In this systematic review, we will consider and debate studies that have explored the effects of ω-3 polyunsaturated fatty acids (PUFAs) in three major, and somehow related, developmental psychiatric disorders: Autism, Attention Deficit and Hyperactivity disorder and Psychosis. The impact of ω-3 PUFAs on clinical symptoms and, if possible, brain trajectory in children and adolescents suffering from these illnesses will be reviewed and discussed, considering the biological plausibility of the effects of omega-3 fatty acids, together with their potential perspectives in the field. Heterogeneity in study designs will be discussed in the light of differences in results and interpretation of studies carried out so far. Mental disorders, despite the growing pharmacological discoveries, will gradually increase in the next decades . InteresEssential Fatty Acids (EFAs) are obtained from plants or other organisms that possess enzymatic pathways for their synthesis. EFAs are therefore essential dietary nutrients for survival of humans and other mammals because of the absence of the desaturase (Δ)12 and Δ 15 enzymes necessary to insert a double bond at the n ω-6 or -3 position of a fatty acid carbon chain . There aMoreover, LCPUFAs are incorporated into membrane phospholipids and the incorporation of DHA takes place in uniquely high levels in the central nervous system . This acOmega-3 PUFAs deficiencies have been reported in people with a wide range of mental disorders, including attention deficit hyperactivity disorder (ADHD), depression, schizophrenia (SCZ), and Autism Spectrum Disorder (ASD) ,22,23,24In this context, the aim of this systematic review is to provide an updated account of the evidence of the efficacy and safety exerted by ω-3 PUFAs supplementation in ASD, ADHD and early psychotic symptoms (ultra-high risk of psychosis and first psychotic episode) to check the hypothesis that ω-3 PUFAs might be useful either sole or in augmentation as a potential therapy for these disabling psychiatric disorders.The worldwide prevalence of psychosis has been estimated to be approximately 1% . NotablyTo date, only five RCTs explored the role of ω-3 PUFAs supplementation in UHR patients or in first episode of psychosis .The study with the larger sample is a multicenter RCT study carried out by McGorry et al.  on 304 sWe identified two RCT studies reporting contrasting results. Pawelczy  demonstrInterestingly, although the evidence reporting the effectiveness of ω-3 PUFAs in psychosis is still on its infancy, several meta-analyses conducted in patients affected by SCZ ,61,62,63Autism spectrum disorders (ASD) refers to a group of conditions related to neurodevelopment including impaired social behavior, restricted communication, repetitive activities and limited interests. The etiology is primarily linked to genetics but also environmental factors may play a relevant role.The World Health Organization (WHO) updated the prevalence estimating that worldwide 1 in 160 children has an ASD. The disorder is evident in early childhood and tends to persist into adolescence and adulthood.Despite progress in medically treating ASD, there is an increasing interest in alternative treatments including melatonin, vitamins, a gluten- and casein-free diet, and the use of ω-3 PUFAs, although the biological plausibility is quite different among these alternatives. Indeed, ω-3 PUFAs and their metabolic products offer a solid basis, since they have been implicated in ASD via their roles in brain structure and function, neurotransmission, cell membrane structure and microdomain organization, inflammation, immunity and oxidative stress. There is accumulating data to support that EPA and DHA are important for brain structure and function and have been advocated for the treatment of multiple neurodevelopmental disorders including mood disorders, schizophrenia, ADHD, and ASD.Abnormality in blood levels of ω-3 PUFAs has been reported in psychiatric disorders including, but not limited to, ADHD and ASD ,24,25. IIn this paragraph, we provide an update regarding the effects of ω-3 PUFAs supplementation on symptoms of ASD in children. We included RCTs reporting outcome measures as core symptoms of ASD  and symptoms or behaviors associated with ASD .n = 57) affected by ASD between the age of five and eight were randomly assigned to six weeks of treatment (n = 29) with 1.3 g of ω-3 PUFAs (and 1.1 g of DHA + EPA) or an identical placebo (n = 28). We identified three RCT studies . The firThe primary outcome measure was defined a priori as the change in hyperactivity on the Aberrant Behavior Checklist  over the six-week treatment period: children in the treatment group did have greater mean improvements in hyperactivity compared to the placebo group (a 5.3 point reduction in the ABC-H in the ω-3 PUFAs group vs. 3.4 in the placebo group), but this difference was not significant. Concerning the secondary outcome measures, this study found statistically significant improvements in the ω-3 PUFAs group in two secondary outcome measures, the stereotypy and lethargy subscales of the ABC.n = 24) or placebo (n = 24).The second RCT  as conduThe authors did not show any improvement in core symptoms of autism or a broad range of associated developmental and behavioral difficulties. They only found a favorable change in functional communication reported by teachers in children with autism who received DHA supplementation but further investigations are required.n = 7)  or placebo (n = 6) in 13 participants in the age range 6–28 years who had autistic disorder. The results suggest that supplementation with larger ARA doses added to DHA improves impaired social interaction in individuals with ASD.The third study  is a 16-The treatment effect sizes for ABC social withdrawal (treatment group: 0.88 vs. placebo: 0.54) and Social Responsiveness Scale (SRS) communication (treatment group: 0.87 vs. placebo: 0.44) subscales were more favorable for the treatment group than for the placebo group.In conclusion, these findings reported a small but not significant benefit of ω-3 PUFAs supplementation in children with ASD. Data in this field are few and the sample size is often too limited. This is in agreement with recent systematic reviews and meta-analysis ,74 concln = 17) employed ω-3 PUFAs as monotherapy, whereas eight studies used ω-3 PUFAs as an adjunctive therapy to methylphenidate (MPH) or atomoxetine (ATMX). Sample age ranged from 4 [The association between ADHD symptoms and low blood levels of ω-3 PUFAs represents a consistent finding among observational studies. Driven by this evidence, several intervention studies have been carried out in the last 15 years to evaluate possible beneficial effects of ω-3 PUFAs in the treatment of behavioral and cognitive symptoms of children with ADHD. Our aim was to review current evidence from RCTs investigating the efficacy of ω-3 PUFAs supplementation on ADHD symptomatology. The main characteristics of the 25 RCTs on ADHD included in this review are shown in d from 4  to 18 [7d from 4  years. Ad from 4 ,77, EPA d from 4 ,85,86,87d from 4 ,92,93,94d from 4 ,96. Two d from 4  or in cod from 4 , withoutTwo RCTs were performed supplementing children with ADHD with either DHA or EPA alone, as add-on therapy. The first study was carried out by Voigt et al. , in whicWith regard to RCTs exploring the effect of combined EPA and DHA at different dose levels, 11 studies have been identified. Among them, six reported some improvement in ADHD symptoms, whereas the other five studies did not find any significant ameliorating effect.In a recent RCT , 50 chiln = 25) higher doses of DHA than EPA  with the addition of AA (40 mg) and GLA (96 mg) compared with a placebo (n = 25). For attention problems rated by teachers and for conduct problems rated by parents, PUFA showed a small but significant effect over placebo whereas no treatment effect was found on neuropsychological measures . Hariri et al. [Focusing on the six trials of DHA + EPA supplementation reporting improvement on ADHD symptoms, they all choose a minimum duration of 12 weeks and a minimum sample size of 40. Recently, Bos et al.  found a i et al. , in a sai et al.  randomizTwo recent studies ,88 testeAs mentioned above, two RCTs have supplemented with ω-3 PUFAs alone  or in coFinally, Raz et al.  and DubnThe aim of this review was to provide a comprehensive overview of the effects of ω-3 PUFAs in three major neuropsychiatric disorders: psychosis, ASD, and ADHD . The intDespite these limitations, overall, the results seem to highlight the beneficial role of ω-3 PUFAs in the three neuropsychiatric disorders described above. Specifically, for psychotic patients, it has been reported that ω-3 PUFAs supplementation could be effective in preventing transition to psychosis and in the treatment of severity symptoms and global functioning.Furthermore, the available evidence also suggests that the detection and treatment of ω-3 PUFAs deficiency early in the course of illness may be required to exert the greatest protection against transition to psychosis and severity of symptoms. However, this hypothesis requires future investigations.With regard to ADHD, the effect of ω-3 PUFAs supplementation has been widely studied in this disorder via RCTs. However, also in this case, the great methodological heterogeneity across studies, including variations in sample size, study duration, type and dosage of supplementation, makes difficult to compare the findings and draw firm conclusions about the efficacy. We found 13 out of 25 studies reporting some beneficial effect of ω-3 PUFAs on ADHD symptoms, whereas the other 12 found negative results. A common characteristic shared by RCTs reporting positive outcomes is that they all have—in tandem or alone—a minimum sample size of 50 and minimum study duration of 15 weeks. In terms of supplementation, they involve both EPA and DHA, except for two studies whose ω-3 PUFAs composition is not declared. Studies that add GLA to EPA and DHA were more likely to obtain positive than negative outcomes. On the other hand, looking at studies reporting negative outcomes, they follow a different methodology compared to positive studies, including the use of small sample sizes, short study duration (less than 15 weeks), supplementations with either DHA or EPA alone, the lack of a placebo arm. An exception is represented by Milte and coworkers’ study , which hMoreover, considering the eight studies exploring the effect of ω-3 PUFAs as an add-on therapy to MPH or ATX, six failed to find a better outcome for combined treatment versus pharmacotherapy alone, whereas only two observed a greater improvement in the combined treatment group. However, as described above, negative studies—more than positive ones—have several weaknesses that could have affected the results so that it is still premature to draw conclusions about the appropriateness of combined treatment for ADHD. Interestingly, Barragán et al. , despiteWhat has frequently emerged from recent meta-analyses ,108,109 Finally, regarding ω-3 PUFAs and ASD, the limited evidence available is insufficient for drawing any conclusion. The trials included in this review varied in their durations, sample size and amounts of ω-3 PUFAs supplementation, therefore there is still uncertainty about the effects of these fatty acids on symptoms of ASD in children. In particular the three RCTs included have different duration , while ω-3 PUFAs erythrocyte membranes may reach a steady state after six months and at least four months is needed to demonstrate an effect on cognitive performance. Even longer study periods of one year might be needed to demonstrate behavioral changes in response to ω-3 PUFAs supplementation .Given the importance of DHA in brain function and development, and its possible implications in the modulation of ASD symptoms, it is important to continue to investigate the positive effects of the supplementation. In this population, the dietary intake of ω-3 PUFAs rich foods is low due to a monotonous dietary pattern: the incorporation of DHA into cellular membranes may be therefore insufficient.In conclusion, the lack of consistency across studies that have explored the ω-3 PUFAs effects in these major neurodevelopmental disorders implies the necessity of larger prospective interventional clinical studies, with intervention starting at the beginning of illness, utilizing therapeutic dosage of ω-3 PUFAs, and new methodologies of investigation. Despite all the uncertainties that have been mentioned, we do believe that this is an exciting area for future scientific studies since it will help elucidate the critical role played by ω-3 PUFAs in human brain development with wide-reaching implications in health and disease.A comprehensive search on PUBMED of all RCTs using ω-3 PUFAs on patients with autism, ADHD and psychotic symptoms published up to August 2017 was performed. Articles of potential interest were identified by using the following search terms: “omega-3“, ”polyunsaturated fatty acids”, “PUFAs”, “trial”, “EPA”, “DHA”, “docosahexaenoic acids”, “eicosapentaenoic acids” combined with the following term: “autism”, “neurodevelopmental spectrum disorder”, “attention deficit hyperactivity disorder”, “adhd”, “psychosis”, “psychotic disorder” or “psychotic symptom” or “first psychotic episode”, “ultrarisk psychosis”, “risk psychosis”. In this review, RCTs examining the efficacy of ω-3 PUFAs in young adults, adolescents and children with autism, ADHD and psychotic symptoms were selected. Trials were included if they examined the efficacy of ω-3 PUFAs to target autism, ADHD and psychotic symptoms as a primary outcome and in case they investigated the efficacy of ω-3 PUFAs in transition to psychosis status in the context of subjects with risk or ultra-risk for psychotic disorder. We included also subjects at risk for ADHD if the authors used validated rating scales to measure the presence and severity of ADHD symptoms as a primary outcome. We considered only trials in which the authors used an exposure of ω-3 PUFAs as a unique treatment or as an adjunctive therapy to other drugs , or other no pharmacological strategies such as psychotherapy, vitamin and mineral supplements compared to placebo or pharmacotherapy alone.To limit the heterogeneity of this review and to reduce selection biases, we decided to exclude: trials examining the efficacy of ω-3 PUFAs in treating psychotic symptoms in subjects with diagnosis of chronic schizophrenia; trials examining the efficacy of ω-3 PUFAs in treating ADHD symptoms in subjects with diagnoses different from ADHD ; trials involving healthy subjects; trials analyzing levels of ω-3 PUFAs; studies that not explore the effects of ω-3 PUFAs on autism, ADHD and psychotic symptoms as primary outcome. In addition, we excluded trials that employed diet enriched of ω-3 PUFAs as a supplementation. Among the 384 articles retrieved, 116 RCT studies were identified and screened by reading the abstract and, when necessary, the full text, in order to select those articles relevant for the analysis. A manual search of bibliographic cross-referencing complemented the search. Reference lists of relevant papers were also inspected to identify any additional trials. Relevant articles were obtained and included in the review if they used an exposure of ω-3 PUFAs, included autism, ADHD and psychotic symptoms as an outcome measure, enrolled human participants, included a comparison group, and reported a trial. The process of identification and inclusion of trials is summarized in


Children with attention deficit hyperactivity disorder (ADHD) often fail to comply with teacher instructions in the classroom. Using action during presentation or recall can enhance typically developing children’s abilities to complete multi-step instruction sequences. In this study, we tested the ability to following instructions in children with ADHD under different conditions to explore whether they show the same beneficial effects of action. A total of 24 children with ADHD and 27 typically developing children either listened to or viewed demonstrations of instructions during encoding, and then either verbally repeated or physically performed the sequences during recall. This resulted in four conditions: spoken-verbal, spoken-enacted, demonstration-verbal, and demonstration-enacted. Children with ADHD were significantly impaired in all conditions of the following instructions task relative to the typically developing group. Both groups showed an enacted-recall advantage, with superior recall by physical performance than oral repetition. Both groups also benefitted from demonstration over spoken presentation, but only when the instructions were recalled verbally. These findings suggest that children with ADHD struggle to complete multi-step instructions, but that they benefit from action-based presentation and recall in the same way as typically developing children. These findings have important implications for educators, suggesting that motor-based methods of instruction-delivery might enhance classroom learning both for children with and without developmental disorders. Attention deficit hyperactivity disorder (ADHD) is a common developmental disorder associated with elevated symptoms of hyperactivity/impulsivity and inattention. Symptoms typically emerge in childhood and continue into adolescence and adulthood . The ecoThe ability to complete complex multi-step sequences of instructions is important for many everyday tasks ranging from following parent or teacher instructions to guide learning and development in childhood through to understanding how to use new systems in the workplace in adulthood. Little is currently known about the cognitive and neural systems underpinning this fundamental skill, but it likely draws on a variety of higher-order cognitive control functions that allow us to remember what has to be done , attend to the task at hand , make plans to sequential actions , inhibit the tendency to execute the current action immediately , and switch flexibly between different steps to reach an end goal . Although there have been no direct investigations into the relationship between other executive function skills and FI abilities, greater problems in daily activities relying on FI are reported in populations with poor executive control  . NeuroimIn addition, recent research suggests that working memory, the cognitive system responsible for the temporary maintenance and processing of information e.g., , might sTouch the white bag and then pick up the yellow ruler), often involving action-based processing at either encoding or retrieval stage enhanced the performance. Action-related benefits at encoding emerge when participants are asked to perform instructions themselves during spoken presentation  to provide the first direct assessment of FI skills in children with ADHD relative to a typically developing group and (ii) to investigate whether action during the presentation of the instructions in the form of on-screen demonstration, or physical action during recall, could enhance performance in both groups. We used a paradigm based on that reported by We predicted that FI would be impaired in the ADHD group relative to the control group across all four conditions of the FI task for several reasons. First, deficits in working memory are a core feature of the disorder  and typiDue to both the heterogeneity in cognitive problems associated with ADHD and the complex nature of FI no specific predictions were made regarding differences in the magnitude of impairments across FI conditions for the ADHD group. Different conditions might be expected to draw on different cognitive processes. For example, the spoken and verbal conditions might rely more heavily on language skills than the action-based conditions, which may in turn draw more on visuospatial resources, motor control, and the ability to construct motor representations. The language problems commonly reported in ADHD  might beSecond, we predicted improved memory accuracy following demonstrated encoding and using enacted recall for both ADHD and typically developing children. For typically developing children, this prediction was based on previous observations . How migChildren diagnosed with ADHD were recruited from a local hospital in Beijing. The inclusion criteria were: (1) diagnosed with ADHD according to DSM-IV criteria  by pediaSD = 1.44, age ranged from 6.60 to 11.00 years) were recruited. Of the 24 children with ADHD, 10 were diagnosed with the inattentive subtype, 12 with the combined subtype, and two with the hyperactive/impulsive subtype. At the time of testing, 18 out of 24 children were taking medication for their ADHD symptoms. Eleven children were taking Methylphenidate Hydrochloride Prolonged-Release tablets . Seven children were taking atomoxetine hydrochloride Capsules . Those who were medicated continued to take their medication throughout the study.A total of 24 ADHD children  were recruited from local communities in Beijing and Weifang, China. None had an ADHD diagnosis. The mean IQ was 106.04 (9.59) for the ADHD group and 109.78 (10.62) for the typically developing group. Standard and Bayesian t-tests (t(49) = -0.47, p = 0.640, Bayes Factor (BF) = 0.31), gender (χ(1)2 = 0.30, p = 0.585, BF = 0.32) or IQ (t(48) = -1.30, p = 0.201, BF = 0.57).Twenty-seven typically developing children , Walk Don’t Walk, and the FI span task. The FI tasks were always administered last, but the sequence of conditions was counterbalanced across children using a Latin square design.A 2 × 2 × 2 mixed design was used. The within-subjects factors were presentation (spoken vs. demonstrated instructions) and recall type . The four conditions are spoken-verbal, spoken-enacted, demonstration-verbal, and demonstration-enacted. The between-subjects factor was group . The order of the four within-subject conditions was counterbalanced between the participants, and the same counterbalanced order was implemented for the two groups.Two tasks were administered from the Chinese version of the Test of Everyday Attention for Children .This task tapped a child’s ability to sustain attention and inhibit a prepotent response. The child is given a sheet showing paths made up of footprints and has to dot the next footprint on the path with a marker pen when they hear a frequently occurring “go” sound. The child is instructed not to dot the next footprint when an occasional “no go” sound is played. There were 20 trials, resulting in a score ranging from 0 to 20.This task measures attentional control and response inhibition. The child is shown an array of 24 randomly arranged digits (either digit 1 or 2) on a sheet. In a “same world” trial, the child names the digits as quickly as possible. In an “opposite world” trial, he/she names the alternate digit to the one that is visually presented . If a child makes an error, he/she is required to correct it. The extra time cost of the correction is taken into account. The average time (in ms) to complete the same and opposite world trials was scored.r = 0.95).IQ scores for the ADHD group were provided by the hospital using the Chinese version of the full Wechsler Intelligence Scale for Children , which wThe home version of the Chinese ADHD Rating Scale–IV (ADHD RS-IV) was used to evaluate children’s inattention, hyperactivity and impulsive behaviors . The scaspin the green eraser), the second block contained two actions , and so forth. Four sets of instructional lists were constructed (one for each condition).This task was adapted from a previous study with young adult participants . A typicSpoken instructions were recorded by a Native Chinese female speaker at a moderate speed of approximately 350 ms per word. Demonstration of instructions involved use of video clips showing a series of hand movements upon objects. In both the spoken and demonstration conditions, the durations for the presentation of sequences of 1–6 actions were 3, 5, 8, 11, 13, and 16 s, respectively.Figure 1). The experimenter sat at another desk away from the child and controlled the delivery of instructions. The experimenter first introduced the task, followed by a practice of object naming and operation to ensure that the child understood the task requirements. Children were told not to repeat the instructions aloud, touch, operate or move the objects during encoding. In a typical trial of the spoken instruction, the experimenter first signaled the child to get ready, and then played the instructions through speakers. In a trial of the demonstration condition, children viewed silent video clips of actions. In all conditions, a blank screen would appear at the end of the trial, indicating the recall phase. Children then either repeated the instructions  or performed the actions . Children started from one-action instruction and progressed to the next span if they correctly recalled four out of six trials at a given sequence length. Performance on these tasks was measured in terms of action scores, with a score recorded as correct when the movement, color and object of an action “chunk” were recalled in the correct serial position (range 0–126).Each child completed all four conditions. In each condition, a child sat at a desk facing the stationary objects and a computer monitor for displaying instructions  was 8.83 (5.15) for the unmedicated ADHD group, and 9.56 (4.51) for the medicated group, t(22) = -0.33, p = 0.746, Cohen’s d = 0.16; Opposite Worlds, Means (SD) was 34.63 (15.01) for the unmedicated ADHD group, and 35.18 (6.80) for the medicated ADHD group, t(22) = -0.13, p = 0.902, Cohen’s d = 0.06]. Bayesian t-tests favored the absence of group differences on these measures .Descriptive statistics and group comparisons are reported in Table 2. The ADHD group were rated as significantly more inattentive and hyperactive/impulsive than the typically developing group, with higher overall scores that were indicative of a greater number of ADHD symptoms.The behavior rating scale data is presented in Figure 2.There were no significant differences in performance on any of the FI tasks between the ADHD subtypes (inattentive vs. combined), or between those with ADHD who were medicated and those who were unmedicated . The data were therefore collapsed into a single ADHD group in all subsequent analyses. Descriptive statistics and group comparisons in action scores for all conditions of the FI span task are presented in t-tests comparing the typically developing and ADHD group in each FI condition. The ANOVA test indicated a significant main effect of group, with the ADHD group showing reduced recall performance compared to the typically developing group  = 16.72, p < 0.001, t-tests revealed significant deficits in each FI condition  = 2.04, p = 0.047, Cohen’s d = 0.58; spoken presentation/enacted recall, t(49) = 4.26, p < 0.001, Cohen’s d = 1.22; demonstration presentation/verbal recall, t(49) = 3.49, p = 0.001, Cohen’s d = 0.99; demonstration presentation/enacted recall, t(49) = 2.58, p = 0.013, Cohen’s d = 0.74).To investigate whether there were group differences in the impact of action at presentation or recall, a 2 × 2 × 2 mixed ANOVA was run with presentation condition  and recall modality  as within-subjects factors and group  as a between-subjects factor. This was followed by F = 44.98, p < 0.001, F = 1.58, p = 0.215, F = 13.77, p = 0.001, t-tests revealed an advantage for demonstration over spoken presentation when the instructions were recalled verbally (t(50) = 3.81, p < 0.001, Cohen’s d = 0.57), but not when they were enacted at recall (t(50) = -1.36, p = 0.179, Cohen’s d = 0.19). The benefits of enactment at recall were present for both spoken (t(50) = 8.18, p < 0.001, Cohen’s d = 1.19), and demonstrated instruction sequences (t(50) = 2.30, p = 0.025, Cohen’s d = 0.32), with substantially larger effect sizes for spoken instructions. There was no significant interaction between group and presentation type  = 0.29, p = 0.596, F = 2.14, p = 0.150, F = 2.23, p = 0.142, In terms of action-based advantages, the mixed ANOVA showed a significant main effect of recall type, with superior recall by enactment than oral repetition  included two main effects  and the interaction between presentation and recall. Inclusion of effects of recall (BF > 1000) and group (BF = 136) were strongly favored, as was the interaction between presentation and recall (BF = 41). The analysis did not support the inclusion of the presentation factor (BF = 0.31), or the interactions between presentation and group (BF = 0.26), recall and group (BF = 0.52), or the three-way interaction (BF = 0.56). Bayesian t-tests indicated evidence for differences between typically developing and ADHD groups in each condition . These outcomes are therefore in line with those obtained using the null hypothesis testing analysis of variance.In addition to the traditional frequentist analysis above, a 2 × 2 × 2 mixed Bayesian ANOVA was also carried out , in order to assess the strength of evidence for each main effect and interaction. The best model (This study investigated FI in children with ADHD and explored whether action-based presentation and recall improved performance equally in typically developing children and those with ADHD. The ADHD group were impaired in FI compared to the typically developing group irrespective of the mode of presentation or recall. They did, however, display similar patterns of action-related benefits as the typically developing group. Both groups showed an enacted-recall advantage, with superior recall of instructions by enactment than oral repetition. There were also benefits of demonstration at presentation over spoken presentation, but only when recall was verbal.Overall, and in line with our prediction, children with ADHD were impaired in all conditions of the FI paradigm. As the FI task involves multiple modalities and recruits working memory resources , 2016, tAn advantage was found for both groups for instructions that were enacted at recall. This is consistent with previous literature showing robust benefits of action at recall following the spoken presentation of instructions , 2016. IImportantly, both the typically developing and ADHD groups showed equivalent performance benefits as a result of demonstration and enacted recall. Particular deficits in ADHD for both visuospatial working memory e.g.,  and motoThe ADHD children were a convenience sample, which does introduce certain limitations. First, the majority of the ADHD sample were on medication during testing. However, it should be noted that there were no differences in attention between those who were medicated and those who were not. To exclude the influence of medication, future work should replicate and extend this study with unmedicated samples or prohibit the ADHD sample from taking medication with sufficient time prior to testing for medication effects to wash out. A second limitation is that the ADHD group consisted of children with both combined and inattentive subtypes. Although there were no differences in performance between the inattentive and combined subtypes, the sample sizes were relatively small. The conclusions drawn here are therefore preliminary and necessitate further exploration. Finally, a third limitation is that we did not exclude children with comorbid disorders, such as dyslexia and language impairment. Language problems are often comorbid with ADHD , with coThis study has important practical implications concerning the ability to follow instructions in different developmental groups. The classroom is a predominantly verbal environment, which places heavy demands on children to retain spoken or written instructions either overtly or sub-vocally. The current data suggest that teacher demonstration may improve the retention of important information both for children with and without developmental difficulties. The benefits observed in both groups when they knew they had to act out the instruction sequences suggests that telling children to plan for action could also enhance the encoding, retention and successful implementation of classroom instructions. To our knowledge, this is the first study to directly assess FI skills in children with ADHD and show they have substantial impairments. This provides a possible target for training and intervention. Future work should continue to explore how to optimize the demonstration methodology in practical contexts.Experimental procedures were approved by the Institutional Review Board of the Institute of Psychology, Chinese Academy of Sciences and the Peking University Sixth Hospital. The experiment was carried out in accordance with the approved guidelines. Informed consent was obtained from parents/carers at the start of the testing. During the stage of data analyses and data archive, demographic and clinical information was kept confidential.TY generated the idea, designed the study, analyzed the data, and wrote the paper. RA interpreted the data and wrote the paper. JH contributed significantly to the interpretation of the findings and writing of the paper. RC contributed to the design of the study and interpretation of the findings. All authors read and commented the final version of the paper.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.The reviewer KH and the handling Editor declared their shared affiliation, and the handling Editor states that the process nevertheless met the standards of a fair and objective review.


Measurement invariance was investigated through Confirmatory Factor Analysis and Multiple Indicators Multiple Causes models. Measurement invariance was attested in both methods, demonstrating the direct comparability of the groups. Children with ADHD were 0.51 SD lower in word recognition and 0.33 SD lower in spelling tests than controls. Results suggest that differences in performance on word recognition and spelling tests are related to true mean differences based on ADHD diagnostic status. Implications for clinical practice and research are discussed.Although studies have consistently demonstrated that children with attention-deficit/hyperactivity disorder (ADHD) perform significantly lower than controls on word recognition and spelling tests, such studies rely on the assumption that those groups are comparable in these measures. This study investigates comparability of word recognition and spelling tests based on diagnostic status for ADHD through measurement invariance methods. The participants ( Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition encompassing symptoms of inattention, hyperactivity, and impulsivity that interfere with a person’s daily functioning DSM-5; . The worThere is a clear association between ADHD and learning disabilities, with comorbidity rates ranging from 31 to 45% e.g., . Moreovet-test or analyses of variance procedures , and between which the test maybe compared statistically. Demonstrating this property, measurement invariance, is a prerequisite for valid comparisons between groups , for exaocedures .Word recognition and spelling under dictation are cognitive abilities related to the acquisition of mental representations of words, which depends heavily on phonological and orthographic skills . While rTwo methods are frequently used for accessing measurement invariance, namely, Multigroup Confirmatory Factor Analysis (MGCFA) and Multiple Indicators Multiple Causes (MIMIC) modeling . In the The MIMIC modeling uses a unique matrix of data  and characteristics of the subpopulations  are regressed on the items that comprise the scale. If the subpopulation characteristic produces an effect on the individual items of the scale, it is an evidence of measurement non-invariance. Therefore, the items affected by the subpopulation characteristic are assumed to be affected by differential item functioning (DIF) and should be revised for diagnostic purposes because the items work differently in different subpopulations confounding the estimates generated by the scale. In other words, demonstrating DIF in a task implies that a given item could be easier (or more difficult) for a person based on his or her diagnostic category, regardless of his or her latent trait or actual ability.Measurement invariance has been a topic of interest in clinical ADHD studies; however, most of those studies explored the underlying construct of ADHD across various subgroups defined by demographics, for example, based on gender, age, or different raters . In geneTo our knowledge, no study has examined the possibility of measurement invariance for measures of word recognition and spelling between the subpopulations of children with and without ADHD. This question is essential to establish direct comparability of those subpopulations, and it is the main objective of the present study. The comparability of groups in a certain psychological trait should not be assumed; instead, it must be empirically demonstrated. The question addressed in the present study is relevant regarding the validity of word recognition and spelling measures and the use of these measures to compare populations of children with and without ADHD. This study will determine if the items composing word recognition and spelling single words tests measure the same underlying constructs , and if these constructs exhibit similar relationships  in the groups of children with and without a diagnosis of ADHD. Furthermore, we investigate if there is a significant direct effect of an ADHD diagnosis on the items that compose the reading and spelling tests, to determine if the items function differently between subgroups. We hypothesize that ADHD will not interfere with the constructs of word recognition and spelling and that the items will function comparably between the tasks, because the constructs underlying these abilities are tied to phonological representations of the words, rather than to domains of function  affected in ADHD.n = 2,371) and random  sample groups. The selection for the high-risk group was based on a risk prioritization procedure to identify individuals with current symptoms and/or a family history in five target disorders . Therefore, this procedure do not produce a diagnosis for these disorders, but create an index for screening possible risk for such target disorders. For example, for learning disorders screening, there were only two questions: “in childhood, somebody in your family presented difficulties with reading, writing, or math?” and “in the childhood, somebody in your family presented difficult for speaking or understanding what is said?” Based on this screening procedure, we lost 817 participants of the high-risk sample and 542 children from the random sample due withdrawal of participation, changing address, lost contact, and other reasons. Therefore, 1,554 children with high-risk for mental disorders and 958 children from the random sample were selected for further individual evaluation . From this sample, we excluded those who did not complete all tasks, resting 2,401 children. For the purpose of the present study, we excluded the children with low intelligence quotient (IQ < 70), and those not yet instructed in reading and spelling . The final sample was therefore composed of 1,935 participants from 58 schools .This study makes use of data from the baseline wave of a large longitudinal community school-based study from Brazil from which detailed methodological description is available . The samIQ was estimated from scores on Vocabulary and Block Design subtests of the Wechsler Intelligence Scale for Children (WISC-III), using n = 1,935). DAWBA presents good evidence of validity and reliability  responded to the DAWBA for psychiatric diagnosis of the children. All procedures followed standard instructions in the manuals (see section “Measures”).The research received approval from the Ethical Committee of the Federal University of São Paulo (protocol no. 1.327.777/15). The parents or legal guardians of all non-adult participants provided written informed consent prior to participation of their children, as well as written informed consent for their own participation. The children, in turn, gave their verbal assent to the evaluators.Measurement invariance was tested using two procedures: MGCFA and MIMIC models. In both cases, the models were estimated with Mplus 7.0  using a d was used to estimate the effect size in the difference between reading and spelling abilities between children with and without ADHD.For the CFA models, grouping was based on ADHD diagnostic status (ADHD vs. controls). To avoid bias due to sample selection , weights were created to counterbalance bias selection as described in detail elsewhere . Additioa) and difficulty  parameters in both groups, it is likely to obtain bivariate empty cells.After proving evidence regarding the unidimensional fit of the word recognition and spelling tasks , a sequential strategy for testing measurement invariance was performed, following Empty cells generate statistically perfect correlations between two items, meaning that they are not statistically distinguishable and, for purpose of the analysis, one or both should be removed. This problem is most common when variables have extreme cuts like (95% of children had correct answer for a given item against 5% who did not). Hence, where empty cells appeared, we excluded one of the items to maintain the maximum as possible number of original items for both reading and spelling tasks.2), the 90% CI of the root mean square error of approximation (RMSEA), the comparative fit index (CFI), and the Tucker-Lewis Index (TLI). To interpret these indices, we follow the recommendations of p > 0.05 for the χ2, RMSEA ≤ 0.06, CFI ≥ 0.95, and TLI ≥ 0.95. It was then tested if the item thresholds and factor loadings were equivalent between groups .First, it was tested if the factor structure was the same between groups . For model fit and adjustment index, we report the chi-squared statistic  did not worsen the model as compared to the least constrained model wherein the parameter was freely estimated . Becausehan 0.01 , and if Figure 1: the IQ and a single dichotomous indicator of general psychopathology, which, via DAWBA, assess if the children endorse at least one positive item for the five domains of evaluated psychopathology (see section “Participants”), called here “any symptom of mental disorder.” As described in Two different MIMIC models were conducted for word recognition and spelling measurement models: one using ADHD diagnostic (dichotomous variable status) and another incorporating ADHD symptoms as a continuous variable. Because MIMIC models do not split the sample (based on group comparisons), using a single covariance matrix, it does not require a large sample size compared to multiple-groups CFA . MIMIC iTable 1 presents the descriptive statistics for the study participants . The ADHD and control groups did not differ by age . Nevertheless, the ADHD group presented significantly lower estimated IQ  and more males , what agrees with previous results from the literature  model. Two items were excluded when testing the reading unidimensional model due to bivariate empty cells. The spelling model was admissible with all items included.re e.g., . Table 2SD = 1.40; minimum = 1.25; maximum = 7.38) and mean item difficulty was -0.87 . For the spelling initial model, mean item discrimination was 1.47  and mean item difficult was -0.15 .For the initial measurement invariance models, both the reading and spelling models showed good fit indices for a unidimensional solution. For the initial reading model, mean item discrimination was 2.76 . Table 3). Scalar against configural invariance was achieved for both reading and spelling tasks . For both models, ΔCFI was 0.000. Since scalar invariance was achieved, the mean in the latent traits can be compared in both groups. In the MGCFA models, word recognition and spelling abilities were poorer in children with ADHD as compared to children without, with a moderate effect size in the word recognition task  and small effect size in the spelling task .As the configural model produced good fit index for both tasks, we investigated scalar invariance by holding the items’ factor loadings and thresholds  equal between the groups. For the word recognition and the spelling tasks, all items proved to be invariant  and the spelling tasks (b). Table 4 presents model fit index for the MIMIC analysis. Regardless if ADHD was measured as continuous or dichotomous covariate, the four MIMIC models showed excellent fit index. The MIMIC analysis confirmed the absence of DIF for all items in both tasks regardless of the ADHD diagnostic status or inattention and hyperactivity impulsivity scores, IQ, and the presence of any symptom of mental disorder. Regarding population heterogeneity, ADHD as continuous variable predicted poorer word recognition  and spelling  latent traits. IQ predicted positively word recognition and spelling . In the MIMIC models, an ADHD diagnosis was associated with poorer word recognition  and spelling  abilities. Lack of evidences were found for population heterogeneity in relation to the presence of any symptom of mental disorder for both word recognition  and spelling  tests.Figure 1), no evidence of DIF was found based on ADHD diagnostic status or ADHD symptoms (as a continuous variable representing). This last result was obtained even after controlling for IQ and the presence of any symptom of mental disorder. The results indicate that word recognition and spelling scores can be compared between children with and without ADHD, regardless of the severity of inattention and hyperactivity-impulsivity domain symptoms. In addition, it provides support that lower performance in word recognition and spelling in children with ADHD, when compared to children without ADHD, are not due to measurement problems.The present study investigated measurement invariance in word recognition and spelling measures  for groups of children with and without ADHD in a sample of school-aged children. To our knowledge, this is the first study to evaluate measurement invariance for word recognition and spelling latent traits considering the ADHD diagnostic status as subpopulations in a large community based sample. Two structural equation modeling techniques were used to investigate and confirm the results. In multigroup CFA, properties of configural, scalar, and scalar against structural invariance were demonstrated for both word recognition and spelling tests. In MIMIC models  and dimensional inattention and hyperactivity-impulsivity scores. These results confirm that children with different levels of ADHD symptoms or those reaching a threshold to be diagnosed with ADHD vs. those without a diagnosis, have equal probabilities to endorse correctly the items in the word recognition and spelling tasks.per se where the sample is split and the correlation matrix, per group, is estimated. The other adopted measurement invariance technique, MIMIC, allowed us to verify issues related to DIF, and because MIMIC is not so restrictive  regarding the process involving to invariance testing, we observed that in terms of difficulty, none of the items showed DIF.Demonstrating measurement invariance between groups in a measure is important to avoid bias that could invalidate comparisons between these groups. When equivalence is not attested, subjects with the same level of competence (ability or latent trait) can attain different scores in the measure, leading to erroneous conclusions about means differences. As states The results for both CFA and MIMIC models confirmed measurement invariance and, therefore, the direct comparability of the groups in such tasks. Nevertheless, some limitations of the study should be acknowledged. First, diagnostic status for ADHD was assessed based only in a structured interview  administered to biological parents, as opposed to psychiatric assessments of the children directly or by including evaluations by teachers. Second, although weights were used to minimize selection bias in the high-risk study, the data from this community sample may not generalize to predominantly clinical populations. Third, despite we demonstrated measurement invariance above and beyond the influence of IQ and the presence of any symptoms of mental disorders, we still have to demonstrate that the presence of learning disorders will not affect the results. Finally, the extent that our results are limited to word recognition and spelling single words, or are applicable to other related abilities, as reading comprehension and expressive writing , remains to be demonstrated e.g., .The results of this study suggest that the domains of function affected in ADHD do not alter the constructs of word recognition and spelling abilities, which are tied to the processing of phonological and orthographic representations. ADHD symptoms do not change the probability to correctly endorse items in the used tests and children with ADHD do not consider the word recognition and spelling items more difficult than children without ADHD given a comparable amount of latent word recognition and spelling ability. On the other hand, children with ADHD have lower mean performance, demonstrated by the contrast on both trait levels. Therefore, ADHD symptoms  may lead to poorer word recognition and spelling achievement, but this is not due to changes in how the construct is being measured. For clinical practice, it means that specific norms for scoring word recognition and spelling tasks are not recommended for children with ADHD because they are directly comparable to children without ADHD. Implications for education of children with ADHD may indicate that teaching practices should involve more the management of the ADHD symptoms  than specificities in the teaching procedures itself . Given that the direct effect of ADHD on reading/spelling skills is not biased due to DIF, although these traits are highly correlated, it is suggested that identifying the neuropsychological deficits common to children with reading/spelling difficulties and ADHD might clarify the nature of high co-prevalence of these disorders e.g., .∗ of PL, who conceived the research question, analyzed and interpreted the data, and drafted and reviewed the manuscript considering coauthors directions. HC-M was the advisor and contributed with the analysis and interpretation of the data, and with theoretical and methodological insights. GS, JM, RB, and LR conceived, planned, and carried out the “High risk cohort study,” from which this research is part. The authors contributed with insights in the manuscript’s writing on the topic of ADHD and its relation to Reading/spelling disability and critically revised de manuscript. WS helped with analysis and interpretation of the data and revised the manuscript in terms of content and grammar. PP and AG participated of data collection, training the psychiatrists and the lay-interviewers of the study. They critically revised the article and provided important insights to data interpretation. All the authors declare agreement with the submitted version of the manuscript and ensure that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. ∗The dissertation represents the only medium it has appeared in, is in line with the author’s university policy, and cannot be accessed online.The research is part of the doctoral dissertationRB has received research grants from AstraZeneca, Janssen Cilag, Novartis, Roche and the governmental funding agencies: CAPES, CNPq, and FAPESP; has been a forum consultant for Eli Lilly, Janssen, Novartis, and Roche; and has participated in speaker bureaus for Ache, Janssen, Lundbeck and Novartis, in the last 5 years. Dr. Nuechterlein is a non-compensated officer of MATRICS Assessment, Inc., he has received unrelated research support from Janssen Scientific Affairs, Genentech, and Posit Science, Inc., and he has consulted to Genentech, Otsuka, Janssen, and Takeda. LR was in the speakers’ bureau, and acted as a consultant for Eli-Lilly, Janssen-Cilag, Novartis, and Shire in the last 3 years. He receives authorship royalties from Oxford Press and ArtMed. He also received travel award (air tickets + hotel) for taking part in two child psychiatric meetings from Novartis and Janssen-Cilag in 2010. The ADHD and Juvenile Bipolar Disorder Outpatient Programs chaired by him received unrestricted educational and research support from the following pharmaceutical companies in the last 3 years: Abbott, Eli-Lilly, Janssen-Cilag, Novartis, and Shire. The other authors report no conflicts of interest to disclose.


Objective: The aim of this study was to identify any potential genetic overlap between attention deficit hyperactivity disorder (ADHD) and obsessive compulsive disorder (OCD). We hypothesized that since these disorders share a sub-phenotype, they may share common risk alleles. In this manuscript, we report the overlap found between these two disorders.Methods: A meta-analysis was conducted between ADHD and OCD, and polygenic risk scores (PRS) were calculated for both disorders. In addition, a protein-protein analysis was completed in order to examine the interactions between proteins; p-values for the protein-protein interaction analysis was calculated using permutation.Conclusion: None of the single nucleotide polymorphisms (SNPs) reached genome wide significance and there was little evidence of genetic overlap between ADHD and OCD. Attention deficit hyperactivity disorder (ADHD) and obsessive compulsive disorder (OCD) are two neurodevelopmental disorders with their onset in childhood. They are two of the most common psychiatric disorders found in pediatric populations. Approximately 5% of the population worldwide has ADHD . This also justified our efforts to conduct an analysis between ADHD and OCD, which to our knowledge had not been previously studied, as the Davis et al.  data. Davis et al.  conductes et al.  study usN = 3351) and OCD (N = 5415) samples. The ADHD sample contained 2064 trios, 896 cases, and 2455 controls. The OCD sample consisted of 2998 individuals from nuclear families. Further, the meta-analysis results are examined for the enrichment of functional single nucleotide polymorphisms (SNPs) that were previously associated with gene expression levels. Additionally, polygenic risk score (PRS) analyses were completed to test the hypothesis that multiple genes of small effect jointly contribute to the susceptibility of ADHD and OCD. PRS analyses were also conducted to investigate the genetic relationship between these two disorders. Furthermore, an additional analysis was conducted to examine protein-protein interactions to examine potential common pathways between proteins. Lastly, an expression quantitative trait locus (eQTL) analysis was carried out to identify non-randomly occurring genes that are associated with the prefrontal cortex region. We used the nominated genes generated by two additional approaches: eQTL and Disease Association Protein-Protein Link Evaluator (DAPPLE)To achieve our research goal, we performed a meta-analysis between the ADHD , 155 pedigrees (a proband and unaffected sibling), and 450 families with a complex family structure. An additional 192 probands that lacked another family member in the study (singletons) were included in the sample as well. The genotyping was performed at the Johns Hopkins SNP Center using Illumina’s HumanOmniExpress bead chips.The Gene Environment Association Studies (GENEVA) seek to identify genetic factors that may play a part in addiction, in the form of a large genome-wide association study. The subjects are DSM-IV alcohol dependent as well as illicit drug dependent cases and controls. The controls are non-dependent and unrelated subjects of European and African American descent. This data is available for download at the dbGaP database (phs000092.v1.p1). One-thousand-two-hundred and ninty-six of the European controls were combined with the OCD data for PRS analyses, as there were very few controls in the OCD data. The samples were genotyped using the Illumina Human 1M platform.The ADHD dataset was downloaded from the Psychiatric Genomics Consortium (PGC)The CHOP data contains trio families that were recruited from both pediatric and behavioral health clinics in the surrounding Philadelphia area , which is a semi-structured diagnostic interview used to obtain the clinical phenotypes often associated with ADHD , conduct disorder (CD), as well as mood and anxiety disorders. A majority of this data was collected for a sibling pair genome-wide linkage study of ADHD. Patients were accessed using the DSM-IV version of the Diagnostic Interview Schedule for Children  was used to access both the children and parents  test were removed as well. After QC, 591,322 SNPs remained from the 2998 individuals for statistical analyses. For the GENEVA controls after QC, 849,063 SNPs were left from the 1296 individuals.Quality control (QC) measures were previously completed in-house for a cross-disorder genome-wide study that used the same OCD dataset. QC was conducted using PLINKImputation was also previously completed for the same cross-disorder genome-wide study. The IMPUTE2Post imputation QC was previously completed for a cross-disorder genome-wide study on the OCD dataset. GTOOLThe ADHD sample was cleaned prior to upload to the siteBecause the OCD dataset has pedigree structure, the initial genome wide association analyses were completed using FBATPRS analyses were conducted using PRSicep-value thresholds of p < 0.01, 0.1, 0.2, 0.3, 0.4 and 0.5. PRSice also automates the LD pruning process. Within each of these LD thresholds, p-value significance thresholds were determined, and R2 values were calculated based on how well the regression fits the data, which can be seen in Figure p-value significance thresholds quantitative polygenic scores were calculated for each individual within the target data. These scores were calculated by multiplying the number of risk alleles for each SNP  by the score for that same SNP, estimated from the discovery sample.For this study, ADHD was used as the discovery sample because that sample size was larger and only the summary statistics were available for this analysis. Using OCD as the target dataset and ADHD as the discovery sample, the PRSice software was used to calculate these scores. PRSice was designed to automate the steps of the PRS analyses by using both PLINK  plot and Manhattan plot show the association The polygenic risk model was tested on the target sample to obtain the PRS for each individual. Logistic regression was conducted to examine the relationship between risk score and the case-control status of the target data. The percentage of the phenotypic variance that can be explained by the risk score was automated by PRSice Figure .R2 value indicates how well the logistic regression approximates the data, based on the p-value thresholds. The p-value threshold of 0.15 had an R2 value of 0.0834%. This means that approximately 0.08% of the data overlapped between the OCD and ADHD data.The p-value <0.001 were included in the analysis to investigate whether any protein(s) associated with the disorders would give a statistically significant p-value; A total of 123 genes were included in the analysis based on this criterion. Six direct protein-protein interactions were identified and included ten proteins in all , 20,929 (7.7%), 28,664 (10.5%), 35,776 (13.1%), 48,191 (17.7%), 59,096 (21.7%) and 68,295 (25.0%). The 20,929 SNPs for p < 0.1 in the discovery sample, contributed 0.023% variance in the target sample. The low variance could be related to the small number of SNPs included in the analysis. 28,664 SNPs for p < 0.15 in the discovery sample, contributed 0.083% of the variance explained by OCD. The other groups of SNPs contributed between 0.028%–0.079% of the variance explained by OCD.A cross-disorder PRS analysis was completed using the ADHD data as the discovery sample and the OCD data and GENEVA controls as the target sample. An LD pruning threshold was set at 0.1. The predetermined significance thresholds were p-value <1.00 × 10−4 from the genome wide association tests were included in an eQTL analysis. An eQTL analysis was conducted in order to compare the results with the proteins identified from DAPPLE. The top SNPs associated with the prefrontal cortex are listed in Table SNPs with a Psychiatric disorders, such as ADHD and OCD, are extremely complex and clinically heterogeneous. However, it has been reported that ADHD and OCD may share common sub-phenotypes. For example, Palumbo et al.  suggestep-value = 1.65 × 10−4). This SNP is in an intergenic region, but is near the LOC100127962 pseudo gene. None of the other SNPs were in any known biologically relevant genes. The GWAS conducted on the ADHD PGC data found the most significant SNP on the CDH13 gene (Neale et al., CHMP4B, EIF2S2, EIF3I, FGF10, FGFR2, ITCH, PIK3C2B, SELE, SELL and UQCC all contributed to disease susceptibility. EIF2S2 and FGFR2 were found to be associated with both disorders. Zayats et al. (EIF2S2 may participate in a protein network that is impaired in individuals with ADHD.To summarize our findings, we conducted a meta-analysis between ADHD and OCD. The SNP rs10989904 had the strongest association signal (s et al.  reportedFGFR2, was reported to be associated with hyperactive behavior in mice deficient in the protein (Kaga et al., FGFR2 is involved in generating the excitatory glutamatergic pyramidal neurons in the medial prefrontal cortex. The prefrontal cortex has been implicated in the pathophysiology of several neurodevelopmental disorders, including ADHD and OCD, and both disorders exhibit impairments in inhibitory control (Schubert et al., Another protein found in the direct network, SELE, which plays a role in inflammation. Inflammation, especially in the brain, has been found to be associated with the development of neuropsychiatric disorders. Specifically, in populations of youth and adolescents, there were elevated markers for inflammation among several neuropsychiatric disorders including ADHD and OCD (Mitchell and Goldstein, The eQTL results were compared to the findings from the DAPPLE analysis. Only one gene overlapped between DAPPLE and eQLAnalysis. The overlapping gene was p-value of 2.136 × 10−6 and a permuted p-value of 0.0041 (Table More interestingly, the WDFY3 gene was found to be associated with axon guidance in mice, which was previously reported to be associated with ADHD (Dragich et al., p-value <0.15 from the discovery sample contributed 0.083% of the variance explained by OCD. In general, psychiatric disorders such as OCD and ADHD are likely to arise from the influence of a large number of susceptibility genes across the genome, as well as the proportion of OCD phenotypic variance explained directly by the targeted SNP’s (Yu et al., Our study also showed that SNPs with a Notably, our study has a limited sample size for both the ADHD and OCD samples, and thus are likely to be underpowered in detecting statistically robust polygenic score effects and signals in the meta-analysis. In the future, a larger sample size may provide a more accurate PRS and better estimate of heritability. Additionally, the samples may exhibit heterogeneity that each of these diseases are clinically heterogeneous.Clinical heterogeneity tends to increase as the number of data collection sites increases. A study by Anttila et al.  examinedAlthough the analyses conducted including meta, PRSs, DAPPLE provide little evidence to suggest that ADHD and OCD share common genetic etiologies, our eQTL analysis suggested a potential role for the WDFY3 gene in psychiatric disorders such as ADHD and/or OCD. We also anticipate that more genes/pathways will emerge with future studies of larger sample sizes.MLR, WG, GN and YYS co-designed and completed the statistical analysis. MLR wrote the manuscript. MLR, PSN, GN and YYS edited the manuscript. JFS, YW, PSN, JK, MAG, MAR, BC, JB, FSG, AEP, BDG, AJF, JTM, DAG, DLM, JAK, SAR, NCM, ELN, KDA, JP, DLP, ES, BM, MM, JQ and GN collected data, provided information for the OCD dataset, attended many phone discussions and contributed to the writing and data interpretation.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer YSJ and handling Editor declared their shared affiliation, and the handling Editor states that the process nevertheless met the standards of a fair and objective review.


The Barkley Adult Attention Deficit/Hyperactivity Disorder (ADHD) Rating Scale-IV (BAARS-IV) was developed, and it demonstrated good psychometric properties. The BAARS-IV includes 27 questions on the symptoms of adult ADHD. The purpose of the present study is to investigate the psychometric testing of the Persian version of BAARS-IV among the elderlies in Tabriz City. This cross-sectional study was conducted in Tabriz City—in the west of Iran—in 2015 via enrolling of 121 old-aged people. We did the process of translation and adaptation of BAARS-IV and examined its concurrent validity, internal consistency, and test-retest reliability. The BAARS-IV demonstrated good internal consistency and test-retest reliability. Correlations between the BAARS-IV and the CAARS-S: SV were high and evidence supporting concurrent validity was revealed. Cronbach's alpha for the overall scale and subscales stood at 0.89, 0.81, 0.66, 0.56, and 0.82, respectively. The Persian BAARS-IV showed acceptable reliability and validity. BAARS-IV was determined to be composed of internally consistent and psychometrically sound items. Attention Deficit/Hyperactivity Disorder (ADHD) is among the most common neurobehavioral disorders seen in the people referring to the children-adult psychiatric clinics . This diThus far, most studies in adulthood concern young or middle-aged adults, but little literature is present with regard to the elderly . ElderliA study in Netherlands reported prevalence of syndromic ADHD in elderlies as 2.8 and prevalence of symptomatic ADHD at 4.2, by using DSM-IV criteria. The prevalence was higher in elderlies aged between 60 and 70 in comparison with the ones aged 71 to 94 [Choice for the BAARS-IV. The Barkley Adult ADHD Rating Scale-IV (BAARS-IV) is meant to replace the current symptoms scale [ms scale . The selms scale , 10. SCTms scale , 11–14. ms scale , 14. Thems scale . Moreovems scale –18. One ms scale .In fact, Barkley Adult ADHD Rating Scale-IV was adequately valid and predictive of disorder. This scale is highly recommended as first step screening in clinical evaluation of ADHD among adults. Thus considering all features of this tool and the absence of an accurate tool for diagnosing such disorders in elderlies, this study was carried out to psychometrically test the Persian version of BAARS-IV among elderlies in Tabriz-Iran.This cross-sectional study was conducted in Tabriz City, the west of Iran, in 2015 enrolling 121 old-aged people (over 60 years old). In order to recruit these participants, we selected Golgasht district of Tabriz City that has a population with a range of low to high socioeconomic status inhabiting it. The sampling method used was cluster sampling in which we chose three clusters and the people were selected according to convenience sampling. Also to consider psychiatric disorders, medical records of persons were obtained. In case of facing any subject suspected of having psychiatric disorder, we considered psychiatric visit using the Structured Clinical Interview (SCID) on the basis of DSM-IV-TR criteria , but no The process for development and assessment of the tool is shown in In translation phase, we translated the tool based on the standards of WHO's translation and adaptation protocol. A person fluent in English (in the native tongue) and familiar with the concepts translated the questionnaire into Persian. After reviewing the correctness and validity of the translation and editing it according to the Persian and English language professor's comments, necessary changes with formal and conceptual compliance  were applied by a panel of experts (including eight psychiatrists and an epidemiologist). The Persian version of the questionnaire, on the other hand, was first translated by an Iranian person living abroad—without seeing the original English items of the questionnaire. After that the panel of experts accomplished the process of evaluating and conceptual compliance of the retranslated sentences with the original ones in the English version, and eventually the questionnaire was finalized.A Persian version of Conner's Adult ADHD Rating Scales (self-report version) which is one of the most substantial and practical tools used for diagnosing and screening adult ADHD  was admiIn order to determine the internal consistency reliability of questions, Cronbach's alpha coefficient was used for total scale and each subscale separately. Plus, to ascertain test-retest reliability, the questionnaires were distributed simultaneously among 60 older adults in two weeks and then the process was assessed by ICC.A value of above 0.7 for Cronbach's alpha and one higher than 0.5 for ICC were considered as acceptable reliability. The value of  .05 was considered as the statistical significance level for all tests.STATA (version 13) statistical software packages were used for the analysis of data.The study protocol was approved by the regional committee of ethics in Tabriz University of Medical Science under the Ethical Registration Number 660. Verbal informed consent was obtained from all the participants.In order to receive the original questionnaire, we communicated with Dr. Barkley. He gave us the questionnaire with his own permission after we explained the methodology and aims of our study.One hundred and twenty-one aged people were enrolled in this study. 67 persons (55.37%) were male and 54 (44.63%) of them were female. The mean age of the participants was 68.15 ± 7.99 years.After the forward and backward translation process, we shared it with the panel of experts and collected their comments; then the necessary modifications were made using these comments through simplification or replacement of words or phrases as required in the meaning .ICCs and Kendall's tau-b correlations between the BAARS-IV and CAARS-S: SV were calculated at 0.88 and 0.69, respectively.It is a given fact that adult ADHD draws extensive scientific interest in the West, yet it remains less known in Iran. As we mentioned, Persian literature on adult ADHD is practically nonexistent and its prevalence is unknown since all local studies focus on ADHD in child population. Despite the fact that there is a general agreement recognizing ADHD as having a reliable diagnosis in child population through the official diagnostic criteria, there is less agreement on it as a valid diagnostic tool in elderly population .Unfortunately, no efforts have been taken to establish a reliable and valid tool to assess ADHD symptoms in the elderly despite the growing need to render services to this expanding population. Therefore, the aim of this study is to provide a Persian version of BAARS-IV, which is well-established as a rating scale of ADHD symptoms and developed in USA , consideBasically, tests for mental health are designed in one country and used by others, by taking into account the existing cross-national and cross-cultural differences. Translating an instrument from the source to the target language is a rather complicated matter, the goal of which is to stay as close as possible to the semantic, conceptual, and technical aspects of the original found in the different versions of the instruments . The BAAPsychometric assessment of Persian version of BAARS-IV proves that it is a valid and stable tool for screening ADHD in elderlies. Classic psychometric analysis confirmed the scale capability for sound measurement with adequate psychometric properties.α's = .56–.82) and the Current ADHD total score (α = .89). In the original tool, Current ADHD Inattention = .902, Current ADHD Hyperactivity = .776, Current ADHD Impulsivity = .807, and Current ADHD total score = .914 [Internal consistency was examined using Cronbach's alpha for the BAARS-IV total and subscale scores: in particular, alpha coefficients of the Current ADHD Inattention, Hyperactivity, and Impulsivity subscales (range of e = .914 . The twoThe stability of test/retest was moderate after two weeks (0.69). Although ADHD is a chronic disorder and persist over time. The moderate test-retest reliability may have been caused by slight variability in the self-perceived symptoms on the two measurements. It could also be that the questions are not specific enough for older adults to recognize the symptoms or that they experience other problems in their daily life caused by ADHD.We used Conner's Adult ADHD Rating Scales for concurrent validity analysis which is a similar tool for assessing adult ADHD. A positive connection between BAARS-IV and CAARS-S: SV was observed in all subscales.The first limitation was that the tool (BAARS-IV) was not only specialized for elderlies. Another was that the tool used for concurrent validity analysis was in the form of a self-report questionnaire which may inflate the connection between research variables. More valid researches need to be done by clinical interviews as a golden standard and finally BAARS-IV screening must be undergone more times.The Persian BAARS-IV showed good reliability and satisfactory validity. This research suggests that the BAARS-IV appears to be a promising measure of older adult ADHD. The BAARS-IV was determined to be composed of internally consistent and psychometrically sound items.Considering all features of this tool and absence of an accurate tool for diagnosing ADHD in elderlies, it has been recommended to create a specialized tool with high sensitivity and high specificity for ADHD in elderlies in future researches.


KChIP4, KChIP1, DPP10, FHIT, and KCNC1) and the risk of developing ADHD. In the discovery stage comprising 256 cases and 372 controls, KChIP1 rs1541665 and FHIT rs3772475 were identified; they were further genotyped in the validation stage containing 328cases and 431 controls.KChIP1 rs1541665 showed significant association with a risk of ADHD at both stages, with CC vs TT odds ratio (OR) = 1.961, 95% confidence interval (CI) = 1.366–2.497, in combined analyses (P-FDR = 0.007). Moreover, we also found rs1541665 involvement in ADHD-I subtype (OR (95% CI) = 2.341, and Hyperactive index score (P = 0.005) in combined samples.Intriguingly, gene-environmental interactions analysis consistently revealed the potential interactionsof rs1541665 collaboratingwith maternal stress pregnancy (Pmul = 0.021) and blood lead (Padd = 0.017) to modify ADHD risk. In conclusion, the current study provides evidence that genetic variants of Kv accessory proteins may contribute to the susceptibility of ADHD.Further studies with different ethnicitiesare warranted to produce definitive conclusions.Attention-deficit/hyperactivity disorder (ADHD) is an early onset childhood neurodevelopmental disorder with high heritability. A number of genetic risk factors and environment factors have been implicated in the pathogenesis of ADHD. Genes encoding for subtypes of voltage-dependent K channels (Kv) and accessory proteins to these channels have been identified in genome-wide association studies (GWAS) of ADHD. We conducted a two-stage case–control study to investigate the associations between five key genes ( Attention-deficit/hyperactivity disorder (ADHD) is an early onset childhood neurodevelopmental disorder with a prevalence estimated at 5.9%-7.1% worldwide , KChIP4 [alias name KCNIP4], dipeptidyl-peptidase 10 [DPP10], and fragile histidine triad protein [FHIT]) related to potassium-channel function associated with total ADHD symptom count [KChIP4 gene in ADHD susceptibility [The etiology of ADHD remains unclear. Family studies reported that ADHD heredity is as high as 80%–90%, indicating a strong genetic component . In addi(KChIP4) . At the (KChIP4) . GWAS anom count . In addiom count . Furthertibility .Kv1.1 to 1.8), Shab (Kv2.1 andKv2.2), Shaw (Kv3.1 to 3.4), and Shal (Kv4.1 to Kv4.3)according to Drosophila genes and regulated by many accessory proteins including Kv channel-interacting proteins (KChIPs) and dipeptidyl peptidase-like proteins . KChIP4, KChIP1 and DPP10 have been found binding to subunits of the Kv4.2 family to modulate their cell-surface expression and subcellular localization [Kv channel genes have been classified as subfamiliesShaker and the risk of ADHD. Also, given the etiological complexity of ADHD, it was deemed important toinvestigate the interactions between these genes andenvironmental risk factors implicated in ADHD.To date, no combined analysis for the genes of Kv channels and ancillary proteins to these channels in ADHD has been performed. Therefore, we carried out a two-stage case–control study to comprehensively evaluate the associations between five key genes (We applied a two-stage case-control study to investigate the association of genetic variants inKv channels and accessory proteins with ADHD risk. The discovery sample (stage one) included 256 ADHD children and adolescents with ADHD consecutively recruited from Wuhan Medical and Health Center for Women and Children between October 2013 and December 2014, and 372 control children from the same hospital who underwent physical examination during the same time period. The validation sample (stage two) included 328 ADHD cases enrolled from the Children's Hospital of Hunan province (Changsha) from January 2014 to December 2015, and 431 controls selected among children who visited the same hospital for physical examination during the same time period. All cases were diagnosed ADHD for the first time according to the diagnostic criteria of the DSM-IV .All subjects were required to meet the following criteria: (1) be between 6 and 18 years old; (2) have a full scale Intelligence Quotient (IQ≥70) according to the Chinese-Wechsler Intelligence Scale for Children ; (3) chiThis study was approved by the Ethics Committees of Tongji Medical College of Huazhong University of Science and Technology, Wuhan Medical and Health Center for Womenand Children and Children's Hospital of Hunan province. At recruitment, written informed consent was obtained from the parents of each subject, and blood samples and demographic information were collected.Information about basic demographic variables  and other potential risk factors for ADHD was obtained from the questionnaire, including maternal stress pregnancy , maternal smoking or alcohol pregnancy , parental marital status (couple or divorced), preterm birth (<37 weeksor ≥37 weeks), low birth weight (<2.5kg or ≥2.5kg) and blood lead.To measure maternal stress pregnancy, the 30-item Chinese version of Pregnancy Stress Rating Scale (PSRS) was used , 32. TheTo measure lead level in blood, 3–5mL of whole blood was drawn from each child and was collected in heparin-containing tubes. Blood lead level (BLL)was determined by atomic absorption spectrophotometry  at a commercial laboratory. The coefficient of variation for the BLLs was 4.9%. The limit of detection for blood lead was 0.2μg/dL. None of the blood samples below the limit of detection are shown. In our study, a median was used for cutoff point for differentiating blood lead level; thus, median or more was defined as indicative of a high lead level and less than median of a low lead level.ADHD symptoms were measured with a Chinese version of the Conners Parent Symptom Questionnaire (PSQ) , 34. Thehttp://hapmap.ncbi.nlm.nih.gov/, HapMap Data Rel24/phaseII Nov08, on NCBI B36 assembly, dbSNP b126) for the CHB (Han Chinese from Beijing) population, using the criteria of r2>0.8 and minor allele frequency (MAF) >0.15 across the region of the candidate genes. We placed the selected tag SNPs into an integrated bioinformatics tool “F-SNP” (http://compbio.cs.queensu.ca/F-SNP/) [KChIP4 rs876477, KChIP1 rs1541665, DPP10 rs272000, and FHIT rs6791644) were also included in our study. Finally, 17 SNPs were identified as the candidate SNPs .Genomic DNA was extracted from 2 ml of peripheral blood sample using the Relax Gene Blood DNA System DP319-02  according to the manufacturer’s instructions. Candidate SNPs were genotyped using MassARRAY technology  in both stage one and stage two according to the manufacturer’s iPLEX Application Guide. The primers were designed using the Assay Design 3.0 software supplied by Sequenom. The iPLEXQuality control was performed by exclusion of SNPs with a genotype call rate of <90% and those that deviated from the Hardy-Weinberg Equilibrium (HWE) in controls. Notably, genotyping was performed by experimenters blinded to the status of the participants.χ2 goodness-of-fit test. Pearson’s χ2test or two independent sample t-test was used to examine differences between cases and controls in the distribution of demographic characteristics. The risks of ADHD, ADHD subtypes and CPT results associated with SNPs were estimated by using odds ratios (ORs) and the 95% confidence intervals (95% CIs) were calculated by multivariate logistic regression model (LR) after adjustment for age and gender. The Bonferroni [http://www.r-project.org/). All other statistical analyses were conducted using IBM SPSS software .The HWE for genotypes in the control groups was assessed by a nferroni  and falsnferroni  methods nferroni . For SNPFurthermore, to assess the high-order gene-environment interactions, multifactor dimensionality reduction (MDR) analyses were carried out using MDR 2.0 beta 8.1 program  in combiPage= 0.148, Pgender = 0.570, PIQ = 0.159; stage two: Page= 0.266, Pgender = 0.076, PIQ = 0.083). In stage one, we also found significant differences in the distribution of maternal stress pregnancy, parental marital status, low birth weight and blood lead level . In stage two, significant difference was found in the distribution of maternal stress pregnancy (P = 0.030). For ADHD subtypes, ADHD-I was the most in both stage one (40%) and stage two (42%). For PSQ scores, significant differences have been found in the two stages for the Hyperactivity index score .The distributions of selected characteristics in the two stages are listed in P values did not surpass the Bonferroni threshold in the association tests . However, as shown in KCNIP1 rs1541665 was significantly associated with ADHD under the codominant model , dominant model , and addictive model  after FDR correction. FHIT rs3772475 has also been observed to have significant association with ADHD under dominant model .Distribution of genotypes of the SNPs in stage one was presented in KChIP1 rs1541665 and FHIT rs3772475 were further genotyped in the validation stage. We successfully validated the significant association between KChIP1 rs1541665 with ADHD risk    after FDP-FDR = 0.027) after FDR correction. In stage two, rs1541665 has been consistently associated with ADHD-I  after FDR correction. In combined samples, we replicated these results . For rs757511, lower hyperactive symptom score has been found in AA genotype compared to that of the GG genotype. In validation stage, hyperactive symptom scores in CC genotype of rs1541665 and rs3772475 were found to be higher than the scores in the TT genotype   have been nominally found associated with PSQ scores . For rs1ctively) . Resultsctively) .Padd = 0.034) and multiplicative terms(Pmul = 0.021)was detectedwith an OR of 3.052  among the subjects with maternalstress carrying an CT+CC genotype compared with those without maternalstress carrying TT genotypes (Padd = 0.017).In the MDR analyses in combined samples, the three-factor model including rs1541665, maternal stress pregnancy and BLL was selected as the best predictor for ADHD risk, because it had the optimal testing accuracy and the maximal CVC values . A signienotypes . SubjectKChIP1 rs1541665 genetic variant as a new susceptibility locus for ADHD. The following analysis suggested that KChIP1 rs1541665 also associated with hyperactive index score of PSQ scores and the ADHD-I risk. Gene-environmentinteractions analysis consistently revealed the potential interactionsof rs1541665 collaboratingwith maternal stress and blood lead to modify ADHD risk. To the best of our knowledge, this is the first study that comprehensively investigates the association betweenthe genetic variants of Kv channels and their accessory proteins and ADHD risk.We conducted a two-stage case-control study to explore the effects of variants in Kv channels and their accessory proteins on the risk of ADHD, and identified KChIP1 gene, was consistently shown to be associated with ADHD risk in the discovery and validation stages. KCNIP1 gene  encodes the potassium channel-interacting protein 1 (KChIP1), which is expressed predominantly in the brain, with relative abundance in cerebellum, hippocampus, striatum, and the reticular thalamic and medial habenular nuclei [rs1541665, located in the intron of the r nuclei . Abnormar nuclei . KChIP1 r nuclei , 46. Indr nuclei . Since hr nuclei , 49, KChIn addition, it may also be possible that KChIP1 involvement in ADHD is by regulating GABA levels, although the mechanism remains ambiguous. Studies have shown that KChIP1 potentially modulated GABAergic system by regulating inhibitory synaptic transmission , 51. GABAs a neuronal calcium sensor (NCS) protein, KChIP1 is also potentially involved in ADHD by regulating neuronal calcium. Calcium, which acts intracellularly like a second messenger, has an immediate impact on synaptic activity . Gene diGrizenko N et al. observed that maternal stress pregnancy may interact with the child’s DRD4 7/7 genotype to produce more severe ADHD symptoms [Gene-environment interaction analysis also showed KChIP1 rs1541665 collaboratingwith maternal stress pregnancy and blood lead to modify ADHD risk. symptoms . The intsymptoms . Plasticsymptoms . Evidencsymptoms  and intesymptoms , 69. Luosymptoms , and earsymptoms , 72. Bessymptoms . Thus, wP = 5.60E-05) [http://compbio.cs.queensu.ca/F-SNP/) with an FS score of 0.101 for regulating transcription [2 = 0.905 in the 1000 Genomes Project, Phase 3 CHB), which was identified as a binding site for micro RNAs (miRNAs) by miRNA SNP2.0 (http://www.bioguo.org/miRNASNP/) [www.braineac.org) [KChIP1 gene expression (P = 0.0053 in substantia nigra). Accordingly, we could speculate that rs1541665 might not be the “real” causal variant for ADHD but only a “proxy” for other true biologically functional SNPs like rs1363713, which might provide a clue for further studies in the future.Neale et al found rs1541665 to be one of top 25 results associated with ADHD in corrected transmission disequilibrium test (TDT) (.60E-05) . Althougcription , the SNPRNASNP/) . The e-Qeac.org)  indicateFHIT rs3772475 and KCNC1 rs757511 nominal association with ADHD and ADHD symptoms respectively, in the discovery stage. FHIT gene, encoding the fragile histidine triad protein, is preferentially and stably expressed in brain microglia. McCarthy et al. noted that FHIT gene was associated with ADHD by genomic study, in addition to having altered expression in the mouse brain in response to lithium [In addition, in our study, we found evidence of  lithium . KCNC1 e lithium , 79. A r lithium , implicaIn addition, in published GWAS studies, 5 loci  were found to be associated with ADHD . HoweverIn conclusion, this study comprehensively explored for the first time the role of Kv channels and their accessory proteins genes and their interaction with environment in ADHDand provided a clue for KChIP1 involvement in ADHD. Although we did not replicate the association in stage two for FHIT and KCNC1 and did not observe any association between other gene variants and ADHD,Neale et al and Stergiakouli et al. also did not show a clear effect for potassium channel genes , 82, whiS1 Table*MAF from 1000 Genomes Phase 3 CHB database.(DOCX)Click here for additional data file.S2 TableAbbreviations: HW, wild type homozygote; HT, heterozygote; HV, variant homozygote; HWE: Hardy-Weinberg; MAF: minor allele frequency.(DOCX)Click here for additional data file.S3 TableP values were adjusted for age and gender. The significant level was corrected with the formula of α' = α/15*5 = 0.00067 according to the Bonferroni method. The nominal significant results were in bold.Abbreviations: Ref, Reference allele; HW, wild type homozygote; HT, heterozygote; HV, variant homozygote; OR, odds ratio; CI, confidence interval. a All the (DOCX)Click here for additional data file.S4 Tablea All the P values were adjusted for age and gender. The significant level was corrected with the formula of α' = α/15*3 = 0.0011according to the Bonferroni method. The nominal significant results were in bold.(DOCX)Click here for additional data file.S5 Tableacompared with ANOVA analysis, posthoc comparisons with SNK. The significant results were in bold.(DOCX)Click here for additional data file.