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Journey towards a personalised medicine approach for OSA: Can a similar approach to adult OSA be applied to paediatric OSA?
Journal Pre-proofs Review Journey towards a personalised medicine approach for OSA: Can a similar approach to adult OSA be applied to paediatric OSA? Leon S. Siriwardhana, Gillian M. Nixon, Rosemary S.C. Horne, Bradley A. Edwards PII: DOI: Reference:
S1526-0542(20)30018-X https://doi.org/10.1016/j.prrv.2020.01.002 YPRRV 1361
To appear in:
Paediatric Respiratory Reviews
Received Date: Revised Date: Accepted Date:
11 December 2019 21 January 2020 31 January 2020
Please cite this article as: L.S. Siriwardhana, G.M. Nixon, R.S.C. Horne, B.A. Edwards, Journey towards a personalised medicine approach for OSA: Can a similar approach to adult OSA be applied to paediatric OSA?, Paediatric Respiratory Reviews (2020), doi: https://doi.org/10.1016/j.prrv.2020.01.002
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TITLE PAGE Article title: Journey towards a personalised medicine approach for OSA: Can a similar approach to adult OSA be applied to paediatric OSA?
Authors: Leon S Siriwardhana1, Gillian M Nixon1, 2, Rosemary SC Horne1*, Bradley A Edwards3, 4*. 1The
Ritchie Centre, Hudson Institute of Medical Research and Department of Paediatrics, Monash University, Melbourne, Australia. 2Melbourne
Children’s Sleep Centre, Monash Children’s Hospital, Melbourne, Australia.
3Sleep
and Circadian Medicine Laboratory, Department of Physiology, Monash University, Melbourne, Australia. 4School
of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia. *both authors jointly supervised this work
Corresponding author: Dr Bradley A Edwards Address: 264 Ferntree Gully Road, Notting Hill, Victoria 3168, Australia Office. +613 9905 0187 Fax. +613 9905 3948 Email: [email protected]
Declarations of interest: none This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
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Abstract The concept of personalised medicine is likely to revolutionise the treatment of adult obstructive sleep apnoea as a result of recent advances in the understanding of disease heterogeneity by identifying clinical phenotypes, pathophysiological endotypes, biomarkers and treatable traits. Children with the condition show a similar level of heterogeneity and paediatric obstructive sleep apnoea would also benefit from a more targeted approach to diagnosis and management. This review aims to summarise the adult literature on the phenotypes and endotypes of obstructive sleep apnoea and assess whether a similar approach may also be suitable to guide the development of new diagnostic and management approaches for paediatric obstructive sleep apnoea.
Keywords Sleep; Sleep disordered breathing; obstructive sleep apnoea; phenotyping; personalised medicine
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Educational Aims The reader will be able to appreciate that:
Obstructive sleep apnoea is a complex heterogeneous condition with dynamic and variable disease pathways, disease expression and sequelae.
A number of clinical phenotypes and pathophysiological endotypes have been identified in adult obstructive sleep apnoea.
Emerging evidence in paediatric obstructive sleep apnoea also indicates the presence of a number of phenotypes and endotypes.
Further research is needed to more comprehensively characterise the heterogeneity of paediatric obstructive sleep apnoea and identify factors that could lead to more targeted treatment.
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Introduction Obstructive sleep disordered breathing (SDB) is prevalent across the lifespan, from young children to adults. Obstructive sleep apnoea (OSA) is at the severe end of the SDB spectrum, with a prevalence of 9-36% in the adult population [1] and 1-6% in the paediatric population [2]. The repetitive complete or partial collapse of the pharyngeal airway that occurs during SDB exposes the sufferer to intermittent hypoxia and hypercapnia, large swings in intrathoracic pressure, sympathetic activation and sleep fragmentation [3]. As a result, SDB is associated with cardiovascular, behavioural and neurocognitive morbidity, adversely affecting quality of life in both adults [4] and children [5, 6]. Despite significant advances in our understanding of this disorder and awareness of its significance in both adult and paediatric populations, our diagnostic and treatment approach is far from ideal. Diagnosis is reliant on overnight polysomnography (PSG), which is costly and has limited availability and there is a discrepancy between PSG-based indicators of severity, such as the apnoea hypopnoea index (AHI) or obstructive apnoea hypopnoea index (OAHI), clinical features and the likelihood of adverse outcomes [7, 8]. Furthermore, knowing which patients to treat and who is likely to benefit most from treatment remains a key clinical challenge. For example, in adults, most patients are encouraged to trial continuous positive airway pressure (CPAP) and in children adenotonsillectomy is considered the firstline treatment. However, a significant proportion of patients have residual OSA following these treatments due to various reasons, including poor adherence (in the case of CPAP) or the presence of other disease mechanisms not targeted through these treatments. Therefore, better disease characterisation and more targeted treatment stand to provide a more personalised and effective approach to resolution of SDB.
The personalised medicine approach is based on recognising that interactions between the genetic make-up of an individual and their environmental exposures, through various molecular mechanisms, result in disease or a disease subtype (endotype), eventually manifesting as a set of distinct clinical characteristics (phenotype) [9]. Objectively validated indicators that reflect a specific biological or 4
pathogenic process (biomarkers) can then be used to detect endotypes and phenotypes, as well as to identify treatable traits to guide management (Figure 1) [10]. Emerging literature in adult OSA has sought to identify and define these elements to improve the diagnostic and management accuracy of OSA, with the ultimate aim of improving patient outcomes. This review will summarise the adult literature on the phenotypes and endotypes of OSA and assess whether a similar approach may also be suitable to guide the development of new diagnostic and management approaches for paediatric SDB.
Figure 1: The conceptual elements of the personalised medicine approach. The genetic make-up or the genotype of an individual interacts with their environmental exposures to result in disease or a disease subtype (endotype). An endotype is a subset of a disease defined by a pathological mechanism or based on treatment response. This can then manifest as a set of distinct clinical characteristics through various clinical phenotypes. A biomarker is an objectively validated indicator of a biological or pathophysiological process which can be used to identify therapeutic targets and guide management. 5
Endotypes of adult OSA To date, there are at least 4 key endotypes identified to play a causal role in OSA pathogenesis. In order to have OSA, an individual must have some degree of anatomical compromise of their upper airway. Key factors that contribute towards this compromise are varied and include a combination of craniofacial features and obesity-related factors [11]. In addition to this anatomical endotype, it is now established that three other non-anatomical endotypes also play a key role in the pathogenesis of OSA, in at least a proportion of individuals [12]. These include (1) impairment in neuromuscular activation of the upper airway dilator muscles, (2) a low respiratory arousal threshold and (3) a hypersensitive (or unstable) ventilatory control system [13]. It has been suggested that it is a combination of anatomical and non-anatomical endotypes that result in OSA, with a high degree of individual variation. The presence of these endotypes varies among adults with OSA, even amongst patients with similar OSA severity [14]. Emerging evidence from a number of small physiological studies has demonstrated that unique combinations of these endotypes can predict which patients are more likely to respond to a number of alternative (i.e. non-CPAP) therapies. For example, patients with a less collapsible airway (i.e. more favourable upper airway anatomy) and a stable ventilatory control system are more likely than other patients with OSA to respond to upper airway surgery [15, 16] and oral appliance therapy [17, 18]. In contrast, patients with poor upper airway muscle activation are more likely to benefit from drugs that stimulate the upper airway dilator muscles [19, 20]. However, it is currently unclear whether these findings are reproducible, as most drug studies have only evaluated acute intervention effects after one-night of therapy. Furthermore, while these results seem promising, there are still a number of challenges before this approach could become part of mainstream clinical practice - a major hurdle being that the techniques to measure this physiology are rather complex. Nevertheless, it appears that having a detailed understanding of a patient’s pathophysiological
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endotype may allow clinicians to tailor treatment, in combination with the patient’s clinical phenotype.
Figure 2: Endotypes of adult OSA. A degree of anatomical compromise of the upper airway is necessary for the development of OSA. An individual with a less collapsible, stable upper airway is unlikely to develop OSA. Conversely, an individual with a highly collapsible airway has a high likelihood of developing OSA. The likelihood of developing OSA in an individual who has a mild anatomical predisposition or a ‘vulnerable’ upper airway is thought to depend on the presence or absence of three non-anatomical endotypes: poor upper airway muscle responsiveness, low arousal threshold and ventilatory control instability. OSA, Obstructive sleep apnoea Phenotypes of adult OSA OSA represents a diverse range of clinical manifestations and a number of clustering approaches have been used to identify discernible clinical phenotypes based on symptomology and comorbidities. Three different symptomology-based, OSA phenotypes or clusters have been described: (1) disturbed sleep, (2) minimally symptomatic, and (3) excessive daytime sleepiness [21-24]. Cluster one subjects had the highest probability of having insomnia-related symptoms, whereas cluster two subjects had the lowest probability of experiencing symptoms and were more likely to feel rested upon waking. Cluster three subjects had the highest probability of sleepiness-related symptoms and had a higher
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Epworth Sleepiness Score compared to clusters 1 and 2 [25]. While this clustering approach has good generalisability and shows promise in predicting response to treatment [23], further sub-classification into management-relevant clusters and validation in larger patient cohorts is likely to improve clinical utility. It has also been suggested that patient subgroups, for example older patients [26], female patients [27], non-obese patients [28] and patients with co-morbidities such as treatment-resistant arterial hypertension [29] likely represent different clinical phenotypes of OSA that might also require tailored treatment strategies. Although phenotypic clusters of adult OSA show promise as a pathway to personalised medicine, more studies are needed before this approach can be implemented into clinical practice. Another approach to phenotype patients with OSA has been to use the information included within the PSG. Notably, clinicians most often utilise PSG-based indicators such as the AHI to assess the severity of OSA and to guide management decisions. However, the AHI is often a poor predictor of the severity of symptoms or consequences of disease and reliance on the AHI-based clustering approach to guide treatment decisions and risk stratification can be problematic [30]. As a result, a number of ways to better utilise the PSG to identify alternative single metrics of OSA, as well as novel PSG metrics that can supplement the AHI have been suggested [31]. For example, the depth and duration of hypoxaemia [32] and duration of respiratory events [33] may be better candidates for a clustering approach based on disease burden. Furthermore, recent reports suggest that certain biomarkers could be used to assist with OSA risk stratification, identify individuals at risk of certain complications and to assess treatment response. For example, measurement of biomarkers such as plasma free fatty acids, glucose and cortisol could help identify individuals at risk for metabolic sequelae of OSA [34]. However, further validation of these biomarkers is required prior to application into clinical practice. In summary, significant attention has been focussed on unravelling the complexity of OSA to be able to identify phenotypic and endotypic traits and the interactions between them to identify potential 8
treatable traits. While these findings show promise in revolutionising the management approach for adults with OSA, there is a paucity of data examining the various phenotypes and endotypes of paediatric OSA.
Personalised medicine approach for paediatric OSA? Prior to discussing the potential for a personalised medicine approach to paediatric OSA, it is important to highlight the differences between adult and paediatric OSA (Table 1), which might impact the ability to translate findings from the adult literature. In summary, OSA in children tends to be less prevalent compared with adults, with most children found at the lower end of the SDB severity spectrum. The diagnostic threshold is also much lower in children compared to adults due to apnoeic events being less common in normal children and the first line treatment for paediatric OSA is adenotonsillectomy due to adenotonsillar hypertrophy being the primary airway limiting factor. Despite these differences, similarly to adult OSA, paediatric OSA is a complex heterogeneous disorder and the current diagnostic and management approach is not able to adequately recognise this complexity to optimally manage this condition in all children. Therefore, an approach based on recognising pathophysiological endotypes and clinical phenotypes warrants exploration.
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Table 1: Comparison of prevalence, clinical presentation and management of obstructive sleep apnoea in adults and children Epidemiology Prevalence Sex predominance
Aetiology Primary risk factor Clinical Features Typical presentation
Common associations
Diagnosis First-line investigation Classification of severity based on AHI/OAHI Management First-line Treatment
Adults
Children
9-36% [1] Male predominance, rates rises in women postmenopausally, such that rates are similar between postmenopausal women and men [11]
1-6% [2] Some studies report male predominance after puberty, while others report no difference in prevalence across all ages [35]
Obesity [11]
Adenotonsillar hypertrophy [36]
Daytime sleepiness, snoring, chocking, gasping during sleep, restless sleep, morning headaches, nocturia [37]
Snoring, mouth breathing, pauses in breathing, restless sleep, nocturnal sweating, nocturnal enuresis, hyperactive/aggressive/inattentive behaviour [38] Behaviour problems Impaired neurocognition Academic difficulty Elevated blood pressure Metabolic syndrome [38]
Hypertension Cardiovascular disease Cerebrovascular disease Metabolic syndrome Non-alcoholic fatty liver disease Chronic kidney disease [11] Home sleep apnoea testing or overnight laboratory-based PSG [37] Mild OSA: 5-15 events/h Moderate OSA: 15-30 events/h Severe OSA: >30 events/h [39]
Overnight laboratory-based PSG [36] Mild OSA: 1-≤5 events/h Moderate OSA: >5-≤10 events/h Severe OSA: >10 events/h [36]
CPAP [11]
Adenotonsillectomy [36]
Table legend: PSG, Polysomnography; AHI, Apnoea-hyponoea index; OAHI, Obstructive apnoea-hypopnoea index; OSA, Obstructive sleep apnoea; CPAP, continuous positive airway pressure
Endotypes of paediatric OSA Akin to adult OSA, paediatric OSA in typically developing children is predominantly driven by poor or compromised upper airway anatomy. The principal contributor to this anatomical impairment is the enlargement of adenoids and tonsils. In support of this, the peak incidence of OSA coincides with the pre-school age when the size of the adenoids and tonsils is largest in relation to the underlying upper 10
airway skeletal structure [40]. In addition, the size of the adenoids, tonsils and soft palate is larger in children with OSA compared to controls when measured by magnetic resonance imaging [MRI] [41] and removing this anatomical impairment via adenotonsillectomy leads to resolution of OSA in up to 79% of children [42]. However, depending on the population studied and criteria used, complete resolution of OSA (AHI<1 event/hour) following adenotonsillectomy has been reported to be as low as 27.2% [43]. It is important to note that most of these studies have been conducted in typically developing children. Craniofacial dysmorphology involving retro-positioning or hypoplasia of the mandible or maxilla may also pose an additional risk for the development of OSA, as these anomalies decrease the size of the upper airway. However, in the absence of obvious syndromic anomalies (e.g. Pierre Robin sequence, Apert syndrome, Treacher Collins syndrome), the role of subtle craniofacial factors in predisposing towards SDB in children is less clear [44]. Notably, the presence and severity of OSA is clearly not explained by anatomical factors alone. OSA is not seen in every child with adenotonsillar hypertrophy and only a modest positive correlation between adenotonsillar size and OSA severity have been reported [45, 46], with some reports finding no association [47]. Such evidence suggests that, similarly to adults, there may be other nonanatomical endotypes that contribute to paediatric OSA. The available evidence suggests that both altered neuromuscular control of the upper airway dilator muscles and abnormal ventilatory control are likely implicated in the pathogenesis of paediatric OSA (Table 2). It is often noted that children snore less and have fewer episodes of apnoea compared to adults, despite having a narrower airway. This has been attributed to children having an airway that is more resistant to collapse, potentially due to the upper airway dilator muscles being able to maintain airway patency, despite a lower airway circumference [48]. It has been reported that children with OSA show impaired upper airway dilator muscle activation in response to respiratory stimuli (i.e. hypercapnia and acute negative pressure) compared to children without OSA, and that these responses show a trend towards normalisation following adenotonsillectomy [49]. Furthermore, the
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majority of children with OSA have REM-predominant OSA, a sleep state characterised by generalised muscle atonia, with an increased vulnerability to SDB [50, 51]. In children, it has been reported that the activity of the genioglossus (the most widely studied pharyngeal dilator muscle) is lowest and most variable in REM [52]. Reductions in genioglossus activity are coincident with apnoeic and hypopnoeic events during REM sleep in children [52] and a significant correlation between genioglossus activity and OSA severity has also been reported across all sleep stages [52]. Early reports showed that ventilatory responses to hypoxia and hypercapnia are not different between children with and without OSA during both wakefulness and sleep [53, 54]. Consistent with these reports, recent studies that measured an individual’s loop gain to assess the stability/sensitivity of the ventilatory control system have found no difference in overall loop gain between children with and without OSA [55-57]. However, despite no difference in overall loop gain between children with and without OSA, abnormalities in components that constitute loop gain have been found. More specifically, it has been reported that children with OSA have a lower controller gain (sensitivity of the chemoreceptors to fluctuations in blood gases) and a higher plant gain (the efficiency of a given level of ventilation to cause changes in blood gases) compared to children without OSA in certain subpopulations (e.g. children born preterm, overweight adolescents) [55-59]. These findings indicate that abnormal ventilatory control could be a possible pathophysiological endotype in at least a proportion of children. Further studies are needed to characterise the role of loop gain in paediatric OSA, particularly to assess whether overall loop gain becomes a key determinant of apnoea severity when stratified by the degree of upper airway anatomical impairment, as has been suggested in the adult literature [12, 60]. Furthermore, whether a low respiratory arousal threshold that increases the likelihood of cyclical obstructive events, contributes to the pathogenesis of OSA in children is less clear. The observation that only ~50% of obstructive apnoeas in children are associated with a visible EEG arousal, suggests that children with OSA may actually have a higher arousal threshold than adults [54]. In addition, it
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has also been reported that children with OSA have a higher arousal threshold during sleep in response to inspiratory resistive loading [61] and hypercapnia [54] compared to children without OSA – suggesting that the elevated threshold for arousal may occur as a consequence of the disorder. Thus the available evidence, although limited, suggests that a low arousal threshold may be less of a contributor towards OSA in children. Taken together, the limited available evidence highlights that similar to adults, the pathophysiological mechanisms that contribute to paediatric OSA are likely to be complex. Despite our increased understanding of the endotypes causing OSA, a major limitation that prevents measuring them in clinical practice is the lack of validated non-invasive tools to characterise these traits in individual patients. However, this is an active area of research and some promising non-invasive techniques have recently been identified and validated in adults [62]. In the paediatric setting, further research is needed to develop clinically applicable techniques to measure these traits, which will then allow us to measure them in large patient cohorts to definitely quantify the heterogeneity of OSA as well as their utility in predicting treatment outcomes.
Phenotypes of paediatric OSA The heterogeneity of paediatric SDB suggests the presence of many clinical phenotypes. The spectrum of SDB in children ranges from primary snoring (snoring not associated with gas exchange abnormalities or sleep disruption) to OSA [63]. It has been established that clinical history and examination alone are insufficient for the diagnosis and classification of SDB severity in children [38]. However, clustering approaches based on clinical presentation to identify distinct clinical phenotypes of paediatric OSA have started to emerge. A recent report identified three distinct clusters based on symptomology and co-morbidities, similar to the adult literature [64]. These were described as (1) “nocturnal snoring and daytime sleepiness group” (2) “hyperactivity group” and a (3) “minimally symptomatic group” [64]. Children in cluster one were more likely to have snoring, heavy breathing 13
and difficulty waking compared to clusters two and three. Children in cluster 2 demonstrated behavioural problems such as increased hyperactivity and excessive movements, while around 20% of children in cluster three reported no habitual snoring (snoring > 3 nights/week) and were more likely to have mild symptoms [64]. While treatment response was not assessed in this study, these initial findings highlight the potential for a classification system based on clinical presentation in paediatric OSA. Furthermore, certain sub-populations of children have been identified to have distinct clinical phenotypes. It has been suggested that adolescents with OSA have a set of clinical features (i.e. prominent daytime symptoms (e.g. sleepiness)), which is more closely aligned with features seen in adults with OSA, than in younger children. Reports also indicate that this age group is likely to have a distinct pathophysiological endotype, with non-anatomical factors potentially playing important roles in the development of OSA [57, 59]. Obesity is also more prevalent in the adolescent age group and is becoming an important risk factor for the development of paediatric OSA, particularly in older children [65]. Children who are overweight or obese are less likely to respond to adenotonsillectomy [66] and are at a greater risk of cardiovascular and metabolic morbidity [67, 68]. As a result, it has been proposed that children with OSA who are overweight or obese might represent a separate disease entity with a distinct clinical phenotype and pathophysiological endotype, and are likely to benefit from a tailored management approach [69]. Similar to adult OSA, clinicians often rely on PSG-based indices such as the OAHI to categorise disease severity and guide treatment decisions in children. However, while PSG is currently the most comprehensive tool available for the assessment of SDB severity, PSG-based indices are weakly correlated with clinical features and are poor predictors of disease morbidity and treatment response [7]. For example, children with primary snoring, despite exhibiting less than 1 obstructive apnoea or hypopnoea per hour of sleep on PSG, have cardiovascular [70], cognitive and behavioural sequelae [71] similar to children with OSA. As a result, researchers have started to explore the role of
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biomarkers in paediatric OSA. Promising findings have been reported for C-reactive protein (CRP), which may have the ability to discriminate children with OSA at increased risk of cardiovascular and neurocognitive sequelae [72, 73]. Urinary catecholamines have also shown potential as a screening tool for identifying those at risk of cognitive morbidity in children OSA [74]. A number of other biomarkers (e.g. Andropin, Monocyte Chemoattractant Protein-1 (MCP-1)) have been evaluated and with further validation these could be used for risk stratification and to assist in the implementation of targeted therapeutic interventions [75].
Summary and Conclusions It is now evident that OSA is a heterogeneous disorder with multiple clinical phenotypes and complex aetiology. Significant advances have been made in our understanding of this multifaceted condition, particularly in adults, highlighting the importance of recognising the need to shift our thinking from a traditional one-size fits-all approach to a more individualised, targeted approach to the diagnosis and management of OSA. Paediatric OSA also shows a similar pattern of heterogeneity to adult OSA and better characterising this heterogeneity should allow the development of an improved diagnostic and treatment paradigm in this population.
Directions for future research Improving our understanding of OSA phenotypes, endotypes and the interactions between them will open new avenues for personalised treatment. The field of adult sleep medicine is already making significant advances in our understanding of adult OSA over the last decade. The heterogeneity of paediatric OSA suggests that careful characterisation of the different clinical phenotypes and pathophysiological endotypes is likely to be useful in improving patient outcomes. Translating these findings into clinical practice will require identification of patient phenotypes with clinical relevance
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and developing validated and reproducible tools for the measurement of endotypes that can be scaled to clinical settings. Linking clinical phenotypes and pathophysiological endotypes with underlying molecular mechanisms and biological pathways may assist in the identification of novel therapeutic targets as well as identify patients at greater risk of long term morbidity. This will allow clinicians provide more tailored care to patients, ultimately improving patient outcomes.
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Table 2: Studies that have evaluated non-anatomical traits implicated in the pathophysiological of paediatric OSA Trait Ventilatory control
Study Marcus et al. 1994 [53]
n 39
Ventilatory control/arousal response
Marcus et al. 1998 [54]
25
Ventilatory control
Yuan et al. 2012[76]
86
Ventilatory control
Nava-Guerra et al. 2016[57]
24
Ventilatory control Ventilatory control
Marcus et al. 2017 [59]
79
Domany et al. 2018 [56]
92
Ventilatory control
Amin et al. 2019 [55]
99
Ventilatory control
He et al. 2019 [58]
134
Upper airway muscle responsiveness
Katz et al. 2004[52]
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Age range
Population
Mean age of 8 years
Otherwise healthy children
Mean age of 8 years
Otherwise healthy children
Mean age of 14 years
Obese adolescents
13-21 years Mean age of 14 years 6 months to 11 years
Overweight and obese adolescents Obese adolescents Pre-term and term born children
7-13 years
Otherwise healthy children
5-18 years
Children with persistent asthma
Mean age of 10 years
Otherwise healthy children
Key findings Children with OSA have normal ventilatory responses to hypercapnia and hypoxia compared to children without OSA during wakefulness No differences in ventilatory responses to hypoxia and hypercapnia between children with and without OSA. Children with OSA had a blunted arousal response to hypercapnia Hypercapnic ventilatory response is increased in obese adolescents during wakefulness. Obese adolescents with OSA have a blunted ventilatory response to CO2 during sleep OSA group had a higher plant gain and lower controller gain compared to non-OSA group. No difference in loop gain between groups Reduced hypercapnic ventilatory responses during sleep in the OSA group A decreased controller gain, an increased plant gain and decreased cardiorespiratory coupling is associated with increased risk of OSA in pre-term born children Children with OSA had a higher plant gain and lower controller gain but no difference in overall loop gain compared to non-OSA children at baseline Higher plant gain and lower controller gain in children with OSA and positive correlation between plant gain and OSA severity Children with OSA displayed increased genioglossus EMG activity compared to controls across all sleep states and the application of CPAP led to a decrease in EMG activity in children with OSA
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Upper airway muscle responsiveness/ arousal response Arousal response
Marcus et al. 1999 [61]
18
Moreira et al. 2005 [77]
41
Upper airway sensory function
Huang et al. 2008 [78]
21
Upper airway sensory function
Tapia et al. 2010 [79]
22
Upper airway sensory function
Huang et al. 2013 [80]
48
Upper airway sensory function
Tapia et al. 2015 [81]
47
Upper airway sensory function
Tapia et al. 2016 [82]
61
Mean age of 8 years
Otherwise healthy children
2-10 years
Otherwise healthy children
5-12 years
Otherwise healthy children
6-16 years
Otherwise healthy children
6-16 years
Otherwise healthy children
6-16 years
Otherwise healthy children
Children with OSA have a higher arousal response to inspiratory resistance loading compared to children without OSA No difference in arousal response to moderate acoustic stimulation between OSA children and controls Children with OSA have decreased evoked K-complex production in stage 2 and slow wave sleep (SWS) and reduced respiratory-related evoked potentials (RREPs) in SWS compared to children without OSA Children with OSA had impaired two-point discrimination in the anterior tongue and hard palate compared to children without OSA Children with OSA have persistent irreversible (with treatment) respiratory afferent cortical processing deficits during sleep compared to children without OSA Children with OSA have partial delay of respiratory afferent cortical processing during wakefulness that improves after treatment Children with OSA and controls have similar palatal vibration threshold detection
Otherwise healthy children Table legend: OSA, Obstructive sleep apnoea; CO2, Carbon dioxide; EMG, Electromyogram; CPAP, Continuous positive airway pressure; SWS, Slow wave sleep. 6-16 years
18
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S1526-0542(20)30018-X https://doi.org/10.1016/j.prrv.2020.01.002 YPRRV 1361
To appear in:
Paediatric Respiratory Reviews
Received Date: Revised Date: Accepted Date:
11 December 2019 21 January 2020 31 January 2020
Please cite this article as: L.S. Siriwardhana, G.M. Nixon, R.S.C. Horne, B.A. Edwards, Journey towards a personalised medicine approach for OSA: Can a similar approach to adult OSA be applied to paediatric OSA?, Paediatric Respiratory Reviews (2020), doi: https://doi.org/10.1016/j.prrv.2020.01.002
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TITLE PAGE Article title: Journey towards a personalised medicine approach for OSA: Can a similar approach to adult OSA be applied to paediatric OSA?
Authors: Leon S Siriwardhana1, Gillian M Nixon1, 2, Rosemary SC Horne1*, Bradley A Edwards3, 4*. 1The
Ritchie Centre, Hudson Institute of Medical Research and Department of Paediatrics, Monash University, Melbourne, Australia. 2Melbourne
Children’s Sleep Centre, Monash Children’s Hospital, Melbourne, Australia.
3Sleep
and Circadian Medicine Laboratory, Department of Physiology, Monash University, Melbourne, Australia. 4School
of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia. *both authors jointly supervised this work
Corresponding author: Dr Bradley A Edwards Address: 264 Ferntree Gully Road, Notting Hill, Victoria 3168, Australia Office. +613 9905 0187 Fax. +613 9905 3948 Email: [email protected]
Declarations of interest: none This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
1
Abstract The concept of personalised medicine is likely to revolutionise the treatment of adult obstructive sleep apnoea as a result of recent advances in the understanding of disease heterogeneity by identifying clinical phenotypes, pathophysiological endotypes, biomarkers and treatable traits. Children with the condition show a similar level of heterogeneity and paediatric obstructive sleep apnoea would also benefit from a more targeted approach to diagnosis and management. This review aims to summarise the adult literature on the phenotypes and endotypes of obstructive sleep apnoea and assess whether a similar approach may also be suitable to guide the development of new diagnostic and management approaches for paediatric obstructive sleep apnoea.
Keywords Sleep; Sleep disordered breathing; obstructive sleep apnoea; phenotyping; personalised medicine
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Educational Aims The reader will be able to appreciate that:
Obstructive sleep apnoea is a complex heterogeneous condition with dynamic and variable disease pathways, disease expression and sequelae.
A number of clinical phenotypes and pathophysiological endotypes have been identified in adult obstructive sleep apnoea.
Emerging evidence in paediatric obstructive sleep apnoea also indicates the presence of a number of phenotypes and endotypes.
Further research is needed to more comprehensively characterise the heterogeneity of paediatric obstructive sleep apnoea and identify factors that could lead to more targeted treatment.
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Introduction Obstructive sleep disordered breathing (SDB) is prevalent across the lifespan, from young children to adults. Obstructive sleep apnoea (OSA) is at the severe end of the SDB spectrum, with a prevalence of 9-36% in the adult population [1] and 1-6% in the paediatric population [2]. The repetitive complete or partial collapse of the pharyngeal airway that occurs during SDB exposes the sufferer to intermittent hypoxia and hypercapnia, large swings in intrathoracic pressure, sympathetic activation and sleep fragmentation [3]. As a result, SDB is associated with cardiovascular, behavioural and neurocognitive morbidity, adversely affecting quality of life in both adults [4] and children [5, 6]. Despite significant advances in our understanding of this disorder and awareness of its significance in both adult and paediatric populations, our diagnostic and treatment approach is far from ideal. Diagnosis is reliant on overnight polysomnography (PSG), which is costly and has limited availability and there is a discrepancy between PSG-based indicators of severity, such as the apnoea hypopnoea index (AHI) or obstructive apnoea hypopnoea index (OAHI), clinical features and the likelihood of adverse outcomes [7, 8]. Furthermore, knowing which patients to treat and who is likely to benefit most from treatment remains a key clinical challenge. For example, in adults, most patients are encouraged to trial continuous positive airway pressure (CPAP) and in children adenotonsillectomy is considered the firstline treatment. However, a significant proportion of patients have residual OSA following these treatments due to various reasons, including poor adherence (in the case of CPAP) or the presence of other disease mechanisms not targeted through these treatments. Therefore, better disease characterisation and more targeted treatment stand to provide a more personalised and effective approach to resolution of SDB.
The personalised medicine approach is based on recognising that interactions between the genetic make-up of an individual and their environmental exposures, through various molecular mechanisms, result in disease or a disease subtype (endotype), eventually manifesting as a set of distinct clinical characteristics (phenotype) [9]. Objectively validated indicators that reflect a specific biological or 4
pathogenic process (biomarkers) can then be used to detect endotypes and phenotypes, as well as to identify treatable traits to guide management (Figure 1) [10]. Emerging literature in adult OSA has sought to identify and define these elements to improve the diagnostic and management accuracy of OSA, with the ultimate aim of improving patient outcomes. This review will summarise the adult literature on the phenotypes and endotypes of OSA and assess whether a similar approach may also be suitable to guide the development of new diagnostic and management approaches for paediatric SDB.
Figure 1: The conceptual elements of the personalised medicine approach. The genetic make-up or the genotype of an individual interacts with their environmental exposures to result in disease or a disease subtype (endotype). An endotype is a subset of a disease defined by a pathological mechanism or based on treatment response. This can then manifest as a set of distinct clinical characteristics through various clinical phenotypes. A biomarker is an objectively validated indicator of a biological or pathophysiological process which can be used to identify therapeutic targets and guide management. 5
Endotypes of adult OSA To date, there are at least 4 key endotypes identified to play a causal role in OSA pathogenesis. In order to have OSA, an individual must have some degree of anatomical compromise of their upper airway. Key factors that contribute towards this compromise are varied and include a combination of craniofacial features and obesity-related factors [11]. In addition to this anatomical endotype, it is now established that three other non-anatomical endotypes also play a key role in the pathogenesis of OSA, in at least a proportion of individuals [12]. These include (1) impairment in neuromuscular activation of the upper airway dilator muscles, (2) a low respiratory arousal threshold and (3) a hypersensitive (or unstable) ventilatory control system [13]. It has been suggested that it is a combination of anatomical and non-anatomical endotypes that result in OSA, with a high degree of individual variation. The presence of these endotypes varies among adults with OSA, even amongst patients with similar OSA severity [14]. Emerging evidence from a number of small physiological studies has demonstrated that unique combinations of these endotypes can predict which patients are more likely to respond to a number of alternative (i.e. non-CPAP) therapies. For example, patients with a less collapsible airway (i.e. more favourable upper airway anatomy) and a stable ventilatory control system are more likely than other patients with OSA to respond to upper airway surgery [15, 16] and oral appliance therapy [17, 18]. In contrast, patients with poor upper airway muscle activation are more likely to benefit from drugs that stimulate the upper airway dilator muscles [19, 20]. However, it is currently unclear whether these findings are reproducible, as most drug studies have only evaluated acute intervention effects after one-night of therapy. Furthermore, while these results seem promising, there are still a number of challenges before this approach could become part of mainstream clinical practice - a major hurdle being that the techniques to measure this physiology are rather complex. Nevertheless, it appears that having a detailed understanding of a patient’s pathophysiological
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endotype may allow clinicians to tailor treatment, in combination with the patient’s clinical phenotype.
Figure 2: Endotypes of adult OSA. A degree of anatomical compromise of the upper airway is necessary for the development of OSA. An individual with a less collapsible, stable upper airway is unlikely to develop OSA. Conversely, an individual with a highly collapsible airway has a high likelihood of developing OSA. The likelihood of developing OSA in an individual who has a mild anatomical predisposition or a ‘vulnerable’ upper airway is thought to depend on the presence or absence of three non-anatomical endotypes: poor upper airway muscle responsiveness, low arousal threshold and ventilatory control instability. OSA, Obstructive sleep apnoea Phenotypes of adult OSA OSA represents a diverse range of clinical manifestations and a number of clustering approaches have been used to identify discernible clinical phenotypes based on symptomology and comorbidities. Three different symptomology-based, OSA phenotypes or clusters have been described: (1) disturbed sleep, (2) minimally symptomatic, and (3) excessive daytime sleepiness [21-24]. Cluster one subjects had the highest probability of having insomnia-related symptoms, whereas cluster two subjects had the lowest probability of experiencing symptoms and were more likely to feel rested upon waking. Cluster three subjects had the highest probability of sleepiness-related symptoms and had a higher
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Epworth Sleepiness Score compared to clusters 1 and 2 [25]. While this clustering approach has good generalisability and shows promise in predicting response to treatment [23], further sub-classification into management-relevant clusters and validation in larger patient cohorts is likely to improve clinical utility. It has also been suggested that patient subgroups, for example older patients [26], female patients [27], non-obese patients [28] and patients with co-morbidities such as treatment-resistant arterial hypertension [29] likely represent different clinical phenotypes of OSA that might also require tailored treatment strategies. Although phenotypic clusters of adult OSA show promise as a pathway to personalised medicine, more studies are needed before this approach can be implemented into clinical practice. Another approach to phenotype patients with OSA has been to use the information included within the PSG. Notably, clinicians most often utilise PSG-based indicators such as the AHI to assess the severity of OSA and to guide management decisions. However, the AHI is often a poor predictor of the severity of symptoms or consequences of disease and reliance on the AHI-based clustering approach to guide treatment decisions and risk stratification can be problematic [30]. As a result, a number of ways to better utilise the PSG to identify alternative single metrics of OSA, as well as novel PSG metrics that can supplement the AHI have been suggested [31]. For example, the depth and duration of hypoxaemia [32] and duration of respiratory events [33] may be better candidates for a clustering approach based on disease burden. Furthermore, recent reports suggest that certain biomarkers could be used to assist with OSA risk stratification, identify individuals at risk of certain complications and to assess treatment response. For example, measurement of biomarkers such as plasma free fatty acids, glucose and cortisol could help identify individuals at risk for metabolic sequelae of OSA [34]. However, further validation of these biomarkers is required prior to application into clinical practice. In summary, significant attention has been focussed on unravelling the complexity of OSA to be able to identify phenotypic and endotypic traits and the interactions between them to identify potential 8
treatable traits. While these findings show promise in revolutionising the management approach for adults with OSA, there is a paucity of data examining the various phenotypes and endotypes of paediatric OSA.
Personalised medicine approach for paediatric OSA? Prior to discussing the potential for a personalised medicine approach to paediatric OSA, it is important to highlight the differences between adult and paediatric OSA (Table 1), which might impact the ability to translate findings from the adult literature. In summary, OSA in children tends to be less prevalent compared with adults, with most children found at the lower end of the SDB severity spectrum. The diagnostic threshold is also much lower in children compared to adults due to apnoeic events being less common in normal children and the first line treatment for paediatric OSA is adenotonsillectomy due to adenotonsillar hypertrophy being the primary airway limiting factor. Despite these differences, similarly to adult OSA, paediatric OSA is a complex heterogeneous disorder and the current diagnostic and management approach is not able to adequately recognise this complexity to optimally manage this condition in all children. Therefore, an approach based on recognising pathophysiological endotypes and clinical phenotypes warrants exploration.
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Table 1: Comparison of prevalence, clinical presentation and management of obstructive sleep apnoea in adults and children Epidemiology Prevalence Sex predominance
Aetiology Primary risk factor Clinical Features Typical presentation
Common associations
Diagnosis First-line investigation Classification of severity based on AHI/OAHI Management First-line Treatment
Adults
Children
9-36% [1] Male predominance, rates rises in women postmenopausally, such that rates are similar between postmenopausal women and men [11]
1-6% [2] Some studies report male predominance after puberty, while others report no difference in prevalence across all ages [35]
Obesity [11]
Adenotonsillar hypertrophy [36]
Daytime sleepiness, snoring, chocking, gasping during sleep, restless sleep, morning headaches, nocturia [37]
Snoring, mouth breathing, pauses in breathing, restless sleep, nocturnal sweating, nocturnal enuresis, hyperactive/aggressive/inattentive behaviour [38] Behaviour problems Impaired neurocognition Academic difficulty Elevated blood pressure Metabolic syndrome [38]
Hypertension Cardiovascular disease Cerebrovascular disease Metabolic syndrome Non-alcoholic fatty liver disease Chronic kidney disease [11] Home sleep apnoea testing or overnight laboratory-based PSG [37] Mild OSA: 5-15 events/h Moderate OSA: 15-30 events/h Severe OSA: >30 events/h [39]
Overnight laboratory-based PSG [36] Mild OSA: 1-≤5 events/h Moderate OSA: >5-≤10 events/h Severe OSA: >10 events/h [36]
CPAP [11]
Adenotonsillectomy [36]
Table legend: PSG, Polysomnography; AHI, Apnoea-hyponoea index; OAHI, Obstructive apnoea-hypopnoea index; OSA, Obstructive sleep apnoea; CPAP, continuous positive airway pressure
Endotypes of paediatric OSA Akin to adult OSA, paediatric OSA in typically developing children is predominantly driven by poor or compromised upper airway anatomy. The principal contributor to this anatomical impairment is the enlargement of adenoids and tonsils. In support of this, the peak incidence of OSA coincides with the pre-school age when the size of the adenoids and tonsils is largest in relation to the underlying upper 10
airway skeletal structure [40]. In addition, the size of the adenoids, tonsils and soft palate is larger in children with OSA compared to controls when measured by magnetic resonance imaging [MRI] [41] and removing this anatomical impairment via adenotonsillectomy leads to resolution of OSA in up to 79% of children [42]. However, depending on the population studied and criteria used, complete resolution of OSA (AHI<1 event/hour) following adenotonsillectomy has been reported to be as low as 27.2% [43]. It is important to note that most of these studies have been conducted in typically developing children. Craniofacial dysmorphology involving retro-positioning or hypoplasia of the mandible or maxilla may also pose an additional risk for the development of OSA, as these anomalies decrease the size of the upper airway. However, in the absence of obvious syndromic anomalies (e.g. Pierre Robin sequence, Apert syndrome, Treacher Collins syndrome), the role of subtle craniofacial factors in predisposing towards SDB in children is less clear [44]. Notably, the presence and severity of OSA is clearly not explained by anatomical factors alone. OSA is not seen in every child with adenotonsillar hypertrophy and only a modest positive correlation between adenotonsillar size and OSA severity have been reported [45, 46], with some reports finding no association [47]. Such evidence suggests that, similarly to adults, there may be other nonanatomical endotypes that contribute to paediatric OSA. The available evidence suggests that both altered neuromuscular control of the upper airway dilator muscles and abnormal ventilatory control are likely implicated in the pathogenesis of paediatric OSA (Table 2). It is often noted that children snore less and have fewer episodes of apnoea compared to adults, despite having a narrower airway. This has been attributed to children having an airway that is more resistant to collapse, potentially due to the upper airway dilator muscles being able to maintain airway patency, despite a lower airway circumference [48]. It has been reported that children with OSA show impaired upper airway dilator muscle activation in response to respiratory stimuli (i.e. hypercapnia and acute negative pressure) compared to children without OSA, and that these responses show a trend towards normalisation following adenotonsillectomy [49]. Furthermore, the
11
majority of children with OSA have REM-predominant OSA, a sleep state characterised by generalised muscle atonia, with an increased vulnerability to SDB [50, 51]. In children, it has been reported that the activity of the genioglossus (the most widely studied pharyngeal dilator muscle) is lowest and most variable in REM [52]. Reductions in genioglossus activity are coincident with apnoeic and hypopnoeic events during REM sleep in children [52] and a significant correlation between genioglossus activity and OSA severity has also been reported across all sleep stages [52]. Early reports showed that ventilatory responses to hypoxia and hypercapnia are not different between children with and without OSA during both wakefulness and sleep [53, 54]. Consistent with these reports, recent studies that measured an individual’s loop gain to assess the stability/sensitivity of the ventilatory control system have found no difference in overall loop gain between children with and without OSA [55-57]. However, despite no difference in overall loop gain between children with and without OSA, abnormalities in components that constitute loop gain have been found. More specifically, it has been reported that children with OSA have a lower controller gain (sensitivity of the chemoreceptors to fluctuations in blood gases) and a higher plant gain (the efficiency of a given level of ventilation to cause changes in blood gases) compared to children without OSA in certain subpopulations (e.g. children born preterm, overweight adolescents) [55-59]. These findings indicate that abnormal ventilatory control could be a possible pathophysiological endotype in at least a proportion of children. Further studies are needed to characterise the role of loop gain in paediatric OSA, particularly to assess whether overall loop gain becomes a key determinant of apnoea severity when stratified by the degree of upper airway anatomical impairment, as has been suggested in the adult literature [12, 60]. Furthermore, whether a low respiratory arousal threshold that increases the likelihood of cyclical obstructive events, contributes to the pathogenesis of OSA in children is less clear. The observation that only ~50% of obstructive apnoeas in children are associated with a visible EEG arousal, suggests that children with OSA may actually have a higher arousal threshold than adults [54]. In addition, it
12
has also been reported that children with OSA have a higher arousal threshold during sleep in response to inspiratory resistive loading [61] and hypercapnia [54] compared to children without OSA – suggesting that the elevated threshold for arousal may occur as a consequence of the disorder. Thus the available evidence, although limited, suggests that a low arousal threshold may be less of a contributor towards OSA in children. Taken together, the limited available evidence highlights that similar to adults, the pathophysiological mechanisms that contribute to paediatric OSA are likely to be complex. Despite our increased understanding of the endotypes causing OSA, a major limitation that prevents measuring them in clinical practice is the lack of validated non-invasive tools to characterise these traits in individual patients. However, this is an active area of research and some promising non-invasive techniques have recently been identified and validated in adults [62]. In the paediatric setting, further research is needed to develop clinically applicable techniques to measure these traits, which will then allow us to measure them in large patient cohorts to definitely quantify the heterogeneity of OSA as well as their utility in predicting treatment outcomes.
Phenotypes of paediatric OSA The heterogeneity of paediatric SDB suggests the presence of many clinical phenotypes. The spectrum of SDB in children ranges from primary snoring (snoring not associated with gas exchange abnormalities or sleep disruption) to OSA [63]. It has been established that clinical history and examination alone are insufficient for the diagnosis and classification of SDB severity in children [38]. However, clustering approaches based on clinical presentation to identify distinct clinical phenotypes of paediatric OSA have started to emerge. A recent report identified three distinct clusters based on symptomology and co-morbidities, similar to the adult literature [64]. These were described as (1) “nocturnal snoring and daytime sleepiness group” (2) “hyperactivity group” and a (3) “minimally symptomatic group” [64]. Children in cluster one were more likely to have snoring, heavy breathing 13
and difficulty waking compared to clusters two and three. Children in cluster 2 demonstrated behavioural problems such as increased hyperactivity and excessive movements, while around 20% of children in cluster three reported no habitual snoring (snoring > 3 nights/week) and were more likely to have mild symptoms [64]. While treatment response was not assessed in this study, these initial findings highlight the potential for a classification system based on clinical presentation in paediatric OSA. Furthermore, certain sub-populations of children have been identified to have distinct clinical phenotypes. It has been suggested that adolescents with OSA have a set of clinical features (i.e. prominent daytime symptoms (e.g. sleepiness)), which is more closely aligned with features seen in adults with OSA, than in younger children. Reports also indicate that this age group is likely to have a distinct pathophysiological endotype, with non-anatomical factors potentially playing important roles in the development of OSA [57, 59]. Obesity is also more prevalent in the adolescent age group and is becoming an important risk factor for the development of paediatric OSA, particularly in older children [65]. Children who are overweight or obese are less likely to respond to adenotonsillectomy [66] and are at a greater risk of cardiovascular and metabolic morbidity [67, 68]. As a result, it has been proposed that children with OSA who are overweight or obese might represent a separate disease entity with a distinct clinical phenotype and pathophysiological endotype, and are likely to benefit from a tailored management approach [69]. Similar to adult OSA, clinicians often rely on PSG-based indices such as the OAHI to categorise disease severity and guide treatment decisions in children. However, while PSG is currently the most comprehensive tool available for the assessment of SDB severity, PSG-based indices are weakly correlated with clinical features and are poor predictors of disease morbidity and treatment response [7]. For example, children with primary snoring, despite exhibiting less than 1 obstructive apnoea or hypopnoea per hour of sleep on PSG, have cardiovascular [70], cognitive and behavioural sequelae [71] similar to children with OSA. As a result, researchers have started to explore the role of
14
biomarkers in paediatric OSA. Promising findings have been reported for C-reactive protein (CRP), which may have the ability to discriminate children with OSA at increased risk of cardiovascular and neurocognitive sequelae [72, 73]. Urinary catecholamines have also shown potential as a screening tool for identifying those at risk of cognitive morbidity in children OSA [74]. A number of other biomarkers (e.g. Andropin, Monocyte Chemoattractant Protein-1 (MCP-1)) have been evaluated and with further validation these could be used for risk stratification and to assist in the implementation of targeted therapeutic interventions [75].
Summary and Conclusions It is now evident that OSA is a heterogeneous disorder with multiple clinical phenotypes and complex aetiology. Significant advances have been made in our understanding of this multifaceted condition, particularly in adults, highlighting the importance of recognising the need to shift our thinking from a traditional one-size fits-all approach to a more individualised, targeted approach to the diagnosis and management of OSA. Paediatric OSA also shows a similar pattern of heterogeneity to adult OSA and better characterising this heterogeneity should allow the development of an improved diagnostic and treatment paradigm in this population.
Directions for future research Improving our understanding of OSA phenotypes, endotypes and the interactions between them will open new avenues for personalised treatment. The field of adult sleep medicine is already making significant advances in our understanding of adult OSA over the last decade. The heterogeneity of paediatric OSA suggests that careful characterisation of the different clinical phenotypes and pathophysiological endotypes is likely to be useful in improving patient outcomes. Translating these findings into clinical practice will require identification of patient phenotypes with clinical relevance
15
and developing validated and reproducible tools for the measurement of endotypes that can be scaled to clinical settings. Linking clinical phenotypes and pathophysiological endotypes with underlying molecular mechanisms and biological pathways may assist in the identification of novel therapeutic targets as well as identify patients at greater risk of long term morbidity. This will allow clinicians provide more tailored care to patients, ultimately improving patient outcomes.
16
Table 2: Studies that have evaluated non-anatomical traits implicated in the pathophysiological of paediatric OSA Trait Ventilatory control
Study Marcus et al. 1994 [53]
n 39
Ventilatory control/arousal response
Marcus et al. 1998 [54]
25
Ventilatory control
Yuan et al. 2012[76]
86
Ventilatory control
Nava-Guerra et al. 2016[57]
24
Ventilatory control Ventilatory control
Marcus et al. 2017 [59]
79
Domany et al. 2018 [56]
92
Ventilatory control
Amin et al. 2019 [55]
99
Ventilatory control
He et al. 2019 [58]
134
Upper airway muscle responsiveness
Katz et al. 2004[52]
16
Age range
Population
Mean age of 8 years
Otherwise healthy children
Mean age of 8 years
Otherwise healthy children
Mean age of 14 years
Obese adolescents
13-21 years Mean age of 14 years 6 months to 11 years
Overweight and obese adolescents Obese adolescents Pre-term and term born children
7-13 years
Otherwise healthy children
5-18 years
Children with persistent asthma
Mean age of 10 years
Otherwise healthy children
Key findings Children with OSA have normal ventilatory responses to hypercapnia and hypoxia compared to children without OSA during wakefulness No differences in ventilatory responses to hypoxia and hypercapnia between children with and without OSA. Children with OSA had a blunted arousal response to hypercapnia Hypercapnic ventilatory response is increased in obese adolescents during wakefulness. Obese adolescents with OSA have a blunted ventilatory response to CO2 during sleep OSA group had a higher plant gain and lower controller gain compared to non-OSA group. No difference in loop gain between groups Reduced hypercapnic ventilatory responses during sleep in the OSA group A decreased controller gain, an increased plant gain and decreased cardiorespiratory coupling is associated with increased risk of OSA in pre-term born children Children with OSA had a higher plant gain and lower controller gain but no difference in overall loop gain compared to non-OSA children at baseline Higher plant gain and lower controller gain in children with OSA and positive correlation between plant gain and OSA severity Children with OSA displayed increased genioglossus EMG activity compared to controls across all sleep states and the application of CPAP led to a decrease in EMG activity in children with OSA
17
Upper airway muscle responsiveness/ arousal response Arousal response
Marcus et al. 1999 [61]
18
Moreira et al. 2005 [77]
41
Upper airway sensory function
Huang et al. 2008 [78]
21
Upper airway sensory function
Tapia et al. 2010 [79]
22
Upper airway sensory function
Huang et al. 2013 [80]
48
Upper airway sensory function
Tapia et al. 2015 [81]
47
Upper airway sensory function
Tapia et al. 2016 [82]
61
Mean age of 8 years
Otherwise healthy children
2-10 years
Otherwise healthy children
5-12 years
Otherwise healthy children
6-16 years
Otherwise healthy children
6-16 years
Otherwise healthy children
6-16 years
Otherwise healthy children
Children with OSA have a higher arousal response to inspiratory resistance loading compared to children without OSA No difference in arousal response to moderate acoustic stimulation between OSA children and controls Children with OSA have decreased evoked K-complex production in stage 2 and slow wave sleep (SWS) and reduced respiratory-related evoked potentials (RREPs) in SWS compared to children without OSA Children with OSA had impaired two-point discrimination in the anterior tongue and hard palate compared to children without OSA Children with OSA have persistent irreversible (with treatment) respiratory afferent cortical processing deficits during sleep compared to children without OSA Children with OSA have partial delay of respiratory afferent cortical processing during wakefulness that improves after treatment Children with OSA and controls have similar palatal vibration threshold detection
Otherwise healthy children Table legend: OSA, Obstructive sleep apnoea; CO2, Carbon dioxide; EMG, Electromyogram; CPAP, Continuous positive airway pressure; SWS, Slow wave sleep. 6-16 years
18
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