods based on the oral glucose tolerance test. Diabetologia 2005;48:748–51. [8] Randle PJ. Regulatory interactions between lipids and carbohydrates: the glucose fatty acid cycle after 35 years. Diabetes Metab Rev 1998;14:263–83. [9] Roden M, Price TB, Perseghin G, et al. Mechanism of free fatty acid-induced insulin resistance in humans. J Clin Invest 1996;97:2859–65. [10] Boden G, Jadali F, White J, et al. Effects of fat on insulin-stimulated carbohydrate metabolism in normal men. J Clin Invest 1991;88:960–6. [11] Boden G, Lebed B, Schatz M, et al. Effects of acute changes of plasma free fatty acids on intramyocellular fat content and insulin resistance in healthy subjects. Diabetes 2001;50:1612–7. [12] Schmitz-Peiffer C. Signalling aspects of insulin resistance in skeletal muscle: mechanisms induced by lipid oversupply. Cell Signal 2000;12:583–94. [13] Boden G, Cheung P, Stein TP, et al. Ffa cause hepatic insulin resistance by inhibiting insulin suppression of glycogenolysis. Am J Physiol 2002;283:E12–9.

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