ADHD subtypes are associated differently with circadian rhythms of motor activity, sleep disturbances, and body mass index in children and adolescents: a case-control study

Sleep disturbance in children with attention-deficit hyperactivity disorder: relationship with melatonin and behavior

AIM

To evaluate the prevalence and types of sleep problems and their correlations with melatonin content and behavior in Attention-Deficit Hyperactivity Disorder (ADHD) children.

METHOD

Sleep in ADHD children and typically developing children (TD) aged 6-14 was assessed by the Sleep Disorders Scale for Children (SDSC) and actigraphy, salivary melatonin quantified by ELISA, and behavior was analyzed using the Strengths and Difficulties Questionnaire.

RESULTS

ADHD children showed a higher frequency of sleep disturbances, higher sleep latency, and lower sleep efficiency than in the TD group. The ADHD group presented lower melatonin nocturnal content compared to the TD group. Disorders of Initiating and Maintaining Sleep (DIMS) was moderately associated with nocturnal melatonin. The total behavior difficulties were correlated with Disorders of Initiating and Maintaining Sleep (DIMS), Sleep/Wake Transition Disorders (SWTD), Disorders of Excessive Somnolence (DES), Sleep Hyperhidrosis (SHY) and Total SDSC Score. The behavior was the only determinant of the total SDSC score (R2 = 0.499; p < 0.002).

CONCLUSION

This study provides, for the first time, evidence that among the frequent sleep disturbances in ADHD, the disorders in initiating and maintaining sleep are associated with the low levels of melatonin found in this population. Additionally, these, along with other sleep disturbances, are linked to behavioral problems in ADHD.

The circadian system: A neglected player in neurodevelopmental disorders

Patients with neurodevelopmental disorders, such as autism spectrum disorder, often display abnormal circadian rhythms. The role of the circadian system in these disorders has gained considerable attention over the last decades. Yet, it remains largely unknown how these disruptions occur and to what extent they contribute to the disorders' development. In this review, we examine circadian system dysregulation as observed in patients and animal models of neurodevelopmental disorders. Second, we explore whether circadian rhythm disruptions constitute a risk factor for neurodevelopmental disorders from studies in humans and model organisms. Lastly, we focus on the impact of psychiatric medications on circadian rhythms and the potential benefits of chronotherapy. The literature reveals that patients with neurodevelopmental disorders display altered sleep-wake cycles and melatonin rhythms/levels in a heterogeneous manner, and model organisms used to study these disorders appear to support that circadian dysfunction may be an inherent characteristic of neurodevelopmental disorders. Furthermore, the pre-clinical and clinical evidence indicates that circadian disruption at the environmental and genetic levels may contribute to the behavioural changes observed in these disorders. Finally, studies suggest that psychiatric medications, particularly those prescribed for attention-deficit/hyperactivity disorder and schizophrenia, can have direct effects on the circadian system and that chronotherapy may be leveraged to offset some of these side effects. This review highlights that circadian system dysfunction is likely a core pathological feature of neurodevelopmental disorders and that further research is required to elucidate this relationship.

Exploring an objective measure of overactivity in children with rare genetic syndromes

BACKGROUND

Overactivity is prevalent in several rare genetic neurodevelopmental syndromes, including Smith-Magenis syndrome, Angelman syndrome, and tuberous sclerosis complex, although has been predominantly assessed using questionnaire techniques. Threats to the precision and validity of questionnaire data may undermine existing insights into this behaviour. Previous research indicates objective measures, namely actigraphy, can effectively differentiate non-overactive children from those with attention-deficit hyperactivity disorder. This study is the first to examine the sensitivity of actigraphy to overactivity across rare genetic syndromes associated with intellectual disability, through comparisons with typically-developing peers and questionnaire overactivity estimates.

METHODS

A secondary analysis of actigraphy data and overactivity estimates from The Activity Questionnaire (TAQ) was conducted for children aged 4-15 years with Smith-Magenis syndrome (N=20), Angelman syndrome (N=26), tuberous sclerosis complex (N=16), and typically-developing children (N=61). Actigraphy data were summarized using the M10 non-parametric circadian rhythm variable, and 24-hour activity profiles were modelled via functional linear modelling. Associations between actigraphy data and TAQ overactivity estimates were explored. Differences in actigraphy-defined activity were also examined between syndrome and typically-developing groups, and between children with high and low TAQ overactivity scores within syndromes.

RESULTS

M10 and TAQ overactivity scores were strongly positively correlated for children with Angelman syndrome and Smith-Magenis syndrome. M10 did not substantially differ between the syndrome and typically-developing groups. Higher early morning activity and lower evening activity was observed across all syndrome groups relative to typically-developing peers. High and low TAQ group comparisons revealed syndrome-specific profiles of overactivity, persisting throughout the day in Angelman syndrome, occurring during the early morning and early afternoon in Smith-Magenis syndrome, and manifesting briefly in the evening in tuberous sclerosis complex.

DISCUSSION

These findings provide some support for the sensitivity of actigraphy to overactivity in children with rare genetic syndromes, and offer syndrome-specific temporal descriptions of overactivity. The findings advance existing descriptions of overactivity, provided by questionnaire techniques, in children with rare genetic syndromes and have implications for the measurement of overactivity. Future studies should examine the impact of syndrome-related characteristics on actigraphy-defined activity and overactivity estimates from actigraphy and questionnaire techniques.

Sleep problems in children with autism spectrum disorder and attention-deficit/hyperactivity disorder: A comparative study and effects on communication skills

Sleep disturbances are highly prevalent among children with neurodevelopmental disorders, like Autism Spectrum Disorder (ASD) and Attention-Deficit/Hiperactivity Disorder (ADHD). The first objective of this study is to examine the differences in sleep problems between a group of children with ASD without intellectual disabilities, a group with ADHD and a typically developing (TD) group. A second objective is aimed at analyzing the effects of sleep problems and symptom severity on their communication skills. Participants were 122 children between 7 and 12 years old distributed in three groups: 32 TD children, 47 children with ASD and 43 children with ADHD, matched on age and intelligence. Parents completed different questionnaires that measured sleep disturbances and communication skills. Findings show significant differences between the clinical groups and the TD group in most types of sleep disorders. Moreover, the group with ADHD showed significantly more sleep breathing disorders and hyperhidrosis in comparison with ASD and TD, as well as more total sleep problems. In contrast to ASD, the predictive power of sleep problems on communication difficulties was greater in the group with ADHD. The results of the mediation analysis indicate that in both groups, sleep problems partially mediate the relationship between symptoms and communication. This investigation highlights the need of considering sleep disorders when assessing communication skills in ASD and ADHD, given its indirect influence in this domain. Understanding the sleep dysfunctions of both conditions and their repercussions is crucial to develop adjusted interventions.

Adolescent Cannabis Use, Comorbid Attention-Deficit/Hyperactivity Disorder, and Other Internalizing and Externalizing Disorders

Cannabis use often co-occurs with attention-deficit/hyperactivity disorder and other internalizing and externalizing disorders. Treatment planning, including pharmacologic and psychosocial interventions, for these comorbid disorders require thorough diagnostic evaluation to determine the extent of social, emotional, and behavioral impairments, severity of substance use, and motivation for change. Improved understanding of these comorbid disorders will inform treatment planning that address current symptoms and behaviors and may also prevent the development of mental health and substance use disorders in early adulthood.

Objectively measured sleep continuity in children and adolescents with ADHD: A systematic review and meta-analysis

Sleep disturbances are often linked to attention-deficit/hyperactivity disorder (ADHD). Consistent findings document that children and adolescents with ADHD report more sleep problems than their typically developing (TD) peers across subjective sleep domains. However, few differences between these groups were observed in objectively measured sleep parameters, such as polysomnography (PSG) and actigraphy. This study synthesized empirical studies to identify objectively measured sleep continuity differences between children and adolescents with ADHD and TD. We included observational research and baseline data from intervention studies between 5- to 18-year-old individuals with ADHD and their TD peers at five databases from inception and September 2022. This systematic review and meta-analysis of 45 articles, including 1622 children and adolescents with ADHD and 2013 TD, found that compared with TD, children and adolescents with ADHD have higher sleep latency and moderately decreased sleep efficiency measured by actigraphy. Polysomnography-measured differences between ADHD and TD were not significant. Medication status and comorbid psychiatric status significantly moderated the group differences in sleep efficiency between ADHD and TD. Also, the group differences in sleep latency between ADHD and TD were moderated by actigraphy recorded nights. These findings highlight the importance of reducing disparities in sleep parameters among children and adolescents with and without ADHD.

Anthropometric status of preschoolers and elementary school children with ADHD: preliminary results from the EPINED study

BACKGROUND

A current area of research interest is the association between ADHD and weight status. This paper aimed to describe the anthropometric status of school children with ADHD, considering age and clinical presentation (inattentive, hyperactive-impulsive, or combined), compared with control children.

METHODS

Participants came from the "Epidemiological Research Project on Neurodevelopmental Disorders" and consisted of 198 preschoolers (41 with ADHD) and 389 elementary school children (163 with ADHD). ADHD was diagnosed using DSM-5 criteria. Anthropometric measurements were taken at various anatomical points, and height, weight, and body composition were also measured.

RESULTS

In preschoolers, an association was found between hyperactive-impulsive ADHD and greater height and lower waist-to-height ratio. In elementary school children, regardless of the medication, combined ADHD was associated with smaller head, hip, arm, and thigh circumferences and lower weight, height, and BMI. A total of 19.7% of them were underweight. In contrast, children with inattentive and hyperactive/impulsive presentations presented the highest percentage of overweight/obesity (56%).

CONCLUSION

The anthropometric status of the school children with ADHD showed differences in terms of age and presentation. Preschoolers with hyperactive-impulsive ADHD are taller, and elementary school children with combined ADHD are shorter and smaller than their age-matched control peers.

IMPACT

The anthropometric status of the school children with ADHD showed differences in terms of age and presentation. Preschoolers with hyperactive-impulsive ADHD are taller than their control peers. Elementary school children with combined ADHD, regardless of the pharmacological treatment, are shorter and smaller than their control peers. Medication may anthropometrically affect the height of children with inattentive presentation. Anthropometric and dietary monitoring should be recommended to parents of children with ADHD, with and without medication.

[Physical growth and dietary characteristics of children with attention deficit hyperactivity disorder: a cross-sectional study]

OBJECTIVES

To investigate the physical growth and dietary characteristics of children with attention deficit hyperactivity disorder (ADHD), and to analyze their relationship with core symptoms of ADHD.

METHODS

A total of 268 children who were newly diagnosed with ADHD in Children's Hospital of Nanjing Medical University from June to December 2020 were included in the ADHD group, and 102 healthy children who underwent physical examination during the same period were selected as the control group. Physical evaluations and dietary surveys were conducted for both groups. ADHD diagnosis and scoring were performed according to the Diagnostic and Statistical Manual of Mental Disorders (5th edition). Factor analysis, Spearman correlation analysis, and mediation analysis were used to study the relationship between core symptoms of ADHD, dietary patterns, and physical growth.

RESULTS

The rate of overweight/obesity in the ADHD group was significantly higher than that in the control group (35.8% vs 21.6%, P<0.05). Three dietary patterns were extracted from the food frequency questionnaire: vegetarian dietary pattern, traditional dietary pattern, and snack/fast food pattern. The factor score for the snack/fast food pattern in the ADHD group was higher than that in the control group (P<0.05). There was a significant positive correlation between ADHD symptom scores, snack/fast food pattern factor scores, and body fat percentage (P<0.05). The mediation analysis showed that the snack/fast food pattern played a partial mediating role in the relationship between ADHD symptom scores and body fat percentage, with a mediation proportion of 26.66%.

CONCLUSIONS

The rate of overweight/obesity in children with ADHD is higher than that in non-ADHD children. Core symptoms of ADHD are related to dietary patterns and physical growth, with the snack/fast food pattern playing a partial mediating role in the relationship between core symptoms of ADHD and physical growth.

Machine Learning-Based Prediction of Attention-Deficit/Hyperactivity Disorder and Sleep Problems With Wearable Data in Children

IMPORTANCE

Early detection of attention-deficit/hyperactivity disorder (ADHD) and sleep problems is paramount for children's mental health. Interview-based diagnostic approaches have drawbacks, necessitating the development of an evaluation method that uses digital phenotypes in daily life.

OBJECTIVE

To evaluate the predictive performance of machine learning (ML) models by setting the data obtained from personal digital devices comprising training features (ie, wearable data) and diagnostic results of ADHD and sleep problems by the Kiddie Schedule for Affective Disorders and Schizophrenia Present and Lifetime Version for Diagnostic and Statistical Manual of Mental Disorders, 5th edition (K-SADS) as a prediction class from the Adolescent Brain Cognitive Development (ABCD) study.

DESIGN, SETTING, AND PARTICIPANTS

In this diagnostic study, wearable data and K-SADS data were collected at 21 sites in the US in the ABCD study (release 3.0, November 2, 2020, analyzed October 11, 2021). Screening data from 6571 patients and 21 days of wearable data from 5725 patients collected at the 2-year follow-up were used, and circadian rhythm-based features were generated for each participant. A total of 12 348 wearable data for ADHD and 39 160 for sleep problems were merged for developing ML models.

MAIN OUTCOMES AND MEASURES

The average performance of the ML models was measured using an area under the receiver operating characteristics curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). In addition, the Shapley Additive Explanations value was used to calculate the importance of features.

RESULTS

The final population consisted of 79 children with ADHD problems (mean [SD] age, 144.5 [8.1] months; 55 [69.6%] males) vs 1011 controls and 68 with sleep problems (mean [SD] age, 143.5 [7.5] months; 38 [55.9%] males) vs 3346 controls. The ML models showed reasonable predictive performance for ADHD (AUC, 0.798; sensitivity, 0.756; specificity, 0.716; PPV, 0.159; and NPV, 0.976) and sleep problems (AUC, 0.737; sensitivity, 0.743; specificity, 0.632; PPV, 0.036; and NPV, 0.992).

CONCLUSIONS AND RELEVANCE

In this diagnostic study, an ML method for early detection or screening using digital phenotypes in children's daily lives was developed. The results support facilitating early detection in children; however, additional follow-up studies can improve its performance.

Adolescent Cannabis Use, Comorbid Attention-Deficit/Hyperactivity Disorder, and Other Internalizing and Externalizing Disorders

Cannabis use often co-occurs with attention-deficit/hyperactivity disorder and other internalizing and externalizing disorders. Treatment planning, including pharmacologic and psychosocial interventions, for these comorbid disorders require thorough diagnostic evaluation to determine the extent of social, emotional, and behavioral impairments, severity of substance use, and motivation for change. Improved understanding of these comorbid disorders will inform treatment planning that address current symptoms and behaviors and may also prevent the development of mental health and substance use disorders in early adulthood.

Evaluation of the Regulatory Role of Circadian Rhythm Related Long Non-Coding RNAs in ADHD Etiogenesis

OBJECTIVE

ADHD is associated with increased sleep problems and circadian rhythm disturbances. This study aimed to examine ADHD patients and healthy controls in terms of chronotypic features and expression levels of CLOCK, PER1, lncRNA HULC, lncRNA UCA1.

METHOD

Eighty-three children were included (43 ADHD). Conner's Parent Rating Scale-Revised Short Form, Childhood Chronotype Questionnaire, Children's Sleep Disorders Scale were administered. Gene expression levels were studied from peripheral blood.

RESULTS

Evening chronotype, sleep initiation/maintenance disorder, sleep-wake transition disorder, excessive sleepiness disorder were higher in the ADHD group compared to the controls in the scales reported by the parents. Expression levels of all examined genes were statistically significantly higher in the ADHD group. There was no significant relationship between genes and sleep parameters in the ADHD group.

CONCLUSION

Our study provides the first evidence that lncRNA HULC and lncRNA UCA1 might have a role in the etiology of ADHD.

Sleep Disturbances in Children with Attentional Deficit Hyperactivity Disorder and Specific Learning Disorders

Sleep disturbances may be a significant source of distress for children with neurodevelopmental disorders, and consequently also for their families. Crucially, sleep disturbances might be influenced by comorbidity. Attention deficit hyperactivity disorder (ADHD) and specific learning disorder (SLD) often co-occur, and consequently, investigating sleep disturbances in children with comorbidity of ADHD and SLD is essential. Our study aimed at detecting sleep difficulties in a group of 74 children with ADHD, 78 children with SLD, and 76 children with ADHD and SLD by using the Sleep Disturbances Scale for Children. The results showed that sleep difficulties emerge more clearly in children with comorbid ADHD and SLD compared to children with only ADHD or SLD. These sleep difficulties were not due to differences in ages and behavioral/emotional problems. In conclusion, evaluating sleep disturbances is important when assessing and managing children with ADHD, SLD, and particularly with the two comorbid conditions, to better understand their difficulties and develop tailored interventions.

The Use of Drosophila to Understand Psychostimulant Responses

The addictive properties of psychostimulants such as cocaine, amphetamine, methamphetamine, and methylphenidate are based on their ability to increase dopaminergic neurotransmission in the reward system. While cocaine and methamphetamine are predominately used recreationally, amphetamine and methylphenidate also work as effective therapeutics to treat symptoms of disorders including attention deficit and hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Although both the addictive properties of psychostimulant drugs and their therapeutic efficacy are influenced by genetic variation, very few genes that regulate these processes in humans have been identified. This is largely due to population heterogeneity which entails a requirement for large samples. Drosophila melanogaster exhibits similar psychostimulant responses to humans, a high degree of gene conservation, and allow performance of behavioral assays in a large population. Additionally, amphetamine and methylphenidate reduce impairments in fly models of ADHD-like behavior. Therefore, Drosophila represents an ideal translational model organism to tackle the genetic components underlying the effects of psychostimulants. Here, we break down the many assays that reliably quantify the effects of cocaine, amphetamine, methamphetamine, and methylphenidate in Drosophila. We also discuss how Drosophila is an efficient and cost-effective model organism for identifying novel candidate genes and molecular mechanisms involved in the behavioral responses to psychostimulant drugs.

Relationship between sleep disorders and attention-deficit-hyperactivity disorder in children

OBJECTIVE

To explore the correlation between sleep disorders and attention-deficit-hyperactivity disorder (ADHD) in children.

METHODS

We studied 100 Chinese children (70 boys and 30 girls; mean age, 8.77 ± 2.39 years). Parents completed the Children's Sleep Disturbance Scale (SDSC) and the Swanson Nolan and Pelham Version IV Scale (SNAP-IV) questionnaires. SNAP-IV and SDSC scores were compared in children with and without sleep disorders and ADHD.

RESULTS

There were significant differences in SDSC scores, Arousal Disorder (AD) scores, and Sleep Breathing Disorder (SBD) scores between children with and without ADHD (P < 0.05). The sleep disorder group had higher SNAP-IV scores than the non-sleep disorder group (P < 0.05). Children with sleep disorders showed higher ADHD symptom values (inattention, hyperactivity/impulsivity, and oppositional defiance) than children without sleep disorders (P < 0.01). There was a moderate correlation between SDSC scores and SNAP-IV scores (r = 0.486, P < 0.05). Using SNAP-IV scores as the dependent variable, multiple linear regression analysis was applied, and a statistically significant effect of AD and Sleep-Wake Transition Disorder (SWTD) scores on SNAP-IV scores was found (P < 0.05). The area under the curve (95% CI) of the SDSC score for predicting sleep disorders with ADHD was 0.714 (0.606, 0.821; P = 0.0005).

CONCLUSION

Children with ADHD are prone to sleep disorders. The higher the ADHD symptom score, the more sleeping problems. Sleep disorders can also cause or exacerbate ADHD symptoms, and the ADHD symptom score correlates with sleep disorder severity. We can reduce the severity of attention-deficit-hyperactivity in children with ADHD by improving their sleep with behavioral sleep interventions.

Actigraphy-Derived Sleep Profiles of Children with and without Attention-Deficit/Hyperactivity Disorder (ADHD) over Two Weeks-Comparison, Precursor Symptoms, and the Chronotype

Although sleep problems are common in children with ADHD, their extent, preceding risk factors, and the association between neurocognitive performance and neurobiological processes in sleep and ADHD, are still largely unknown. We examined sleep variables in school-aged children with ADHD, addressing their intra-individual variability (IIV) and considering potential precursor symptoms as well as the chronotype. Additionally, in a subgroup of our sample, we investigated associations with neurobehavioral functioning (n = 44). A total of 57 children (6-12 years) with (n = 24) and without ADHD (n = 33) were recruited in one center of the large ESCAlife study to wear actigraphs for two weeks. Actigraphy-derived dependent variables, including IIV, were analyzed using linear mixed models in order to find differences between the groups. A stepwise regression model was used to investigate neuropsychological function. Overall, children with ADHD showed longer sleep onset latency (SOL), higher IIV in SOL, more movements during sleep, lower sleep efficiency, and a slightly larger sleep deficit on school days compared with free days. No group differences were observed for chronotype or sleep onset time. Sleep problems in infancy predicted later SOL and the total number of movements during sleep in children with and without ADHD. No additional effect of sleep problems, beyond ADHD symptom severity, on neuropsychological functioning was found. This study highlights the importance of screening children with ADHD for current and early childhood sleep disturbances in order to prevent long-term sleep problems and offer individualized treatments. Future studies with larger sample sizes should examine possible biological markers to improve our understanding of the underlying mechanisms.