We investigated the relation between dimensional aspects of inattention and hyperactivity-impulsivity in childhood and peer problems 4 years later, as well as the potential mediating effects of intellectual function. The sample included 127 children (32 with attention-deficit/hyperactivity disorder). Symptoms of inattention and hyperactivity-impulsivity were assessed via parent and teacher reports on Swanson Nolan and Pelham-IV questionnaire. Peer problems were assessed by parent reports on the Strengths and Difficulties Questionnaire, and children's intellectual functioning by the third edition of the Wechsler Intelligence Scale for Children. Linear regressions showed a significant effect of inattention on future peer problems, partially mediated by slow processing speed. These effects remained significant when ADHD status was covaried. Findings highlight the importance of processing speed in explaining the predictive relation between childhood inattention and later peer problems. Inattention and processing speed in early childhood are potentially malleable factors influencing adolescent social functioning. Attention-deficit/hyperactivity disorder (ADHD) is a common childhood psychiatric disorder , and peer problems were reported by parents at baseline as well as when the children were in early adolescence (ages 11–13 years). Key demographic variables (age and sex), the presence of an ADHD diagnosis, and baseline peer problems reported by parents were adjusted for in the statistical analyses. Second, we investigated whether the association between IA/HI and peer problems was mediated by the child's performance on the key indices of the WISC-III at ages 8–10. Based on previous findings, we hypothesized that (i) IA and HI in primary school children would predict later peer problems over and above demographic variables and baseline peer problems; (ii) indices from WISC-III would partially mediate the direct effect of IA and/or HI on peer problems, with the strongest mediating effect from processing speed, given its prior linkages with IA; and (iii) that these findings would be retained with the presence of an ADHD diagnosis included as a covariate.The Bergen Child Study (BCS) is a longitudinal, multi-wave, population-based study on childhood mental health and development. The present study includes data from three sequential time points of data collection. The first study wave was launched in 2002, organized into three phases. In the first phase, a questionnaire including the Strength and Difficulties Questionnaire  of the children and their parents were invited to a third clinical phase, including all children with any diagnosis according to DAWBA (n = 139). A total of 329 children and their parents participated in this phase, consisting of a short physical examination, a neuropsychological assessment including a test of intellectual function  and parents of a subset of screen negative children were interviewed according to the Development and Well-Being Assessment . Parents gave written consent for participation, and the study was approved by the Regional Committee for Medical and Health Research Ethics in Western Norway.The present study included the subsample of 127 children with complete data for the variables of interest . Approximately half of the mothers and fathers of the participating children had completed education at a college or university level  = 0.64, p < 0.01, and HI, r(125) = 0.58, p < 0.01. Therefore, the mean scores reported by the parents and teachers were summed to construct cross-informant composite scores of IA and HI. To run an extra check for cross-informant discrepancy in predicting parent-rated peer problems, separate reports by source were included in supplementary analyses.Swanson,  at the fSwanson, . It inclIntellectual function was assessed by the four indices generated from the Norwegian version . Twenty-eight children with ADHD also met criteria for another diagnosis . Ninety-five children did not meet criteria for ADHD , but 29 of them met the criteria for one or more other mental disorders according to the KSADS-PL  meeting criteria for an ADHD diagnosis (p = 0.01). Boys showed higher scores on the IA and HI subscales, and scored lower on the FFDI and PSI indices, compared to girls . Children with ADHD were older, obtained higher scores on the IA and HI scales, had higher peer problems scores, and obtained lower scores on VCI, POI, FFDI and PSI indices, compared to children without ADHD  and 45 girls, and boys were more likely to meet criteria for an ADHD diagnosis  = 3.67, p = 0.01] to future peer problems at age 11 – 13. Not surprisingly, information about baseline peer problems added 18.5% to the explained variance . Next, the IA and HI subscales added 4.5% to the explained variance , with the total model explaining 31.5% of the variance .Hierarchical regression analyses revealed significant contributions of age, gender, and ADHD diagnosis , whereas IA did, increasing the model's explained variance by 4% . Entering IA and HI scores rated by either parents or teachers separately did not alter the results. Inspection of the single predictors in the total model showed that only IA  and baseline peer problems  were significant in predicting future peer problems, when covarying the other variables.To ascertain the relative contributions of IA and HI, we added each subscale in separate analyses  = 27.59, p < 0.001), and VCI and PSI in a later step  best explained variance in future peer problems, in total explaining 34.6% of variance . At the level of the individual variables, baseline peer problems, IA, and PSI (but not VCI) were significant predictors  on future peer problems were analyzed using LARS, providing a reduced model including variables for the PROCESS analysis. LARS showed that the combination of baseline peer problems and IA in one step , with a significant direct effect of IA . Mediation analyses showed that PSI was a significant mediator of the effect , whereas VCI was non-significant  (see Figure The results from the LARS restricted the PROCESS analysis to include baseline peer problems as a covariate, IA as a direct predictor, and VCI and PSI as potential parallel mediators, with peer problems in preadolescence as the criterion variable. The PROCESS analysis showed a significant total effect for the baseline peer problems, IA, VCI, and PSI on peer problems in preadolescence [Previous research has consistently linked ADHD to peer problems (Ros and Graziano, Out of the four WISC-III indices, only PSI was identified as a significant predictor and mediator of later peer problems, despite significant correlations between IA and all WISC indices. Thus, our findings emphasize PSI's contribution to future peer problems, along with the value of considering specific intellectual indices in studies of functional outcomes (e.g., Keith and Witta, IA also predicted later peer problems when ADHD diagnosis was covaried, even though the IA scores were high in the ADHD group. This result suggests that IA may be important for both typically developing children and for those with ADHD, and fits previous research emphasizing the dimensional impact of ADHD symptoms (e.g., Kofler et al., Processing or psychomotor speed has not been studied to the same extent as other aspects of intellectual function, but is nonetheless an important dimension in developmental neuropsychology (Kail and Hall, Although the longitudinal design, inclusion of dimensional measures of ADHD symptom clusters, and assessment of intellectual functioning according to validated instruments comprise key main strengths of the present study, several limitations constrain the findings. First, we lacked sociometric measures for the assessment of children's real-life interactions with peers and peer reputations, which are considered the “gold standard” for appraisal of these variables. We also lacked complete data for teacher reports of peer problems to conduct the cross-informant analysis of peer problems strongly recommended by findings in previous studies (Renk and Phares, Findings from the present longitudinal study reveal that dimensions of IA, measured by teacher and parental reports, along with processing speed, are important factors in predicting peer problems in preadolescence, even when adjusting for prior peer problems. Mediation analyses confirmed the meaningful role of IA as well as its pathway through processing speed, linked to later peer problems 3–4 years later. The results remained significant after adjusting for ADHD status, showing that the results were not restricted to children with an ADHD diagnosis. A better understanding of the determinants of peer problems is needed to develop effective interventions procedures preventing development of social and other mental health problems later in life.AT was responsible for the data analysis, interpretation, drafting, and revising the manuscript. JM and SH contributed to drafting and revising the manuscript. AL was responsible for data collection in the Bergen Child Study, and contributed to the data analysis, interpretation, drafting, and revising the 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.


Children with attention deficit/hyperactivity disorder (ADHD) frequently have motor problems. Previous studies have reported that the characteristic gait in children with ADHD is immature and that subjects demonstrate higher levels of variability in gait characteristics for the lower extremities than healthy controls. However, little is known about body movement during gait in children with ADHD. The purpose of this study was to identify the characteristic body movements associated with ADHD symptoms in children with ADHD.Using a three-dimensional motion analysis system, we compared gait variables in boys with ADHD  and boys with typical development (TD)  to determine the specific gait characteristics related to ADHD symptoms. We assessed spatiotemporal gait variables , and kinematic gait variables  to measure body movement when walking at a self-selected pace.t = 3.33, p = 0.002) and anterior pelvic angle . In multiple regression analysis, anterior pelvic angle was associated with the ADHD rating scale hyperactive/impulsive scores , but not other psychiatric symptoms in the ADHD group.In comparison with the TD group, the ADHD group demonstrated significantly higher values in cadence (Our results suggest that anterior pelvic angle represents a specific gait variable related to ADHD symptoms. Our kinematic findings could have potential implications for evaluating the body movement in boys with ADHD. Attention deficit hyperactivity disorder (ADHD) is the most prevalent childhood onset neurodevelopmental disorder, affecting 7.2% of school-age children . ADHD isPrevious studies of gait in children with ADHD have mainly focused on the differences of gait variables in children with ADHD , or age-Three-dimensional (3D) motion analysis, which uses an infrared camera to assess body movement in terms of gait kinematics, has been helpful for investigating and understanding body movement to determine disease-specific gait characteristics . For pedThe aim of this study was to identify the kinematic gait characteristics of children with ADHD to measure the body movement of gait quantitatively. Furthermore, to determine the ADHD-specific gait characteristics, we sought to assess further whether alterations in gait variables are associated with psychiatric symptom measurements. We predicted that the severity of ADHD is related to the kinematic gait variables that have significant differences between children with ADHD and children with typical development.The protocol of this study was approved by the Ethics Committee of the University of Fukui (Assurance No. 20130066). After reading a complete description of the study, all participants and their parents provided written informed consent for participation. The experimental protocol was conducted in accordance with the Declaration of Helsinki.This study examined 19 boys with ADHD aged 7–12 years [9.58 ± 1.84 years (mean ± S.D.)]. Each child had been referred to the Department of Child and Adolescent Psychological Medicine, University of Fukui Hospital. Diagnosis was made following DSM-5 , 27. ExcTo evaluate the severity of ADHD symptoms, we used ADHD-RS, an 18-item questionnaire . Each itWe measured gait variables  by using a 3D motion analysis system (VICON-MX) that included ten T10 cameras  and four synchronized force plates  placed in the middle of a 10-meter walkway . We placth cervical vertebrae, 10th thoracic vertebrae, clavicle, sternum, the middle of right scapula, shoulder, elbow, wrist, anterior superior iliac spine, posterior superior iliac spine, shank, knee, shin, ankle, heel, and toe) according to the Plug-in-Gait marker set. Participants were instructed to walk with bare feet to the cone at their own pace. All participants conducted a few warm-up trials to acclimatize to the gait laboratory setting before placing makers.Height and weight were measured prior to gait assessment to control for body size differences, and spatiotemporal variables were normalized for each trait in accordance with the method described by Hof . The 14 All trials in which the force plates were hit were checked visually using Vicon NEXUS motion capture software . Error trials, such as ones in which markers fell off or no impact was made on the force plate, were excluded from further analysis. Marker trajectory was reconstructed and filtered using the Woltring filtering routine with Vicon NEXUS. The gait cycle started when one foot touched the floor and ended when that same foot touched the floor again. Gait variables were normalized as a percentage of the gait cycle using Polygon 3 .The assessed spatiotemporal variables were walking speed (m/s), stride length (m), and cadence (steps/min). The kinematic variables consisted of joint angle (degrees) in the sagittal plane for pelvis , hip, knt test and clinical symptoms were tested using ANCOVA with age and FISQ as covariates. To examine the correlation between ADHD symptoms based on ADHD-RS scores, and gait variables demonstrating significant differences for both groups, partial correlation coefficients were calculated with FSIQ as a covariate. Additionally, gait variables in children are multifactorial, with contributions from developmental indices (i.e. age and cognitive function) [p < 0.05 and used the Bonferroni adjustment for multiple comparisons. All analyses were conducted using the Statistical Package for the Social Sciences 20 software .Demographic data and gait variables were tested using independent unction) , 34 and unction) –25. Thert = 2.70, p = 0.011). Significant differences were found in the measures of severity of ADHD symptoms , ASD traits , and DCD traits  between the two groups.Demographic and clinical characteristics for the study participants are listed in t test. In comparison with the TD group, the ADHD group showed significantly higher cadence in spatiotemporal variables , and also showed significantly higher anterior pelvic angle . Normalization of the data according to Hof [Gait variables are shown in g to Hof  did not r = 0.17, p = 0.287). Therefore, we adopted pelvic angle and cadence as the representative gait variables for the following correlation analysis with ADHD symptoms. Since we observed a significant difference in FSIQ between groups, we calculated partial correlation coefficients between these gait variables and ADHD symptoms, controlling for FSIQ. As shown in r = 0.38, p = 0.018), whereas there were no significant correlations between these variables in each group separately . In contrast, as shown in r = 0.54, p = 0.021) as well as in the whole group , whereas no significant correlation was observed in the TD group . These results suggest the possibility that pelvic angle is specifically associated with the severity of ADHD symptoms.To assess the relationship between gait variables and ADHD symptoms, we explored the correlation between the gait variables and ADHD-RS scores beginning with the inter-correlation of the gait variables. There was no significant correlation between the kinematic variables and cadence as a spatiotemporal variable  in all subjects, although there were no associations with any psychiatric symptoms. For pelvic angle, however, a higher anterior pelvic angle was associated with an increased ADHD-RS score in all subjects. As indicated in β = 0.52, t = 2.40, p = 0.023), and cognitive ability, based on FSIQ , were significant predictors for anterior pelvic angle in all subjects, and explained approximately 33% of the variance in the pelvic angle . However, anterior pelvic angle had no association with AQ  or M-ABC2 . In the ADHD group, anterior pelvic angle also had an association with ADHD-RS hyperactive/impulsive score , and explained approximately 21% of the variance in the pelvic angle . In the TD group, anterior pelvic angle had an association with FSIQ .Next, we determined the core set of variables to develop an explanatory model of gait. We then performed multiple regression analyses to further characterize the relationship between psychiatric symptom measures and gait variables such as cadence and pelvic angle. For cadence, as shown in The purpose of the present study was to determine whether spatiotemporal and kinematic gait variables differ between controls and children with ADHD by using a 3D motion analysis system. Our results demonstrated that children with ADHD exhibit higher values for cadence and anterior pelvic angle compared to healthy controls, and that pelvic angle had a significant positive correlation with the severity of ADHD symptoms. These results suggest that children with ADHD have the characteristics of a high frequency gait cycle and an increased anterior pelvic angle. Furthermore, in multiple regression analysis, anterior pelvic angle was associated with the severity of ADHD symptoms, whereas there was no association with ASD or DCD symptoms in children with ADHD. Additionally, the variable of cadence showed no association with any psychiatric traits. These findings suggest that increased anterior pelvic angle during gait is a specific variable of ADHD symptoms.As expected, cadence, a spatiotemporal variable, had a positive correlation with ADHD symptoms in all subjects. A recent study reported that children with ADHD walked faster and with a higher cadence and that ADHD symptoms were associated with increased cadence in the “fast walking condition” . AlthougCuriously, in the present investigation we found a positive association between pelvic angle as a kinematic gait variable and ADHD symptoms. Why pelvic angle might be associated with ADHD is an interesting question. Pelvic movement is essential as an inherent mechanism of postural control in normal children  and has Moreover, as suggested by multiple regression analysis, we have observed that anterior pelvic angle shows an association with the severity of ADHD symptoms, although it shows no association with ASD or DCD symptoms, suggesting that pelvic angle may be one of the candidates for gait-specific variables in ADHD. To the best of our knowledge, the present study is the first to clarify the association between kinematic gait variables and the severity of ADHD symptoms.There were several limitations of this study. The first major limitation is the small sample size in this study. The cleanliness of the sample  might have compensated for that shortcoming, at least in part, by reducing error variance. To generalize our results, studies involving a larger number of participants must be conducted to compare with children with ASD or DCD. Second, this study used a cross-sectional design that precludes identification of causal links between ADHD and gait variables. Longitudinal studies must be conducted to investigate how gait variable differences associated with ADHD change in response to treatment programs aimed at diminishing signs of ADHD.In conclusion, increased anterior pelvic angle was associated with increased severity of ADHD symptoms. These preliminary findings could have potential implications for our understanding of gait control related to ADHD and a possible contribution for evaluating the body movement in boys with ADHD. Combining 3D motion analysis for body movement with neurophysiological indicators of brain activity should prove fruitful in further elucidating the mechanisms underlying motor control in children with ADHD.S1 Dataset(XLSX)Click here for additional data file.


This study aimed to assess the prevalence of Attention Deficit Hyperactivity Disorder (ADHD) and its characteristics and risk factors in children with epilepsy at a tertiary medical center in New Delhi. Children with active epilepsy, aged 6 to 12 years, were assessed for ADHD using DSM-IV-TR criteria. Epilepsy and psychiatric characteristics, sociodemographic indicators, and use of antiepileptic drugs were analyzed for differences between the ADHD and non-ADHD groups. Among the 73 children with epilepsy, 23% (n = 17) had comorbid ADHD, of whom 59% (n = 10) had predominantly inattentive type, 35% (n = 6) combined type, and 6% (n = 1) predominantly hyperactive-impulsive type. Lower IQ scores, epileptiform EEG activity, not attending school, and male sex were significantly associated with comorbid ADHD in children with epilepsy. Groups were similar in terms of age, socioeconomic indicators, family history of psychiatric disorders, seizure frequency in the last six months, seizure etiology, and seizure type. Epilepsy is a common pediatric neurological condition with frequent psychiatric comorbidities, including ADHD. Specialists should collaborate to optimize treatment for children with epilepsy and ADHD, especially for families in developing countries where the burden of disease can be great. Several factors may contribute to this comorbidity6, including underlying brain pathology, chronic effects of seizures, epileptiform brain activity as seen on electroencephalogram (EEG), and effects of antiepileptic drugs7 (AEDs). This comorbidity also presents challenges to clinicians in determining a medication regimen and treatment plan8.Attention Deficit Hyperactivity Disorder (ADHD) is a common comorbidity experienced by children with epilepsy, and is associated with problems in social functioning, learning, quality of life, and academic attainment11, which is much higher than the reported worldwide pooled prevalence of ADHD of 5.3%12. Prevalence estimates of behavioral comorbidities in epileptic children and adolescents in India ranges from 40 to 54%14. In India, several studies have investigated psychopathology in children with epilepsy18; however, research focused on characterizing the ADHD comorbidity in epilepsy has been limited19.The reported prevalence of ADHD in children with epilepsy from high-income countries ranges from 23 to 70%, depending on sample studied and criteria used for diagnosisThis study aimed to quantify the prevalence of ADHD and its subtypes among children with epilepsy at an urban tertiary medical center. Measures of epilepsy severity, academic and sociodemographic factors, and use of AEDs were compared to describe the clinical profile of this pediatric group.20. The inclusion criteria were (1) children aged 6 to 12 years and (2) duration of epilepsy ≥ 6 months. Patients were excluded if they had an intellectual disability or comorbid chronic systemic disease. In total, 512 patients were screened for eligibility, 172 fulfilled the inclusion criteria, 62 had IQ ≤ 70, and 10 had comorbid systemic illness. Thus 100 patients were enrolled in a general epilepsy and psychopathology cohort (ages 6 to 16) whose findings have been previously reported13, and those aged 6 to 12 (n = 73) were included in this ADHD study.In this cross-sectional, observational study, children diagnosed with active epilepsy attending the outpatient services of the Child Neurology Division, Department of Pediatrics, All India Institute of Medical Sciences (AIIMS), New Delhi, were screened for eligibility. Active epilepsy was defined as two or more unprovoked seizures occurring 24 hours apart after four weeks of age, with at least one epileptic seizure in the previous five years, regardless of AED treatment, based on International League Against Epilepsy definitions21. Data collection took place between October 2008 and August 2009.Patients’ health records were retrospectively reviewed during the clinical course of their epilepsy. Epilepsy-related factors included age at seizure onset, duration of epilepsy, etiology, predominant seizure type, EEG pattern, seizure frequency in last six months, and AED therapy. Socioeconomic status categorization was based on monthly income per Agarwal’s six-stage classification22 (MISIC), an Indian adaptation of the Wechsler Intelligence Scale for Children. MISIC assesses verbal IQ, performance IQ, and full-scale IQ for children between 6 and 16 years of age. For the present study, verbal IQ was assessed, encompassing six domains: information, general comprehension, arithmetic, analogies and similarities, vocabulary, and digit span. Intellectual disability was defined as a verbal IQ of 70 or lower.IQ was evaluated with Malin’s Intelligence Scale for Indian Children23 (CBCL/4–16). For participants scoring above the CBCL total score threshold for their age and sex24, an experienced psychiatrist and pediatric neurologist used the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision25 (DSM-IV-TR) criteria for evaluation and diagnosis of 15 clinical disorders, including ADHD. Seventeen participants met the diagnostic criteria for ADHD.Preliminary assessment of behavior problems used parent/caregiver ratings on the Child Behavior ChecklistInterictal digital EEG recording  using an international 10–20 system of electrode placement was done at AIIMS for participants who did not have a good-quality EEG recording from the previous three months. Both awake and sleep states were recorded. Hyperventilation, photic stimulation, and sleep were used as activation procedures. EEG records were reported by two pediatric neurologists as either normal or showing epileptiform discharges.t-tests were used for normally distributed continuous variables. Chi-square (χ2) tests for association were used for categorical variables. The Mann-Whitney U Test was used for epilepsy duration and IQ, which had nonparametric distributions as assessed by Shapiro-Wilk’s test (p < 0.05). Post-hoc pairwise comparisons using Fisher’s exact tests (2 × 2) were used for seizure frequency.IBM SPSS version 24  was used for univariate analyses and descriptive statistics. Independent samples This study was approved by the Institutional Ethics Committee at AIIMS, and the study was carried out in accordance with the relevant guidelines and regulations. Informed consent was obtained from the parents/caregivers of all participants.Data analyzed during this study are included in the Supplementary Dataset.Of the 73 participants, 17 (23.3%) had both epilepsy and ADHD: within this group, 10 (58.8%) had ADHD predominantly inattentive type, 6 (35.3%) had ADHD combined type, and one (5.9%) had ADHD predominantly hyperactive-impulsive type.p < 0.0001). The ADHD group had significantly more males. Almost a quarter of the ADHD group did not attend school compared to 1.8% of non-ADHD participants (χ2(1) = 9.664, p = 0.0019), with epilepsy given in all cases as a reason for not attending. The group difference in school attendance was not driven by age. Seven participants with ADHD (41.2%) met the diagnostic criteria for an additional behavioral disorder, while 14 participants (25%) in the non-ADHD group did (see Supplementary Dataset). Age, socioeconomic indicators, and family history of psychiatric disorders were similar between groups.Sociodemographic and family background information is presented in Table 2(1) = 4.718, p = 0.030), with 52.9% of children with both epilepsy and ADHD showing epileptiform discharges, compared with 25% of those without ADHD. The ADHD and non-ADHD groups were comparable in terms of seizure etiology and seizure type. Post-hoc analysis of seizure frequency in the last six months did not indicate group differences in any of the frequency categories.Comparison of clinical epilepsy characteristics is presented in Table 2(1) = 2.952, p = 0.086).The following AEDs were used by study participants: valproate (27 participants), phenytoin (22), carbamazepine (20), clobazam (9), lamotrigine (6), oxcarbazepine (3), clonazepam (1), levetiracetam (1), and zonisamide (1). Three participants reported not currently taking any AEDs. Use of AED polytherapy was positively associated with ADHD diagnosis, but not significantly  of ADHD was identified in children with epilepsy. In agreement with several previous studieset al.19 in a pediatric neurology outpatient population in Karnataka, India (n = 94). A recent register-based study in Sweden26 of 1,899,654 individuals found that 13.5% of those with epilepsy also had a diagnosis of ADHD, while 4.3% of the full sample had ADHD, meaning a 3.5-fold increased risk in the comorbid group. In Asia, recent reports from Thailand27 and China28 found prevalences of 19% and 42%, respectively, of ADHD comorbidity among children with epilepsy. Studies of ADHD prevalence in India are limited, use different methodologies, and report varying figures. Recently reported prevalence figures of ADHD in children in the general population include 1.3% in a study of children in Bengaluru, Karnataka29 (n = 3120), 1.7% in a study of families in central India30 (n = 4278 families), 11.32% in a study of children in Coimbatore, Tamil Nadu31 (n = 770), and 12.66% in a study of children in the state of Assam32 (n = 300).This prevalence rate is similar to the 23.4% of children with epilepsy and comorbid ADHD reported by Philip 34, in line with the results presented here. In an American study, Dunn et al.35 found that of children aged 9 to 14 with epilepsy, 24% had ADHD inattentive type, compared to 14% with hyperactive-impulsive or combined types. In a Nigerian tertiary care facility, Chidi et al.36 found that of the 14% of epileptic children who also had ADHD, the inattentive type was predominant (69%).The population of children with comorbid epilepsy and ADHD differs in several ways from those with primary ADHD. For instance, the gender distribution is less skewed towards boys than in primary ADHD, and inattention symptoms are more frequent and severe than impulsivity/hyperactivity39. While some evidence implicates shared neurobiological abnormalities41, other studies suggest that independent factors are at play40. Regions of decreased cortical thickness have been reported in groups with comorbid epilepsy and ADHD, compared to epilepsy alone, which could indicate altered development of functional networks42. Saute et al.38 reported that pediatric epilepsy with comorbid ADHD was associated with reduced cortical thickness in bilateral areas of the frontal, parietal, and temporal regions, along with smaller caudate, thalamus, hippocampus, and brainstem volumes, compared to the epilepsy non-ADHD group; smaller cerebellum and thalamus were related to epilepsy generally, but brain volume and surface area did not show major group differences. Similarly, Dabbs et al.43 reported that ADHD problems assessed with the CBCL were associated with decreased cortical thickness in left superior frontal and lateral occipital regions and right fusiform gyrus. In a functional MRI study of boys with ADHD, Bechtel et al.44 reported similar patterns of brain activity during block-design working memory tasks in the groups with and without comorbid epilepsy, which differed from healthy controls. Neural mechanisms underlying epilepsy and ADHD, as opposed to ADHD or epilepsy alone, remain to be fully elucidated and will benefit from further neuroimaging research.Recent neuroimaging research using magnetic resonance imaging (MRI) has sought to shed light on possible shared neural mechanisms underlying epilepsy and ADHD comorbidity45. Relatives of those with epilepsy have an increased risk of ADHD themselves26, suggesting genetic and environmental linkages within families, and evidence of an association between maternal epilepsy and ADHD has also been reported46. However, Brikell et al.26 found only a modest genetic correlation between the disorders. In addition to inherited genetic factors, de novo mutations and other rare variants, such as those involved in synaptic function, neurotransmission, and methylation remodeling, should be investigated as potential risk factors (see review by Lo-Castro and Curatolo47).Genetic studies, especially at the population level, have also begun to identify risk factors related to these and other neurodevelopmental disorders34. It is possible that epilepsy alters the ADHD symptoms in children who have both, based on possible shared etiology and pathophysiology48. For example, children with ADHD are predisposed to epileptic seizures40 and have an increased rate of EEG abnormalities without a history of epilepsy49.A clearer understanding of medication effects on the symptomatology and progression of combined epilepsy and ADHD is needed to tailor medical management in this population52. Sleep disturbances due to AEDs, along with subclinical seizures and learning disabilities, can contribute to inattention51, which was the ADHD subtype diagnosed in 59% of children with ADHD in this study. Several studies suggest that use of methylphenidate appears to be effective in children with comorbid epilepsy and ADHD53. A 2015 Brazilian study54, which administered low to moderate doses of methylphenidate, observed reduced seizure frequency and severity along with improved quality of life among adolescents with ADHD and difficult-to-treat epilepsy. However, increased risk of seizures with high dosage of osmotic release oral system methylphenidate55 and lowered seizure threshold associated with tricyclic antidepressants and bupropion use has also been reported56. Most studies of medication for ADHD in children with epilepsy have had small numbers of participants and/or short study duration52, and clinical trials in developing countries have been limited58. Research on other medications, such as amphetamines, atomoxetine, and alpha-2 adrenergic agonists, has also been limited in this population. Medication effects on attentive behavior and seizure threshold should therefore be closely monitored. EEG monitoring is a useful tool in this population to identify whether staring episodes or repetitive movements are related to seizure activity or ADHD. Children with epilepsy in this study experienced ADHD at a high rate, and further research in larger populations should therefore clarify the risk-benefit ratios associated with various medications.Determining an effective treatment regimen for children with epilepsy and ADHD is challenging, as clinicians must consider a patient’s seizure frequency, cognitive function, drug interactions, and medication adherence. Use of AEDs, in particular polytherapy, has in some studies been associated with cognitive deficits in children including attention problems and hyperactivityet al.59 report that children with epilepsy and ADHD often have additional comorbidities, such as anxiety or oppositional defiant disorder, making treatment decisions complex33. AED polytherapy may also create financial stress for some families3. Holistic management of children with epilepsy would include screening and management of psychiatric problems, including ADHD. School failure and drop-out was a problem for a number of children in this study and underscores the need to engage the education community in this region to improve academic outcomes60. Further studies are required to evaluate the efficacy of behavior therapy, drug therapy, and other treatment modalities for individuals with epilepsy and ADHD, as well as their effect on improving quality of life61.Moreover, Gonzalez-Heydrich Limited research in India has examined ADHD comorbidity in children with epilepsy using diagnostic criteria. In this study, standard criteria from the DSM-IV-TR were used for diagnosing ADHD. Participants were recruited from the outpatient population of a government hospital which serves children from all socioeconomic backgrounds.The study population was drawn from the tertiary care center outpatient population, and all participants in this study had a history of epilepsy, making it difficult to generalize to primary care settings and to the typically developing pediatric population. Future studies should therefore also include a healthy matched group without epilepsy. Within-group analysis, for example more detailed analysis of seizure frequency related to comorbidity, would be strengthened by a larger number of participants. While Malin’s Indian adaptation of the WISC has been widely used across India for cognitive testing in children, future studies should consider using newer assessments, such as the WISC-IV India. Finally, the revised DSM-V was released after the data collection in this study. Using the updated diagnostic criteria for ADHD may have classified additional children with ADHD, meaning that the prevalence figures reported here are likely conservative. The DSM-V designation of mild, moderate, or severe ADHD would have provided extra detail to the current study.62. Further research examining potential shared neurological causes as well as strategies to optimize medication and treatment are needed to better serve this pediatric population.Prevalence of comorbid ADHD was 23% in children with epilepsy attending outpatient services at a tertiary medical center in New Delhi, with inattentive type being predominant. In this study, children with comorbid ADHD had lower IQ scores on average, and four of the five children who did not attend school had both ADHD and epilepsy. Clinicians should be sensitive to identify ADHD in children with epilepsy since this may lead to more effective intervention and improved quality of lifeSupplementary Information


Pathway enrichment analyses revealed an over-representation of genes involved in nervous system development and function among the eGenes. Categories related to neurological diseases, psychological disorders and behaviour were also significantly enriched. We subsequently meta-analysed the association with clinical outcome for the 33 eSNPs across the discovery sample and an independent cohort of 189 ADHD adult patients (target sample) and we detected 15 suggestive signals. Following this comprehensive strategy, our results provide a better understanding of the molecular mechanisms implicated in MPH treatment effects and suggest promising candidates that may encourage future studies.Methylphenidate (MPH) is the most frequently used pharmacological treatment in children with attention-deficit/hyperactivity disorder (ADHD). However, a considerable interindividual variability exists in clinical outcome. Thus, we performed a genome-wide association study of MPH efficacy in 173 ADHD paediatric patients. Although no variant reached genome-wide significance, the set of genes containing single-nucleotide polymorphisms (SNPs) nominally associated with MPH response (P < 0.05) was significantly enriched for candidates previously studied in ADHD or treatment outcome. We prioritised the nominally significant SNPs by functional annotation and expression quantitative trait loci (eQTL) analysis in human brain, and we identified 33 SNPs tagging  With a worldwide prevalence ranging from 5.3 to 7.1% in school-age children and adolescents2, ADHD is one of the most common childhood psychiatric conditions and causes high costs to the healthcare system and society4. Although its aetiology is largely unknown, several family, twin and adoption studies reported heritability estimates around 76%5, suggesting a strong genetic component in the pathogenesis of the disorder.Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterised by persistent and age-inappropriate symptoms of inattention, hyperactivity and/or impulsivity7. However, a considerable interindividual variability exists in clinical outcome, optimal dosage and duration of effect9, which may reflect underlying genetic influences.Among the wide variety of pharmacological options available in ADHD treatment, methylphenidate (MPH) is the first-line choice in paediatric patients, given its proved general efficacy in reducing ADHD symptoms and improving neuropsychological performance on executive functionsSLC6A3 and DRD4 being the most extensively investigated, since MPH is thought to exert its therapeutic effects through the inhibition of the dopamine and the norepinephrine transporters10. Based on this putative mechanism of action, additional genes such as DRD2, DRD5, COMT, SLC6A2, ADRA2A, TPH2, SLC6A4, HTR1B, HTR2A and MAOA11 have been considered plausible candidates that may influence medication response. Nevertheless, a recent review on ADHD pharmacogenetics in childhood reported no consistent effects for dopaminergic and serotoninergic signaling, and suggested neurodevelopmental genes as new promising targets12.Most of the pharmacogenetic studies conducted so far in ADHD patients have focused on genes related to the catecholamine neurotransmission, with 13. Although no genome-wide significant associations were found, the metabotropic glutamate receptor 7 (GRM7) and two SNPs within the SLC6A2 gene showed potential involvement in MPH response. Using that sample, Mick et al.14 conducted a secondary GWAS of changes in blood pressure after MPH therapy and detected nominal evidence for genes functionally related to blood pressure regulation and other cardiovascular phenotypes, including a SNP in a K+-dependent Na+/Ca2+ exchanger (SLC24A3). Furthermore, despite the fact that GWAS have been useful to identify genetic risk loci for multiple complex conditions, yet the functional effects of the trait-associated variants and the underlying pathological mechanisms remain mainly elusive.Given that candidate gene-based investigations have not reached many compelling results, genome-wide association studies (GWAS) may represent an alternative, hypothesis-free approach to unravel the molecular mechanisms implicated in MPH treatment. To date, only one prior GWAS evaluated the efficacy of a MPH transdermal system in 187 children with ADHDBased on the absence of clear conclusions regarding MPH response raised by previous genetic studies, we undertook a GWAS of MPH efficacy in 173 ADHD paediatric patients and, for the first time to our knowledge, we integrated data from functional annotation, expression quantitative trait loci (eQTL) and enrichment analyses to characterise the biological pathways associated with treatment response. Additionally, we performed a polygenic risk score analysis and a meta-analysis across the study sample and an independent population of 189 ADHD adult patients.The study sample included 173 ADHD paediatric patients for whom MPH was prescribed. Subjects were required to satisfy full DSM-IV criteria for ADHD, be under 18 years of age, Spanish of Caucasian origin and have never received MPH treatment. Patients with an IQ below 70 or having pervasive developmental disorders were not eligible for the investigation. Additional exclusion criteria included schizophrenia or other psychotic disorders; adoption; sexual or physical abuse; birth weight <1.5 kg; any significant neurological or systemic disease that might explain ADHD symptoms; and clinical contra-indication to MPH. Comorbid oppositional defiant disorder, conduct disorder, depression and anxiety disorders were allowed unless determined to be the primary cause of ADHD symptomatology. The study was approved by the Ethics Committee of the Hospital Universitari Vall d’Hebron and all methods were performed in accordance with the relevant guidelines and regulations. Written informed consent was obtained from parents/caregivers.15.Diagnoses of ADHD and comorbidities were established by child psychiatrists blind to patients’ genotypes through the Present and Lifetime version of the Kiddie Schedule for Affective Disorders and Schizophrenia for School-Age Children (K-SADS-PL). Furthermore, families were interviewed with the Clinical Global Impression-Severity scale (CGI-S). Additional information on clinical assessment is available elsewherePatients were treated according to the program’s recommendations of initiating treatment with MPH at low to moderate dose and titrating to higher doses until no further clinical improvement or limiting adverse effects were observed. The mean daily dose of MPH prescribed was 1.06 mg/kg (SD = 0.28). Risperidone was the most frequent concomitant drug.16, which ranges from 1 (‘very much improved’) to 7 (‘very much worse’), as the primary outcome measure of treatment success. Those patients rated with a CGI-I score of two points or less after eight weeks of treatment were considered as responders, while the remaining were classified as non-responders.We considered the Clinical Global Impression-Improvement scale (CGI-I)17. A total of 173 samples were genotyped on the Infinium PsychArray-24 BeadChip platform , which covers 588,628 markers, and processed at the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard . Pre-imputation quality control and principal components analysis were implemented following the QC and PCA modules from the Ricopili with the default settings (https://sites.google.com/a/broadinstitute.org/ricopili/). Genotype imputation was performed with the pre-phasing and imputation strategy using the EUR population of the 1,000 Genomes Project Phase 1 dataset as the reference panel (http://www.1000genomes.org/). We assured the accuracy of the imputation data by filtering best-guess genotypes for an info score <0.3. This resulted in a total of 11,051,824 markers eligible for association tests.Genomic DNA was isolated from peripheral blood leukocytes by a salting out procedure18. Individuals exhibiting high rates of genotype missingness (>98%) were removed, as well as SNPs with low call rate (<0.99), MAF < 0.01 or failing Hardy-Weinberg equilibrium test (P < 1e-06).Before GWAS analysis, further quality control measures were applied using the PLINK softwareFinally, 173 subjects and 3,566,199 variants were tested for association with MPH response through logistic regression under an additive model, which included those clinical variables  and principal components  significantly associated with clinical outcome (P ≤ 0.05) as covariates.http://snpinfo.niehs.nih.gov/)19 to prioritise those that were more likely to affect protein sequence, transcriptional regulation, mRNA splicing or miRNA binding based on functional annotation. GenomePipe parameter values included: GWAS population = CEU; study population = CEU; flanking region = 200,000 bp; GWAS P-value < 0.05; LD threshold = 0.8; and MAF = 0.01 for all prediction methods. Additionally, we combined both the predicted conserved transcription factor-binding sites (TFBS) with the regulatory potential score  to improve predictions as suggested in several studies22.Among the SNPs showing nominal association with treatment outcome (P < 0.05), we used the genome pipeline of SNPinfo . IPA was also used to test for over-representation of genes previously studied in either ADHD or treatment outcome. Candidate genes for ADHD or MPH response were selected based on the gene list provided by the ADHDgene database (http://adhd.psych.ac.cn/index.do)25 and a comprehensive search for published reviews of ADHD genetic and pharmacogenetic studies31. Thus, a total of 436 genes were considered (Supplementary Table B-H) < 0.05 as significance threshold, were applied in all analyses. To achieve meaningful statistics and interpretation of the results, we restricted the enrichment analysis to those annotation terms that included ≥2 genes of our dataset.The biological functions and pathways related to genes containing at least one SNP nominally associated with both MPH response and human cortical expression levels (referred to as eSNPs) were assessed through the Ingenuity Pathway Analysis software (IPA)  predicted treatment outcome in an independent sample of patients with ADHD (target population). The target population comprised 189 Brazilian adults from the Adult ADHD Outpatient Clinic of the Hospital de Clínicas de Porto Alegre, who underwent immediate-release MPH treatment. Diagnoses of ADHD and comorbidities, as well as inclusion/exclusion criteria, were achieved as previously described33. The outcome measures of MPH treatment were the CGI-S scale, applied before medication and at least four weeks after its beginning, and the CGI-I scale. Drug response was defined following the criteria used in the discovery sample. Similarly, samples were genotyped and imputed using the same platform, imputation protocol and reference panel. The resulting dataset consisted of 7,304,149 SNPs with an info score >0.6, a genotype call probability >0.8 and a missing rate <0.02.We generated polygenic risk scores (PRS) based on the results of the present GWAS using the Polygenic Risk Score software (PRSice)Potential confounders were included as covariates in the PRS model if they were associated with MPH response (P ≤ 0.05) in the target sample , as well as the 10 first principal components to control for population stratification.The eSNPs nominally associated with MPH response in the discovery sample were meta-analysed across the discovery and the target population used in the PRS analysis by the inverse-variance weighted method. The threshold for significance was set at P ≤ 1.52e-03 under the more conservative Bonferroni correction, taking into account 33 SNPs.The datasets generated and/or analysed during the current study are not publicly available due to ethics constraints but are available from the corresponding author on reasonable request.Subjects were predominantly male (84.4%), with an average age at assessment of 9.59 (SD = 2.91) years (range 5–17). One hundred and thirty-one participants (75.7%) met DSM-IV criteria for ADHD-combined subtype, 37 (21.4%) had ADHD-inattentive subtype and 5 (2.9%) were diagnosed with ADHD-hyperactive-impulsive subtype. Comorbid disorders were present in a modest number of patients (22.5%), the main ones being disabilities in reading and writing (12.7%), oppositional defiant disorder (5.8%) and tic disorders (1.7%). One hundred and forty-one subjects (81.5%) responded favourably to treatment according to the CGI-I scale, while 32 (18.5%) failed to show a clinical response to MPH. Responders and non-responders were comparable with regard to age, sex, ADHD subtype, comorbidity, use of concomitant medication, MPH dose and drug formulation (P > 0.05). There were significant differences, however, in the severity of symptoms as assessed by the CGI-S scale (P < 1e-03), with children resistant to MPH scoring higher at the baseline evaluation than children showing clinical improvement (Supplementary Table B-H = 1.56e-31).No variant reached genome-wide significance (P < 5e-08). However, the set of 4,709 genes containing SNPs nominally associated with MPH response , with eight SNP-gene pairs surpassing the 0.05 false discovery rate (FDR) threshold: rs12302749-SPSB2, PFDR = 1.13e-05; rs1061115-PYROXD2, PFDR = 2.17e-04; rs2071421-ARSA, PFDR = 7.26e-04; rs11553441-RRP7A, PFDR = 7.26e-04; rs4902333-CHURC1, PFDR = 7.26e-04; rs17279558-GGH, PFDR = 0.013; rs9901673-SENP3, PFDR = 0.023; and rs17685420-PEBP4, PFDR = 0.041 , and showed over-representation of genes implicated in abnormal morphology of molecular layer of cerebellum (PB-H = 0.012), abnormal morphology of white matter (PB-H = 0.012), morphology of axons (PB-H = 0.012), morphology and length of neurites , coordination (PB-H = 0.022), and formation of hippocampus (PB-H = 0.033). Interestingly, categories related to neurological diseases, psychological disorders and behaviour were also significantly enriched, including learning deficit (PB-H = 0.012), hyperactive behaviour (PB-H = 0.015) and spatial learning (PB-H = 0.018) , P = 7.90e-05), followed by additional compelling markers such as rs2071421 within ARSA (OR = 2.63 (1.29–5.37), P = 7.71e-03), rs2886059 in ALDH1L1 (OR = 2.30 (1.14–4.66), P = 0.020), and rs17712523 in CDH23 (OR = 2.13 (1.07–4.24), P = 0.031).Finally, in order to assess the predictive value of our findings we first computed PRS derived from the present GWAS in an independent sample of ADHD adult patients for whom data on response to MPH were available. The demographic and clinical characteristics of the target population according to the response status are presented in Supplementary Table To our knowledge, this is the first study investigating the genetic basis of MPH response from an integrative perspective that combines GWAS data, functional annotation, eQTL in relevant tissues to ADHD and pathway enrichment analyses. Our results highlight genes related to nervous system development and function, neurological diseases and psychological disorders. Thus, this comprehensive strategy provides a better understanding of the molecular mechanisms implicated in MPH treatment effects and suggests promising candidates that may contribute to clinical outcome.cis-eQTL analysis in human brain, and we identified three candidates previously investigated in ADHD: ALDH1L134, CDH2335 and CMTM836. Of these, CMTM8 showed overlapping association between adult ADHD and bipolar disorder36, and ALDH1L1, which yielded suggestive results in the present meta-analysis of MPH response, has been related to other neuropsychiatric conditions such as major depressive disorder or schizophrenia38. In addition, the ALDH1L1 locus was found among the top hits of a GWAS conducted on children and adolescents with ADHD34 and contains non-synonymous rare variants identified through whole-exome sequencing in an ADHD nuclear family39. Similarly, CDH23 harbours one of the top SNPs from a pooling-based GWA of adult ADHD35 and reached nominal significance in our meta-analysis. CDH23 is a member of the cadherin superfamily that mediates calcium-dependent cell-cell adhesion. The activity of cadherins depends on their anchorage to the neuronal cytoskeleton through proteins termed catenins , which in turn activate KALRN, a key regulator of dendritic spine development and synaptic plasticity underlying learning and memory40. This is of particular interest since catenin-cadherin cell-adhesion complexes are important in cerebellar and hippocampal lamination41 and both CTNNA2 and KALRN have shown nominal associations with clinical outcome in our GWAS. In this sense, Park et al.41 demonstrated that mice lacking the actin-binding domain of Ctnna2 (cdf-mutant mice) exhibited abnormal morphology of cerebellum and hippocampus. Moreover, the cdf-mutant mice showed an impaired control of the startle response and deficits in startle modulation have also been found in ADHD patients43. Therefore, cell-adhesion molecules and regulators of synaptic plasticity may play a role in MPH treatment effects, which is in agreement with data from genome-wide linkage and association studies pointing to cadherin13 (CDH13) as one of the most consistent candidates implicated in ADHD pathophysiology. Specifically, CDH13 was detected in three independent GWAS44 and lies within the 16q22-16q24 region identified in a meta-analysis of seven ADHD linkage scans45. Furthermore, SNPs in this gene have been linked to defects in verbal working memory and hyperactive/impulsive symptoms in subjects with ADHD47, addiction vulnerability and drug dependence 49.In our attempt to improve earlier genetic studies by bridging the gap between genotype and phenotype, we prioritised the nominally significant SNPs based on functional annotation and 53. In addition to structural alterations, ADHD patients exhibit deficits in neural functioning, which may be normalised by MPH. In this sense, Rubia et al.56 demonstrated that MPH restores the aberrant activation and functional connectivity in attention, motivation and interference inhibition networks, as well as during error processing, thus improving neuropsychological performance of subjects with ADHD.Pathway enrichment analysis provided further evidence for neuroplastic changes in response to MPH treatment, considering the over-representation of genes involved in morphology of neurons, neuroglia, white matter and brain regions relevant to ADHD  that we found among eGenes associated with drug response. Our results are in accordance to a wealth of data from neuroimaging studies showing that unmedicated ADHD patients present cortical thickness and reduced white matter volume in several areas of the brain compared to healthy subjects, while medicated children do not differ from control group57. Given that serine proteases are implicated in many processes during development and tissue homeostasis , disturbances in their activity on the nervous system have been proposed as a possible pathological mechanism for neurological disorders58. Indeed, Hohman et al.59 identified a gene-gene interaction involving PEBP4 associated with late onset Alzheimer’s disease (AD) across 13 independent datasets, and decreased expression levels have been found in hippocampus of both AD patients and mouse models for another phosphatidylethanolamine binding protein, the PEBP162, which has also shown alterations after methamphetamine and morphine administration64. Additional compelling results were detected for ARSA, SPSB2, CORO7 and PIGM. The ARSA gene encodes the arylsulfatase A, whose deficiency is characterised by decline in school performance, emergence of behavioural problems and neurologic symptoms, such as cerebellar ataxia, among others65. SPSB2 has been associated with borderline personality disorder in a genome-wide methylation analysis66 and CORO7, which has shown to be important in brain development67, was identified as a novel candidate gene for emotionality by comparing the expression profile of two mouse lines with either high or low anxiety-related behaviour68. Finally, mutations in the PIGM gene, which encodes a protein involved in the synthesis of the glycosylphosphatidylinositol anchor, have been reported in individuals with severe neurological features, including seizures, muscular hypotonia and intellectual disability69.It should also be noted that 15 out of the 32 eGenes included in the pathway enrichment analysis harboured variants which provided preliminary evidence for an association with clinical outcome across the discovery and an independent sample. Our top hit from the meta-analysis, rs17685420, is located in the phosphatidylethanolamine binding protein 4 (PEBP4), a member of an evolutionary conserved family of proteins with pivotal biological functions such as cell proliferation and survival, stimulation of acetylcholine synthesis and inhibition of serine proteasesCTNNA2 , PARD3B , LRP1B  and GRM7 , were significant at P < 1e-03 in the present GWAS analysis. In particular, the metabotropic glutamate receptor 7 (GRM7), which is widely expressed in brain regions relevant to ADHD such as the cerebral cortex, the hippocampus and the cerebellum70 and has been associated with the disorder73, was also found among the top hits in a prior GWAS of MPH efficacy13, thus supporting the role of the glutaminergic system as a moderator of treatment outcome.Another interesting finding arising from our research is the significant enrichment for candidates previously related to ADHD or MPH response detected among the set of genes nominally associated with treatment outcome. It is worth mentioning that four of these candidates, namely et al.13 , the use of an integrative approach that combines GWAS data with bioinformatic methods, and the follow up of our top signals in an independent cohort, which did increase the association of a number of markers located in loci with biologically plausible functions . Nevertheless, some limitations should also be considered when interpreting these results. Given the limited sample size, the present study might not be sufficiently powered to detect individual variants of modest effects and we did not identify any loci reaching the genome-wide threshold. This constraint, however, is heavily conditioned on the difficulty to find the required phenotype as shown by the sample size of the studies included in the last meta-analysis of candidate gene-based investigations on MPH response74. The small dimension of our paediatric sample could also explain the lack of significance of the PRS derived from the GWAS results in an independent population of ADHD adult patients. Alternatively, this discrepancy may be attributed to differences in the genetic background and the clinical heterogeneity  of ADHD among children and adults, as suggested by most of the pharmacogenetic studies conducted in adult samples, which failed to replicate variants previously identified in children and adolescents75. Additional methodological aspects or distinct environmental influences between the discovery and the target population may also be responsible for the absence of association.The main strengths of our design include the coverage of a considerably higher number of genetic variants in comparison with the study from Mick In conclusion, despite not reaching any genome-wide significant association, our results are consistent with previous findings and highlight genes related to morphological abnormalities in brain regions important for motor control, attention and memory, thus supporting the use of bioinformatic and biological evidence as a complement to GWAS data to disentangle the genetic basis of MPH response.Supplementary InformationSupplementary Table S3Supplementary Table S4


This study analyzed the prevalence of attention deficit hyperactivity disorder (ADHD) medication use among children and adolescents in Korea between January 1, 2007 and December 31, 2011.Using the Korea National Health Insurance claims database, we identified patients between one and 17 years of age who had at least one medical claim for the diagnosis of ADHD . The annual prevalence of ADHD diagnoses was calculated, using national census data from Statistics Korea on the population aged between one and 17 years as the denominator. The prevalence was age-standardized using the 2010 population as the standard population. The number of patients who were treated with methylphenidate and/or atomoxetine and the prevalence of total patients with ADHD that were treated with either drug were also calculated for each year. All analyses were stratified according to gender and age group .The number of patients diagnosed with ADHD increased from 72,704 persons (0.71%) in 2007 to 85,468 persons (0.93%) in 2011. The annual age-standardized prevalence of ADHD diagnoses increased from 0.67% in 2007 to 0.94% in 2011. The prevalence of methylphenidate use among children and adolescents with ADHD decreased from 73.91% in 2007 to 70.33% in 2011, whereas that of atomoxetine use increased from 5.77% in 2009 to 13.09% in 2011.While methylphenidate remains the most commonly prescribed ADHD drug, the use of atomoxetine has increased. Attention deficit hyperactivity disorder (ADHD) is the most common pediatric mental disorder, and the prevalence of ADHD is increasing in many parts of the world . The useIt has been documented that methylphenidate has greater effects than atomoxetine on performance measures of sustained attention in youths with ADHD . The ratThis study was conducted using the Korea National Health Insurance (NHI) claims database. The study subjects consisted of children and adolescents in Korea aged between one and 17 years who had been diagnosed with ADHD between January 1, 2007 and December 31, 2011. We identified patients who had at least one medical claim containing an International Classification of Diseases, 10th revision code for ADHD (F90.0) as a primary or secondary diagnosis. The ADHD medications included methylphenidate and atomoxetine prescribed at least once in inpatient or outpatient settings. Methylphenidate and atomoxetine are the only drugs that have been approved for the treatment of ADHD in Korea; dexamphetamine has not been approved. All preparations of methylphenidate, such as immediate release and sustained release formulations, were included.The annual prevalence of ADHD diagnoses was calculated using the national census data from Statistics Korea on the total population aged between one and 17 years as the denominator. The prevalence of ADHD diagnosis was age-standardized using the 2010 population as the standard population. The number and proportion of patients with ADHD who were treated with either methylphenidate or atomoxetine were also calculated for each year. The number of prescriptions of ADHD medications per year and the prescribed days of ADHD medication per patient were also estimated. All analyses were stratified by gender and age group .To examine the time trend of prevalence, the monthly numbers of patients diagnosed with ADHD and patients treated with medications were calculated and plotted. Drug treatment groups were categorized into methylphenidate users, atomoxetine users, and combined users.All statistical analyses were performed using SAS version 9.3 . The study protocol was approved by the institutional review board (IRB) of the Sungkyunkwan University (IRB no. 2016-08-013).Overall, fewer than 1% of children and adolescents in Korea were diagnosed with ADHD in 2007-2011. The total number of patients diagnosed with ADHD increased from 72,704 persons (0.71%) in 2007 to 85,468 persons (0.93%) in 2011. The age-standardized annual prevalence of ADHD diagnosis increased from 0.67% in 2007 to 0.94% in 2011. The prevalence increased from 1.07% to 1.41% in boys and from 0.30% to 0.41% in girls over the study period. The prevalence increased from 1.09% to 1.45% in children 6-12 years of age and from 0.58% to 0.94% in those 13-17 years of age. The mean (±standard deviation [SD]) age of the diagnosed patients increased from 10.41 (±3.18) years in 2007 to 11.19 (±3.20) years in 2011. The mean age of patients on methylphenidate or atomoxetine increased as well. The number of diagnosed patients aged 1-5 years decreased from 2,944 (0.13%) to 2,449 (0.11%), while the number of patients 13-17 years of age diagnosed with ADHD increased from 20,316 (0.58%) to 31,413 (0.94%) between 2007 and 2011 .Moreover, the monthly number of ADHD diagnoses and patients prescribed medication showed generally upward trends, except for atomoxetine use . The majThis study showed that less than 1% of children and adolescents in Korea were diagnosed with ADHD in 2007-2011. A recent study in Korea also showed that the prevalence of ADHD diagnosis and medication use in the pediatric population aged 6-18 years during 2008-2011 was 0.799% and 0.610%, respectively . The preThe age-standardized annual prevalence of ADHD diagnoses in Korea increased substantially, from 0.67% in 2007 to 0.94% in 2011. Increasing trends have also been reported in many other countries. The rate of ADHD diagnosis in the US increased from 2.5% in 2001 to 3.1% in 2010 [We found that the age structure of patients diagnosed with ADHD changed over time, with the mean age of patients becoming older. The number of patients aged 1-5 years decreased, while more patients aged 13-17 years were diagnosed with ADHD. Likewise, increases in the prevalence of ADHD in Canada were steeper among school-age children than among preschoolers between 1994 and 2007 .A gender disparity in the prevalence of ADHD diagnosis and medication use was also noted in this study. Not only was the number of boys diagnosed with ADHD greater than that of girls, but the proportion of ADHD patients prescribed medication was also higher for boys than for girls. This is consistent with previous findings . NonetheAlong with the increasing prevalence of ADHD diagnoses over time, the number of prescriptions of ADHD medication per year and the number of prescribed days of ADHD medication per patient also increased. A prior study showed that 69% of newly diagnosed ADHD patients in Korea were pharmacologically treated and that methylphenidate was the most commonly used first medication . Our datOur data suggest that a seasonal trend was present in ADHD diagnoses and the use of methylphenidate. This seasonal pattern appears to be attributable to school-year dosing in children; the number of diagnoses and methylphenidate users decreased in school-break months in the school calendar in Korea. However, similar seasonal variations were not observed for atomoxetine and combined ADHD drug users. It is plausible that our observed seasonal variation may be associated with the inappropriate prescribing of methylphenidate. Anecdotal experiences and/or perceptions of the incorrect belief that the use of methylphenidate may heighten a child’s learning ability, thus improving test scores, may have contributed to the use of methylphenidate and the increase in ADHD diagnoses required for its prescription during spring and fall semester, followed by discontinuation during school breaks. It is possible that this phenomenon was observed only for methylphenidate, an ADHD drug that has been widely used since the 1990s, but not for atomoxetine, a relatively new drug.A limitation of this study is that it used data on patients with ADHD obtained from the NHI database. It is highly likely that psychological disorders such as ADHD may be diagnosed and treated outside of the NHI system and paid for with out-of-pocket payments due to the stigma attached with the disorder. Therefore, the prevalence of ADHD diagnoses and medication use might have been underestimated in this study.Additionally, the study subjects were limited to the population aged 17 years and younger, as most ADHD drugs approved by the Ministry of Food and Drug Safety are indicated for children and adolescents aged 6-17 years. However, as the prevalence of ADHD diagnoses has recently increased in adults and ADHD drug reimbursement has also been expanded to include adults (18-65 years) , future In conclusion, this study revealed that the prevalence of ADHD diagnoses and medication use in Korea increased from 2007 to 2011, although it remained relatively low compared to Western countries. The proportion of methylphenidate users among pediatric patients with ADHD decreased while the proportion of atomoxetine users increased. Future research is needed to examine comparative drug use patterns and how changes in the epidemiology of ADHD medication use affect patient safety.


Globally, low birth weight (LBW) remains a leading cause of neonatal and infant mortality and poses significant challenges toward the progress of achieving infant mortality-related goals. Experience from developed countries shows that two major causes of LBW (premature delivery and intrauterine growth restriction) can be averted to a great extent by adequate utilization of maternal health-care services, during pregnancy. In this study, we attempt to measure the prevalence of LBW in Zimbabwe and explore the association between adequate utilization of prenatal care (PNC) services and LBW in Zimbabwe. We also explore other possible associations with LBW.This study was based on nationally representative, cross-sectional data from Multiple Indicator Cluster Survey round 5, conducted in 2014. Participants included 3,221 mothers from both rural and urban areas. The participants were selected regardless of their current pregnancy status. Sample characteristics were presented using descriptive statistics. Association between utilization status of ANC and LBW was measured by chi-square (bivariate) test and logistic regression methods.Prevalence of LBW was 12.8%. There was 11% reduction in the odds of having LBW babies for participants from urban area when compared with rural area . When compared to women with higher education, those having primary/below primary and secondary level qualification had higher odds of experiencing LBW babies by 73 and 56%, respectively. Participants who had less than four PNC/ANC visits had 34% higher odds  than those with at least four visits, and those who had given birth more than once, had 38% lower odds  of giving birth to LBW babies when compared to those who had given birth only once.per se and not only in terms of hospitalization but also in terms of outpatient and physician visits during the first year of their life.The findings of this study have programmatic and policy implications for low-resource nations and suggest that promoting access to ANC services especially in the rural areas is likely to reduce prevalence of LBW in Zimbabwe. This is important as LBW babies consume lot of health resources  Low birth weight (LBW) is regarded as an important predictor of public health and a measure of progress toward sustainable development goals (SDGs) in developing countries . The SDGIn 2003, about 17% of infants in developing countries were born with LBW. Though there were disparities in the prevalence of LBW within countries, on the average, about 13% of births in sub-Saharan Africa (SSA) were categorized as LBW . Apart fAlso, previous studies have attempted to explore the impact of maternal health-care services (MHS) utilization on birth weight outcomes. A growing body of evidence suggests that utilization of prenatal care (PNC) services holds a great potential in improving pregnancy outcomes. Intuitively, maternal health status and access to MHS are two very crucial indicators of child health. However, the utilization of PNC services remains remarkably low in the countries of the SSA region, including Zimbabwe . StudiesPreterm birth and intrauterine growth retardation (IUGR) are cited as the two main clinical factors behind LBW. Much of the information on LBW is hospital based, and there is dearth of information on community-based factors . Most ofThere are several variables when it comes to confounding effects on a dependent variable like LBW. For example, one study found that 90 LBW infants per 1,000 live births were born from 1975 through 1979 in South Carolina. In this study, after controlling for the confounding variables like education and wealth inequity, presence of Black ancestry was found as an independent variable affecting birth weight of the infant . SimilarIn addition, one study reported several risk factors associated with the presence of LBW. However, socioeconomic status was associated with only extreme cases of LBW –18. It hThe MICS program was launched in the mid-1990s with the aim to provide quality data about individuals (women and children) and households, on a wide range of socioeconomic and health indicators. Information collected is internationally comparable and range from crucial topics, such as malaria, HIV, health knowledge, and health service utilization. Surveys are designed, based on the assessed priorities of data requirements at national and subnational levels. In conjunction with UNICEF, the MICS program is currently operational in 109 countries and contributes to policy making toward and promotion of maternal and child health by providing data sources in the given countries. UNICEF Regional Office provides technical support for the MICS program.Using 2012 census data as the sample frame, census enumeration areas, being used as primary sampling units, were defined and selected from the two strata, urban and rural created from each of the nine provinces of Zimbabwe except one province, the tenth province of Zimbabwe, Bulawayo, which had no stratification of urban and rural areas. This was the first stage of sampling in which specified number of clusters, a total of 683, was selected with probability proportional to size. The number of households in the clusters determined the size. In the second stage, a list of households was separately created through field visits owing to the inadequacy of census listing of households. A total of 25 households were selected in each cluster resulting in a total selection of 17,075 households. One cluster in Masvingo province was not enumerated due to flooding and relocation of the households.The survey included four types of questionnaires: one for the households, one for women aged 15–49 years, one for men aged 15–59 years, and one for children aged below 5 years. For this study, we utilized women sample dataset to gather information on LBW and the related variables. From the selected households, 12,507 women were identified for interview, and finally, 11,510 were successfully interviewed with a response rate of 92%. Face-to-face interviews were conducted for all women aged 15–49 years in the selected households and men aged 15–59 years in every third household from the sampled households, by use of questionnaires covering socioeconomic, demographic, and health indicators. Overall response rate was 98%.The outcome variable was LBW and was defined as birth weights less than 2.5 kg. Teenage pregnancy was defined as pregnancy with age of mother less than 19 years at the time of the survey.The baseline characteristics of the sample population were presented by descriptive statistics (numbers and percentages). Prevalence of LBW across the explanatory variables was presented in numbers, and percentages and the difference between two groups  were estimated by Chi-square bivariate tests. The explanatory variables, which showed significant associations with LBW, were entered in the regression model .p-Value of <0.05 (two-tailed) was considered statistically significant. All analyses were performed with SPSS® 21 for Mac.Regression analysis was then carried out to determine the strength of association between the exposure variables and the outcome, LBW. Results of regression were reported in terms of odds ratios and 95% confidence interval. http://mics.unicef.org/surveys.Data used in this study are secondary, available in public domain, and were obtained through registration in the MICS website. Furthermore, institutional approval was not necessary since UNICEF who approved the data for this research has the data available under public domain. More details regarding the MICS data and ethical standards are available at: The sample included 3,221 women in the 15–49 years age group. The prevalence of LBW babies was 12.8% at national level. Province-wise distribution of sample population and LBW babies are shown in Figures p = 0.036. Regarding wealth status, more than half of the women reported residing in poor economic conditions (51.7%). Of these, 14% had LBW babies compared to 11.6% of those from non-poor background, and the difference was statistically significant. A higher percentage of women reported having ever drunk alcohol as compared to those having ever smoked. However, both factors were found statistically not significant for the occurrence of LBW babies. About one-third of women reported last pregnancy as unplanned (30.9%), and 33.5% reported becoming pregnant before reaching 18 years. Only about a quarter (23.7%) of the women received at least four prenatal/antenatal visits and 70.2% were primiparous and both these variables were statistically significant associated with the occurrence of LBW babies.Table The results of univariable and multivariable regression analyses are presented in Table Our main finding is that the proportion of babies with LBW was high similar to the report of Onis et al. . The meaAnother factor examined is the wealth status of the women. The proportion of LBW among women of low economic class was higher when compared to those in high economic status, which is similar to the findings of Hirve and Ganatra  and YayaUsing multivariate analysis to determine key factors of LBW and adjust for confounders, women who attended antennal care below minimum required visits had more risk of giving birth to babies with LBW when compared to women who paid adequate visit for PNC; this is similar to previous studies . More soThe study involved a representative and large data set. This study has become one of the foremost in Zimbabwe to reveal the association between PNC factors and LBW. Notwithstanding, the study had a few drawbacks. Use of secondary data implied that the measurement of indicators, selection of variables, and data quality determination were not under our control. Also, the low variability in birth weight that was explained by independent variables used in the regression model suggests that there were some confounding factors not accounted for. In addition, the missing link is that some mothers in Zimbabwe may have given birth at local centers and hence their babies were not weighed at birth.This study explored the factors leading to inadequate utilization of PNC services associated with LBW. The findings indicate that utilization of PNC services have a great potential to improve in the context of LBW babies. Parity is significantly correlated with the occurrence of LBW and validates the findings from previous studies. The results of this study suggest that for reducing LBW, the strategy needs to focus attention prevention to facilitate better weight gain during pregnancy, focusing more on the regular antenatal care visits. Free ANC services must be provided for all pregnant women to encourage regular attendance to health facilities irrespective of their status with respect to the National Health Insurance Scheme. Within the limits of this study, however, antenatal care, parity, wealth status, residence, and educational attainment contributed significantly in predicting birth weight of babies in Zimbabwe.The implication of this study is that policy makers and stakeholders in health care may be overly optimistic about the ability PNC services campaigns will solely encourage utilization during pregnancy to improve the birth weight and health of children.http://mics.unicef.org/surveys.Data for this study were sourced from the Multiple Indicator Cluster Survey (MICS) program and available here: No consent to publish was needed for this study as we did not use any details, images, or videos related to individual participants. In addition, data used are available in the public domain.SY and GB participated in the conception and design of the study, data cleaning and analysis, results interpretation, and drafting and revision of the manuscript. SY, GB, VS, and ME participated in review of statistical methods, results interpretation, and revision of the manuscript; read and approved the final 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. The reviewer DM and handling Editor declared their shared affiliation, and the handling Editor states that the process nevertheless met the standards of a fair and objective review.