Chapter 12

Diabetes andmetabolic aspects ofOSAJ. C-M. Lam, M. M-S. Lui and M. S-M. Ip

SummaryObstructive sleep apnoea (OSA) is increasingly recognised as arisk factor for cardiometabolic dysfunction. Obesity is the mostcommon risk factor in OSA, and various obesity-relatedcardiometabolic disorders, including a spectrum of glucosedisorders from insulin resistance to overt type 2 diabetesmellitus, hypertension, dyslipidaemia and the metabolic syn-drome, have all been found to be highly associated with sleep-disordered breathing.

Current evidence on the magnitude of the impact on ultimatemorbidity or mortality attributable to OSA-induced metabolicdysfunction is scarce. Given the known pathophysiology ofintermittent hypoxia and sleep disturbance/loss in OSA, it ispostulated that OSA independently contributes towards meta-bolic dysfunction through various downstream intermediarypathways of sympathetic activation, neurohumoral changes,inflammation and oxidative stress. Human and animal/cellexperiments are providing clues to these mechanistic pathways.Regardless of any independent role in the causation ofmetabolic dysfunction, awareness of the concurrence of OSAand metabolic disorders, and the modifying roles of diet andlifestyle behaviour on metabolic function cannot be overemphasised.

Keywords: Glucose metabolism, lipid metabolism, metabolicfunction, metabolic syndrome, obesity, obstructive sleepapnoea

Dept of Medicine, Queen MaryHospital, The University of HongKong, Hong Kong, SAR, China.

Correspondence: M.S-M. Ip, Room409, 4/F., Professorial Block, Dept ofMedicine, Queen Mary Hospital, TheUniversity of Hong Kong, HongKong, SAR, China, Emailmsmip@hkucc.hku.hk

Eur Respir Mon 2010. 50, 189–215.Printed in UK – all rights reserved.Copyright ERS 2010.European Respiratory Monograph;ISSN: 1025-448x.DOI: 10.1183/1025448x.00024809

Obstructive sleep apnoea (OSA) is highly associated with cardiometabolic disorders [1, 2].There is increasing evidence to suggest that OSA poses an independent risk for metabolic

dysfunction [3] but, to date, the data remain controversial. Due to the common presence ofobesity in those with OSA, it is not easy to irrefutably demonstrate independent effects of OSA onvarious metabolic derangements which are highly driven by obesity. Many epidemiological orclinical studies have shown that untreated OSA has an independent association with various

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metabolic derangements, including impaired glucose tolerance/insulin resistance/diabetes mellitus(DM), dyslipidaemia and the metabolic syndrome. However, a causal role of OSA in metabolicdysfunction cannot be firmly established with data from cross-sectional studies, and definitiveevidence requires longitudinal cohort studies and rigorously designed interventional trials. Otherthan causality, many further questions on clinical outcomes, which result from complexinteractions of multiple biological and environmental factors, are also being pursued.

In OSA, recurrent intermittent hypoxia-reoxygenation occurs during sleep, as well as disruption ofsleep architecture, over a period of years. It is postulated that these direct pathophysiologicalconsequences of sleep-disordered breathing (SDB) act as triggers for various pathological cascadeswhich involve sympathetic over activity, neurohumoral activation, systemic inflammation andoxidative stress, which may individually, collectively or interactively lead to adverse cardiometa-bolic function [2–4]. These mediating mechanisms for metabolic dysfunction are beinginvestigated through clinical and translational studies, as well as in vitro and in vivo experimentalmodels of intermittent hypoxia or arousals [3–5].

This chapter will give a comprehensive review of the current state of knowledge of variousmetabolic aspects of OSA, focusing on glucose metabolism, lipid metabolism and obesity.

OSA and impaired glucose metabolism

DM is a metabolic disorder associated with long-term microvascular and macrovascularcomplications [6]. The International Diabetes Federation estimates that 246 million adultsworldwide suffer from this chronic disease, the incidence of which is escalating with the pandemicof obesity, and it is expected to reach 380 million by the year 2025. DM accounts for 6% of thetotal global mortality, with 50% of DM-associated deaths being attributed to cardiovasculardisease [7].

There is compelling evidence that OSA is highly associated with impaired glucose metabolism, in aspectrum of insulin resistance, glucose intolerance and type 2 DM (table 1) [8]. This associationbrings out further research questions of clinically relevant outcomes. Does OSA per se predisposeto the development or aggravation of adverse glucose metabolism? If it does, is there anyadditional/synergistic burden on atherosclerosis and other cardiovascular complications seen inDM? Recent studies show that the prevalence of OSA in type 2 diabetic patients range from 23%to 75% in different ethnic groups [9], and such figures obviously implicate a significantmagnification of any negative influence which OSA may have on glucose metabolism, no matterhow small this may be in an individual.

Table 1. Disease definitions of altered glucose metabolism

Abnormal glucose metabolismFasting plasma glucose o100 mg?dL-1 or 5.6 mmol?L-1

Impaired fasting glucoseFasting plasma glucose 100–125 mg?dL-1 or 5.6–6.9 mmol?L-1

Impaired glucose toleranceOral glucose tolerance test is performed after fasting for at least 8 h, 2 h after drinking 75 ganhydrous glucose dissolved in water: 2 h post-load glucose 140–199 mg?dL-1 or7.8–11.1 mmol?L-1

DiabetesFasting plasma glucose o126 mg?dL-1 or 7 mmol?L-1

OrSymptoms of hyperglycaemia and random plasma glucose o200 mg?dL-1 or 11.1 mmol?L-1

Or2-h plasma glucose o200 mg?dL-1 or 11.1 mmol?L-1 during an oral glucose tolerance test

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Cross-sectional/longitudinal studies on OSA and disorders of glucose metabolism

Reported studies in the literature have used a variety of designs, subjects and methodology toinvestigate the relationship between OSA and glucose metabolism. There is a spectrum ofmeasurement tools for glucose metabolism, ranging from simple assays of blood glucose, insulinor glycosylated haemoglobin (HbA1c) to the laborious hyperinsulinaemic euglycaemic clampstudies. Most of the recently published cross-sectional studies supported an independentassociation between OSA and disorders of glucose metabolism (table 2).

OSA and type 2 DM

Common occurrence of OSA in diabetic subjects or vice versa can be anticipated since bothdiseases share the same risk factor of obesity. Apart from comorbid existence, studies haveattempted to address whether the presence of OSA would confer any independent risk ofdeveloping DM, or worse glycaemic control in those with established DM.

In the Wisconsin Sleep Cohort study (n51,387), the risk of DM was elevated two-fold in subjectswith OSA (defined by an apopnoea/hyponoea index (AHI) o15 events?h-1) after adjustment forknown confounders on cross-sectional analysis at baseline, but no independent increase inincident DM was found at 4 yrs follow-up [15], contrary to the findings for hypertension [30].However, a recent study including 544 nondiabetic subjects in the USA reported a dose–dependent relationship between the severity of OSA and the risk of developing incident DM. Therisk was attenuated by effective continuous positive airway pressure (CPAP) treatment with meanduration of follow-up being 2.7 yrs [26]. In a study of 129 Japanese middle-aged adults with OSA,DM was found to be present in 30% of subjects while glucose intolerance affected another 30%,and the frequency of DM and glucose intolerance was higher among patients with increasingseverity of OSA [22]. Male sex and AHI were identified to be the predictors of impaired glucosemetabolism. Another Japanese study found that the prevalence of DM in 629 obstructive sleepapnoea syndrome (OSAS) patients was higher than that of the control group (25.9% versus 8.2%;p,0.001). The very severe OSAS group (AHI o45 events?h-1) had significantly higherhomeostasis model assessment for estimating insulin resistance (HOMA) than those with milderOSA and the control group [31].

Studies reported from various countries have also addressed the occurrence of OSA in diabeticpopulations of different ethnicities. In a Swedish cohort of 2,668 males with hypertension, theprevalence of moderate-to-severe OSA (AHI o20 events?h-1) was significantly higher in thediabetic group compared to the normoglycaemic group (36% versus 14%), and the presence ofOSA in addition to obesity contributed further to the risk of DM [10]. In a UK study among 240male subjects with type 2 DM recruited from a tertiary hospital centre and five primary carecentres, the prevalence of OSA, defined as .10 events?h-1 oxygen saturation dips of o4% onovernight oximetry, was estimated to be ,23%, which was much higher than that of 6% whichwas reported from their general population [17]. Recently, the Sleep Ahead Study from the USAreported that OSA (AHI o5 events?h-1) affected as many as 86% of very obese type 2 diabeticadults (mean body mass index (BMI) 36 kg?m-2) and increasing waist circumference was thepredictor for OSA. Similarly, a sample of 60 type 2 diabetics with a mean BMI of 33.8 kg?m-2 [28],recruited from a diabetic clinic in the USA also showed a very high prevalence of OSA (77%) [29].The authors further demonstrated that measures of OSA severity, including AHI, rapid eyemovement (REM) AHI and oxygen desaturation index, were positively correlated with increasingHbA1c levels after adjustment for confounders. Our group has recently studied Chinese diabeticsin Hong Kong, and found an OSA (AHI o5 events?h-1) prevalence of ,23% of males and 10% offemales with type 2 DM, free of recent/unstable/severe organ damage such as renal failure, strokeor cardiac events. However, in contrast to the US study [29], we were unable to identify anindependent association between severity of OSA and glycaemic control (HbA1c) (C.L. Lam,Queen Mary Hospital, The University of Hong Kong, Hong Kong, SAR, China; unpublished data).

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Table 2. Cross-sectional/longitudinal studies on sleep-disordered breathing (SDB) and glucose metabolism inadults

First author[Ref.]

Study sample AverageBMI

Toolsassessingglucose

metabolism

Findings

ELMASRY [10] Population-based,116 hypertensive

males with orwithout diabetes

mellitus

27–30 FG andinsulin,HbA1c

Severe OSA was more commonin diabetic subjects

Significant relationship betweenvariables of SDB and fastinginsulin, glucose and HbA1c

IP [11] Clinic-based, 270non-diabetic Chinesewith or without OSA

26 Fastinginsulin,HOMA

AHI and minimum Sa,O2 areindependent predictors

of insulin resistance

MESLIER [12] Clinic-based, 491males with orwithout OSA

27–31 FG andinsulin,OGTT

Both diabetes mellitus and IGTwere more common in OSA

subjects compared tonon-apnoeic snorers

Insulin sensitivity decreased withincreasing severity of OSA

RESNICK [13] Community-basedfrom the Sleep HeartHealth Study, 5874

subjects with orwithout diabetes

mellitus

28–31 Self-report Significant difference betweendiabetic and nondiabetic in RDI,

sleep time ,90% Sa,O2 saturation,CAI and periodic breathing

Statistical significance was lostafter adjustment for obesity

PUNJABI [14] Sleep Heart HealthStudy, 2656 subjects

from the USA

27 OGTT, HOMA Degree of insulin resistance wasindependently associated with

severity of OSAAHI and minimum Sa,O2 were

associated with both fasting and2-h glucose levels

REICHMUTH [15] Wisconsin SleepCohort, 1387

subjects, 4-yr follow-up in 987 subjects

29 FG Diabetes mellitus was more com-mon in OSA (AHI o15), OR 2.3(95% CI 1.28–4.11) after adjust-ment for age, sex and habitusNo independent relationship

between incident diabetes mellitusand OSA at 4-yr follow-up

SULIT [16] 394 subjects fromCleveland Family

Study

32 OGTT Threshold dose response formeasures of hypoxic stress

(o2% time with ,90% Sa,O2)and glucose

intolerance; adjusted OR 2.33

WEST [17] 240 diabetics froma hospital clinic and

five primary careclinics in the UK

29.6 HbA1c OSA (.10 dips?h-1 of o4%desaturation) was estimated to

be present in 23%No correlation between number

of Sa,O2 dips?h-1 and HbA1c

MAKINO [18] Clinic-based, 213OSA subjects

25–28 FG andinsulin,HOMA

SDB was associated with insulinresistance independent of

visceral obesity

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Table 2. Continued

First author[Ref.]

Study sample AverageBMI

Toolsassessingglucose

metabolism

Findings

PELED [19] Clinic-based, 98 withsuspected OSA

25–31 HOMA Insulin resistance correlatedsignificantly with AHI

KONO [20] 94 Japanese males,42 with OSA and 52

without OSA,matched for age,

BMI and visceral fat

23 FG, HOMA FG and HOMA were significantlyhigher in those with OSA

AHI was a predictor of number ofmetabolic syndrome parameters

SHARMA [21] 40 obese OSA 30 FG, fastinginsulin,HOMA

OSA was not associated withinsulin resistance40 obese non-OSA 29

40 non-obese control 21

TAMURA [22] Clinic-based, 129Japanese with OSA

24–27 OGTT Diabetes mellitus and IGT weremore common in those with

severe OSAAHI was independently

associated with diabetesmellitus and IGT

THEORELL-

HAGLOW [23]400 females from a

Swedish city25–31 OGTT AHI was associated with

increased fasting and 2-h insulinlevels after adjusting for

confoundersLow nocturnal minimal Sa,O2

was associated with decreasedinsulin sensitivity

KAPSIMALIS [24] Clinic-based, 67nondiabetic males

with or without OSA

29–31 HOMA Insulin resistance was notassociated with sleep apnoeaseverity after adjustment for

obesityPUNJABI [25] Population-based,

118 nondiabeticsubjects with or

without SDB

26–33 FSIVGTT SDB is associated with impair-ments in insulin sensitivity,glucose effectiveness, andpancreatic b-cell function

BOTROS [26] 544 nondiabeticsfrom a sleep centre in

the USA

33–34 FG An independent associationbetween OSA and incident

diabetes after mean duration offollow-up for 2.7 yrs, afteradjusting for confounders

RONKSLEY [27] Sleep clinic-based,2149 subjects

31 Self-reportedhistory ofdiabetesmellitus

The prevalence of diabetesmellitus increased withincreasing OSA severity

Severe OSA was independentlyassociated with diabetes mellitus

exclusively in sleepy subjects

FOSTER [28] 306 subjects from 16diabetes mellitus

centres in the USA

36.5 HbA1c .86% had OSA with AHI5 events?h-1, 30.5% had moderateOSA, 22.6% had severe OSA

Waist circumference was asignificant predictor of the

presence of OSA

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Although the reported OSA prevalence among diabetics varied widely in the published studies, theoverall higher rates of OSA in diabetics compared with the relevant general population wereconsistent [13, 17, 27–29]. The evidence for the presence of untreated OSA as a risk factor for poorglycaemic control is controversial. Diabetic control across individuals is well known to besubjected to many influencing factors, notably lifestyle variations, duration of DM and anti-diabetic medications which, theoretically, should be closely titrated to the level of HbA1c as anindex of therapeutic control. These confounding factors are not easily controlled or adequatelyaccounted for in statistical adjustments.

OSA and glucose intolerance/insulin resistance

Glucose intolerance is clinically managed as pre-diabetes while insulin resistance is one of themajor pathophysiological phenomena leading to clinical DM. The presence of such pre-diabeticstatus provides an imperative opportunity to prevent the upcoming complications associated withthe development of frank DM, if timely effective treatment can be implemented. The association ofOSA and glucose intolerance/insulin resistance has been consistently shown in numerous studiesinvolving different ethnicities and study design [2, 3, 9]. The Sleep Heart Health Study including alarge sample of community-dwelling subjects not on any diabetic medications (n52,656) foundthat respiratory disturbance index (RDI) and hypoxaemia were associated with severity of insulinresistance and glucose intolerance, independent of age, sex, BMI and waist circumference [14]. Ina case–control study, HOMA in subjects with OSA of moderate severity was higher compared toage and weight matched Caucasian control subjects [32]. In a cohort of 400 Swedish females, agradual decrease in insulin sensitivity, based on the glucose/insulin ratios before and after an oralglucose tolerance test, was seen with increasing AHI, independent of confounders [23]. Similarassociations independent of obesity were also observed in a few studies [11, 12, 19, 20, 33],although the findings were inconsistent other studies [21, 24].

The presence of excessive sleepiness has been suggested to be a phenotypic marker for thedevelopment of hypertension in OSA [34]. Similar observation of the impact of sleepiness onglucose metabolism in OSA subjects has been reported, whereby only OSA subjects who hadexcessive daytime sleepiness but not the nonsleepy ones, had worse insulin resistance compared tocontrols without OSA [35]. Findings from a diabetic sample were in line, observing that theassociation between severe OSA and DM took place exclusively in sleepy patients, after adjust-ment for multiple confounders in stratified analyses [27]. In children, the presence of enlargedadenotonsillar tissue is conventionally considered as the major factor contributing to OSA, whilethe role of obesity is relatively minor as compared to adults. Paediatric subjects with SDB have

Table 2. Continued

First author[Ref.]

Study sample AverageBMI

Toolsassessingglucose

metabolism

Findings

ARONSOHN [29] Clinic based, 60diabetic subjects

33.8 HbA1c 77% had OSA with AHI 5events?h-1

Increasing OSA severity wasassociated with poorer glucose

control, after controlling foradiposity and other confounders

BMI: body mass index; OSA: obstructive sleep apnoea; FG: fasting glucose; HbA1c: glycosylated haemoglobin;HOMA: homeostatic model assessment; OGTT: oral glucose tolerance test; FSIVGTT: frequently sampledintravenous glucose tolerance test; AHI: apnoea/hypopnoea index; Sa,O2: arterial oxygen saturation;IGT: impaired glucose intolerance; RDI: respiratory disturbance index; CAI: central apnoea index.

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previously provided a desirable model for research on cardiometabolic effects of OSA, withoutobesity or established comorbidities as confounding factors. However, the epidemic of obesity isalso increasingly affecting the paediatric population, and evidence is increasing to support thegrowing importance of obesity as a causative factor of OSA [36]. There have been data to supportan independent association between OSA and adverse glucose metabolism in children andadolescents [37–39]. In the Cleveland Cohort, children with SDB had a six-fold increased odds ofmetabolic syndrome compared to those without SDB, after adjusting for age, sex, ethnicity andpre-term status [39]. However, such findings were not consistently reported. In a study of 135children from the USA, about half of whom were obese, insulin resistance and dyslipidaemia weredetermined primarily by the degree of adiposity rather than the severity of SDB among those withOSA [40], and the severity of OSA was not a significant predictor of insulin resistance in anotherstudy involving non-obese children [41].

Most studies have focused on the impact of SDB on insulin sensitivity/resistance, which reflectglucose utilisation in peripheral tissue in response to insulin. Pancreatic b-cells, like any othertissues in the body, are also subject to the detrimental effects of sleep apnoea and intermittenthypoxia. The frequently sampled intravenous glucose tolerance test was used to evaluate thedynamic relationship between insulin sensitivity and insulin secretion in 118 subjects with a rangeof SDB severity [25]. Other than a progressive reduction in insulin sensitivity with increasingseverity of SDB, the disposition index, a measure of pancreatic b-cell function, was also reduced inthose with moderate-to-severe OSA. The latter finding suggested that insulin secretion may beaffected by OSA.

Impact of intervention in OSA on glucose metabolism

A number of interventional studies have examined the effects of OSA treatment on glucosemetabolism, although most of the studies were observational with small sample sizes, andadequately powered randomised controlled trials have been scarce. In adult studies, theintervention was almost exclusively CPAP, with a wide range of treatment durations of one nightto 6 months, while adenotonsillectomy was the predominant treatment in children.

Treatment of OSA and insulin resistance/sensitivity

Table 3 focuses on published studies in the past decade. Using the hyperinsulinaemic euglycaemicclamp to evaluate insulin sensitivity, CPAP for 2 days in 40 nondiabetic OSA males was shown topromptly improve insulin sensitivity. This beneficial effect persisted at 3 months of CPAPtreatment, and was more prominent in the non-obese subgroup with a mean BMI of 28 kg?m-2

[42]. The improvement was sustained at further follow-up of nine subjects at 2.9 yrs [52]. Thesame group of investigators also found improvement in insulin sensitivity in diabetic OSA subjectswith usage of CPAP for 3 months [43]. A Spanish group reported that sleepy OSA subjects weremore resistant to insulin than nonsleepy OSA subjects at baseline, and insulin resistance improvedwith CPAP treatment for 3 months, while no response was seen in the nonsleepy group who hadsimilar HOMA as the non-OSA controls at baseline [35]. Such beneficial effects of CPAP were notseen in other prospective observational studies [46, 53, 54].

There have only been a few randomised controlled studies on the effects of CPAP treatment oninsulin sensitivity/resistance in either diabetic or nondiabetic subjects. In a randomised controlledcrossover trial of 34 obese nondiabetic males with moderate-to-severe OSA, no change in fastingglucose levels or HOMA could be demonstrated with either therapeutic or sham CPAP for6 weeks, despite a significant decrease in blood pressure [47]. Another randomised controlled trialwith two parallel treatment arms using therapeutic or sham CPAP for 3 months was conducted indiabetic males with OSA. Again, no change was demonstrated in insulin sensitivity/resistance asmeasured by the hyperinuslinaemic euglycaemic clamp and HOMA, respectively [48]. Recently,LAM et al. [55] used the short insulin tolerance test to measure insulin sensitivity in a randomisedcontrolled trial of CPAP treatment involving 61 non-diabetic Chinese males with and without OSA.

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Table 3. Interventional studies about the effects of continuous positive airway pressure (CPAP) on glucosemetabolism in adults

First author[Ref.]

Design/sample Tools assessingglucose

metabolism

Findings

HARSCH [42] 40 nondiabetic maleswith OSA

Hyperinsulinaemiceuglycaemic

clamp

Insulin sensitivity improvedafter CPAP for 2 days and after

3 months, more pronouncedin non-obese subjects

HARSCH [43] 9 obese diabeticmales with OSA

Hyperinsulinaemiceuglycaemic

clamp, HbA1c

Insulin sensitivity wasunchanged after CPAP

for 2 days, but was significantlyimproved after 3 months

Glycaemic control and leptinwere unchanged after 3 months

BABU [44] 24 diabetic subjectsand OSA

CGMS, HbA1c Post-prandial glucose improvedafter CPAP for 3 months

HbA1c also improved in thosewith HbA1c .7%

HASSABALLA [45] 38 diabetic subjectsand severe OSA

HbA1c HbA1c decreased after CPAP for,4 months (baseline 7.8¡1.4%,

post-CPAP 7.3¡1.3%)Retrospective study

TRENELL [46] 29 OSA subjects: 19regular CPAP, 10

irregular CPAP

FG, fasting insulin,HOMA

No change in insulinresistance after CPAP for

12 weeks"

COUGHLIN [47]# RCT (crossover, CPAP/sham CPAP): 34 non-

diabetic subjects with OSA

FG, HOMA No change after CPAPfor 6 weeks"

WEST [48]# RCT (parallel, CPAP/shamCPAP): 42 diabetic males

with OSA

HOMA, HbA1c,hyperinsulinaemic

euglycaemic clamp

No change after CPAPfor 3 months"

BARCELO [35] 44 nondiabetic subjectswith OSA (22 with and 22without EDS matched for

age, BMI and OSAseverity), 23 healthy

controls

HOMA Sleepy subjects had higherglucose/insulin level and

HOMA index compared withnonsleepy patients and controls

CPAP for 3 months reducedinsulin and HOMA index in

patients with sleepiness, butnot in the nonsleepy group

PALLAYOVA [49] 14 subjects with severeOSA and diabetes mellitus

CGMS Reduction of nocturnal glucosevariability and improved

overnight glucose controlon CPAP

DAWSON [50] 20 diabetic subjectswith OSA

CGMS Mean sleeping glucosedecreased after treatment with

CPAP for an average of 41 daysNo change in HbA1c

DORKOVA [51] 32 subjects with severeOSA and metabolic

syndrome (16 compliant toCPAP, 16 noncompliant)

HOMA Compliant with CPAP(o4 h?night-1) for 8 weeks ledto improved HOMA and global

CVD riskSCHAHIN [52] 9 nondiabetic

subjects with OSAHyperinsulinaemic

euglycaemicclamp

Improvement in insulin sensitivitymaintained after 2.9 yrs of

CPAP treatment

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Therapeutic CPAP for 1 week improved insulin sensitivity, compared to the sham CPAP group.Interestingly, no change in HOMA was seen, highlighting the impact of difference in evaluative toolson study results. In contrast to the findings of a German group [42], the beneficial effect appeared tobe more prominent and sustainable in those who were moderately obese by Asian ethnic criteria(mean BMI 28 kg?m-2) compared to the non-obese subjects. However, the study included few non-obese subjects, limiting further definitive conclusion.

Data from paediatric subjects were also conflicting. A brisk increase in fasting levels of insulin andinsulin/glucose ratio after adenotonsillectomy for OSA was seen only in the obese children but not thenon-obese group [56]. In contrast to such positive findings, two other studies did not find anydifference in insulin resistance before and after adenotonsillectomy [57, 58]. In 34 children with themetabolic syndrome, those with SDB had increased sympathetic nervous system activity and nocturnalleptin levels but not worse insulin sensitivity, and CPAP treatment for 3 months in 11 subjects reducednoradrenalin and leptin levels but did not change the insulin sensitivity index [59].

Treatment of OSA and glycaemic control in diabetes mellitus

For studies involving subjects with established DM, the effect of OSA treatment on glycaemiccontrol may be highly influenced by other factors, such as anti-diabetic medications, lifestylevariations and the duration of DM. Most of these studies were observational, and a few wereretrospective analyses [44, 45, 49, 50]. The small numbers of subjects and suboptimal complianceto CPAP posed further limitations in the interpretation of findings in some of these studies.

Using the continuous glucose monitoring system to measure interstitial glucose in 24 diabeticsubjects with OSA, a significant reduction in post-prandial interstitial glucose was seen after usingCPAP for 3 months, while the beneficial effect on HbA1c was confined to those who had higherbaseline HbA1c levels of .7% [44]. Using a similar glucose monitoring system, 14 obese subjectswith severe OSA and type 2 DM were evaluated, and reduction of nocturnal glucose variabilitywith improved overnight glucose control during CPAP treatment was demonstrated [49].

Table 3. Continued

First author[Ref.]

Design/sample Tools assessingglucose

metabolism

Findings

VGONTZAS [53] 16 with OSA; 15obese controls; 13non-obese controls

FG, insulin, HOMA No change after CPAP for 3months"

CUHADAROGLU [54] 44 nondiabetic subjectswith moderate–severeOSA (31 compliant to

CPAP)

HOMA Good CPAP compliance for 8weeks reduced leptin levels andcholesterol, and increased insulinsecretion capacity, but not insulin

resistanceLAM [55]# RCT: 61 OSA subjects

free of comorbidconditions (31 CPAP, 30

sham CPAP)

Short insulintolerance test,

HOMA

Therapeutic nCPAP for 1 weekimproved glucose disappearancerate, and the improvement wasmaintained after 12 weeks ofCPAP in those with moderate

obesityNo change in HOMA"

OSA: obstructive sleep apnoea; RCT: randomised controlled trial; EDS: excessive daytime sleepiness;BMI: body mass index; HbA1c; glycosylated haemoglobin; CGMS: continuous glucose monitoring system;FG: fasting glucose; HOMA: homeostatic model assessment; CVD: cardiovascular disease; nCPAP: nasalCPAP. #: indicates an RCT; ": negative findings.

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In keeping with this finding, another study also reported a reduction in mean sleeping glucoseafter treatment with CPAP for an average of 41 days, while there was no change in HbA1c, whichwas probably not an appropriate outcome measure to use, given the ,3 months treatmentduration needed for assessing any change in HbA1c levels [50]. In a study of OSA subjects with themetabolic syndrome, compliant CPAP therapy for 2 months reduced insulin resistance (HOMA)[51]. The only randomised controlled study in diabetic OSA subjects reported to date found nochange in either HbA1c or insulin sensitivity in those receiving therapeutic CPAP compared tothose receiving sham CPAP for 3 months [48]. Average CPAP usage was ,4 h?night-1 in bothtreatment groups, and this could have reduced any positive effect on metabolic control, butdespite the less than ideal CPAP compliance, daytime sleepiness in the therapeutic CPAP groupwas significantly improved.

OSA and obesity

Obesity is highly prevalent in modern western societies, and is becoming a global health burdenthis century [60]. The World Health Organization (WHO) declared obesity as the alarming‘‘globesity’’ problem in 2009. The rise in obesity coincides with increased modernisation and aworldwide explosion in the availability of highly processed foods. At present, one in three adults isoverweight and one in 10 is obese [61]. By 2015, WHO estimates the number of overweight adultswill increase to 2.3 billion worldwide, which is equivalent to the combined populations of China,Europe and the USA [61]. Obesity, in particular visceral obesity, is an established risk factor for anumber of cardiometabolic diseases including hypertension and type 2 DM, and it is one definingcomponent of the metabolic syndrome [62]. Regardless of ethnicity, obesity is a major risk factorfor the development of OSA in adults [63–67], and it was also estimated to increase the risk ofsleep apnoea by ,10- to 14-fold in children [68]. Both gaining and losing weight are associatedwith deterioration and improvement of sleep apnoea, respectively [69, 70].

Both the Wisconsin Sleep Cohort Study [68] and the Sleep Heart Health Study [70] demonstratedthe impact of changes in body weight on the ‘‘natural course’’ of sleep apnoea. The overallincidence of moderate-to-severe OSA over a 5-yr period was 11.1% in males and 4.9% in females.Males with .10 kg weight gain over the follow-up period had a five-fold risk of increasing theirAHI to .15 events?h-1. In contrast, for the same degree of weight gain in females, a 2.5-fold risk ofa similar increment in their severity of sleep apnoea was seen [70]. Given the impact of obesity onOSA, it is generally accepted that global rise in obesity has a major impact on the prevalence andseverity of sleep apnoea.

Weight loss should be recommended for all overweight or obese patients with sleep apnoea, as itsbeneficial effects embrace other obesity-related health problems, notably cardiometabolic diseases[71, 72]. However, it is well appreciated that it takes time to lose weight and only a minority ofpatients will successfully maintain it. In a prospective study of 101 OSA patients who underwentbariatric surgery for weight reduction, the prevalence of OSA was reported as 45% [73]. Pre-operative BMI correlated with the severity of OSA after adjustment for age and sex. At a median of11 months after bariatric surgery, mean BMI was significantly reduced from 56¡1 kg?m-2 to38¡1 kg?m-2 and mean RDI from 51¡4 to 15¡2 events?h-1. In addition, their minimum oxygensaturation, sleep efficiency and REM latency improved [73]. Alternatively, an anti-obesity drug,sibutramine, a serotonin/noradrenalin re-uptake inhibitor, has also been shown to lead toimprovement in OSA severity and daytime sleepiness with weight reduction [74]. Therefore,surgically and medically induced weight loss can significantly improve obesity-related OSA.

Weight reduction also has many beneficial effects on the metabolic profile in OSA subjects. In acase–control longitudinal study of obese subjects in Sweden, the average change of BMI in the1,729 subjects in the bariatric surgical group was -9.7¡5 kg?m-2 compared to 0¡3 kg?m-2 for the1,748 subjects in the control group [75]. The significant weight reduction in the bariatric surgerygroup was accompanied by marked improvement in sleep apnoea symptoms and a lower 2-yrincidence of type 2 DM and hypertriglyceridaemia. Sibutramine for 6 months was also efficacious

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in reducing weight in 93 nondiabetic males with moderate-to-severe OSA, along with reduction ofRDI by 30% as well as improvement in insulin resistance and lipid profile [76]. In an Australianstudy of 25 severely obese patients with moderate-to-severe OSA, mean BMI was 52.7 kg?m-2,laparoscopic adjustable gastric banding resulted in an average weight loss of 44.9¡22 kg and asignificant fall in AHI from 61.6¡34 to 13.4¡13, when assessed at 17.7¡10 months after thesurgery [77]. Their fasting plasma glucose, serum insulin and triglycerides were decreased andhigh-density lipoprotein (HDL)-cholesterol was significantly increased. At baseline, 20 (80%) ofthese subjects fulfilled the criteria of the metabolic syndrome, and this was drastically reduced tothree (12%) subjects at the post-operative reassessment.

Some theoretical mechanisms have been postulated for the association between OSA andmetabolic processes that influence fat accumulation and deposition. It is possible that hypoxia andsleep interruption in OSA would contribute to changes in body composition over time [53]. It hasbeen hypothesised that a stress reaction activating the hypothalamic-pituitary-adrenal axis leadingto release of cortisol and other hormones may trigger mechanisms generating insulin resistanceand preferential abdominal fat accumulation [78]. By inducing neurohumoral changes, OSA couldpromote the development of central obesity directly or indirectly through increasing insulinresistance [53, 79, 80]. The increased obesity would in turn result in progressive deterioration ofsleep apnoea, and thus sleep apnoea and metabolic disturbances may run into a vicious cycle [81].As yet, this hypothesis remains to be proven, although there is cumulating evidence to supportsome of the individual mechanisms in this complex network.

Adiposity in OSA carries another dimension, especially in terms of its pathogenetic role inmetabolic dysfunction. It is now recognised that adipose tissue is much more than a warehouse ofenergy, and that it is a metabolically active tissue which participates in many systemic metabolicprocesses [82]. It was recently proposed that adipose tissue hypoxia may be a trigger ofinflammation in obesity [83], and inflammation is well known to be in close association withcardiometabolic dysfunction, possibly through promoting the mediators of atherosclerosis:endothelial dysfunction, insulin resistance and lipid peroxidation [84–86].

A more recently recognised consequence of obesity and insulin resistance is nonalcoholic fatty liverdisease (NAFLD) [87, 88]. Obesity, age .45 yrs, DM, hypertriglyceridaemia and hypertension havebeen identified as risk factors for the progression of NAFLD [87]. Tissue hypoxia in OSA may alsocontribute to the progression of NAFLD, in a spectrum of disease severity, ranging from steatosiswithout inflammation to nonalcoholic steatohepatitis and liver cirrhosis [88, 89].

OSA and lipid metabolism

Abnormal lipid metabolism is a major risk factor in the development of coronary artery disease,and the increased ratios of low-density lipoprotein (LDL)-cholesterol/HDL-cholesterol and totalcholesterol/HDL-cholesterol are indicative of increased cardiovascular risk [90]. There is a highprevalence of dyslipidaemia in the general population. In a multicentre study of atherosclerosis ofdifferent ethnic groups, 29.3% of 6,800 subjects aged 45–84 yrs had dyslipidaemia, and theprevalence of dyslipidaemia was similar among different ethnic groups [91].

Dyslipidaemia is present in many OSA subjects, and an independent association between the twowas observed in a number of studies (table 4) [22, 92–94, 96–98, 101]. Obesity/visceral obesity arethe most common risk factors in OSA, which probably make a substantial contribution to theadverse lipid profile. Insulin resistance is thought to be a driving force of abnormal lipidmetabolism through promoting increased assembly and secretion of very LDL-cholesterol andtriglycerides via the complex post-translational regulation pathway of apolipoprotein B, which inturn leads to reduced HDL-cholesterol levels [102]. OSA subjects tend to be obese and, thus,insulin resistant, but as previously presented, there is suggestive evidence of an independentcontribution of OSA towards insulin resistance and hence potentially, the downstream sequelae ofdyslipidaemia.

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Table 4. Clinical studies of obstructive sleep apnoea (OSA) and lipid metabolism

First author[Ref.]

Design Sample Lipid profile Findings

Ip [92] Case–control:CPAP treatment

for 6 months

Hong Kong, Chinesemales and females

OSA: n530Controls: n530

Matched for age, BMI,sex and menopausal

status

TC, HDL-C,LDL-C, TC/HDL-C, TG

OSA subjects hadincreased TG and

TC/HDL-CTG decreased

significantly aftertreatment

BARCELO [93] Case–control:CPAP treatment

for 1 yr

Spain, malesSevere OSA: n514

Healthy controls: n513Matched for age

LDL-CLipid

peroxidation

Severe OSA hadabnormal lipid

peroxidation andimproved with CPAP

NEWMAN [94] Sleep HeartHealth Study:longitudinal

study

USA, males andfemales: n54991RDI in quartiles

TC, HDL-C, TG HDL-C was inverselyrelated to AHI, while

TG was positivelyassociated with AHI,

independent ofobesity, in those

aged ,65 yrs onlyROBINSON [95] Pooled data

from two RCTs:4 weeks of

CPAP versussham CPAP

UK, malesOSA: n5220

CPAP: n5108Sham CPAP: n5112

TC, TG TC was significantlyreduced within CPAP

group but nodifference between

two groupsBORGEL [96] Longitudinal

study:6 months ofCPAP/BiPAP

treatment

Germany, males andfemales

OSA: n5366After treatment, OSA:

n586

TC, TG, HDL-C,LDL-C

AHI was associatedwith HDL-C after

adjusting for age, sex,BMI, diabetes andlipid-lowering drugsHDL-C increased

significantly by 5.8%after treatment

CAN [97] Cross-sectional Turkey, malesGroup 1 (AHI o5):

n530Group 2 (AHI ,5):

n532Controls (AHI ,1): n530

TC, TG, HDL-C,LDL-C, Apo-AI,

Apo-B,lipoprotein A

Elevated TC, TG,LDL-C, lipoprotein A,

Apo-B in group 1/group 2 compared to

controls separately

IESATO [98] Cross-sectional:3 months of

CPAP treatment

Japan: n5194OSA: n5155

Non-OSA: n539

LPL LPL concentrationdecreased with AHI,and its concentrationwas increased after

treatmentMCARDLE [32] Case–control Australia, males

OSA: n521Non-OSA: n521

Matched for age, BMI andcurrent smoking status

TC, HDL-C,LDL-C, TG

OSA subjects hadincreased TC and

LDL-C

SHARMA [21] Case–control India, males andfemales

Apnoeic obese,OSA: n540

TC, LDL-C,HDL-C, TG, TC/HDL-C, LDL-C/

HDL-C

No differencebetween OSA

subjects and obesecontrols

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Data on effects of treatment of OSA on lipid metabolism has been controversial, and there wereboth positive [55, 51, 92, 93, 98] and negative [48, 95, 100] studies (table 4). In a randomisedstudy with a cross-over design for 6 weeks of therapeutic versus sham CPAP treatment, there wereno changes in the lipid profiles compared to sham CPAP but the short duration of treatment maybe a limiting factor [47]. In a prospective longitudinal follow-up, we observed that 3 months ofCPAP treatment significantly reduced total cholesterol, triglycerides and apolipoprotein B levelswithout significant changes in BMI [55]. In another study of CPAP treatment for 8 weeks, lipidprofile improved significantly in those with good CPAP compliance of o4 h?night-1 compared tothose using CPAP for less time [51]. OSA may also affect the quality of the lipids, and increasedoxidation of lipids, which are more atherogenic, has been demonstrated in OSA and was taken toreflect a state of enhanced oxidative stress [86]. TAN et al. [99] have also shown that HDL-cholesterol in OSA subjects was less effective in preventing LDL oxidation, and the severity of OSAaccounted for 30% of the variance in HDL dysfunction in sleep apnoea.

Table 4. Continued

First author[Ref.]

Design Sample Lipid profile Findings

Non-apnoeic obese,controls: n540

Normal weight, controls:n540

Obesity was themajor determinant

of metabolicabnormalities

TAN [99] Cross-sectional Hong Kong, Chinesemales and females:

n5210OSA: n5128

Controls: n582

TC, TG, HDL-C,LDL-C, Apo AI,

Apo-B, HDLdysfunction,oxidised LDL

Increased HDLdysfunction and

oxidised LDL in OSAsubjects

AHI was the majordeterminant of HDL

dysfunctionCOUGHLIN [47] RCT with

crossover:6 weeks of

CPAP versussham CPAP

UK, malesOSA: n535

CPAP: n535Sham CPAP: n534

TC, TG, HDL-C,LDL-C

No improvementafter treatment

DORKOVA [51] Cross-sectional:CPAP treatment

for 8 weeks

Slovakia, males andfemales

Severe OSA: n532Good CPAP compliance

(o4 h?night-1): n516Poor compliance

(,4 h?night-1): n516

TC, HDL-C,LDL-C, TG,

Apo AI, Apo-B

TC, TG and Apo-Bimproved within CPAPcompliance group and

TC, TG, LDL-C andApo-B improved

between two groups

COMONDORE

[100]RCT withcrossover:4 weeks of

CPAP versus notreatment

Canada, males andfemales

Moderate-to-severeOSA: n513

TC, TG, HDL-C,LDL-C

No improvementwithin CPAP group

or between twogroups

LAM [55] Longitudinalstudy:

CPAP treatmentfor 3 months

Hong Kong, Chinesemales

OSA: n529

TC, TG, HDL-C.LDL-C, Apo-B

TC, TG and Apo-Blevels were reduced

after treatment

CPAP: continuous positive airway pressure; RCT: randomised controlled trial; BiPAP: bilevel positive airwaypressure; BMI: body mass index; RDI: respiratory disturbance index; AHI: apnoea/hypopnoea index; TC: totalcholesterol; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol;TG: triglycerides; Apo-AI: apolipoprotein AI; Apo-B: apolipoprotein B; LPL: lipoprotein lipase.

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Lipid metabolism involves a series of enzymatic interactions, and lipoprotein lipase is one of thestep-limiting enzymes. Reduced lipoprotein lipase activity provokes early inflammatory responsescentral to atherosclerosis. It was reported that enzyme levels decreased with the severity of OSA,and 3 months of CPAP treatment significantly increased its concentration [98]. This finding mayindicate that treatment of OSA could be effective in reducing inflammatory responses andameliorating lipid metabolism.

Data from animal models of intermittent hypoxia also support a causal role of OSA in thepathogenesis of abnormal lipid metabolism. Exposure to intermittent hypoxia in genetically obeseob/ob mice models caused an upregulation of lipid biosynthesis and dyslipidaemia, and led to lipidperoxidation in the liver in a dose-dependent manner [103, 104]. In another experiment of leanmice exposed to different levels of intermittent hypoxia (21%, 10% and 5% oxygen nadir) for 4weeks, hypercholesterolaemia and lipid peroxidation developed in the absence of obesity, and thedegree of metabolic dysregulation was dependent on the severity of the hypoxic stimulus [105].

OSA and metabolic syndrome

The metabolic syndrome was first described as a cluster of metabolic abnormalities, with insulinresistance as the central pathophysiological feature, and was labelled as ‘‘syndrome X’’ [106].Currently, metabolic syndrome is defined as a group of inter-related risk features of metabolicorigin, including hypertension, insulin resistance, dyslipidaemia and obesity/visceral obesity as itsmajor components [107]. The cause of the syndrome remains unknown. Insulin resistance andcentral obesity have been acknowledged as key driving forces for the metabolic syndrome and,independently, they are also well known cardiovascular risk factors. The syndrome is associatedwith a three-fold and two-fold increase in type 2 DM and cardiovascular diseases respectively. Notsurprisingly, given its defining components which are all risk factors for atherosclerosis, themetabolic syndrome is associated with cardiovascular mortality [108].

Many studies have investigated the relationship of OSA and individual cardiometabolicparameters. There is increasing interest in exploring the relationship between sleep apnoea andthe metabolic syndrome and its defining components [109–111].

Snoring or OSA has been shown to be strongly associated with the metabolic syndrome, and thiswas consistent across different ethnic samples (table 5) [19, 33, 112–120]. The frequent clusteringof OSA and metabolic syndrome or its components has led to the description of ‘‘syndrome Z’’[121]. In a study of subjects with newly diagnosed metabolic syndrome, who were expectedlyobese, OSA was present in 68% of them, a figure which was similar to that for other establishedindividual components of metabolic syndrome [119]. OSA also demonstrated independentassociations with many of the other individual components as well as the syndromic entity inmany of these studies (table 5). Interestingly, in a study of 195 patients with cardiovasculardiseases, the metabolic syndrome was found to be a better predictor of nocturnal desaturationthan AHI in those with sleep apnoea [117]. A recent study from India suggested sequentialdevelopment of metabolic syndrome and OSA [122]. Given these closely interwoven relationshipsbetween OSA and the metabolic syndrome or its defining components, it has been proposed thatOSA may well be considered as a manifestation of an expanded metabolic syndrome [81, 120].

It is logical to surmise that the coexistence of OSA and the metabolic syndrome may lead to worsecardiometabolic outcomes than either condition alone. In a cross-sectional study of 81 patientswith multiple comorbidities recruited from a heart institute, those who suffered from OSA and themetabolic syndrome had higher levels of carotid intima media thickness, carotid-femoral pulsewave velocity and carotid diameter compared to those without metabolic syndrome [123].Therefore, the concurrent presence of metabolic syndrome in OSA patients may have an additiveeffect on atherosclerosis. In subjects with metabolic syndrome who were not yet overtly diabetic,presence of OSA was associated with higher fasting glucose level and glycosylated haemoglobin butnot with BMI [119]. In an interventional study of 38 OSA patients with metabolic syndrome,

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Table 5. Clinical studies of obstructive sleep apnoea (OSA) and metabolic syndrome (MS)

First author[Ref.]

Sample Metabolicparameters

MS (%) Findings

COUGHLIN [112] Clinic-basedUK, males

Obese OSA: n561Obese controls: n543

BMI, WC, SBP,DBP, FBS, insulin,HOMA-IR, TC, TG,

HDL-C,LDL-C, TC/HDL

OSA (87)Non-OSA

(35)

OSA was associated withmultiple

metabolic risk factorsMS: OR 9.1 (95%

CI 2.6–31.2)LAM [113] Community-based

Hong Kong, Chinesemales and females:

n5255OSA: n595

Non-OSA: n5160

BMI, WC, SBP,DBP, TC, TG,

HDL-C, LDL-C,TC/HDL-C,

FBS

OSA (58)Mild OSA

(54)ModerateOSA (56)Severe

OSA (70)Non-OSA

(21)

OSA was associated withall metabolic components

in MSMS: OR 5.3 (95% CI

3.03–9.26)

GRUBER [114] Clinic-basedUK, males and females:

n579Obese OSA: n538

Obese controls: n541

BMI, WC, SBP,DBP, TC, TG

HDL-C, LDL-C,FBS, insulin,

HOMA-IR

OSA (73)Controls

(37)

Insulin resistance was notassociated with OSA,

independentof obesity

MS: OR 5.9 (95%CI 2–17.6)

AMBROSETTI [111] Clinic-basedItaly, males and

femalesOSA: n589

WC, HDL-C,TG, BP, FBS

OSA (53) Subjects with OSAand MS were

younger, had ahigher AHI but did

not increase the riskof cardiovascular eventsafter 22¡10 months of

CPAP treatmentcompared

to those OSAsubjects without MS

COUGHLIN [47] Clinic-basedUK, males: n535

RCT with crossover6 weeks of CPAPCPAP: n518+17

Sham CPAP: n517+17

BMI, WC, BRS,SBP, DBP, MBP,

insulin, FBS,HOMA-IR,

TC, HDL-C,LDL-C, TG

OSA (80) CPAP treatment didnot improve MS but SBP,

DBP, MBPand BRS in those

on CPAP foro3.5 h?night-1

PELED [19] Clinic based: n598Snorers: n59

Mild OSA: n59Moderate OSA: n527

Severe OSA: n553

BMI, WC,FBS, insulin,TC, HDL-C,

TG, Hs-CRP,serum amyloid

Mild OSA(11)

ModerateOSA (21)Severe

OSA (30)

The prevalence ofMS increased

with OSA severity

SASANABE [115] Clinic-basedJapan, males andfemales, n5907

OSA: n5819Controls: 89

BMI, WC,SBP, DBP,

FBS, insulin,HOMA-IR,

TC, TG, HDL-C,LDL-C, b-cell

function

OSA (50)Controls

(22)

MS was associatedwith severity of OSA

In severe OSA:MS in males: OR 5.1

(95% CI 2.7–9.7)MS in females: OR 14

(95% CI 2.9–66.8)

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Table 5. Continued

First author[Ref.]

Sample Metabolicparameters

MS (%) Findings

SHIINA [110] Clinic-basedJapan, males andfemales: n5184

OSA: n594Non-OSA: n590

BMI, SBP,DBP, MBP,TC, HDL-C,

TG, FBS,brachial–

ankle PWV

OSA (43)Non-OSA

(16)

MS may constitutean additive

cardiovascularrisk in OSA

KONO [20] Clinic-basedCase–controlJapan, malesOSA: n542

Non-OSA: n552Matched for age, BMI

and VFA

BMI, VFA,SFA, SBP,

DBP, TC, HDL-C,TG, insulin, FBS,

HOMA-IR

OSA (19)Non-OSA

(4)

AHI was the predictorof the number of

metaboliccomponents in MS

MCARDLE [32] Clinic-basedCase–control

Australia, malesOSA: n521

Controls: n521Matched for age, BMIand current smoking

status

BMI, WC, SBP,DBP, insulin,

FBS, TC, LDL-C,HDL-C, TG,IGF-1, leptin,

TNF-a,adiponectin, urinecatecholamines

OSA (23)Controls (4)

OSA was associatedwith multiple

cardiometabolicrisk factors

PARISH [116] Clinic-basedRetrospective review

USA, males and females:n5228

OSA: n5146Non-OSA: n582

MS,hypertension,

hyperlipidaemia,diabetes

OSA (60)Non-OSA

(40)

MS was associatedwith OSA severity

TKACOVA [109] Clinic-basedSlovakia, males and

females: n598AHI ,5: n528

AHI o5 to ,30: n539AHI o30: n531

BMI, WC, TC,TG, HDL-C,

LDL-C,Apo-AI, Apo-B,

FBS, SBP,DBP, MBP

AHI ,5(46)

AHI o5 to,30 (51)AHI o30

(77)

MS was associatedwith OSA severity

Severe OSA: OR 8.4(95% CI 2.5–28)

Mild-to-moderate OSA:OR 1.8 (95% CI 0.6–6)

TAKAMA [117] Hospitalised inpatientswith cardiovasculardiseases: n5195

MS: n556Non-MS: n5139

WC, BMI,SBP, DBP,

FBS, TC, TG,HDL-C, BNP

OSA (77) MS was a strongpredictor of nocturnaldesaturations ,90%

in patients withcardiovascular

diseasesOKTAY [118] Clinic-based

Turkey, males andfemales

with OSA+MS: n520Longitudinal study of 1 yr

CPAP treatment

WC, BMI, SBP,DBP, TC, HDL-C,LDL-C, TG, FBS

The prevalence ofMS was reducedby 45% after 1 yr

of CPAP treatment

DRAGER [119] Clinic-basedBrazil, males and females

with MS: n581OSA: n551

Non-OSA: n530

BMI, WC, SBP,DBP, FBS,TC, LDL-C,HDL-C, TG,

IMT, PWV, CD

OSA (63)OSA (63)

OSA increasedcardiovascular riskin patients with MS

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20 of whom were evaluated after receiving 1 yr of CPAP treatment, the prevalence of metabolicsyndrome was decreased by 45% [118]. These data give rise to the attractive notion that earlyCPAP treatment in otherwise ‘‘healthy’’ OSA subjects may help to prevent the development ofovert cardiometabolic diseases, although it is still a long way before this can be proven.

Mechanistic links between OSA and metabolic disorders

Sleep fragmentation and altered sleep architecture

OSA is characterised by disrupted sleep architecture with repetitive arousals, sleep fragmentationor even sleep loss, resulting in daytime sleepiness.

Sleep duration and sleep quality play a major role in hormonal regulation in human physiologicalsystems. Sleep duration is believed to regulate leptin and ghrelin levels in humans, which act inparallel as metabolic counterparts for body weight control through different mechanisms onfeeding, wakefulness and energy expenditure [124].

There are epidemiological and clinical data to suggest that short sleep duration may lead to weightgain [125–127]. In the Wisconsin Sleep cohort study, a 3-h sleep loss was associated with a 4–5%weight gain, provided that the baseline sleeping duration was 8 h as self-reported in their sleepquestionnaires [125]. In a retrospective study of 1,000 patients from four different family practicegroups in the USA, females were shown to sleep more than males, and the overweight (BMI o25)and obese patients (BMI o30) slept less than the patients with normal weight (BMI ,25) [127].In addition, in a recent systematic review of 36 observational studies in children and adults from1966 to January 2007, short sleep duration was associated with significant weight gain, particularlyin the young age groups [126].

Evidence from epidemiological and in-laboratory studies suggest that sleep loss or poor sleep quality,irrespective of SDB, may adversely affect glucose metabolism [128, 129]. In the Massachusetts Male

Table 5. Continued

First author[Ref.]

Sample Metabolicparameters

MS (%) Findings

NIETO [120] Community-basedUSA, males andfemales: n5546OSA: n5 253

Non-OSA: n5293

WC, BMI, SBP,DBP, insulin, FBS,

HOMA, TG,HDL-C, urinary

cortisol andadrenalin

OSA (32) OSA is associatedwith the prevalenceof MS, independentof sympathetic and

neuroendocrineactivation

MS In mild OSA:OR 4.0 (95% CI

2.6–6.3)Ms in moderate/

severe OSA:OR 5.3 (95% CI

3.2–8.8)

RCT: randomised controlled trial; CPAP: continuous positive airway pressure; BMI: body mass index; VFA: visceralfat accumulation; AHI: apnoea/hypopnoea index; WC: waist circumference; SBP: systolic blood pressure;DBP: diastolic blood pressure; FBS: fasting blood sugar; HOMA-IR: homeostasis model assessment for estimatinginsulin resistance; TC: total cholesterol; TG: triglycerides; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol; BP: blood pressure; BRS: baroreceptor sensitivity; MBP: mean BP; Hs-CRP: high-sensitivity C-reactive protein; PWV: pulse wave velocity; SFA: subcutaneous fat accumulation; IGF-1: insulingrowth factor-1; TNF-a: tumour necrosis factor-a; Apo-AI: apolipoprotein AI; Apo-B: apolipoprotein B; BNP: brainnatriuretic peptide; IMT: carotid intima–media thickness; CD: carotid diameter.

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Aging Study, males free of DM at baseline had a two and three-fold increase in the risk of developingincident diabetes for both short and long sleep duration, respectively, after ,10–15 yrs of follow-up[130]. In the Sleep Heart Health Study (n51,486), self-reported sleep durations of f6 h or o9 h,with adjustment for body habitus and AHI, were associated with higher prevalence of impairedglucose tolerance and DM [131]. The same predisposition to glucose intolerance and DM wereobserved across various ethnic populations in a number of prospective studies investigating theadverse impact from shortened sleep duration or poor sleep quality for 7–32 yrs [132–136].

Most epidemiological studies were based on subjective self-reporting of sleep duration and quality.In a population study using objective measurement of sleep duration by in-laboratory monitoring,the risk of having DM was three-fold higher in individuals with f5 h sleep duration, compared tothe groups with normal and o6 h sleep duration [136]. In addition to the reduction in sleepduration, certain changes in sleep architecture in OSA, most commonly reduced slow-wave sleep,might also adversely affect the glucose metabolism. All-night suppression of slow-wave sleep,without a change in sleep duration, was shown to result in dramatic worsening in insulinsensitivity in young healthy adults [137]. It has also been shown in the laboratory that sleepcurtailment for 2 days led to adverse glucose profile and increase in appetite for high caloriccarbohydrates when compared to extended sleep [138]. The decrease in the anorexigenic hormoneleptin and increase in ghrelin, an appetite-stimulating peptide, suggested that sleep loss couldpredispose to overeating with consequent weight gain and dysregulation of glucose metabolism[139]. Mechanically induced sleep fragmentation can also produce acute adverse effects on glucosehomeostasis, including reduced insulin sensitivity and impaired insulin secretion [140].

With these data, it is proposed that the associated sleep loss and sleep disturbance may be oneprimary trigger for promoting obesity and DM in OSA, possibly through complex hormonalregulations in the body.

Intermittent hypoxia and oxidative stress

Increased oxidative stress has been shown to be a key mechanism for insulin resistance anddiabetes [141]. In contrast to other chronic respiratory diseases, the disturbance in oxygenation inOSA is unique with recurrent intermittent hypoxia and reoxygenation alternating in rapid cycles.The rapid reoxygenation of transiently ischaemic tissues could lead to tissue injury and release ofreactive oxygen species, the culprit of oxidative stress, from inflammatory cells [142, 143] In aCanadian study of 10 young healthy males subjected to intermittent hypoxia for 6 h?day-1 for4 days to simulate the situation in OSA, increased production of reactive oxygen species without acompensatory increase in anti-oxidant activity was found [144].

The intermittent hypoxia and resultant oxidative stress have been proposed to be a pathogeneticlink between OSA and disturbance of glucose homesostasis [142]. A study of 4,398 community-dwelling Japanese followed up for a median of 3 yrs showed that those with moderate-to-severenocturnal intermittent hypoxia (3% oxygen saturation dips o15 per hour) on pulse oximetry atbaseline had a 1.7-fold risk of incident DM compared to those without significant hypoxia, with adiscernible dose–response relationship of incident DM with the desaturation index, after thoroughadjustment for multiple confounders [145]. In the Cleveland Family study, measures of hypoxicstress (time spent with ,90% O2 saturation) was the strongest polysomnographic index associatedwith glucose intolerance [16].

The pathogentic role of OSA in metabolic derangements has also been investigated using animal/cell models of intermittent hypoxia. In leptin-deficient obese mice, repeated exposure tointermittent hypoxia (30 s hypoxia alternating with 30 s normoxia for 12 h?day-1) for 12 weeks ledto a time-dependent increase in fasting insulin level and deterioration in glucose tolerance andinsulin resistance [146]. Reduced insulin sensitivity, as measured by hyperinsulinemic euglycemicclamp, was also demonstrated in lean mice exposed to intermittent hypoxia, and this developedindependent of autonomic nervous system activity [147]. An in vitro study of the effect of

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intermittent hypoxia on b-cells showed that it led to increased b-cell proliferation and cell death,and the cell death response appeared to be due to oxidative stress [148].

Inflammation and cytokine release

Many cytokines, in particular adipokines, play a role in the mediation of vascular inflammationand adverse glucose metabolism [149, 150]. Intermittent hypoxia and sleep fragmentation in OSAare postulated to be triggers of the cascade of inflammation in adipose tissue and vascularcompartment and, thus, an array of inflammatory products may be released. Many of thesemarkers have documented inhibitory effects on insulin sensitivity in the liver and peripheraltissues and, in addition, pose deleterious effects on the cardiovascular system [151].

Inflammatory cytokines, such as tumour necrosis factor-a and interleukin (IL)-6 were found to beelevated in subjects with OSA, and these markers were positively correlated with excessive daytimesleepiness [152]. In relation to inflammation and insulin resistance, it has been suggested that visceralobesity and insulin resistance, is a potential pathogenetic mechanism promoting inflammation andleading to sleep apnoea [152]. In a study using an in vitro model of intermittent hypoxia/reoxygenation and HeLa cells, the regulation of inflammatory and adaptive pathways on hypoxicstimulation was mapped [153]. HeLa cells exposed to intermittent hypoxia demonstrated selectiveactivation of the pro-inflammatory transcription factor nuclear factor-kB whereas the adaptiveregulator hypoxia inducible factor (HIF)-1 was not activated; suggesting that selective activation ofinflammatory over adaptive pathways with intermittent hypoxia might be an important molecularmechanism of cardiometabolic dysfunction in OSA. In addition, in both human and murineadipocytes, hypoxia inhibits insulin signalling through HIF transcription factor expression, creating astate of insulin resistance, and inhibiting glucose transport as well as inducing IL-6 secretion. Hence,this mechanism may be involved in the development of insulin-resistant state in obesity [154].

Elevated levels of C-reactive protein (CRP), a marker of inflammation, correlated positively withworsening HOMA in a general population followed up for 5 yrs [155]. The association betweenOSA and an elevated level of CRP has been investigated in many studies with conflicting results,probably related to the confounding effects of obesity and presence of comorbidities. LUI et al.[156] have demonstrated an independent association between severity of OSA and elevated CRPlevel in males free of comorbidities, after careful consideration of the confounding effect fromvisceral obesity measured by magnetic resonance imaging.

Overall, the data are still controversial regarding the role of OSA, independent of obesity, in thegeneration of the inflammatory state seen in OSA subjects.

Adipocyte-derived hormones/proteins

Fat tissue produces many biomolecules which have regulatory effects on various metabolicprocesses [80]. Some of these have been investigated in relation to OSA.

Adiponectin

Adiponectin is produced in white adipose tissues and is found in high circulating levels in humans.Its levels are decreased with obesity and visceral obesity. Adiponectin is a key promoter of insulinsensitivity, and it has anti-inflammatory and protective vascular effects [81, 157, 158].Hypoadiponectinaemia has been demonstrated to be closely associated with endothelial dysfunctionand cardiovascular morbidity in clinical studies [159, 160].

It has been postulated that OSA may down regulate adiponectin expression in adipose tissue.Studies on serum adiponectin levels in OSA have been controversial [18, 32, 161]. In a Japanesestudy of 200 male patients with cardiovascular diseases, hypoadiponectinaemia was significantlyassociated with visceral adiposity and insulin resistance but not with any of the sleep indices [18].In another study of 68 subjects with no known comorbidity undergoing sleep studies,

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OSA subjects actually had a higher level of adiponectin compared to BMI-matched non-OSAsubjects, but their blood samples were taken in a nonfasting state in the evening [161]. In a case–control study of 28 otherwise healthy subjects with moderate OSA, there was no difference inadiponectin levels between OSA and BMI-matched non-OSA subjects, though significantdifferences were seen in other metabolic parameters [32]. LAM et al. [162] found that serumadiponectin levels was suppressed in OSA and independently associated with sympathetic activityand severity of sleep apnoea, suggesting that sympathetic activation is a pathway through whichSDB may contribute to the determination of adiponectin levels. This was supported by previouswork which showed that adiponectin gene expression in pre-adipocyte cell lines was severelysuppressed by the synthetic b-adrenergic agonist isoproterenol [163]. The use of CPAP treatmentfor 2–3 months has been reported to increase serum adiponectin levels significantly in OSAsubjects in a few observational studies [164, 165] but not in a randomised controlled study ofdiabetics with OSA [48].

Leptin

Leptin acts by binding to specific receptors in the hypothalamus to alter the expression of severalneuropeptides that regulate neuroendocrine function, energy intake and expenditure. Leptin isfunctionally a ‘‘thrifty’’ hormone, but most obese subjects have high circulating leptin levels,indicating that obesity is a leptin-resistant state [166]. Leptin levels increase exponentially withincreasing fat mass [167]. Increased serum leptin levels were related to endothelial dysfunction[168, 169], thus, leptin may contribute to the pathogenesis of cardiovascular complications in OSA.

The evidence for enhanced leptin resistance attributable to OSA is controversial. Visceral obesityaccounted for the increase in leptin levels in OSA in some studies [32, 170], while others reportedthat serum leptin levels were significantly higher in OSA subjects than in BMI-matched controls[92, 171–173]. A study found that leptin levels correlated with cardiac sympathetic activity in OSAsubjects [174]. Several observational studies showed a reduction of serum leptin levels after weeksor months of CPAP treatment [92, 175] and in one study, the impact was more pronounced inpatients with a BMI ,30 [176]. However, the lack of control group is a major limitation due topotentially significant confounding effect from changes in body weight.

Adipocyte fatty acid-binding protein

Fatty acid-binding proteins are a family of small intracellular lipid-binding proteins. Adipocytefatty acid-binding protein (A-FABP) is abundantly present in adipocytes and regulatesintracellular fatty acid trafficking and glucose metabolism [177]. In animal experiments, theapparent functions of A-FABP were mediation of insulin resistance independent of the effects ofobesity and the promotion of atherosclerosis [178, 179]. Positive associations between serumA-FABP levels and adiposity, hyperglycaemia, insulin resistance and the metabolic syndrome havebeen reported in cross-sectional and longitudinal studies [180]. In a recent large population-basedgenetic study, there was a reduced risk for hypertriglyceridaemia, type 2 DM and coronary arterydisease in subjects who carried a functional genetic variant of the A-FABP gene that resulted inreduced adipose tissue A-FABP gene expression [181].

LAM et al. [182] demonstrated that A-FABP level was elevated in severe OSA subjects compared tonon-OSA or less severe OSA subjects, and its level significantly correlated with insulin resistance.These findings suggested that A-FABP levels may be upregulated by severe OSA and may be one ofthe mediators which propagate metabolic dysfunction in sleep apnoea.

Alterations of the neuroendocrine and autonomic system

Neuroendocrine factors and autonomic activity are important in glucose regulation [84].Adrenalin and cortisol are counter-regulatory hormones of insulin, and the level of thesehormones may be affected in OSA. Heightened sympathetic activity has been convincingly

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demonstrated in OSA, which contributes significantly to the elevation of blood pressure [183].There is also substantial evidence that activation of the sympathetic nervous system and increasedadrenalin levels promote insulin resistance and are associated with abnormalities in glucosemetabolism [184–186]; although, the role of this mechanistic pathway in the metabolic regulationin OSA has not been well studied. It has been demonstrated that intermittent hypoxia resulted inimpaired insulin sensitivity in lean mice, and this occurred independent of autonomic nervoussystem activity [147]. Studies of cortisol secretion in OSA have shown inconsistent results [3].Recently, CPAP therapy was reported to alleviate the disordered adrenocorticotrophic hormoneand cortisol secretory dynamics in subjects with moderate-to-severe OSA [187].

Conclusions

Many OSA subjects have an adverse metabolic profile. In relation to OSA, intermittenthypoxaemia and sleep fragmentation have been identified as major triggering factors that lead todownstream pathophysiological cascades which may result in metabolic dysfunction. Obesity/visceral obesity, present in the majority of OSA subjects, are significant sources of inflammatorybiomarkers, hormones and binding proteins believed to be players in the pathogenesis ofcardiometabolic complications at the molecular level, and may act in concert with OSA in thegeneration of metabolic aberrations. In the complex human biological system, the regulation ofhormones, adipokines, inflammatory cytokines and oxidative stress mediators, is likely to bemultifactorial and inter-crossed with various feedback signals. Apart from disease states,body metabolism is also influenced by endogenous factors of genetics and exogenous factors oflifestyle behaviour. Current data suggest that SDB may contribute to adverse glucose and lipidmetabolism, but pieces of the huge jigsaw puzzle of OSA and metabolic function are just beginningto appear.

Statement of Interest

J. C-M. Lam has received a university grant for HK$150,000 for a clinical trial on patients withdiabetes mellitus and OSA from the University of Hong Kong in 2008. He has also received a grantof HK$800,000 from GSK for a clinical randomised controlled trial on asthma in 2008. J. C-M.Lam received sponsorships for travel and accommodation to overseas conferences in 2008 (forAPSR from GSK) and 2009 (for the World Congress of Sleep Apnea from Celki and for ERS fromBoehringer Ingelheim). M. M-S. Lui received financial support (including travel, accommodationand registration fees) from ResMed for attending the World Congress of Sleep Apnea (Seoul,South Korea; 2009), and from Celki for attending the Sleep Course organised by the University ofHong Kong in 2008 and 2009. M. S-M. Ip has received reimbursement from ResMed for attendinga symposium, which supported a working group meeting of the International Diabetes Panel onOSA and diabetes mellitus in February 2007 (Sydney, Australia). M. S-M. Ip was a working groupmember invited by the International Diabetes Foundation and has also received a fee fromRespironics for speaking at a satellite symposium (World Congress of Sleep Apnea, Seoul, SouthKorea; 2009).

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