The Metabolic Role of Saturated and Monounsaturated Dietary Fatty Acids

Chapter 22

The Metabolic Role of Saturated and Monounsaturated Dietary Fatty Acids: Their Contribution to Obesity, Brain Activity, and Sleep Behavior Tina Sartorius1,2,3 and Hans-Ulrich Häring1,2,3 1Department

of Internal Medicine, Division of Endocrinology, Diabetology, Vascular Disease, Nephrology and Clinical Chemistry, University of Tuebingen, Baden-Württemberg, Germany; 2German Center for Diabetes Research (DZD), Tuebingen, Baden-Württemberg, Germany; 3Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tuebingen (IDM), Tuebingen, Baden-Württemberg, Germany

Chapter Outline Metabolic Abnormalities during Obesity Insulin Action in the Brain Brain Insulin Resistance Fatty Acid Signaling through Receptors Impact of Fat on Glucose Homeostasis

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Fat Quality Correlates with Insulin Sensitivity 206 Consequences of Impaired Sleep Behavior on Metabolism206 Metabolic Sleep Disturbances 207 References208

Over the past 3 decades, insulin resistance-associated conditions such as obesity and type 2 diabetes (T2D) have reached epidemic proportions. Obesity is a well-recognized factor for T2D, and the incidence for obesity is climbing at an alarming rate, underscoring urgency for the discovery of effective therapies to combat this epidemic, particularly because overweight and obesity are the fifth leading risks for death (IDF, 2013). Globally, about 0.5 billion adults are obese, 0.9 billion are overweight, and nearly 0.4 billion have T2D (IDF, 2013). A central cause of overweight and obesity is an energy imbalance between calories consumed and calories expended, and it is proposed that a complex interplay of environmental, including fetal programing and genetic, behavioral, neuronal, and endocrine factors, has a central role in the development of obesity and T2D. Most obese individuals have insulin resistance, T2D, dyslipidemia, and other metabolic complications. However, a subgroup of approximately 10–25% of subjects with obesity preserves insulin sensitivity and is metabolically healthy (Stefan,

Häring, Hu, & Schulze, 2013; Stefan et al., 2008). Neither the genetic factors causing healthy obesity nor the causal factors for transition between the healthy and unhealthy obese phenotype are understood in detail. It is accepted that visceral adipose tissue distribution and ectopic fat deposition are key parameters and potential causal factors for the development of insulin resistance independently of total body fat mass (Kirchhoff et al., 2007; Stefan et al., 2008; Wildman, 2009). Thus, it was found that enlarged adipocytes size, gene expression modifications of key adipose tissue genes, macrophage infiltration with impaired adipocytes function, and a dysregulation of circulating adipokines and cytokines are related to insulin-resistant unhealthy obesity (Hardy et al., 2011; Stefan et al., 2013). A growing body of evidence indicates that impaired regulation of metabolic physiology by the central nervous system (CNS) is a characteristic feature of obesity and T2D (Sisley & Sandoval, 2011). To effectively combat the current obesity epidemic, it is urgent to increase our understanding of the complex and neural mechanisms underlying the homeostatic and non-homeostatic control of energy balance (intake and expenditure).

METABOLIC ABNORMALITIES DURING OBESITY

Modulation of Sleep by Obesity, Diabetes, Age, and Diet. http://dx.doi.org/10.1016/B978-0-12-420168-2.00022-3 Copyright © 2015 Elsevier Inc. All rights reserved.

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INSULIN ACTION IN THE BRAIN Insulin has pleiotropic effects on core physiological functions, such as regulation of glucose homeostasis by promoting glucose uptake in muscle and fat tissue, and by suppressing hepatic glucose production (Könner et al., 2007). The CNS in part regulates these homeostatic mechanisms, because it was demonstrated that centrally administered insulin mediates the antigluconeogenic effect (Könner et al., 2007; Obici, Zhang, Karkanias, & Rossetti, 2002; Pocai et al., 2005). Furthermore, insulin has neuroprotective properties and is involved in the regulation of learning and memory (Plum, Schubert, & Brüning, 2005), but this recently emerging field is not yet fully understood. Likewise, the anorexigenic effect of insulin has been attributed to its action in the arcuate nucleus of the hypothalamus (Elmquist, Coppari, Balthasar, Ichinose, & Lowell, 2005), and insulin signaling specifically in the ventromedial nucleus of the hypothalamus is involved in the onset of obesity upon high-fat diet (HFD) feeding (Klöckener et al., 2011). However, insulin may also act directly on associated neuronal circuitries, because it was shown that energy homeostasis is subject to the control of insulin action in catecholaminergic neurons, apparently via regulation of hedonic feeding circuits (Könner et al., 2011).

BRAIN INSULIN RESISTANCE Insulin resistance significantly contributes to diabetes development and is strongly linked to obesity, excess ectopic lipid deposition in insulin target tissues, and perturbations in lipid metabolism (Samuel & Shulman, 2012). So far, the exact molecular mechanisms are not yet fully understood, and it is becoming increasingly accepted that the brain is involved in metabolic abnormalities seen in obesity, insulin resistance, and T2D. Similar to animal studies in which insulin sensitivity in the brain is blunted in obese and insulin-resistant mice, the effect of insulin on neuronal activity in humans is impaired in obesity (Tschritter et al., 2006) and aging (Tschritter, Hennige, et al., 2009). Further, functional magnetic resonance imaging (fMRI) studies identified specific brain areas related to object processing, memory, and locomotion in lean and obese subjects. Thus, the hippocampus is known to control brain activity in the theta frequency band, and this frequency range could be correlated to locomotor activity during lifestyle intervention lasting 9 months (Tschritter et al., 2012). Thereby, high insulin sensitivity of the human brain facilitates loss of body weight and body fat by lifestyle intervention. There is a growing body of evidence demonstrating that one of the prominent progressions toward the onset of neuronal insulin resistance is existing crosstalk between insulin signaling and low-grade inflammation associated with HFD-induced obesity (Sartorius, Lutz, et al., 2012; Thaler,

Guyenet, Dorfman, Wisse, & Schwartz, 2013). Many molecular signaling pathways have been described at the interface between inflammation and metabolism (e.g., insulin receptor (IR) signaling). Thus, it was demonstrated that insulin signaling is directly impaired by activation of inflammatory signaling cascades within the brain by elevated saturated fatty acids (SFAs) and/or increased release of obesityinduced proinflammatory cytokines such as tumor necrosis factor-α (TNF-α), interleukin 6 (IL-6), and osteopontin (OPN) (Sartorius, Lutz, et al., 2012; Thaler et al., 2013). In detail, inflammatory kinases such as c-Jun N-terminal kinase (JNK) and inhibitor of κB-kinase-β (IKKβ), which activates nuclear factor-κB (NF-κB), are activated and further trigger endoplasmic reticulum (ER) stress, which enhance NF-κB activity (Zhang et al., 2008). Thereby, IR signaling is directly blunted by interference with phosphorylation sites downstream of IR signaling, and JNK activation leads to phosphorylation of insulin receptor substrate 1 at serine-307 residue with impaired insulin action (Aguirre, Uchida, Yenush, Davis, & White, 2000). Interestingly, when these intracellular proinflammatory signals are inhibited, peripheral metabolism and central insulin sensitivity are restored. For instance, this was observed in a study performed in rodents in which peripherally and centrally administered IL-6 antibody ameliorated insulin sensitivity in the brain of HFD-fed mice (Sartorius, Lutz, et al., 2012).

FATTY ACID SIGNALING THROUGH RECEPTORS One of the hallmarks of obesity is an increase of circulating free fatty acids (FFAs), which act as metabolic sensors in the brain, and intracellular lipid intermediates (such as diacylglycerols and ceramides) are implicated in the pathogenesis of insulin resistance by impairing intracellular key signaling pathways. Signaling mechanisms through surface receptors such as Toll-like receptors (TLRs) are a proposed link by which obesity causes central insulin resistance (see Figure 1). TLRs belong to the pattern recognizing receptors, components of the innate immune system, and have the ability to sense endogenous ligands in the obese state. Among TLRs, TLR2 and TLR4 are expressed in almost all cell types within the brain (Hanisch, Johnson, & Kipnis, 2008), and recent findings demonstrated that TLR2 and TLR4 are a causal link in the progression toward obesity and central insulin resistance (Sartorius, Lutz, et al., 2012; Tsukumo et al., 2007). This is highlighted by the observation that lack of functional TLR2/4 protects mice from SFA-mediated impairment in peripheral and central insulin action, brain activity, locomotion, and sleep architecture by an IL-6/OPN-dependent mechanism (Sartorius, Lutz, et al., 2012). However, current evidence suggests that FFAs do not directly bind to TLR4, but an endogenous ligand for TLR4, fetuin-A, has a crucial role in regulating insulin sensitivity

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increase in FFAs potentiates glucose-induced insulin secretion by activating FFAR1 (Itoh et al., 2003). In vitro experiments further revealed that the SFA palmitate stimulates glucose-induced insulin secretion through FFAR1. The proapoptotic effect of chronic exposure of β cells to palmitate was independent of FFAR1, because inhibition of FFAR1 promoted apoptosis (Wagner et al., 2013). In accordance, animal studies suggested that the deleterious effect of prolonged FFA elevation is independent of FFAR1 activation, because mice deficient in FFAR1 were not protected against HFD-induced glucose intolerance (Lan et al., 2008).

IMPACT OF FAT ON GLUCOSE HOMEOSTASIS

FIGURE 1  Free fatty acids (FFAs) and Toll-like receptor 4 (TLR4) signaling in fat-induced inflammation leading to insulin resistance. FFAs bind to the endogenous ligand for TLR4, fetuin-A, which is produced by the liver. TLR4 signaling induces the activation of the transcription factors nuclear factor κB (NFκB), which results in the production of proinflammatory cytokines leading to insulin resistance. ER, endoplasmic reticulum; IKKβ, inhibitor of NFκB kinase-β; IL-6, interleukin 6; OPN, osteopontin; TNF-α, tumor necrosis factor-α. Modified after Heinrichsdorff and Olefsky (2012).

via TLR4 signaling in mice (Pal et al., 2012). Although these results might imply that SFAs are affected by TLR4 activation, a recent study revealed that hepatic insulin resistance is independent of TLR4 signaling and ceramide synthesis (Galbo et al., 2013). Another cell-surface fatty acid receptor is the free fatty acid receptor 1 (FFAR1) (formerly G protein-coupled receptor 40 (GPR40)), which is activated by physiological concentrations of medium and long chain saturated and unsaturated fatty acids with carbon chain lengths of more than 10 (Briscoe et al., 2003). In humans, FFAR1 is specifically expressed in brain and pancreas, accurately in pancreatic insulin-producing β cells. Some physiological effects of fatty acids in pancreatic islets and brain are mediated through this cell-surface receptor. For instance, an acute

The obesogenic lifestyle, characterized by an increased intake of energy-dense foods that are high in fat, and reduced physical activity, is often the result of environmental and societal change, and the association between lipids and insulin resistance is widely accepted. Per definition, fatty acids are aliphatic monocarboxylic acids derived from or contained in esterified form in an animal or vegetable fat, oil, or wax (IUPAC, 1997). Fatty acids are classified as SFAs and unsaturated fatty acids. The latter have one or more carbon–carbon double bonds and are adequately subdivided into monounsaturated fatty acids (MUFAs) and polyunsaturated fatty acids (PUFAs). MUFAs are highly presented, for example, in canola oil (>63% oleic acid), whereas plant oils such as linseed oil and fish contain high amounts of PUFAs (such as linoleic acid and arachidonic acid). The most important PUFAs for humans are divided into two groups: n-6 and n-3 PUFAs. Western diets are high in n-6 and low in n-3 PUFAs, which is speculated to promote insulin resistance and diabetes; decreasing the dietary n-6/n-3 ratio in T2D patients could improve insulin action (De Caterina, Liao, & Libby, 2000; Raheja, Sadikot, Phatak, & Rao, 1993). There is further evidence of the importance of n-3 PUFAs for brain development during fetal and early postnatal life. For instance, the abundance of n-3 PUFAs in the diet of pregnant females is indispensable for development of the glutamatergic system and normal behavior performance in the adult offspring (Moreira et al., 2010). MUFAs were shown to prevent the deleterious effects of palmitate, an SFA, and glucose on pancreatic β-cell turnover and function (Maedler, Oberholzer, Bucher, Spinas, & Donath, 2003), and MUFAs completely prevented palmitate-induced apoptosis in β cells (Eitel et al., 2002). Insulin secretion was further inhibited by chronically elevated SFAs, which led to an increased rate of apoptotic β cells in the pancreas (Eitel et al., 2003). A study that shaped the concept of an inverse correlation between FFAs and insulin sensitivity was performed in offspring of T2D patients, in whom elevated FFAs represent an early step in the progression toward T2D (Perseghin, Ghosh, Gerow, & Shulman, 1997). The notion that fatty acids can signal nutrient availability to the

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CNS, which in turn limits further delivery of nutrients to the circulation, is supported by studies in rodents, in which the centrally administered MUFA oleic acid markedly inhibits glucose production and food intake (Obici, Feng, et al., 2002). Moreover, Lam et al. (2005) demonstrated an important role of hypothalamic sensing of circulating fatty acids in the regulation of glucose homeostasis in response to a physiological increase in lipid availability. Circulating fatty acids are generally bound to albumin and penetrate the blood–brain barrier by simple diffusion in the unbound form. Hydrolysis of lipoproteins by lipoprotein lipase within blood or at the cerebral capillary bed further produces unbound fatty acids. Therefore, in the post-meal state, chylomicrons are presumably a major circulating source of brain fatty acids, whereas in the fasting state the fatty acid pool in the brain is constituted by a combination of unbound fatty acids and locally hydrolyzed lipoproteins. Notably, a direct uptake of lipoproteins by specific receptors in the luminal surface of the cerebrovascular endothelium also accounts for a small portion of fatty acid accretion into the brain (Qi, Hall, & Deckelbaum, 2002). Proportionality exists between the plasma concentration of circulating FFAs and their access to the CNS (Rapoport, 1996), and it was shown several decades ago that in fasted anesthetized dogs the concentration of plasma in cerebrospinal fluid (CSF) is around 6% (Goto & Spitzer, 1971). Interestingly, a recent study in humans revealed a positive relationship between the n-3 PUFA docosapentaenoic acid and docosahexaenoic acid, and the n-6 PUFA arachidonic acid in the blood and the CSF (Guest, Garg, Bilgin, & Grant, 2013). The authors further found an inverse association between central and peripheral oleic acid. With regard to the impact of fatty acids on neuronal function, magnetoencephalography studies in humans revealed that chronically elevated serum levels of SFAs are associated with impaired insulin action in the brain. Therefore, levels of SFAs were negatively correlated with insulin-stimulated brain activity in certain frequency bands, and obese subjects who were characterized by elevated levels of SFAs displayed insulin resistance independently of body weight (Tschritter, Preissl, et al., 2009; Tschritter et al., 2006). Moreover, rodent data suggested that mice challenged with HFD based on lard are characterized by impaired insulin action in the brain and impaired cortical activity and locomotion as assessed by radiotelemetry (Hennige et al., 2009). This might further promote glucose intolerance, physical inactivity, and obesity.

FAT QUALITY CORRELATES WITH INSULIN SENSITIVITY An emerging body of evidence suggests that dietary fat quality and not its total fat content more closely correlates with alterations in insulin sensitivity and weight gain in humans and animals (Haag & Dippenaar, 2005; Jucker, Cline, Barucci, & Shulman, 1999). Thus, to assess the effects of

quality and quantity of several diets high in fat, mice were fed long-term with different concentrations and types of fat (Yu et al., 2010). The analysis of the study implied that these diets not only modified the brain fatty acid composition but also altered spatial memory and learning ability in mice. However, numerous studies demonstrating aversive effects of SFA overload on glucose metabolism were performed in rodents fed high caloric diets consisting of a large amount of fat. However, it remains to be determined whether moderate, isocaloric fat enrichment with diets that differ in fat quality have an impact on glucose homeostasis. This issue was examined in a study in which an SFA-enriched diet was accompanied by glucose intolerance, reduced brain activity, and central insulin resistance in mice, whereas an isocaloric MUFA-enriched diet protected from these deleterious effects (Sartorius, Ketterer, et al., 2012). The MUFA-fed animals gained significantly increased fat mass comparable to the SFA-fed group, but this did not raise concerns about glucose homeostasis.

CONSEQUENCES OF IMPAIRED SLEEP BEHAVIOR ON METABOLISM Sleep is an important modulator of neuroendocrine function and glucose metabolism, and electroencephalography and electrocorticography recordings are widely used to define sleep stages. A large number of laboratory studies of humans as well as epidemiological data suggest that short sleep duration is associated with metabolic and endocrine alterations, including impaired glucose tolerance, decreased insulin sensitivity, and increased hunger and appetite (Chaput, Després, Bouchard, & Tremblay, 2007; Knutson, Van Cauter, Zee, Liu, & Lauderdale, 2011). Most recent evidence linking decreased nocturnal sleep duration and poor sleep quality to an increased risk of developing obesity and its complications were demonstrated by multiple epidemiological studies in adults and children (Knutson, Van Cauter, 2008; Patel & Hu, 2008; Leproult & Van Cauter, 2010; Lucassen, Rother, & Cizza, 2012; Mathew & Narang, 2013). A significant association between short sleep duration (6 h or less per night) and elevated obesity risk was found in which hormonal alterations favored an increase in caloric intake and decreased energy expenditure, and led to body weight gain. Multiple pathways are prone to mediate the relationship between sleep and obesity. For instance, sleep restriction enhances the food intake-stimulating peptide ghrelin (Spiegel, Tasali, Leproult, Scherberg, & Van Cauter, 2011) and conversely, the satiety-inducing hormone leptin declines (Spiegel et al., 2004). Importantly, the secretion of these two hormones from adipocytes (leptin) and from stomach and pancreas (ghrelin), respectively, is also modulated by the autonomic nervous system, and a shift of the sympathovagal balance to higher sympathetic activity has been observed in sleep deprivation studies (Spiegel et al., 2004). Furthermore, an association

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was found for partial sleep loss and disturbance of glucose homeostasis that involves both reduced β-cell responsiveness and lower insulin sensitivity (Van Cauter et al., 2007). Notably, a recent study explored brain regions most susceptible to sleep deprivation-induced changes when processing food stimuli, assessed by fMRI in humans (Benedict et al., 2012). Thus, total sleep deprivation was associated with increased activation in the right anterior cingulate cortex in response to food images, and this was independent of calorie content and plasma glucose levels.

METABOLIC SLEEP DISTURBANCES Against the background of the previous section it is interesting to assess whether specific fat classes have effects on sleep architecture and to explore the role of different brain areas taking part in regulating sleep behavior mediated by different fat qualities. Sartorius, Ketterer, et al. (2012) showed that mice chronically fed an isocaloric SFA-enriched diet were characterized by decreased wakefulness and increased non-rapid eye movement (NREM) sleep (see Figure 2(A)–(C)). In line with these findings, an intervention study in humans demonstrated that SFA

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intake deteriorates brain activity in the hippocampus and the inferior parietal cortex, whereas MUFAs did not display averse effects as assessed by fMRI techniques (see Figure 2(D)–(E)) (Sartorius, Ketterer, et al., 2012). It is known that the lateral and posterior hypothalamic areas contain neurons specifically active during wakefulness (Vanni-Mercier, Sakai, & Jouvet, 1984), and that the medial prefrontal cortex and basal forebrain are counted among wake-promoting regions (Datta & Maclean, 2007). The promising findings of this fat quality study (Sartorius, Ketterer, et al., 2012) suggest that SFAs may specifically act on brain areas controlling wakefulness and NREM sleep, whereas MUFAs preferentially alter mechanisms in the brainstem and especially the pons and adjacent portions of the midbrain, because this fat class predominantly affects rapid eye movement (REM) sleep. So far, however, the underlying molecular mechanisms are unclear and remain to be determined. Further findings suggest an association between n-3 PUFAs and pineal function, which is implicated in the sleep–wake rhythm. Syrian hamsters nourished with an n-3 PUFA-deficient diet are characterized by disturbance in melatonin rhythm, weakened endogenous functioning of the circadian clock, and impaired nocturnal sleep (Lavialle,

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FIGURE 2  Different sleep–wake patterns in monounsaturated fatty acid (MUFA)- and saturated fatty acid (SFA)-fed mice and response of the human brain to MUFA- and SFA-enriched diet. (A–C): Diurnal variations of wakefulness (wake), non-rapid eye movement (NREM) sleep, and rapid eye movement (REM) sleep in MUFAs- (gray circles), SFAs- (black circles), or chow-fed (white circles) mice. Data (mean ± SEM of 11–14 animals/diet group) are expressed as minutes per hour for each hour over a 24-h episode (light on 07:00 AM to 07:00 PM). (D–E): Color-coded T-value map represents significant voxels of decreased intrinsic brain activity 3 months after SFA-enriched yogurt consumption compared with the control group (p < .001, whole brain). Plots show change of intrinsic activity in the hippocampus 3 months after SFA-enriched, MUFA-enriched, and control diet. Only SFA-enriched diet revealed a significant decrease in hippocampal activity. Statistically significant differences between fat-enriched diet groups and control group are depicted by asterisks (*p < .05; **p < .005). Data are presented as mean ± SEM.

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Champeil-Potokar, Alessandri, Balasse, & Guesnet, 2008). Likewise, rats deficient in n-3 PUFAs showed dysregulation of monoaminergic systems in the frontal cortex and nucleus accumbens, both of which areas have a central role in the reward circuit (Chalon, 2006). In general, the obesogenic lifestyle, particularly present in Western society, with an excess uptake of SFAs and, to some extent, n-6 PUFAs, entails negative consequences, whereas MUFAs and n-3 PUFAs are advantageous. Recent research provides new opportunities to understand the pathogenesis of organ-specific diseases associated with obesity and offers new strategies for beneficial and targeted therapy. However, in studies using a nutritional approach, other food ingredients may exert positive or negative effects that may limit the translatability of controlled successful animal studies into therapeutic interventions in humans. Moreover, evidence from multiple sleep and obesity studies supports the importance of sufficient sleep of good quality in subjects at risk for obesity. Finally, sleep is the most sedentary activity and yet may be the only one that protects from weight gain (Chaput, Klingenberg, & Sjodin, 2010).

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210  PART | III  Metabolic Syndrome and Sleep Deprivation

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