Introduction
Methods
Sleep problems in ASD: from childhood to adulthood
References | Participants | Materials | Main findings | Limitations and strengths |
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Schreck et al. [13] | ASD children (N = 55, range 5–12 years, mean age = 8.2 years) | A database of parent report of sleep problems of children based on a self-report demographic form, the GARS, and the BEDS | Sleep problems (fewer hours of sleep per night, increased sensitivity to environmental stimuli in the bedroom) and the diagnostic characteristics of autism (social skill deficits, communication problems, developmental sequence) disturbances) may be related | Limitations: absence of a control group of healthy individuals |
Sikora et al. [14] | ASD children (N = 1193, M = 1014, F = 179, range = 4–10 years) | Measures included Children’s Sleep Habits Questionnaire, Vineland Adaptive Behavior Scales, Survey Interview Form, Second Edition, and Child Behavior Checklist | Even if sleep is negative related with internalizing and externalizing behaviour, it could be differently related with the acquisition of adaptive skills | Limitations: few differences were clinical significant; information about sleep and daytime behaviour was registered through parents reports; use of quartile scores as the cutoff between mild and moderate to severe sleep problems may not be valid; even though the study highlights the bidirectional relationship between sleep and daytime behaviour, other factors are supposed to be implicated; disproportion between male and female (M/F = 1014/179) Strengths: large sample size |
Goldman et al. [15] | ASD children (N = 1859, range 3–18 years, mean age 80.1 ± 42.3 months) | CSHQ, PCQ | Sleep problems persist through adolescence in ASD with differences in types of problems experienced | Limitations: data are subjective and based on parental report; the cross-sectional nature of these data limits evaluation of a temporal relationship between age and sleep; the CSHQ and PCQ have not been validated with adolescents; not differentiation between males and females Strengths: large sample size |
Ballester et al. [20] | ASD adults (N = 41, M = 31, F = 10, mean age = 33 ± 6 years) Typically developing adults (N = 51, M = 21, F = 30, mean age = 33 ± 5 years) | ACM recording wrist temperature, motor activity, body position, sleep, and light intensity | Poorer sleep conditions in adults with autism (increased sleep latency and number/length of night awakenings) resulted in decreased sleep efficiency | Limitations: these problems are life-long conditions, not only childhood related; parents or legal guardians of adults with ASD and ID with disturbed sleep were more likely to participate compared to those without sleep problems; ACM had not been validated in ASD to study sleep; while the comparison group was healthy, ASD one was medicated with polypharmacy; disproportion in M/F ratio particularly in the first group Strengths: it is a controlled study with similar numerosity between groups |
Baker et al. [22] | ASD adults (N = 36, M = 17, F = 19, IQ > 80, range = 21–44 years, 20 of them met criteria for insomnia and/or a circadian rhythm sleep–wake disorder) and age and sex-matched controls (N = 36, M = 17, F = 19 4 of them met criteria for the disorders above) | 14-day actigraphy assessment and questionnaire battery | It has emerged, for the first, time that sleep problems are associated with unemployment in adults with autism spectrum disorder | Strengths: it is a controlled study with similar M/F ratio in both groups. Limitations: studies with larger ASD samples would be useful |
Deserno et al. [23] | ASD adults with subjective QoL as outcome (N = 598, M = 310, F = 288, range = 17–83 years) ASD adults with objective QoL as outcome (N = 544, M = 270, F = 274, range = 17–82 years) | For objective QoL: five subscales of the Autism Quotient (Baron-Cohen, Wheelwright, Skinner, Martin, & Clubley, 2001), five subscales of the Sensory Perception Quotient (Tavassoli, Hoekstra, & Baron-Cohen, 2014), seven items of the Insomnia Severity Index (Bastien, Vallières, & Morin, 2001). For subjective QoL: an item assessing how satisfied participants were with their own life | Sleep problems are highly influential in predicting long-term QoL in ASD individuals | Limitations: a specific set of symptom data and environmental factors was used for determination of multivariate pathways; individuals have a long-term level of happiness to which they always spontaneously return after life events of either valence; the authors were limited by online survey context and were unable to verify diagnosis and IQ of participants; the study sample has a large age range (17–83); there is not a control group Strengths: similar groups composition in terms of age and M/F ratio |
Horiuchi et al. [16] | Autistic toddlers (N = 26, M = 20, F = 6) and non-autistic toddlers (N = 400, M = 184, F = 216) Total range:17–19 months Total mean age: 18 months | Japanese version of the M-CHAT-JV and the CASC | Autistic traits are associated with sleep problems in toddlers. As a result, daytime sleepiness might be a visible symptom that enables the earlier detection of ASD in children | Limitations: parents of toddlers who attended nursery school (199/426) had few information about their children’s daytime behavior; it is difficult to assess sleepiness in toddlers; few data are available on the reliability and validity of the CASC, and the previous studies that have used the CASC with toddlers; some items are not suitable for toddlers; disproportion between ASD and control group and in M/F ratio in ASD toddlers Strengths: controlled study |
Türkoğlu et al. [17] | ASD drug-naïve children (N = 46, M = 38, F = 8, range: 4–17 years, mean age 7.89) | AuBC, CSHQ, CCQ | Children with ASD during the home confinement reported higher chronotype scores and autism symptom scores compared to the normal non-hone confinement state. The sleep problems of the children with ASD during the home confinement period mediated the relationship between chronotype score and severity of autism symptoms | Limitations: lack of a control group; small sample size; family members were not screened for psychopathology, post-confinement follow-up with participants was not done; disproportioned M/F ratio |
Miike et al. [18] | ASD children from K-Development Support Center for Children (K-ASD, N = 121, M = 94, F = 27), ASD children from H-Children’s Sleep and Development Medical Research Center (H-ASD, N = 56, M = 40, F = 16), Children from recruited from four nursery schools in T-city (control) (N = 203, M = 104, F = 99) | Questionnaires to assess parent(s) of children with ASD and controls investigating: maternal lifestyle during pregnancy, neonatal sleep patterns, status of parent(s) in the child-rearing years | Neonatal sleep–wake rhythm abnormalities, especially in irritable-type neonates, are important precursors for future ASD development and so it is important to pay much more attention to the maternal role in fetal chronobiology formation and to circadian rhythm formation | Limitations: disproportioned M/F ratio in ASD groups Strengths: it is a controlled study |
Yavuz-Kodat et al. [19] | ASD children (N = 52, M = 41, F = 11, range = 2.75–9.57 years, mean age = 5.39 ± 1.50 years) | Sleep and circadian rest–activity rhythms were objectively measured with actigraphy and subjectively with the Children’s Sleep Habits Questionnaire. Behavioral difficulties were assessed using the ABC-C | Problem behaviors were strongly accounted for by both sleep and circadian rhythm disturbances. Particularly, the longest continuous sleep episode is a novel clinically meaningful sleep parameter to consider, especially in children with severe sleep disorders | Assessment of both sleep and circadian rhythms with actigraphy is a strength because it is an objective measure, but also it is a limitation due to the fact that it remains a proxy of the circadian timing system. Another limitation: the lack of a control group |
Jovevska et al. [21] | ASD group (N = 297, mean age = 34.36 ± 15.24) and comparison group (N = 233, mean age = 33.01 ± 15.53) | PSQI to examine sleep quality, SoL, total night sleep, and sleep efficiency. Other predictors of sleep quality: autistic traits, mental health condition, medication, employment, and sex | Autistic adolescents and adults, particularly females, remain vulnerable to sleep problems. Times where the risk is highest are early and middle adulthood | Limitations: sleep was measured using a self-report, retrospective questionnaire; the study was cross-sectional and so long-term trends for sleep quality in the context of chronicity or aging are not captured; autistic adults with intellectual disability were not included; about half the autistic sample was female, but the generally accepted male:female ratio in autism spectrum disorder is 4:1; the sample consisted of volunteers who responded to an advertisement, and not all participants had responses for all variables Strengths: a large part of ASD population included (18–80 years old); large sample size, including an age-matched comparison group; the first study which examines male–female differences in sleep in autistic adolescents and adults |
Biochemical correlates of altered circadian regulation in ASD
Genetic pathways
References | Participants | Materials | Principal findings | Strengths and limitations |
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Nicholas et al. [27] | ASD probands and all their parents (N = 90, M = 65, F = 25 for the first stage of the study; N = 20, M = 14, F = 6 for the second stage of the study) | For screening candidate genes genotyping SNPs | Significant association (P < 0.05) for two single-nucleotide polymorphisms in per1 and two in npas2; in npas2 40 out of the 136 possible two-marker combinations were significant at the P < 0.05 level. The best result was between markers rs1811399 and rs2117714, P = 0.001. In per1 the significant result was for the markers rs2253820–rs885747. Epistatic clock genes may be involved in the etiology of autistic disorder. Problems in sleep, memory and timing are all characteristics of autistic disorder and aspects of sleep, memory and timing are each clock-gene-regulated in other species | Limitations: lack of a control group and the higher number of males compared to females |
Hu et al. [5] | Three groups of autistic probands, selected after the exclusion of females, individuals with cognitive impairment, genetic or chromosomal abnormalities, born prematurely and comorbid psychiatric disorder and a control group (non-autistic controls) | DNA microarray analyses | In the most severely affected ASD group, 15 genes, which regulate circadian rhythm, have neurological and metabolic functions deregulated in ASD, were found. From other groups, 20 genes were pointed out, mostly located in non-coding regions and associated with androgen sensitivity | Limitations: the lack of the exact number of participants in each group and information about age and gender of the included people; epigenetic modifications related to inflammatory status Strengths: utility of subdividing individuals with ASD on the basis of cluster analyses of ADIR scores that incorporate all three core domains of ASD (as described in the accompanying manuscript) |
Yang et al. [29] | ASD patients (N = 28, 14 of them with sleep problems and 14 without sleep problems. In the first group, M = 5 and F = 9, with an age range 3–28 years, while in the second group M = 12 and F = 2, with an age range 3–19 years) Healthy controls (N = 23) | Sequencing of the coding regions of 18 canonical clock genes and clock-controlled genes; direct sequence analyses verified detected mutations and additional control individuals were screened | Mutations in circadian-relevant genes affecting gene function are more frequent in patients with ASD than in controls. Circadian-relevant genes may be involved in the psychopathology of ASD | Limitations: small sample size Strength: presence of a control group (even if it is not known its internal composition) |
Olde-Loohuis et al. [28] | Wistar rats | Rat mPFC collection, RNA isolation, RNA sequencing, gene ontology analysis, cDNA synthesis, qRT-PCR | Three different subsets of genes discovered: the first involved in the regulation of circadian rhythm, the second contributing to extracellular matrix, the third important to understand autism at a molecular level | Limitations: it is a study conducted on animals model, and it is difficult to make precise distinction between groups Strengths: it suggests a possible linking between circadian rhythm and molecular basis of autism |
Role of melatonin
References | Participants | Materials | Main findings | Strengths and limitations |
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Rossignol et al. [36] | Initial studies review: 35 reviewed independently by two reviewers Five of them were investigated through meta-analysis | Database used: PubMed, Google Scholar, CINAHL, EMBASE, Scopus, ERIC Quality of studies was assessed through Downs and Black checklist | Nine studies measured melatonin or its metabolites in ASD: all reported at least one alteration (four studies: abnormal melatonin circadian rhythm; seven studies: below average physiological levels; four studies: positive correlation between melatonin/derivatives levels and autistic behaviors). Five studies reported gene abnormalities that could decrease melatonin production or impair melatonin receptor function in a small percentage of ASD children | Limitations of the review: small sample size; variation in protocols for measuring changes in sleep parameters; five studies contained a mixture of individuals with ASD and other developmental disabilities |
Wang et al. [40] | ASD children (N = 398, M = 367, F = 31, range 2–17 years) and healthy controls (N = 437, M = 406, F = 31) | Genotyping sequences in ASMT, DNA analysis and prediction the effects of coding non-synonymous variants on protein function | Four rare ASMT mutations were found only in ASD group (p.R115W, p.V166I, p.V179G, and p.W257X) | Limitations: low sample size for a rare genetic mutations investigation; important disproportion between F and M composition (367/31 in ASD group vs. 406/31 in control one); lack of information on the clinical and biochemical impacts of the ASMT deleterious variants and/or SNPs; other genes in melatonin pathway were not sequenced Strengths: controlled study |
Veatch et al. [41] | ASD individuals (N = 29, M = 24 and F = 5, 15 of them underwent analysis for ASMT sequences, while 14 of the total for CY1A2 genotypes) | Examination of variation in two melatonin pathway genes, ASMT and CYP1A2 | Higher frequencies than currently reported for variants evidenced to decrease ASMT expression and related to decreased CYP1A2 enzyme activity; a relationship between genotypes in ASMT and CYP1A2 was revealed; expression of sleep onset delay relates to melatonin pathway genes | Limitations: lack of a well-defined control group; all 11 individuals who participated in the melatonin trial were responsive to treatment; minimalization of the environmental effect of poor sleep habits through parent sleep education |
Pagan et al. [32] | Unrelated patients with ASD (N = 278), first-degree relatives (129 unaffected siblings, 377 patients) and controls (N = 416) | Serotonin, melatonin and the intermediate NAS measured through whole-blood serotonin, platelet NAS and plasma melatonin | In patients the melatonin deficit was only significantly associated with insomnia. Impairments of melatonin synthesis in ASD may be linked with decreased 14-3-3 proteins. Disruption of the serotonin-NAS-melatonin pathway is a very frequent trait in ASD patients and may be a useful biomarker for a large subgroup of these individuals | Limitations: not equally subdivision between three groups Strengths: two groups of possible controls (unaffected siblings and other controls) |
Pagan et al. [44] | ASD patients (N = 239), ASD parents (N = 303), unaffected siblings (N = 78), controls (N = 278) | Examination of melatonin synthesis in post-mortem pineal gland, serotonin synthesis in gut samples, blood platelets | Melatonin deficits in ASD depends on reduction activity of both enzymes implicated in melatonin synthesis (AANAT and ASMT) | Limitations: small number of patient samples Strengths: three different groups |
Braam et al. [33] | Mothers of an ASD child (N = 60, mean age: 42.9 ± 5.7 years), control group of mothers (N = 15, mean age = 44.3 ± 9.7 years) | 6-SM concentration | 6-SM levels were significantly lower in mothers with an ASD child than in controls, and so, low parental melatonin levels could be one of the contributors to ASD and possibly ID etiology | Limitations: differences between number composition of both groups and small sample size; CYP1A2 activity not measured; different children ASD etiologies Strength: presence of a control group |
Maruani et al. [45] | ASD individuals (N = 81), unaffected relatives (N = 90), control participants (N = 48) | PGV estimation based on magnetic resonance imaging; blood sampling and plasma melatonin measurement | Patients had both morning melatonin levels and PGV lower than controls; plasma melatonin was correlated to the group of the participant, but also to the PGV melatonin; variations in ASD could be mainly driven by melatonin pathway dysregulation | Limitations: melatonin was detected only in mornings; difficulties in exactly detecting PGV; numeric differences between the first two groups and the third Strengths: three experimental groups |
Cortisol levels and hyperarousal
References | Participants | Materials | Main findings | Strengths and limitations |
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Priya Lakshimi et al. [49] | ASD children (N = 45 divided into three groups: low, medium and high functioning. Each group included 15 children. M/F = 36/9, range 4–12 years) Typically developed children (N = 45, M/F = 36/9, range = 4–12 years) | CARS classification as preliminary screening and urinary level of free cortisol, corticosteroids, VMA, and 5-hydroxyindole acetic determination | Corticosteroids excretion levels were higher in all the groups of children with ASD than in the control group. An alteration in the pattern of cortisol excretion was observed in children with LFA. The level of 5-hydroxyindole acetic acid was higher in children with LFA and MFA than in the control group | Limitations: not determined the blood and saliva levels of corticosteroids, free cortisol, VMA, 5-hydroxyindole acetic acid, and prostaglandin E Strengths: group of ASF and controls very identical in number composition, M/F ratio and range age |
Gabriels et al. [51] | Pre-pubescent ASD males (N = 21, 11 of them with high-RB, and 10 with low RB) Mean age of high-RB group: 7.8 ± 1.7 years Mean age of low-RB: 8.1 ± 1.4 years Range: 3–9 years | Measure of screening: tanner criteria, caregiver-report RBS-R scale, CCIF-RV, SCQ, ADOS, Leiter-R, VABS, BEDS Other measure: salivary cortisol level | Participants with more severe repetitive behaviors had lower diurnal salivary cortisol than others | Limitations: patients were only males and the sample size was low Strengths: patients were carefully selected through different scales |
Tomarken et al. [50] | ASD children (N = 36, M = 30, F = 6, Mean age 10.20 ± 1.96) Typically developed controls (N = 27, M = 23, F = 4, mean age = 9.71 ± 1.54) Total range: 7–16 years | Salivary cortisol collection | A decline in evening levels of cortisol was detected, whereas no difference was reported in the morning levels. 25% of ASD children had an attenuated linear decline in cortisol level, while the trajectory of the other ones was indistinguishable from that of TD children | Limitations: disproportioned M/F ratio in both groups Strengths: controlled study |
Sharpley et al. [53] | ASD girls (N = 39) Mean age = 10.1 ± 2.7 years Range = 6–17 years | CASI, WASI-II, ADOS-2, DF of cortisol and CAR | Over half of the participants showed inverse CAR and over 14% had inverted DF cortisol concentrations; three potential sets of predictor factors (physiological, ASD-related, and mood) revealed that only self-reported Major Depressive Disorder was significantly associated with CAR status, and that the girls' concern about dying or suicide was the most powerful contributor to the variance in CAR status | Limitations: sample size; statistical power; cultural and geographical isolation; use of a snap-shot design rather than a prospective design; collection of salivary cortisol on a single day; one third of the cohort reported thoughts of “dying or killing oneself; it is not a direct comparison study |
Muscatello et al. [48] | ASD youths (N = 64, M = 57, F = 7, mean age 12.02 years) and typically developed youths (N = 49, M = 42, F = 7, mean age = 11.17 years) Total range = 7–17 years | Diagnostic and assessment measures: ADOS, WASI, SCQ, SRS-2, PDS, CBCL, SSS, SES, Salivary cortisol sampling | ASD child, pubertal and adolescents had significantly higher evening cortisol than controls. Adolescent had higher cortisol levels than children | Limitations: predominantly male sample and differences in IQ between groups; the current sample consisted only of those with high-functioning ASD; numeric disproportion between males and females included Strengths: large ASD sample and a comprehensive age range of children and adolescents |
Baker et al. [7] | ASD adults (N = 29, M = 51.7%, F = 48.3%, 13 of them were medicated for comorbid anxiety or ASD-Med with mean age = 33.93 ± 6.53 years 16 were drug-free or ASD-only with mean age = 33.55 ± 6.50) and controls (N = 29, mean age = 30.99 ± 5.25 years) | Participants completed a questionnaire battery, 14-day sleep/wake diary and 14-day actigraphy assessment; On one day during the data collection period, participants collected five saliva samples, hourly, prior to sleep and two morning samples, immediately upon waking and 30 min thereafter for the analysis of cortisol | ASD participants reported greater reduction in evening cortisol concentrations when compared with controls; In the ASD group, poor sleep efficiency and increased wake duration was significantly correlated with cortisol levels measured 1 h before habitual sleep onset time; increased sleep onset latency and poorer sleep efficiency was associated with higher subjective arousal in the ASD group | Limitations: cortisol was not retained in the model; comorbid diagnoses of anxiety and depression in the ASD-Med group were not confirmed with clinical interviews; small sample sizes Strengths: controlled study with proportioned ASD and controls group; subdivision into ASD group in ASD-Only and ASD-Med |
Anesiadou et al. [54] | Four groups: ASD children (N = 56, M = 49, F = 7 mean age = 8.40 ± 1.60 years) ADHD children (N = 34, M = 22, F = 12, mean age = 8.79 ± 1.43 years), SLD children (N = 43, M = 25, F = 18, mean age = 9.55 ± 1.64 years), TD group (N = 24, M = 16, F = 8, mean age = 9.74 ± 1.98 years) | APT, moral cognition task, sAA | ASD children showed lower diurnal sAA secretion, adjusted for age, compared to typically developed ones; sAA evening levels resulted significantly higher in ADHD group compared to controls; the academic performance task increased sAA levels in ASD children, while the moral cognition task did not activate the sympathetic nervous system in any group | Limitations: cross-sectional design does not allow us to make inferences; small sample size of population; sample procedure to a single day; lack of multiple time point sampling; disproportion in M/F ratio between groups Strengths: four different groups |
Autonomic nervous system (ANS) alterations in ASD
References | Participants | Materials | Main findings | Strengths and limitations |
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Anderson et al. [62] | Study 1: ASD group (N = 12, M = 11, F = 1, mean age = 50.25 months, range = 30–69 months), down syndrome (DS) group (N = 9, M = 7, F = 2, mean age = 48.67 months, range = 20–73 months), TD group (N = 11, M = 10, F = 1, mean age = 51.73 months, range = 34–69 months) Study 2: ASD group (N = 18, mean age = 57.78 months, range = 39–73 months), TD group (N = 19, mean age = 52.26 months, range = 33–79 months) | Tonic pupil size, saliva sample collection | ASD showed larger pupil size and lower sAA levels than controls; sAA was strongly correlated with tonic pupil size; typical controls showed a linear increase in sAA during the day | Limitations: small sample size, disproportioned M/F ratio in groups of the first study, not stratification in the second study for males and females Strengths: two different studies, presence of two a control groups (healthy individuals and down syndrome) |
Pace et al. [64] | ASD group (N = 19, mean age = 10.7 ± 1.2 years), control group (N = 19, mean age = 9.9 ± 1.6 years) | Questionnaire, actigraphy; nocturnal recordings; HRV analysis | Lower mean HR values were found during sleep with respect to those registered during wakefulness; however, the ASD group showed a lower decrease in HR during deep sleep despite the presence of a higher parasympathetic tone | Limitations: small sample size, not stratification in males and females Strengths: presence of a control group |
Harder et al. [65] | ASD children (N = 21, all males, mean age = 7.8 ± 1.8 years) and typically developed children (N = 23, M = 18, F = 5, mean age = 8.0 ± 1.9 years) | Polysomnography, HR and HRV | In both groups, HR decreased during non-REM sleep and increased during REM sleep; HR was significantly higher in stages N2, N3 and REM sleep in the ASD group; ASD children showed less HF modulation during N3 and REM sleep; LF/HF ratio was higher during REM; heart rate decreases with age at the same level in ASD and in TD. LF was influenced by age | Limitations: small sample size, ASD children were composed only by males Strengths: controlled study |
Tessier et al. [66] | ASD children (N = 13, range 7–12 years, mean age = 10.2 ± 2.1), ASD adults (N = 16, range = 16–27 years, mean age = 22.0 ± 3.8 years), TD children (N = 13, range = 6–13 years, mean age = 10.5 ± 1.8 years), TD adults (N = 17, range = 16–27 years, mean age = 21.1 ± 4.0 years) | Sleep laboratory measures, ECG recordings | Results show that ASD adults had lower HFnu in the morning than TD adults. During REM sleep, adults had higher LF/HF ratio than children, regardless of their clinical status | Limitations: high number of males, ASD participants were medicine-free; LH/FH ratio significance has been largely questioned Strengths: four different equally subdivided groups (children and adults with or without ASD) |
Bharath et al. [8] | ASD children (N = 40, M = 24, F = 16, range = 5.25–12 years, mean age = 10 years), TD controls (N = 40, M = 26, F = 14, range = 7.25–11.75 years, mean age = 9 years) | Autonomic index was assessed by the analysis of short term HRV; urinary levels of VMA estimation was used as a biochemical autonomic index | ASD children exhibit lower cardio-vagal activity as measured by HRV and increased sympathetic activity as assessed by urinary VMA compared to that of TD children | Limitations: small sample size, difference in M/F ratio Strengths: presence of a control group similar to ASD ones (same number of participants) |
Sheinkopf et al. [59] | Infants later diagnosed with ASD (N = 12, M = 12, F = 0) and controls non-later ASD (N = 106, M = 58, F = 48) range: 1–72 months | HR and RSA | Both groups showed an expected age-related decrease in HR and increase in RSA, without difference in rate of HR decrease over time; ASD infants demonstrated a smaller linear increase in RSA, indicating slower growth in RSA over time in comparison to controls, thus suggesting that differences in physiological regulation may develop with age in ASD | Limitations: small sample size; participants were drawn from a high-risk cohort designed to investigate the developmental effects of prenatal drug exposure, which could have effects on RSA at one moth of age; disproportion between two groups composition Strengths: controlled study |
Thapa et al. [61] | ASD group (N = 55, M = 74.5%, F = 25.5%, mean age = 23.11 ± 5.98 years) control group (N = 55, M = 80%, F = 20%, mean age = 22.00 ± 5.24 years) | HRV | Difference in resting-state HRV between adults diagnosed with ASD compared to the neurotypical control group, with lower parasympathetic activity in ASD | Limitations: ASD group had psychiatric comorbidities, whose effect was difficult to determine due to small sample size; two different devices were used to determine HRV; majority of patients were males Strengths: presence of a control group |
Mohd et al. [60] | ASD children (N = 6), TD controls (N = 14) | HRV derived from PPG | HRV response can differentiate between ASD and TD children and could contribute to the detection of ASD to facilitate the children getting the best intervention at the earliest possible time | Strengths: controlled study Limitations: small sample size, not stratification in age and sex |
Chong et al. [67] | ASD children (N = 13) divided in: dysregulated sleep group (N = 7, M = 63%, F = 37%, mean age = 7.53 ± 1.35 years) Regulate sleep group (N = 6, M = 80%, F = 20%, mean age = 4.46 ± 1.28 years) | Actigraphy for sleep measure, EDA (which included NSSCR and SCL, SCQ for ASD symptoms core, VABS-II for adaptive behavior | Children in the dysregulated sleep group had fewer NSSCRs and lower SCL in the afternoon | Limitations: small and heterogeneous sample; prevalence of males in both groups; absence of a control group Strengths: subdivision in two groups based on facility/difficulty in sleeping |
Current pharmacological perspectives for sleep disorders in ASD
References | Participants | Materials | Main findings | Strengths and limitations |
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Posey et al. [91] | Subjects with neurodevelopmental disorder (PDDs), (N = 26, M = 21, F = 5, range = 3.8–23.5 years, mean age = 10.1 ± 4.8 years, 20 of them with ASD, 1 with Asperger’s disease, 1 with Rett’s disorder, 4 with PDDs not specified) | Treatment with mirtazapine (dose range = 7.5–45 mg daily, mean = 30.3 ± 12.6 mg daily) | Mirtazapine did not improve core symptoms of social or communication impairment. Adverse effects were minimal and included increased appetite, irritability, and transient sedation | Limitations: lack of a control group, disproportion between male and female number in group, small sample size |
Thirumalai et al. [84] | ASD patients (N = 11, range 3–9 years, M = 9, F = 2, mean age = 5.09 years) | Polysomnography, EEG, EMG | REM sleep behavior disorder was identified in 5 of these 11 patients. Since REM sleep behavior disorder typically affects elderly males with neurodegenerative diseases, the identification of this phenomenon in autistic children could have profound implications for our understanding of the neurochemical and neurophysiologic bases of autism. Accurate diagnosis of REM sleep behavior disorder would enable specific treatment with clonazepam and help the family and the child | Limitations: small sample size, absence of a control group, disproportion between males and females |
Ingrassia et al. [89] | Children (N = 6, 3 ADHD and 3 with mental retardation, range = 6–14 years, mean age = 11.2 years) | Clonidine administration (range dose = 50–100 mcg daily) | All children showed maintained improvements in their sleep pattern following the use of clonidine with only mild side-effects reported | Limitations: small sample size, lack of a control group, case series |
Dosman et al. [94] | ASD children (N = 33, M = 27, F = 6, mean age = 6 years and 6 moths, range = 2 year 8 months–10 year 8 months) | Questionnaires (Sleep Disturbance Scale for Children, movements during sleep scale of Chervin and Hedger, Food records) made by parents after iron supplementation | High prevalence of restless sleep, which improved with oral iron supplementation, suggests that sleep disturbance may be related to iron deficiency in autism | Limitations: absence of a control group, disproportion between males and females |
Rossignol et al. [36] | Initial studies review: 35 reviewed independently by two reviewers Five of them were investigated through meta-analysis | Database used: PubMed, Google Scholar, CINAHL, EMBASE, Scopus, ERIC Quality of studies was assessed through Downs and Black checklist | Six studies reported improvements in daytime behavior using melatonin; 18 studies on melatonin treatment in ASD reported improvements in sleep duration, sleep onset latency, night-time awakenings From the meta-analysis: improvements in sleep duration but not in night-time awakenings | Strengths: the meta-analysis increases the statistical significance, funner plot didn’t indicate publication bias Limitations: small sample size, protocol which measured changes in sleep parameters were variable |
Buckley et al. [81] | ASD subjects (N = 5, range = 2.5–6.9 years) compared with within-lab controls | Polysomnography for REM sleep augmentation after donepezil administration | REM sleep as a percentage of Total Sleep Time was increased significantly and REM latency was decreased significantly after drug administration in all subjects | Limitations: open-label study without controls; very small sample size |
Malow et al. [73] | ASD children (N = 24, range = 3–9 years, mean age = 5.9 years) | Melatonin supplementation, Actigraphy, Children’s Sleep Habits Questionnaire (CSHQ), Child Behavior Checklist (CBCL) scale | Supplemental melatonin improved sleep latency, as measured by actigraphy, in most children at 1 or 3 mg dosages. It was effective in week 1 of treatment, maintained effects over several months, was well tolerated and safe, and showed improvement in sleep, behavior, and parenting stress | Limitations: absence of a control group, small sample size |
Mendez et al. [85] | ASD people (N = 3, range = 34–43 years, mean age = 39.33 years), controls (N = 3, range = 37–40 years, mean age = 38.66 years) | PET with receptor PET ligand [11C] Ro15-4513 was used to measure a1 and a5 subtypes of the GABA-A receptor levels | Lower [11C]Ro15-4513 binding was found throughout the brain of participants with ASD compared with controls. Planned region of interest analyses also revealed significant reductions in two limbic brain regions, namely the amygdala and nucleus accumbens bilaterally, thus suggesting a GABA-A a5 deficit in ASD | Limitations: very small number of participants Strengths: controlled study, accurate technique of investigation (PET) |
Maras et al. [74] | Initial participants: Children (N = 125, 96,8% of them ASD, 3,2% with Smith-Magenis syndrome, range = 2–17.5 years) Final number of participants: N = 95, 51 of them received PedPRM, 44 placebo | Administration of 2, 5, or 10 mg PedPRM; Measures were: CSDI, PSQI, ESS, quality of life WHO-5 Well-Being Index | PedPRM, an easily swallowed formulation shown to be efficacious versus placebo, is an efficacious and safe option for long-term treatment (up to 52 weeks reported here) of children with ASD and NGD who suffer from insomnia and subsequently improves caregivers' quality of life | Limitations: open-label design of the study; lack of a control group made by healthy individuals; some individuals discontinuated treatment Strengths: presence of a group receiving placebo |
Ballester et al. [80] | ASD people (N = 23, M = 83%, mean age = 35 ± 12 years) | Administration of agomelatine or placebo | Agomelatine was effective and well tolerated for treating insomnia and circadian rhythm sleep problems present in adults with ASD and ID | Limitations: small sample size; absence of a control group Strengths: placebo-controlled study |
Gabis et al. [83] | ASD children (N = 60, range = 5–16 years, mean age = 9.5 ± 3.22 years) | AChE inhibitors and choline supplements in children and adolescents with ASD | Combined treatment of donepezil hydrochloride with choline supplement demonstrates a sustainable effect on receptive language skills in children with ASD for 6 months after treatment, with a more significant effect in those under the age of 10 years | Limitations: safety concerns limited the dose and the compounds used in the study; small sample size; two different language tests were used to assess global language skill; absence of a control group |