Sleep profiles in children with 22q deletion syndrome: a study of 100 consecutive children seen in a multidisciplinary clinic

Abstract

Study Objectives:

While previous studies have suggested a high prevalence of sleep disorders in children with 22q deletion syndrome (22qDS), they were limited by potential selection bias. In the current investigation, we assessed sleep characteristics in 100 consecutive children presenting to a 22qDS multidisciplinary clinic.

Methods:

An observational retrospective case series of consecutive children presenting to 22qDS multidisciplinary clinic was performed. Children aged 2 to 17 years of age were included, and data were abstracted including sleep characteristics (sleep history, Childhood Sleep Habits Questionnaire [CSHQ], and free response questions), comorbid medical conditions, and demographics.

Results:

Overall, 100 children were included in analysis, 85% of whom had scores on the CSHQ consistent with clinically meaningful sleep disorder. Sleep problems were common in all domains of the CSHQ, including daytime sleepiness (66%), sleep-onset delay (54%), parasomnias (52%), night wakings (52%), sleep-disordered breathing (49%), sleep duration (45%), bedtime resistance (38%), and sleep anxiety (33%). Overall CSHQ score was significantly associated with daytime behavioral problems and speech delay [F_(2,97) = 10.4, P < .001, adjusted R² = 0.16]. The most common interventions reported to be helpful for sleep by parents were behavioral (routine, bedtime story), environmental (light avoidance at night, calming music), and pharmacologic (melatonin, clonidine).

Conclusions:

These data confirm a high prevalence of sleep disorders in a large, unselected sample of children with 22qDS, and suggest an important relationship between sleep dysfunction and daytime behavioral challenges. Our findings highlight the potential role for multimodal treatment approaches including behavioral, environmental, and pharmacologic interventions.

Citation:

Ingram DG, Raje N, Arganbright JM. Sleep profiles in children with 22q deletion syndrome: a study of 100 consecutive children seen in a multidisciplinary clinic. J Clin Sleep Med. 2023;19(1):27–34.

BRIEF SUMMARY

Current Knowledge/Study Rationale: Previous studies of children with 22q deletion syndrome (22qDS) have demonstrated a high prevalence of sleep disorders but were limited by potential selection bias. We examined sleep characteristics of 100 unselected, consecutive children presenting to a multidisciplinary 22qDS in order to determine the prevalence and type of clinical sleep problems.

Study Impact: Our results confirm a high prevalence (85%) of clinical sleep problems in children with 22qDS that span all domains and are associated with daytime behavioral challenges. We highlight potential multimodal treatment approaches based on parental report.

INTRODUCTION

Children with 22q deletion syndrome (22qDS) experience a multitude of health challenges, including congenital heart disease, airway and palate abnormalities, endocrinopathies, immunodeficiencies, developmental delay, gastrointestinal abnormalities, and behavioral challenges.¹ A growing body of literature has suggested that children with 22qDS may also struggle with sleep problems. Arganbright and colleagues² performed a survey of parents of children with 22qDS and found that 96% had a clinical sleep problem. Similarly, a survey study from Leader and colleagues³ demonstrated that 91% of parents reported their child with 22qDS had sleep challenges. In contrast, data from neurotypical children^4,5 indicate 20–30% prevalence of sleep problems in the general population.

While the above cited studies suggest an increased prevalence of sleep problems in children with 22qDS, they were limited by possible selection bias due to their survey format. Specifically, it is possible that parents of children who had sleep problems were more likely to respond to a study invitation, potentially inflating the prevalence of sleep disorders as compared with an unselected or random sample of parents of children with 22qDS. Furthermore, emerging data suggest a potential relationship between nighttime sleep and other health and behavioral challenges in this population of children.^3,6–8 Therefore, the purpose of the present investigation was to examine sleep profiles and correlates in an unselected sample of children with 22qDS.

METHODS

This was an observational retrospective case-series study design. Participants were patients seen in a 22qDS multidisciplinary clinic at a tertiary-care children’s hospital. Children’s Mercy Hospital developed a multidisciplinary clinic for children who have 22qDS. This clinic is named the Super Q Express clinic and cares for children from birth through age 21 years in our region. The Super Q theme reflects the fact that the clinic focuses on bringing all providers from different subspecialties together so that everyone is on the same track. The clinic was initiated in 2013 and includes experts from endocrinology, cardiology, otolaryngology, gastroenterology, genetics, psychology, immunology, hearing, and speech, and a clinical social worker. Approximately 5 years ago, a sleep medicine provider (D.G.I.) was added to the clinic based on the anecdotal impression that the children with 22q being seen in the clinic had a variety of sleep challenges that might benefit from such services. Since that time, the sleep physician has attended clinics and provided care alongside the other subspecialists. Data collection was performed and managed using Research Electronic Data and Capture (REDCap, Vanderbilt University), a secure, web-based software platform designed to support data capture for research studies.^9,10 As a part of clinic intake, families complete multiple surveys administered using REDCap tools. Surveys were completed between December 2017 and May 2021. Children were excluded if they were less than 2 or older than 17 years of age or had incomplete questionnaire data. In addition, in the case of children with data from multiple visits, the initial visit data were included in order to ensure each participant included was unique.

From the parent-report clinic survey, variables of interest were extracted for analysis. Demographics included sex, race, genetic diagnosis, age, and parent respondent (mother vs father). Several questions regarding sleep history were asked including if the child had a previous polysomnogram, diagnosis of sleep apnea, previous tonsillectomy, use of positive airway pressure, or use of sleep medication. The presence or absence of other medical and behavioral problems was queried. Comorbidities were assessed by parent report as a part of the clinic visit survey intake. This information was obtained at the same time that the sleep questionnaire was filled out.

The Children’s Sleep Habits Questionnaire (CSHQ) was used to assess sleep profiles. The CSHQ is a 33-item comprehensive questionnaire that asks about the frequency of sleep symptoms across 8 domains: Bedtime Resistance, Sleep Onset Delay, Sleep Duration, Sleep Anxiety, Night Wakings, Parasomnias, Sleep‐Disordered Breathing, and Daytime Sleepiness.⁴ In addition to the individual items, a total score and domain scores can be calculated, with higher scores indicating more sleep problems and total scores above 41 representing a high likelihood of the presence of a clinically significant sleep problem.⁴ The CSHQ is well validated and has been used in a wide array of previous research studies, including children with or without neurodevelopmental disorders and of a variety of ages.^4,5,11–14 In addition to the structured questionnaire, parents were asked 2 open-ended questions regarding their child’s sleep: “What is the biggest sleep challenge your child faces?” and “What have you found helpful for your child’s sleep?”

Data were summarized with frequency counts for categorical variables and means (standard deviation) for continuous variables. Associations between sleep characteristics on the CSHQ and other patient characteristics were explored via forward stepwise logistic regression. A forward selection method for stepwise regression was used where 1 variable at a time was considered for entry into the regression model. The entry criterion for candidate variables was based on the F-statistic, and the threshold used in the current study was the probability of F to enter ≤ 0.05. Results for the overall resulting model are characterized by reporting the results of the F-test, including the F-value, degrees of freedom, and P value; this test compares the model with predictor variables with an intercept-only model without additional predictors, so a significant result means that adding predictor variables significantly improves the predictive ability of the model. Furthermore, the overall adjusted R² value is reported, which provides the reader a degree of magnitude for the result and signifies the percent variance of the outcome explained by the model predictors. Statistical tests were 2‐sided with results considered statistically significant at the P < .05 level. This study was approved by the Institutional Review Board at Children’s Mercy Hospital. All data analyses were performed in SPSS (released 2014; IBM SPSS Statistics for Windows, version 23.0; IBM Corporation, Armonk, NY). Institutional board review was obtained for this under IRB #15060239.

RESULTS

During the study period, there were 132 patient research encounters recorded in the database. All patients enrolled in the study between December 2017 and May 2021 were given the survey at the time of enrollment, regardless of their sleep history. Seven patients were excluded for incomplete CSHQ data, and another 25 encounters were excluded because they represented multiple visits from the same patient (Figure 1). Overall, 100 consecutive, unique children seeking care at the Children’s Mercy Hospital 22qDS multidisciplinary clinic and consented for research enrollment were included in analysis. Fifty-five children were male, and mothers were the survey respondent 87% of the time. The mean age of children was 8.3 (4.5) years, with 29% of children aged 2–5 years, 48% of children aged 6–12 years, and 23% of children aged 13–17 years. Race of participants was as follows: 82% White, 5% African American, 1% Asian, and 12% other. In terms of 22qDS genetic anomaly, 85% of participants had a deletion and 15% had duplication. Parent-reported comorbidities included the following: developmental delay (65%), speech delay (64%), seasonal allergies (50%), congenital heart disease (36%), immunodeficiency (31%), gastroesophageal reflux disease (26%), significant daytime behavioral problems (18%), eczema (17%), cleft palate–repaired (16%), growth hormone deficiency (11%), hypothyroidism (10%), cleft palate–unrepaired (8%), epilepsy (7%), and kidney disease (4%).

Figure 1. Flowchart of patients included and excluded for study from the 22q research database.

CSHQ = Children’s Sleep Habits Questionnaire.

Overall individual sleep problem frequencies are presented in Figure 2. Nine individual sleep problems were endorsed by half or more of participants. The most common sleep problem endorsed was restless sleep (75%). Several commonly endorsed problems related to daytime sleepiness, including seeming tired (67%), others needing to wake child (65%), waking in negative mood (61%), sleepy riding in a car (54%), doesn’t wake by himself (54%), and hard time getting out of bed (53%). Finally, sleep-onset delay (54%) and awakening during the night (66%) were reported in the majority of participants. The least frequent sleep problems reported were sleepwalking (8%), witnessed apneas (13%), and awakening screaming and sweating (15%).

Figure 2. Frequency (%) of individual sleep symptoms endorsed by families as occurring “sometimes” or “usually.”.

mins = minutes.

Total CSHQ scores and subdomain scores are presented in Table 1. The mean CSHQ score was 50.5 (8.7), with 85% of participants scoring above the threshold (> 41) for probable clinically meaningful sleep disorder. While direct comparison between samples from previous studies is challenging, summative data from 2 previous studies of children with 22qDS and 1 large study from neurotypical children are presented in Table 1 for comparison. In order to examine type of sleep problem from subscale scores, the frequencies of children in the current sample scoring above the threshold of subscale score greater than the mean + 1 standard deviation of normative data were used, and were as follows: daytime sleepiness (66%), sleep-onset delay (54%), parasomnias (52%), night wakings (52%), sleep-disordered breathing (49%), sleep duration (45%), bedtime resistance (38%), and sleep anxiety (33%).

Table 1.

CSHQ scores of consecutive children with 22qDS compared with previously reported 22qDS samples and typically developing children.

	22q Clinical Sample in Current Study (n = 100)	22q Survey Sample from Leader et al3 (n = 149)	22q Survey Sample from Arganbright et al4 (n = 30)	Typically Developing Sample from Owens et al (n = 357 to 415)
Age, y	8.3 (4.5)	9.0 (4.7)	6.8 (4.2)	7.5 (1.5)
Bedtime resistance	8.6 (2.9)	9.4 (3.5)	10.3 (3.6)	7.0 (1.8)
Sleep-onset delay	1.7 (0.7)	1.7 (0.7)	1.9 (0.9)	1.2 (0.5)
Sleep duration	4.3 (1.5)	5.0 (2.0)	5.2 (1.9)	3.4 (0.9)
Sleep anxiety	6.1 (2.0)	6.9 (2.2)	7.1 (1.7)	4.8 (1.4)
Night waking	4.8 (1.6)	5.2 (1.8)	5.8 (1.8)	3.4 (0.8)
Parasomnias	10.1 (2.3)	11.0 (2.5)	11.2 (3.0)	8.1 (1.3)
Sleep-disordered breathing	3.9 (1.3)	4.3 (1.5)	4.4 (1.8)	3.2 (0.6)
Daytime sleepiness	13.9 (3.1)	14.9 (3.0)	14.7 (4.2)	9.7 (2.8)
Total CSHQ	50.5 (8.7)	52.1 (9.1)	57.2 (9.9)	38.7 (5.5)
CSHQ > 41	85%	91%	96%	23%

Values are mean (standard deviation). CSHQ = Children’s Sleep Habits Questionnaire.

In order to explore potential associations between participant characteristics and sleep problems, forward stepwise regression analysis was performed, with results presented in Table 2. With forward stepwise regression, 1 variable at a time was considered for entry into the regression, and only those variables that significantly improved model predictive ability were retained. Individual predictors that were included in final models are listed in Table 2, along with their beta-coefficients and associated errors. Overall CSHQ score was significantly associated with daytime behavioral problems and speech delay [F_(2,97) = 10.4, P < .001, adjusted R² = 0.16]. Bedtime resistance was predicted by younger age, lack of immunodeficiency, presence of eczema, and presence of reflux [F_(4,95) = 9.7, P < .001, adjusted R² = 0.26]. Sleep duration was associated with the presence of eczema [F_(1,98) = 7.4, P = .008, adjusted R² = 0.06]. Sleep anxiety was associated with younger age, lack of heart disease, presence of developmental delay, and presence of eczema [F_(4,95) = 9.0, P < .001, adjusted R² = 0.24]. Night wakings were predicted by younger age and daytime behavioral problems [F_(2,97) = 5.4, P = .006, adjusted R² = 0.08]. Parasomnias were associated with younger age, daytime behavioral problems, and speech delay [F_(3,96) = 14.4, P < .001, adjusted R² = 0.29]. Sleep-disordered breathing was associated with younger age and growth hormone deficiency [F_(2,97) = 5.5, P = .005, adjusted R² = 0.08]. Daytime sleepiness was associated with behavioral problems [F_(1,98) = 5.1 P = .025, adjusted R² = 0.04]. No characteristics were found to predict sleep-onset delay.

Table 2.

Relationship between patient characteristics and sleep problems.

	CSHQ Total	Bedtime Resistance	Sleep-Onset Delay	Sleep Duration	Sleep Anxiety
Sex
22q genetic diagnosis
Parent reporting
Age		–0.25 (0.05)			–0.12 (0.03)
Congenital heart disease					–0.95 (0.37)
Cleft, not repaired
Cleft, repaired
Kidney disease
Developmental delay					1.09 (0.37)
Immunodeficiency		–1.52 (0.58)
Seasonal allergies
Eczema		2.23 (0.69)		1.08 (0.40)	1.6 (0.46)
Epilepsy
Reflux		1.23 (0.61)
Growth hormone deficiency
Hypothyroidism
Behavioral problems	8.1 (2.1)
Speech delay	3.5 (1.6)
Model-adjusted R2	0.16	0.26		0.06	0.24
	Night Wakings	Parasomnias	Sleep-Disordered Breathing		Daytime Sleepiness
Sex
22q Genetic diagnosis
Parent reporting
Age	–0.08 (0.03)	–0.11 (0.04)	–0.07 (0.03)
Congenital heart disease
Cleft, not repaired
Cleft, repaired
Kidney disease
Developmental delay
Immunodeficiency
Seasonal allergies
Eczema
Epilepsy
Reflux
Growth hormone deficiency			0.96 (0.42)
Hypothyroidism
Behavioral problems	0.95 (0.41)	2.66 (0.52)			1.81 (0.79)
Speech delay		1.04 (0.43)
Model-adjusted R2	0.08	0.29	0.08		0.04

Predictors that provided statistically significant improvement in model fit and therefore retained in the final model from stepwise regression analysis are displayed. Values are beta-coefficients (B) and associated standard error (SE). CSHQ = Children’s Sleep Habits Questionnaire.

Parent free-text responses were analyzed and categorized based on common themes. The most cited sleep challenges were sleep initiation (n = 32), sleep maintenance (n = 20), sleeping independently (n = 12), daytime sleepiness (n = 10), restless sleep (n = 9), and sleep-disordered breathing (n = 7). The most helpful interventions for sleep noted by parents included consistent routine (n = 19), nothing (n = 15), melatonin (n = 13), cosleeping (n = 11), limiting light exposure at night (n = 8), bedtime story (n = 6), and calming music (n = 6).

Regarding previous sleep disorder diagnostics and management, 35% of children had previously undergone formal polysomnography and 17% had been diagnosed with obstructive sleep apnea (OSA). In terms of medical treatments related to sleep, 32% of children had previously undergone tonsillectomy, 8% had used positive airway pressure, and 13% had been prescribed a medication for sleep. Melatonin was helpful in 30 of 39 children, iron in 10 of 14 children, clonidine in 7 of 8 children, trazodone in 1 of 1 child, and gabapentin in 1 of 3 children; no child had previously trialed zolpidem.

DISCUSSION

Children with 22qDS are at risk of a wide array of health challenges, the most recognized of which are developmental delays, heart disease, hypocalcemia, immune deficiency, and palatal abnormalities. While preliminary data from recent studies suggest that sleep disorders are highly prevalent in this population, those studies were limited by potential selection bias.^2,3 In order to overcome that limitation and further explore sleep in children with 22qDS, we systematically assessed sleep profiles in 100 consecutive children seen in a multidisciplinary 22qDS clinic. Our findings confirm an overall high prevalence of clinically meaningful sleep disorders in our sample, with 85% of children scoring above a predefined threshold on a standardized questionnaire. Importantly, the total CSHQ score was significantly predictive of daytime behavioral problems and speech delay, suggesting a potential connection between nighttime sleep and daytime function.

Our current findings complement and augment recent studies examining sleep in children with 22qDS. Like 2 recent studies that also utilized the CSHQ,^2,3 our data demonstrate an overall high prevalence of sleep disorders in an unselected sample. Restless sleep and sleep initiation/maintenance challenges were very common in our sample. In addition, we found a significant association between sleep challenges and daytime behavioral challenges. These findings are similar to those recently published by Moulding and colleagues,⁸ who found 2 major patterns of sleep problems in children with 22qDS (restless sleep and insomnia), and also found significant associations between sleep problems and a variety of daytime challenges including anxiety, coordination problems, executive function, and conduct disorder. Other studies in children with 22qDS show a relationship between sleep problems and self-injurious behavior, aggressive/destructive behavior, stereotyped behavior, cognitive dysfunction, and daytime affect.^3,6,7

While there are likely a multitude of reasons for the high prevalence of sleep problems in children with 22qDS, recent data highlight a possible genetic contribution. In the current study, we did not find any differences in sleep problems between children with 22q deletion vs duplication, which is consistent with a recent study completed by O’Hora and colleagues.¹⁵ A more detailed analysis of genetic factors was explored via a Drosophila model of 22qDS to investigate individual genes in relation to sleep and behavior.¹⁶ Neuronal knockdown allowed the investigators to identify several genes as important contributors to dysregulated sleep, including CDC45L (human CDC45), CG13192 (GNB1L), Es2 (DGCR14), and Septin4 (SEPT5), resulted in short-sleep phenotypes; CG13192 (human GNB1L) and slgA (PRODH) resulted in an increased number of sleep episodes that have a shorter length; and nowl/LZTR1 decreased total sleep amount and caused highly fragmented sleep. These genetic factors may relate to our findings of a high prevalence of challenges with restless sleep, sleep initiation, and sleep maintenance.

In addition to sleep problems predicting daytime behavior function, as discussed above, several other correlates were found between specific sleep challenges and participant characteristics. Younger age was associated with several domains of sleep dysfunction, which is not surprising given the known higher prevalence of bedtime resistance in younger children.⁵ Eczema was also significantly related to several sleep domains, consistent with previous studies demonstrating eczema as a potent disruptor of nighttime sleep.¹⁷ Our finding of reflux being associated with sleep dysfunction adds to recent studies that also identified this as significantly associated with sleep problems in children with 22qDS.^2,3 These associations, while important for identifying potential modifiable risk factors for sleep dysfunction, should be viewed as exploratory findings with relatively modest predictive value.

An increased prevalence of sleep-disordered breathing in children with 22qDS is congruent with our experience and previously published literature. Airway anomalies that can predispose to obstruction are common in children with 22qDS, including midface hypoplasia, micrognathia, oropharyngeal hypotonia, subglottic stenosis, laryngomalacia, tracheomalacia, and bronchomalacia.^18,19 Given the multiple sites of potential airway obstruction, the management of patients with 22qDS and OSA is complex. A study by Kennedy and colleagues²⁰ examined 323 patients with 22qDS, of whom 57 had at least 1 sleep study and 33 had been diagnosed with OSA by polysomnography; the overall prevalence of OSA in this study was 10.2% (33/323), compared to 1–3% in generally healthy children. Similarly, a study by Lee and colleagues²¹ examined 40 patients with 22qDS undergoing speech surgery who had a sleep study as part of their preoperative workup, and they found an overall OSA prevalence of 37.5% in their sample. These data suggest that patients with 22qDS should be regularly screened for symptoms of airway obstruction. Last, patients with 22q often need surgical correction of velopharyngeal dysfunction with speech surgery. Given that all speech surgeries carry a risk of worsening airway obstruction, patients with 22qDS should be closely monitored for OSA following this type of surgical intervention.

Given the high frequency of sleep challenges and associated daytime impairments documented by the current and previous studies, an important next question is regarding treatment options. While a large portion of sleep dysfunction may be related to underlying genetic differences, our data suggest that an important first step is evaluating for possible modifiable contributors, such as eczema and reflux. Although the cross-sectional nature of the current study did not allow for robust evaluation of treatment modalities, our results suggest that behavioral (routine, bedtime story), environmental (light avoidance at night, calming music), and pharmacologic (melatonin, clonidine) interventions hold promise. While there are currently no Food and Drug Administration–approved medications with an indication for pediatric insomnia, pharmacotherapy is occasionally a part of a comprehensive plan for pediatric sleep providers. The current study provides some limited experience in this population, and from a practical standpoint, we suggest that the review provided by Bruni and colleagues²² provides a reasonable approach. Matching a particular medication to the characteristics of the sleep challenge and associated comorbidities may help guide choice of pharmacotherapy. Furthermore, it is noteworthy that the second most commonly provided answer to what had been helpful was “nothing,” which highlights the need for additional research into effective sleep disorder management and treatment within this population.

The current study has several strengths that lend robustness to our findings. First, the design of including consecutive patients allowed us to avoid selection bias of those children with sleep problems and enhances the generalizability of our results to children with 22qDS. We feel that our results are likely generalizable to children and families who seek care at 22qDS multidisciplinary clinics at children’s hospitals across the country. Our multidisciplinary 22q clinic has a regional scope, and the fact that we examined consecutive children presenting to the clinic likely limits potential bias of only selecting those children with sleep challenges. Furthermore, our clinic provides care to all children with 22qDS, regardless of disease severity. Second, the use of a standardized sleep questionnaire, the CSHQ, ensured a valid measurement of all sleep domains as well as the ability to compare with previously reported results in the literature. Third, providing parents the ability of free-response questions added depth and richness to our results that is otherwise unavailable with close-ended questions. Fourth, the availability of participant characteristics allowed for exploratory analysis of factors associated with sleep dysfunction.

Despite the several strengths listed above, our study also has multiple limitations. First, the examined sleep measurements were self-reported, with a lack of polysomnographic and actigraphy data. Similarly, while we feel that the association between sleep challenges and daytime behavioral problems in our sample is noteworthy, the behavioral challenges were also parent-reported and subjective in nature. Our sample had a parent-reported developmental delay prevalence of 65%. Developmental delay is a fairly broad term and is subject to interpretation by the responding parent. A more refined examination of developmental delay might include differentiating cognitive delays, specific learning disabilities, growth delays, motor delays, social emotional delays, and results from formal neuropsychiatric testing to better parse out specific attributes related to sleep characteristics. If the prevalence of developmental delay was underreported in our sample, it is possible that the prevalence of sleep problems would have been even higher. Second, we did not have sufficient data available for exploring the possible relationship between calcium and iron stores on sleep profiles. Third, for the purposes of the present study, we chose to limit the sample to children aged 2 years to 17 years, given that the main sleep measure of the CSHQ has the most validity within that age range. Future studies are warranted to evaluate sleep challenges in children younger than 2 years of age and older than 17 years of age within this population. Fourth, another question left unanswered by this study is if the behavioral challenges are due to sleep concerns alone vs the underlying neurodevelopmental disorder itself. Given that this study included children entirely composed of those with 22qDS and did not involve neurotypical children, the present data cannot differentiate the effects of sleep disturbance vs underlying 22qDS on the behavioral outcomes. That said, these data do demonstrate a significant association between sleep disturbance and behavioral challenges within this population. Fifth, while the current study identifies interventions for sleep challenges that may hold promise, these findings should be viewed as preliminary and require additional study. Finally, the cross-sectional nature of our study limited our ability to make causal inferences.

CONCLUSIONS

These data confirm a high prevalence of sleep disorders in a large, unselected sample of children with 22qDS, and suggest an important relationship between sleep dysfunction and parent-reported daytime behavioral challenges. Our findings highlight the need for routine screening of sleep problems in this population, evaluation for potential exacerbating factors (such as eczema), and the importance of including a sleep provider in multidisciplinary 22qDS clinics. Potential avenues for future study include analysis of polysomnographic data, the potential role of calcium and iron regulation in sleep, and further evaluation of treatment modalities.

ABBREVIATIONS

CSHQ

Children’s Sleep Habits Questionnaire

OSA

obstructive sleep apnea

22qDS

22q deletion syndrome

DISCLOSURE STATEMENT

All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work. The authors report no conflicts of interest.