Shared cognitive impairments and aetiology in ADHD symptoms and reading difficulties

Where do neurodevelopmental conditions fit in transdiagnostic psychiatric frameworks? Incorporating a new neurodevelopmental spectrum

Features of autism spectrum disorder, attention-deficit/hyperactivity disorder, learning disorders, intellectual disabilities, and communication and motor disorders usually emerge early in life and are associated with atypical neurodevelopment. These "neurodevelopmental conditions" are grouped together in the DSM-5 and ICD-11 to reflect their shared characteristics. Yet, reliance on categorical diagnoses poses significant challenges in both research and clinical settings (e.g., high co-occurrence, arbitrary diagnostic boundaries, high within-disorder heterogeneity). Taking a transdiagnostic dimensional approach provides a useful alternative for addressing these limitations, accounting for shared underpinnings across neurodevelopmental conditions, and characterizing their common co-occurrence and developmental continuity with other psychiatric conditions. Neurodevelopmental features have not been adequately considered in transdiagnostic psychiatric frameworks, although this would have fundamental implications for research and clinical practices. Growing evidence from studies on the structure of neurodevelopmental and other psychiatric conditions indicates that features of neurodevelopmental conditions cluster together, delineating a "neurodevelopmental spectrum" ranging from normative to impairing profiles. Studies on shared genetic underpinnings, overlapping cognitive and neural profiles, and similar developmental course and efficacy of support/treatment strategies indicate the validity of this neurodevelopmental spectrum. Further, characterizing this spectrum alongside other psychiatric dimensions has clinical utility, as it provides a fuller view of an individual's needs and strengths, and greater prognostic utility than diagnostic categories. Based on this compelling body of evidence, we argue that incorporating a new neurodevelopmental spectrum into transdiagnostic frameworks has considerable potential for transforming our understanding, classification, assessment, and clinical practices around neurodevelopmental and other psychiatric conditions.

The underlying neuropsychological and neural correlates of the impaired Chinese reading skills in children with attention deficit hyperactivity disorder

Impaired basic academic skills (e.g., word recognition) are common in children with Attention Deficit Hyperactivity Disorder (ADHD). The underlying neuropsychological and neural correlates of impaired Chinese reading skills in children with ADHD have not been substantially explored. Three hundred and two children with ADHD (all medication-naïve) and 105 healthy controls underwent the Chinese language skill assessment, and 175 also underwent fMRI scans (84 ADHD and 91 controls). Between-group and mediation analyses were applied to explore the interrelationships of the diagnosis of ADHD, cognitive dysfunction, and impaired reading skills. Five ADHD-related brain functional networks, including the default mode network (DMN) and the dorsal attention network (DAN), were built using predefined regions of interest. Voxel-based group-wise comparisons were performed. The ADHD group performed worse than the control group in word-level reading ability tests, with lower scores in Chinese character recognition (CR) and word chains (WS) (all P < 0.05). With full-scale IQ and sustained attention in the mediation model, the direct effect of ADHD status on the CR score became insignificant (P = 0.066). The underlying neural correlates for the orthographic knowledge (OT) and CR differed between the ADHD and the control group. The ADHD group tended to recruit more DMN regions to maintain their reading performance, while the control group seemed to utilize more DAN regions. Children with ADHD generally presented impaired word-level reading skills, which might be caused by impaired sustained attention and lower IQ. According to the brain functional results, we infer that ADHD children might utilize a different strategy to maintain their orthographic knowledge and character recognition performance.

Prediction of attention deficit hyperactivity disorder based on explainable artificial intelligence

Accurate assessment of Attention Deficit Hyperactivity Disorder (ADHD) is crucial for the effective treatment of affected individuals. Traditionally, psychometric tests such as the WISC-IV have been utilized to gather evidence and identify patterns or factors contributing to ADHD diagnosis. However, in recent years, the use of machine learning (ML) models in conjunction with post-hoc eXplainable Artificial Intelligence (XAI) techniques has improved our ability to make precise predictions and provide transparent explanations. The objective of this study is twofold: firstly, to predict the likelihood of an individual receiving an ADHD diagnosis using ML algorithms, and secondly, to offer interpretable insights into the decision-making process of the ML model. The dataset under scrutiny comprises 694 cases collected over the past decade in Spain, including information on age, gender, and WISC-IV test scores. The outcome variable is the professional diagnosis. Diverse ML algorithms representing various learning styles were rigorously evaluated through a stratified 10-fold cross-validation, with performance assessed using key metrics, including accuracy, area under the receiver operating characteristic curve, sensitivity, and specificity. Models were compared using both the full set of initial features and a well-suited wrapper-type feature selection algorithm (Boruta). Following the identification of the most suitable model, Shapley additive values were computed to assign weights to each predictor based on their additive contribution to the outcome and to elucidate the predictions. Strikingly, a reduced set of 8 out of the initial 20 variables produced results comparable to using the full feature set. Among the ML models tested, the Random Forest algorithm outperformed others on most metrics (ACC = 0.90, AUC = 0.94, Sensitivity = 0.91, Specificity = 0.92). Notably, the principal predictors, ranked by importance, included GAI - CPI, WMI, CPI, PSI, VCI, WMI - PSI, PRI, and LN. Individual case examples exhibit variations in predictions depending on unique characteristics, including instances of false positives and negatives. Our ML model adeptly predicted ADHD diagnoses in 90% of cases, with potential for further enhancement by expanding our database. Furthermore, the use of XAI techniques enables the elucidation of salient factors in individual cases, thereby aiding inexperienced professionals in the diagnostic process and facilitating comparison with expert assessments. It is important to note that this tool is designed to support the ADHD diagnostic process, where the medical professional always has the final say in decision-making.

Kynurenine and oxidative stress in children having learning disorder with and without attention deficit hyperactivity disorder: possible role and involvement

Background

The etiological and pathophysiological factors of learning disorder (LD) and attention deficit hyperactivity disorder (ADHD) are currently not well understood. These disorders disrupt some cognitive abilities. Identifying biomarkers for these disorders is a cornerstone to their proper management. Kynurenine (KYN) and oxidative stress markers have been reported to influence some cognitive abilities. Therefore, the aim was to measure the level of KYN and some oxidative stress indicators in children with LD with and without ADHD and to investigate their correlations with the abilities of children with LD.

Methods

The study included 154 participants who were divided into 3 groups: one for children who have LD (N = 69); another for children with LD and ADHD (N = 31); and a group for neurotypical (NT) children (N = 54). IQ testing, reading, writing, and other ability performance evaluation was performed for children with LD. Measuring plasma levels of KYN, malondialdehyde, glutathione peroxidase, and superoxide dismutase by enzyme-linked immunosorbent assay was performed for all participants.

Results

Some IQ measures and learning skills differed between the first two groups. The biochemical measures differed between children with LD (with and without ADHD) and NT children (p < 0.001). However, the biochemical measures did not show a significant statistical difference between the first two groups. KYN and glutathione peroxidase levels were correlated with one-minute writing and at-risk quotient, respectively (p = 0.03;0.04). KYN and malondialdehyde showed the highest sensitivity and specificity values.

Conclusion

These biochemical measures could be involved or have a role in the abilities’ performance of children with specific learning disorder.

Polygenic risk for ADHD and ASD and their relation with cognitive measures in school children

BACKGROUND

Attention deficit and hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are child-onset neurodevelopmental disorders frequently accompanied by cognitive difficulties. In the current study, we aim to examine the genetic overlap between ADHD and ASD and cognitive measures of working memory (WM) and attention performance among schoolchildren using a polygenic risk approach.

METHODS

A total of 1667 children from a population-based cohort aged 7-11 years with data available on genetics and cognition were included in the analyses. Polygenic risk scores (PRS) were calculated for ADHD and ASD using results from the largest GWAS to date (N = 55 374 and N = 46 351, respectively). The cognitive outcomes included verbal and numerical WM and the standard error of hit reaction time (HRTSE) as a measure of attention performance. These outcomes were repeatedly assessed over 1-year period using computerized version of the Attention Network Test and n-back task. Associations were estimated using linear mixed-effects models.

RESULTS

Higher polygenic risk for ADHD was associated with lower WM performance at baseline time but not over time. These findings remained significant after adjusting by multiple testing and excluding individuals with an ADHD diagnosis but were limited to boys. PRS for ASD was only nominally associated with an increased improvement on verbal WM over time, although this association did not survive multiple testing correction. No associations were observed for HRTSE.

CONCLUSIONS

Common genetic variants related to ADHD may contribute to worse WM performance among schoolchildren from the general population but not to the subsequent cognitive-developmental trajectory assessed over 1-year period.

Examining Distinctive Working Memory Profiles in Chinese Children With Predominantly Inattentive Subtype of Attention-Deficit/Hyperactivity Disorder and/or Reading Difficulties

Although evidence has shown that both RD and ADHD-I children suffer from working memory problems, inconsistencies in impaired modalities have been reported. This study aimed to (1) compare the three WM domains (i.e., verbal WM, visual-spatial WM, and behavioral WM) among pure ADHD-I, pure RD, comorbid ADHD-I+RD, and typical control groups and (2) examine the impact of comorbidity on the three WM domains. A Chinese sample of participants from Hong Kong included 29 children in the ADHD-I group, 78 children in the RD group, 31 children in the comorbid group (ADHD-I+RD), and 64 children in the TD control group. All participants completed the assessments individually. The findings showed that the children with ADHD-I and/or RD exhibited diverse cognitive profiles. In particular, RD was associated with verbal and visual-spatial working memory deficits, while ADHD-I was associated with behavioral working memory deficits. Interestingly, the comorbid condition demonstrated additive deficits of the two disorders but with greater deficits in behavioral working memory. These findings support the cognitive subtype hypothesis and provide a clearer picture of the distinctive working memory profiles of different groups, allowing for the development of intervention programs in the future.

Is executive dysfunction a potential contributor to the comorbidity between basic reading disability and attention-deficit/hyperactivity disorder?

Our study is one of the few to analyze executive functioning (EF) in a comprehensive, multi-modal fashion as a potential contributor to the comorbidity between attention-deficit/hyperactivity disorder (ADHD) and basic reading disability (RD). We included multiple, traditional, neuropsychological measures of EF, along with the Behavior Rating Inventory of Executive Function (BRIEF) questionnaire, to assess inhibit, shift, working memory (WM), planning, generation fluency, and problem-solving. Participants included 263 children, ages 8-12 years, with RD, ADHD, RD/ADHD, and typically developing controls. When using the traditional measures in a 2 × 2 MANCOVA, we found both RD and ADHD had poor cognitive EF in most areas at the group level, with phonological loop deficits being more specific to RD and behavioral regulation deficits being more specific to ADHD. Children with RD/ADHD performed comparably to those with RD and ADHD alone. Results were similar on the BRIEF. In contrast, only WM predicted both basic reading and inattention when the data were assessed in a continuous fashion. It also explained the correlations between basic reading and inattention, being worthy of longitudinal research to determine if it is a shared contributor to RD/ADHD. When comparing hypotheses as to the nature of RD/ADHD, we found the multiple deficit hypothesis was better supported by our EF data than the phenocopy hypothesis or the cognitive subtype hypothesis.

Movement Patterns in Students Diagnosed with ADHD, Objective Measurement in a Natural Learning Environment

Attention deficit hyperactivity disorder is the most common neuropsychological disorder in childhood and adolescence, affecting the basic psychological processes involved in learning, social adaptation and affective adjustment. From previous research, the disorder is linked to problems in different areas of development, with deficiencies in psychological processes leading to the development of the most common characteristics of the disorder such as inattention, excess of activity and lack of inhibitory control. As for the diagnosis, in spite of being a very frequent disorder, there are multiple controversies about which tools are the most suitable for evaluation. One of the most widespread tools in the professional field is behavior inventories such as the Strengths and Difficulties Questionnaires for Parents and Teachers or the ADHD Rating Scale-V. The main disadvantage of these assessment tools is that they do not provide an objective observation. For this reason, there are different studies focused on recording objective measures of the subjects' movement, since hyperkinesia is one of the most characteristic symptoms of this disorder. In this sense, we have developed an application that, using a Kinect device, is capable of measuring the movement of the different parts of the body of up to six subjects in the classroom, being a natural context for the student. The main objective of this work is twofold, on the one hand, to investigate whether there are correlations between excessive movement and high scores in the inventories for the diagnosis of ADHD, Rating Scale-V and Strengths and Difficulties Questionnaire (SDQ) and, on the other hand, to determine which sections of the body present the most significant mobility in subjects diagnosed with ADHD. Results show that the control group, composed of neurotypical subjects, presents less kinaesthetic activity than the clinical group diagnosed with ADHD. This indicates that the experimental group presents one of the main characteristics of the disorder. In addition, results also show that practically all the measured body parts present significant differences, being higher in the clinical group, highlighting the head as the joint with the highest effect size.

In Quest of Pathognomonic/Endophenotypic Markers of Attention Deficit Hyperactivity Disorder (ADHD): Potential of EEG-Based Frequency Analysis and ERPs to Better Detect, Prevent and Manage ADHD

Attention deficit hyperactivity disorder (ADHD) is a chronic heritable developmental delay psychiatric disorder requiring chronic management, characterized by inattention, hyperactivity, hyperkinectivity and impulsivity. Subjective clinical evaluation still remains crucial in its diagnosis. Discussed are two key aspects in the “characterizing ADHD” and on the quest for objective “pathognomonic/endophenotypic diagnostic markers of ADHD”. The first aspect briefly revolves around issues related to identification of pathognomonic/endophenotypic diagnostic markers in ADHD. Issues discussed include changes in ADHD definition, remission/persistence and overlapping-symptoms cum shared-heritability with its co-morbid cross-border mental disorders. The second aspect discussed is neurobiological and EEG-based studies on ADHD. Given the neurobiological and temporal aspects of ADHD symptoms the electroencephalograph (EEG) like NeuralScan by Medeia appears as an appropriate tool. The EEGs appropriateness is further enhanced when coupled with suitable behavior/cognitive/motor/psychological tasks/paradigms yielding EEG-based markers like event-related-potential (ERPs like P3 amplitudes and latency), reaction time variability (RTV), Theta:Beta ratio (TBR) and sensorimotor rhythm (SMR). At present, these markers could potentially help in the neurobiological characterization of ADHD and either help in identifying or lay the groundwork for identifying pathognomonic and/or endophenotypic EEG-based markers enabling its diagnosis, treatment and management.

Attention Deficit Hyperactivity Disorder and Psychiatric Comorbidities

Aim: This study aims to obtain current information on the clinical features of attention deficit hyperactivity disorder cases, comorbid psychiatric disorders and psychiatric drug use. Methods: All patients between the ages of 6 and 18 years who were admitted to our outpatient clinic and diagnosed with attention deficit hyperactivity disorder were included in the study. The files of the patients were examined and their demographic characteristics, symptoms, psychiatric diagnoses and drug profiles were recorded. The pattern of the psychiatric disorders accompanied by attention deficit hyperactivity disorder cases and the differences according to age and gender were analyzed. The differences were determined in patients with psychiatric comorbidity compared to those without. Result: The mean age of the 777 patients included in the study was 11.1±2.94 and 76.6% were boys. 60.9% of attention deficit hyperactivity disorder patients had comorbid psychiatric disorders. The most common psychiatric comorbidities were specific learning disability (23.6%), oppositional defiant disorder (12.9%) and conduct disorder (12.1%). There was no difference between the genders in terms of the incidence of psychiatric comorbidities. The rate of psychiatric comorbidity was significantly higher in adolescents than in children. A psychotropic medication was used in 86.4% of the cases and psychotropic polypharmacy was present in 31.5%. The rate of polypharmacy was significantly higher in the group with psychiatric comorbidity. Conclusion: Attention deficit hyperactivity disorder is frequently accompanied by other psychiatric disorders and the psychiatric comorbidity leads to a more complicated clinical profile. Approximately one-third of attention deficit hyperactivity disorder patients have psychiatric polypharmacy and these patients should be carefully monitored. Primary care physicians who are frequently confronted with attention deficit hyperactivity disorder cases should be careful about psychiatric comorbidities. Keywords: Child psychiatry, attention deficit hyperactivity disorder, mental disorders, Family practice

Are there shared neural correlates between dyslexia and ADHD? A meta-analysis of voxel-based morphometry studies

BACKGROUND

Dyslexia and Attention-deficit/hyperactivity disorder (ADHD) are highly comorbid neurodevelopmental disorders (estimates of 25-40% bidirectional comorbidity). Previous work has identified strong genetic and cognitive overlap between the disorders, but neural overlap is relatively unexplored. This study is a systematic meta-analysis of existing voxel-based morphometry studies to determine whether there is any overlap in the gray matter correlates of both disorders.

METHODS

We conducted anatomic likelihood estimate (ALE) meta-analyses of voxel-based morphometry studies in which individuals with dyslexia (15 studies; 417 cases, 416 controls) or ADHD (22 studies; 898 cases, 763 controls) were compared to typically developing controls. We generated ALE maps for dyslexia vs. controls and ADHD vs. controls using more conservative (p < .001, k = 50) and more lenient (p < .005, k = 50) thresholds. To determine the overlap of gray matter correlates of dyslexia and ADHD, we examined the statistical conjunction between the ALE maps for dyslexia vs. controls and ADHD vs. controls (false discovery rate [FDR] p < .05, k = 50, 5000 permutations).

RESULTS

Results showed largely distinct gray matter differences associated with dyslexia and ADHD. There was no evidence of statistically significant gray matter overlap at our conservative threshold, and only one region of overlap in the right caudate at our more lenient threshold. Reduced gray matter in the right caudate may be relevant to shared cognitive correlates in executive functioning and/or procedural learning. The more general finding of largely distinct regional differences in gray matter between dyslexia and ADHD suggests that other neuroimaging modalities may be more sensitive to overlapping neural correlates, and that current neuroimaging recruitment approaches may be hindering progress toward uncovering neural systems associated with comorbidity.

CONCLUSIONS

The current study is the first to meta-analyze overlap between gray matter differences in dyslexia and ADHD, which is a critical step toward constructing a multi-level understanding of this comorbidity that spans the genetic, neural, and cognitive levels of analysis.

Delineating and validating higher-order dimensions of psychopathology in the Adolescent Brain Cognitive Development (ABCD) study

Hierarchical dimensional systems of psychopathology promise more informative descriptions for understanding risk and predicting outcome than traditional diagnostic systems, but it is unclear how many major dimensions they should include. We delineated the hierarchy of childhood and adult psychopathology and validated it against clinically relevant measures. Participants were 9987 9- and 10-year-old children and their parents from the Adolescent Brain Cognitive Development (ABCD) study. Factor analyses of items from the Child Behavior Checklist and Adult Self-Report were run to delineate hierarchies of dimensions. We examined the familial aggregation of the psychopathology dimensions, and the ability of different factor solutions to account for risk factors, real-world functioning, cognitive functioning, and physical and mental health service utilization. A hierarchical structure with a general psychopathology ('p') factor at the apex and five specific factors (internalizing, somatoform, detachment, neurodevelopmental, and externalizing) emerged in children. Five similar dimensions emerged also in the parents. Child and parent p-factors correlated highly (r = 0.61, p < 0.001), and smaller but significant correlations emerged for convergent dimensions between parents and children after controlling for p-factors (r = 0.09-0.21, p < 0.001). A model with child p-factor alone explained mental health service utilization (R² = 0.23, p < 0.001), but up to five dimensions provided incremental validity to account for developmental risk and current functioning in children (R² = 0.03-0.19, p < 0.001). In this first investigation comprehensively mapping the psychopathology hierarchy in children and adults, we delineated a hierarchy of higher-order dimensions associated with a range of clinically relevant validators. These findings hold important implications for psychiatric nosology and future research in this sample.

Current Pattern of Psychiatric Comorbidity and Psychotropic Drug Prescription in Child and Adolescent Patients

Background: In recent years, patterns of the use of psychotropic drugs vary with increasing rates of psychiatric presentation and diagnosis in children and adolescents. Purpose: In this study, we aimed to investigate distributions of current psychiatric symptoms and diagnosis, patterns of the use of psychotropic drugs, and differences according to age and gender in patients presented to a child and adolescent outpatient clinic. Methods: All patients aged between 0 and 18 years presenting to a child and adolescent psychiatry outpatient clinic between November 1, 2017 and November 1, 2018 were included in the study. Files of all patients were examined in detail, and patients' demographic characteristics, symptoms, psychiatric diagnoses established according to the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), psychotropic drugs initiated, and side effect profiles were recorded. Psychiatric symptoms and diagnostic features of the patients were determined, and the differences were investigated according to gender. Clinical characteristics were compared between diagnosed and undiagnosed patients, and between patients with and without drug initiation. Results: Of the 2066 patients, 1298 (62.8%) were male and the mean age was 10.14 ± 4.42 years. The most common symptoms were hyperactivity (23.8%) and inattention (21.6%) in males, inattention (15.1%) and irritability (14.2%) in females, and 79% of the patients received one or more psychiatric diagnoses. The most common psychiatric diagnoses in both genders were attention-deficit hyperactivity disorder (ADHD), specific learning disorder (SLD), and conduct disorder, respectively. Of the patients who received a psychiatric diagnosis, 61.8% were using psychotropic drugs, with the majority of them (71.3%) receiving monotherapy. The most frequently initiated drugs included psychostimulants, antipsychotics, and antidepressants, with 28.7% of the drug user patients receiving multiple drug therapy. Conclusion: Our study indicates that rate of presentation to child and adolescent psychiatry outpatient clinics is increasing, and rates of diagnosis and initiation of psychiatry drugs are high among the presented children. The prevalence of ADHD shows an increase in males and females in our country, and psychiatric polypharmacy has reached significant rates.

Assessment of Psychiatric Comorbidity and WISC-R Profiles in Cases Diagnosed with Specific Learning Disorder According to DSM-5 Criteria

Introduction

In this study, the frequency of psychiatric comorbidity in children and adolescents who were diagnosed with specific learning disorder, the factors that affect the frequency of comorbidity, the subtypes of specific learning disorder and the effects on cognitive profile have been investigated.

Methods

Our study was performed among 80 cases with the age range 6-15 years who diagnosed with specific learning disorder Child and Adolescent Psychiatry Department between January and June 2015. In the study, DSM-IV Based Screening and Evaluation Scale for Child and Adolescent Behavioral Disorders, Specific Learning Disability Evaluation Scale and the WISC-R test were performed. During the interview, reading-writing-math abilities evaluation list (error analysis) was performed in order to define the specific learning disorder subgroup and to evaluate the detailed error profile of the specific learning disorder subgroup. Kiddie Schedule for Affective Disorders and Schizophrenia for School-age Children-Present and Lifetime Turkish Version (KSADS) was performed to detect psychiatric comorbidity diagnoses.

Results

92.5% of the cases have a comorbid psychiatric disorder. The most frequent psychiatric comorbidity was attention deficit hyperactivity disorder (82.3%), followed by specific phobia (46.3%), oppositional defiant disorder (26.3%), enuresis (25%) and tic disorders (22.5%). Psychiatric comorbidity is detected more often in patients with specific learning disorder accompanied by attention deficit and hyperactivity disorder. The most frequent subtype of specific learning disorder is combined type disorder consisting of reading, writing and math disorder (37.5%). The WISC-R score of the patients who had math disorder were found to be lower than the others, and also it was detected that they learned reading and writing later, and have more comorbid psychiatric disorders.

Conclusion

The results of our study indicate that associated psychiatric disorders are frequent with specific learning disorder. Specific learning disorder should not be considered as a single disorder, but should be assessed and treated with comorbid psychiatric disorders.

Cognitive mechanisms underlying the associations between inattention and reading abilities

This study aims to test cognitive skills underlying the association between inattention and reading in early primary school. Teachers rated inattention symptoms when children (N = 523-962) were 6-7 years old. Children were assessed at age 7-8 on phonological awareness, rapid automatized naming (RAN), rapid auditory and bimodal processing, vocabulary, and reading (decoding and comprehension). Phonological awareness, RAN of numbers, and vocabulary mediated the association between inattention and both decoding and comprehension. Rapid bimodal processing mediated the association between inattention and decoding, while RAN of colors mediated the association between inattention and comprehension. This study highlights mediators underlying inattention-reading associations.

[Learning disorders in ADHD: How are they related?]

Learning difficulties in general and learning disabilities in particular are almost constant in attention deficit disorder with or without hyperactivity (ADHD). Despite a major research effort, the extent and diversity of these comorbid events still raise many questions about the exact nature of their pathogenetic condition (simple consequences of ADHD or specific related disorders?) and consequently the best way to support them. This article aims to present a brief review of the current data.

Cognitive Function of Children and Adolescents with Attention Deficit Hyperactivity Disorder and Learning Difficulties: A Developmental Perspective

Background:

The cognitive function of children with either attention deficit hyperactivity disorder (ADHD) or learning disabilities (LDs) is known to be impaired. However, little is known about the cognitive function of children with comorbid ADHD and LD. The present study aimed to explore the cognitive function of children and adolescents with ADHD and learning difficulties in comparison with children with ADHD and healthy controls in different age groups in a large Chinese sample.

Methods:

Totally, 1043 participants with ADHD and learning difficulties (the ADHD + learning difficulties group), 870 with pure ADHD (the pure ADHD group), and 496 healthy controls were recruited. To investigate the difference in cognitive impairment using a developmental approach, all participants were divided into three age groups (6–8, 9–11, and 12–14 years old). Measurements were the Chinese-Wechsler Intelligence Scale for Children, the Stroop Color-Word Test, the Trail-Making Test, and the Behavior Rating Inventory of Executive Function-Parents (BRIEF). Multivariate analysis of variance was used.

Results:

The results showed that after controlling for the effect of ADHD symptoms, the ADHD + learning difficulties group was still significantly worse than the pure ADHD group, which was, in turn, worse than the control group on full intelligence quotient (98.66 ± 13.87 vs. 105.17 ± 14.36 vs. 112.93 ± 13.87, P < 0.001). The same relationship was also evident for shift function (shifting time of the Trail-Making Test, 122.50 [62.00, 194.25] s vs. 122.00 [73.00, 201.50] s vs. 66.00 [45.00, 108.00] s, P < 0.001) and everyday life executive function (BRIEF total score, 145.71 ± 19.35 vs. 138.96 ± 18.00 vs. 122.71 ± 20.45, P < 0.001) after controlling for the effect of the severity of ADHD symptoms, intelligence quotient, age, and gender. As for the age groups, the differences among groups became nonsignificant in the 12–14 years old group for inhibition (meaning interference of the Stroop Color-Word Test, 18.00 [13.00, 25.00] s vs. 17.00 [15.00, 26.00] s vs. 17.00 [10.50, 20.00] s, P = 0.704) and shift function (shifting time of the Trail-Making Test, 62.00 [43.00, 97.00] s vs. 53.00 [38.00, 81.00] s vs. 101.00 [88.00, 114.00] s, P = 0.778).

Conclusions:

Children and adolescents with ADHD and learning difficulties have more severe cognitive impairment than pure ADHD patients even after controlling for the effect of ADHD symptoms. However, the differences in impairment in inhibition and shift function are no longer significant when these individuals were 12–14 years old.

Poor stimulus discriminability as a common neuropsychological deficit between ADHD and reading ability in young children: a moderated mediation model

BACKGROUND

Attention deficit hyperactivity disorder (ADHD) is frequently associated with poorer reading ability; however, the specific neuropsychological domains linking this co-occurrence remain unclear. This study evaluates information-processing characteristics as possible neuropsychological links between ADHD symptoms and RA in a community-based sample of children and early adolescents with normal IQ (⩾70).

METHOD

The participants (n = 1857, aged 6-15 years, 47% female) were evaluated for reading ability (reading single words aloud) and information processing [stimulus discriminability in the two-choice reaction-time task estimated using diffusion models]. ADHD symptoms were ascertained through informant (parent) report using the Development and Well-Being Assessment (DAWBA). Verbal working memory (VWM; digit span backwards), visuospatial working memory (VSWM, Corsi Blocks backwards), sex, socioeconomic status, and IQ were included as covariates.

RESULTS

In a moderated mediation model, stimulus discriminability mediated the effect of ADHD on reading ability. This indirect effect was moderated by age such that a larger effect was seen among younger children.

CONCLUSION

The findings support the hypothesis that ADHD and reading ability are linked among young children via a neuropsychological deficit related to stimulus discriminability. Early interventions targeting stimulus discriminability might improve symptoms of inattention/hyperactivity and reading ability.

Combined Modality Intervention for ADHD With Comorbid Reading Disorders: A Proof of Concept Study

To evaluate the relative efficacy of two reading programs with and without adjunctive stimulant medication for children with attention-deficit/hyperactivity disorder and comorbid reading disorder (ADHD+RD). Sixty-five children (7-11 years in age) were assigned randomly to one of three intensive remedial academic programs (phonologically or strategy-based reading instruction, or general academic strategy and social skills training) in combination with either immediate-release methylphenidate or placebo. Multiple-blind procedures were used for medication/placebo, given twice daily. Children received 35 hours of instruction in 10 weeks, taught by a trained teacher in a separate school classroom, in small matched groups of 2 to 3. Children's behavior and reading abilities were assessed before and after intervention. Stimulant medication produced expected beneficial effects on hyperactive/impulsive behavioral symptoms (reported by classroom teachers) but none on reading. Children receiving a reading program showed greater gains than controls on multiple standardized measures of reading and related skills (regardless of medication status). Small sample sizes precluded interpretation of possible potentiating effects of stimulant medication on reading skills taught in particular reading programs. Intensive reading instruction, regardless of treatment with stimulant medication, may be efficacious in improving reading problems in children with ADHD+RD and warrants further investigation in a large-scale study.

Testing for the mediating role of endophenotypes using molecular genetic data in a twin study of ADHD traits

Family and twin studies have identified endophenotypes that capture familial and genetic risk in attention-deficit/hyperactivity disorder (ADHD), but it remains unclear if they lie on the causal pathway. Here, we illustrate a stepwise approach to identifying intermediate phenotypes. First, we use previous quantitative genetic findings to delineate the expected pattern of genetically correlated phenotypes. Second, we identify overlapping genetic associations with ADHD-related quantitative traits. Finally, we test for the mediating role of associated endophenotypes. We applied this approach to a sample of 1,312 twins aged 7-10. Based on previous twin model-fitting analyses, we selected hyperactivity-impulsivity, inattention, reading difficulties (RD), reaction time variability (RTV) and commission errors (CE), and tested for association with selected ADHD risk alleles. For nominally significant associations with both a symptom and a cognitive variable, matching the expected pattern based on previous genetic correlations, we performed mediation analysis to distinguish pleiotropic from mediating effects. The strongest association was observed for the rs7984966 SNP in the serotonin receptor gene (HTR2A), and RTV (P = 0.007; unadjusted for multiple testing). Mediation analysis suggested that CE (38%) and RTV (44%) substantially mediated the association between inattention and the T-allele of SNP rs3785157 in the norepinephrine transporter gene (SLC6A2) and the T-allele of SNP rs7984966 in HTR2A, respectively. The SNPs tag risk-haplotypes but are not thought to be functionally significant. While these exploratory findings are preliminary, requiring replication, this study demonstrates the value of this approach that can be adapted to the investigation of multiple genetic markers and polygenic risk scores. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

Cognitive and neurophysiological markers of ADHD persistence and remission

BACKGROUND

Attention-deficit hyperactivity disorder (ADHD) persists in around two-thirds of individuals in adolescence and early adulthood.

AIMS

To examine the cognitive and neurophysiological processes underlying the persistence or remission of ADHD.

METHOD

Follow-up data were obtained from 110 young people with childhood ADHD and 169 controls on cognitive, electroencephalogram frequency, event-related potential (ERP) and actigraph movement measures after 6 years.

RESULTS

ADHD persisters differed from remitters on preparation-vigilance measures (contingent negative variation, delta activity, reaction time variability and omission errors), IQ and actigraph count, but not on executive control measures of inhibition or working memory (nogo-P3 amplitudes, commission errors and digit span backwards).

CONCLUSIONS

Preparation-vigilance measures were markers of remission, improving concurrently with ADHD symptoms, whereas executive control measures were not sensitive to ADHD persistence/remission. For IQ, the present and previous results combined suggest a role in moderating ADHD outcome. These findings fit with previously identified aetiological separation of the cognitive impairments in ADHD. The strongest candidates for the development of non-pharmacological interventions involving cognitive training and neurofeedback are the preparation-vigilance processes that were markers of ADHD remission.

The aetiological association between the dynamics of cortisol productivity and ADHD

Attention-deficit/hyperactivity disorder (ADHD) has been linked to dysregulation of the hypothalamic–pituitary–adrenal (HPA) axis, indexed by salivary cortisol. The phenotypic and aetiological association of cortisol productivity with ADHD was investigated. A selected twin design using 68 male twin-pairs aged 12–15, concordant or discordant for high ADHD symptom scores, or control twin-pairs with low ADHD symptoms, based on developmentally stable parental ADHD ratings. A genetic growth curve model was applied to cortisol samples obtained across three points during a cognitive-electroencephalography assessment, to examine the aetiological overlap of ADHD affection status (high versus low ADHD symptom scores) with latent intercept and slope factors. A significant phenotypic correlation emerged between ADHD and the slope factor, with cortisol levels dropping faster for the group with high ADHD symptom scores. The analyses further suggested this overlap was mostly driven by correlated genetic effects. We identified change in cortisol activity over time as significantly associated with ADHD affection status, primarily explained by shared genetic effects, suggesting that blunted cortisol productivity can be a marker of genetic risk in ADHD.

Differences in the performance of NK1R-/- ('knockout') and wildtype mice in the 5‑Choice Continuous Performance Test

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We compared the behaviour of NK1R−/− mice and wildtypes in the 5-Choice Continuous Performance Test.

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NK1R−/− mice did not express excess impulsivity (premature response or false alarms) in this test.

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NK1R−/− mice expressed excessive perseveration, which is common in ADHD.

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The findings point to a behavioural phenotype for ADHD patients with polymorphism of the TACR1 gene.

Mice lacking functional NK1 (substance P-preferring) receptors typically display excessive inattentiveness (omission errors) and impulsivity (premature responses) when compared with wildtypes in the 5-Choice Serial Reaction-Time Test (5-CSRTT). These abnormal behaviours are analogous to those seen in humans suffering from Attention Deficit Hyperactivity Disorder (ADHD). Here we used the 5-Choice Continuous‑Performance Test (5C-CPT) to ascertain whether NK1R−/− mice also display excessive false alarms (an inappropriate response to a ‘no-go’ signal), which is another form of impulsive behaviour. NK1R−/− mice completed more trials than wildtypes, confirming their ability to learn and carry out the task. At the start of Stage 1 of training, but not subsequently, they also scored more premature responses than wildtypes. When the mice were tested for the first time, neither false alarms nor premature responses was higher in NK1R−/− mice than wildtypes but, as in the 5-CSRTT, the latter behaviour was strongly dependent on time of day. NK1R−/− mice expressed excessive perseveration during all stages of the 5C-CPT. This behaviour is thought to reflect compulsive checking, which is common in ADHD patients. These findings point to differences in the 5-CSRTT and 5C-CPT protocols that could be important for distinguishing why the cognitive performance and response control of NK1R−/− mice differs from their wildtypes. The results further lead to the prediction that ADHD patients with polymorphism of the TACR1 gene (the human equivalent of Nk1r) would express more perseveration, but not false alarms, in Continuous Performance Tests when compared with other groups of subjects.