Objectives: To assess the impact of long-term pharmacotherapy with guanfacine immediate- or extended-release (GXR), administered alone or as an adjunctive to a stimulant, on weight and height in children and adolescents with attention-deficit/hyperactivity disorder (ADHD).Methods: Data were extracted from U.S. Department of Defense medical records for patients 4–17 years of age at index date  with weight/height measurements for the analysis period (January 2009–June 2013) and the previous year (baseline). Longitudinal weight and height z-scores were analyzed using multivariable regression in three cohorts: guanfacine , first-line stimulant monotherapy , and unmedicated. Guanfacine cohort subgroups were based on previous/concurrent stimulant exposure.Results: The weight analyses included 47,910 patients  and the height analyses 41,248 . Mean initial exposure in the weight analyses was 237 days  for guanfacine and 257 days  for first-line stimulant monotherapy, and was similar in the height analyses. Modeling indicated that guanfacine monotherapy was not associated with clinically meaningful deviations from normal z-score trajectories for weight  or height . In patients receiving guanfacine adjunctive to a stimulant, modeled weight (n = 1657) and height (n = 1343) z-scores followed declining trajectories. In this subgroup, mean standardized weight/height had decreased during previous stimulant monotherapy. For first-line stimulant monotherapy, modeled weight  and height  z-scores followed declining trajectories during year 1. In the unmedicated cohort, modeled weight  and height  z-scores were stable.Conclusions: Guanfacine monotherapy (first-line or nonfirst-line) was not associated with marked deviations from normal growth in this modeling study of children and adolescents with ADHD. In contrast, growth trajectories followed an initially declining course with stimulants, whether given alone or with adjunctive guanfacine. Guanfacine extended release (GXR) is a long-acting nonstimulant treatment for patients with attention-deficit/hyperactivity disorder (ADHD)  recommends monitoring weight and height in children and adolescents receiving stimulants for ADHD because of concerns about growth retardation  shifted to a higher BMI category, and 8.2% (17/207) shifted to a lower category   administered as monotherapy or adjunctive to a stimulant, mean weight, height, and BMI percentiles in children and adolescents with ADHD were stable at 12 months ; or guanfacine adjunctive to stimulant treatment. Similar analyses of patients receiving first-line stimulant monotherapy and patients not receiving ADHD pharmacotherapy provided context for the guanfacine results. This retrospective, longitudinal, observational study used data from anonymized electronic medical records (EMRs) from the U.S. Department of Defense Military Health System (MHS), which provides health care to military families stationed in the United States and overseas. Weight and height measurements were not recorded in the MHS until October 2008, but data from January 1, 2003 to June 30, 2013 were extracted to provide historical information on diagnosis and treatment.z-scores and were based on a data extract of EMRs that included a prescription for guanfacine . Subsequently, two control cohorts were derived from a separate data extract of EMRs that included an ADHD diagnosis: those with a prescription for first-line stimulant monotherapy (any formulation of amphetamine or methylphenidate) and those with no prescriptions for an ADHD medication . ADHD was defined according to codes 314.0, 314.00, and 314.01 of the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) 2013  or an ADHD diagnosis (for patients with no documented prescriptions for a study medication during the study period).A guanfacine initiation date was also defined for patients receiving guanfacine during the study period. The baseline period was defined as the 12 months before the guanfacine initiation date for patients receiving guanfacine during the study period, or as the 12 months before the index date for all other patients. The initial period of exposure to a study medication was defined as the period between the guanfacine initiation date (for patients receiving guanfacine during the study period), or the index date , and the date of discontinuation or change in ADHD pharmacotherapy regimen, or censoring of observations. Observations were censored when the patient reached 20 years of age, at the end of the study period, or at loss to follow-up, whichever occurred first.In assessing discontinuation, gaps between study medication prescriptions of up to 30 days during the months of September to May and up to 121 days during the months of June to August were allowable to account for delays in renewing prescriptions and for drug holidays (structured treatment interruptions). For longer gaps, the patient was considered to have discontinued on the last day covered by the prescription that preceded the gap, under the assumption that medication was taken as indicated until all dispensed drug had been consumed.Included patients had a diagnosis of ADHD (at any time), were 4–17 years of age on the index date, had an EMR extending to at least 12 months before the index date, and had no prescriptions for an ADHD medication (a study medication or any formulation of atomoxetine) in the 12 months before the index date. Included patients also had a baseline weight or height measurement (the most recent from the baseline period), and at least one eligible postbaseline measurement.z-scores adjusted for age and gender were calculated according to the 2000 CDC growth charts for children and adolescents 2–20 years of age and the methods provided by the CDC  and occurred during the initial period of exposure to guanfacine (for patients with a guanfacine prescription) or a stimulant (for patients with a stimulant prescription but no guanfacine prescription), or during the postbaseline period (for patients not receiving ADHD pharmacotherapy).Weight and height Patients were assigned to one of three cohorts according to the study medications they were prescribed during the study period: guanfacine, first-line stimulant monotherapy, or unmedicated . No matcThe prescribed amount (in days) of a particular drug at a specified dose was defined as the sum of the length of all such prescriptions, ignoring overlaps . The total prescribed amount (in days) of a study medication  was defined as the sum of the prescribed amount of each particular drug at a specified dose, with overlaps of prescriptions for different drugs and/or doses capped at 90 days . Adherena priori power or sample size estimates were performed and no adjustments to alpha were made to control for multiple comparisons. All p-values are therefore nominal.In this retrospective database study, no z-score as the response variable and three with height z-score . An unstructured covariance matrix was used for the random effects . Several spatial covariance structures conceptually similar to an autoregressive structure  were examined in addition to the unstructured matrix that was ultimately used. Fixed-effect predictor variables (see the following two paragraphs) represented characteristics of patients or of ADHD medications received before or during the period covered by the regression analyses. There were no issues with model convergence and the unstructured covariance model was considered adequate. No variables were removed from the models.Multivariable regression  was carried out in SAS version 9.3 . Each cohort was analyzed separately and six models were constructed per cohort, three with weight Analyses of the guanfacine cohort used the baseline weight or height measurement (with the time of the measurement imputed to time = 0), and all weight or height measurements recorded during the initial period of guanfacine exposure and the 60 days afterward. Each model included the following fixed-effect predictor variables: age at baseline measurement (continuous), gender , guanfacine MPR during the initial period of guanfacine exposure (continuous), stimulant prescribed amount (in days) preguanfacine (continuous), use of atomoxetine before guanfacine exposure (binary), use of atomoxetine during guanfacine exposure (binary), and guanfacine cohort subgroup . The inclusion of an interaction term between time and subgroup allowed the trajectories for each subgroup to follow differently shaped paths.Analyses of the first-line stimulant monotherapy and unmedicated cohorts used the baseline weight or height measurement (with the time of the measurement imputed to time = 0), and all weight or height measurements recorded in the initial period of stimulant exposure and the 60 days afterward (first-line stimulant monotherapy cohort), or all weight or height measurements from the index date until censoring of observations (unmedicated cohort). Each model included the following fixed-effect predictor variables: age at baseline measurement (continuous), gender , and stimulant MPR during the initial period of stimulant exposure .post hoc regression analyses. Patients in the first-line guanfacine monotherapy subgroup, the first-line stimulant monotherapy cohort, and the unmedicated cohort were included in separate models, using the same weight or height measurements as the earlier analyses. Each model included a binary predictor variable to indicate whether a weight or height measurement was made before or on/after the index date, with linear and quadratic time at measurement as random effects.The impact of ADHD treatment initiation in treatment-naive patients was assessed in separate z-score shifts between the baseline measurement and the last measurement included in the regression analyses were analyzed post hoc in the guanfacine cohort subgroups. In the absence of guanfacine-specific recommendations for potentially clinically meaningful shifts, the criteria recommended for monitoring stimulant-treated individuals in the American Academy of Child and Adolescent Psychiatry (AACAP) Practice Parameter for the Assessment and Treatment of Children and Adolescents with ADHD were used, namely a shift in weight or height z-score crossing two percentile lines on a chart showing the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles , giving a mean time in the analysis of ∼10 months. Patients in the guanfacine cohort with previous (or concurrent) stimulant exposure had initiated stimulant a mean of ∼12–13 months (SD ∼11 months) before initiating guanfacine .z-scores at the index date  were similar across cohorts and higher than the reference population mean (0) (not shown). By the time of the baseline measurement, weight and height z-scores were substantially lower in patients in the guanfacine cohort with previous (or concurrent) stimulant exposure  at the index date (last measurement before stimulant initiation) to −0.075 [−0.138 to −0.013] at baseline (last measurement before guanfacine initiation), and mean height z-score fell from 0.231 [0.165–0.298] to 0.009 [−0.057 to 0.076]. Similar trends were seen in the nonfirst-line guanfacine monotherapy subgroup (not shown).Mean weight and height exposure . For exaThe mean time between the baseline measurement and the start of the regression analyses was ∼2–3 months across all cohorts, with high variance (SD ∼2–3 months) .Approximately half of patients had at least three postbaseline measurements , but by z-score trajectories, either when administered first-line or when administered nonfirst line  and declined in males .In separate analyses stratified by sex, modeled trajectories for combined pharmacotherapy remained stable in females   of stimulant before initiating guanfacine was a significant predictor of lower weight z-score  but not in females (p = 0.19), according to the model with the binary predictor variable  than a negative shift (2.0%), in contrast to combined pharmacotherapy   .This large database study is the first to present an analysis of longitudinal growth trajectories in children and adolescents with ADHD receiving guanfacine in a real-world clinical setting. The models covered a time period of over 3 years, but data became increasingly sparse with elongated follow-up beyond 1 year in cohorts receiving an ADHD medication and the mean analysis period was ∼10 months. Thus, trends observed during the first year of the study are more reliable than later trends.z-score trajectories followed those of the reference population norms   and controls (n = 289) indicates that extended use of stimulants is associated with suppression of adult height at 25 years of age .The initial trends in the first-line stimulant monotherapy cohort are consistent with the results of a quantitative analysis of 20 longitudinal studies of children and adolescents with ADHD receiving stimulant monotherapy with at least 1 year of follow-up, in which the authors concluded that stimulant treatment was associated with slower-than-expected increases in weight and height, an effect that attenuated over time  and matched controls (n = 124) who were followed up to a mean age of 22 years. In that study, the investigators concluded that any delays in expected growth had resolved by adulthood  Fourth Edition  are known to be unreliable  for those remaining is within an “acceptable” range as time progresses (Howell Another limitation is the high level of drop-out, meaning that trends at later time points were based on far fewer patients than trends at earlier time points. Although longitudinal regression results are minimally affected by randomly occurring drop-out, they can become seriously biased when drop-out is predicted by baseline or response variables (Gustavson et al. s Howell . In the Guanfacine monotherapy given first-line or following a stimulant was not associated with marked deviation from a normal growth trajectory at the group level in this large, retrospective regression modeling study of children and adolescents with ADHD. At the individual level, fewer than 5% of patients had a potentially clinically meaningful increase in weight, based on z-score shifts. The study confirmed that stimulant therapy, with or without guanfacine augmentation, is associated with slower-than-expected growth during the first year of treatment at the group level.These findings support current recommendations for regular monitoring of patients' weight and height to assess the potential impact of ADHD treatment regimens on growth.


Attention Deficit Hyperactivity Disorder (ADHD) is a developmental disorder characterized by severe inattention, hyperactivity, and impulsivity. This research aims to determine the frequency of ADHD symptoms in children who were treated in emergency paediatric services due to unintentional injuries.This study was carried out with children who were treated due to unintentional injuries in an Emergency Department. ADHD symptoms were evaluated using the DSM-IV-based Screening and Assessment Scale for Behavioural Disorders in Children and Adolescents.The study sample consisted of 89 girls (40.1%) and 133 boys (59.9%)—a total of 222 children. The participants ranged from 5 to 18 years of age, and the mean age was found to be 11.5±3 years. According to medical evaluations, the most common diagnosis for the unintentional injuries was soft tissue trauma (41.9%). The mean ADHD and ODD  scores of our study sample were, respectively, 19.9±12 and 7.7±5.7. The prevalence of children with possible ADHD was as high as 81.6% (179) and, for ODD, was 62.6% (139), according to cut-off values.Our results pointed out very high levels of ADHD and ODD symptoms among children who were treated at emergency services for accidental injuries. Appropriately screening for ADHD in children with accidental injuries and referring them to child psychiatry units may prevent later accidents and injuries. Responsible for 830,000 childhood deaths every year, accidents and injuries are a major public health problem as they are one of the main causes of death and permanent disability in children and adolescents , 2. PedeAttention Deficit Hyperactivity Disorder (ADHD) is a developmental disorder characterized by severe inattention, hyperactivity, and impulsivity . In commADHD causes loss of functioning, which has a negative impact on the academic and social lives of children , 9. BesiIt has also been suggested that ADHD may be accompanied by decreased life expectancy and increased accident and injury rates are thought to be one reason for this , 14. AloThe types of injuries associated with ADHD vary with age. For example, foreign body penetration into the nose and mouth was more frequently observed in younger children , while bVarious psychotropic drugs are used in the treatment of ADHD, and treatment response rates vary between studies. Two recent systematic review and meta-analyses have concluded that there is a significant decrease in the risk of unintentional injuries among ADHD children who are treated with ADHD medications , 24. Ano diagnosed with ADHD, but few publications have examined the rates of ADHD in children who are actually admitted to emergency services due to accidents or injuries [Though many studies have examined the rates of accidents and injuries in children with ADHD, it has been stated that these studies were mostly carried out in the USA and that their results could not be generalized to other cultures . Howeverinjuries . TherefoThis study was carried out with children and adolescents who were treated for accidental injuries between September and November 2017 in the Şanlıurfa Mehmet Akif İnan Training and Research Hospital Emergency Department. The participants who applied were primarily diagnosed and treated. Children and parents were informed about the study during an interview, and only patients who agreed to take part in the study and made an affirmation of their agreement have been considered in the research. Parents participating in the study were asked to complete a DSM-IV-based Screening and Assessment Questionnaire (Parent Form) for the children and adolescents, as well as a sociodemographical form, prepared by the authors, which was used to ascertain the parents' sociodemographic characteristics. Only the data of the families who fully filled out the forms were taken into account.For the purpose of the study, characteristics of the child and his/her parents and the economic situation of the family were gathered through the prepared form. Information on the accidents and injuries was filled in by examining the patient's medical file.This scale was developed by Turgay for scanning destructive behavioural disorders . Ercan e t-test was used to compare two groups with normal distribution, and the Anova test compared sets of more than two groups with normal distribution. A chi-square test was used for group comparisons of categorical variables. A value of p < 0.05 was considered statistically significant.The data was analysed with SPSS for Windows, version 23.0. Continuous variables in descriptive statistics were expressed as mean and standard deviations; categorical variables were expressed as numbers and percentages. The Mann-Whitney U test was used in analysing data with no normal distribution in binary group comparisons, and the Kruskall-Wallis test was used for comparing more than two groups with no normal distribution. Student's89 (40.1%) girls and 133 (59.9%) boys diagnosed with soft tissue injuries, burns, fractures, cuts/lacerations, and bleeding between September and November 2017 were included in the study . The mean age of children and adolescents was 11.5±3, the youngest being five years old and the oldest 18. The most frequent reason for application was falling off something or somewhere (41.9%), while the most common medical diagnosis, according to the physician evaluation, was soft tissue trauma (41.9%). In this process, 66 (29.7%) children required hospitalisation, while 32 (14.4%) required surgery. The sociodemographic characteristics of children and their families, the reasons for the emergency application, and their medical diagnoses are shown in There was no statistically significant difference between the age, reasons for presentation, and the medical diagnosis of injury in the girls (11.5±3.5) and the boys (11.5±3.2). Hospitalisations after the accident and surgical rates were also similar. However, it was determined that boys had a higher prevalence of psychiatric disorders (P = 0.047) and accident history (P = 0.002) in the past.Although there were no significant differences in the reasons for emergency service admission and medical diagnoses between the paediatric (5-12 years) and adolescent age groups (13-18 years), the adolescents had higher rates of hospitalisation (P = 0.034).ADHD symptoms in children were assessed using the DSM-IV-based Screening and Assessment Scale Parent Form for Behavioural Disorders in Children and Adolescents. From the scale filled out by the parents, the average score of inattentiveness was found to be 9.3±7, and the average score of hyperactivity-impulsivity was 10.6±7. The relations between the scale total, subscores, and demographic variables within the sample population are given in Inattentiveness, hyperactivity-impulsivity, and combined ADHD and ODD rates were calculated by accounting for cut-off values that was proposed by the developer of the scale. ADHD symptomatology was observed in 81.6% (179) of children who were admitted to emergency services with accidents and injuries, and ODD symptomatology was observed in 62.6% (139). The behaviour scores of 134 (60.4%) children exceeded the threshold values for both ADHD and ODD. The distribution of ADHD subtypes according to scale cut-off values is given in The analysis determined that the ADHD subtype in which inattentiveness is dominant was observed more frequently in males (72.9%) than in females (56.2%) (P = 0.010). There was, however, no difference in the distribution of ADHD and subtype diagnoses between female and male patients, nor between child and adolescent groups. t-tests; there was no significant difference between the groups in sociodemographic factors, including age and gender, postoperative hospitalization, and surgical necessity.Patients with ADHD (179) and without ADHD (43) were compared with a chi-square test and withχ2 = 9.815, P = 0.002) and children with a family member who had a psychiatric illness had more accidents  in the past. When children with both ODD and ADHD symptomatology (n = 134) were compared with children without ODD and ADHD symptomatology (n = 38), it was found that the number of individuals with a psychiatric disorder in the family  was higher in the comorbidity group. There was no other difference between the groups.The analyses also observed that male patients (23%; 7%, Our study shows that symptomatology of ADHD and ODD is observed in the majority of children who are admitted to emergency service due to accidental injuries. Given that the DSM-IV-based Screening and Assessment Scale used in our study highly predicts clinical ADHD diagnoses, this ratio is significantly higher than the rates established in the community sample of Turkish pupils . These rAlthough it is well known that children with ADHD diagnoses are accident-prone and have a risk of injury, most of the studies in this field only investigate the frequency of general accidents and injuries in children with ADHD , 30. TheResearch has reported that ADHD is associated with increased mortality rates in children and adults and that mortality rates are even higher when ADHD is accompanied by ODD or behavioural disorders . The higIn a similar study, ADHD frequency was reported to be 28% in children who were admitted to emergency services due to injuries, and the likelihood of ADHD was three times higher in children who were admitted to the hospital for injuries than in those who were admitted for appendicitis . In a stLange et al. conducted a comparable study in Germany, with a sample representative of western European society and stated that ADHD increases the risk of accidents, but electing to receive or not receive treatment may not affect the risk of accidents . Most stSince such results indicate that ADHD symptoms are common in children admitted to emergency services for accidents and injuries , 25, pubADHD has generally been observed more frequently in males, and the ratio of male to female is about 2:1 . It is, Beyond being merely an accident-prone individual, it has been stated that injuries to children and adolescents with ADHD are more severe; hospitalisations after the accident are longer; and disability rates are higher . AlthougIt has been reported that boys are exposed to accidents and injuries more often than girls . The datIn some publications, it has been stated that the types of injuries may vary according to age , 18, butMortality is reportedly increased in children with ADHD, and this correlates with increased accident rates in those children . Our stu


Attention-deficit/hyperactivity disorder (ADHD) is associated with atypical fronto-subcortical neural circuitry and heightened delay discounting, or a stronger preference for smaller, immediate rewards over larger, delayed rewards. Recent evidence of ADHD-related sex differences in brain structure and function suggests anomalies in fronto-subcortical circuitry may differ among girls and boys with ADHD. The current study examined whether the functional connectivity (FC) within fronto-subcortical neural circuitry differs among girls and boys with ADHD compared to same-sex typically developing (TD) controls and relates to delay discounting.n = 72, 20 girls) and TD controls . Fronto-subcortical regions of interest were functionally defined by applying independent component analysis to resting-state fMRI data. Intrinsic FC between subcortical components, including the striatum and amygdala, and prefrontal components, including ventromedial prefrontal cortex (vmPFC), anterior cingulate cortex (ACC), and anterior dorsolateral prefrontal cortex (dlPFC), was compared across diagnostic groups overall and within sex. Correlations between intrinsic FC of the six fronto-subcortical pairs and delay discounting were also examined.Participants include 8–12-year-old children with ADHD  and amygdala (weaker negative FC in ADHD), with the greatest diagnostic effects among girls. In addition, girls with ADHD show atypical intrinsic FC between the striatum and dlPFC components, including stronger positive FC with ACC and stronger negative FC with dlPFC. Further, girls but not boys, with ADHD, show heightened real-time delay discounting. Brain–behavior correlations suggest (1) stronger negative FC between the striatal and dlPFC components correlated with greater money delay discounting across all participants and (2) stronger FC between the amygdala with both the dlPFC and ACC components was differentially related to heightened real-time discounting among girls and boys with and without ADHD.Our findings suggest fronto-subcortical functional networks are affected in children with ADHD, particularly girls, and relate to delay discounting. These results also provide preliminary evidence of greater disruptions in fronto-subcortical FC among girls with ADHD that is not due to elevated inattention symptom severity, intellectual reasoning ability, age, or head motion.The online version of this article (10.1186/s11689-018-9254-9) contains supplementary material, which is available to authorized users. Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by developmentally inappropriate and impairing inattention, hyperactive, and impulsive behaviors. Etiological models of ADHD postulate dysfunction in fronto-subcortical neural pathways involved in executive functions and motivation as contributing to deficient self-regulation of cognition, behavior, and emotion , 2. ExecDelay discounting is central to many theories of ADHD, which postulate altered reinforcement sensitivity  either dEvidence of ADHD-associated disruptions in intrinsic fronto-subcortical functional connectivity (FC) using resting state functional MRI (rs-fMRI) has been inconsistent. In general, studies have shown aberrant FC of fronto-subcortical networks in children and adolescents with ADHD . HoRecent evidence suggests ADHD-related sex differences across behavioral and neural domains are another important inter-individual variable to consider. There is a surprising lack of research comparing girls and boys with ADHD to same-sex TD children despite reports that the proportion of males to females diagnosed with the disorder has fallen to approximately 2:1 . EvidencThe current study adds to the existing literature and builds off of our previous findings of greater delay discounting in girls, but not boys, with ADHD by examining ADHD-related sex differences in intrinsic FC of fronto-subcortical brain networks implicated in ADHD and delay discounting. We hypothesized that fronto-subcortical intrinsic FC would be disrupted in ADHD with the greatest differences involving ventromedial regions of the PFC. Given previous evidence of ADHD-related differences in delay discounting being greater among girls, we expected greater disruptions in fronto-subcortical FC among girls. We also examined correlations between delay discounting and intrinsic FC of fronto-subcortical networks.A total of 147 8–12-year-old children participated in this study: 72 with ADHD (20 girls) and 75 TD children (21 girls).n = 121, WISC-IV [n = 26, WISC-V [An initial telephone screening with a parent was conducted. Children with a history of intellectual disability, learning disability, seizures, traumatic brain injury, or other neurological illnesses were excluded. Eligible participants and their parents attended two laboratory sessions. Intellectual ability was assessed during the initial visit using the Wechsler Intelligence Scale for Children, Fourth Edition ( WISC-IV ) or Fift, WISC-V ) and par, WISC-V ) and wern = 113, DICA-IV [n = 34, KSADS-PL [T-scores ≥ 65 or ≥ 6 symptoms endorsed on at least one rating scale). Inclusion in the TD group required scores below clinical cutoffs  or the KSADS-PL ). ChildrKSADS-PL , 55 and KSADS-PL ). A diagAll children completed a mock scan to acclimate to the scanning environment. rs-fMRI was acquired during a 6-min 30-s scan on a 3.0 T Philips scanner using a single-shot, partially parallel, gradient-recalled echo planar sequence with sensitivity encoding and an ascending slice order . Participants were instructed to relax, fixate on a cross-hair, and remain as still as possible.Functional data were preprocessed using SPM12  and custom MATLAB  code. rs-fMRI scans were slice-time adjusted using the slice acquired in the middle of the TR as a reference, and rigid body realignment parameters were estimated to adjust for motion. The volume collected in the middle of the scan was spatially normalized using the Montreal Neurological Institute (MNI) EPI template . The esthttp://mialab.mrn.org/software/gift/index.html; Medical Image Analysis Lab, Albuquerque, New Mexico) [To examine intrinsic FC between fronto-subcortical regions, we decomposed the data into temporally coherent networks using the Group ICA of fMRI Toolbox (GIFT:   Mexico) , 60. We  Mexico) , its inc Mexico) , and its Mexico)  and chos Mexico)  and the  Mexico)  with ran Mexico) . The SMsWe used available brain atlases to extract our cortical and subcortical components of interest from the 66 estimated sources. The Wake Forest Pick Atlas  was usedhttp://afni.nimh.nih.gov/afni; NIMH Scientific and Statistical Computing Core, Bethesda, Maryland); this despiking removes lingering noise artifacts not decomposed well by ICA [Z-scores using Fisher’s transformation. FC scores further from zero reflect stronger FC regardless of sign; positive scores reflect positive correlations, or in-sync and more integrated activity, while negative scores reflect negative correlations or out-of-sync and more segregated activity.We estimated fronto-subcortical synchrony using Pearson’s correlation coefficient between relevant pairs of participant-specific TCs , 69. Befl by ICA . PairwisParticipants completed a computer-based classic money delay discounting task involving 91 choices between a varying amount of money now ($0–$10.50 in $0.50 increments) or $10.00 after a varying delay  , 71, 72 Data analysis was accomplished using SPSS Statistics Version 24 . To examine diagnostic group differences in between-network FC between frontal  and subcortical  components, we conducted a 2 diagnosis (ADHD vs. TD) × 2 sex analysis of variance (ANOVA) for each fronto-subcortical pair. Of note, head motion (mean FD) was correlated with FC for some, but not all, of the fronto-subcortical pairs , thereby eliminating the difference in inattention symptom severity observed among the full sample of boys with ADHD compared to girls with ADHD (p = .276). We also compared FC among high- and low-symptom severity groups rather than comparing girls and boys. Collectively, these analyses suggest that inattention symptom severity is not driving the observed sex differences  [To examine diagnostic group differences in delay discounting, we conducted a 2 diagnosis (ADHD vs. TD) × 2 sex ANCOVA with general ability index (GAI)e ~ 0.8)  consistee ~ 0.8) .z-values so image intensities reflected the degree to which the component was present in each participant’s data. These SMs were combined in a second-level random effects analysis using a two-sample t test in SPM12. Voxels that contributed unequally to the components across groups were identified using a voxelwise p = .001 uncorrected and a cluster-level p = .05 corrected for multiple comparisons. We found no significant group differences in the spatial topography of any of the cortical or subcortical components representing our ROIs.The cortical and subcortical networks are illustrated in Fig. p = .048) and F1-S2 , due to much larger effects in girls (ds = .74 and .94 in girls compared to .01 and .20 in boys), although these interactions did not survive the FDR correction. Given our a priori hypotheses of sex differences in the diagnostic effects, we tested whether fronto-subcortical FC differed between diagnostic groups separately for girls and boys. Examination of post hoc comparisons for girls and boys separately indicated that diagnostic group differences were driven by girls, with greater FC of S1 (striatum component) with all frontal components and weaker F1-S2  = 4.0, p = .048. Consistent with previous research [p = .028, d = 0.68) whereas boys with ADHD did not differ from TD boys . In contrast, diagnostic groups did not differ on the money-discounting task, diagnosis: F = 0.06, p = .811 and diagnosis × sex: F = 0.02, p = .897.For the delay discounting analyses, there was a significant diagnosis × sex interaction for real-time discounting, research , 47, girr(143) = − .235, p = .004  < .14, ps > .10. Thus, within the full sample, children who displayed more negative F3-S1 FC also showed greater money delay discounting. To further explore this relationship, we tested whether diagnosis, sex, and their interaction moderate the relationship between F3-S1 FC and money discounting observed in the full sample. In this model, F3-S1 FC, diagnosis, sex, and the 2- and 3-way interactions among variables were entered as predictors of money discounting along with GAI and mean FD as covariates. The results suggest that F3-S1 significantly predicts money discounting , whereas there was no evidence that diagnosis  or a diagnosis × sex interaction  moderates this relationship. As shown in Fig. r(21) = − .591) and TD boys (r(54) = − .292), followed by ADHD girls (r(20) = − .244), with no evidence of a relationship among ADHD boys (r(52) = − .031).Examination of partial correlations (with GAI and mean FD as covariates) between the delay discounting and FC measures across all children suggested a significant relationship between F3-S1 (anterior dlPFC-striatum components) FC and performance on the money discounting task, β = − 1.56, p < .0001) and the F2-S2  components  and ADHD boys (p = .004) but not among ADHD girls (p = .293) or TD boys (p = .604). Further, stronger positive F2-S2  FC was related to greater real-time discounting among TD girls only (p = .007), but not among ADHD girls (p = .541), TD boys (p = .124), or ADHD boys (p = .139). There were no significant diagnosis × sex × FC interactions for the remaining fronto-subcortical pairs.Due to the diagnosis × sex interaction for real-time discounting, we tested whether diagnosis and sex moderate the brain–behavior relationship between fronto-subcortical FC (for each of the six pairs) and real-time discounting and applied an FDR correction for six tests . The results suggest a diagnosis × sex interaction moderates the relationship between real-time discounting and FC between the F3-S2  components , and this correlated with money delay discounting. Thus, individuals showing stronger functional segregation between striatal regions involved in reward processing and prefrontal regions involved in cognitive control tend to show greater delay discounting  was positively correlated with delay discounting . AlthougThe novel findings of ADHD-related sex differences in fronto-subcortical FC and associations with delay discounting must be considered within the limitations of this study. First, the majority of sample of children with ADHD included in this study were not naïve to stimulant medication and it is unclear what, if any, affect this might have on our findings. Second, in order to understand the pathophysiology of ADHD specifically, we excluded children with comorbid disorders other than ODD, which limits the generalizability of our results. Our results also may not generalize to children with more severe ADHD and behavioral problems due to the exclusion of participants with excessive motion during the resting-state scan. Future research must attempt to replicate these findings given the small sample of girls with ADHD as well as the inconsistent results in the ADHD neuroimaging literature and the lack of studies comparing girls and boys with ADHD, and to extend these findings using longitudinal methods to understand the developmental trajectory of anomalous fronto-subcortical FC in ADHD.Our findings suggest functional fronto-subcortical networks are affected in children with ADHD, particularly girls, such that the striatum is intrinsically more strongly connected to frontal regions, being both more functionally segregated  with the anterior dlPFC and more functionally integrated  with the vmPFC, while the amygdala/hippocampus is intrinsically less connected to the vmPFC. In addition, intrinsic FC of the striatum and amygdala is differentially related to money and real-time discounting, providing support for unique neural correlates of delay discounting tasks involving real versus hypothetical delays and rewards. These findings add to the extant literature implicating fronto-striatal circuitry in children with ADHD and expand upon these findings to reveal associations with a behavioral preference for immediate reward and atypical functional connectivity of the amygdala in ADHD. Moreover, this is the first study to show greater anomalies in fronto-subcortical functional networks among girls with ADHD. This study adds to our understanding of the neurobiological correlates of ADHD and suggests potential differences among school-age girls and boys with ADHD that relate to reward-based decision-making.Additional file 1:3D image of the frontal and subcortical functional components. An interactive tool to view the five frontal and subcortical functional components used in the analyses. The frontal components include F1 , F2 , and F3 . The subcortical components include S1  and S2. (HTML 27309 kb)Additional file 2:Supplementary Material. Table S1. Anatomical information for resting state components. Table S2. Correlation between covariates and dependent variables across ADHD and TD groups. Table S3. Framewise displacement (FD) for diagnostic x sex subgroups. Table S4. a. correlation between head motion (mean FD) and ADHD symptoms among the full sample and separately among girls and boys; b. Partial correlations between head motion (mean FD) and functional connectivity (FC) accounting for ADHD Inattention T-scores. Table S5. Effects of diagnosis and interactions with sex for intrinsic functional connectivity (FC) of fronto-subcortical pairs among children with ADHD and TD controls with and without mean FD and age as covariates. Table S6. Intrinsic functional connectivity of fronto-subcortical pairs for children with ADHD and TD children with and without S1-S2 FC as a covariate. Table S7. Intrinsic functional connectivity of fronto-subcortical pairs for children with ADHD and TD children in the full sample (n = 147) and among a reduced sample including a subset of boys with ADHD (n = 17/52) with similar inattention symptom severity T-scores as the sample of girls with ADHD (n = 112). Table S8. Correlation between FC of fronto-subcortical network pairs and delay discounting (area over the curve) across ADHD and TD groups. (DOCX 34 kb)Additional file 3:An interactive tool to view the spatial overlap of the anatomical ROI for the OFC (yellow) and the functional component with the highest spatial overlap  and the functional component with the highest spatial overlap (F2). (HTML 2054 kb)Additional file 5:An interactive tool to view the spatial overlap of the anatomical ROI for the dlPFC (yellow) and the functional component with the highest spatial overlap (F3). (HTML 2047 kb)Additional file 6:An interactive tool to view the spatial overlap of the anatomical ROI for the striatum and the functional component with the highest spatial overlap (S1). (HTML 3113 kb)Additional file 7:An interactive tool to view the spatial overlap of the anatomical ROI for the amygdala and the functional component with the highest spatial overlap (S2). (HTML 3209 kb)


Attention-deficit/hyperactivity disorder (ADHD) is highly heritable and the most common neurodevelopmental disorder in childhood. In recent decades, it has been appreciated that in a substantial number of cases the disorder does not remit in puberty, but persists into adulthood. Both in childhood and adulthood, ADHD is characterised by substantial comorbidity including substance use, depression, anxiety, and accidents. However, course and symptoms of the disorder and the comorbidities may fluctuate and change over time, and even age of onset in childhood has recently been questioned. Available evidence to date is poor and largely inconsistent with regard to the predictors of persistence versus remittance. Likewise, the development of comorbid disorders cannot be foreseen early on, hampering preventive measures. These facts call for a lifespan perspective on ADHD from childhood to old age. In this selective review, we summarise current knowledge of the long-term course of ADHD, with an emphasis on clinical symptom and cognitive trajectories, treatment effects over the lifespan, and the development of comorbidities. Also, we summarise current knowledge and important unresolved issues on biological factors underlying different ADHD trajectories. We conclude that a severe lack of knowledge on lifespan aspects in ADHD still exists for nearly every aspect reviewed. We encourage large-scale research efforts to overcome those knowledge gaps through appropriately granular longitudinal studies. The clinical disorder is defined by age-inappropriate levels of inattention and/or hyperactivity-impulsivity interfering with normal development, or functioning, of a person. Although ADHD carries the stigma of being a consequence of modern lifestyle, the first mentioning of the syndrome dates back to the late 18th century . HistoriAs discussed in detail in this review, the clinical presentation of ADHD is very heterogeneous, with a wide spectrum of severity and symptoms that partially overlap with other conditions. In fact, ADHD symptoms can be observed transiently not only in psychiatric disorders, but also in somatic diseases and physiological states, such as after sleep deprivation or during over-exhaustion . This coUnfortunately, the fields of research on childhood and adulthood ADHD have operated in relative isolation, mainly due to a historical hiatus between child/adolescent and adult psychiatry. However, the need for a lifespan perspective is becoming increasingly apparent, and is enhanced by the voices of patients and their representatives (see e.g. the Textbox below). In this review, we present selected literature to summarise the current knowledge on ADHD from a developmental, lifespan perspective. Preventive measures as well as age-specific diagnostics and interventions require knowledge about the highly dynamic changes in ADHD presentation from childhood to adulthood, and our review of the current state of knowledge is intended to provide researchers and clinicians with an overview on the trajectory of this disorder. We focus on phenotypic changes across the lifespan, age of onset issues , lifespan aspects of comorbidity, pharmacological and non-pharmacological treatment, as well as aspects of disease outcome with and without treatment. In addition, we summarise knowledge on cognitive and neuroimaging changes during life with the disorder and touch on lifespan aspects in the study of genetic and environmental risk factors for the disorder as well as the interplay of those two. Subsequent to these reviews, we point out existing knowledge gaps and identify needs for further research.Textboxhttp://www.adhdeurope.eu), aims to advance the rights of, and advocate on every level throughout Europe, for people affected by ADHD and comorbid conditions, helping them reach their full potential. ADHD-Europe plays a critical role in promoting awareness of ADHD and evidence-based treatments, facilitate the efforts of national and regional ADHD support groups, and advocate to European Institutions for the delivery of appropriate services for children, adolescents, and adults with ADHD.Despite considerable advances in our understanding of ADHD, patients still experience significant problems gaining access to the support and treatment they need. Service user groups are established in most European countries. One of these groups, ADHD-Europe  hyperactivity . EmotionSex differences in the rates of ADHD are prominent but change throughout development in both clinical and community settings . TypicalWhile diagnostic criteria for ADHD originate from diagnosis of children, the currently used diagnostic criteria, when applied to adults, are also well-validated and therefore appear to work well in the classification of clinical cases of the disorder . Validat3As pointed out above, ADHD has always been viewed as a childhood-onset condition, although the first age at onset criterion was not seen until the advent of DSM-III, which required onset prior to age 7 years . This thde novo, in adulthood is controversial. Three population studies estimated high rates of adult-onset idiopathic ADHD, with a prevalence of 2.7% in New Zealand (NZ)  , 10.3% iand (NZ) , and 5.5and (NZ) . The autand (NZ) . Firstlyand (NZ) , suggestand (NZ) . Moreoveand (NZ) , which cand (NZ) .In all three studies, a participant was defined as having “adult-onset” ADHD only if full diagnostic criteria for ADHD had not been achieved at prior assessments. In each study, however, many of the “adult-onset” cases had evidence of psychopathology in childhood. In the NZ study, in their childhood years, the adult-onset ADHD group had more teacher-rated symptoms of ADHD, were more likely to have been diagnosed with conduct disorder (CD), and were more likely to have had a combined parent-teacher report of ADHD symptom onset prior to age 12 years . In the apparent adult-onset ADHD (AAOA). An urgent clinical question is whether stimulant treatment is appropriate for AAOA. This issue has not yet been systematically assessed. From a clinical perspective, AAOA cases require extra caution. Although many show significant functional impairments that require treatments for ADHD, some may have other disorders.Given the issues discussed above, and until more evidence is available, it seems best to refer to the adult-onset cases reported by the studies from NZ, Brazil, and the UK as In conclusion, substantial research indicates that a diagnosable ADHD syndrome can arise in adulthood subsequent to brain injury. Other forms of apparent adult-onset ADHD may exist, but many of these are likely to have had undiagnosed ADHD or subthreshold ADHD in youth.4To complicate matters further, not only does the clinical phenotype of ADHD change over the lifespan, but comorbid conditions might dominate the initial appearance of a patient. This is of high relevance as ADHD patients frequently suffer from psychiatric and non-psychiatric comorbid conditions, posing significant clinical and public health problems . Through4.1ADHD and symptoms of autistic spectrum disorders (ASDs) often co-exist, as 20–50% of children with ADHD also meet criteria for ASDs . Several4.2The comorbidity of ADHD with antisocial behaviours is of particular societal relevance, as ADHD seems to convey an increased risk for violence and incarceration especially in the context of such comorbidity . In chil4.3Another (related) issue of importance in ADHD across the lifespan is the liability to develop addictions. The earlier onset and increased use of tobacco, alcohol, and illicit substances in adolescents with ADHD compared to controls has been demonstrated in various studies, and a high prevalence of drug abuse or dependency (9–40%) is also reported in adulthood . A meta-4.4Adult ADHD is significantly comorbid with anxiety disorders  and major depression . Although these disorders are among the most common comorbidities of ADHD, especially in adolescents  and adul4.5An issue of increasing interest in research and clinic is the presence of extreme and uncontrolled emotional and mood changes in both children and adults with ADHD. Indeed, in DSM-5, problems with emotion regulation are listed as characteristic features of ADHD that support the diagnosis. Emotional dysregulation and ADHD are known to share genetic risks . In adul5The continuity of treatment of ADHD across the lifespan is an issue that still receives too little attention. Especially the transition from adolescence to adulthood, which is accompanied by a transition from child and adolescent psychiatric clinics to adult psychiatry, is problematic; many patients are lost to follow up at that point. At every age, recommended treatment of ADHD should be multimodal, including psycho-education, pharmacotherapy, and disorder-oriented psychotherapy, including training, cognitive-behavioural therapy, and family or couple therapy if needed .and adulthood in most European countries  head to head as done in a pioneering study . At the It is important to highlight the positive impact of ADHD treatment on aspects of daily functioning. Although initial studies were disappointing regarding the longer-term effects of treatment , the stuIn addition to pharmacotherapy, several non-pharmacological approaches are used in the control and management of ADHD across the lifespan . In manyOf particular importance is the transition from childhood to adult services, requiring continuation of both medical and psychological support . As indi6Assessment of disease outcome in ADHD requires longitudinal study designs, which are generally scarce. As a result, also the knowledge about the role of treatment during the different phases of life in such outcomes is still patchy. Some clinically-based studies of high quality that have followed up pre-adolescents with ADHD into adulthood are already available and have been instrumental in documenting the disease outcomes of ADHD in different aspects of life. Those include academic, occupational, and social aspects as well as morbidity and mortality. It has been shown that ADHD is associated with academic outcomes, such as poor academic performance   and loweIn terms of mortality, several studies from Scandinavia have explored the association of ADHD with mortality and which factors are likely to increase mortality. These studies have used information from national registers in Sweden and Denmark that have been linked using a unique person identifier. A Danish register-based study has found that ADHD is associated with significantly increased mortality rates, and that the excess mortality in ADHD is mainly driven by deaths from unnatural causes, especially accidents . Other rSystematic reviews of the long-term disease outcomes of treated versus untreated ADHD are somewhat inconsistent. This is partly because long-term observational studies are often limited by a lack of data about treatment compliance and can be confounded by indication, since more severe cases will be more likely to be treated. A systematic review of randomised controlled trial open-label extension studies and naturalistic studies of adults with ADHD concluded that ADHD medications have long-term beneficial effects and are well tolerated, but that more longitudinal studies of long duration need to be performed . A seconPharmaco-epidemiological analyses of large-scale databases, such as the national registers in Scandinavia, are an alternative source of information about potential (long-term) effects of ADHD medication on important disease outcomes. A large register-based Swedish study of adults with ADHD found that treatment with ADHD medication significantly reduces the risk for criminality . AnotherThe pharmaco-epidemiological studies can also help clarify the potential role of medication in causing morbidity. For example, two register-based studies of adolescents and adults with ADHD suggest that the co-occurrence of ADHD and suicidal behaviour is due to shared familial risk factors , rather 7In addition to a lifespan perspective on phenotypic and outcome parameters in ADHD, also the dynamics across life in biological markers and risk factors for the disorder need to be understood better. ADHD is associated with several cognitive impairments and brain alterations, both in childhood and in adulthood. Cognitive deficits in ADHD encompass both higher-level, effortful cognitive functions  and lower-level, potentially more automatic cognitive processes  . Meta-anStructural and functional neuroimaging studies have documented abnormalities in brain anatomy and function in individuals with ADHD . Meta-anOverall, cross-sectional studies indicate that many cognitive and brain abnormalities are associated with ADHD in both children and adults, although some differences have also been observed between age groups. Looking at the developmental trajectories of cognitive, neuroanatomical and neurofunctional alterations in ADHD across the lifespan, it is important to examine whether cognitive and brain abnormalities (1) show an age-independent, consistent association with ADHD across the lifespan; (2) are predictors in childhood of later ADHD outcome; (3) can differentiate between individuals with persistent ADHD (from here on “ADHD persisters”) and individuals who have remitted from ADHD over time (from here on “ADHD remitters”).As for point (1), prospective longitudinal studies with repeated assessments of ADHD and cognitive measures are needed to confirm cross-sectional studies suggestive of similar impairments across the lifespan. Such studies to date, mostly focusing on higher-level cognitive functions using IQ tests, executive functioning and attentional tasks, show that impairments tend to persist from childhood to adolescence and early adulthood in ADHD persisters . Fewer pAmong neuroimaging studies, longitudinal studies using multiple assessments from childhood to adulthood are scarce, and have mainly examined neuroanatomical abnormalities with MRI. Available MRI studies consistently show that smaller brain volumes and morphometric abnormalities persist over time in ADHD persisters re-assessed in adolescence and early adulthood . For exawithin an ADHD sample (point 2) is important for early identification of those at risk for worse long-term outcomes (The prediction of future ADHD outcome (remission/persistence) based on early cognitive and neural impairments measured in childhood outcomes , with anoutcomes , whereasoutcomes . Studiesoutcomes . This isoutcomes . In a fooutcomes . The preoutcomes , but notoutcomes . The onloutcomes , especiaAs for point (3), the identification of cognitive and neural processes underlying the trajectories of persistence and recovery from childhood-onset ADHD during the transition to adulthood may further contribute to the prevention of negative long-term outcomes. It has been hypothesised that the persistence of ADHD would be predicted by the degree of maturation and improvement over time in higher-level cognitive function, and lower-level cognitive functions would be linked to the presence of ADHD in childhood irrespective of later clinical status . In a foLarge-scale neuroanatomical studies also found evidence of differences between ADHD persisters and remitters in adolescents and adults in measures of brain volume and structural connectivity. ADHD remitters have shown a slower rate of cortical thinning from childhood to adulthood compared to persisters, such that brain dimensions may be more similar to those of control individuals in frontal and parietal regions with age . StructuOverall, despite some inconsistencies between studies, some convergence for cognitive and neuroimaging markers of ADHD persistence and remission is starting to emerge. For example, the majority of studies to date show that impairments in executive function do not distinguish ADHD remitters and persisters . A parti8While investigations into the dynamics of cognitive and neuroimaging markers across life have gained traction, the research into lifespan aspects of underlying risk factors for ADHD is still very much in its infancy. ADHD has a strong genetic component. Family studies have consistently shown familial clustering, with an ADHD relative risk of about 5- to 10-fold in first-degree relatives of probands with ADHD . Twin stGiven the multifactorial, polygenic nature of ADHD, genetic research has mainly focused on common variants through hypothesis-driven candidate gene association studies (CGAS) and genome-wide association studies (GWAS) with case-control or family-based designs. These designs consist on observational studies in which the frequencies of specific common genetic variants within candidate genes for ADHD or a genome-wide set of polymorphisms are compared between affected (cases) and unaffected (controls) individuals or between affected subjects and their relatives. Several linkage studies have also been performed. They allow genetic mapping of complex traits showing familiar aggregation by assessing the co-segregation of the disease phenotype with sequence variants across the genome. More recently, genetic studies in ADHD have also focused on rare variation  through copy-number variant (CNV) analyses, which inspect alterations in genomic segments of more than 1Kb in length, and exome chip analysis and whole-exome sequencing, targeting point mutations or small indels. These investigations have shown converging evidence for common biological pathways underlying ADHD, which highlights that both common and rare genetic variants account for a significant proportion of the genetic susceptibility to the disorder .DIRAS2  in children or adolescents with the disorder  and in aith ADHD . Rare miith ADHD .Overall, while it is well-established that ADHD is a highly heritable condition with a complex genetic architecture, more research is needed to identify the specific genetic underpinnings of the disorder and its persistence into adulthood. In addition to risk factors stably involved in ADHD throughout the lifespan, the susceptibility to ADHD persistence may be a dynamic process, with specific genetic influences acting at different developmental stages . Thus, d9DRD4 and exposure to prenatal smoking , were confirmed in the replication sample. SKI , ZNF544 (previously linked to ADHD), and ST3GAL3 , although none of these genes maintained an association with ADHD trajectories at age 7 years. Together, these studies – some in small cohorts – provide initial insight into the epigenetic background of ADHD, underscoring the relevance of differential DNA methylation in genes related to monoaminergic, cholinergic and GABAergic transmitter system function and neurodevelopmental processes that play a role in the formation, maturation, and plasticity of distinct brain networks.A pioneering study on ADHD epigenetics was a whole-epigenome screening of two independent samples in boys with ADHD by 10In this review, we aimed to provide an overview of the current knowledge about ADHD across the lifespan. We covered the major phenotypic and biological issues related to this disorder, which is a prominent cause of psychiatric morbidity and impairment in both childhood and adulthood. We discussed developmental trajectories in core phenotype definition, comorbidity, cognitive and brain structural/functional markers, as well as treatment trajectories, outcomes, and genomic markers. Our review shows that beyond research into the core symptoms of ADHD, information is still very patchy, and relatively little is known about developmental trajectories from childhood into adulthood for most of the issues of interest. This defines priorities in the coming years for research of phenotypic issues, treatment and prediction of outcome, as well as our understanding of the biological underpinnings of ADHD.In all areas of our investigation into the ADHD literature, the absence of studies in the elderly is highly apparent. Old age is the current blind spot of ADHD research, which has to be factored in when interpreting all the data presented above. This lack of knowledge limits the possibility to perform a review of the complete lifespan, as most available studies deal with ADHD in children – even 50 years after the first studies showed that ADHD also exists in adults and can continue from childhood to adulthood . Beyond (1)Only in such longitudinal cohorts the relation of apparent adult-onset ADHD to the neurodevelopmental form of the disorder can be defined: are these different disease entities, with different aetiologies and (co)morbidity profiles, or can they be different subtypes/presentations of the same, overarching disorder? To study this question, one needs also to enrol children with mental disorders other than ADHD and sub-threshold ADHD symptoms.(2)Is the persistent form of ADHD really persistent, or do ADHD symptoms over time fluctuate with varying intensity, thus creating suffering and burden only in specific life phases, e.g. characterised by high life stress or high demands for self-management ? Persist(3)There are only a few studies on ADHD remitters. However, this particular group brings up important questions: which are the resilience factors that protect against persistence? Are there differential genetic factors that have a role in remission versus persistence? What about environmental factors and GxE phenomena? What is the brain's developmental trajectory? Clues that help to answer these questions might translate into clinical practice to improve the outcome of patients, and thus according studies should be prioritised.(4)Developmental trajectories of comorbidity profiles and cognitive functioning across the lifespan: as we have reviewed above, ADHD is characterised by extensive comorbidity in childhood and adulthood. However, the comorbidity profiles of child and adult ADHD change and only partly overlap. Clinical longitudinal studies are needed to understand onset and changes in comorbidity. Recent findings from large genetic studies as well as register-based studies show that comorbidity is often based on shared familial and genetic factors e.g. .(5)Cognitive functioning, brain structure/function, and the contribution of genetic and environmental risk factors across the lifespan: overall, cognitive and neuroimaging studies to date converge in indicating that most impairments persist when ADHD persists from childhood to later assessments. Yet, most existing studies are cross-sectional and have used samples in young or middle adulthood only. Large longitudinal studies are needed, also including assessments of older age groups, to fully characterise the developmental trajectories of ADHD-related cognitive and brain impairments across the lifespan. In addition, since some of the cognitive and neural alterations observed in ADHD are non-specific, but rather shared with other disorders (e.g. autism and bipolar disorder) (6)Finally, prediction of disease outcome is an area of research that can directly influence treatment decisions in daily clinical practice. Cognitive, electrophysiological, and neuroimaging markers associated with childhood ADHD persist into adulthood, but show variable trajectories reflecting both delayed maturation and within-group differences. Findings suggest a pattern of corresponding biomarkers that predict remission versus persistence of ADHD symptoms in adolescence and adulthood. However, to move forward towards potential clinical applications of these markers as a means to identify those childhood and adolescent cases with ADHD that are at high risk for persistent ADHD, prediction parameters at the individual level have to be examined. Importantly, the predictive power/accuracy of currently identified biomarkers is individually low. Future studies should therefore explore whether combining markers from different cognitive and imaging domains as well as (epi)genetic approaches may improve prediction. Future longitudinal and clinical studies should address these questions while using sophisticated approaches, like normative modelling and multivariate pattern recognition . While AAn important additional caveat of current literature is the limited availability of longitudinal studies with a careful and repeated, detailed characterisation of participants across different phases of the lifespan regarding terms of deep clinical phenotyping as well as biomarkers. Such work is essential to chart the trajectory of ADHD symptoms over the lifetime and will answer important questions about the interplay of ADHD disposition with environmental conditions. Those studies are urgently needed for clinical cohorts as well as the general population, and should include broad assessment batteries of disease phenotypes and treatments, quantitative behavioural measures, cognitive tasks and neuroimaging, as well as repeated biomaterial collection. Some existing population studies, like MoBA , ALSPAC The questions raised above reach far beyond mere academic interest, as respective answers will immediately impact on ADHD treatment. For instance, timing of treatment is an essential issue, as we are only about to begin to understand the long-term effects of pharmacological ADHD treatment regarding outcome . To address this, however, we need granular longitudinal studies, initiated in childhood and followed up long-term. A tightly linked question is how adolescents can be kept in treatment – or at least in mental health services – during the transitional period, thereby preventing the “transition gap” and potentially the development of comorbid disorders such as depression or SUD. On the other hand, a waxing and waning pattern of ADHD symptoms and related burden of disease in specific life situations might allow for interval treatment, and especially addressing the role of resilience in the interaction of life stress and ADHD disposition might unleash a huge potential for psychotherapy. More research into persistence within and across different age-ranges is therefore urgently needed. Beyond these “traditional” approaches, novel treatments, such as non-invasive brain stimulation, neurofeedback, and nutritional interventions, should be assessed for their lifespan effects. Within this framework of long-term treatment effects, prediction has also to be factored in. If ADHD persistence or development of comorbidity could reliably be foreseen, this would dramatically alter the way ADHD is treated over the lifespan, opening up a perspective for precision medicine. Most likely, predictive approaches will be multimodal  of behavioural patterns), but also require biomarker studies on disease trajectories of the lifespan.In terms of understanding the risk factors underlying ADHD, which might be linked to such predictive markers, important progress has been made in the areas of environmental and genetic risk factors in recent years. In particular, the latter one has been enabled by technological progress as well as the formation of large, international collaborations, like the Psychiatric Genomics Consortium . Still, More than 1000 genes/genomics regions may contribute to neurodevelopmental disorders like ADHD. Many of those genes/regions can be expected to contain several independent risk loci. How informative the identification of all of those will be for our understanding of disease mechanisms and potential new treatment routes has recently been questioned by a paper discussing “omnigenic” diseases and traits . In theiLastly, epigenetics research offers great opportunities to integrate genetic and environmental risk in ADHD. Also here, only first steps have been made towards exploring the involvement of aberrant epigenetic patterning in ADHD. As discussed above, these steps are hampered by the tissue specificity of epigenetic modifications, leading to uncertainty about the predictive value of proxy tissues like blood and saliva, which are the only accessible tissues available in large samples. Changes in epigenetic profiles over time, like those needed to explore lifespan changes in the ADHD phenotype/outcome, might be more informative in those proxy tissues, but this hypothesis awaits testing.In conclusion, ADHD is the prototypic example of a neurodevelopmental disorder starting early in life and developing with a highly variable trajectory. While in some cases it might be the entry point into a negative, burdensome trajectory, other patients may remit and even transform some deficits into adaptive behaviours, living highly successful lives. The latter suggests that there is potential for improvement in many ADHD patients, if recognised early on and receiving optimal treatment. To clarify the course, to identify those at risk of unfavourable outcome and to provide tailored treatment, longitudinal, granular, and multimodal studies are clearly needed. While we appreciate that this poses a challenge, we are confident that such an endeavour would – just like the fight against HIV three decades ago – pay off in every respect to improve the life of many patients.


Cogmed Working Memory Training (CWMT), an online cognitive training program developed for children, is an increasingly popular non-pharmacological intervention for ADHD amongst all ages, despite limited supporting evidence. The initial objective of the present work was to examine the short- and long-term impacts of CWMT on brain function in adults with ADHD. However, during the conduct of our study, we experienced multiple levels of failures in recruitment and retention that signaled potential concerns about the suitability of CWMT for adults with ADHD. This perspective piece aims to describe the difficulties we encountered in the context of studies examining the efficacy of CWMT in comparable populations. We trace these difficulties to the limited tolerability of the current CWMT structure for adults with ADHD, and review similar limitations in the literature. We suggest that efficacy of CWMT in children may be due in large part to close monitoring and scaffolding provided by clinicians and caregivers. For CWMT to have viability for widespread use in adults, greater support and structure will be needed for users to improve the likelihood of adherence. We discuss implications and considerations for future efforts in both research and clinical practice. Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders in children, characterized by impairing levels of inattention and/or hyperactivity-impulsivity. Longitudinal studies have found that impairing ADHD symptoms persist into adulthood in up to 65% of cases , 2. AcroWhen treating adults with ADHD, clinicians commonly encounter additional obstacles relating to adherence and efficacy. Stimulants, which are among the most effective treatments for ADHD in children, have been suggested to be less efficacious in adults , 8, withCognitive training has gained increasing attention for the potential to overcome these obstacles, leveraging computerized platforms to decrease challenges of delivery. With regard to ADHD, working memory (WM) has emerged as a particularly attractive target for computerized training due to its demonstrated impairment in ADHD –16. WM iOf the many WM training programs that exist, Cogmed Working Memory Training (CWMT) has become the most widely empirically researched intervention , 21. TheThe goal of the present perspective piece is to draw attention to questions regarding the feasibility of using CWMT in the treatment of adults with ADHD. These concerns emerged from a failed study of CWMT, which aimed to examine the short- and long-term impact of working memory training on brain function in adults with ADHD, using functional magnetic resonance imaging (fMRI). We focus on the acceptability and practicality of the intervention, defined by Bowen et al.  as the eIQ < 85, as established through the Wechsler Abbreviated Scale of Intelligence (WASI); (5) contraindications to MRI; and (6) a change in psychotropic medication during study participation. All research procedures were approved by the Institutional Review Board at the Nathan Kline Institute.Participants were recruited through local newspapers, internet-based advertising, college and university learning centers, and ADHD support groups. Participants taking psychotropic medications were included provided that their medication dosage had been stable for 1 month prior to study enrollment, and remained stable throughout their participation. Inclusion criteria were as follows: (1) male or female between 18 and 40 years of age; (2) capacity to provide informed consent; (3) right-handed; (4) fluent in English; and (5) met criteria for ADHD (current and in childhood), either inattentive or hyperactive/impulsive type, as established through the Adult ADHD Clinical Diagnostic Scale (ACDS) v 1.2 . ExclusiOutreach generated a total of 166 contacts; 13 individuals met full criteria for participation and were provided CWMT accounts ; Adult ADHD Self-Report Scale (ASRS) v1.1; Behavior Rating Inventory of Executive Function (BRIEF)-Adult Version), abbreviated psychological -abbreviated, second edition) and neurocognitive testing . Socioeconomic status (SES) was measured using the Hollingshead Four-Factor Index of Socioeconomic Status. The second visit took place within 2 weeks before beginning CWMT and consisted of an MRI scan. The third and fourth visits took place 1 week after and 1 month after completing CWMT, respectively, and each consisted of an MRI scan as well as abbreviated psychological and neurocognitive testing. Each participant was provided with a trained CWMT coach, a Licensed Master Social Worker, who gave verbal and written feedback and monitored progress through the program on a weekly basis. Coaching content included reviewing daily and weekly schedules to choose consistent daily training times, building in rewards around training, and offering praise when positive patterns in training occurred. Participants unable to complete at least 20 computerized training sessions over a 5-week period were excluded from the study due to dosage-dependent nature of CWMT effects.Participants were compensated for in-person assessments . All aspects of CWMT, including coaching, were provided at no cost to participants.n = 5) completed the program  to complete each session. We hypothesize that the prolonged duration of each session resulted in part from the executive functioning impairments that are characteristic of ADHD.Our high attrition rate and final sample size prevented us from carrying out our intended aims. Of the 13 participants who began CWMT, only 38% (Post-hoc (t-tests and chi-squared tests) analysis did not reveal any differences between completers and non-completers in age, sex, race, executive function capabilities, SES, IQ, symptom severity, medication status, or pre-training self-reported motivation , indicating that the decision to discontinue was not precipitous in most cases. As such, it appears that CWMT did not meet participants' desired levels of acceptability or practicality, and that participants experienced CWMT as more time consuming than advertised. Due to difficulties intrinsic to ADHD, this population found multiple aspects of CWMT extraordinarily challenging. For example, one diagnostic criteria for ADHD, endorsed by 100% of our participants, is the tendency to avoid and dislike sustained mental effort. Additionally, the requirement for sufficient self-organization to perform massed at-home training bears on another core disability in ADHD.Given that our initial sample consisted of only 13 participants, it is possible that unappreciated biases in our sample selection may somehow explain the 62% drop-out rate we observed. To validate our concerns about CWMT, we turned to the literature. While no systematic review examining CWMT attrition in comparable populations exists, we did find a number of studies that provided insights. In particular, three research groups , 26, 32 not see the high attrition rates that our present study and Mawjee et al. experienced, with 87% of students completing training. In attempting to put the pieces together among these studies, it is not clear what factor(s) may be driving differences in drop-out rates across studies. Differences in age-group, recruitment setting, and qualifications of the CWMT coach provided do not cleanly explain completion rate disparities. Of note, our study, which involved recruitment from the community rather than a school or clinic, had the lowest retention rate -possibly suggesting differences in the nature of the therapeutic relationship may matter.Two recent studies provide somewhat more optimistic estimates of tolerability. First, Dentz et al.  investigIn contrast to studies focusing on CWMT in adults, those in children tend to have higher completion rates, though still with significant variation across studies (6–26%). This is not surprising as Cogmed was initially developed for children, where the support of a teacher or parent is included to promote treatment compliance. Chacko et al.'s.  review eThe present perspective draws attention to possible concerns regarding the readiness of CMWT for usage in adults with ADHD. Review of the literature, combined with our own findings, revealed notable variation in the tolerability of CWMT for adults with ADHD. It is important to emphasize the need for conducting ecologically valid research before implementing interventions in the community. This is especially so when costs and burden of potential interventions are high-the CWMT fee-structures for patients in the community require payment in full  to access the program, which is often not covered or reimbursed by insurance. Moreover, adult CWMT users are faced with unique scheduling challenges, such as work and family commitments, highlighting the need for treatments that are both efficacious and efficient. CWMT touts having been developed by “leading neuroscientists” using a top-down expert-driven method, but to our knowledge no empirical end-user validation research for Cogmed exists. Active end-user involvement in development can prevent deployment of intolerable training models. CWMT may still be a promising solution for current issues surrounding accessibility and efficacy of adult ADHD therapies, though it appears that significant examination and refinement will likely be needed for it to realize its potential.This study was carried out in accordance with the recommendations of Institutional Review Board at the Nathan Kline Institute, with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the Institutional Review Board at the Nathan Kline Institute.EM: data acquisition, data organization, data analysis, drafting of manuscript. EH: data acquisition, data organization, drafting of manuscript. MK: data acquisition. LA, FC, and MPM: experiment design, drafting of 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.


Attention deficit hyperactivity disorder (ADHD) is a lifelong neurodevelopmental disorder which impacts many aspects of function at each stage of the life journey through which it passes. Central to the understanding of this process is the recognition of the symptoms of ADHD itself and how they change over time. Beyond this the process itself has to be appreciated in terms of how this core integrates with parallel emerging patterns of comorbid disorders. The key to understanding how ADHD and its comorbidity integrate into and become part of the developing person is to realise that at each developing stage the symptoms of ADHD (as well as the comorbidity) will impact the overall development, creating backlogs or impairments which may ‘colour’ the persons as they grow and will not be as amenable to treatment as the ADHD or its comorbidity. If ADHD has this potential impact as the individual gets older, what are the treatment considerations in terms of early intervention?