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Themed Issue Papers |
1 Cardiovascular/Metabolic Diseases, Pfizer Global Research & Development, Pfizer Inc., Groton, CT, USA 2 Division of Cardiovascular Diseases, Department of Medicine, Mayo Clinic College of Medicine, Rochester, MN, USA
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(Received 3 August 2006;
accepted after revision 30 October 2006; first published online 3 November 2006)
Corresponding author R. Wolk: Cardiovascular/Metabolic Diseases, Pfizer Global Research & Development, Eastern Point Road, MS 8260-2506, Groton, CT 06340, USA. Email: robert.wolk{at}pfizer.com
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Introduction |
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As indicated above, obesity and physical inactivity may account for only about 50% of the variability in insulin-mediated glucose disposal in healthy, non-diabetic, normotensive individuals (Reaven, 2006). Therefore, other contributors to the pathogenesis of insulin resistance need to be identified to explain the emerging epidemic of glucose intolerance and the metabolic syndrome. Recent data suggest that sleep disturbances may not only contribute to weight gain but also, in their own right, may lead to the development of insulin resistance. Thus, the high prevalence of qualitative and quantitative sleep disorders may help explain the high and rising population-wide prevalence of the metabolic syndrome and insulin resistance.
Obstructive sleep apnoea
Obstructive sleep apnoea (OSA) is a common condition characterized by recurrent episodes of cessation of respiratory airflow caused by upper airway inspiratory collapse during sleep, with a consequent hypoxaemia and decreases in oxygen saturation (to levels as low as 40–50%) as well as sleep fragmentation and deprivation. The presence and severity of OSA is assessed based on the number of apnoea/hypopnoea episodes per hour of sleep (apnoea/hypopnoea index, AHI) and the severity of oxygen desaturations. When defined as an AHI greater than 5, the incidence of OSA in the general population is estimated at 24 and 9% of middle-aged men and women, respectively (Young et al. 1993). OSA will be discussed below in the context of its implications for the development of individual components of the metabolic syndrome, including insulin resistance.
Abdominal obesity. OSA has been linked to visceral obesity, although the relationship between these two conditions is complex (Wolk et al. 2003). Obesity is a recognized risk factor for OSA. Total body weight, body mass index (BMI) and fat distribution all correlate with the odds of having OSA (Young et al. 2002). Every 10 kg increment in body weight increases OSA risk twofold. Every 6 kg m–2 increment in BMI increases OSA risk more than fourfold. An increase in waist or hip circumference by 13–15 cm also increases OSA risk approximately fourfold. Visceral fat especially predicts OSA and significantly correlates with AHI (Shinohara et al. 1997; Vgontzas et al. 2000). Furthermore, in a population-based prospective study of 690 randomly selected Wisconsin residents, a 10% weight gain was associated with a sixfold increase in the odds of developing sleep apnoea (Peppard et al. 2000a). In the same study, a 10% weight loss predicted a 26% decrease in the AHI.
There may be a reciprocal relationship between obesity and OSA, such that not only does obesity increase the risk of OSA, but also that sleep apnoea may predispose to weight gain and obesity. Indeed, patients with newly diagnosed OSA have difficulty losing weight and, in fact, are predisposed to excessive weight gain, far more than is evident in similarly obese control subjects proven to be free of OSA (Phillips et al. 1999a, 2000). In addition, OSA seems to have an independent effect on visceral fat distribution (Shinohara et al. 1997; Vgontzas et al. 2000; Schafer et al. 2002; Fig. 1). Chronic continuous positive airway pressure (CPAP) therapy has been shown to decrease visceral fat accumulation (assessed by computed tomography) in patients with OSA (Chin et al. 1999). Importantly, visceral fat decreased also in those OSA subjects who had no accompanying body weight reduction (Fig. 2), suggesting a pathophysiological link between OSA and excess visceral fat independent of overall body weight. Thus, the presence of OSA is conducive to accumulation of visceral fat and thereby contributes to the occurrence of this component of the metabolic syndrome.
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While further studies are needed to confirm these preliminary observations and to investigate whether the association between OSA and dyslipidaemia is causal and independent of other confounders (especially obesity), it is of note that decreases in total cholesterol (Robinson et al. 2004) and increases in HDL cholesterol levels (even in the absence of a significant change in body weight; Chin et al. 1999, 2000) have been reported after CPAP treatment, suggesting that OSA and dyslipidaemia may in fact be causally related. Further support for this hypothesis has been provided recently by experimental studies showing that intermittent hypoxia (a hallmark of OSA) causes an increase in the liver content of triglyceride and phospholipid, upregulates genes of lipid biosynthesis (Li et al. 2005a) and causes dyslipidaemia in lean mice (Li et al. 2005b). The changes observed in lipid profile included increased fasting total cholesterol, HDL cholesterol, phospholipids and triglycerides. While the elevated triglyceride levels in the mouse model are consistent with the observations in human subjects with OSA, elevations in HDL cholesterol are unlike those seen in OSA subjects (who usually have lower HDL), which suggests that there may be interspecies differences in cholesterol processing.
Notably, not only HDL levels, but possibly also HDL function can be affected by OSA. In a recent study of 128 OSA patients and 82 control subjects, despite similar concentrations of plasma lipids and apolipoproteins in the two groups, OSA subjects had greater HDL dysfunction (determined as the ability of HDL to inhibit low-density lipoprotein (LDL) oxidation ex vivo) and increased oxidized LDL levels (Tan et al. 2006). The AHI was the main determinant of HDL dysfunction, accounting for 30% of its variance. Thus, OSA has the potential to induce not only quantitative, but also qualitative changes in plasma lipids.
High blood pressure. There is compelling evidence supporting the causal association between OSA and hypertension (Wolk et al. 2003). This evidence is based on numerous cross-sectional, longitudinal and treatment studies, all of which support the notion that the prevalence of hypertension is greater in patients with OSA, and vice versa, and that CPAP treatment leads to a decrease in both daytime and nighttime blood pressure. In one such benchmark prospective study (the Wisconsin Sleep Cohort Study), a dose–response relationship was demonstrated between sleep-disordered breathing at baseline and the presence of hypertension 4 years later (Peppard et al. 2000b). The odds ratios for the presence of incident hypertension at follow-up were 1.42, 2.03 and 2.89 for AHI of < 5, 5–15 and > 15 events h–1 at baseline, respectively (Fig. 3). This association was independent of other known risk factors, such as baseline hypertension, body mass and habitus, age, gender, and alcohol and cigarette use.
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Glucose intolerance and insulin resistance. Subjects with OSA might intuitively be expected to have at least some degree of glucose intolerance and insulin resistance by virtue of their increased body weight and visceral obesity. Evidence has accumulated over the last few years, however, to support the concept that OSA may be directly related to insulin resistance, independent of obesity and other anthropometric measures, in both obese and non-obese subjects (Vgontzas et al. 2000; Ip et al. 2002; Punjabi et al. 2002; Tassone et al. 2003; Coughlin et al. 2004; Makino et al. 2006; Fig. 4). Several reports suggest that these metabolic abnormalities can be reversed by effective treatment of OSA with CPAP (Harsch et al. 2004b,c; Babu et al. 2005), lending further support to the notion that OSA and insulin resistance may be causally related. Earlier studies, however, provided somewhat conflicting results and did not consistently demonstrate an improvement in metabolic disturbances after CPAP treatment (Punjabi et al. 2003). Some of the differences in study outcomes can be attributed to different durations of CPAP therapy as well as to the fact that compliance with CPAP (and therefore any improvement in the severity of apnoea and hypoxic episodes) was not objectively assessed in most studies. Also, several studies employed relatively small sample sizes and did not have a control group.
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, TNF-) (Vgontzas et al. 1997, 2000; Ciftci et al. 2004; Minoguchi et al. 2004), which may lead to insulin resistance (Hotamisligil et al. 1993; Uysal et al. 1997). Furthermore, OSA may induce oxidative stress owing to repetitive episodes of intermittent hypoxia (Schulz et al. 2000a; Dyugovskaya et al. 2002), and increased oxidative stress has been shown to be an important pathogenic mechanism of insulin resistance (Matsuoka et al. 1997; Rudich et al. 1998; Maddux et al. 2001; Furukawa et al. 2004). Indeed, Polotsky et al. (2003) reported that leptin-deficient obese mice developed a time-dependent increase in fasting serum insulin levels and worsening glucose tolerance after long-term (12 week) exposure to intermittent hypoxia. However, whether oxidative stress can be consistently demonstrated in OSA is controversial (Svatikova et al. 2005). Insulin resistance is also caused by increased lipolysis and fatty acid availability (Rebrin et al. 1996; Hertz et al. 1998; Kruszynska et al. 2002). OSA may act through this mechanism by virtue of its association with central adiposity (Chin et al. 1999) and sympathetic activation (Somers et al. 1995). Sympathetic activation raises circulating free fatty acids via stimulation of lipolysis and promotes insulin resistance (Kjeldsen et al. 1992). Several adipose tissue-derived hormones (such as leptin, adiponectin and resistin) have also been linked to the pathophysiology of insulin resistance (Segal et al. 1996; Vettor et al. 1997; Steppan et al. 2001; Weyer et al. 2001; Stefan et al. 2002, 2003; Rajala et al. 2003; Whitehead et al. 2006), and their plasma levels may be influenced by OSA (Ip et al. 2000b; Phillips et al. 2000; Vgontzas et al. 2000; Harsch et al. 2004a,d; Wolk et al. 2005b; Zhang et al. 2006). Finally, an important role may be played by monocyte chemoattractant protein-1 (MCP-1). That MCP-1 is involved in the regulation of glucose homeostasis is suggested by the observations that MCP-1 expression and secretion is insulin responsive, that circulating MCP-1 levels are elevated in subjects with type 2 diabetes and that MCP-1 levels are associated with measures of glycaemia and insulin resistance (Piemonti et al. 2003; Sartipy & Loskutoff, 2003; Simeoni et al. 2004). Preliminary data suggest that MCP-1 levels may be elevated in OSA (Ohga et al. 2003), raising the possibility that MCP-1 may be involved in the pathogenesis of insulin resistance in OSA.
Other abnormalities accompanying the metabolic syndrome. It is apparent from the discussion above that there may be a pathophysiological link between OSA and the individual components included in the clinical definition of the metabolic syndrome, such as abdominal obesity, elevated triglycerides, decreased HDL cholesterol, high blood pressure and glucose intolerance. However, there are other metabolic abnormalities that, although not included in the ATP III criteria, are also manifest in the metabolic phenotype of the syndrome. Examples of such abnormalities include systemic inflammation, oxidative stress, endothelial dysfunction and hypercoagulability. It is noteworthy that all of these other abnormalities have also been found in OSA.
Several studies are consistent in demonstrating that OSA can induce an inflammatory state. OSA is independently associated with elevation of C-reactive protein (Shamsuzzaman et al. 2002; Yokoe et al. 2003; Fig. 5), serum amyloid A (Svatikova et al. 2003) and various adhesion molecules, as well as increased expression of adhesion molecules on leucocytes and their adherence to endothelial cells (Chin et al. 2000; Dyugovskaya et al. 2002; El-Solh et al. 2002). Oxidative stress may be present in OSA (Schulz et al. 2000a; Dyugovskaya et al. 2002), as is impaired endothelium-dependent vasodilatation (Kato et al. 2000b) and hypercoagulability (Chin et al. 1996; Sanner et al. 2000; Wessendorf et al. 2000; Guardiola et al. 2001). Impaired endothelial function in OSA probably has multiple contributing factors, such as hypertension, increased sympathetic tone, vascular inflammation, oxidative damage, etc. Specific abnormalities may be evident, including decreased nitric oxide production (Ip et al. 2000a; Schulz et al. 2000b) and increased endothelin (Saarelainen et al. 1997; Phillips et al. 1999b). OSA-related hypercoagulability may be related to increased platelet aggregability, increased haematocrit, elevated fibrinogen levels and increased blood viscosity (Chin et al. 1996; Sanner et al. 2000; Wessendorf et al. 2000; Guardiola et al. 2001).
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Effects of the metabolic syndrome on OSA.
While there is experimental and clinical evidence to implicate OSA in the development of the metabolic syndrome, the evidence is often circumstantial, and the issue of causality still remains unproven. To this end, Vgontzas and co-workers have recently proposed that, rather than sleep apnoea being merely a cause of the metabolic syndrome, the latter may potentially be conducive to sleep apnoea (Vgontzas et al. 2003, 2005). This supposition is based on the following premises: (i) many sleep apnoeics do not have structural abnormalities in their upper airways and, vice versa, many patients with narrow upper airways owing to anatomical abnormalities do not have sleep apnoea; (ii) as discussed earlier, some early studies did not support any beneficial effect of CPAP on metabolic abnormalities in OSA (Punjabi et al. 2003); (iii) obesity (a component of the metabolic syndrome) increases the risk of OSA; (iv) sleep apnoea is very frequent in disorders in which insulin resistance is a primary pathophysiological abnormality, independent of obesity (an example of such a disorder is the polycystic ovary syndrome, in which insulin resistance is the strongest predictor of the presence of sleep apnoea); (v) insulin resistance, by releasing growth factors, may lead to soft tissue oedema and tissue proliferation in the neck; (vi) some metabolic abnormalities are associated with excessive daytime sleepiness; (vii) pro-inflammatory mediators (known to be elevated in OSA) are also independently associated with excessive daytime sleepiness; and (viii) anti-inflammatory interventions have the potential to decrease sleepiness and AHI in sleep apnoeics. With respect to this latter observation, in a pilot study of eight male obese apnoeics, administration of etanercept (which neutralizes TNF-) resulted in a significant decrease in sleepiness and in the number of apnoeas/hypopnoeas per hour (Vgontzas et al. 2004). This suggests that pro-inflammatory cytokines may conceivably contribute to the pathogenesis of OSA, although this hypothesis remains to be proven.
The concept that the metabolic syndrome and insulin resistance may be conducive to sleep apnoea finds further support in the observation that diabetes may lead to a marked depression in ventilatory control mechanisms (Polotsky et al. 2001). In a model of streptozotocin-induced diabetes in C57BL/6J mice, diabetes resulted in depression of the hypercapnic ventilatory response and there was a strong association between the duration of hyperglycaemia, the decline in hypercapnic ventilatory response and increased glycosylation of the diaphragm. In another experimental study of streptozotocin-induced diabetes in rats, compared with normal rats, diabetic rats had a lower ventilatory response to CO2 challenge and their sleep apnoea scores were markedly increased. Furthermore, metformin (known to reduce insulin resistance) returned sleep apnoea scores to their baseline levels, supporting the idea that insulin resistance is an important factor leading to the occurrence of apnoeas in this experimental model (Ramadan et al. 2006). While some clinical studies suggest that OSA patients have normal hypercapnic responses and CPAP treatment does not markedly affect hypercapnic chemosensitivity in OSA (Narkiewicz et al. 1999; Spicuzza et al. 2006), it should be noted that in those studies only ‘healthy’ and untreated OSA subjects were studied and diabetes was an exclusion criterion. Thus, whether or not ventilatory control is impaired by diabetes in humans with OSA needs to be established.
All this evidence notwithstanding, any claim that the metabolic syndrome may be a major cause of sleep apnoea is probably premature, although it is certainly an intriguing and conceivable hypothesis that may have important therapeutic consequences and therefore requires further studies. It is plausible that, in the setting of OSA and the metabolic syndrome, there may be a feedforward relationship between these two conditions, in that OSA predisposes to the metabolic syndrome, and the metabolic syndrome then impairs ventilatory control (by promoting obesity, inflammatory state, glucose intolerance, etc.), leading to progression of OSA with a consequent further deterioration in the metabolic syndrome. This reciprocal relationship between OSA and the metabolic syndrome may be more pronounced at the more advanced, diabetic stage.
Sleep duration and the metabolic syndrome
Altered sleep duration is an example of a quantitative sleep abnormality. While sleep deprivation is also characteristic of OSA, there is evidence to suggest that decreased sleep duration per se is not a benign phenomenon and can, in and of itself, exert important metabolic effects.
For example, a reduced amount of sleep is associated with overweight and obesity, such that obese subjects show a nearly inverse linear relationship between weight and sleep time (Gangwisch et al. 2005; Vorona et al. 2005). Several other reports also support the association between sleep duration and adiposity (Shigeta et al. 2001; Sekine et al. 2002). Although the exact mechanisms linking sleep deprivation to obesity remain to be established, preliminary data point to several neurohumoral consequences of sleep restriction, such as changes in sympathovagal balance, cortisol levels, thyrotropin concentration, growth hormone secretion patterns, or the diurnal rhythm and plasma levels of leptin (which regulates appetite and energy expenditure) (Spiegel et al. 1999, 2000, 2004).
In addition to visceral obesity, other components of the metabolic syndrome can also be affected by sleep duration. Sleep deprivation has been shown to raise blood pressure, may be independently associated with an increased risk for hypertension (Lusardi et al. 1996; Tochikubo et al. 1996; Kato et al. 2000a; Ogawa et al. 2003; Gangwisch et al. 2006), may activate systemic inflammatory processes (Vgontzas et al. 1999; Shearer et al. 2001; Meier-Ewert et al. 2004) and increase susceptibility to oxidative stress (Ramanathan et al. 2002; Everson et al. 2005), although this latter effect may be controversial and tissue specific (D'Almeida et al. 1998; Gopalakrishnan et al. 2004). Furthermore, in prospective studies, sleep deprivation has been suggested to be an independent risk factor for diabetes (Ayas et al. 2003; Yaggi et al. 2006), and evidence has recently emerged that sleep curtailment may be associated with glucose intolerance and insulin resistance, independent of obesity per se. For example, healthy subjects limited to 4 h of sleep for six consecutive nights demonstrated reduced glucose tolerance and a blunted insulin response to glucose (Spiegel et al. 1999). Decreased insulin sensitivity is observed with different durations of sleep deprivation (VanHelder et al. 1993; Gonzalez-Ortiz et al. 2000), and also as a result of sustained sleep debt owing to habitually sleeping less than 6 h per day (Shigeta et al. 2001). Thus, restricted sleep and glucose intolerance may be causally related.
Taken together, these data suggest that sleep deprivation may be both indirectly (through obesity) and directly implicated as a risk factor for the metabolic syndrome.
Shift work
Insufficient sleep is not only a consequence of voluntary sleep curtailment, but also a common feature of shift work. On average, shift workers get less sleep during the week compared with regular day workers. In contrast to habitual sleep deprivation, however, shift work is also characterized by changes in biological rhythms, cumulative circadian phase delay, variable photoperiod, napping, ‘paying back’ sleep debt in the daytime, etc.
Shift work increases the risk of hypertension and may exert potentially detrimental effects on circadian blood pressure control, such that the diurnal variation is changed from a dipper to a non-dipper pattern (Yamasaki et al. 1998; Kitamura et al. 2002). Decreased brachial artery endothelial function was found in shift workers and was independently related to the length of shift work history (Amir et al. 2004). Other metabolic effects of shift work include abdominal obesity, dyslipidaemia (lower HDL cholesterol and higher triglycerides) and changes in glucose tolerance (Hampton et al. 1996; Karlsson et al. 2001, 2003; Nagaya et al. 2002; Di Lorenzo et al. 2003), all suggestive of the possibility that shift work may contribute to the metabolic syndrome. Reduced fibrinolytic activity has also been reported in men on night shift compared with those on day shift (Meade et al. 1979). In addition, shift work may act as an oxidative stressor and decrease plasma antioxidant capacity (Sharifian et al. 2005).
Summary and conclusions
Considering the prevalence of sleep disorders in the general population and considering the epidemiological and pathophysiological links between the metabolic syndrome and incident diabetes and cardiovascular disease, the association of OSA with the metabolic syndrome and insulin resistance is of critical importance. The weight of evidence clearly suggests that the two conditions coexist, although the exact nature of this association is not entirely clear. While OSA may be just another component of the metabolic syndrome (‘Syndrome Z’; Wilcox et al. 1998), both human and experimental data suggest that OSA may also be causally related to individual components of the metabolic syndrome, including insulin resistance. The complex interactions between OSA and the metabolic syndrome are summarized in Table 2. Regardless of the exact underlying mechanism/s, the available data suggest that treatment of OSA may attenuate features of the metabolic syndrome.
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Nevertheless, it has to be emphasized that at this stage the evidence is mainly circumstantial and at times controversial, such that there are only limited data from which definitive conclusions can be drawn. Available data are often observational, uncontrolled and based on small sample sizes. Even controlled studies are often confounded by the presence of comorbidities in the control population. Finally, a publication bias cannot be excluded such that negative data are not published as often as the positive findings. Carefully designed experimental and clinical studies are necessary to better elucidate the link between sleep disorders and the metabolic syndrome, and in particular with insulin resistance.
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, OSA; 
, obese controls. Indices of OSA were positively correlated with visceral fat, but not with BMI or total or subcutaneous fat. Adapted and reproduced from 
