8 genetic aspects of osa

7/28/2019 8 Genetic Aspects of OSA

http://slidepdf.com/reader/full/8-genetic-aspects-of-osa 1/17

Chapter 5

Genetic aspects of OSA

in adults and childrenR.L. Riha

Summary

Obstructive sleep apnoea (OSA) is known to be hereditary but anumber of environmental and developmental factors can affect

its expression, e.g. obesity, hormonal changes, nasal occlusionand lymphoid tissue growth.For this reason, OSA is generally considered to be a sum of its

component parts with relative contributions in each individualfrom craniofacial morphology, susceptibility to sleepiness, ventilatory control, obesity, upper airway control and lymphoidtissue overgrowth.

The phenotypic complexity of OSA makes establishment of a single genetic basis elusive. Furthermore, unlike other poly-genic disease models, such as chronic obstructive pulmonary disease, asthma and hypertension, funding for studies in OSAhas been limited. A number of genetic approaches have beenutilised, including genome-wide studies, case–control studiesand genome-wide association studies. The results of thesedemonstrate our first tentative, but hopeful, steps of uncover-ing some of the markers of disease expression, as well asdisease progression.

Future efforts aimed at exploring the sequelae of OSA andpossible genetic modulators of these are more likely to yield

clinically useful data, which will ultimately result in improvedpatient care.

Keywords: Case–control studies, genetics, genomics,obstructive sleep apnoea

Correspondence: R.L. Riha, Dept of Sleep Medicine, The Royal Infirmary of Edinburgh, 51 Little FranceCrescent, EH16 4SA, Edinburgh, UK,

Email [email protected]

Eur Respir Mon 2010. 50, 69–85.Printed in UK – all rights reserved.Copyright ERS 2010.European Respiratory Monograph;ISSN: 1025-448x.DOI: 10.1183/1025448x.00024109

M

any questions regarding sleep biology remain unanswered, despite intensive research in thelast few decades. Even fundamental issues such as the functions of sleep, individual

differences in response to sleep deprivation and inter-individual differences in sleep durationrequirements continue to perplex us [1].

The genetic underpinnings and influences on the sleep/wake cycle, let alone of the various sleepdisorders ranging from parasomnias through to narcolepsy, remain imperfectly investigated andunderstood.

6 9

R . L

. R I H A



Technology and studies of genetic traits

Rapid advances have been made in the technologies utilised in molecular biology and genomics;however, basic issues such as phenotyping remain imperfectly resolved.

Over the last few decades, time and resources (albeit many orders of magnitude smaller incomparison to other chronic diseases such as hypertension) have been invested in defining the

genetic basis of the sleep apnoea/hypopnoea syndrome. However, the results of studies are difficultto interpret meaningfully as a whole and replication studies are minimal. This is partly attributableto the lack of funding that has been forthcoming at all levels of research in this area and partly because this area of medicine is still relatively new and only recently recognised (decades, ratherthan centuries). Increasingly, incontrovertible evidence of the harmful effects of recurrentbreathing pauses during sleep and associated intermittent hypoxia due to obstructive sleep apnoea(OSA) are creating exciting new avenues for exploring the genetic basis of their expression and,thus, potentially leading to better understanding of disease modulation and prevention.

Aims

This chapter will focus on the current issues surrounding human genetic studies in OSA across thelifespan and will include a brief discussion of the technological aspects which have helped to bringabout advances in the field.

The phenotypic complexity of OSA

Heterogeneity of OSA

The first issue that requires adequate resolution prior to commencing any genetic study is the

phenotyping of the disorder or disease in question. OSA is a heterogeneous disorder whose key pathophysiological feature is the occurrence of upper airway obstruction during sleep only.Additional factors influence the severity and degree of upper airway dysfunction and these will bediscussed below.

The role of obesity

Obesity and ageing are the strongest risk factors for OSA [2, 3]. Morbid obesity, defined as a body mass index (BMI) of .30 kg?m-2, is present in 60–90% of patients with OSA. In particular, centralobesity and increased neck circumference are strongly correlated with OSA. However, not all obese

subjects will snore or have sleep-disordered breathing (SDB) [4]. The severity of OSA has alsobeen shown to vary with weight loss and gain, most recently in the longitudinal study of theWisconsin Sleep Cohort Study [5].

Sex

OSA is more common in males. However, the ratio of males to females with OSA, previously thought to be as high as 9:1, is more likely to be in the order of 2–3:1 when presentation bias istaken into account [5]. The risk of OSA is higher in females who are obese and post-menopausalcompared to pre-menopausal females [6].

Craniofacial phenotype

OSA is also associated with craniofacial abnormalities, particularly of the midface and jaw, withthese abnormalities playing a more prominent role in thinner OSA patients [7]. Race and certaincongenital conditions affecting craniofacial characteristics such as Marfan’s syndrome, Down’s

7 0

G E N E T I C

A S P E C T S O

F

O S A



syndrome and the Pierre Robin sequence can predispose to the development of OSA. Acquiredconditions such as acromegaly and hypothyroidism are additional confounders.

Nature versus nurture

OSA has a hereditary component and is more prevalent in those with family members who haveSDB [8]. Hereditary factors invoke 40% of the variance in the occurrence of OSA in the

population; the rest is apparently attributable to environmental factors [9].Environmental factors predisposing to the development and clinical expression of OSAS includealcohol ingestion, sedative use, sleep deprivation, tobacco use and sleeping in the supine posture[10, 11]. Reduced nasal patency can also significantly contribute to OSA [12].

Children

Paediatric SDB may affect up to 3% of school-aged children (although more recent studies suggestthis may be an underestimate [13]) with consequences very similar to those of adults [14–17].

The most common cause of OSA in children is related to enlargement of the tonsillar andadenoidal tissue. The role of obesity is more controversial in childhood OSA [18]. Additionally,congenital craniofacial abnormalities as well as abnormalities of brainstem control of breathing,such as the PHOXB mutations, will result in problems with breathing during sleep [19]. Sleepinessis not necessarily a correlate of SDB in childhood and various manifestations including hyperactivebehaviour and failure to thrive can be important indicators for problems with the upper airway during sleep [20]. Recent attempts to phenotype childhood OSA have been undertaken [21]. Themajor differences between adult and paediatric OSA are summarised in table 1.

Natural history of OSA

Long-term cohort studies of OSA patients commencing either in childhood of adulthood are notavailable. The dominant paradigm suggests that the snoring individual will progress to developingincreased resistance of the upper airways culminating in SDB and finally OSA. However, there isno evidence to support this apart from a few small studies which have demonstrated a worseningof SDB over variable periods of time [22, 23]. There have also been a small number of studies

Table 1. Differences and similarities in the clinical presentation of adult and paediatric obstructive sleep

apnoea

Children AdultsSubjective and objective sleepiness less apparent Subjective and objective sleepiness

Behavioural difficulties in up to

25% of children

Concentration and memory affected,

personality changes

Concentration affected Driving impairment

Academic progress affected Intellectual impairment

Enuresis Nocturia

Failure to thrive: increased sleep energy expenditure

and decreased growth hormone secretion

Mood disturbances

Reduced libido/impotence

Increased inflammatory markers: Marital disharmony

independently of Reduced quality of lifeadenotonsillar hypertrophy Increased inflammatory markers

Hypertension Hypertension

Increased insulin resistance Increased insulin resistance

Increased risk of cardiovascular/

cerebrovascular morbidity

7 1

R . L

. R I H A



investigating the cardiovascular consequences of untreated OSA in adults which have shownincreased mortality from cardiovascular and cerebrovascular disease in those with more severeSDB [24, 25]. However, these studies are not controlled for possible confounders such as non-compliance with other treatment and baseline cardiovascular disease severity; patients were notstudied again to assess whether oxygen desaturation and SDB had worsened over time. Morerecently, results from the Wisconsin Sleep Cohort Study reporting results over 16 yrs of follow-uphave shown sleep apnoea (defined as an apnoea/hypopnoea index (AHI) .5 or .15 events?h-1)

prevalence fluctuates according to the population’s weight. The prevalence of a high AHI increasescontingent with greater obesity. Using controlled regression models, untreated SDB predictsincreased depression, stroke, mortality and hypertension [5].

There have been no studies which have followed up paediatric patients into adulthood to seewhether SDB improves, worsens or recurs after treatment. There is currently no publishedevidence to suggest that the majority of adult snorers snored in childhood or adolescence.Furthermore, the development and characteristics of OSA in adults may vary as a function of thenormal ageing process [26]. The aetiology of the disease may change with increasing age due tochanges in parapharyngeal fat pad deposition [27], serotonergic dysregulation of brainstem

respiratory control (due to ‘‘wear and tear’’) [28], and age-related changes in bony structures suchas edentulism [29]. Variations in neuromuscular control of the upper airway become moreimportant in the elderly [30], and increased background prevalence of cardiac and cerebrovasculardisease increase the likelihood of periodic breathing. The clinical phenotype of OSA also changeswith older subjects reporting less daytime sleepiness for a given level of OSA [31]. Hypotheses havebeen postulated suggesting that the development of SDB with intermittent hypoxia may lead toischaemic preconditioning which may act as a protective mechanism in the older subject [32].Thus, SDB and OSA in the elderly are unlikely to be equivalent to the same disorders that developin childhood, youth or middle age.

Clinico-physiological phenotypes of OSA

Phenotype is the total physical appearance and constitution of a living entity [33]. The genotypeinteracting with the environment creates the phenotype. Phenotyping OSA is difficult.

In 1999, the American Academy of Sleep Medicine Task Force developed the most widely accepteddefinition of OSA syndrome for adults in present use [34]. OSA syndrome severity is based on thedegree of daytime sleepiness and overnight monitoring of breathing. Both are rated separately.However, there is no accounting for age- or sex-related changes. Paediatric OSA has an uncleardefinition with an AHI o1 event?h-1 generally considered to be sufficient to confirm SDB,

although some studies have used an AHI o5 events?h-1 [20]. Whether this definition is equally relevant to a newborn as to a 13-yr-old has not been formally incorporated into guidelines.Furthermore, symptomatology is more difficult to define. An additional factor which should beborne in mind is that the AHI as measured objectively using physiological monitoring is unrelatedto measures of sleepiness across any given population, so that two concepts which may becompletely unrelated to each other are used to establish the definition of OSA [35–37].

Within the population as a whole, there are few normative data regarding SDB without symptomsor minimally symptomatic. Additionally, SDB severity is highly dependent on the technology usedto measure it overnight.

Due to this, many researchers in the area have conceived OSA as a sum total of a number of intermediate phenotypes, which include craniofacial morphology, obesity, susceptibility tosleepiness, and ventilatory and upper airway control. Observational and epidemiological studieshave shown that various components will have greater influence in some individuals with OSAcompared to others.

7 2

G E N E T I C

A S P E C T S O

F

O S A



Craniofacial morphology

In both adults and children, craniofacial features associated with SDB include more obtuse cranialbase dimensions, inferior displacement of the hyoid bone, macroglossia, adenotonsillarhypertrophy, increase in lower facial height, a retroposed maxilla and a short mandible [7, 29].Craniofacial growth occurs in specific stages throughout embryogenesis, into childhood andadulthood [38]. Craniofacial skeletal growth continues throughout adulthood, into old age

accompanied by significant sexual dimorphism. For instance, females experience growth of thecraniofacial skeleton with pregnancy and other hormonal changes; mandibular orientation andocclusal relations also change throughout the life cycle [38]. Environmental mechanisms play astrong role; these include habits such as thumb sucking, abnormal tongue posturing,nasopharyngeal disease, disturbed respiratory function (e.g. mouth breathing), tumours, loss of teeth, malnutrition and endocrinopathy [39]. Thus, environmental influences can significantly alter the skeleton and affect phenotypic expression, with mandibular position and size playing thegreatest role in determining facial alignment and predisposition to SDB. The number of studiesexamining this intermediate phenotype in children and adults is limited. Genes involved in theembryogenesis, growth, development and expression of the craniofacial complex are subject to

very complex gene-gene and gene-environmental effects and their pathways are yet to be fully elucidated [40]. Adenotonsillar hypertrophy (AT) is one of the most common causes of SDB andOSA in children and removal of the tonsils can be effective in both thin and obese children [20, 41].Genetic predisposition to AT hypertrophy has recently been shown [42] to be an important factorin children, with other research groups neatly demonstrating environmental factors such asrespiratory syncytial virus infection in early life playing a possible role [43]. Furthermore, tonsillartissue from children with SDB has shown greater upregulation of inflammatory cytokine pathwayscompared to children with recurrent tonsillitis alone [44]. The prevalence of AT hypertrophy inadults with OSA is unknown.

Obesity

As stated previously, obesity is the most commonly identified risk factor for OSA in adults and isincreasingly becoming a factor contributing to childhood OSA. Fat deposition results in areduction in nasopharyngeal calibre and, if severe enough, can lead to hypoventilation due toreduced chest wall compliance [45]. There is increasing evidence that adipokines, such as leptin,may affect regulation of the respiratory centre [46]. The heritability in BMI is said to rangebetween 25% and 40%, thus suggestive of a strong environmental influence [47]. Susceptibility toobesity is largely genetic but a favourable environment must exist for its phenotypic expression.Regulation of appetite and energy expenditure is complex and redundant pathways are biased

towards weight gain. Information on obesity susceptibility genes is updated regularly through thehuman obesity gene map (http://obesitygene.pbrc.edu). To date, over 300 markers, genes andchromosomal regions have been associated or linked with human obesity phenotypes. Only a few single gene mutations causal of obesity have been found in rare cases. Supporting cellular work islacking at the present time.

Sleepiness

In adults, sleepiness, as a direct consequence of nocturnal SDB, is required for the definition of OSA. However, there are many instances of individuals who may have an AHI of 100 but deny

sleepiness or impairment during the day. Observations like this support an inherent differentialsusceptibility to somnolence among individuals. A network of neuronal and humoral mechanismsregulates sleep [48], with the cytokines, interleukin (IL)-1 and tumour necrosis factor-a central tosleep activation pathways. Other sleep inducing cytokines include IL10, IL6, interferon, IL2, IL4,colony stimulating factor and fibroblast growth factor [49]. Many of these cytokines arepleiotropic and implicated in initiating or propagating the sequelae of OSA, particularly

7 3

R . L

. R I H A



inflammation [50]. In children, sleepiness is not always manifest as a symptom of fragmentednocturnal sleep due to SDB. Behavioural disorders are more common [20].

Upper airway control

Neural pathways central to maintaining upper airway muscle tone during sleep are thought to belargely serotonin dependent [51]. Thus, selective serotonin reuptake inhibitors have been trialled

as a pharmacological therapy for increasing upper airway tone with mixed results [52]. At present,further characterisation of upper airway neurophysiology is necessary in order to make geneticstudies more meaningful.

Ventilatory control

Ventilatory responses to hypoxia and hypercapnia vary widely in the normal population [53]. A highdegree of heritability of peripheral chemoreceptor responses to hypoxia and hyperoxia has beenevidenced through studies in monozygotic twins [54] and three-generation family studies [55].

The genetic basis for arousal thresholds from sleep to hypercapnoea or hypoxia has never been

studied. A number of studies have been conducted in children and adults with OSA and theirfamily members examining their hypercapnic and hypoxia ventilatory responses, but numbershave been small (nf50 in each study) and have shown either no or only small differences acrossgroups [56–63]. Several studies have shown abnormalities of respiratory control in patients withOSA that have been reversed by the use of continuous positive airways pressure, therefore, thechanges may be a secondary and not a primary manifestation of the OSA genotype.

Sequelae of OSA

In OSA, repetitive upper airway obstruction with attendant hypoxaemia and increased arousals

contribute to the disruption of cardiovascular, metabolic and endocrine function [64, 65]. OSA isan independent risk factor for diurnal hypertension and has been implicated as a risk factor instroke [66]. Repetitive hypoxaemia contributes to systemic inflammation and may enhance thedevelopment of atherosclerosis [67]. Cell and molecular mechanisms involving inflammatory mediators are upregulated in patients with OSA [68]. Genetic predisposition to pro-inflammatory cytokine production may exacerbate these effects [69].

The presence of hypercytokinaemia, hyperleptinaemia, insulin resistance, hypertension andvisceral obesity occur in disproportionate measure in the population with OSA, even when obesity is controlled for [70, 71].

Similar effects of OSA have been identified in children, specifically regarding hypertension [72],inflammation [73] and metabolic syndrome [74].

Genetic and genomic approaches in OSA

Two general approaches in study design have been used to explore the genetics of human disease:linkage studies and case–control association studies which incorporate candidate gene associationand genome-wide association.

Linkage studies

Linkage studies are mainly utilised in the study of single-gene disorders. Genetic markersthroughout the genome are identified, which are not necessarily functionally significant in termsof phenotypic effect. Generally these studies use extended families. Complex statistical techniquesare deployed to assess the strength of association of a genetic locus with a phenotypic marker. Thisis reported as a LOD score (logarithm of the odds). In linkage analyses, a LOD score .3 indicates

7 4

G E N E T I C

A S P E C T S O

F

O S A



significant linkage (the phenotypic locus and putative genetic marker have a chance of ,1/1000 of not being linked). A score between 2 and 3 is ‘‘suggestive’’ of linkage and a score ,2 is notsuggestive of linkage [75].

To date, three genome-wide scans have been undertaken in adults with SDB [76–78]. All threestudies utilised a 9cM genome scan. OSA was phenotyped on the basis of AHI alone usingovernight, in-home measurement of breathing using a portable monitor. DNA was pooled andmultipoint, variance-component linkage analysis was performed for the OSA-associated

quantitative phenotypes of AHI and BMI. The first study was in European-American pedigreescomprising 66 families and 349 subjects [76]. The second study involved 59 African-Americanpedigrees [77]. The third study extended the first two by including more pedigrees in both ethnicgroups and increasing the data set to 634 individuals from 128 African-American families and 641individuals from 109 European-American families [78]. Results of the studies are summarised intable 2. In all studies, adjustment of AHI to BMI and statistical modelling reduced the LODscores, making linkage of OSA to AHI insignificant or questionable.

Candidate gene-association studies

A gene of interest is chosen as the result of a biological hypothesis for the disease and is thensequenced in cases with the disease and unrelated, disease-free controls. Both common and rarevariants of the gene can be detected. There are two main classes of variation at the molecular level:copy number variants (deletions or duplications of DNA segments) and single nucleotidepolymorphisms (SNP; single-base positions with sequence variation). However, the association of the genetic variant with disease is a statistical finding not necessarily reflecting genetic association[79]. A pathological effect should only be inferred if there is both a lower frequency of the variant

Table 2. Genome-wide scans of obstructive sleep apnoea in two populations living in the USA

Study Candidate region onchromosome UnadjustedLOD score

Linkage to AHI unadjusted

P ALMER [76]

66 European-American pedigrees 1p 1.39

2p 1.64

12p 1.43

19p 1.4

P ALMER [77]

59 African-American pedigrees 8q 1.29

L ARKIN [78]109 European-American pedigrees 1 46cM 2.0

6 162cM 4.7

10 122cM 2.7

19 35cM 1.9

128 African-American pedigrees 8 45cM/100cM/140cM 1.3–2.0

13 49cM 2.0

20 p 3.9

Linkage to AHI adjusted

L ARKIN [78]

109 European-American pedigrees 6 80.4cM 3.3

11 38cM 2.1128 African-American pedigrees 8 43cM 2.3

18 126cM 3.5

22 52cM 2.2

LOD: logarithm of the odds; AHI: apnoea/hypopnoea index; cM: centi-Morgans.

7 5

R . L

. R I H A



SNP in the control population and further studies reveal alteration in gene product. A number of candidate gene studies have been performed in adult and paediatric OSA. To date, there has beenno consistent replication of the findings of any of the studies and most are underpowered, poorly controlled and variably phenotyped. Adult studies, which have been replicated, are summarised intable 3. Only five case–control studies have been published in the paediatric literature examiningthe following candidate genes in relation to OSA: apolipoprotein E (APOE) epsilon 4 [98, 99],SNPs in cysteinyl leukotriene receptors in tonsils [100], insulin gene variable number of tandem

repeats [101], and angiotensin converting enzyme SNPs [102].Meta-analyses are a useful method for pooling the results of a number of genetic studies andexamining a true effect in a larger population. A recent meta-analysis of eight studies examiningthe APOE epsilon 4 allele and its association with the risk for OSA found an odds ratio (OR) of 1.13 (95% CI 0.86–1.47) [103]. There was statistically significant heterogeneity (I2572%,P50.001). The authors concluded that there was currently no evidence to support a causalrelationship between this gene and OSA.

Genome-wide association studies

Candidate-gene studies may be refined by using the common patterns of DNA sequence variation(HapMap Project: www.hapmap.org), thus making the indirect association approach readily applicable and more cost-effective. In this approach, ‘‘tag’’ SNPs are used to identify uniquehaplotypes. The Human Genome Project has made possible an SNP map, which is a high-density map of 200,000–600,000 SNPs and a database that contains 1.8 million SNPs (http://snp.cshl.org/).Advances in SNP mapping and high-throughput SNP genotyping platforms are making itincreasingly feasible to conduct genome-wide association studies (GWAS).

GWAS can be used to survey the entire genome at once and are hypothesis free. Common, ratherthan rare, variants are more likely to be detected and SNP associations are generally of modest

effect. Association with disease is more difficult to establish in comparison to the techniquesdiscussed previously. This method has been instrumental in the discovery of several possiblecandidate genes in type I diabetes mellitus [104], obesity [105] and hypertension [106]. Mostrecently, the results of a large candidate gene study of OSA in pedigrees involving 729 African-Americans and 694 European-Americans revealed differential associations of various SNPsassociated with AHI or OSA (defined as a dichotomous trait using AHI .15 events?h-1) [107]. 505SNPs in European-Americans and 1,080 SNPs in African-Americans were genotyped with resultsbeing adjusted variably for BMI, age, age-squared and sex. In European-Americans, AHI wassignificantly associated with allelic variants within C-reactive protein and glial cell line-derivedneurotrophic factor; in African-Americans, only serotonin receptor 2a was significantly associatedwith AHI. The results await replication, although with improved approaches to phenotyping thismay not be readily achievable.

Genomic approaches to OSA

The total sum of an individual organism’s genes is known as the genome and, thus, genomics isthe study of all the genes of a cell or tissue at the DNA (genotype), mRNA (transcriptome) orprotein (proteome) levels. For instance, gene expression studies can be used to identify associations between genes and OSA. Analysis of mRNA levels expressed by proband genes incomparison to levels expressed by normal controls can identify genetic factors underlying thedisease and the secondary molecular factors that are consequential to it [108]. Such an approachmay also lead to the recognition of previously unknown pathophysiological pathways.

High-throughput technologies have been developed to principally address gene expression andproducts of gene expression, such as RNA, protein and metabolites and can be used to provide asnapshot of gene function in the cell at a given time-point. These techniques are summarised intable 4 [109] and include: genomics, proteomics (identification of proteins in the body and the

7 6

G E N E T I C

A S P E C T S O

F

O S A



T a b l e 3 . C a n d

i d a t e g e n e s t u d i e s f o r c a u s e s a n

d c o n s e q u e n c e s o f o b s t r u c t i v e s l e e p a p n o e a ( O S A ) i n a d u l t s

#

G e n e

A l l e l e

H y p o t h e s i s

P

o p u l a t i o n

P h e

n o t y p e

A s s o c i a t i o n

R e f .

A C E

I / D

A C E S N P

s a s s o c i a t e d w i t h

d e v e l o

p m e n t o f O S A

H a n C h i n e s e w i t h d i f f e r i n g

d e g r e e s o

f s l e e p a p n o e a a n d

h y p e r

t e n s i o n : n 5 1 7 4

A H I

C e n t r a l o b e s i t y

a s s o c i a t e d

w i t h D a l l e l e

, O S A ,

h y p e r t e n s i o n

[ 8 0 ]

A C E

I / D

A C E S N P


d e v e l o p m e

n t o f h y p e r t e n s i o n

i n O S A

W i s c o n

s i n S l e e p C o h o r t :

n 5 1 1 0 0

A H I

D a l l e l e a s s o c i a t e d

w i t h h y p e r t e n s i o n a t

m i l d / m o d e r a t e l e v e l s

o f O S A o n l y

[ 8 1 ]

A C E

I / D

A C E S N P


d e v e l o p m e


i n O S A

C l e v e l a

n d F a m i l y S t u d y :

n 5 9 7 2

A H I

H y p e r t e n s i o n r i s k r e d u c e d

i n s u b j e c t s w i t h D a l l e l e ; o n e

o r t w o D a l l e l e s

p r o t e c t i v e

a g a i n s t h y p e r t e n s i o n i n

s e v e r e a p n o e a

[ 8 2 ]

A C E

I / D

A C E S N P


d e v e l o

p m e n t o f O S A

P a t i e n t s

w i t h h y p e r t e n s i o n :

n 5 1 5 7

P o p u l a t i o

n c o n t r o l s : n 5 1 8 1

A H

I . 1 0

S i g n i f i c a n t i n t e r a c t i o n

b e t w e e n O S

A a n d

A C E I / D p o l y m

o r p h i s m

[ 8 3 ]

A C E

I / D

A C E S N P


d e v e l o p m e


i n O S A

3 0 H a

n C h i n e s e w i t h :

O S A a n d

h y p e r t e n s i o n , n 5 3 0

O S A n o

r m o t e n s i v e , n 5 3 0

C o

n t r o l s , n 5 3 0

A H I a n d b l o o d

p r e

s s u r e

I / I g e n o t y p e a n d I a l l e l e

m o r e c o m m

o n i n

h y p e r t e n s i v e

p a t i e n t s

w i t h O S

A

[ 8 4 ]

A C E

I / D

A C E S N P


O S A p r e s e n c e

O S A T u r k i s h p a t i e n t s : n 5 6 4

C o

n t r o l s : n 5 3 7

A H I

N o d i f f e r e n c e

i n a l l e l e

d i s t r i b u t i o n a m o n g

c a s e s a n d c

o n t r o l s

[ 8 5 ]

A D R B 2

C y

s 4 7 - A r g G l y 1 6 A r g

G l n 2 7 G l u

A D R B 2

S N P s i n f l u e n c e

c a r d i o v a s

c u l a r m o r b i d i t y i n

O S A

G e r m

a n p a t i e n t s w i t h

m o d e r a t e - t o - s e v e r e O S A :

n 5 4 2 9

A H I

H i g h e r r i s k o f a b n o r m a l

C V S p r o f i l e w i t h

d e l e t e r i o u s

S N P s ;

h i g h e r r i s k o f

m o r t a l i t y

p o s t - M I w i t h

d e l e t e r i o u s

S N P s

[ 8 6 ]

A D R B 3

T r p 6 4 A r g

O S A a s s o c i a t e d w i t h o b e s i t y

a n d i n s u l i n r e s i s t a n c e a n d

h y p e r t e n s i o n

P a t i e n t s

w i t h O S A : n 5 3 8 7

C o n t r o l s : n 5 1 3 7

A H I

N o a s s o c i a t i o n

o f A D R B 3

S N P w i t h O S

A ; B M I

h i g h e r i n s u b j e c t s w i t h

- 6 4 A r g

[ 8 7 ]

7 7

R . L

. R I H A



T a b l e

3 . C o n t i n u e d

G e n e

A l l e l e

H y

p o t h e s i s

P

o p u l a t i o n

P h e

n o t y p e


R e f .

A D R B 2

A D R B 3

C y

s 4 7 - A r g G l y 1 6 A r g

G l n 2 7 G l u T r p 6 4 A r g

C e n t r a l

o b e s i t y i s m o r e

c o m m o n i n O S A

M a l e H

a n C h i n e s e w i t h :

O

S A , n 5 1 6 5

C o n t r o l s , n 5 1 5 3

A H I

- 6 4 A r g S N P o

f A D B R 3

m o r e c o m m o n i n O S A

a n d p o s s i b l e a s s o c i a t i o n

w i t h o b e s i t y ; n o a s s o c i a t i o n o f

A D B R 2 S N P s w i t h O S A

[ 8 8 ]

T N F - a

- 3 0 8 A / G

T N F - a

a s s o c i a t e d

w

i t h O S A

S c o t t i s h

p a t i e n t s w i t h O S A :

n 5 1 0 3

C o n t r o l s : n 5 1 9 0

A H I , E S S , h i s t o r y o f

s l e e p i n e s s , a g e a n d

s e x - r e l a t e d c u t - o f f s

f o r A H I

d e v e l o p e d

- 3 0 8 A S N P a s

s o c i a t e d

w i t h O S

A

[ 6 9 ]

T N F - a

- 3 0 8 A / G

T N F - a

a s s o c i a t e d

w

i t h O S A

I n d i a n O S A p a t i e n t s

( n 5 1 0 4 ) v e r s u s

1 0 3 c o n t r o l s

( n 5 1 0 3

) ; a l l w e r e o b e s e

A H I

- 3 0 8 A S N P a s

s o c i a t e d

w i t h O S

A

[ 8 9 ]

H T R 2 A

-

1 4 3 8 G / A T 1 0 2 C

U p p e r

a i r w a y c o n t r o l

d e p e n d e n t o n t h e

s e r o t o n e r g i c s y s t e m

T u r k i s h O

S A p a t i e n t s : n 5 5 5

C o n t r o l s : n 5 1 0 2

A H I

T 1 0 2 C S N

P n o t

a s s o c i a t e d w i t h O S A ;

- 1 4 3 8 A S N P

m o r e

c o m m o n i n

O S A

[ 9 0 ]

5 H T R 2 A

5 H T R 2 C

T 1 0 2 C 7 9 6 G / C

U p p e r

a i r w a y c o n t r o l

d e p e n d e n t o n t h e

s e r o t o n e r g i c s y s t e m

M a l e J a p a

n e s e O S A p a t i e n t s :

n 5 1 7 7

M a l e c o n t r o l s : n 5 1 0 0

A H I . 5 a n d

d a

y t i m e

s o m n o l e n c e

H T R 2 C S N P

o f t o o

l o w a f r e q u e n c y ; n o

a s s o c i a t i o n o f 5 - H T 2 A

r e c e p t o r S N P w i t h O S A

[ 9 1 ]

L E P R

G l n 2 2 3 A r g ( A / G )

L e p t i n

l e v e l s r a i s e d

i n O S A

O S A p a t i e n t s : n 5 1 0 2

C o

n t r o l s : n 5 7 7

A H

I . 5

- 2 2 3 A r g c a r r i a g e m o r e

f r e q u e n t i n t h e m

o r e o b e s e

e s p e c i a l l y f e

m a l e s

S u b j e c t s w i t h

A r g / A r g

g e n o t y p e h a d h i g h e r t r i -

g l y c e r i d e a n d c h o l e s t e r o l l e v e l s

[ 9 2 ]

L E P

L E P R

T e t r a n u c l e o t i d e

r

e p e a t i n 3 9 - f l a n k

r e

g i o n l e p t i n g e n e ;

L

y s 1 0 9 A r g ( A / G ) ;

G

l n 2 2 3 A r g ( A / G ) ;

L

y s 6 5 6 A s n ( G / C )

L e p t i n r e g u l a t i o n

a l t e

r e d i n O S A

J a p a n e

s e O S A p a t i e n t s :

n 5 1 3 0

C o

n t r o l s : n 5 5 0

A H

I . 5

N o a s s o c i a t i o n o

f a n y S N P s

w i t h O S

A

[ 9 3 ]

7 8

G E N E T I C

A S P E C T S O

F

O S A



determination of their role in physiologicaland pathophysiological functions); transcrip-tomics (the study of messenger RNA mole-cules produced in an individual or populationof a particular cell type); epigenomics (theexpression of epigenetic mechanisms such asDNA methylation and modifications to his-

tone proteins which regulate high-order DNAstructure and gene expression); and metabo-lomics (the study of the metabolites in abiological cell, tissue, organ or organism, whichare the end products of cellular processes).

Results from these studies should be inter-preted as preliminary, and await replicationin other and larger populations.

Limitations of the techniques are currently

significant and substantial work needs to beundertaken in order to identify body tissuesand fluids which provide the most mean-ingful information about the consequencesof OSA. The reader is referred to two recent,exhaustive reviews of this area in the contextof OSA [116, 117].

Unresolved questions and

future researchIn spite of tremendous technological advancesin the fields of molecular biology andgenomics, a number of issues remain regard-ing OSA as a disorder. First, OSA defies anunequivocal phenotypic definition. If there isto be any progress, it is essential to address thecomplexity of the disease fully using astandardised approach. This has major impli-cations for assessing disease prevalence, causaleffects on cardiovascular and metabolic statusand the long-term effectiveness of treatment.A variety of approaches could be trialled,including the use of cluster analysis [108, 118]and mathematical modelling incorporatingnon-linear approaches and chaos theory. Theparadigm that OSA and SDB are inextricably linked on the same disease spectrum hasremained unchallenged for over 30 yrs. Thereis no evidence that snoring will develop intoSDB and then develop into OSA.

Secondly, longitudinal studies of populationswith OSA (both paediatric and adult) shouldbe established in order to address change inphenotype over time.

T a b l e

3 . C o n t i n u e d

G e n e

A l l e l e

H y p o t h e s i s

P

o p u l a t i o n

P h e

n o t y p e


R e f .

A P O E

A P O E 4

A P O E 4 p r e c u r s o r o f

a t h e r o s c l e r o s i s

F i n n i s h

p a t i e n t s : n 5 2 9 1

R a n d o m

c o n t r o l s : n 5 7 2 8

D i a g n o s i s o f O S A

N o d i f f e r e n c e i n a

l l e l i c v a r i a n t s

o f A P O

E

[ 9 4 ]

A P O E

A P O E 4



J a p a n e s

e - A m e r i c a n m a l e s

a g e d 7

9 – 9 7 y r s : n 5 7 1 8

A H

I . 5

N o a s s o c i a t i o n o f

A p o E E 4 w i t h A H I

[ 9 5 ]

A P O E

A P O E 4



A p o E

E 4 + v e ( n 5 2 2 2 )

v e r s u s A p

o E E 4 - v e ( n 5 5 6 9 )

S t r a t i f i c a t i o n o f

O S A S g r o u p w i t h

A H I . 5

a c c o r d i n g

t o A P O E g e n o t y p e

H i g h e r A H I i n

E 4 + v e

g r o u p

[ 9 6 ]

A P O E

A P O E 4



S l e e p H

e a r t H e a l t h S t u d y

c o m m u n i t y r e c r u i t s : n 5 1 7 7 5

A H

I . 5

N o r m a l d i s t r i b

u t i o n o f

E 4 / E 4

[ 9 7 ]

A C E : a n g i o t e n s i n c o n v e r t i n g e n z y m e ; A D R B 2 : b 2

- a d r e n o r e c e p t o r ; A D R B 3 : b 3 - a d r e n o r e c e p t o r ; T N F - a : t u m o u r n e c

r o s i s f a c t o r - a ; H T R 2 A : 5 - h y d r o x y t r y p t a m i n e r e c e p t o r 2 A ;

H T R 2 C : 5 - h y d r o

x y t r y p t a m i n e r e c e p t o r 2 C ; L E P R

: l e p t i n r e c e p t o r ; L E P : l e p t i n ; A P O E : a p o l i p o p r o t e i n E g e n e ; S N P :

s i n g l e n u c l e o t i d e p o l y m o r p h i s m ;

A p o E : a p o l i p o p r o t e i n E ;

A H I : a p n o e a / h y p o p n o e a i n d e x ; E S S : E p w o r t h S

l e e p i n e s s S c a l e ; O S A S ; o b s t r u c t i v e s l e e p a p n o e a s y n d r o m e ; C

V S : c a r d i o v a s c u l a r ; p o s t - M I : p o

s t - m y o c a r d i a l i n f a r c t i o n ;

B M I : b o d y m a s s

i n d e x ; I : i n s e r t i o n ; D : d e l e t i o n ; +

v e : p o s i t i v e ; - v e : n e g a t i v e .

# : s t u d i e s r e p l i c a t e d i n d i f f e r e n t p o p u l a t i o n s .

7 9

R . L

. R I H A



Table 4. High-throughput technologies utilised in human populations with obstructive sleep apnoea (OSA)

Technology Analyte Abnormality

detected

Use in human

populations

with OSA

Genomics

Global genome

sequencing

Genomic DNA Mutations No studies published

CGH arrays Sequences of genomic

DNA

Alterations in copy

number

No studies published

SNP arrays Oligonucleotides Polymorphisms,

alteration in copy number,

loss of heterozygosity


Epigenomics

DNA methylation

arrays

Oligonucleotides over

whole genome

DNA hyper- or

hypomethylation


Transcriptomics

Gene expressionarrays

Oligonucleotides orcDNA

Modification of geneexpression levels

4 adult OSA patientsand 4 controls [110]

20 non-obese OSA

children and 20

controls [111]

Adenotonsillar

hypertrophy in

paediatric OSA [112]

miRNA expression

arrays

Oligonucleotides Modification of

miRNA levels


Proteomics

2D-gel

electrophoresis

Proteins, peptides Modification of

relative abundance

and activity of proteins

11 OSA children and

11 controls [113]

60 OSA children; 30

snoring children; 30

controls [114]

MALDI-TOF MS;

SELDI-TOF MS

Proteins, peptides 20 OSA children and

20 controls [115]

11 OSA children and

11 controls [113]

Tandem MS Peptide sequences No studies publishedProtein arrays Lysates, proteins,

peptides


Tissue microarrays Tissue biopsies No studies published

Metabolomics

Separation by GC,

HPLC or CE

Molecules ,1 kDa in

size and certain

macromolecules such

as albumin; protein

Detection of products

resulting from cell

metabolism


Detection by MS or

NMR

CGH: comparative genomic hybridisation; SNP: single nucleotide polymorphism; MALDI-TOF MS: matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MS); SELDI-TOF MS: surface-enhanced

laser desorption/ionisation time-of-flight MS; GC: gas chromatography; HPLC: high-performance liquid

chromatography; CE: capillary electrophoresis; NMR: nuclear magnetic resonance spectroscopy. Data takenfrom [109].

8 0

G E N E T I C

A S P E C T S O

F

O S A



Thirdly, better characterisation of clinico-physiological phenotypes should be undertaken.Innovative approaches have been developed to assess the craniofacial dimensions most pertinentto the development of OSA using simple photographic techniques combined with digitaltechnology [119, 120]. Finally, why conduct genetic studies in OSA? A single genetic basis to thedisorder is unlikely. OSA appears to be a polygenic disorder, both in children and adults; the resultof breakdown in many quantitatively varying physiological systems, heavily influenced by theenvironment. Potentially, the most meaningful studies are those addressing the sequelae of OSA

where recognition of genetic predisposition to their development could lead to more targetedtreatments in the future.

The speed with which the field of genetics is evolving lends hope that those who work in the fieldof OSA learn from the studies conducted in other polygenic disorders, their pitfalls and successesand, in due course, move further and faster.

Conclusion

OSA is a highly prevalent condition throughout most countries. With obesity being one of thestrongest risk factors for its development it will become increasingly common as our populationsgain weight. Untreated, OSA carries a significant economic burden to society in the form of public-health risk (e.g. sleepiness whilst driving) and the risk of cardiovascular morbidity andmortality as its most important sequelae.

OSA is known to be hereditary but a number of environmental and developmental factors canaffect the degree of its expression, e.g. obesity, hormonal changes, nasal occlusion and lymphoidtissue growth.

The definition of OSA in adults and children, as well as the limited knowledge regarding itsevolution and natural history, makes phenotyping of the condition difficult.

For this reason OSA is generally considered to be a sum of its component parts with relativecontributions in each individual from craniofacial morphology, susceptibility to sleepiness,ventilatory control, obesity, upper airway control and lymphoid tissue overgrowth.

Because OSA is phenotypically heterogeneous, this complexity makes establishment of a singlegenetic basis elusive. Furthermore, unlike other polygenic disease models, such as chronicobstructive pulmonary disease, asthma and hypertension, funding for studies in OSA has beenlimited. A number of genetic approaches have been utilised, including genome-wide studies, case–control studies and GWAS. The results of these demonstrate our first tentative, but hopeful, stepsof uncovering some of the markers of disease expression as well as disease progression and itssequelae, such as hypertension and increased metabolic abnormalities.

Rapid technological advances in the field of genomics may lead to the discovery of importantmarkers of dysfunctional metabolic pathways worsened or precipitated by the presence of OSA.However, at present, only a few studies have been undertaken and numbers are small. Futureefforts aimed at exploring the sequelae of OSA and possible genetic modulators of these are morelikely to yield clinically useful data, which will ultimately result in improved patient care.

Statement of Interest

None declared.

References1. Mackiewicz M, Zimmerman JE, Shockley KR, et al. What are microarrays teaching us about sleep? Trends Mol

Med 2009; 15: 79–87.

2. Strohl KP, Redline S. Recognition of obstructive sleep apnea. Am J Respir Crit Care Med 1996; 154: 279–289.

8 1

R . L

. R I H A



3. Davies RJ, Stradling JR. The relationship between neck circumference, radiographic pharyngeal anatomy, and the

obstructive sleep apnoea syndrome. Eur Respir J 1990; 3: 509–514.

4. Pillar G, Shehadeh N. Abdominal fat and sleep apnea: the chicken or the egg? Diabetes Care 2008; 31: Suppl. 2,

S303–S309.

5. Young T, Palta M, Dempsey J, et al. Burden of sleep apnea: rationale, design, and major findings of the Wisconsin

Sleep Cohort Study. WMJ 2009; 108: 246–249.

6. Guilleminault C, Quera-Salva MA, Partinen M, et al. Women and the obstructive sleep apnea syndrome. Chest

1988; 93: 104–109.

7. Lowe AA, Santamaria JD, Fleetham JA, et al. Facial morphology and obstructive sleep apnea. Am J Orthod

Dentofacial Orthop 1986; 90: 484–491.8. Mathur R, Douglas NJ. Family studies in patients with the sleep apnea–hypopnea syndrome. Ann Intern Med

1995; 122: 174–178.

9. Redline S, Tishler PV. The genetics of sleep apnea. Sleep Med Rev 2000; 4: 583–602.

10. Scanlan MF, Roebuck T, Little PJ, et al. Effect of moderate alcohol upon obstructive sleep apnoea. Eur Respir J

2000; 16: 909–913.

11. Wetter DW, Young TB, Bidwell TR, et al. Smoking as a risk factor for sleep-disordered breathing. Arch Intern

Med 1994; 154: 2219–2224.

12. Lavie P, Fischel N, Zomer J, et al. The effects of partial and complete mechanical occlusion of the nasal passages

on sleep structure and breathing in sleep. Acta Otolaryngol 1983; 95: 161–166.

13. Li AM, So HK, Au CT, et al. Epidemiology of obstructive sleep apnoea syndrome in Chinese children: a two-

phase community study. Thorax 2010; 65: 991–997.

14. Ali NJ, Pitson DJ, Stradling JR. Snoring, sleep disturbance, and behaviour in 4–5 year olds. Arch Dis Child 1993;68: 360–366.

15. Amin RS, Kimball TR, Bean JA, et al. Left ventricular hypertrophy and abnormal ventricular geometry in children

and adolescents with obstructive sleep apnea. Am J Respir Crit Care Med 2002; 165: 1395–1399.

16. Kheirandish L, Gozal D. Neurocognitive dysfunction in children with sleep disorders. Dev Sci 2006; 9: 388–399.

17. de la Eva RC, Baur LA, Donaghue KC, et al. Metabolic correlates with obstructive sleep apnea in obese subjects.

J Pediatr 2002; 140: 654–659.

18. Kalra M, Chakraborty R. Genetic susceptibility to obstructive sleep apnea in the obese child. Sleep Med 2007; 8:

169–175.

19. Gozal D. Congenital central hypoventilation syndrome: an update. Pediatr Pulmonol 1998; 26: 273–282.

20. Schechter MS. Technical report: diagnosis and management of childhood obstructive sleep apnea syndrome.

Pediatrics 2002; 109: e69.

21. Dayyat E, Kheirandish-Gozal L, Gozal D. Childhood obstructive sleep apnea: one or two distinct disease entities?Sleep Med Clin 2007; 2: 433–444.

22. Pendlebury ST, Pepin JL, Veale D, et al. Natural evolution of moderate sleep apnoea syndrome: significant

progression over a mean of 17 months. Thorax 1997; 52: 872–878.

23. Sforza E, Addati G, Cirignotta F, et al. Natural evolution of sleep apnoea syndrome: a five year longitudinal study.

Eur Respir J 1994; 7: 1765–1770.

24. Marin JM, Carrizo SJ, Vicente E, et al. Long-term cardiovascular outcomes in men with obstructive sleep apnoea-

hypopnoea with or without treatment with continuous positive airway pressure: an observational study. Lancet

2005; 365: 1046–1053.

25. Doherty LS, Kiely JL, Swan V, et al. Long-term effects of nasal continuous positive airway pressure therapy on

cardiovascular outcomes in sleep apnea syndrome. Chest 2005; 127: 2076–2084.

26. Arens R, Marcus CL. Pathophysiology of upper airway obstruction: a developmental perspective. Sleep 2004; 27:

997–1019.27. Malhotra A, Huang Y, Fogel R, et al. Aging influences on pharyngeal anatomy and physiology: the predisposition

to pharyngeal collapse. Am J Med 2006; 119: 72.

28. Behan M, Brownfield MS. Age-related changes in serotonin in the hypoglossal nucleus of rat: implications for

sleep-disordered breathing. Neurosci Lett 1999; 267: 133–136.

29. Riha RL, Brander P, Vennelle M, et al. A cephalometric comparison of patients with the sleep apnea/hypopnea

syndrome and their siblings. Sleep 2005; 28: 315–320.

30. Pack AI, Silage DA, Millman RP, et al. Spectral analysis of ventilation in elderly subjects awake and asleep. J Appl

Physiol 1988; 64: 1257–1267.

31. Weaver TE, Chasens ER. Continuous positive airway pressure treatment for sleep apnea in older adults. Sleep

Med Rev 2007; 11: 99–111.

32. Lavie L, Lavie P. Ischemic preconditioning as a possible explanation for the age decline relative mortality in sleep

apnea. Med Hypotheses 2006; 66: 1069–1073.

33. Morris AH. Rigorous genotype-phenotype association research depends on scientific rigor at multiple scales of

investigation. Crit Care Med 2008; 36: 2956–2958.

34. American Academy of Sleep Medicine Task Force, Sleep related breathing disorders in adults: recommendations

for syndrome definition and measurement techniques in clinical research. Sleep 1999; 22: 667–689.

35. Sauter C, Asenbaum S, Popovic R, et al. Excessive daytime sleepiness in patients suffering from different levels of

obstructive sleep apnoea syndrome. J Sleep Res 2000; 9: 293–301.

8 2

G E N E T I C

A S P E C T S O

F

O S A



36. Koutsourelakis I, Perraki E, Bonakis A, et al. Determinants of subjective sleepiness in suspected obstructive sleep

apnoea. J Sleep Res 2008; 17: 437–443.

37. Engleman HM, Hirst WS, Douglas NJ. Under reporting of sleepiness and driving impairment in patients with

sleep apnoea/hypopnoea syndrome. J Sleep Res 1997; 6: 272–275.

38. Behrents RG. The biological basis for understanding craniofacial growth during adulthood. Prog Clin Biol Res

1985; 187: 307–319.

39. Lavie P, Rubin AE. Effects of nasal occlusion on respiration in sleep. Evidence of inheritability of sleep apnea

proneness. Acta Otolaryngol 1984; 97: 127–130.

40. Thesleff I. The genetic basis of normal and abnormal craniofacial development. Acta Odontol Scand 1998; 56:

321–325.41. Verhulst SL, Van Gaal L, De Backer W, et al. The prevalence, anatomical correlates and treatment of sleep-

disordered breathing in obese children and adolescents. Sleep Med Rev 2008; 12: 339–346.

42. Friberg D, Sundquist J, Li X, et al. Sibling risk of pediatric obstructive sleep apnea syndrome and

adenotonsillarhypertrophy. Sleep 2009; 32: 1077–1083.

43. Goldbart AD, Mager E, Veling MC, et al. Neurotrophins and tonsillar hypertrophy in children with obstructive

sleep apnea. Pediatr Res 2007; 62: 489–494.

44. Kim J, Bhattacharjee R, Dayyat E, et al. Increased cellular proliferation and inflammatory cytokines in tonsils

derived from children with obstructive sleep apnea. Pediatr Res 2009; 66: 423–428.

45. Crummy F, Piper AJ, Naughton MT. Obesity and the lung: 2. Obesity and sleep-disordered breathing. Thorax

2008; 63: 738–746.

46. Kapsimalis F, Varouchakis G, Manousaki A, et al. Association of sleep apnea severity and obesity with insulin

resistance, C-reactive protein, and leptin levels in male patients with obstructive sleep apnea. Lung 2008; 186:209–217.

47. Bouchard C. Genetics of human obesity: recent results from linkage studies. J Nutr 1997; 127: 1887S–1890S.

48. Krueger JM, Obal F Jr, Fang J. Humoral regulation of physiological sleep: cytokines and GHRH. J Sleep Res 1999;

8: Suppl. 1, 53–59.

49. Krueger JM, Majde JA. Humoral links between sleep and the immune system: research issues. Ann N Y Acad Sci

2003; 992: 9–20.

50. Williams A, Scharf SM. Obstructive sleep apnea, cardiovascular disease, and inflammation: is NF-kB the key?

Sleep Breath 2007; 11: 69–76.

51. Fenik P, Veasey SC. Pharmacological characterization of serotonergic receptor activity in the hypoglossal nucleus.

Am J Respir Crit Care Med 2003; 167: 563–569.

52. Kraiczi H, Hedner J, Dahlof P, et al. Effect of serotonin uptake inhibition on breathing during sleep and daytime

symptoms in obstructive sleep apnea. Sleep 1999; 22: 61–67.53. Hirshman CA, McCullough RE, Weil JV. Normal values for hypoxic and hypercapnic ventilaroty drives in man.

J Appl Physiol 1975; 38: 1095–1098.

54. Thomas DA, Swaminathan S, Beardsmore CS, et al. Comparison of peripheral chemoreceptor responses in

monozygotic and dizygotic twin infants. Am Rev Respir Dis 1993; 148: 1605–1609.

55. el Bayadi S, Millman RP, Tishler PV, et al. A family study of sleep apnea. Anatomic and physiologic interactions.

Chest 1990; 98: 554–559.

56. Redline S, Tishler PV, Hans MG, et al. Racial differences in sleep-disordered breathing in African-Americans and

Caucasians. Am J Respir Crit Care Med 1997; 155: 186–192.

57. Rajagopal KR, Abbrecht PH, Tellis CJ. Control of breathing in obstructive sleep apnea. Chest 1984; 85:

174–180.

58. Javaheri S, Colangelo G, Corser B, et al. Familial respiratory chemosensitivity does not predict hypercapnia of

patients with sleep apnea-hypopnea syndrome. Am Rev Respir Dis 1992; 145: 837–840.59. Gold AR, Schwartz AR, Wise RA, et al. Pulmonary function and respiratory chemosensitivity in moderately obese

patients with sleep apnea. Chest 1993; 103: 1325–1329.

60. Narkiewicz K, van de Borne PJ, Pesek CA, et al. Selective potentiation of peripheral chemoreflex sensitivity in

obstructive sleep apnea. Circulation 1999 9 , 99: 1183–1189.

61. Marcus CL, Gozal D, Arens R, et al. Ventilatory responses during wakefulness in children with obstructive sleep

apnea. Am J Respir Crit Care Med 1994; 149: 715–721.

62. Radwan L, Koziorowski A, Maszczyk Z, et al. Respiratory response to inspiratory resistive load changes in

patients with obstructive sleep apnea syndrome. Pneumonol Alergol Pol 2000; 68: 44–56.

63. Ibrahim LH, Patel SR, Modarres M, et al. A measure of ventilatory variability at wake-sleep transition predicts

sleep apnea severity. Chest 2008; 134: 73–78.

64. Levy P, Bonsignore MR, Eckel J. Sleep, sleep-disordered breathing and metabolic consequences. Eur Respir J 2009;

34: 243–260.

65. McNicholas WT, Bonsigore MR, Management Committee of EU COST ACTION B26. Sleep apnoea as an

independent risk factor for cardiovascular disease: current evidence, basic mechanisms and research priorities.

Eur Respir J 2007; 29: 156–178.

66. Yaggi HK, Concato J, Kernan WN, et al. Obstructive sleep apnea as a risk factor for stroke and death. N Engl J

Med 2005; 353: 2034–2041.

8 3

R . L

. R I H A



67. Ryan S, Nolan GM, Hannigan E, et al. Cardiovascular risk markers in obstructive sleep apnoea syndrome and

correlation with obesity. Thorax 2007; 62: 509–514.

68. Ryan S, Taylor CT, McNicholas WT. Selective activation of inflammatory pathways by intermittent hypoxia in

obstructive sleep apnea syndrome. Circulation 2005; 112: 2660–2667.

69. Riha RL, Brander P, Vennelle M, et al. Tumour necrosis factor-a (-308) gene polymorphism in obstructive sleep

apnoea-hypopnoea syndrome. Eur Respir J 2005; 26: 673–678.

70. Vgontzas AN, Papanicolaou DA, Bixler EO, et al. Elevation of plasma cytokines in disorders of excessive daytime

sleepiness: role of sleep disturbance and obesity. J Clin Endocrinol Metab 1997; 82: 1313–1316.

71. Vgontzas AN, Papanicolaou DA, Bixler EO, et al. Sleep apnea and daytime sleepiness and fatigue: relation to

visceral obesity, insulin resistance, and hypercytokinemia. J Clin Endocrinol Metab 2000; 85: 1151–1158.72. Bhattacharjee R, Kheirandish-Gozal L, Pillar G, et al. Cardiovascular complications of obstructive sleep apnea

syndrome: evidence from children. Prog Cardiovasc Dis 2009; 51: 416–433.

73. Goldbart AD, Tal A. Inflammation and sleep disordered breathing in children: a state-of-the-art review. Pediatr

Pulmonol 2008; 43: 1151–1160.

74. Korner A, Kratzsch J, Gausche R, et al. Metabolic syndrome in children and adolescents: risk for sleep-disordered

breathing and obstructive sleep-apnoea syndrome? Arch Physiol Biochem 2008; 114: 237–243.

75. Lander E, Kruglyak L. Genetic dissection of complex traits: guidelines for interpreting and reporting linkage

results. Nat Genet 1995; 11: 241–247.

76. Palmer LJ, Buxbaum SG, Larkin E, et al. A whole-genome scan for obstructive sleep apnea and obesity. Am J

Hum Genet 2003; 72: 340–350.

77. Palmer LJ, Buxbaum SG, Larkin EK, et al. Whole genome scan for obstructive sleep apnea and obesity in African-

American families. Am J Respir Crit Care Med 2004; 169: 1314–1321.78. Larkin EK, Patel SR, Elston RC, et al. Using linkage analysis to identify quantitative trait loci for sleep apnea in

relationship to body mass index. Ann Hum Genet 2008; 72: 762–773.

79. Daly AK, Day CP. Candidate gene case-control association studies: advantages and potential pitfalls. Br J Clin

Pharmacol 2001; 52: 489–499.

80. Zhang J, Zhao B, Gesongluobu, et al. Angiotensin-converting enzyme gene insertion/deletion (I/D)

polymorphism in hypertensive patients with different degrees of obstructive sleep apnea. Hypertens Res 2000; 23:

407–411.

81. Lin L, Finn L, Zhang J, et al. Angiotensin-converting enzyme, sleep-disordered breathing, and hypertension. Am J

Respir Crit Care Med 2004; 170: 1349–1353.

82. Patel SR, Larkin EK, Mignot E, et al. The association of angiotensin converting enzyme (ACE) polymorphisms

with sleep apnea and hypertension. Sleep 2007; 30: 531–533.

83. Bostrom KB, Hedner J, Melander O, et al. Interaction between the angiotensin-converting enzyme gene insertion/deletion polymorphism and obstructive sleep apnoea as a mechanism for hypertension. J Hypertens 2007; 25:

779–783.

84. Li Y, Zhang W, Wang T, et al. [Study on the polymorphism of angiotensin converting enzyme genes and serum

angiotensin II level in patients with obstructive sleep apnea hypopnea syndrome accompanied hypertension]. Lin

Chuang Er Bi Yan Hou Ke Za Zhi 2004; 18: 456–459.

85. Yakut T, Karkucak M, Ursavas A, et al. Lack of association of ACE gene I/D polymorphism with obstructive sleep

apnea syndrome in Turkish patients. Genet Mol Res 2010; 20: 734–738.

86. Bartels NK, Borgel J, Wieczorek S, et al. Risk factors and myocardial infarction in patients with obstructive sleep

apnea: impact of b2-adrenergic receptor polymorphisms. BMC Med 2007; 5: 1.

87. Pierola J, Barcelo A, de la Pena M, et al. b3-adrenergic receptor Trp64Arg polymorphism and increased body

mass index in sleep apnoea. Eur Respir J 2007; 30: 743–747.

88. Zhang LQ, Yao WZ, He QY, et al. Polymorphisms in theb

2 andb

3 adrenergic receptor genes in obstructive sleepapnea/hypopnea syndrome. Zhonghua Nei Ke Za Zhi 2005; 44: 333–336.

89. Bhushan B, Guleria R, Misra A, et al. TNF-a gene polymorphism and TNF-alpha levels in obese Asian Indians

with obstructive sleep apnea. Respir Med 2009; 103: 386–392.

90. Bayazit YA, Yilmaz M, Ciftci T, et al. Association of the -1438G/A polymorphism of the 5-HT2A receptor gene

with obstructive sleep apnea syndrome. ORL J Otorhinolaryngol Relat Spec 2006; 68: 123–128.

91. Sakai K, Takada T, Nakayama H, et al. Serotonin-2A and 2C receptor gene polymorphisms in Japanese patients

with obstructive sleep apnea. Intern Med 2005; 44: 928–933.

92. Popko K, Gorska E, Wasik M, et al. Frequency of distribution of leptin receptor gene polymorphism in

obstructive sleep apnea patients. J Physiol Pharmacol 2007; 58: Suppl. 5, 551–561.

93. Hanaoka M, Yu X, Urushihata K, et al. Leptin and leptin receptor gene polymorphisms in obstructive sleep apnea

syndrome. Chest 2008; 133: 79–85.

94. Saarelainen S, Lehtimaki T, Kallonen E, et al. No relation between apolipoprotein E alleles and obstructive sleep

apnea. Clin Genet 1998; 53: 147–148.

95. Foley DJ, Masaki K, White L, et al. Relationship between apolipoprotein E epsilon4 and sleep-disordered

breathing at different ages. JAMA 2001; 286: 1447–1448.

96. Kadotani H, Kadotani T, Young T, et al. Association between apolipoprotein E epsilon4 and sleep-disordered

breathing in adults. JAMA 2001; 285: 2888–2890.

8 4

G E N E T I C

A S P E C T S O

F

O S A



97. Gottlieb DJ, De Stefano AL, Foley DJ, et al. APOE epsilon4 is associated with obstructive sleep apnea/hypopnea:

the Sleep Heart Health Study. Neurology 2004; 63: 664–668.

98. Gozal D, Capdevila OS, Kheirandish-Gozal L, et al. APOE epsilon 4 allele, cognitive dysfunction, and obstructive

sleep apnea in children. Neurology 2007; 69: 243–249.

99. Kalra M, Pal P, Kaushal R, et al. Association of ApoE genetic variants with obstructive sleep apnea in children.

Sleep Med 2008; 9: 260–265.

100. Goldbart AD, Goldman JL, Li RC, et al. Differential expression of cysteinyl leukotriene receptors 1 and 2 in

tonsils of children with obstructive sleep apnea syndrome or recurrent infection. Chest 2004; 126: 13–18.

101. Carotenuto M, Santoro N, Grandone A, et al. The insulin gene variable number of tandemrepeats (INS VNTR)

genotype and sleep disordered breathing in childhood obesity. J Endocrinol Invest 2009; 32: 752–755.102. Gu XQ, Liu DB, Wan GP. Polymorphism of angiotensin converting enzyme genes in children with obstructive

sleep apnea-syndrome. Zhonghua Er Ke Za Zhi 2006; 44: 874–875.

103. Thakre TP, Mamtani MR, Kulkarni H. Lack of association of the APOE epsilon 4 allele with the risk of

obstructive sleep apnea: meta-analysis and meta-regression. Sleep 2009; 32: 1507–1511.

104. Qu HQ, Bradfield JP, Li Q, et al. In silico replication of the genome-wide association results of the Type 1

Diabetes Genetics Consortium. Hum Mol Genet 2010; 19: 2534–2538.

105. Hinney A, Vogel CI, Hebebrand J. From monogenic to polygenic obesity: recent advances. Eur Child Adolesc

Psychiatry 2010; 19: 297–310.

106. Sober S, Org E, Kepp K, et al. Targeting 160 candidate genes for blood pressure regulation with a genome-wide

genotyping array. nPLoS One 2009; 4: e6034.

107. Larkin EK, Patel SR, Goodloe RJ, et al. A candidate gene study of obstructive sleep apnea in European Americans

and African Americans. Am J Respir Crit Care Med 2010; 182: 947–953.108. Williams RW. Expression genetics and the phenotype revolution. Mamm Genome 2006; 17: 496–502.

109. Ocak S, Sos ML, Thomas RK, et al. High-throughput molecular analysis in lung cancer: insights into biology and

potential clinical applications. Eur Respir J 2009; 34: 489–506.

110. Hoffmann MS, Singh P, Wolk R, et al. Microarray studies of genomic oxidative stress and cell cycle responses in

obstructive sleep apnea. Antioxid Redox Signal 2007; 9: 661–669.

111. Khalyfa A, Capdevila OS, Buazza MO, et al. Genome-wide gene expression profiling in children with non-obese

obstructive sleepapnea. Sleep Med 2009; 10: 75–86.

112. Khalyfa A, Gharib SA, Kim J, et al. Transcriptomic analysis identifies phosphatases as novel targets for

adenotonsillar hypertrophy of pediatric obstructive sleep apnoea. Am J Respir Crit Care Med 2010; 181: 1114–1120.

113. Krishna J, Shah ZA, Merchant M, et al. Urinary protein expression patterns in children with sleep-disordered

breathing: preliminary findings. Sleep Med 2006; 7: 221–227.

114. Gozal D, Jortani S, Snow AB, et al. Two-dimensional differential in-gel electrophoresis proteomic approachesreveal urine candidate biomarkers in pediatric obstructive sleep apnea. Am J Respir Crit Care Med 2009; 180:

1253–1261.

115. Shah ZA, Jortani SA, Tauman R, et al. Serum proteomic patterns associated with sleep-disordered breathing in

children. Pediatr Res 2006; 59: 466–470.

116. Arnardottir ES, Mackiewicz M, Gislason T, et al. Molecular signatures of obstructive sleep apnea in adults: a

review and perspective. Sleep 2009; 32: 447–470.

117. Polotsky VY, O’Donnell CP. Genomics of sleep-disordered breathing. Proc Am Thorac Soc 2007; 4: 121–126.

118. Wardlaw AJ, Silverman M, Siva R, et al. Multi-dimensional phenotyping: towards a new taxonomy for airway

disease. Clin Exp Allergy 2005; 35: 1254–1262.

119. Lee RW, Petocz P, Prvan T, et al. Prediction of obstructive sleep apnea with craniofacial photographic analysis.

Sleep 2009; 32: 46–52.

120. Lee RW, Chan AS, Grunstein RR, et al. Craniofacial phenotyping in obstructive sleep apnea: a novel quantitativephotographic approach. Sleep 2009; 32: 37–45.

R . L

. R I H A

8 genetic aspects of osa

Documents