Neuropsychological and academic measures and behavioral, emotional, and mindfulness ratings were collected before and after the two programs. On average, MOM training had positive effects on neuropsychological measures, as evidenced by a significant mean improvement in all outcome measures after training. Moreover, positive effects on ADHD symptoms were found only in the MOM group. Although they are preliminary, our results documented that MOM training promotes changes in neuropsychological measures and in certain behavioral symptoms, suggesting it as a promising tool for ameliorating cognitive and clinical manifestations of ADHD.Mindfulness-oriented meditation (MOM) is a self-regulatory training used for attentional and behavioral problems. With its focus on attention, MOM is a promising form of training that is gaining empirical support as a complementary or alternative intervention for attention deficit/hyperactivity disorder (ADHD). In this study, we tested the preliminary efficacy of MOM training in children with ADHD, by comparing its efficacy with an active control condition . Twenty-five children with ADHD aged 7–11 years participated in MOM training ( Attention deficit/hyperactivity disorder (ADHD) is one of the most common developmental disorders, with high persistence into adulthood. The global prevalence of ADHD is 3–7% , and appMany studies have highlighted deficits in executive functions as one of the main characteristics of ADHD, especially with regard to response inhibition, attention, and working memory ,13,14,15Given the serious academic, social, familial, and accidental injury-related effects of ADHD, the need to develop and disseminate effective treatments is pressing .In Europe, the guidelines that were produced by The National Institute for Health and Clinical Excellence ,19 recomWith its focus on attention, mindfulness meditation is a promising form of training that is gaining empirical support as a complementary or alternative intervention for ADHD ,23. It iResearching the efficacy of mindfulness training in children and adolescents is a relatively new domain . Several studies have also determined the effects of mindfulness meditation training in ADHD ,23,29. ACompared with the meta-analysis by Cairncross and Miller , a revieA more recent meta-analysis and review by Zhang et al.  assessedIn summary, preliminary studies on mindfulness training in children and adolescents with ADHD have demonstrated a positive effect on ADHD symptoms. Data derived by combining objective neuropsychological measures with parent- and self-report questionnaires is scarce, and the results that exist are controversial.Moreover, evidence is limited by the lack of an active control group or the heterogeneity of control conditions, which varied between studies, encompassing self-guided handouts on skills, nonviolent resistance training for parents, psychoeducation, and wait list. Selection bias, lack of protocol, and the simultaneous use of medication should also urge caution in the interpretation of the results.In considering mindfulness training in children with ADHD, studies must comprise homogeneous groups  and replicable procedures .The present study attempted to control for issues affecting previous results on mindfulness training such as by providing an active control condition designed to be comparable with and structurally equivalent to the mindfulness-oriented meditation (MOM) program, by the combination of objective neuropsychological measures with parent and self-report questionnaires, the selection of children with ADHD with a narrow age range and no concurrent treatment, and the random assignment of participants to the MOM group (MOM G) or to the active control group.With this aim, 32 children with ADHD aged 7–11 years were randomly assigned to the MOM G, which underwent mindfulness training or to the active control group, the Emotion Education Program group (EEP G), which entered the emotion awareness and recognition program. Participants were assessed at baseline (T0) and post-training (T1) for neuropsychological measures that involved executive functions , ADHD symptoms, behavioral and emotional aspects, mindfulness measures, depressive and anxious symptoms, parenting stress (by using self-ratings and parent ratings), and academic skills . None of the children had received or was receiving any pharmacological, psychological, behavioral, or educational treatment.The MOM program, as one form of mindfulness , was recThe EEP was designed to be comparable with and structurally equivalent to the MOM program. It was organized into 3 sessions per week for 8 weeks and the duration of the sessions followed the same progression as the MOM training. The activities of the EEP G consisted of listening to and commenting on chapters of a book to discover and be aware of various emotions.Because mindfulness meditation programs focus on attention regulation and on reducing automatic responding, we predicted that MOM would have positive effects on neuropsychological measures that involve executive functions. We also expected to observe better effects on mindfulness measures and symptoms of ADHD, as rated by parents, in the MOM G versus EEP G. Due to the short duration of the intervention, we predicted limited effectiveness on academic skills, perceived family stress, anxiety, and depressive symptoms.The estimated sample size  for thisSD = 1.2; 9 females) were recruited from a waiting list for a multimodal intervention that was based on psychological, behavioral, and educational interventions at the Child and Adolescent Neuropsychiatry Unit of the Bambino Gesù Children’s Hospital .Thirty-five children with ADHD -5 criteria  and was According to DSM-5 , the chiGlobal functioning was assessed with the Children’s Global Assessment Scale (C-GAS) . The C-GIQ was measured by using the Wechsler Intelligence Scale for Children-IV   or ColorChildren with ADHD who were included in the study met the following criteria: (a) a primary diagnosis of ADHD, according to the criteria of DSM-5 ; (b) ageThe exclusion criteria were as follows: (a) the presence of neurological and neurosensory deficits; (b) the presence of comorbid psychopathological disorders or autism spectrum disorder; (c) past or present drug treatment, cognitive behavioral therapy, training/education program, or any other group-based psychological treatment for parents.All participants and their parents gave written informed consent after receiving a comprehensive description of the study. This study was performed in accordance with the Declaration of Helsinki and was approved by the local ethical committee of the Bambino Gesù Children’s Hospital (Process Number 1162/2016).This randomized study comprised two arms see . The basBoth of the training programs were provided at the Child and Adolescent Neuropsychiatry Unit of the Bambino Gesù Children’s Hospital. Before the training began, one participant in the MOM-G and six in the EEP G dropped out.SD = 1.3; CA EEP G: M = 9, SD = 1.2), IQ , or C-GAS score .At T0, the two groups did not differ in chronological age  were conducted twice within two weeks after the end of the training by two child developmental psychologists who were blind to the interventions, with each session lasting approximately 1.5 h.The MOM program was conducted by two qualified mindfulness meditation instructors (VC and OS). A developmental psychologist (VZ) was also present to help children with ADHD to follow the sessions.The training was inspired by previous MOM interventions for clinical and nonclinical adult and child populations ,56,57,58Each session was divided into a series of three meditation exercises that focused on three types of activity: (i) mindfulness of breathing, (ii) mindfulness of body parts, and (iii) mindfulness of thoughts and emotions. After the meditation exercise, there was a brief debriefing phase that lasted approximately half of the time that was dedicated to the meditation exercises to allow the children to express their feelings and pose questions about the exercise that had just been completed.Specifically, the three meditation activities were proposed to the MOM G as “games” that were meant to promote awareness of breath, body parts, and thoughts. In each of the three weekly sessions, children with ADHD were first required to concentrate on breath. In the second meditation exercise, participants had to focus their attention on various body parts. In the last activity, children were encouraged to observe the stream of their thoughts and emotions. For a brief description of the structure of the sessions and activities included in the MOM training, see The activities of the EEP G were designed to be comparable with and structurally equivalent to those of the MOM program  .The program was led by the same trainers as in the MOM training. The book is about a shy and sensitive child who decides to avoid all of his emotions to avoid being defined as “sensitive” by his friends and schoolmates. However, at the end of the book, the child learns the importance of feeling positive and negative emotions in his heart and appreciates that he is sensitive.During the sessions, the trainers asked the children to discuss the stories, the emotions that they felt, and the physical sensations that were associated with these emotions. The activities of listening to and commenting on the chapters allowed children to discover various emotions that can be experienced in many situations and to consider and be aware of their own emotions. At the end of each session, the children were recommended to pay attention to the emotions that were experienced in their everyday life in order to generalize the gains that were made in training to daily life.During the eight weeks of the EEP, participants were given homework (“Diaries”) and instructed to write down the situations in which they were aware of their emotions. For a brief description of the structure of the sessions and activities included in the EEP, see In summary, EEP was an active control condition for the MOM program because it shared several crucial elements with MOM, including timing and setting, requests for silence, group work, interaction between children and trainers, and the assignment of homework, but was designed not to be related to the practice of mindfulness .Children from both groups were assessed at T0 and T1 with regard to the following.The Continuous Performance Test-II (CPT-II) 5th version  is a comn = 100).In the Stroop Color Word Test , childreThe stop task ,65,66,67In the N-Back task, children were presented with a single blue square at any location in a 3 × 3 grid on a computer screen and instructed to make a decision (yes/no) by pressing a button with regard to whether the current stimulus was in the same location as that presented N-positions earlier. Only when the accuracy was 80% was the next N-back level submitted. A N-Back Inefficiency Index (N-BACK II) was calculated, based on the percentage of errors in the last not-achieved n-back.Conners’ Parent Rating Scales Long Version Revised (CPRS-R:L)  is compoThe Child Behavior Checklist for Ages 6–18 (CBCL 6-18)  is a papThe Multidimensional Anxiety Scale for Children (MASC)  is a 39-The Children’s Depression Inventory (CDI)  is a 27-The Child and Adolescent Mindfulness Measure (CAMM)  is an awThe Parenting Stress Index-Short Form (PSI-SF) ,74,75 isText Reading (MT-2) . ReadingMental Calculation ) ,78. The 1,23 = 4.8, p = 0.039, ηp2 = 0.17), Time , Task , and Group × Time  were found. However, Group × Task , Task × Time , and Group × Task × Time interactions were not significant .Concerning Neuropsychological Measures see , a repeap = 0.0028), while EEP G mean scores did not change from T0 to T1 (p = 0.99). Moreover, the two groups differed at T0 (p = 0.027) but not at T1 (p = 0.99).The post hoc analysis  of the effect of Group × Time showed that MOM G mean scores decreased from T0 to T1 , Subscale , Group × Subscale , and Group × Time × Subscale interactions  were found. The main effect of Time  and Group × Time interaction  were not significant. As shown by the post hoc analysis of Group × Time × Subscale interaction , only scores in the MOM G decreased from T0 to T1 for the CGI Restless-Impulsive and CGI Total subscales .Concerning ADHD symptoms see , a repeaFurther, the change between T0 and T1 for the CGI Restless-Impulsive and CGI Total subscales had clinical significance only in the MOM G: the subscales scores decreased, on average, from a clinical level at T0 (mean T-scores higher than 70) to a borderline range at T1 (between 60 and 70). Although no effect of the training program was observed for the Oppositional subscale, the change between T0 and T1 had clinical significance only in the MOM G: Oppositional subscale scores decreased, on average, from a borderline range at T0 (mean T-scores between 60 and 70) to a typical level at T1 (lower than 60). Similarly, although training did not have any effect on it, DSM-IV Hyperactive/Impulsive subscale scores between T0 and T1 declined, on average, only in the MOM G, from a clinical level at T0 (mean T-scores above 70) to a borderline range at T1 (between 60 and 70).1,23 = 3.14, p = 0.09, ηp2 = 0.12), Time , Group × Time  nor the Group × Time × Subscale interactions  were significant. However, the main effect of Subscale  and the Group × Subscale interaction were significant . For the CBCL 6-18, a repeated measures ANOVA was conducted on T-scores of the 24 subscales as the dependent variables, and Group  and Time  as the independent variables. Neither the Group  and Time  were not significant. The Group × Time  and Group × Time × Task interactions  were also not significant. However, the main effect of Task  was significant.To determine the effects of MOM on parent and self-report questionnaires on anxiety, depressive symptoms, mindfulness, and parenting stress, a repeated measure ANOVA was performed, with MASC, CDI, CAMM, and PSI-SF scores as the dependent variables, and Group  and Time  as the independent variables. The main effects of Group  was significant but Time effect  and Group × Time interaction  were not significant.Concerning academic skills, a repeated measure ANOVA was performed on mental calculation Z-score as the dependent variable, and Group  and Time  as the independent variables. The main effect of Group  or accuracy  did not differ.Chi-squared test was used to compare the number of participants in the two groups whose reading performance changed (medium/high or low/poor) from T0 to T1 with regard to reading speed or reading accuracy. For text reading also, the number of participants in the two groups whose reading performance changed from T0 to T1 with regard to speed , as evidenced by the average responses on neuropsychological measures improving significantly at T1 compared with T0 in the MOM G but not in the EEP G.With regard to ADHD symptoms, only the MOM G had significantly lower T-scores at T1 than at T0 on the CGI Restless-Impulsive and CGI Total subscale scores , with a small effect size. Moreover, the changes in ADHD symptoms after MOM training had clinical significance, based on parent rate T-scores declining on several CPRS-R:L subscales.The significant mean improvement in all neuropsychological measures after training in the MOM G suggested that MOM training could appreciably reduce executive functions deficits in ADHD. Our tasks involved higher-order cognitive abilities, such as working memory, inhibitory control, switching, and sustained performance. However, there are few data on the association between mindfulness and executive functions ,80,81 inConcerning studies on typical populations, our results are in line with findings that showed an association between inhibition, working memory and mindfulness. Specifically, Riggs et al.  tested aThe other two studies investigating working memory in relation to mindfulness in healthy adolescents ,84 documHowever, the review by Gallant  on the aA recent study  evaluateTo date, it is difficult to compare our results with other findings on ADHD because only few studies have focused on the association between mindfulness and executive functions in children/adolescents with ADHD. No significant effects of mindfulness interventions were found in a review  on neuroWith regard to ADHD symptoms, our results were in line with a recent meta-analysis aimed at investigating the efficacy of mindfulness-based interventions on ADHD core symptoms in comparison with active control conditions . The metLooking at the effect sizes, our results also indicated that the effects of MOM training on neuropsychological measures were stronger than on parent ratings.In general, the positive outcomes of MOM training on neuropsychological measures and ADHD symptoms that we found could be explained by considering that our program focused on three meditation exercises that allocated attentional resources to breath, various body parts, and thoughts. Thus, during MOM, our children with ADHD developed self-regulatory skills, especially attentional control, to maintain focus on present moment experiences and inhibit distractions .Our results, although they are derived from a small group of children with ADHD, are strengthened by the inclusion of an active control group (the EEP group) that helps to control the alternative interpretation of the possible effects of the MOM intervention. As previously suggested , the inOur study has some limitations. As a preliminary study, the number of participants was limited, but the results are encouraging and helpful in designing and executing a large-scale clinical trial on MOM. Recruiting more participants could remediate the possible bias of gender in our study, and children could be more equally distributed between the two conditions with regard to demographics such as gender.Another limitation was the lack of multiple informants. Parents would/should be aware of the intervention condition to which their child was assigned, which would likely affect their ratings. Including several informants, such as teachers, would have helped with this problem.Our study lacked also of a follow-up period, which should be included in future studies to verify the duration of changes in the MOM G.Future studies should also understand why other measures, such as some behavioral and emotional aspects, depressive and anxiety symptoms, the mindfulness measure, parenting stress index, and academic skills, did not change after mindfulness practice, and should determine whether a longer duration of training would thus be more useful.Our study is a preliminary step towards establishing the effectiveness of MOM intervention in ADHD and future studies are needed to confirm the benefits of MOM by including more participants, using longer training periods, combining neuropsychological measures with questionnaires from multiple respondents , and comparing results from groups of parents who do not participate in MOM interventions (as in our study) versus those who are asked to meditate with their children  or underWhen comparing our study with previous works on mindfulness training in children and adolescents with ADHD, it is one of the few that combined objective neuropsychological measures with parent- and self-report questionnaires. Moreover, our study included an active control condition (focused on emotion awareness and recognition) that was structurally equivalent to the mindfulness-meditation program, and we randomly assigned to the two conditions children with ADHD with a narrow age range and no concurrent treatment.Overall, our results are encouraging and suggest that mindfulness meditation practices that are performed for a short period (eight weeks) promote changes in neuropsychological measures, especially those in which executive functions are involved, and behavioral symptoms in children with ADHD.


Attention-deficit/hyperactivity disorder (ADHD) is a highly heritable neurodevelopmental disorder that often persists into adulthood. There is growing evidence that epigenetic dysregulation participates in ADHD. Given that only a limited number of epigenome-wide association studies (EWASs) of ADHD have been conducted so far and they have mainly focused on pediatric and population-based samples, we performed an EWAS in a clinical sample of adults with ADHD. We report one CpG site and four regions differentially methylated between patients and controls, which are located in or near genes previously involved in autoimmune diseases, cancer or neuroticism. Our sensitivity analyses indicate that smoking status is not responsible for these results and that polygenic risk burden for ADHD does not greatly impact the signatures identified. Additionally, we show an overlap of our EWAS findings with genetic signatures previously described for ADHD and with epigenetic signatures for smoking behavior and maternal smoking. These findings support a role of DNA methylation in ADHD and emphasize the need for additional efforts in larger samples to clarify the role of epigenetic mechanisms on ADHD across the lifespan. ADHD is a disabling condition in childhood and adolescence which often persists into adulthood, interfering with the quality of social, academic, or occupational functioning3.Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder characterized by age-inappropriate levels of inattention, impulsivity and hyperactivity4 and the proportion of variance still to be explained might be, to some extent, accounted for by gene by environment interactions. In this context, epigenetic processes have emerged as a plausible mechanism by which environmental exposures can lead to long-lasting alterations, such as variation in brain structure or neuronal circuits, found in psychiatric disorders7. There is growing evidence that epigenetic dysregulation is a feature of ADHD11, depression12, autism16, schizophrenia18 and bipolar disorder19.ADHD is a multifactorial disorder with an estimated heritability of 76%. Twenty-two percent of its phenotypic variance is explained by common genetic variants28. Candidate gene studies have revealed differential methylation patterns in genes involved in the dopaminergic, serotoninergic and neurotrophic systems, including SLC6A4, DRD4, COMT, ANKK1, BDNF, or NGFR, associated with ADHD symptomatology and severity28. Seven epigenome-wide association studies (EWASs) on ADHD have been run to date, with sample sizes ranging from 54 subjects for clinical samples21 to 4,689 individuals in a meta-analysis considering ADHD symptomatology in general population9, yielding non-overlapping findings across them22. There is limited research on adults using this approach, given that most of the EWASs have focused on pediatric samples22. To the best of our knowledge, only two studies evaluated methylome-wide patterns on adults21. One identified methylation changes associated with ADHD symptomatology that did not remain significant when results were meta-analyzed across cohorts9. The second one found hypermethylated regions in genes involved in fatty acid metabolism and fatty acid oxidation pathways associated with ADHD persistence when compared to remittance21. In the childhood period, Wilmot et al. analyzed a population cohort of school-age boys and found lower methylation levels at the VIPR2 gene in ADHD subjects compared to their age- and sex- matched controls10, results that were recently replicated in the largest EWAS on ADHD in children conducted so far22. In a similar aged population cohort, Walton et al. investigated ADHD symptom trajectories from birth to adolescence and pointed to epigenetic marks in genes related to neural tube development and peroxisomal mechanisms as candidates to be involved in the different ADHD symptom trajectories across time6. In the most recent EWAS evaluating ADHD symptoms in population-based cohorts, aberrant methylation patterns at birth in different regions, lying in the ERC2 and CREB5 genes among others, were associated with later ADHD symptoms in childhood or adolescence11. And finally, the latest and largest EWAS conducted in a clinical sample of children with ADHD supported the association between ADHD polygenic risk and DNA methylation patterns at the GART and SON genes22.Studies of DNA methylation profiles in ADHD have been conducted using peripheral blood, cord blood, buccal samples or saliva29, but little is known about the co-occurrence between the epigenetic signatures characterizing both groups of age. In addition, although various studies report shared genetics between ADHD and several psychiatric and behavioral traits29, this overlap has not been assessed yet using epigenome-wide data.Recent evidence supports a large genetic overlap between ADHD in children and adultsWhereas most previous studies considered pediatric clinical samples or adult population-based cohorts with measures of ADHD symptoms, we report an EWAS on a clinical sample of adults with ADHD. With these data we (i) assessed DNA methylation signatures for ADHD in adults through an EWAS in peripheral blood mononuclear cells, (ii) tested whether either polygenic risk burden for ADHD or smoking status had an impact on those DNA methylation signatures, (iii) examined whether exposure to stressful life events had an effect on these methylation patterns in ADHD subjects and (iv) explored the overlap between these findings and results from previous meta-analyses of genome-wide association studies (GWAS-MA) on clinical ADHD or ADHD symptoms in population-based samples, and EWAS on ADHD symptoms or exposure to stressful life events.The clinical sample consisted of 103 ADHD subjects that were referred to an ADHD program from primary care centers and adult community mental health services. All subjects were evaluated and recruited prospectively from a restricted geographic area of Catalonia (Spain) in a specialized out-patient program for Adult ADHD and by a single clinical group at Hospital Universitari Vall d’Hebron of Barcelona (Spain).30.The clinical assessment consisted of structured interviews and self-reported questionnaires in two different steps: (i) assessment of ADHD diagnosis based on symptomatology using the Conner’s Adult ADHD Diagnostic Interview for DSM-IV (CAADID) by a psychiatrist and, (ii) assessment of the severity of ADHD symptoms, the levels of impairment and the presence of comorbid disorders by a psychologist to increase the diagnostic accuracy and reduce the likelihood of misdiagnosis with the Conners ADHD Rating Scale (CAARS), the ADHD Rating Scale (ADHD-RS), the Clinical Global Impression (CGI), the Wender Utah Rating Scale (WURS), the Sheehan Disability Inventory (SDS), and the Structured Clinical Interview for DSM-IV Axis I and II Disorders (SCID-I and SCID-II). Afterwards, the psychiatrist and psychologist integrate the clinical information and self-reports for the valid assessment of symptoms and impairments. In case of discordance between different raters of ADHD symptoms or inconsistencies between reporters in responses to items measuring similar symptoms, the clinician-identified symptoms on the CAADID prevailed. Exclusion criteria were IQ < 70; lifelong and current history of mood, psychotic, anxiety, substance abuse, and DSM-IV axis II disorders; pervasive developmental disorders; a history or the current presence of a condition or illness, including neurologic, metabolic, cardiac, liver, kidney, or respiratory disease; a chronic medication of any kind; birth weight≤1.5 kg; and other neurological or systemic disorders that might explain ADHD symptoms. For more detailed information on clinical assessment see Sánchez-Mora et al.31 and were available from 98 subjects with ADHD. No information was available from controls. Specifically, this questionnaire includes: premature birth, illegal drug abuse during pregnancy, maternal smoking, prenatal exposure to drugs, maternal health problems during pregnancy, other problems during maternal pregnancy, exposure to heavy metals, malnutrition, financial stress and/or poverty, extreme familial stress, neglect, familiar violence, emotional and physical maltreatment, sexual abuse, death or separation from a loved one, and other trauma in childhood or adolescence.Data pertaining to exposure to 17 stressful life events  were collected retrospectively with the CAADID Part IThe control sample consisted of 100 unrelated healthy blood donors matched by sex and ethnicity with the clinical group. Individuals with ADHD symptomatology were excluded retrospectively under the following criteria: (1) having been diagnosed with ADHD previously or (2) answering positively to the lifetime presence of the following ADHD symptoms: (a) often has trouble in keeping attention on tasks, (b) usually loses things needed for tasks, (c) often fidgets with hands or feet or squirms in seat, and (d) often gets up from seat when remaining in seat is expected.All subjects reported European ancestry, which was confirmed through principal component analysis (PCA) using genetic data. The study was approved by the Clinical Research Ethics Committee (CREC) of Hospital Universitari Vall d’Hebron, all methods were performed in accordance to the relevant guidelines and regulations and written informed consent was obtained from all subjects before inclusion into the study.® ND-1000  and by PicoGreen® . Genome-wide DNA methylation was assessed with the Illumina Infinium MethylationEPIC BeadChip Kit (EPIC array)  following sodium bisulfite treatment of genomic DNA.Peripheral blood mononuclear cells (PBMCs) of patients with ADHD and controls were isolated using the Ficoll density gradient method, and DNA was extracted using the QIAamp DNA Mini Kit DNA Purification following manufacturer’s instructions . The quality of the samples was checked by NanoDrophttps://support.illumina.com) and were imported into the R software  using the minfiData 0.2 package32. The bisulfite conversion control probes and the 59 single nucleotide polymorphism (SNP) probes of the EPIC array were used to calculate the bisulfite conversion reaction efficiency and to confirm the absence of sample contamination, respectively. Sex was confirmed for all samples using the getSex function of the minfi R package33. The Horvath Epigenetic Clock algorithm34 implemented by the agep function of the wateRmelon R package was used to calculate the estimated age of participants according to their DNA methylation data, which correlated with their reported age . Poorly performing probes or samples were removed using the wateRmelon R package . The exclusion criteria for the probes included detection P-values >0.05 for >1% of the samples and a beadcount <3 for >5% of the samples. Probes that were cross-reactive, present in sexual chromosomes or that contained polymorphisms were also excluded from the study37. Samples with >1% of probes with a detection P-value >0.01 were also removed. Probes that passed the quality control filters were quantile normalized with the dasen function of the wateRmelon R package.The 203 samples included in this study were assayed in three batches, which were preprocessed and normalized separately. Raw signal intensities of each probe were extracted using the Illumina Genome Studio software  of normalized methylation values was tested for association with the Principal Component loadings (PCs). Chip ID was associated with the first PC (PC1) in all three batches, which accounted for the 99% of the variation of samples. We therefore adjusted the beta values with the ComBat function of the SVA R package38 for this variable. The effect of batch and sex on adjusted methylation values of probes present in the three batches after quality control  was tested for association with the PCs estimated in the overall sample. Evidence of clustering according to batch was visually detected and statistically confirmed with a significant association of PC1 with batch .PCA of methylation values was conducted using the 39. To account for methylation differences between cell types, we estimated the cell-type composition using the estimateCellCounts function of the FlowSorted.Blood.450k R package40.Given that detailed smoking information was not available for each individual, an individual smoking score (continuous measure) was generated based on DNA methylation sites known to be associated with current smoking using a method developed by Elliot and colleagueslmFit function of the limma R package41. Each CpG site was tested individually in a linear regression model with normalized, corrected beta values as the dependent variable and ADHD status as independent predictor, including covariates for sex, age, batch, smoking score and cell-type composition. Age was included as covariate in all the analysis, since it was significantly different between cases and controls. Multiple testing corrections were applied using false discovery rate (FDR) with a cut-off of 5%42. The qqman R package was used to generate the Manhattan plot.Probe-wise differential methylation analysis was performed using the https://epigenetics.essex.ac.uk/shiny/EPICDNAmPowerCalcs/)43 using the default significance threshold  showed that 6.12% of sites had > 90% power to detect a mean methylation difference of 1%.The post-hoc power analysis in our sample calculated with the EPIC array online tool  and DNA methylation levels using Spearman’s correlation.At the differentially methylated CpG site, we tested the association between DNA methylation and the exposure to at least one stressful life event, and to each stressful life event separately using the comb-p44 to group spatially correlated CpG sites with a seed of P-value < 0.01 and 500 base pairs (bp) as the maximum distance. DMR P-values were corrected for multiple testing using the Šidák correction45 and significant regions were defined as those with at least two probes and an adjusted P-value < 0.05. DMRs were mapped to genes using the interface provided by the minfi R package or the UCSC Genome Browser to identify the closest gene when no genes were mapped to a region (https://genome.ucsc.edu/cgi-bin/hgGateway).To identify differentially methylated regions (DMRs), we used the Python module Sensitivity analyses were conducted with the same parameters described above for the probe-wise and regional analyses excluding smoking score as covariate in the model.n = 3), Illumina HumanOmni2.5-8 BeadChip (n = 29) and Infinium™ Global Screening Array-24 v2.0 (n = 163) , using summary statistics of the largest GWAS-MA performed to date on ADHD4, with different P-value thresholds ((PT) < 1e−04, 5e−04, 0.001, 0.005, 0.01, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 1). None of the samples used in this study were included in this GWAS-MA4, and thus did not contribute to defining the variants included in the PRS.ADHD polygenic burden was inferred using a Polygenic Risk Score (PRS) built in a subset of 195 individuals with genotype data available, from three different genotyping waves (Illumina HumanOmni1-Quad BeadChip (R2) as an additional covariate to control for ADHD polygenic risk burden.In this subset of 195 individuals, sensitivity analyses for the differentially methylated sites and regions were conducted with the same parameters used in the original EWAS but including the PRS explaining the most variance (Nagelkerke’s https://choishingwan.github.io/PRSice/) including sex and the first five PCs as covariates in the model. To set an empirical threshold for the best-fit PRS, 1,000 permutations were run. Information about the pre-imputation quality control at individual and SNP level for the 195 individuals in the target sample and about the phasing and imputation software used is described elsewhere29. The European ancestry panel of the 1000 Genomes Project was considered as reference for the imputation (ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/) and best guess genotypes were filtered by excluding variants with MAF < 0.05, missing rate>0.01, Hardy-Weinberg Equilibrium (P < 1.00E−06). Ambiguous strand and multiallelic variants were removed and independent SNPs  present in all individuals were included .ADHD PRSs for each individual were generated with PRSice2  probes identified in previous EWASs on exposure to adverse live events50; (iii) probes identified in previous EWASs on ADHD22 or ADHD symptoms9 or (iv) probes located in ADHD-associated loci identified through GWAS51 showed, on average, a stronger association with adult ADHD than other methylation sites by regressing our EWAS test statistics (Zscore) on each CpG category as described by van Dongen et al. 9:We assessed whether probes in different categories: (i) showing a statistically significant proportion of methylation variance explained by additive genetic effects as reported by Zeng et al.Zscore| represents the absolute value of the Zscore from our EWAS on adult ADHD, category x represents whether a CpG belongs or not to a specific category and category x represents the effect estimate for that category. A CpG was assigned to a category if it was associated to the phenotype of interest according to the P-value thresholds shown in Supplementary Table PBootstrap < 3.85E−03; accounting for the 13 analyses conducted).where |mentclass2pt{minimmentclass2pt{minimP-value<1.00E−05 in our results. For the enrichment analysis of regulatory domains, ontological categories and pathways, probes were annotated with the Illumina Human EPIC array annotation R package (“IlluminaHumanMethylationEPICanno.ilm10b2.hg19”). The enrichment analyses for transcription factor binding sites (TFBS) and DNase I hypersensitive sites (DHS) from the ENCODE project52 were performed using a two-sided Fisher’s 2×2 exact test. The enrichment analyses for GO terms and KEGG, Reactome or Biocarta pathways were assessed using the gsameth function of the missMethyl R package53. Gene sets denoting canonical pathways were downloaded from MSigDB (http://www.broadinstitute.org/gsea/msigdb), which integrates Kyoto Encyclopedia of Genes and Genomes (KEGG) (http://www.genome.jp/kegg/), BioCarta (http://www.biocarta.com/), Reactome (https://reactome.org/) and Gene Ontology (GO) (http://www.geneontology.org/) resources.We also tested for enrichment of regulatory domains, ontological categories and pathways, using CpG sites with The datasets for this article are not publicly available because of limitations in ethical approvals and the summary data will be available upon request.2 = 2.60, P = 0.11), with 56% and 45% of cases and controls being male, respectively. Age of participants was significantly different between cases and controls (P = 3.61E−04), with a mean age of 31.90 (SD = 11.45) years in cases and of 37.25 (SD = 9.47) years in controls. In the case group, 35% of participants experienced no stressful life events, 35% were exposed to at least one prenatal stressful life event and 54% were exposed to at least one of them after birth . This CpG lies 77 bp upstream the PCNXL3 gene and was hypermethylated in patients, with a mean difference of 0.2% between groups . When we excluded it from the fitted model as a sensitivity analysis, cg07143296  and the region in chromosome 11 were no longer significant and the other regions remained significant , and was significantly higher in ADHD patients than controls . After adding it as a covariate to the model fitted for the EWAS, we found that the cg07143296 CpG site  and three of the four genomic regions identified remained significant . In addition, when we assessed the overlap between genetic and epigenetic signatures of ADHD, we found suggestive evidence of overlap between our EWAS results and probes annotated to ADHD-associated loci in the largest GWAS meta-analyses on ADHD across the lifespan or GWAS-MA on ADHD symptoms in children , but not with results of previous GWAS-MA on ADHD conducted separately in adults or children   in our EWAS, we found no enrichment of regulatory domains (TFBS and DHS) from the ENCODE project52 nor ontological categories or pathways from GO terms, KEGG, Reactome or Biocarta 55, neuroticism and regulation of histone acetylation dynamics (PWWP2B)57 or regulation of immune signaling (UBASH3A)58. We also identified a CpG site (cg07143296) significantly hypermethylated in ADHD, located close to PCNXL3, a gene related to autoimmune diseases59. Although not achieving significance after multiple comparison correction, CpG sites in ADHD-related genes were found among the top ten signals of the EWAS, including CREM, which has been previously associated with impulsivity, hyperactivity, anxiety-like behavior, circadian rhythmicity and drug addiction62, ADK, whose deficiency may result in altered dopaminergic function, attentional impairment, and learning impairments64, or LAT, whose genetic variation has been associated with educational attainment65.Methylation differences were found in regions that include genes related to cancer and pulmonary function , to random variation and limited statistical power or, as previously suggested by Meijer et al.21, to the fact that the epigenetic effects identified may not be those with the strongest effect sizes on the phenotype21.The lack of overlap between our EWAS results and those from previous EWASs on ADHD in childhood47 and suggestive evidence of enrichment in loci described in the largest GWAS-MA on ADHD4 and on ADHD symptoms51. However, no evidence was found for overlap between our EWAS results and loci from smaller GWAS-MAs on ADHD28 or for a substantial effect of the polygenic burden for ADHD on the methylation patterns identified. These inconsistent results should be interpreted in the context of the limited statistical power of the EWAS and warrant further investigation.Results on the relationship between genetic and epigenetic signatures in ADHD were not conclusive. We found enrichment of signal for adult ADHD in CpGs whose methylation variance is mainly explained by additive genetic effects39.Our EWAS findings do not seem to be driven by an effect of current smoking since they were significant when we adjusted the model for it. When excluding smoking status from the model, we did not detect an effect of methylation on ADHD through smoking for cg07143296 or for the region in chromosome 11 but we cannot rule out a mediating effect for the remaining regions as their signal becomes more significant. Although bearing in mind that we used an estimated smoking score that might be a less accurate tool than clinical data, it has been postulated as a valid marker for current tobacco exposure49 or maternal smoking50 was obtained. In addition, methylation differences were identified in regions lying in or near genes (such as DENND2D or PWWP2B) related to phenotypes where tobacco exposure is a key risk factor68, and maternal smoking, which increases risk of ADHD in the offspring71, was the most frequently prenatal stressful life event reported by participants with ADHD.We also report preliminary data supporting overlap between epigenetic signatures of ADHD and smoking-related traits or behaviors. Enrichment of top-ranking CpGs from previous EWASs on smoking behavior72. Extreme familial stress was found among the most frequently reported postnatal exposures in individuals with ADHD, which is not surprising given that the presence of ADHD has been associated to varying degrees of disturbances in family and marital functioning75. However, no effect of stressful live events on DNA methylation patterns was found in ADHD subjects. Given that our study lacked data on exposure to stressful live events in controls, larger studies including cases and controls are needed to understand the impact of environmental factors on DNA methylation patterns associated with ADHD.To note, sixty-five percent of individuals with ADHD reported having been exposed to stressful life events, a circumstance that has been associated with the persistence of the disorder into adulthood76, although these novel signatures identified in blood might be used as biomarkers for the disorder.The results of the present study should be interpreted in the context of several limitations. First, the limited sample size of the present EWAS, which should be viewed as a pilot study whose findings await further replication. Second, our study design allowed the assessment of methylation patterns in a restricted clinical sample of medication-naïve subjects with no comorbid disorders. This design may have facilitated the identification of novel epigenetic signatures, which may not have been possible using a broader recruitment strategy. However, given that patients under medication and/or with lifetime comorbidities were excluded and this group accounts for a not negligible proportion of the overall ADHD group, further studies in larger samples including cases and controls meeting common inclusion criteria, more relaxed in terms of medication or comorbid disorders, will be required to clarify whether the results obtained could be generalized to a more realistic clinical situation. Third, the low inflation factor obtained indicates that the distribution of effect sizes in the present EWAS were not driven by systematic biases but also suggests that our study had limited statistical power and that the data may have been overcorrected, which may have prevented us from detecting methylation signatures with small effect sizes. And fourth, peripheral tissues used generally as proxies have limited utility for inferring variation in the brainIn summary, we conducted the largest study assessing DNA methylation signatures in a clinical sample of adult patients with ADHD. Our results suggest that ADHD polygenic risk burden or current smoking status do not change substantially the methylomic variation between cases and controls, suggest an overlap between epigenetic signatures of ADHD and smoking-related traits, and point to an overlap between genetic and epigenetic signatures in ADHD. These results emphasize the need of additional efforts in larger samples and the inclusion of stressful life events in future studies to clarify the role of epigenetic mechanisms and environmental risk factors on ADHD across the lifespan.Supplementary MaterialSupplementary Table 1Supplementary Table 3


The aim of this survey study was to examine the etiologies of attention-deficit/hyperactivity disorder (ADHD) attributed by caregivers of Taiwanese children with ADHD, particularly factors affecting such attribution. This study had 400 caregivers of children with ADHD as participants. We examined the caregiver-attributed etiologies of ADHD and factors affecting such attribution. Caregivers completed the self-report questionnaire to rate how likely they perceived various etiologies of ADHD to be; the Affiliate Stigma Scale for the level of affiliate stigma; and the short Chinese version of the Swanson, Nolan, and Pelham, Version IV Scale for child’s ADHD and oppositional symptoms. Brain dysfunction (84.8%) was the most commonly attributed etiology, followed by failure of caregivers in disciplining the child (44.0%); a poor diet, such as a sugar-rich diet (40.8%); a poor living environment (38.8%); the child imitating their peers’ improper behavior (37.3%); failure of school staff in disciplining the child (29.0%); the education system’s overemphasis on academic performance (27.3%); and supernatural beings or divination-based reasons (3.8%). Caregivers’ affiliate stigma was significantly associated with the attribution of several nonbiological etiologies other than brain dysfunction. Caregivers’ education level and children’s sex, hyperactivity/impulsivity, and oppositional symptoms were significantly associated with various caregiver-attributed etiologies. Therefore, to deliver more accurate knowledge about ADHD in educational programs, health professionals should consider those etiologies that are attributed by caregivers of children with ADHD. Attention-deficit/hyperactivity disorder (ADHD) is the most prevalent childhood-onset neurodevelopmental disorder. ADHD is highly heritable and multifactorial; multiple genes and non-inherited factors contribute to the disorder . NeuropsResearch has discovered that many factors—including caregivers’ health beliefs, help-seeking behavior, and access to care—influence whether a child with emotional or behavioral problems receives treatment ,10. CareA study on caregivers of Iranian children with ADHD found that 52.3% of caregivers disagreed that ADHD is the result of biological and genetic reasons; 52.2% considered ADHD to be the result of an overindulgent caregiver . A studyMany factors have been noted to influence caregiver-attributed etiologies of their child’s ADHD. As for caregiver-related factors, mothers tended to attribute their child’s ADHD to biological reasons, whereas fathers tended to attribute ADHD to psychological factors, such as the child’s lack of effort . CaregivAs for child-related factors, the literature has furnished mixed results for the relationship between child’s sex and caregiver-attributed etiologies of ADHD. A study in Iran found no evidence for this relationship , whereasHow affiliate stigma affects caregiver-attributed etiologies of ADHD remains unclear. Affiliate stigma, held by caregivers of people with mental illness, is defined as the perception, awareness, and internalization of public stigma toward those with mental illness . ResearcThe present study examined etiologies attributed by the caregivers of Taiwanese children with ADHD, particularly factors affecting such attribution. We had two hypotheses. First, caregivers attribute their child’s ADHD to various etiologies. Second, caregiver-attributed etiologies of ADHD are related to caregivers’ demographic characteristics and affiliate stigma and children’s demographic and ADHD characteristics.Caregivers of children with ADHD were recruited between June 2018 and April 2019 from outpatient psychiatric clinics for children and adolescents of two medical centers in Kaohsiung, Taiwan. The child had to be aged 18 years or younger and had to have received a diagnosis of ADHD as per the DSM-5 criteria . ADHD waimpossible, 2: unlikely, 3: somewhat likely, and 4: very likely). Ratings of 3 and 4 were considered an attribution of ADHD to the etiology, and ratings of 1 and 2 were considered a nonattribution. Caregivers were further subdivided into those who attributed and did not attribute ADHD to the etiologies. We noted how many of these etiologies each caregiver attributed to their child’s ADHD.First, information on common caregiver-attributed etiologies was gathered through three focus groups sessions; two groups for family caregivers and one group for child psychiatrists. The psychiatrists were interviewed on those caregiver-attributed etiologies they have encountered in their practice. Each group had five to eight members. On the basis of the information collected, we developed a self-report questionnaire. In the questionnaire, caregivers of children with ADHD rated how likely they perceived various etiologies of ADHD to currently be. The etiologies were brain dysfunction; failure of caregivers in disciplining the child; a poor diet, such as a sugar-rich diet; a poor living environment; the child imitating their peers’ misbehavior; failure of school staff in disciplining the child; the education system’s overemphasis on academic performance; and supernatural beings or divination-based reasons. Caregivers rated these etiologies on a four-point scale (1: I feel inferior because one of my children has ADHD), cognition , and behavior . Respondents rated their current agreement with each statement in the ASS items on a four-point Likert scale . A higher score on the ASS indicates greater self-stigma toward their child’s ADHD. The original version was demonstrated to have excellent internal consistency (α = 0.94) and satisfactory predictive validity [The Affiliate Stigma Scale (ASS) is a self-rated 22-item questionnaire measuring the caregivers’ internalization of stigma toward their family member’s mental illness . We focuvalidity . The ASSvalidity . In the the symptom is absent, 3: the symptom is severe). In the present study, Cronbach’s α values for inattention, hyperactivity, and impulsivity, and oppositional behavior were 0.89, 0.90, and 0.92, respectively.The short Chinese version of the SNAP-IV was used to assess the caregiver-reported severity of ADHD symptoms exhibited in the previous month. This version comprises 26 items encompassing the core DSM-derived ADHD subscales of inattention, hyperactivity, and impulsivity, and the oppositional symptoms of oppositional defiant disorder ,31. Eachfrequently) and low .Information regarding caregivers’ and children’s sex, age, and education level was collected. This study also examined caregivers’ marital status . Caregivers’ occupational socioeconomic status (SES) was assessed using the Close-Ended Questionnaire of the Occupational Survey (CEQ-OS) , which cBefore starting the study, the principal investigator (PI) trained the research assistants to make sure that they were competent to direct the participants to complete the research questionnaire. Then, research assistants explained the procedures and methods of completing the questionnaire to the participants individually. The participants could propose any question when they had problems on completing the questionnaires, and the research assistants resolved their problems. The PI discussed with research assistants weekly to ensure the quality of the study.p-value <0.00625 (0.05/8) was considered to indicate significance. Multiple regression was used to analyze factors affecting the numbers of attributed etiologies for each caregiver. A two-tailed p-value <0.05 indicated statistical significance.SPSS 22.0 statistical software  was used for data analysis. We calculated, for each etiology, the proportion of caregivers that attribute ADHD to it . We also calculated the number of attributed etiologies for each caregiver. Forward conditional logistic regression was used to examine etiologies’ associations with caregivers’ and children’s sociodemographic characteristics, caregivers’ affiliate stigma, and children’s ADHD and oppositional symptoms. Significance was indicated using the odds ratio (OR) and 95% confidence interval (CI). Because multiple comparisons were conducted, a The study procedures were conducted in accordance with the Declaration of Helsinki. The IRBs of Kaohsiung Medical University and Chang Gung Memorial Hospital, Kaohsiung Medical Center approved the study. All participants were informed about the study and provided written informed consent before completing research questionnaires.p < 0.001); a poor living environment (p = 0.005); the education system’s overemphasis on academic performance (p = 0.002); and supernatural beings or divination-based reasons (p = 0.003). Caregivers’ education duration was significantly and positively associated with the attribution of brain dysfunction (p = 0.002). Relative to caregivers of girls, caregivers of boys were more likely to attribute ADHD to brain dysfunction (p = 0.006). The severity of hyperactivity/impulsivity symptoms was positively and significantly associated with attributions of imitating peers’ misbehavior (p = 0.001). The severities of oppositional symptoms were significantly and positively associated with the attributions of caregivers’ (p = 0.001) and teachers’ failure to discipline the child (p = 0.001).p = 0.001) and the severity of oppositional symptoms (p = 0.020) were both significantly and positively associated with the number of etiologies to which a caregiver attributes ADHD.This study found that caregivers attributed their child’s ADHD to a variety of etiologies. Caregivers’ education duration and children’s sex were related to the attribution of ADHD to brain dysfunction, whereas caregivers’ affiliate stigma and children’s oppositional and hyperactivity/impulsivity symptoms were related to the attribution of ADHD to nonbiological etiologies. Affiliate stigma and children’s oppositional symptoms were significantly associated with the number of etiologies to which a caregiver attributes their child’s ADHD.Because the caregivers of the present study were recruited from psychiatric outpatient clinics for children and adolescents, a high proportion (84.8%) of caregivers attributed ADHD to brain dysfunction. Notably, 64.4% of caregivers attributed their child’s ADHD to two or more etiologies, indicating that nonbiological etiologies are common explanations for ADHD. Research has demonstrated that caregiver attributions of ADHD etiologies predict their treatment choices . The mosA high proportion of caregivers attributed their child’s ADHD to school-related etiologies, including failure of school staff in disciplining the child, the education system’s overemphasis on academic performance, and the child imitating their peers’ improper behavior. Being deeply influenced by Confucianism, Taiwanese people emphasize harmony, are oriented toward their community, and value academic achievement when raising their children . HoweverSimilar to the results of U.S. studies ,36, a hiOnly 3.8% of caregivers attributed their child’s ADHD to supernatural beings or divination-based reasons. Traditionally, spirituality and interdependence of human beings with the universe have always played a major role in influencing Chinese values and thoughts. Mental problems are at times likened to the evil spirits attaching to the individuals and requiring some form of penance and spiritual cleaning to regain mental wellbeing . HoweverThe present study demonstrated that affiliate stigma is significantly associated with the attributions of several nonbiological etiologies of ADHD, including diet, a poor living environment, the education system’s overemphasis on academic achievement, and supernatural beings or divination-based reasons. Affiliate stigma was also significantly associated with the number of etiologies to which caregivers attributed their child’s ADHD. Affiliate stigma in caregivers of people with mental illness develops through the perception and internalization of public stigma toward caregivers . CaregivOur study demonstrated that the severities of hyperactivity/impulsivity symptoms are significantly and positively associated with the caregiver attributing ADHD to the child imitating their peers’ misbehavior. According to the common-sense model of illness danger , when ont = 8.783, p < 0.001); therefore, the association of occupational SES with attribution of etiologies might be decreased by education duration in forward conditional logistic regression.Caregivers of boys or caregivers who were educated for longer were significantly more likely to attribute ADHD to brain dysfunction. A U.S. study found that parents of boys were more likely than parents of girls to endorse genetic causes and less likely to cite stressful life events as ADHD causes . An inteOur study has several limitations. First, our cross-sectional research design limited the inference of a causal relationship between affiliate stigma and the attribution of ADHD to various etiologies. Second, our data were obtained solely from caregiver self-reports, potentially resulting in common-method variance. Third, we did not examine the effects of multidimensional psychosocial factors, such as social support or health beliefs, on the attribution of ADHD to various etiologies. Fourth, this cross-sectional study recruited caregivers of children with ADHD diagnosed for various time periods, which might influence caregivers’ attribution of ADHD etiologies. Fifth, the present study did not examine the effect of residential areas of families on their attributions. However, research has demonstrated that the Internet becomes the first and most popular source for caregivers to search for opinions regarding the etiologies and intervention models of ADHD . The intThe debate on ADHD’s causes centers on the opposition between neurobiological and psychosocial explanations . We demo


The Wechsler Adult Intelligent Scale (WAIS) is the most frequently administered cognitive assessment for adult Attention‐deficit hyperactivity disorder (ADHD); therefore, identifying discrepancies in WAIS profile in patients and comparing with matched controls would be clinically and diagnostically beneficial.The WAIS‐III profiles of 50 adults with ADHD were compared to an age‐matched typical development (TD) group.The adult ADHD group exhibited significantly lower WAIS‐III working memory (WM) and processing speed (PS) indices. However, these differences disappeared when intelligence quotient (IQ), Beck Depression Inventory (BDI) score, or Autism Quotient (AQ) score was included as a covariate. The adult ADHD group also demonstrated significantly lower scores in several WM‐ and PS‐domain subscales, while crystallized abilities were comparatively preserved. Additionally, only a small portion of participants in both groups lacked any significant gaps between WAIS‐III verbal and performance IQ scores (VIQ–PIQ) or associated indices.This study confirms previous findings that adult ADHD patients have deficits in WM and PS. However, it is highly likely that comorbidities such as depression and autism spectrum disorder contribute to lower WM and PS scores in adult ADHD. Unexpectedly, a “flat profile” is uncommon even in TD adults. Therefore, clinician should assess how WAIS deficits affect daily life rather than merely considering an uneven WAIS profile when diagnosing and treating adult ADHD. Although attention‐deficit hyperactivity disorder adults have lower scores of WM and PS in WAIS‐III, the comorbidities such as depression considerably contribute to these findings. Significant discrepancies in VIQ‐PIA and among index scores are common even in TD adults. The estimated worldwide prevalence of adult ADHD is 2%‐5%.In childhood, main caregivers or teachers frequently first notice ADHD‐related behaviors and take children to see doctors, while adults suspecting ADHD seek treatment themselves or are advised by workplace supervisors, spouses, or parents. However, self‐referral may lead to under‐ or over‐diagnosis of adult ADHD.The continuous performance test (CPT), eye tracking task, functional MRI, and event‐related potentials have demonstrated promise for detecting ADHD;The WAIS‐IV has been available in Japan since 2018. There are several changes from WAIS‐III to WAIS‐IV such as abolition of VIQ/PIQ, the introduction of General Ability Index (GAI), a minor change of digit span and the addition of visual puzzles to the perceptual reasoning index (PRI). Thus, it is a good opportunity to marshal data about ADHD profile of the former version of the WAIS  so that these findings would be passed onto the next version of the WAIS .In this study, the diagnostic utility of the WAIS‐III profile was investigated in adults with confirmed ADHD by comparing to WAIS‐III profiles to a large control cohort.22.1This study involved 90 participants from two groups: (a) a group of 50 adults diagnosed with ADHD , age range = 19‐54) and (b) a control group of 40 adults , age range = 19‐53). The adult control group was recruited from Japanese companies and facilities or universities. The ADHD group was recruited from outpatients at the clinics where the first author was working.Exclusion criteria for all participants were a current major depressive or manic‐depressive episode, history of psychosis, full‐scale IQ (IQ) < 80, sensory‐motor handicap, and neurological illness. Since many ADHD patients took WAIS‐III shortly after their first visit, only two of them had taken methylphenidate. They stopped taking ADHD medication on the testing day. No patient was prescribed atomoxetine.The ADHD group comprised 32 individuals with predominantly inattentive presentation, 17 with combined, and one with predominantly hyperactive/impulsive presentation. Comorbidities in the present or the past in the ADHD group (some participants had more than one) were major depressive disorder , dysthymic disorder (n = 13), autism spectrum disorder , social anxiety disorder (n = 2), obsessive‐compulsive disorder , generalized anxiety disorder (n = 1), tic disorder (n = 1), post‐traumatic stress disorder , substance use disorder , and developmental coordination disorder .All the participants were administered the WAIS‐III, Assessment System for Individuals with ADHD (ASIA), and Mini International Neuropsychiatric Interview (MINI) and also answered the Japanese versions of the Beck Depression Inventory (BDI)This study was approved by the Ryukoku university ethics committee. All participants gave written informed consent after a detailed description of study aims and protocols.2.1.1never, 1 = sometimes, 2 = often/always). The ASIA ADHD criteria B to E, corresponding to DSM‐5 ADHD criteria B to E, are evaluated on a 2‐point scale . The ASIA shows acceptable reliability and validity.The ASIA is a Japanese semi‐structured diagnostic interview for adult ADHD. The ASIA ADHD criteria A, corresponding to DSM‐5 ADHD criteria A, is comprised of 144 questions that assess nine inattention symptoms and nine hyperactivity‐impulsivity symptoms in childhood and adulthood on a 3‐point scale , perceptual reasoning index (PR), working memory index (WMI), and processing speed index (PSI) in addition to full intelligence quotient (FIQ), Verbal IQ (VIQ), and Performance IQ (PIQ). The VC includes vocabulary (V), similarities (S), and comprehension (C) subtests. The PR includes block design (BD), picture completion (PC), and matrix reasoning (MR) subtests. The WMI includes arithmetic (A), digit span (DS), and letter‐number sequencing (LN) subtests. Finally, the PSI includes coding (CD) and symbol search (SS) subtests.2.1.3The Mini‑International Neuropsychiatric Interview (MINI) is a structured interview used to diagnose 17 DSM disorders. It is composed of 130 questions with adequate psychometric properties for the English version. This measure was validated with a Japanese sample, with adequate levels of reliability and validity .2.1.4The Beck Depression Inventory‐II (BDI‐II) is a self‐report inventory that evaluates depression severity. BDI‐II includes 21 items measuring depressive symptoms, such as sadness, pessimism, suicidal thoughts or wishes, tiredness or fatigue, loss of energy, and loss of pleasure. Each item is scored on a four‐point scale ranging from 0 to 3. Higher scores indicate higher depression severity. The Japanese version of the BDI‐II developed by Kojima et al2.1.5The AQ is a self‐reporting questionnaire for autism spectrum disorders, consisting of 50 items rated on 4‐point scale. It had satisfactory internal consistency reliability, test‐retest reliability and construct validity.2.1.6The Adult ADHD Self‑Report Scale‐Japanese version (ASRS‑J) parallels the English version of the ASRS 2.2IBM SPSS Statistic 25 was used for statistical analyses. Differences in frequencies were examined by chi‐square test unless the minimum case number (frequency) was 5 or below, in which case Fisher exact test was employed. Specific comparisons and tests are described below.2.2.1t test with effect size .t test indicated statistical significance (P < .05), ANCOVA was conducted with FIQ as a covariate, and then, ANCOVA with BDI or AQ as a covariate was conducted.Full‐scale IQ, VIQ, PIQ, index scores , and index subscale scores were compared between adult ADHD and TD groups by independent samples 2.2.2Ratio gaps of significant discrepancy at the 15% or 5% levels in VIQ–PIQ or any 6 pairs of index scores between groups were evaluated by chi‐square test. Additionally, ratio gaps for index pairs in each discrepancy direction were compared between groups by chi‐square test . Furthermore, the ratios of indices with no discrepancy in VIQ‐PIQ or 6 pairs of index scores were tested by chi‐square test at 15% or 5% levels.2.2.3A range of 8 points or more among verbal or performance scales was considered abnormal scatter.2.2.4To examine group differences in the frequencies of FIQ, VIQ, PIQ, and any 4 index scores over 115 or below 85  or over 130 or below 70 , chi‐square test was performed. Similarly, chi‐square test was performed to examine group differences in the frequencies of subscale scores over 13 or below 7 .2.2.5For each subscale, significant deviation from each individual's (not population's) mean was assessed at the 15% and 5% level. If there was significant difference between VIQ and PIQ at ≥15% level, deviation of verbal (performance) scale scores from the mean verbal (performance) was checked. Then, the frequencies of relative strengths and weaknesses were compared between ADHD and TD groups.2.2.6Logistic regression analysis with stepwise forward elimination and maximum likelihood estimation was performed to predict ADHD from WAIS variables. Only variables that reached significance in univariate comparison were entered in the model.3t = 0.03, P = .98) or gender ratio . The ADHD group demonstrated a significantly higher BDI‐II score than the TD group did , and a significantly greater proportion of the ADHD group exceeded the BDI‐II cutoff (14) for mild depression compared to the TD group . Additionally, there was a moderate positive correlation between BDI‐II score and ASRS score .There was no significant group difference in mean age . The ADHD group also demonstrated a significantly higher AQ score than the TD group did , and there was a moderate correlation between AQ and ASRS score . Additionally, the proportion of subjects with AQ scores exceeding the cutoff (7) for ASD was significantly greater in the ADHD group than in the TD group .Total ASRS score and both inattention and impulsivity‐hyperactivity subscores were significantly higher in the ADHD group than in the TD group  but the ADHD group exhibited significantly lower WM and PS index scores . However, the significance of the WM difference vanished when tested by ANCOVA with FIQ as a covariate . Furthermore, the significance of the PS difference was also reduced to marginal when compared by ANCOVA with BDI or AQ as a covariate . In subtests, the ADHD group demonstrated significantly higher coding and symbol search subscores  , VC‐WM discrepancy at 5% (χ2 = 9.51), VC > WM at 15% (χ2 = 6.77), VC < WM at 5% (χ2 = 9.50), VC > PS at 15% (χ2 = 4.94), and VC > PS at 5% (χ2 = 4.68) .There was no significant difference in the rate of 5% or 15% VIP‐PIQ discrepancy between groups. However, the ADHD group showed significant VC‐WM discrepancy at 15% (χP = .08 by Fisher's exact test), while 4 TD and 2 ADHD subjects showed no discrepancy at the 5% level (P = .40 by Fisher's exact test)  or P scatter .There were no significant group differences in abnormal V scatter . For subscales, there were significant differences in A under 7 (A7), D under 7 (D7), LN under 7 (LN7), PC over 13 (PC13), and CD under 7 (CD7) .There were significant group differences in the frequencies of WM score under 85, PS score under 85, and PS score over 115 .There were significant group differences in the ratios of C weakness (Cw) at 15%, D weakness (Dw) at 15%, PA strength (PAs) at 5% and 15%, PA weakness (PAw) at 5%, and MR strength (MRs) at 5%  were eliminated, while VC‐WM (5%), C7, MR13, and CD7 reached significance .Finally, logistic regression analysis with stepwise forward elimination and maximum likelihood estimation was conducted, including variables that reached significance in previous analyses. If one variable was related to multiple significance discrepancies, the following rules were applied. 1. A continuous variable is preferred over a categorical variable. 2. Variables with larger effect sizes are preferred. Consequently, VC > PS (15%), A4In our study, there was no significant difference in FIQ between ADHD and TD groups, but FIQ was numerically lower in the ADHD group. Theiling and Petermann speculated that this FIQ reduction is most likely due to decrements in WM and PS.Our study confirmed that these WM and PS deficits extend to adult ADHD. Alternatively, crystallized intelligence was preserved in adult ADHD, in accord with a previous study.Compared to TD controls, the ADHD group also demonstrated significantly lower CD and SS subscores, both of which are included in the PS index. In adult ADHD, CD, DS, A, and BD are often impaired.This study found no significant difference in VIQ‐PIQ discrepancy ratio between groups. While it is believed that differences between VIQ and PIQ are indicative of a cognitive disorder, this is not necessarily the case. The standardized sample for WAIS‐III showed that higher IQ individuals are more susceptible to large differences between VIQ and PIQ. This tendency is also found in discrepancies between index scores.The ADHD group showed a significantly higher ratio of VC > WM and significantly lower ratio of VC < WM than the controls did. There are few studies reporting discrepancies in index scores among adults; however, children with ADHD do exhibit significant discrepancies between FD and other indices of the WISC‐III. Anastopoulous et alThe most striking finding in this study is the low “flat profile” rate in both TD and AHDH subjects. Only a small portion of both groups completely lacked discrepancies in index scores at the 15% or 5% level. The former was mathematically expected but the latter is beyond expectation. Significant discrepancies in index scores appear to be the rule rather than the exception and, thus, are of no value for ADHD diagnosis, although specific discrepancies may be clinically and diagnostically meaningful to ADHD deficits observed in daily life.4.1t test. For instance, WM and PS index scores and CD subscales were absolute weaknesses in the ADHD group. Additionally, the ADHD group showed significantly higher rates of weakness in A, DS, and LN but a significantly higher rate of strength in PC compared to controls. However, these discrepancies could reflect deviation of control sample distributions from population distributions.As expected, the frequencies of most individual scores exceeding the cutoff differed significantly between groups by 4.2Strengths and weaknesses in individual profiles may be clinical useful for treatment decisions.4.3In this study, 35% of ADHD and 20% of TD group participants showed abnormal scatter with no significant group difference in ratio of scatter. Ryan reported that intersubtest scatter among brain‐damaged patients as a whole was no greater than that for persons in the standardization sample.4.47 reached significance in logistic regression analysis for discriminating adult ADHD from TD controls. The significance of Cw and MRs for distinguishing ADHD from TD controls is unexpected as neither has been identified previously as a diagnostic marker.In this study, VC‐WM (5%), Cw (15%), MRs (15%), and CDIn accordance with the previous studies, scores of WM and PS are lower in adult ADHD than control; however, these deficits could be well explained by FSIQ, ASD trait, or depression. Unexpectedly, this study revealed that profile discrepancies in index scores  are the rule even in typically developed adult controls. Thus, it is risky for clinicians to diagnose ADHD or other developmental disorders, heavily relying on the up‐and‐down profile in index scores. This finding also raises the question of how most people adapt to the challenges posed by their environment despite an uneven WAIS profile.Although there were some minor alterations in the WAIS‐IV from the WAIS‐III, findings in this study could be of clinical use because the WAISs are relatively robust among any versions. Theiling and PetermanDespite the minor alterations, the correlations between the IQ, index, and subtest scores in the former and the current Japanese version of WAIS are generally high .4.5This study has several limitations. First, the relatively small number of subjects precluded comparisons between genders and specific ADHD subtypes. Second, participants in both groups in this study are regarded as a convenient sample. Thus, this fact may limit generalizability of the results in this study. Finally, these findings do not necessarily reflect deficits in daily life. Test interpretation should consider ecological context,The authors declare no conflicts of interest.TT and YT contributed to the study's design, acquisition of the data, analysis and interpretation of the data, and drafting of the manuscript. YN contributed to the acquisition of the data, the analysis, and interpretation of the data.Written informed consents were obtained from all participants.Registry and the Registration NO. of the study/trial: None.Animal Studies: None.