Objective: Attention-deficit/hyperactivity disorder (ADHD) is a common neurobiological disorder for which effective and safe medication is recommended as first-line treatment. However, many parents and teachers do not believe that ADHD is a disorder or do not accept medication treatment in China. Treatment is often short term or intermittent. Our study aimed to investigate the clinical effect of employing a 4-week, session-based training for both parents and teachers in improving medication adherence for primary school children with ADHD.Methods: From January 2018 to December 2018, a total of 5,118 primary school children were screened. Among 211 children diagnosed with ADHD, 116 were assigned to the intervention group and 95 to the control group. This study provided systematic training for parents and teachers in the intervention group. The training consisted of education about the disorder and ADHD behavioral intervention for both parents and teachers as well as classroom management techniques for just the teachers. A cluster randomized controlled trial (RCT) was conducted to investigate the effect of this training at 6 months follow-up. The study determined medication adherence using a questionnaire and scoring with a rating scale at baseline and at the 6 month follow-up endpoint. The questionnaire was self-report.Results: The study population had a relatively low rate of attention deficit hyperactivity disorder (4.1%) compared to the generally accepted prevalence. After the training, more parents and teachers believed that ADHD is a neurobiological disorder and that medication is the first line treatment. At 6 months follow-up, the Medication Adherence Report Scale (MARS) score for the intervention group was 22.8 ± 0.75 and 16.5 ± 1.63 for the control group . Based on parents' reports and medical records, 82 children (70.69%) were continuously taking medication for 6 months in the intervention group, while only 35 children (36.84%) were doing so in the control group. In the intervention group, the mean SNAP-IV score was 1.98 ± 0.42 at baseline but 0.99 ± 0.31 at 6-month follow-up. In the control group, the mean SNAP-IV score was 1.89 ± 0.47 at baseline but 1.37 ± 0.42 at 6-months follow-up . Factors influencing medication adherence for children with ADHD were parent's beliefs, teacher's beliefs, socioeconomic status, adverse effect, insurance coverage, gender, and trust of the medical system.Conclusions: Our findings indicate that comprehensive training programs improve the understanding of ADHD and medication adherence for both children's parents and teachers, providing a promising approach for improving clinical efficacy for children with ADHD. Attention-deficit/hyperactivity disorder (ADHD) is a common neurobiological disorder, characterized by symptoms of overactivity, impulsivity, and inattention . ApproxiIn recent years, with the expectation and hope that early treatment will diminish poor mental health and psychosocial outcomes in adolescence and adulthood, ADHD interventions have largely targeted children of primary school age . In ChinHowever, many parents and teachers do not accept or continue medication treatment in China. They do not believe that ADHD is a neurobiological disorder or that medication is safe . For chiIn addition to parental decisions, teachers are an important part of children's school environments. Whether children's ADHD can be detected earlier depends to some extent on teacher beliefs about ADHD. In the clinical evaluation stage, doctors need to refer to teachers' opinions. In the treatment phase, medication dosing should also be adjusted according to teachers' feedback on school performances . TraininThis study was a cluster randomized controlled trial (RCT) to investigate the effect of parent and teacher training at 6 months follow-up. It consisted of three parts: ADHD screening and diagnosis, parent and teacher training, and evaluation of the effect of the training.A RCT was carried out at 10 primary schools (children aged 6–11 years) located in Putuo District, Shanghai, China. First, an invitation and information letter was sent to each school's in-house health care professional (iHCP) and the headmaster, informing them about the study. Hospital pediatricians conducted a meeting for both teachers and parents to introduce the purpose of this project and the type of intervention. Parents who wanted to participate were asked to complete and return the informed consent letter within 3 days.Students were enrolled in this study between January 2018 and June 2018. Conner's Parent Symptom Questionnaire (PSQ) and Conner's Teacher Rating Scale (TRS) were used for ADHD screening. Children whose results on both scales were positive received a call or a notification to have a pediatric examination in Shanghai Children's Hospital. Within 1 month of issuing the screening questionnaire, pediatricians identified 6- to 11-year-old children diagnosed with ADHD who also met inclusion or exclusion criteria. Hospital pediatricians sent a program invitation and informed consent form to the parents of these children. There were 116 children diagnosed with ADHD in the intervention group and 95 in the control group. A flow diagram of participants is shown in Children were diagnosed with ADHD according to the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5) , IQ ≥70 Exclusion criteria were allergy to methylphenidate or atomoxetine, comorbidity with autism spectrum disorder, schizophrenia, epilepsy, head injury, or verified neurological disorder, intellectual disability (IQ <70), sensory retardation (hearing/vision problems), and unwilling or unable to give consent. Both the intervention group and the control group were treated with medication. This study provided a multimodal treatment for patients and teachers in the intervention group.After the screening and diagnosis of students, the research team used a random number table method to divide the 10 primary schools participating in the study into the intervention group and the control group (5 schools in each group) stratified by school size. This occurred at the school, not at the class or individual level, in order to avoid contamination between individuals. Outcomes were obtained through questionnaires filled out by parents or teachers, and a limitation of the study is that teachers' and parents' assessment (questionnaires) are non-blinded. Statistical analysis was blinded to school intervention status when performing analysis of data results.Parent training involved 4 weekly 2-h sessions, delivered in primary schools and consisted of: (1) knowledge about ADHD: etiology, manifestation, harm, and treatments; (2) medication: side effects and how to deal with them, teaching parents how to evaluate their children's behavior with the SNAP-IV scale; (3) teaching parents behavioral strategies to manage conduct problems, typically apply principles of positive and negative reinforcement; and (4) teaching parents to combine procedures and behavior management techniques, which can constructively target impairments in underlying processes, such as attention, impulse control, self-regulation, and working memory .Teacher training involved 4 weekly 2-h sessions, delivered in primary schools and conducted simultaneously with parent training. The teacher training was delivered in primary schools and conducted concurrently with parent training. It consisted of: (1) knowledge about ADHD: etiology, manifestation, harm, treatment, and follow-up; (2) behavioral strategies to manage conduct problems, typically applying principles of positive and negative reinforcement; (3) classroom behavior management; (4) teaching teachers how to use scaffolding to promote the development of self-regulation in children with ADHD, and how to take on the role of skilled tutor to create settings and occasions in a positive emotional climate, which can produce playful and reciprocal interactions .When we designed training for parents and teachers, we referred to Family School Success (FSS) and simplified it. FSS is an integrative and novel psychosocial intervention for children with ADHD, which combines components of efficacious interventions to improve children's behavioral and academic functioning at home and school settings . FSS aimT-test was used for continuous variables and chi-square tests for categorical variables between the intervention group and the control group. Multiple regression models were created in which the scores of the total MARS were used as dependent variables.The Statistical Package for the Social Sciences (SPSS) 21.0 was used. Descriptive statistics, means, standard deviations and frequencies were calculated. PSQ is used to assess ADHD symptoms in primary school patients. It is a 48-item, parent-reported questionnaire using a four-point scale ranging from 0 to 3 and six subscales: conduct problems, learning problems, psychosomatic, hyperactivity–impulsivity, anxiety, and ADHD index . If the TRS is a widely used instrument for evaluating behavioral problems in children and adolescents. It contains a 28-item teacher-reported questionnaire using a four-point scale ranging from 0 to 3 and four subscales: conduct, hyperactivity, inattention, and ADHD index . If the The Medication Adherence Report Scale (MARS) questionnaire is used to assess adherence to prescribed medication, which includes five statements using a five-point scale ranging from 1 to 5. One statement is related to the subscale of unintentional non-adherence (forgot to take them) and four statements are related to intentional non-adherence behaviors  . Higher The Chinese Version of Swanson Nolan and Pelham, Version IV Scale (SNAP-IV) is used as the measure for the severity of ADHD symptoms. It consists of 26 items using a four-point scale ranging from 0 to 3 and three subscales: inattention, hyperactivity, and impulsivity . The priFrom the 5,118 children who completed the screening questionnaire, 335 (6.55%) were positive from the screening. From those children, 230 (68.66%) were physician- diagnosed with ADHD. However, 19 students were excluded: 5 had intellectual disability, 1 dropped out of school, and 13 declined to participate in this study. One hundred sixteen children were assigned to the intervention group, and 95 were assigned to the control group.P > 0.05).Among parents, only 29.2% believed that ADHD was a neurological disorder before training, while after training, 60.3% believed that. In addition, only 20.2% believed that medication was the first-line treatment for ADHD before training, while after training, 60.3% believed that. Among teachers, only 45.4% believed that ADHD was a neurological disorder before treatment, while after training, 75.1% believed that. Before training, only 32.6% believed that medication was the first line-treatment for ADHD, while after training, 67.3% believed that. The differences were statistically significant . BeliefsSD = 0.75), while it was 16.5 (SD = 1.63) for the control group , as shown in A statistically significant difference was found in adherence measured by MARS. The MARS score for the intervention group was 22.8 .Taking medication continuously for 6 months based on parents' reports and medical records was considered good medication adherence. In the intervention group, there were 82 children (70.69%) continuously taking medication for 6 months, while in the control group, there were only 35 children (36.84%) . The difMultiple regression analysis was used to determine the factors influencing medication adherence. They were parent beliefs, teacher beliefs, socioeconomic status, adverse effects, insurance coverage, gender, and trust of the medical system .F = 2.67, P = 0.009), as shown in In the intervention group, the SNAP-IV score was 1.98 ± 0.42 at baseline, while it was 0.99 ± 0.31 at 6-month follow-up. In the control group, the SNAP-IV score was 1.89 ± 0.47 at baseline and 1.37 ± 0.42 at 6-month follow-up. The difference of SNAP-IV score changes between the two groups was statistically significant  nor child-specific , which weakened the interpretation of results. Risk factors identified to contribute to medication adherence were not validated because statistical results from multiple regression showed that OR value for insurance coverage only passed 1. Finally, information regarding the medication management of children in this study, both in the intervention and control groups, was not provided regarding changes in doses or medications utilized.Our study employed 4-week, session-based training for both parents and teachers and determined the medication adherence with questionnaire and score of rating scale baseline and endpoint of 6-month following up. The findings from our study indicate that comprehensive training programs improve the knowledge of ADHD and medication inherence for both children's parents and teachers, providing a promising approach for improving clinical efficacy for children with ADHD.All datasets generated for this study are included in the article/The studies involving human participants were reviewed and approved by Ethics Committee of Shanghai Children's Hospital. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.XZ, GY, and YW contributed to the conception, data analysis, and writing. LJ contributed to the data analysis and editing of the manuscript. LS, XS, and YX contributed to the data analysis. All authors approved of the final submitted version of this manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


This study aimed to examine whether endocrine-disrupting chemicals (EDCs), such as phthalates, para-hydroxybenzoic acids, and bisphenol-A (BPA), affect gonadal hormones and further link to the susceptibility to attention-deficit/hyperactivity disorder (ADHD). We recruited 98 boys with ADHD, 32 girls with ADHD, 42 boys without ADHD and any other psychiatric disorders, and 26 girls without ADHD and any other psychiatric disorders. Urine levels of EDCs, including mono-methyl phthalate (MMP), monoethyl phthalate (MEP), mono-n-butyl phthalate (MnBP), monobenzyl phthalate (MBzP), monoethylhexyl phthalate (MEHP), methylparaben (MP), ethylparaben (EP), propylparaben (PP), butylparaben (BP), and bisphenol A (BPA), were examined. Endocrine systems were evaluated by using the serum levels of follicle-stimulating hormone (FSH), luteinizing hormone (LH), testosterone, free testosterone, estradiol, progesterone, sex hormone-binding globulin (SHBG), and prolactin. We found that boys with ADHD had higher levels of MnBP and EP than control boys. There were no significant differences regarding EDCs between the females with ADHD and control groups. No significant differences in testosterone, free testosterone, FSH, LH, estradiol, progesterone, or SHBG were found between the ADHD group and controls among either boys or girls. Among boys with ADHD, urine MBzP and MEHP levels were positively correlated with serum testosterone levels. Among girls, urine MEP levels were positively correlated with serum LH, testosterone, and free testosterone levels. The findings suggest that the possibility of an adverse impact of EDCs on gonadal hormones and neurodevelopment may exist. However, the results could be subject to potential selection bias, and the findings in this study should be interpreted with caution. Attention-deficit/hyperactivity disorder (ADHD) is among the most common psychiatric disorders among school-aged children and adolescents. The prevalence of ADHD of school-age children are estimated as 5–10% ,3. ADHD Endocrine-disrupting chemicals (EDCs) are chemicals that can interfere with endocrine  systems at certain doses . EDCs caAmong the EDCs, phthalates, para-hydroxybenzoic acid (paraben), and bisphenol A (BPA) had been reported to exert neuropsychiatric adverse effects. A case-control study conducted in China revealed that child exposure to phthalates may contribute to ADHD and related behavior problems . A recenIn addition to the impact of EDCs, gonadal hormones also play a major role in the organization of the brain and behavioral systems . GonadalNo study has yet performed a comprehensive investigation of the associations between EDCs and gonadal hormones in children with ADHD. Prevalence and pathophysiology may be distinct between boys and girls with ADHD, so we hypothesized that EDCs and gonadal hormones influence susceptibility to ADHD. To clarify this, we conducted a cross-sectional study to examine whether the aforementioned EDCs and gonadal hormones demonstrated differential levels between ADHD patients and healthy controls in both boys and girls. We further examined hormones as intermediates in the analysis given the endocrine disruption nature of these chemicals.For this study, we recruited children with ADHD who were treated in the outpatient Department of Child Psychiatry at Kaohsiung Chang Gung Children’s Hospital in Taiwan, whose parents and/or guardians rendered written consent forms, and who met the following criteria: (a) kids with clinical diagnosis of ADHD by a senior child psychiatrist based on the criterions of Diagnostic and Statistical Manual of Mental Disorders (DSM–5) ,29; (b) Control subjects were recruited from the same geographic area as the ADHD patients. They were children who did not have ADHD or any other psychiatric disorders . In total, we recruited for this study 98 boys and 32 girls with ADHD in addition to 42 boys and 26 girls as controls.About 1.0 mL of urine sample was taken and enzymatically hydrolyzed and purified through solid phase extraction. The phthalate metabolites in the urine were then divided by reverse-phase ultra-performance liquid chromatography and identified by the electrospray ionization tandem mass spectrometry and quantified using an isotope internal standard curve method .We purchased HPLC-grade ethyl acetate from Duksan Pure Chemicals and ammonium acetate (97.0% powder) from Merck. β-Glucuronidase  from Helix pomatia (Type H-2) was obtained from Sigma–Aldrich . Urine samples were embattled with 50 µL of internal standard  spiking solution, 1 mL of 2 M ammonium acetate buffer solution (1.54 g of ammonium acetate/10 mL HPLC-grade water), and 20 µL of β-Glucuronidase. Samples were incubated for 1 h at 37 °C, extracted twice with 4 mL of ethyl acetate, gently shaken a few times, then the organic layer was separated from the non-polar fat layer with a centrifuge at 4000 rpm for 15 min. We performed the chromatographic separation on a Shim-pack GIST C18 column  from Shimadzu Co. Ltd. Target compound was performed with a Shimadzu 8050 Triple Quad liquid chromatograph mass spectrometer equipped with a Shimadzu LC-30 series HPLC system. The following EDCs were identified in this study: mono-methyl phthalate (MMP), monoethyl phthalate (MEP), mono-n-butyl phthalate (MnBP), monobenzyl phthalate (MBzP), monoethylhexyl phthalate (MEHP), methylparaben (MP), ethylparaben (EP), propylparaben (PP), butylparaben (BP) and bisphenol A (BPA). Limits of quantitation (LOQ): 0.8 ng/mL for MMP, 1.0 ng/mL for MEP, 0.8 ng/mL MnBP, 0.8 ng/mL for MBzP, 0.8 ng/mL for MEHP, 1.0 ng/mL for MP, 1.0 ng/mL for EP, 1.0 ng/mL for PP, 1.0 ng/mL for BP, and 1.0 ng/mL for BPA. Limits of detection (LOD) were ≤0.5 ng/mL for all compounds. The between-day imprecision (relative standard deviation) ranged from 3.6 to 8.7%, and the mean relative recoveries ranged from 75.2 to 121.5%.Blood samples were collected from the participants in the morning after an overnight fasting to detect the serum levels of follicle stimulating hormone , luteinizing hormone , estradiol, progesterone, testosterone, free testosterone, SHBG, and prolactin using an electrochemiluminescent immunoassay on a DPC Immulite 2000 XPi device  . AnalytiTo confirm the ADHD diagnosis based on the DSM-5 criteria, a senior psychiatrist interviewed those ADHD patients and control subjects. Moreover, an experienced child psychologist conducted the Wechsler Intelligence Scale for Children—Fourth Edition (WISC-IV). Parents and teachers of each patient were asked to fill out the SNAP-IV  scale parent form and the SNAP-IV teacher form, respectively.The WISC-IV is an individually administered and standardized test tool designed to determine the intelligence of kids aged 6–16 years . It consThe SNAP-IV, a 26-item questionnaire, is used to assess the symptoms and severity of ADHD, which needs to be completed by parents or teachers . These 2p-values of less than 0.05 were considered statistically significant.The statistical software package SPSS, version 21.0  was used to analyze the data and present variables as either statistical means (standard deviation) or frequency. Two-tailed t-test to compare continuous variables between ADHD patients and healthy controls in both boys and girls. Endocrine-disrupting chemicals and gonadal hormones all demonstrated significant levels of positive skewness. We adopted arithmetic log transformations to establish approximate normal distributions for these levels.We adopted the independent We used the general linear model to assess the differences of endocrine-disrupting chemicals and gonadal hormones between ADHD and controls, setting age, urinary creatinine levels, and specific gravity as covariates. Partial correlation (age as the covariate) was used to determine the associations of EDCs with gonadal hormones and clinical measurements among boys and girls with ADHD, respectively.Included in our study  were 98 p = 0.014) and PP levels (p = 0.032). However, we observed no significant differences regarding EDCs between the female with ADHD and control groups. n = 98) and ADHD girls (n = 32). Among boys, we controlled for the confounding effect of age and found that urine MBzP levels  and MEHP levels  positively correlated with serum testosterone levels. And urine MEHP level was also positively correlated with serum prolactin level . Among girls, urine MEP levels were positively correlated with serum levels of LH , testosterone , and free testosterone . And urine BP level was also positively correlated with serum LH level .The associations between EDCs and ADHD clinical measures and gonadal hormones were analyzed separately for ADHD boys , hyperactivity/impulsivity symptoms rated by teachers , and oppositional symptoms rated by teachers . Among girls with ADHD, serum LH levels were positively correlated with oppositional symptoms rated by teachers . Serum levels of FSH were positively correlated to hyperactivity/impulsivity symptoms rated by parents  and negatively correlated to inattention symptoms rated by teachers . The correlation matrix between EDCs, hormone levels, and ADHD characteristics are listed in Among ADHD boys, serum prolactin levels were negatively correlated with oppositional symptoms rated by parents , belongs to the group of phthalates. Phthalates serve as plasticizers to make plastics more flexible and are widely used in the production of polyvinyl chloride (PVC) products, food packaging, medical devices, cosmetics, and personal care products . The finEP (PP ?), a paraben, is a bacteriostatic and fungistatic agent used as a preservative in personal care products, pharmaceuticals, and foods . RegardiBPA has been widely used in various consumer products, including plastics products, personal care products, and thermal receipt paper . In our The results of this study showed no significant differences in testosterone, free testosterone, FSH, LH, estradiol, progesterone, or SHBG between the ADHD group and the control group, which is compatible with previous findings ,28,50. IIt is noteworthy that several EDCs chemicals were significantly associated with endocrine substrates. Among boys with ADHD, urine MBzP and MEHP levels were positively correlated with serum testosterone levels, and urine MEHP level was also positively correlated with serum prolactin level. Among girls, urine MEP levels were positively correlated with serum LH, testosterone, and free testosterone levels, and urine BP level was also positively correlated with serum LH level. In addition, levels of endocrine substrate were significantly correlated to ADHD characteristics. We suppose that EDCs had an adverse impact on the endocrine system, and further link to ADHD characteristics.This study has several limitations. First, this study was a cross-sectional study, and the time effect of exposure and amount of EDC exposure on brain development were undetermined. EDC exposure at different life stages and differences in the amount may have led to different results. Moreover, because children affected by ADHD have a shorter life expectancy , ADHD chThe results suggest that MnBP and EP levels were higher in boys with ADHD than in their counterparts. Furthermore, several EDCs chemicals were significantly associated with endocrine substrates. EDCs may be involved in susceptibility to ADHD, particularly among boys. According to the results in this study, the possibility of an adverse impact of EDCs on neurodevelopment may exist. However, the results could be subject to potential selection bias, and the findings in this study should be interpreted with caution.


Attention deficit hyperactivity disorder (ADHD) is the most commonly diagnosed neurodevelopmental disorder in childhood. It is a heterogeneous disorder in terms of clinical presentation that is probably due to the frequent occurrence of comorbidity. Children with ADHD more frequently report sleep disorders (notably delayed sleep phase syndrome) and excessive daytime sleepiness (EDS) than typically developing children. The aim of this article is to propose a narrative review of the assessment of EDS in the context of ADHD with first a summary of the subjective and objective tools used to measure it. Secondly, perspectives in terms of electroencephalogram (EEG) markers and neurofeedback are proposed. Then, possibilities for new kinds of evaluation are discussed . Lastly, we discuss specific clinical situations with EDS in the context of ADHD as links with narcolepsy, the comorbidity with other psychiatric disorders, and the context of sluggish cognitive tempo. Attention deficit hyperactivity disorder (ADHD) is the most commonly diagnosed neurodevelopmental disorder in childhood with a worldwide estimated prevalence of about 5% . It is cSleep disorders have been extensively investigated in patients with ADHD, and their prevalence is reported to be in the range of 25–55% –6. ChildThe most dominant sleep disturbance observed in patients with ADHD is delayed sleep phase syndrome (DSPS) associated with difficulties in falling asleep, difficulties in awakening, and/or excessive daytime sleepiness (EDS), characterized by difficulties in maintaining adequate alertness for daily activities with sleep occurring unintentionally or at inappropriate times almost daily.Children with ADHD report EDS and more sleep problems than typically developing children . Other sThe aim of this article is to propose a narrative review of the assessment of EDS in the context of ADHD with first a summary of the subjective and objective tools used to measure it. Secondly, perspectives in terms of electroencephalogram (EEG) markers and neurofeedback are proposed. Then, possibilities for new kinds of evaluation are discussed . Lastly, we discuss specific clinical situations with EDS in the context of ADHD as links with narcolepsy, the comorbidity with other psychiatric disorders, and the context of sluggish cognitive tempo (SCT).We used the following search strategy. We considered papers examining the assessment of EDS in ADHD children. Only data published in English were included. We conducted a narrative review using the PubMed database up to June 2019 with the following keywords combination: “ADHD children” and  and “assessment”. For perspectives, the search in PubMed used the following keywords: “ADHD children” and  or “neurofeedback”.The clinical expression of EDS in children is very variable and differs from that exhibited by adults. Sleepiness can occur intermittently, often during passive activities such as reading and watching TV. At first, sleepy children may exhibit inattention, hyperactivity, or behavioral problems. This clinical presentation may mimic a patient with ADHD, which raises the issue of the differential diagnosis.A clinical detailed history is crucial for the initial evaluation of a child with EDS , 21. FirIn the event of ADHD, it is important to explore the clinical history of the sleep symptoms and compare it with the prescription of stimulants. In fact, stimulants can induce insomnia but also can improve sleep disorders in the context of ADHD. Moreover, in a subgroup of children with ADHD taking methylphenidate, EDS increased a few hours after taking it. The study by Cockcroft K  showed tThe physical examination is often normal in children with EDS. This examination can provide indications on sleep disorders such as sleep-disordered breathing in children, as in those with adenoid facies.There is no specific questionnaire to assess sleepiness for children with ADHD. The questionnaires adapted for children can be used in patients with ADHD.Even if EDS is a frequent symptom in sleep disorders, validated tools in pediatric populations are lacking. Three clinical rating scales have been used to assess sleepiness specifically: the Stanford Sleepiness Scale , the EpwThe Pediatric Daytime Sleepiness Scale (PDSS) is a validated measure for assessing daytime sleepiness in children. It was developed to assess EDS in young school-age populations. It is an eight-item questionnaire evaluating subjective experiences of daytime sleepiness (items are scored from 0 to 4). Scores range from 0 to 32 .The Teacher’s Daytime Sleepiness Questionnaire (TSDQ)  is a teaThere are other questionnaires that assess sleep in children. In these questionnaires, some questions concern sleepiness. The most frequently used questionnaires are the following: the Sleep Disturbances Scale for children  with th, the CleThe Multiple Sleep Latency Test (MSLT) is the recommended test to assess objective sleepiness both adults and children . This teAs stated in these guidelines : “The MSActigraphy monitors rest/activity cycle by integrating the occurrence and degree of arm movement activity over time. It provides information about daytime activity, night/sleep activity  and activity circadian rhythm. This information can be useful in assessing sleep problems in adolescents with ADHD, especially to determine sufficient and insufficient sleep duration or stability or variability in sleep/wake patterns , 42. MarSleepiness can be evaluated objectively by power density of waking EEG. The sleepier the subject, the more alpha (8–12 Hz)  and/or tIn children and adolescents with ADHD, the most dominant waking EEG features are increased power of slow waves and/or decreased power of fast waves recorded in resting state and over the fronto-central region in comparison with healthy children/adolescents [reviewed in –50]. TheThis increase in theta band activity can reflect sleepiness  and/or cOther studies have investigated the TBR . InThe review by Newson , which iThe heterogeneity in the EEG characteristics of these children could be related especially with the heterogeneity of the clinical profiles of ADHD. Already in 1996, Chabot and Serfontein  demonstrClarke et al.  identifiLoo et al. , in a laThe results analyzing resting state cortical activity in patients with ADHD are very heterogeneous, and the identification of distinct EEG subgroups is not consensual. Nevertheless, since EEG analysis is considered to be the gold standard to quantify sleepiness, evidence is accumulating of a subgroup of patients characterized by cortical hypoarousal.In a different approach, the group of Hegerl , 70 usinDespite years of research and the identification of clusters, quantitative EEG is not helpful in classifying ADHD patients and cannot be considered as a diagnostic biomarker for ADHD. However, the identification of EEG subgroups may help to optimize treatments  and/or measure the response to them. Indeed, stimulant treatment was more efficient in the hypoarousal subgroup  or unstNeurofeedback training (NFT) analyzes EEG activity and transforms it into instant feedback  received by the user. By learning, the user self-regulates the amplitude of specific EEG activity. Neurofeedback is considered a non-pharmacological treatment option for ADHD .The efficacy of NFB for children with ADHD is controversial. Meta-analyses published in the past decade have been contradictory i.e., –78. For Arousal and attention are heterogeneous processes that interact with each other .On one hand, attention corresponds to the appropriate allocation of processing resources to relevant stimuli. Attention is sub-divided into: (a) attentional orientation (the simple direction of attention to a particular stimulus); (b) selective (or focused) attention ; (c) divided attention (dividing attention between two or more different stimuli); and (d) sustained attention (attending to one stimulus over an increasing period of time). On the other hand, arousal can be defined as the state of physiological reactivity, ranging on a continuum from sleep to alert wakefulness. Sleepiness increases the probability of the transition from wakefulness to sleep.The arousal level controlled by homeostatic sleep pressure and the waking systems has repercussions on the attentional system, which modulates cognitive components such as executive functioning. The fundamental biological rhythm of sleep/wakefulness controlling the level of arousal is essential for maintaining optimal brain functions. Normal sleep ensures alert wakefulness, which is essential for appropriate decision-making and optimal adaptation to the environment, and is beneficial for global cognition .via the modulation of the level of vigilance. Vigilance is a state of high efficiency of the central nervous system and is considered in a behavioral perspective as sufficient preparedness to detect and respond to critical events that occur rarely, and which are difficult to discriminate in extremely monotonous situations   . Vigilanvia modulation of attention also impacts executive functions. Executive functions govern all cognitive functions necessary to control and execute complex non-routine activities , including by measuring these functions when performing complex activities of daily living. The measurement of the level of sleepiness could be considered from a physiological to a psychological–behavioral sphere.Neuropsychological assessment, notably involving vigilance, could be informative about the level of sleepiness. Calhoun, Fernandez-Mendoza, et al.  showed, An innovative approach could be to use the technology of virtual reality to determine the level of sleepiness as a function of cognitive alteration in ADHD children and adolescents immersed in the ecological tasks of everyday life. A study using a simulated driving task showed that not only the objective level of alertness but also inhibitory control deficits contribute independently to highway driving impairment in adults with ADHD . VirtualAnother innovative approach could be the use of EMA to evaluate daily and diurnal variations in sleepiness and repercussions on daily life such as in the emotional, cognitive, behavioral, social, and physical domains , 92 in AThe links between ADHD and sleep disorders remain unclear. While specific sleep disorders are a frequent comorbid condition associated with ADHD according to a categorical approach, they can also induce ADHD-like symptoms if considered dimensionally and are thought to be the consequence of EDS. Given the complexity of the interaction between ADHD and sleep, the team of Miano –95 identNarcolepsy, which is characterized by EDS and abnormal REM sleep, is a chronic sleep disorder caused by a deficiency of hypocretin/orexin-producing neurons within the lateral hypothalamus (type 1 narcolepsy with cataplexy). In type 2 narcolepsy, where cataplexy is absent and orexin levels normal, the physiopathology is unknown. The “narcolepsy-like” phenotype (ADHD and hypersomnia) described by Miano could be part of a subtype of type 2 narcolepsy . A body In addition, adult narcoleptics present more childhood ADHD than controls , 101. UsMoreover, high levels of EDS and shorter REM latency are classically both potential signs of narcolepsy . In the “Sluggish cognitive tempo” (SCT) is a behavioral construct characterized by a set of symptoms as sluggish, under-motivated, lethargic, slowed, and/or forgetful behavior , 107. ThMoreover, SCT is strongly associated with internalizing symptoms, especially depressive symptoms. It is important to evaluate sleep in the context of comorbidity , as mentioned by Spruyt  and by DIn conclusion, ADHD is a heterogeneous disorder in terms of its clinical presentation and underlying physiopathological mechanisms. EDS, a usual complaint in children with ADHD, seems to be a pertinent clinical dimension. Thus, the identification of a specific “sleepy ADHD” phenotype appears to be both a clinical and objective maker. The identification of EEG subgroups would help in defining various phenotypes and optimizing treatments. More studies are needed in children with ADHD to assess EDS. The interactions between EDS and the attentional process and executive functions should also be probed.Introduction and Assessment of Sleepiness in Children of the manuscript. JT wrote section Perspectives in Terms of Evaluation of Sleepiness With EEG Characteristics and Related Treatment of the manuscript. PS wrote section Neuropsychological Markers: Links Between Attention and Sleepiness of the manuscript. PP wrote the Introduction and did a rereading of the manuscript. All authors contributed to manuscript revision, read and approved the submitted version.SB wrote sections The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The aim of this study was to assess cognitive differences between male and female adults with Attention Deficit Hyperactivity Disorder (ADHD).Patients with an ADHD diagnosis according to the DSM-IV guidelines were included in a cross-sectional study evaluating cognitive measures. 28 women and 41 men from ages 19 to 56 completed self-report questionnaires and performed a computer-based test of attentional performance (TAP). The TAP assesses cognitive functions highly affected in ADHD patients, including working memory, alertness and attention as well as behavioral control and response inhibition.There were no measurable differences in self-report scales assessing current symptomology between the sexes, however men scored higher on the scale for childhood symptoms. Performance measures for general wakefulness were comparable between men and women, while working memory and behavioral control test results differed. Females reacted significantly slower and more unstable for both the TAP Go/NoGo paradigm and working memory subtest, while also making more errors in the latter.We found gender-specific effects regarding working memory and behavioral control in this sample of adult patients with ADHD. Further studies are warranted, examining whether these differences relate to differences in clinical presentation and comorbidity patterns between men and women. Although historically viewed as a childhood mental disorder, Attention Deficit Hyperactivity Disorder (ADHD) is now recognized as a dysfunction affecting a considerable number of adults, with a prevalence of 2–5%, depending on the population , 2. DireA distinctive feature of ADHD in children is the high ratio of affected boys vs. girls. Several studies published in the last 20 years showed prevalence differences ranging from 1:1.8 to 1:16 of girls to boys –10. NotaAlong with different symptom presentations, different patterns of comorbidity have also been observed. Males are more likely to experience “externalizing” disorders ,et al. in 2009 summarized 25 studies conducted from 1993 to 2007 and concluded that attentional problems of the ADHD groups was directly associated with higher proportions of men in the group [The heterogeneous characteristics between females and males mentioned above raise the question of possible differences in cognitive function. The cognitive areas that are most notably affected in ADHD patients include sustained and focused attention, working memory, inhibitory control and response inhibition , 25–28. he group . Convershe group , 31, whihe group  and supphe group . Intereshe group . Howeverhe group , 33–35. In this explorative study, we aimed to determine whether these observable symptom differences could be measured via standard assessment tools used in our clinic. Our primary objective was to find potential differences between women and men with ADHD in self-report symptom scales and attentional capabilities, assessed by a computer-based attentional performance test. Our secondary objective was to assess correlations between these two measures to find out whether certain symptoms might influence specific areas of cognition.The long-term goal of these explorations is to use these findings to assist clinicians in better diagnosing adults with ADHD, with special attention to specific gender features, especially for patients with high comorbidities or unclear symptomology.Outpatients with clinically defined ADHD, according to the DSM-IV, were recruited during visits at the ADHD outpatient clinic for adults of the University Hospital Leipzig, Germany. During these visits, experienced psychiatrists and psychologists examined patients’ mental status and obtained their clinical history. Structured clinical interviews and rating scales were applied to confirm the clinical diagnosis of ADHD.At screening, ADHD diagnosis was confirmed using both the standardized German version of the ADHD self-rating behavior questionnaire  and theWortschatztest , was ap69 patients  were included into the study. All of the patients identified as cisgender men and cisgender women, respectively. Therefore, we use the terms ‘gender’ and ‘sex’ interchangeably throughout the text. Written informed consent was obtained from all participants prior to any tests and the study was approved by the local ethics committee of the University of Leipzig (EC numbers 199-13-15072013 and 155/15-ff).For a more thorough assessment of symptomology, the long version of the Conners’ Adult ADHD Rating Scale  was appSecondly, in order to measure attentional deficits more objectively, the computerized Test of Attentional Performance  was use2) was used to investigate gender differences  in educational degree as well as marital and smoker status. For other metrical variables, the independent sample t-Test was used to test for differences between groups based on gender. As the differences for age and other demographical variables between females and males (see 2) in case of categorical variables to assess potential differences in cognition measured by the CAARS and TAP.The Pearson chi-square test . The significance level for all tests was set at p<0.05.In No explicit testing for intellectual capacity was performed, however when using educational degree as an indicator, a balanced level of intellect can be assumed. The same proportion of patients, approximately 85% of each group, attended either a higher secondary school or high school see .p = 0.056, see The only exception in baseline characteristics was the WURS-k scale, with men scoring higher than women. This represents an increased report of occurrence and severity of ADHD symptoms in the male subjects’ childhood compared with the female group. This difference almost reached significance (p ≥ 0.251) (see p ≥ 0.143) between genders for subjects with T scores above 60 in each of the subscales  see . There wales see .In the alertness subtest of the TAP, general wakefulness is measured, which did not differ between males and females see .p = 0.370 and p = 0.244, respectively). However, the results for median reaction time (p = 0.035) and standard deviation (p = 0.033) as well as the number of errors (p = 0.043) were significantly higher in females. These results indicate slower and more unstable reactions in the female group, who also made more errors.In the TAP subscale assessing working memory, correct responses and measures for omissions did not differ between males and females (p = 0.234) and omissions (p = 0.791), the median reaction time was significantly slower in women compared with men  were associated with cognitive performance, we used a correlation analysis. There were two significant correlations measurable between self-reports and performance tests see .p = 0.021), suggesting that an increase in depressive symptoms leads to a higher number of errors in the test. After correcting for gender impact, this correlation still showed the approximate same level of significance , suggesting that gender only has a minor or negligible effect. In other words, depressive symptoms worsen the accuracy of the impulse control test Go/No Go, regardless of the patient’s gender.The BDI correlated negatively with errors in the Go/No Go subtest of the TAP . The correlation was not as significant when gender influence was corrected . This suggests that increased hyperactivity and impulsivity leading to a more unstable reaction in phasic alertness might be partly influenced by gender.The subscale for hyperactivity and impulsivity on the CAARS questionnaire had a negative correlation with the standard deviation of the phasic alertness subtest of the TAP  using self-report scales like the ADHS-SB , ASRS 3, WURS-k Interestingly, in the first part using scales that rely on the self-assessment of current symptomology, namely the ASRS, ADHS-SB and CAARS, did not differentiate between women and men. To this date, there is no consensus regarding gender differences in symptom severity in adults, as some studies have concluded that no differences exist , 43–45, The only scale that differed between men and women in our results was the WURS-k, focusing on reports about symptoms during patients’ childhood, with men scoring significantly higher than women. These results are in line with a previous study comparing male and female ADHD patients  and coulet al. from 2013 observed a significant impairment of women in measures for inattention in a study comparing 55 ADHD patients [In the second part, we objectified core symptoms such as inattention, impulsivity and hyperactivity by measuring performance on the computerized subtests working memory, alertness and the Go/No Go of the TAP . In our patients .et al. published in 1998, which suggested a better score for women than men [et al. however was confirmed by our findings, as the group also saw significantly better measures of working memory for men over women. Notably, the group also analyzed whether presentations could explain cognitive performance differences, but found no such association between ADHD presentation and working memory deficits [et al. examined the neural activation of adult ADHD patients by performing functional MRI (fMRI) scans while the patient performed working memory tasks. The results indicated that compared to same sex controls, ADHD males had less neural activation than females. Moreover, they found negative correlations between hyperactive symptoms in men and inattentive symptoms in women, suggesting a difference in presentation between the sexes [On the other hand, we saw significant differences in working memory and impulse control results. Female patients had significantly lower measures for reaction time in the working memory subtest, with a less stable reaction. Moreover, women made more errors than men. These results are in contrast to early studies from Katz than men  measuredthan men , 62. A mdeficits . With a he sexes .et al. observed faster reactions in males than females in a Go/No Go task, while accuracy was similar for both groups, which is in accordance with our results [The second TAP subtest that yielded differences between sexes in our study, was the Go/No Go subtest with women again reacting significantly slower and less stable than men. Deficits in inhibitory control are deemed a core symptom of ADHD, so much so that it has been studied as a differentiating diagnostic marker between Autism spectrum disorders and ADHD . Other g results .We can only speculate as to why women in our study population did not perform as well in these TAP subtests. One explanation could be that women with ADHD may have problems with maintaining concentration over extended periods of time, which may be supported by the fact that the inattentive presentation is more common among women. The TAP tests were completed in order of increasing complexity: alertness; Go/NoGo; working memory. Particularly in a stress-inducing situation like a computer performance test, this might have resulted in worse performance for women in the latter, more complex tasks. Some preclinical studies also linked stress stimuli to hyperarousal in females, which could have led to wrong actions and less stable performance in the TAP tests . Anotheret al. reported similar executive deficits seen in children with the inattentive and combined presentation [Lastly, we performed correlation analyses of the performance-based and self-report scales. In a first step we did Spearman rank correlation analyses for all tests. In case of a significant result, we corrected these correlations for gender effects in a second step to see whether the result would change. Only two correlations between self-report and performance tests were significant. While the higher scores on the BDI led to more errors in the Go/No Go subtest, the CAARS Hyperactivity/Impulsivity subscores correlated with decreased stability of the phasic alertness subtest. Only the latter seemed to be slightly influenced by gender, while impulse control was solely dependent on the severity of depressive symptoms. Taken together, it seems self-reported symptoms such as hyperactivity and inattention did not automatically worsen performance in either women or men, with the exception of the CAARS hyperactivity/impulsivity subscale indicating a less stable wakefulness on a given cue and the BDI leading to more errors when assessing impulse control. These correlations were only partly influenced by gender and rather suggest a connection to the presentation of ADHD. As a previous study in children suggested, the predominant symptom is more indicative of cognitive performance than the gender itself . Anotherentation . To our Limitations of this study include the lack of control of the possible influence of pharmacotherapy and psychotherapy on the cognitive performance of ADHD patients and the unbalanced numbers of men vs. women in an overall small sample size, making it impossible to generalize our findings. The measures used were also reliant on a subject`s self-assessment. Moreover, we did not differentiate between presentations and a control group of healthy subjects was not included in the analysis to compare gender effects in the general population.In summary, our results indicate that women and men with ADHD may differ in cognitive capacities, with women being more impaired than men in working memory and impulse control. Whether these effects are comparable to gender differences and hormonal influence in the general public, as shown by other studies , 75, or There is, however, certainty that the cognitive performance of ADHD patients varies depending on comorbidities and presentation characteristics , 50, whiS1 Table(XLS)Click here for additional data file.S2 Table(XLS)Click here for additional data file.


This study examined the levels of agreement between the reports of 207 adolescents with attention-deficit/hyperactivity disorder (ADHD) and their parents regarding the adolescents’ callous–unemotional (CU) traits and investigated the factors influencing adolescent–parent agreement. Adolescent–parent agreement about CU traits in three dimensions according to the Chinese version of the Inventory of Callous and Unemotional Traits was examined. The influence of demographic characteristics, comorbid conduct disorder (CD), oppositional defiant disorder (ODD), and ADHD symptoms on adolescent–parent agreement was also examined. The results indicated that adolescent–parent agreement on the CU trait of uncaringness was moderate, whereas agreement on the CU traits of callousness and unemotionality was poor. Adolescent–parent agreement on the three dimensions of CU traits varied depending on the adolescents’ sex and comorbid CD and ODD symptoms as well as parental age. Therefore, multiple sources of information are required when assessing the severity of CU traits in adolescents with ADHD. The factors influencing the levels of the agreement should also be considered. Callous–unemotional (CU) traits are a group of personality characteristics demonstrating a lack of care for values that others share, a lack of remorse, and a general poverty of affect ,2. CrossCU traits have unique roles in subgrouping, prognosis, and treatment responses in children and adolescents with attention-deficit/hyperactivity disorder (ADHD). Research on children with ADHD comorbid with oppositional defiant disorder (ODD) or conduct disorder (CD) determined that strong CU traits were associated with a lack of fearfulness, a reward-dominant response style, and a lack of regret for behavior problems . CU trair = 0.15, p < 0.05). They also revealed that self-reported anxiety levels were associated with behavioral and temperamental characteristics, whereas this relationship was not identified based on parent reports. A study on 91 nonreferred young adolescents determined that self-reports of CU traits on the APSD were moderately correlated with parent ratings [Studies have used reports of CU traits among adolescents from various informants, including adolescent self-reports ,19, pare ratings . Further ratings . Data frThe present study had two aims. First, CU traits contain various dimensions. The Inventory of Callous and Unemotional Traits (ICUT), one of the most used instruments, assesses three dimensions of CU traits in adolescents: callous, uncaring, and unemotional . The dimSecond, understanding the factors for predicting low levels of adolescent–parent agreement regarding CU traits is essential for the early detection of behavioral problems related to strong CU traits. Research has revealed that individuals with CD , ODD 2828, or ADDiagnostic and Statistical Manual of Mental Disorders [Adolescents with ADHD and their parents were enrolled from three child psychiatry outpatient clinics in Taiwan. Patients enrolled in Taiwan’s National Health Insurance program can visit outpatient clinics of teaching hospitals without referrals from general practitioners. Therefore, the adolescents enrolled from these clinics were representative of similar-age populations in Taiwan. The inclusion criteria for adolescents with ADHD were (1) an age range of 11–18 years and (2) a diagnosis of ADHD by a certified child psychiatrist according to the fifth edition of the isorders . The chiThe Chinese version of the ICUT consists of 24 items answered using a 4-point Likert scale to assess the level of how accurately items describe the participants, with 0, 1, 2, and 3 indicating “not at all”, “somewhat true”, “very true”, and “definitely true”, respectively . This scThe parent-reported Chinese-version short form of the Swanson, Nolan, and Pelham Version IV Scale (SNAP-IV-Chinese version) comprises 26 items rated on a 4-point Likert-like scale from 0  to 3 (very much) for assessing the inattention, hyperactivity and impulsivity, and ODD symptoms of adolescents based on the criteria for ADHD and ODD specified in the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) ,34. HighAdolescents were diagnosed as having CD and ODD based on clinical interviews and chart reviews. The sociodemographic characteristics of adolescents and their parents recorded in this study were sex , age, and parental duration of education (years).Adolescents with ADHD and their parents were invited to complete the research questionnaires in the interview rooms of outpatient clinics after providing written informed consent and being assured that their responses to the research questionnaire would be confidential. Two master’s-degree research assistants performed individual interviews with the adolescents to collect data on their self-reported CU traits. Before performing the research interviews, research assistants received comprehensive training on the application of research questionnaires. The principal investigator (C.-F.Y.) introduced the contents of the research questionnaires and discussed it with the research assistants. Each research assistant then performed a research interview with an adolescent with ADHD under the supervision of the principal investigator (C.-F.Y.) and received feedback for modification of the interview. Research assistants’ performance during the interviews was supervised regularly to assess fidelity. The parents completed the C-ICUT and short-form SNAP-IV. The parents could ask the research assistants for clarification if they had any questions about the questionnaires.All adolescents and their parents provided written informed consent. Parents also provided written informed consent regarding their children’s participation in this study. The study was conducted following the Declaration of Helsinki, and the protocol was approved by the Institutional Review Board of Kaohsiung Medical University (KMUHIRB-SV (I)-20150080).The descriptive results are presented as frequencies and percentages for categorical variables  and as mean and standard deviation (SD) for continuous variables .We examined the level of agreement between adolescent- and parent-reported CU traits using a two-way random effect model, consistency, and intraclass correlation (ICC) for average measures. Negative ICC values  were treated as 0 because negative values of ICC coefficients are not theoretically possible or meaningful . AccordiWe categorized our participants based on adolescents’ and parents’ demographics as well as adolescents’ psychiatric comorbidity and ADHD symptoms to examine whether adolescent–parent agreement on CU traits differed according to adolescent and parent demographics and adolescents’ psychiatric comorbidities. For continuous variables , the median score was used to dichotomize participants into low- and high-score groups.z test statistics and their corresponding p values were then computed.To determine whether significant differences in ICC existed between the low- and high-score groups, Fisher’s transformation  was usedt test with a p value < 0.002 (0.05/24) as statistically significant (The adolescent-reported and parent-reported scores of each item on the C-ICUT were further compared by paired nificant . The resn)” and “G2 (n)” indicated the number of participants in group 1 and group 2, respectively. “ICC in G1” and “ICC in G2” indicated the ICC of the CU traits in group 1 and group 2, respectively. For continuous variables , the median score was used to dichotomize participants into low- and high-score groups.The results indicated that adolescents without comorbid CD displayed lower adolescent–parent agreement on the trait of callousness .Adolescent–parent agreement regarding the trait of unemotionality was lower in adolescents with ADHD who had more ODD symptoms than in those who had less severe ODD symptoms .Girls, adolescents with comorbid CD, and adolescents with older parents displayed lower adolescent–parent agreement on the trait of uncaringness .The present study on adolescents with ADHD determined that adolescent–parent agreement on the CU trait of uncaringness was moderate, whereas agreement on the CU traits of callousness and unemotionality was poor. Moreover, adolescent–parent agreement on the three dimensions of CU traits varied depending on the adolescents’ sex and comorbid CD and ODD symptoms and parental age.The results indicated that adolescent–parent agreement on the trait of uncaringness was moderate, but the agreement on the traits of callousness and unemotionality was poor. The various characteristics of these three CU trait dimensions may partially account for the various adolescent–parent agreements regarding CU traits. The trait of uncaringness in the C-ICUT represents behaviors that reflect a lack of care regarding performance in tasks and the feelings of other people . AdolescThe callousness trait captures an aspect of behavior that includes a lack of empathy, guilt, or remorse for misdeeds . UnemotiThe present study did not collect information regarding adolescents’ CU traits from other sources and could not determine the accuracy of adolescent- and parent-reported CU traits. However, the low adolescent–parent agreement on CU traits indicates that multiple sources of information are required when clinicians and researchers assess CU traits in adolescents with ADHD.Previous studies mainly examined the CU traits and their predictive effects on prognoses in ADHD children and adolescents comorbid with CD ,16,17. TThe present study revealed a lower level of adolescent–parent agreement regarding the unemotionality trait in ADHD adolescents with more severe ODD symptoms than in ADHD adolescents with less severe ODD symptoms. ODD refers to the persistent display of anger/irritability , argumentation/defiant behaviors , and vindictiveness  . These eThe present study revealed that adolescent–parent agreement regarding the trait of uncaringness was lower among girls with ADHD and older parents compared with the agreement among boys with ADHD and younger parents, respectively. Studies have demonstrated that adolescent girls with ADHD have lower self-efficacy, poorer coping strategies, higher rates of depression and anxiety, and lower rates of physical aggression and other externalizing behaviors compared with adolescent boys with ADHD . FurtherIt is noteworthy that several studies have found poor parent–child agreement in the assessment of internalizing ,42 and eThis study has limitations that should be addressed. First, no information on the CU traits of adolescents with ADHD was obtained from peers and teachers. Therefore, the possibility of comparing the level of agreement among various informants was limited. Second, the participants of this study were a clinical sample of adolescents with ADHD. Therefore, the results might not be generalizable to adolescents with ADHD in the community who have never received treatment. Moreover, adolescents and their parents who had an intellectual disability, major psychiatric diseases, or any other cognitive deficits with difficulties in understanding study purposes and completing research questionnaires were excluded. The results of the present study might not be generalizable to the groups of adolescents and parents who were excluded. Third, we did not survey parents’ CU traits and could not determine the influence of parental CU traits on adolescent–parent agreement.The present study revealed that the level of adolescent–parent agreement depends on various dimensions of CU traits in adolescents with ADHD. Adolescent–parent agreement on the CU trait of uncaringness was moderate, whereas agreement on callousness and unemotionality were poor. The results indicate that clinicians and researchers should employ multiple sources of information when assessing CU traits in adolescents with ADHD, especially in groups of adolescents with ADHD who have characteristics that predict low adolescent–parent agreement, identified in this study.


There has been ongoing research on the ratio of theta to beta power  as an EEG-based test in the diagnosis of ADHD. Earlier studies reported significant TBR differences between patients with ADHD and controls. However, a recent meta-analysis revealed a marked decline of effect size for the difference in TBR between ADHD and controls for studies published in the past decade. Here, we test if differences in EEG processing explain the heterogeneity of findings. We analyzed EEG data from two multi-center clinical studies. Five different EEG signal processing algorithms were applied to calculate the TBR. Differences between resulting TBRs were subsequently assessed for clinical usability in the iSPOT-A dataset. Although there were significant differences in the resulting TBRs, none distinguished between children with and without ADHD, and no consistent associations with ADHD symptoms arose. Different methods for EEG signal processing result in significantly different TBRs. However, none of the methods significantly distinguished between ADHD and healthy controls in our sample. The secular effect size decline for the TBR is most likely explained by factors other than differences in EEG signal processing, e.g. fewer hours of sleep in participants and differences in inclusion criteria for healthy controls. Many studies have investigated EEG in children with ADHD compared to those of children without ADHD. Ever since the first description of deviant fronto-central slow-wave EEG activity  analysis, the QEEGs recorded from electrodes Fz and Cz were used, in line with the electrode sites most often used in TBR research  and the EEG/MEG analysis MATLAB-toolbox Fieldtrip  in radians per second (t). This is a linear operation and since the FFT assumes that the data is the sum of many sine waves, taking the derivative of the data is equivalent to taking the derivative of all separate sine-wave contributions to the data. The consequence is that the derivative in time results in the Fourier spectrum being multiplied by f (for any frequency). As a consequence, the 1/f effect in the spectrum is counteracted by a 1*f effect of the time-domain derivative, resulting in the power-spectrum being normalized for the 1/f noise, much like the subtraction of a regression model of the 1/f noise.Taking the derivative of a sine multiplies the output with The Welch method is based on the concept of using power spectral density (PSD) estimates, which are the result of converting a signal from the time domain to the frequency domain. Welch's method is an improvement on the standard spectral density estimating method, in that it reduces noise in the estimated power spectra. Due to the noise caused by imperfect and finite data, the noise reduction from Welch's method is often desired Welch . The metAnother widely used method for spectral density estimation is the multi-taper method Thomson . This meContrary to the above described methods, having a fixed taper length, the time windows that are used for wavelet analysis are dependent on the frequency. A wavelet decomposition uses a wave-like scalable function that is well localized in both time and frequency. Spectral density estimations for lower frequencies are computed using larger (time) windows than for higher frequencies. This approach calculates power spectral densities with time windows that depend on frequency, using a taper with Gaussian shape. Thus, it does not convolve the data with sine waves like the FFT, but with Mortlet (or Gabor) wavelets Meyer . Using tAverage theta power and beta power over the complete session and then compute the ratio between the two see Eq. .2\documen is the number of trials.This method could be used to normalize for temporal fluctuations in the EEG. By computing the ratio on the trial level, temporal differences in background activity are less likely to influence the resulting TBR, than averaging over the complete session. We perform this analysis by computing the ratio between theta and beta power for each 2-s epoch and then compute the average ratio over the complete session see Eq. . This alAfter computing the TBR for all different variations for all subjects individually we compared the output of the different methods using Cohen’s d as an effect size measure.d.In addition to computing the various TBR computations, we investigated if any of the variations were of diagnostic value in ADHD. For this we used the iSPOT-A dataset consisting of EEGs of 328 subjects with and 151 subjects without ADHD. We selected 5 methods for computing the TBR that showed a difference with the outcome of the other methods in the ICAN sample and computed these five types of TBR for each individual. We tested for statistical differences in the TBR between the ADHD and controls in the iSPOT-A cohort using unpaired t-tests and for clinical differences using Cohen’s As a final step, the different TBR measures were correlated with age (Spearmans’ Rho) to test for possible differences in this well-known and widely acknowledged association . The TBR resulting from the 1/f-noise-removed analysis showed a large difference from the TBR resulting from the uncorrected analysis . Comparing the different spectral analysis methods, we observed an effect size of d = − 0.011 ± 0.09 at Fz (r2 = 0.902) between the FFT and multi-taper analysis, and d = − 0.097 ± 0.09 at Fz (r2 = 0.872) between the FFT and Welch analysis.In this study we investigated various methods (depicted in Table d(Cz) = 0.102 for method 5 and maximal d(Fz) = 0.215 for method 3. None of the group differences reached significance  .The five methods we described in the previous analysis were used to test whether the resulting TBRs showed differences between ADHD and non-ADHD groups within the iSPOT-A dataset. The selected methods are depicted in Table p < 0.005 unless stated otherwise), as expected, with the strongest correlations for the Session-based averaging method  followed by Welch (Hann)  and the weakest correlation for Trial based . Effectively, this implicates a 1.3% difference in explained variance (6.4–5.5%) between the best and worst permutation for the known association between TBR and age.In the ICAN data, Spearman correlational analyses between age and TBR for all permutations showed highly significant correlations  ratings or for teacher-rated inattention. For teacher rated hyperactivity/impulsivity a significant correlation was found for Welch (Hann) TBR , which does not survive Bonferroni correction. Note the significant teacher-rated correlation is the opposite to what was expected, in that high TBR is associated with low levels of inattention and hyperactivity/impulsivity. With a sample that was adequately powered, the lack of significant correlation casts doubts on the association of TBR with severity of ADHD symptoms. Therefore, we performed the same correlations within the larger iSPOT-A samples as well.No significant partial correlations (covaried for age) were found for parent-rated inattention or hyperactivity/impulsivity  were found as expected, with the strongest correlations for Trial based ; Multi-taper  and Welch .For iSPOT-A significant correlations  with age . For the ADHD group, the most significant correlations (Cz unless stated otherwise) were for Inattention and Trial based averaging  and the lowest correlation for Welch (Hann) . The explained variance ranged from 1.5 to 0.7%, effectively making a 0.8% difference of the explained variance in the association between TBR and inattention. For hyperactivity in the ADHD group, similar patterns were observed with the highest correlation for Trial based averaging  and the lowest correlation for Welch , effectively explaining 1.2% and 0.3% of the variance and thus a 0.9% difference of the variance, however, none of these correlations would have survived a correction for multiple testing e.g. Bonferroni correction.No correlations were found between any of the TBR calculation methods and inattention or Hyperactivity/Impulsivity within the non-ADHD group . The largest difference in absolute TBR values compared to the session average FFT was found for the 1/f corrected data, which is logical because due to the removal of the 1/f (pink) noise the ratio of theta-to-beta power approached 1 (as can be seen in Table d = 2.38). In contrast, the different frequency analysis approaches such as FFT vs. Welch or tapering methods Hann vs. DPSS had no major impact on absolute values of TBR, with very small ES (Cz: d = 0.01).Given the lack of detail on the actual computation of the TBR provided by the papers in the meta-analysis . Inconsistent associations with sum of the teacher-rated inattention and hyperactivity-impulsivity were found that (1) would not have survived correction for multiple testing (most significant correlation was p = 0.017); (2) were in the opposite-of-hypothesized direction in the ICAN sample (high TBR associated with low inattention and hyperactivity/impulsivity) and (3) were in the expected direction in the iSPOT-A sample, but with very low explained variance (max 2.6%), with no such association in the non-ADHD sample. In sum, TBR does not show a consistent association with ADHD symptoms. Our findings paired with the meta-analysis results suggest that TBR is not a useful stand-alone diagnostic tool for ADHD. Further, absolute TBR values might not be comparable from one software system to another  TBRs could distinguish between the ADHD and the non-ADHD group as visualized in Fig. In addition to the lack of detail in the description of the process for computation of the TBR across studies, the specification of inclusion criteria for the “healthy” control groups in studies varies as well. In several of the earlier studies  that could inform future studies. For the age correlations, the Trial Based TBR and Welch method showed the strongest associations in both samples (7% in ICAN and 16–23% in iSPOT-A), with an average difference of 0.18%. So, although differences were overall small, a recommendation for future studies is to use the Trial-Based or Welch method for TBR studies.In summary, with regard to the different EEG processing methods, we conclude that the significant heterogeneity observed in the meta-analysis by Arns et al. (s et al.  of recen


Attenuated baseline arousal has been hypothesized to underlie symptoms of attention deficit/hyperactivity disorder (ADHD). A behavioral signature of reduced baseline arousal is an increased beneficiary effect of warning signals in reaction tasks. This paradoxical effect is believed to be caused by a temporary increase in arousal induced by warning signals. In a preregistered study, we tested the hypothesis that children with high levels of ADHD symptoms would be hyperresponsive to warning signals in a well-established visual attention task (the gap/overlap paradigm). Previous studies using this task have found slower and more variable saccadic reaction times in children with ADHD compared to typically developing children, suggesting that these eye movement metrics are candidate biomarkers. We examined 71 children, of which 1/3 had a diagnosis of ADHD, using both dimensional analyses and group comparisons. Previously reported findings of reduced saccadic latency and increased latency variability were replicated. Importantly, saccadic latency was normalized by auditory warning signals. Analyses of pupil dilation, a physiological index of arousal and locus coeruleus-noradrenergic activity, confirmed that warning signals led to enhanced arousal. Our findings are novel and contribute to our understanding of arousal and attention in ADHD and have implications for treatment and interventions.The online version of this article (10.1007/s00787-020-01484-w) contains supplementary material, which is available to authorized users. Attention deficit/hyperactivity disorder (ADHD) is one of the most prevalent childhood onset mental disorders, affecting approximately 5% of children worldwide . Contempgain, defined as the difference between the observed distance (amplitude) of a saccade and the optimal distance to its intended target. These oculomotor abnormalities may be partly normalized by pharmacological treatment .The study was approved by the regional ethics committee of Uppsala, Sweden, and the study was performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.The final sample consisted of 71 children  of which 24 had received a diagnosis of ADHD.n = 1), the child was lacking valid data from all conditions . Ten included children with ADHD were treated with stimulant or nonstimulant medication for ADHD, but medication was withdrawn at the day of testing. Parents confirmed that the child had received a diagnosis of ADHD from a clinical psychologist or psychiatrist in regular care and specified the clinic and year of diagnosis. Of the included children, one had diagnosis of ADHD-PI, one had ADHD-NOS, and 22 had the combined presentation. Parent ratings confirmed symptom levels within the range of clinical concern according to the SNAP-IV . To test the validity of this approach, the analysis was conducted with the limit of trials set to a range of numbers to 3, 7, and 10 trials. This did not change the significance of any of the results.Saccades were discarded if the point of gaze did not reach the peripheral target within 200 ms, or if the point of gaze was not within the central AOI during at least 25% of the 200 ms directly preceding the onset of the peripheral stimulus. Saccades with latencies < 120 ms were considered anticipatory, and were therefore discarded. Visual inspection of all recorded saccadic latencies indicated that the data were positively skewed due to a small number of very slow saccades. We removed saccades with latencies > 1000 ms (corresponding to the 97.5th percentile) from further analysis. The pupil signal was filtered using a moving median filter with a window size corresponding to 80 ms. A linear interpolation was applied over gaps in the pupil data shorter than 100 ms. Pupil-dilation amplitude was defined as the median size of the pupil during a 0–1500 ms time window after the onset of the visual stimuli, normalized to the median pupil size during a 333 ms (20 samples) baseline period. On silent trials, the baseline period was defined as the 1000–666 ms interval before stimulus onset . For the other cases, parental ratings were used. Median values of saccadic latencies, saccadic gain, and pupil dilation were calculated for each participant and condition. Data were analyzed using generalized linear mixed effects models (GLMMs) with random intercepts for participant , and random slopes for condition. The latency data were positively skewed, and the models were therefore fitted with a log link. As a measure of intraindividual variability, the interquartile range of saccadic gain and latency was calculated for each participant. The significance of main and interaction effects was tested with Analyses of variance (ANOVAs) with Satterthwaite approximated degrees of freedom. Bonferroni corrected p values are reported for all follow-up tests. The alpha level was set to 0.05. All analyses were conducted in MATLAB .Continuous variables were z-transformed for ease of interpretation. Sex and age were added as covariates in all analyses. ODD-symptom level was added as a covariate in the dimensional analyses. No significant main or interaction effects in the analyses involving ODD symptoms were found, and these are presented as Supplementary analysis. All significant results remained unchanged when ODD symptoms were excluded as covariate .The mean value of parent and teacher ratings of ADHD and ODD symptoms were analyzed when both sources were available (p < 0.01). No other covariates were significantly linked to the dependent variables .Age was negatively related to saccadic latency in the silent overlap condition  = 25.48; p < 0.001]. Saccadic gain was lower  in the overlap condition than in the gap condition . A difference between gap and overlap trials was also found on saccadic latency variability, with lower variability in the gap condition . In contrast, no gap effect was found for saccadic gain variability . Thus, the preliminary analyses showed a gap effect for both median saccadic latency and saccadic latency variability. Neither symptoms of ADHD, ODD nor group status  interacted with the gap effect for these measures , suggesting that the gap effect was not related to ADHD symptoms.As expected, overlap trials resulted in longer saccadic latencies than gap trials . However, the hypothesized interaction effect between ADHD symptoms and condition was found, , indicating that a greater reduction in saccadic latency after phasic alerting cues was related to higher levels of ADHD symptoms. Follow-up tests in the two conditions separately showed that ADHD symptoms were linked to longer saccadic latencies in the silent overlap condition , but not in the cued condition . A secondary analysis with group  resulted in highly similar results. First, an interaction effect between group and condition was found , driven by a larger relative reduction in saccadic latencies on cued than on silent trials in the ADHD group. Follow-up analyses showed that saccadic latencies were longer in children with ADHD than in the typically developing group on silent , but not on cued trials . Group wise analyses showed a trend towards decreased saccadic latency in the ADHD group after phasic alerting cues , but not in typically developing children . To sum up, both the dimensional and the categorical analyses showed an association between the ADHD-symptom dimensions and a decrease in saccadic latency after phasic alerting cues. No main or interaction effects involving ODD and the phasic alerting effect were found .Saccadic latencies were shorter after phasic alerting cues, but this effect was not statistically significant,  and similarly there was no significant interaction effect between ADHD symptom level and saccadic gain . Further, there was no main effect of group , and no interaction effect between group and condition . No main or interaction effects involving ODD symptoms and the phasic alerting effect were found .No significant main effect of alerting cue was found on saccadic gain  or ODD .As can be seen in Fig. F  = 6.45, p = 0.013, z = 0.44], but not with variability of saccadic gain . Similarly, variability of saccadic latency was higher in children with ADHD than in children with typical development , whereas no group difference was found on gain variability . Within the overlap condition, cued trials resulted in higher variability than silent trials . There were no significant interactions between ADHD symptoms and condition for either latency  or gain variability . Similarly, group status did not interact with condition for either latency , or gain variability . No main or interaction effects of ODD symptoms and variability of saccadic latency or gain were found .Across conditions, ADHD symptoms were associated with higher variability of saccadic latency [Influential theories suggest that disrupted arousal processes underlie ADHD symptoms , 21, 24.As noted in the introduction, disrupted arousal processes in other clinical conditions have been associated with enhanced sensitivity to phasic alerting effects and warning signals more generally. Therefore, we hypothesized that ADHD symptoms would be associated with greater reduction of saccadic latency following phasic alerting cues. Both dimensional analyses and group comparisons supported this prediction.As expected, higher levels of ADHD symptoms were associated with slower saccadic reaction times in the absence of phasic alerting cues. Indeed, this effect has been reported in a number of previous studies Below is the link to the electronic supplementary material.


Background: Recent findings indicated a high comorbidity between attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), as well as shared genetic influences on them. The latter might contribute at least partly to the former clinical scenario. This study aimed at investigating whether SHANK genes were potential pleiotropic genes to the two said disorders, underlying their genetic overlap.Methods: This study recruited 298 boys with ADHD , 134 boys with ASD, 109 boys with both ADHD and ASD, and 232 typically developing boys as community controls. They were aged between 6 and 11 years old.Results: There was no significant difference in allele frequency of a number of single nucleotide polymorphisms (SNPs) in SHANK2/SHANK3 between the three clinical groups  and between the two control groups (community controls and pseudo-controls), respectively. The three clinical groups and the two control groups were thus, respectively, combined. A comparison between the two aggregated samples identified significant evidence of disease association for three SHANK2 SNPs with both ADHD and ASD, even after multiple testing correction: rs11236616 , rs7106631 , and rs9888288 . Comparisons among individual groups pointed to a similar trend of findings.Conclusion:SHANK2 could be considered a potential pleiotropic gene underlying the genetic overlap between ADHD and ASD. This might contribute partly to their high comorbidity in the afflicted children. Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are two separate common neurodevelopmental disorders in children. However, their diagnoses were previously hierarchical such that a diagnosis of ASD precluded a diagnosis of ADHD. The abandonment of this hierarchical diagnostic arrangement in the current psychiatric classification, Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-5)  means thFamily-based and twin studies have consistently found that both ADHD and ASD are highly heritable, each with genetic influences accounting for approximately 70–80% of the phenotypic variance and a significant portion of them being shared between the two disorders. The latter was implicated by findings of co-aggregation of ADHD and ASD in the same individuals or in the same families . RecentlSHANK genes are good candidates for this strategy. They had established association with ASD, reported in both meta-analysis , which encodes scaffolding proteins required for the proper formation and functioning of neuronal synapses  for association with both ASD and ADHD.Though there are fewer reported association between and ADHD . Second,behavior . Based oThe gender ratios of children with ADHD and children with ASD in the clinic population of Hong Kong were around 10  to 1 , as reported in a local study  and in aThis study was approved by the Joint Chinese University of Hong Kong-New Territories East Cluster Clinical Research Ethics Committee and complied with the latest version of the Declaration of Helsinki. The clinical sample was recruited from three child psychiatric clinics in Hong Kong. The community control sample was recruited via local mainstream schools or advertisements in social media. The interested parents were first asked two sets of questions to screen whether their children, including the sibling(s) of the child to be participating, had ADHD, ASD, or other specific learning problems. Children, whose parents gave a positive reply to one of the two sets of questions, were declined participation in this study. Parents of the clinical and community control samples provided written informed consent for their children to participate in the study.Additionally, for the ADHD group, designated funding was available to examine the DNA of the two biological parents for a family-based study of ADHD without the involvement of ASD. Written informed consent was thus obtained from these parents for their own participation. However, this family-based study of ADHD is beyond the scope of this manuscript to be reported here.Venous blood was collected from the ADHD group and their biological fathers and mothers. Genomic DNA was isolated using QIAamp DNA Blood Mini Kit  in accordance to a standard protocol. Buccal swabs were collected from the ASD and ADHD + ASD children using Catch-All Buccal Swab . Saliva was collected from the community control group using Oragene DNA Collection Kit . Genomic DNA from collected buccal swabs or saliva was isolated by prepIT DNA extraction kit  using a standard procedure.SHANK2 and SHANK3 for genotyping. A cluster-based algorithm which clustered SNPs by r2 was used  of at least 10% in Asians (data from HapMap project Phase I- I- I)  in SHANK2 deviating from HWE distribution (p < 0.1%), one SNP (rs13055562) in SHANK3 having a high missing rate (>10%), and one SNP (rs4980613) in SHANK2 having a >5% Mendel error rate.Tag SNP strategy was used to select the SNPs in was used . The algI- I- I) . GenotypFrom the ADHD family trios’ data, we constructed matched pseudo-controls by an in-house R program, which was based on transmitted and non-transmitted parental alleles using the Haplotype-Relative-Risk (HRR) principle . Accordi2 test using the PLINK software , 8.0 years (SD = 1.8), 8.5 years (SD = 1.4) and 9.2 years (SD = 1.7), respectively. There was no significant age difference between the ADHD and control groups, as well as between the ASD and ADHD + ASD groups. However, the former two groups were significantly older than the latter two by about 1 year (p = 0.001). Two hundred and fifty-six pseudo-controls were constructed based on 256 family trios’ genotyping data.The sample sizes of the three clinical groups were, respectively, 298 boys for the ADHD group , 134 boys for the ASD group and 109 boys for the ADHD + ASD group. The community control group had 232 typically developing boys. The mean ages of the ADHD group, ASD group, ADHD + ASD group, and community control group were 9.3 years 1. Significant association with both ADHD and ASD was found for six SHANK2 SNPs, namely, rs7113016 , rs1073294 , rs11236616 , rs7106631 , rs10899158 , rs9888288  (p = 0.0376), rs7106631 (permuted p = 0.0034), and rs9888288 (permuted p = 0.0407). Significant protective effects were found from the A allele of rs11236616 as well as the T allele of both rs7106631 and rs9888288, all of which decreased disease risk of both ADHD and ASD by around 20–30%. These percentages were calculated based on ORs of those three SNPs. The ORs for rs11236616, rs7106631 and rs9888288 were, respectively, 0.762, 0.720, and 0.770  and rs7106631  in a recessive model  . Three o= 0.770) , i.e., rnd 0.770 . Assuminve model . No signanalysis .p = 0.0685). The ASD and ADHD + ASD groups had even smaller sample sizes  and thus reported fewer instances of statistical significance. Although the ASD group reported only one SNP (rs11236616) among the six SNPs identified above to be significantly associated to ASD, there were three more SNPS among them  reaching marginal significance (p < 0.08). The ADHD + ASD group reported two SNPs of significant association to ADHD and ASD among the above six named SNPs (rs7106631 and rs10899158).We then proceeded to finer comparison between groups . Each clp = 0.0714) associated with ADHD. For the enlarged ASD sample , among the above-named six SNPs, two were significantly associated with ASD (rs7106631 and rs10899158) with three more at marginal significance  (p < 0.08)  marginally missed the statistical significance ( < 0.08) .p-values of a number of SNPs within a gene and provides an overall p-value for the entire gene. As shown in SHANK2, compared to the aggregated control sample, was associated with the ADHD group (p = 0.0082), the enlarged ADHD sample  (p = 0.0034), and finally the aggregated clinical sample (p = 0.0031 and permuted p = 0.0061). Though not entirely unexpected, the smaller sample size and lower statistical power were unable to pick up the association between SHANK2 and ASD, represented by the ASD group or the enlarged ASD sample (involving both ASD and ADHD + ASD groups). As expected, no evidence for disease association was identified for SHANK3.Gene-level association analysis integrates the SHANK2 SNPs, our study finds no significant difference between the three clinical groups, i.e., ADHD, ASD and ADHD + ASD groups, and between the two control groups, respectively. Instead, the three clinical groups combined differ significantly (multiple testing corrected) from the two control groups combined with respect to three SHANK2 SNPs . Significant protective effects are found from the A allele of rs11236616 as well as the T allele of both rs7106631 and rs9888288, all of which decrease disease risk of both ADHD and ASD by around 20–30%. Subsequent analysis with each individual clinical group or with the two enlarged clinical samples by diagnosis shows a largely similar trend of findings, despite that the actual results are impacted by the reduced sample size and statistical power of the comparison groups. To the best of the authors’ knowledge, there is no previous study reporting association of SHANK2 SNPs with both ASD and ADHD. This new finding suggests SHANK2 to be a potential pleiotropic gene to the two disorders. However, at the gene-level analysis, the comparisons between various ASD groups and the aggregated controls are non-significant  with them using the LD information from the Chinese subpopulation (CHB and CHS) in the 1000G project , the latter being the one SNP identified in this study to be strongest in its association with both ADHD and ASD. Interestingly, the three SNPs associated with this SNP (rs7106631) had been classified as functionally important by RegulomeDB database, affecting transcription factor binding sites or regulating gene expression , using FUMA2, suggested that SHANK2 rs1893121, which was in strong LD with the currently identified rs7106631 (r2 = 0.949), was significantly expressed in brain hippocampus (p = 0.046) and basal ganglia (p = 0.037). Future research should explore and define the functional involvement of our identified SNPs, particularly rs7106631, in these two disorders.In this study, the three strongest-linked SNPs to ADHD and ASD  were all clustered in the same intronic region of the gene see . Althoug project . Three opression . Thus, tSHANK genes in NMDA and AMPA glutamate receptors, which are important in defining synaptic plasticity and cognitive functioning  specifically investigated intrauterine phenotypic development.On the contrary to variants . Regardis5770820 . The disSHANK2 has not been reported to be associated to ADHD in GWAS. In fact, ADHD GWAS have not been very successful in detecting a sizable number of significant SNPs in ADHD until recently by SHANK2. However, its sample sizes of 20,183 ADHD participants and 35,191 controls are not considered to be particularly large by comparison to those involved in other common psychiatric disorders, e.g., >450,000 participants in depression  gene on the development of ADHD, but not on the development of ASD traits in ADHD children. Interestingly, SDP had been found to be a marker of genetic predisposition than an independent environmental etiological factor of ADHD (SHANK2 which contributes to their joint development.This study identifies  of ADHD . Indeed, of ADHD . Future SHANK2 SNPs which this study identifies. However, we do find our identified SNPs in strong LD with other SNPs involved in the transcriptional regulation or gene expression of SHANK2. Fourth, we have only genotyped common variants in the present study; subsequent exome sequencing of this Chinese children sample may uncover potential rare variants which drive the presently observed associations with the SHANK2 SNPs. Finally, our new finding that SHANK2 could be a potential pleiotropic gene for ADHD and ASD should be viewed with caution, if not suspicion. Particularly, our modest overall sample size may give rise to potential chance results, despite surviving multiple testing correction. Furthermore, the gene-level analysis is not entirely supportive with respect to ASD. However, even recent large ASD GWAS studies also failed to identify SHANK genes (SHANK genes with ASD in previous association and animal studies, cited above (in vivo and in vitro models.This study has a number of limitations. First, this study only includes boys as participants. It is thus unsure whether our current findings are generalizable to girls. Second, this study relies on clinical diagnosis than on standardized diagnostic interviews. However, while the latter can provide standardization in assessment, clinical diagnosis remains the key criterion against which most, if not all, standardized diagnostic tools are initially validated. Third, in terms of functionality, there are no known functions for those NK genes , despiteed above . Perhapsed above . These eIn clinical practice, screening ADHD in children with ASD and vice versa should be routine. Because of their genetic overlap, they are more likely to be comorbid with each other. The previous hierarchical, mutually exclusive diagnostic practice had seriously misguided clinicians to miss the diagnosis of ADHD in ASD children. Such omission is most unfortunate, since ADHD is a treatable disorder by drug and behavioral intervention. If untreated, it will incur significant psychosocial impairment to a developing child. Our finding also has a significant impact on genetic counseling. In the past, the awareness of the elevated comorbidity between ASD and ADHD was not high. Based on the new knowledge from our study, families seeking genetic counseling will benefit from a better understanding of the genetic interconnectedness of these two disorders in order to make informed decisions.The dataset of this study which supports the findings and conclusions of the article will be available from the corresponding authors upon reasonable request.The studies involving human participants were reviewed and approved by the Joint Chinese University of Hong Kong-New Territories East Cluster Clinical Research Ethics Committee. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.S-LM, C-CL, KL, S-FH, C-PT, T-PH, P-CS, and PL: conceptualization and study design. C-PT, CS, FM, and PL: fieldwork. LC, TM, and P-CS: formal analysis. LC: writing—original draft. S-LM, LC, C-CL, KL S-FH, C-PT, T-PH, CS, FM, TM, P-CS, and PL: writing—review and editing. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.