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(a) Publications:
• Genome-wide association study reveals two novel risk alleles for incident
obstructive sleep apnea in the EPISONO cohort. Farias Tempaku P etal.
2019 Sleep Med PMID:31786426.
• Multi-ethnic Meta-analysis Identies RAI1 as a Possible Obstructive
Sleep Apnea Related Quantitative Trait Locus in Men. Chen H etal. 2017
Am J Respir Cell Mol Biol PMID:29077507.
• Genetic Associations with Obstructive Sleep Apnea Traits in Hispanic/
Latino Americans. Cade BE et al. 2016 Am J Respir Crit Care Med
PMID:26977737.
(b) Traits:
• Obstructive sleep apnea: 36 associations and 6 studies.
• Sleep apnea measurement: 117 associations and 27 studies.
• Sleep apnea measurement during REM sleep: 7 associations and 1 study.
• Sleep apnea measurement during non-REM sleep: 0 associations and
1 study.
• Sleep apnea: 38 associations and 16 studies.
Another recent GWAS on 12,558 Hispanic American ancestry partici-
pants considered different OSA-associated phenotypes, including AHI,
mean oxygen saturation, and mean apnea and hypopnea duration. The associations detected were between a marker in GPR83 and AHI and between
the ARRB1 gene and average apnea and hypopnea duration, which is interesting due to its function as a regulator of HIF1α, which plays a critical role
in hypoxic sensitivity [7].
In a recent publication, the Finnish group of Strausz and coworkers con-
ducted a large-scale GWAS of OSA using the FinnGen study ([8] https://
www.nngen./en) with 16,761 OSA patients. They identied the following
loci associated with OSA: rs4837016 near GAPVD1, rs10928560 near
CXCR4, rs185932673 near CAMK1D, rs9937053 near FTO. They identied
a correlation between OSA and BMI and other comorbidities and a causal
relationship between the two phenotypes [9].
A. Patiño-García
The study of Baik and coworkers aimed to identify genetic variants associated
with OSA and their effect on the association with OSA risk factors, namely obesity, and alcohol consumption. In their analysis, rs10097555, a common polymorphism of the NRG1 gene (neuregulin-1) was the most signicant association
with OSA. Among 1763 participants, the NRG1 polymorphism was inversely
associated with OSA, and the association was modied by alcohol consumption [10].
3. Candidate Gene Association Studies, designed to identify pathogenic, rare and
infrequent variants that can account for an important part of the phenotype.
Sometimes, the candidate gene approach focuses on assessing single-nucleotide
polymorphisms (SNPs) within genes that have a known role in a specic trait or
disease. The genes with the strongest association with OSA are APOE (apolipoprotein E), ACE (angiotensin-converting enzyme), and TNFRSF1A (tumor
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necrosis factor-alpha) [11]. Also, different SNPs in serotonin receptors and
transporter genes (5-HT2A, 5-HT2C, 5-HTT) have been associated with OSA in
given populations [12].
A considerable candidate gene association study for OSA using the Cleveland
Family Study, consisting of European-American and African American subsamples, investigated 45,000 SNPs from approximately 2100 candidate genes. Only
an SNP in the PLEK (pleckstrin) gene, rs7030789, within the African American
subset and rs1409986in the PTGER3 gene (prostaglandin E2 receptor) in the
European subsample were found to be associated with OSA [13]. In addition, in
African Americans, an SNP in the LPAR1 gene (lysophosphatidic acid receptor
I) showed a genome-wide association with a quantitative measure of OSA severity, AHI [14].
4. Whole-genome sequencing (WGS) or deep genome sequencing can identify a
complete set of DNA sequence variants. It can be achieved using next- generation
sequencing (NGS) based on different sequencing platforms. As indicated in
Fig.28.1, WGS aims to assess the role of low frequency (MAF 1%–5%) and rare
(MAF ≤1%) genetic variation. A variation of the technique, often less time and
cost consuming, is whole-exome sequencing (WES), which relies on sequencing only the coding part of the genome.
In a recent study, van der Spek and coworkers performed WES meta-analysis
of symptoms of OSA in 1417 individuals of European descent. They identied
17 rare genetic variants with evidence of association in an identication cohort.
Validation in an independent dataset conrmed the association of rs2229918
with symptoms of OSA, and this genetic marker overlaps with the 3′ UTR
(untranslated region) of ERCC1 and CD3EAP genes on 19q13 [15].
There are likely different phenotypic pathways to OSA, including obesity, usually the main confounding factor, neuronal control of respiration, upper airway morphology, craniofacial features, each with distinct genetic contributions. Thus, some
researchers suggest that the search for genetic factors may be most fruitful if it is
focused on each of the relevant intermediate traits and associated phenotypes
[16, 17].
Li and coworkers analyzed ve patients with severe OSA and paired controls
using NGS to express genes associated with Alzheimer’s disease (AD) since AD
risk is known to be associated with OSA.They identied a differential expression
of CCL2, IL6, CXCL8, HLA-A, and IL1RN in patients with severe OSA, which also
signicantly contributed to changes in the immune response, cytokine–cytokine
receptor interactions, and nucleotide-binding oligomerization domain-like receptor
signaling pathways [18].
In addition, some authors have used high throughput expression assays and
reported differential expression of genes related to endothelial junction, proapoptotic and inammatory gene signatures. Chen etal., aimed to identify molecular
markers of chronic intermittent hypoxia with reoxygenation and adverse consequences in OSA in 48 patients with sleep-disordered breathing. In their analysis,
AMOT P130 protein expression, an endothelial tight junction, was increased in
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OSA patients with excessive daytime sleepiness. In addition, the proapoptotic proteins BIRC3 and LGALS3 were associated with OSA patients with hypertension
and chronic kidney disease, respectively [19].
Other genetic biomarkers such as miRNA (micro-RNA) proling and DNA
methylation have been much less used as potential bridges to the gap between the
pathophysiology and the clinical manifestations of OSA.These miRNAs are small
noncoding RNAs that can regulate gene expression at the posttranscriptional level.
Specic miRNAs are robust biomarkers for risk estimation, for example, in obese
patients. Since obesity and other comorbidities are associated with OSA, identifying a miRNA signature would allow for the understanding of the pathophysiology
of the disease at the molecular level. Still, but these data are not available today [20].
DNA methylation involves adding a methyl group to cytosine, thereby regulating
gene expression in physiology and disease. Very few studies are available on the
role of DNA methylation in OSA, but there are some related to OSA-related phenotypes. For example, hypoxia can lead to modication in the promoter methylation
of AR, NPR2, L1R2, and SP140 [21], and the methylation of other genes such as
FOXP3 and IRF1 are determinants of inammation [22].
Finally, some researchers have approached the association of biomarkers and
OSA from the protein side. Recently, Ambati and coworkers [23] proled over
1300 proteins in the serum of 713 individuals affected of OSA patients. They
concluded that obstructive apnea–hypopnea index (OAHI) was related to
increased proteins of the complement, coagulation, cytokine signaling, hemostasis pathways, and ROBO3, IGFBP3, and LEAP1 with different outcome measures. The analysis of these secreted markers achieved a 76% accuracy for
identifying OSA.Other studies used either ELISA or Luminex to prole differences in OSA using plasma serum or CSF (cerebrospinal uid) and showed associations with elevated Tau and amyloid-beta in CSF and elevated IL6, CRP,
insulin, and high monocyte to HDL ratio in plasma. Other groups have tried to
characterize the cognitive impairment in OSA by proling a 254-serum protein
panel by Luminex and identied an insulin-related signature. Finally, the red
blood cell proteome characterization in OSA patients identied associations with
proteins involved in response to stress or dysregulation of lipids (reviewed
in [23]).
A. Patiño-García
28.3 Conclusion
OSA is a complex disease with many potential genetic and environmental factors
that combine and interact to produce the disease. The identications and biomarkers
for the disease and its comorbidities, and the underlying genetic background will
probably involve the analysis of a high number of samples with whole-genome
sequencing data. There are ongoing international efforts in GWAS and NGS and
other massive technologies that will probably lead to the in-depth proling of this
disease in the coming years.
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Take-Home Messages
• OSA is a very complex trait from the clinical and genetic points of view.
• It is conditioned by a plethora of low-risk genes, their interactions, and their
interplay with a network of environmental factors.
• There are different genetic biomarkers of OSA as well as the different types of
study designs for their identication, namely linkage analyses, genome-wide
association studies (GWAS), candidate gene association studies, and whole-
genome or exome sequencing by next generation sequencing (NGS).
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2. Redline S, Tishler PV.The genetics of sleep apnea. Sleep Med Rev. 2000;4:583–602. https://
doi.org/10.1053/smrv.2000.0120.
3. Mukherjee S, Saxena R, Palmer LJ.The genetics of obstructive sleep apnoea. Respirology.
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4. Palmer LJ, Buxbaum SG, Larkin E, Patel SR, Elston RC, Tishler PV, Redline S. Wholegenome scan for obstructive sleep apnea and obesity. Am J Hum Genet. 2003;72:340–50.
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5. McCarthy MI, Abecasis GR, Cardon LR, Goldstein DB, Little J, Ioannidis JP, Hirschhorn
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6. GWAS Catalogue. https://www.ebi.ac.uk/gwas/. Accessed 2 April 2022; n.d..
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10. Baik I, Seo HS, Yoon D, Kim SH, Shin C.Associations of sleep apnea, NRG1 polymorphisms,
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11. Parish JM. Genetic and immunologic aspects of sleep and sleep disorders. Chest.
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12. Qin B, Sun Z, Liang Y, Yang Z, Zhong R.The association of 5-HT2A, 5-HTT, and LEPR polymorphisms with obstructive sleep apnea syndrome: a systematic review and meta-analysis.
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13. Parsons MJ.On the genetics of sleep disorders: genome-wide association studies and beyond.
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15. van der Spek A, Luik AI, Kocevska D, Liu C, Brouwer RWW, van Rooij JGJ, etal. Exomewide meta-analysis identies rare 3'-UTR variant in ERCC1/CD3EAP associated with symptoms of sleep apnea. Front Genet. 2017;8:151. https://doi.org/10.3389/fgene.2017.00151.
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16. Gehrman PR, Keenan BT, Byrne EM, Pack AI.Genetics of sleep disorders. Psychiatr Clin
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org/10.1016/j.smrv.2016.10.002.
18. Li HY, Tsai MS, Huang CG, Wang RYL, Chuang LP, Chen NH, Liu CH, Hsu CM, Cheng WN,
Lee LA.Alterations in Alzheimer's disease-associated gene expression in severe obstructive
sleep apnea patients. J Clin Med. 2019;8(9):1361. https://doi.org/10.3390/jcm8091361.
19. Chen YC, Chen KD, Su MC, Chin CH, Chen CJ, Liou CW, etal. Genome-wide gene expression array identies novel genes related to disease severity and excessive daytime sleepiness in
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20. Khurana S, Sharda S, Saha B, Kumar S, Guleria R, Bose S.Canvassing the aetiology, prognosis and molecular signatures of obstructive sleep apnoea. Biomarkers. 2019;24:1–16. https://
doi.org/10.1080/1354750X.2018.1514655.
21. Chen YC, Chen TW, Su MC, Chen CJ, Chen KD, Liou CW, etal. Whole genome DNA methylation analysis of obstructive sleep apnea: IL1R2, NPR2, AR, SP140 methylation and clinical
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22. Kim J, Bhattacharjee R, Khalyfa A, Kheirandish-Gozal L, Capdevila OS, Wang Y, Gozal
D. DNA methylation in inammatory genes among children with obstructive sleep apnea.
Am J Respir Crit Care Med. 2012;185:330–8. https://doi.org/10.1164/rccm.201106- 1026OC.
23. Ambati A, Ju YE, Lin L, Olesen AN, Koch H, Hedou JJ, etal. Proteomic biomarkers of sleep
apnea. Sleep. 2020;43:zsaa086. https://doi.org/10.1093/sleep/zsaa086.
A. Patiño-García
Maxillofacial Surgery inOSA
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StanleyYung-ChuanLiu andKristofferSchwartz
29.1 Diagnostic Features
29.1.1 Patient Selection
Maxillofacial surgery to treat OSA was rst integrated into a systematic approach
popularized by Riley and Powell of Stanford. The 2-phase approach begins with
multilevel surgery with nasal surgery, uvulopalatal ap, and genioglossus advancement (GGA). In the 40% of patients that do not respond to phase 1, phase 2 may be
offered. Phase 2 was characterized by maxillomandibular advancement (MMA). It
was known from early in the surgical management of OSA that for select patients,
both skeletal and soft tissue interventions were necessary and complementary for
treatment success [1–3].
The protocol has since been updated at Stanford to incorporate medical and surgical interventions on a continuum of care for OSA patients. There has been
advancement in the precision of phenotyping patients who are likely to achieve success with maxillofacial surgery. The cornerstones remain the same, with the careful
interpretation of polysomnography (PSG) data, static and dynamic airway examination, including drug-induced sleep endoscopy (DISE) and facial skeletal analysis
(Fig.29.1). As part of surgical decision-making, it remains critical to account for
patient preferences, expectations, and risk–benet prole [4–6].
S. Y.-C. Liu (*)
Department of Otolaryngology—Head & Neck Surgery, Stanford University School of
Medicine, Stanford, CA, USA
e-mail: ycliu@stanford.edu
K. Schwartz
Department of Oral & Maxillofacial Surgery, University Hospital of Southwest Denmark,
Esbjerg, Denmark
© The Author(s), under exclusive license to Springer Nature
Switzerland AG 2023
P. M. Baptista et al. (eds.), Obstructive Sleep Apnea,
https://doi.org/10.1007/978-3-031-35225-6_29
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S. Y.-C. Liu and K. Schwartz
Fig. 29.1 Stanford protocol with medical and surgical interventions. BMI Body Mass Index, PSG
Polysomnography, PE Physical examination, PAP Positive Airway pressure, OAT Oral appliance
therapy, CCC Complete Concentric Collapse, LPW Lateral Pharyngeal wall, TB Tongue Base,
TORS Trans Oral Robotic Surgery, DOME Distraction Osteogenesis Maxillary Expansion
29.1.2 Polysomnography
Polysomnography (PSG) is the gold standard for diagnosing and evaluating the
severity of OSA, although it may not reect the patient’s condition over time [7].
Severity of OSA is dened using the apnea–hypopnea index (AHI). Studies have
shown that the oxygen desaturation index (ODI) correlates more strongly with
cardiovascular morbidity than AHI alone [8]. Ambulatory sleep study with cardiorespiratory monitoring (CRM) is easier to obtain than attended PSG in patients
with a high risk of OSA, but it can underestimate OSA severity [9]. Surgical
success can be evaluated using the same diagnostic sleep studies and hypopnea
criteria before and after surgery [10]. It is important to note that AHI alone as an
indicator of success is increasingly inadequate to characterize the complexity of
OSA-related symptoms and comorbidity. As an index, it does not fully capture
changes in sleep architecture and does not account for developmental and aging
changes, or gender and ethnic differences [11]. The PSG offers a wealth of information, and the contemporary sleep surgeon needs to interpret the study beyond
the AHI.
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29.1.3 Clinical Examination
Clinical examination involves a comprehensive medical history with a meticulous
sleep-specic history and a full head and neck examination including the nasal airway, velopharynx, pharyngeal wall, tongue base, epiglottis, and facial skeletal relationship [5].
Endoscopic examination of the nasal airway should identify all possible anatomic and functional causes of nasal obstruction [12]. The negative pressure maneuver (Muller’s maneuver) can be performed simultaneously and is a quick method to
assess upper airway collapsibility [13]. A mandibular protrusion maneuver can also
be performed simultaneously to visualize the degree of lateral pharyngeal wall dilation and tongue base advancement. Examination of the facial skeletal relationship is
essential for diagnosing dentofacial contributors to sleep-disordered breathing.
Long-term nasal obstruction can often lead to facial changes, a long midface, anterior open bite, and retrognathic mandible. Examination of the mouth and dentition
may reveal a high-arched and narrow maxilla with the appearance of a relatively
large tongue and excessive soft palatal tissue.
29.1.4 Diagnostic Tools
Lateral cephalometric X-ray has been used since the early days of evaluating
maxillofacial morphology in OSA patients. It allows for an easy and direct visual
assessment of the anterior-posterior airway space [14, 15]. Compared to lateral
cephalometric X-ray, computed tomography (CT) or cone beam computer tomography (CBCT) signicantly improves soft tissue contrast and provides information regarding upper airway cross-sectional area at different levels. Image
processing allows three-dimensional reconstruction and volumetric assessment [16].
For the evaluation of soft tissue structures, magnetic resonance imaging (MRI)
provides advantages such as excellent soft tissue contrast, three-dimensional assessment of tissue structure, and lack of ionizing radiation. Dynamic sleep MRI is a
diagnostic tool that allows simultaneous real-time evaluation of airway obstructions
and respiratory events during natural sleep. Dynamic sleep MRI can characterize
the actual site of dynamic airway obstruction and potentially improve predictions of
successful surgical outcomes in OSAS patients [17]. It is important to note that
while retropalatal and retrolingual collapse is common with OSA of all severity,
lateral pharyngeal wall collapse during dynamic MRI with a low hyoid bone position have been shown to predict severe OSA [18].
Drug-induced sleep endoscopy (DISE) has shown to be important in optimizing surgical outcomes in OSA patients. With DISE, clinicians can visualize and
phenotype pharyngeal muscle collapse that varies in morphology and degree at
distinct levels of the upper airway [19] (Fig.29.2). There is no consensus regard-
ing standardized protocols for DISE. However, the procedure is usually performed in the supine position in an outpatient setting with monitoring of oxygen
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Fig. 29.2 DISE (Drug
Induced Sleep Endoscopy):
allows visualization and
phenotype pharyngeal
muscle collapse that varies
in morphology and degree
at distinct levels of the
upper airway
S. Y.-C. Liu and K. Schwartz
saturation, heart rate, blood pressure, and sometimes bispectral index score.
Sedation is commonly initiated with propofol, dexmedetomidine, and midazolam. The depth of sedation is crucial and is evaluated by the onset of the
disordered breathing or the Bispectral index score [20]. Several classication
systems have been introduced to characterize DISE ndings in OSA patients [19,
21]. The VOTE classication system, which comprises the Velum, Oropharyngeal
(lateral walls), Tongue, and Epiglottis, is widely used for DISE scoring [22].
Multilevel collapse is the most common nding from DISE, and patterns of complete concentric collapse, multilevel collapse, and tongue base collapse are associated with a higher AHI [23].
A complete concentric collapse has been associated with unfavorable surgical outcomes in multilevel surgery and is currently a contraindication for upper
airway stimulation [24–26]. In the updated Stanford Sleep Surgery Protocol,
patients presenting with both complete concentric collapse of the velum, and
complete lateral pharyngeal wall collapse, may be recommended maxillomandibular advancement (MMA) as rst-line surgical therapy. This is based on
studies showing that MMA addresses these two collapse patterns more reliably
than soft tissue or upper airway stimulation procedures [24, 25, 27, 28]
(Fig.29.3).
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a b
Fig. 29.3 DISE allows visualization of airway collapse sites. DISE before and after maxillomandibular advancement (MMA). (a) Pre MMA pharyngeal collapse. (b) An important improvement
of airway is observed. Post MMA pharyngeal collapse
29.2 Genioglossus–Genioplasty Advancement
29.2.1 Introduction
Genioglossus advancement (GA) was rst described in 1984 by Robert Riley and
Nelson Powell to improve outcomes in patients with obstructive sleep apnea (OSA)
who did not improve sufciently with palatal surgery [29]. Their initial technique with
a modied horizontal mandibular osteotomy was improved in 1986 to include a limited
inferior parasagittal mandibular osteotomy (anterior mandibular osteotomy) [30].
Electromyographic studies have identied the genioglossus muscle as the major pharyngeal dilator musculature of the airway during sleep. Its role has been extensively
implicated in the pathophysiology of OSA with the rationale that the upper airway
collapse occurs with failure of the dilator muscle to sustain patency during the respiratory cycle [31]. The genioglossus muscle is attached to the genial tubercles of the mandible. By advancing the genial tubercles, the genioglossus muscle lengthens and
strengthens over time to allow greater tongue advancement during sleep [3]. GA is
usually performed in conjunction with other sleep surgery procedures (uvulopalatopharyngoplasty, maxillomandibular advancement) [32]. Variations to the GA procedure include the trephine osteotomy, genioplasty with genioglossus suspension sutures,
and combining the GA with a genioplasty [33]. With the wide availability of CT scans
and the development of virtual-surgical- planning (VSP), using 3-dimensional (3D)
printing of medical-grade cutting guides has allowed the contemporary GA to be more
precise and predictable [34]. GA and genioplasty can often be performed in conjunction to improve facial balance in mandibular hypoplastic OSA patients, which also
exerts a strengthening effect on the suprahyoid muscles [35]. The surgical success rate
of GA surgery as an isolated treatment of OSAS ranges from 43% to 53% [32, 36].
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