Attention Deficit Hyperactivity Disorder Subtypes Research Articles

Two neurosubtypes of ADHD different from the clinical phenotypes

Clinical and etiological variability of attention deficit hyperactivity disorder (ADHD) presents an obstacle to understand the disorder. The aim of this study was to disentangle the heterogeneity of ADHD using neuroimaging and a semi-supervised machine learning algorithm. We collected brain structural and functional magnetic resonance imaging (MRI) data and clinical profiles of 183 children with ADHD and 396 neurotypical controls from 7 independent sites. We also used an external validation set with 750 subjects. We adopted a semi-supervised clustering method to subtype ADHD by regional volumetric measures of gray matter, white matter, and fractional amplitude of low frequency fluctuation (fALFF). In addition, split sample test, leave-one-site-out test and external validation were applied to evaluate the reproducibility and stability of ADHD subtypes. Two stable and reproducible neurosubtypes of ADHD were disclosed, which were proved by the split-sample test and leave-one-site-out validation. The structural and functional patterns of ADHD subtypes were also stable in the external validation set. The current two neurosubtypes differed in clinical manifestations and volumetric gray matter, white matter volume and fALFF patterns. The current neurosubtypes of ADHD which were different from clinical phenotypes could facilitate understanding the underlying neuropathological and neurobiological mechanism of the disorder.

Data-driven profiles of attention-deficit/hyperactivity disorder using objective and ecological measures of attention, distractibility, and hyperactivity

In the past two decades, the traditional nosology of attention-deficit/hyperactivity disorder (ADHD) has been criticized for having insufficient discriminant validity. In line with current trends, in the present study, we combined a data-driven approach with the advantages of virtual reality aiming to identify novel behavioral profiles of ADHD based on ecological and performance-based measures of inattention, impulsivity, and hyperactivity. One hundred and ten Spanish-speaking participants (6–16 years) with ADHD (medication-naïve, n = 57) and typically developing participants (n = 53) completed AULA, a continuous performance test embedded in virtual reality. We performed hybrid hierarchical k-means clustering methods over the whole sample on the normalized t-scores of AULA main indices. A five-cluster structure was the most optimal solution. We did not replicate ADHD subtypes. Instead, we identified two clusters sharing clinical scores on attention indices, susceptibility to distraction, and head motor activity, but with opposing scores on mean reaction time and commission errors; two clusters with good performance; and one cluster with average scores but increased response variability and slow RT. DSM-5 subtypes cut across cluster profiles. Our results suggest that latency of response and response inhibition could serve to distinguish among ADHD subpopulations and guide neuropsychological interventions. Motor activity, in contrast, seems to be a common feature among ADHD subgroups. This study highlights the poor feasibility of categorical systems to parse ADHD heterogeneity and the added value of data-driven approaches and VR-based assessments to obtain an accurate characterization of cognitive functioning in individuals with and without ADHD.

Comprehensive review of EEG data classification techniques for ADHD detection using machine learning and deep learning

Children who have Attention-Deficit/Hyperactivity Disorder (ADHD) have a chronic behavioral disease. Children with ADHD have a hard time focusing and controlling their actions. One of the most difficult problems in controlling and treating this condition is early detection. There is yet to be discovered a reliable professional procedure for early detection of this condition. The electroencephalogram (EEG) is a useful neuroimaging technique for researching ADHD; one of the key goals is to define the EEG of ADHD youngsters. Numerous methods based on EEG signals have been put out in the literature to address this issue since they are an effective neuroimaging approach for studying ADHD. The best recording formats and channels for diagnosing ADHD, however, have not been the subject of many research. Machine learning (ML) and Artificial Intelligence (AI) strategies for identifying ADHD using EEG-based tools are discussed in this paper. Although, in the case of ADHD, the utilization of ML and AI approaches is restricted. However, the data clearly imply that combining EEG technologies with ML/AI may be utilized to detect ADHD. For categorizing adult ADHD subtypes based on EEG power spectra, ML algorithms that incorporate several classifiers are presented. A widely used deep learning (DL) method is the convolutional neural network (CNN). The use of DL approaches in ADHD research, on the other hand, is currently restricted. EEG has been used in studies to look for ADHD neurological connections. Recent advances in deep learning algorithms, particularly CNN, are anticipated to overcome the issue.

Timing and delay discounting in attention-deficit/hyperactivity disorder: A translational approach.

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder that often presents with abnormal time perception and increased impulsive choice behavior. The spontaneously hypertensive rat (SHR) is the most widely used preclinical model of the ADHD-Combined and ADHD-Hyperactive/Impulsive subtypes of the disorder. However, when testing the spontaneously hypertensive rat from Charles River (SHR/NCrl) on timing and impulsive choice tasks, the appropriate control strain is not clear, and it is possible that one of the possible control strains, the Wistar Kyoto from Charles River (WKY/NCrl), is an appropriate model for ADHD-Predominately Inattentive. Our goals were to test the SHR/NCrl, WKY/NCrl, and Wistar (WI; the progenitor strain for the SHR/NCrl and WKY/NCrl) strains on time perception and impulsive choice tasks to assess the validity of SHR/NCrl and WKY/NCrl as models of ADHD, and the validity of the WI strain as a control. We also sought to assess impulsive choice behavior in humans diagnosed with the three subtypes of ADHD and compare them with our findings from the preclinical models. We found SHR/NCrl rats timed faster and were more impulsive than WKY/NCrl and WI rats, and human participants diagnosed with ADHD were more impulsive compared to controls, but there were no differences between the three ADHD subtypes.

Treatment of US Children With Attention-Deficit/Hyperactivity Disorder in the Adolescent Brain Cognitive Development Study

Characterizing the extent and pattern of unmet needs for treatment of children with attention-deficit/hyperactivity disorder (ADHD) could help target efforts to improve access to ADHD medications and outpatient mental health care. To describe current ADHD medication use and lifetime outpatient mental health care among a large national sample of children with ADHD. This study uses cross-sectional survey data from the first wave of the Adolescent Brain and Cognitive Development Study (n = 11 723), conducted from June 1, 2016, to October 15, 2018, among 1206 school children aged 9 and 10 years who met parent-reported Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) criteria for current ADHD. Statistical analysis was performed from March 23, 2022, to March 10, 2023. Current ADHD medications including stimulants and nonstimulants, lifetime outpatient mental health care, or either treatment. Weighted results are reported. Among a sample of 11 723 children, 1206 had parent-reported ADHD (aged 9-10 years; 826 boys [68.2%]; 759 White, non-Hispanic children [62.2%]), 149 (12.9%) were currently receiving ADHD medications. Children receiving ADHD medications included a significantly higher percentage of boys (15.7% [121 of 826]) than girls (7.0% [28 of 108]), White children (14.8% [104 of 759]) than Black children (9.4% [22 of 206]), children of parents without a high school education (32.2% [9 of 36]) than of parents with a bachelor's degree or higher (11.5% [84 of 715]), and children with the combined subtype of ADHD (17.0% [83 of 505]) than with the inattentive subtype (9.5% [49 of 523]). Approximately 26.2% of children (301 of 1206) with parent-reported ADHD had ever received outpatient mental health care. Children receiving outpatient mental health care included a significantly higher percentage of children whose parents had a high school education (36.2% [29 of 90]) or some college (31.0% [109 of 364]) than a bachelor's degree or higher (21.3% [153 of 715]), children with family incomes of less than $25 000 (36.5% [66 of 176]) or $25 000 to $49 999 (27.7% [47 of 174]) than $75 000 or more (20.1% [125 of 599]), and children with the combined subtype of ADHD (33.6% [166 of 505]) than with the predominantly inattentive subtype (20.0% [101 of 523]) or the hyperactive-impulsive subtype (22.4% [34 of 178]) of ADHD. This cross-sectional study of children with parent-reported ADHD suggests that most were not receiving ADHD medications and had never received outpatient mental health care. Gaps in treatment, which were not directly associated with socioeconomic disadvantage, underscore the challenges of improving communication and access to outpatient mental health care for children with ADHD.

Speech signal analysis as an aid to clinical diagnosis and assessment of mental health disorders

ObjectiveIn this study, we estimate speech features from different Verbal Fluency Tests (VFT) conditions to distinguish comorbid Bipolar Disorder (BD) in adults suffering from Attention Deficit Hyperactivity Disorder (ADHD) and to identify ADHD subtypes such as the inattentive (ADHD-I) from the combined one (ADHD-C). MethodsProsodic and spectral features in five conditions of VFTs were extracted and selected for the classification performed with machine learning methods. Specifically, a Support Vector Machine exploiting Recursive Features Elimination (SVM-RFE) has been trained with clinical scores and exploiting the within subject variability of speech features across VFT conditions. The final classification was optimized by combining the marginal classification outcomes obtained from the different VFTs using a voting scheme. ResultsOur results show that we successfully classify the ADHD+BD comorbidity and the ADHD subtypes according to clinician diagnosis. The results are discussed in the light of possible benefits of developing such approach within clinical research. ConclusionSignificant information is carried out by speech audio features acquired with VFTs, allowing to classify ADHD subtypes and comorbid patterns. This work clearly shows that the audio analysis of speech, along with properly designed speech tasks, is a candidate for the development of clinical decision support systems in psychiatry. SignificanceThis work represents a major contribution to the applications of speech analysis in ADHD subjects and could support clinicians by identifying objective biomarkers.

Using Digital Measurement-Based Care to Address Symptoms of Inattention, Hyperactivity, and Opposition in Youth: Retrospective Analysis of Bend Health.

Attention-deficit/hyperactivity disorder (ADHD) and associated behavioral disorders are highly prevalent in children and adolescents, yet many of them do not receive the care they need. Digital mental health interventions (DMHIs) may address this need by providing accessible and high-quality care. Given the necessity for high levels of caregiver and primary care practitioner involvement in addressing ADHD symptoms and behavioral problems, collaborative care interventions that adopt a whole-family approach may be particularly well suited to reduce symptoms of inattention, hyperactivity, and opposition in children and adolescents. The purpose of this study is to use member (ie, child and adolescent) data from Bend Health, Inc, a collaborative care DMHI that uses a whole-family approach to address child and adolescent mental health concerns, to (1) determine the effects of a collaborative care DMHI on inattention, hyperactivity, and oppositional symptoms in children and adolescents and (2) assess whether the effects of a collaborative care DMHI vary across ADHD subtypes and demographic factors. Caregivers of children and adolescents with elevated symptoms of inattention, hyperactivity, or opposition assessed their children's symptom severity approximately every 30 days while participating in Bend Health, Inc. Data from 107 children and adolescents aged 6-17 years who exhibited clinically elevated symptoms at baseline were used to assess symptom severity across monthly assessments (inattention symptom group: n=91, 85.0%; hyperactivity symptom group: n=48, 44.9%; oppositional symptom group: n=70, 65.4%). The majority of the sample exhibited elevated symptoms of at least 2 symptom types at baseline (n=67, 62.6%). Members received care for up to 5.52 months and attended between 0 and 10 coaching, therapy, or psychiatry sessions through Bend Health, Inc. For those with at least 2 assessments, 71.0% (n=22) showed improvements in inattention symptoms, 60.0% (n=9) showed improvements in hyperactivity symptoms, and 60.0% (n=12) showed improvements in oppositional symptoms. When considering group-level change over time, symptom severity decreased over the course of treatment with Bend Health, Inc, for inattention (average decrease=3.51 points, P=.001) and hyperactivity (average decrease=3.07 points, P=.049) but not for oppositional symptoms (average decrease=0.70 points, P=.26). There was a main effect of the duration of care on symptom severity (P<.001) such that each additional month of care was associated with lower symptom scores. This study offers promising early evidence that collaborative care DHMIs may facilitate improvements in ADHD symptoms among children and adolescents, addressing the growing need for accessible and high-quality care for behavioral health problems in the United States. However, additional follow-up studies bolstered by larger samples and control groups are necessary to further establish the robustness of these findings.

Hyperfocus symptom and internet addiction in individuals with attention-deficit/hyperactivity disorder trait.

Hyperfocus symptom is the intense concentration on a certain object. It is a common but often overlooked symptom in those with attention-deficit/hyperactivity disorder (ADHD). Hyperfocus disrupts attention control and results in a focus on inappropriate behaviors. It allows individuals to focus on internet use and make them use internet excessively. This excessive internet use can lead to an addiction. This study investigated the status of IA and hyperfocus, the mediation effect of hyperfocus in relation to IA, and the relationship between ADHD subtypes and hyperfocus in those with ADHD symptoms. This web-based cross-sectional study included 3,500 Japanese adults who completed internet-based questionnaires, which included the Adult ADHD Self-Report Scale (ASRS), Internet Addiction Test (IAT), and Hyperfocus Scale (HFS) to assess ADHD symptoms, internet dependence, and hyperfocus symptoms, respectively. The mediating role of HFS in the relationship between ASRS and IAT was assessed by mediation analysis. To analyze the relationship between hyperfocus symptoms and ADHD subtypes, we compared the correlation of HFS with the Inattention and Hyperactive Scores of ASRS. ADHD traits were associated with higher IAT scores (p < 0.001) and higher HFS scores (p < 0.001). Mediation analysis and bootstrap testing showed that HFS significantly mediated the association between ASRS and IAT. Analyses of ADHD subtypes demonstrated that HFS was significantly correlated with the Inattention (R = 0.597, p < 0.001) and Hyperactive (R = 0.523, p < 0.001) Scores. The correlation between HFS and the Inattention Score was significantly higher than that between HFS and the Hyperactive Score (p < 0.001). Our findings suggest that hyperfocus may play an important role in addictive behavior in ADHD as a manifestation of attentional control malfunction.

Prevalence of Personality Disorders in Adults With Attention Deficit Hyperactivity Disorder (ADHD)

Objective: To estimate the prevalence of PDs according to Millon’s evolution-based model among adult ADHD outpatients. Method: Cross-sectional study of consecutive patients referred to an adult ADHD clinic. PDs were evaluated with Millon Clinical Multiaxial Inventory–III (MCMI-III). Results: One-hundred-eighty-one participants had valid MCMI-III, of whom147 were diagnosed with ADHD. Mean age: 32.97, SD:11.56, females: 74 (50.3%). Among the 147 participants with ADHD, 29 (19.7%) did not meet criteria for any PD, 43 (29.3%) met the criteria for one PD, 34 (23.1%) for two PDs and the rest three or more. Most common PD was Dependent (n = 58) followed by Depressive (n = 45). Inattentive sub-type was associated with dependent PD, while combined type with antisocial, negativistic (passive/aggressive) and sadistic PD. Conclusion: Particular personality profiles were more common with different ADHD subtypes. Given the developmental origins of PD, further research may help identify possible links with childhood difficulties.

Response inhibition in children with different subtypes/presentations of attention deficit hyperactivity disorder: A near-infrared spectroscopy study.

Executive dysfunction in children with attention deficit hyperactivity disorder (ADHD) is thought to be closely related to the prefrontal cortex (PFC). However, there is controversy over the activation of the PFC in children with ADHD. Differences could be related to the subtype. Meanwhile, no study to date has used functional near-infrared spectroscopy (fNIRS) to explore the differences between subtypes. Thus, this study aimed to explore the activation of the PFC in children with different subtypes of ADHD during executive function task. Participants in this study include typically developing (TD) children (n = 28), ADHD-predominantly inattentive (ADHD-PI) (n = 39) and ADHD-combined (ADHD-C) (n = 24). To examine the executive function of ADHD, the Go/No-go task is chosen to assess the response inhibition function. The activation of PFC in all participants during the Go/No-go task was recorded by fNIRS. Meanwhile, behavioral data were also recorded. Both TD and ADHD children activated the right PFC [middle frontal gyrus (MFG) and inferior frontal gyrus (IFG)] during response inhibition. However, the range and degree of activation differed among these groups. Compared with TD children, those with ADHD-PI had a smaller extent of activation in the right PFC, and those with ADHD-C only had a tendency to enhance activation. In addition, children with ADHD-PI and ADHD-C had impaired activation of the temporal gyrus. Besides, compared with ADHD-C and TD, those with ADHD-PI also had impaired activation of the right precentral gyrus (PG), and the supplementary motor area (SMA). Compared with ADHD-PI, ADHD-C showed decreased activation of the right MFG. The activation of Ch34 (BA44, rPFC) in children with ADHD-PI and ADHD-C was negatively correlated with their clinical symptoms. The activation of the PFC in children with different subtypes of ADHD has both commonalities and differences. The degree of activation of the right PFC Ch34 in children with ADHD is negatively correlated with clinical symptoms. fNIRS could be served as a candidate hemodynamic biomarker for the diagnosis of ADHD.

Genetic association study between Astrotactin-2 (ASTN2) rs10817999 gene polymorphism and attention deficit hyperactivity disorder in Korean children

ASTN2 is an integral membrane protein whose role is necessary to neuronal migration's neural-glial adhesion. It has been reported its association of ASTN2 with attention deficit hyperactivity disorder (ADHD). ADHD is a heterogeneous disorder influenced by various environmental and genetic factors. Therefore, we analyzed the genetic association of ASTN2 rs10817999 and rs12376789, with ADHD in Korean children with ADHD and children without ADHD. A total of 472 samples (150 ADHD children and 322 controls) were analyzed in this study. There were no significant results of genotype and allele distribution in rs12376789. By contrast, rs10817999 showed significant genotype and allele frequency differences between the control and the cases (p = 0.003 and 0.001, respectively). The OR of ADHD children with the rs10817999 C/T genotype compare with control was 0.335 (95 % CI 0.126–0.893, p = 0.023) and rs10817999 T/T genotype compare with control was 4.406 (95 % CI 1.662–11.680, p = 0.001), and the OR with rs10817999 T allele versus C allele was 1.658 (95 % CI 1.217–2.260, p = 0.001). Significant associations were also observed in the dominant (p = 0.005) and the recessive (p = 0.008) genetic models. In the stratified analyses of ADHD subtypes and sex, we also observed a significant association of rs10817999 and ADHD (p < 0.05). In summary, we identified that the rs10817999 was associated with ADHD in Korean children. These findings may be used as a basis of replication in other ethnic groups or populations to clarify the possible role of this genetic variant in ADHD.

Left insular cortical thinning differentiates the inattentive and combined subtype of adult attention-deficit/hyperactivity disorder

BackgroundNeuroimaging studies in attention-deficit/hyperactivity disorder (ADHD) demonstrated decreased global gray matter volume. In terms of surface parameters, most investigations focused on cortical thickness with a multi-center MEGA-analysis indicating cortical thinning in children, but not in adults with ADHD.In this single-scanner study, for the first time in adult ADHD, we additionally examined metrics beyond cortical thickness and surface area, namely sulcal depth and fractal dimension as measures of cortical alteration and complexity. Unlike most previous studies, ADHD subtypes were considered. MethodsAs part of the Comparison of Methylphenidate and Psychotherapy in Adult ADHD Study (COMPAS), surface parameters were analyzed in 131 adults with ADHD (66 combined, 60 inattentive and 5 hyperactive/impulsive subtype) and 95 healthy controls with the Computational Anatomy Toolbox (CAT12) using Statistical Parametric Mapping Software (SPM). ResultsNeither at the vertex- nor at the region of interest-level, the ADHD and control group differed significantly with regard to cortical thickness, gyrification index, sulcal depth or fractal dimension. Contrasting the combined and the inattentive subtype, patients of the combined subtype showed a significant thinning of the left anterior insular cortex. Thinner left pars opercularis cortical thickness was associated with symptoms of hyperactivity/restlessness. ConclusionsResembling previous findings of a correlation of the left anterior insular gray matter volume with oppositional symptoms in adolescents with ADHD, we detected left anterior insular cortical thinning in the ADHD combined subtype. Left insular cortical thickness could represent a potential marker to distinguish the predominantly inattentive and the combined ADHD subtype in adulthood.

Links between excessive daytime sleepiness and EEG power and activation in two subtypes of ADHD

ObjectivesThis study aimed to replicate previously reported EEG characteristics between typically developing (TD) children and two subtypes of Attention Deficit Hyperactivity Disorder (ADHD) using a frontal, single-channel, dry-sensor portable EEG device, and explore whether differences are moderated by excessive daytime sleepiness (EDS). MethodsChildren with ADHD Inattentive (ADHD-I) and ADHD Combined presentation (ADHD-C) and typically-developing (TD) children (N = 34 in each group) had frontal EEG recorded during eyes-closed resting, eyes-open resting, and focus tasks. Participants also completed the Children’s Self-Report Sleep Patterns - Sleepiness Scale as a measure of EDS. ResultsConsistent with previous literature, there were increases in frontal delta and theta power in the ADHD-C compared to ADHD-I and TD groups, in all conditions. Novel power and activation effects in ADHD subtypes, as well as significant group and EDS interactions for alpha and beta power were also found. ConclusionsThese findings highlight the importance of considering ADHD subtypes and EDS when exploring EEG characteristics, and have important implications for the diagnosis and treatment of children with ADHD.

Clinical-functional characteristics of children with asthma and obstructive sleep apnea overlap associated with attention deficit hyperactivity disorder: A cross-sectional study.

Asthma and obstructive sleep apnea (OSA) are common chronic respiratory disorders in children. The relationship between asthma and OSA is bidirectional; these conditions share multiple epidemiological risk factors. Untreated OSA may cause attention deficit hyperactivity disorder (ADHD) symptoms. This study aimed to assess the prevalence of ADHD in asthmatic children with OSA and the link between asthma control and lung function of children with asthma and OSA. A total of 96 children aged 6-15 years diagnosed with asthma, according to the Global Initiative for Asthma (GINA) 2020, were enrolled in this study. All demographic data, including age, gender, body mass index, asthma control status, therapy, the Vanderbilt ADHD Diagnostic Parent Rating Scale, lung function, and exhaled nitric oxide, were collected. In addition, home respiratory polygraphy was used to identify OSA in study subjects. A total of 96 patients (8.4 ± 2.4 years) were included in the present study. OSA was identified in 60.4% of asthmatic children with a mean apnea-hypopnea index (AHI) of 3.5 ± 3.0 event/h. The inattentive ADHD subtype was significantly lower in the non-OSA asthmatic group than in the OSA asthmatic group (7.9 vs. 34.5%, p < 0.05). ADHD had a higher probability of presence (OR: 3.355; 95% CI: 1.271-8.859; p < 0.05) in the OSA group (AHI >1 event/h). Children with poorly controlled asthma had a significantly high risk of OSA (83.0 vs. 17.0%, p < 0.001) than children with well-controlled asthma. Allergic rhinitis increased the odds of having OSA in patients with asthma [OR: 8.217 (95% CI: 3.216-20.996); p < 0.05]. The prevalence of OSA is increased among poorly controlled asthma. ADHD may have a higher prevalence in children with OSA. Therefore, prompt diagnosis of OSA will lead to an accurate asthma control strategy in patients with asthma.

Sleep Disorders and Attention-Deficit/ Hyperactivity Disorder in Children: A HospitalBased Observational Study from a Regional Early Intervention Centre in Kerala, India

Introduction: Attention Deficit Hyperactivity Disorder (ADHD) is one of the most extensively studied neurobehavioural disorders of childhood. The association of sleep disorders with ADHD is multidimensional, and understanding them is important in effectively managing patients with ADHD. Aim: To examine the presence of sleep disorders in children with ADHD, to correlate it with parameters of age and ADHD subtypes, and to find out the association between sleep disorders and other socio-demographic, and clinical factors. Materials and Methods: The study sample of this hospitalbased observational study consisted of 70 subjects who presented to the Regional Early Intervention Centre (REIC), Thrissur, diagnosed with ADHD based on DSM 5 criteria and belonging to the age group 5-16 years. Subjects were interviewed using a structured questionnaire to assess sociodemographic and clinical details. The ‘Sleep Disturbance Scale for Children’ (SDS-C) was used to assess sleep disorders in children. The information thus obtained was analysed using SPSS software version 23. Results: Out of the 70 subjects with ADHD, 49 (70%) had sleep disorders. The mean age of study population was 8.66±2.72 years, and the male:female ratio was 4:1. There was comorbid behavioural disorder in 32 subjects (45.7%), and parental history of ADHD in 33 subjects (47.1%). There was a significant association between sleep disorders and behavioural disorders (p-value=0.003) and parental history of ADHD (p-value=0.042). There was a significant negative correlation between age and sleep disorder (p-value=0.033). Conclusion: The prevalence of sleep disorders in ADHD is high in the study population. The relationship between sleep disorders and the presence of comorbid behavioural disorders in ADHD suggests that recognition and management of sleep disorders may require more attention. The association between sleep disorder and parental history of ADHD may enhance the understanding of genomic variants associated with ADHD.

Comparison of Leptin, Leptin Receptor, Vitamin D and Brain-Derived Neurotrophic Factor Levels in Major Depressive Disorder and Attention Deficit and Hyperactivity Disorder in Children and Adolescents

Objective: Data on effects of vitamins, hormones and neurotrophic factors on the etiology of attention deficit hyperactivity disorder (ADHD) and major depressive disorder (MDD) in children is limited. We hypothesized that serum vitamin D, brain-derived neurotrophic factor (BDNF), leptin, and leptin receptor levels are different in these patients, and that aforementioned biomarkers may affect symptom severity and risk of suicide. Methods: This study included 33 ADHD, 29 MDD patients and 35 healthy controls. The Turgay DSM-IV-Based Child and Adolescent Disruptive Behavioral Disorders Screening and Rating Scale (T-DSM-IV-S) was used to assess the severity of ADHD, while Children Depression Inventory (CDI) and the Suicide Probability Scale (SPS) were used to measure the severity of depression and suicide risk in the MDD group. Serum vitamin D, BDNF, leptin, and leptin receptor levels were measured from participants’ venous blood samples. Results: Vitamin D and leptin receptor levels were significantly higher in the control group than in the patient groups, and leptin levels were significantly higher in the ADHD group than in the MDD and control groups. There was no difference between the groups in terms of BDNF levels. No significant correlations between ADHD duration, subtype, severity, depression severity, suicide risk, and vitamin D, BDNF, leptin, and leptin receptor levels were found. Conclusion: Although current research supports that BDNF, vitamin D, leptin, and leptin receptor levels may be involved in the etiopathogenesis of MDD and ADHD, large-scale studies are needed to better evaluate the effects of these factors.

Comparison of serum vitamin D levels between healthy and ADHD children.

The most common psychiatric disorder in childhood is Attention-deficit/hyperactivity disorder (ADHD). Researchers have studied the effects of micronutrients on ADHD in recent years, but vitamin D (vit D) deficiency has received less attention. In this study, serum vit D levels were compared between healthy and ADHD children. This case-control study was carried out, in 2020, on 6-to-12-years-old children. There were 45 children with ADHD in the case group and 45 healthy children in the control group. Intravenous blood samples were taken from each child to measure serum vitamin D levels. A p-value < 0.05 was considered as significant. Mean serum vit D levels in children with ADHD (17.34±8.37 ng / ml) were significantly lower than those in the control group (23.02±10.97 ng / ml) (P= 0.007). There were no significant differences in mean serum levels of vit D due to ADHD subtypes. Mean serum vit D levels were not significantly associated with the gender of children with ADHD. There was an inverse correlation between vit D levels and the severity of ADHD, but it was not statistically significant. The present study showed that children with ADHD had significantly lower serum vit D levels than healthy controls.

Attention-Deficit/Hyperactivity Disorder and Problematic Romantic Relationships in Adulthood: A Review of the Literature

Attention-Deficit/Hyperactivity Disorder (ADHD) is one of the most prominent neurodevelopmental disorders worldwide. Although viewed as a childhood behavioural disorder, longitudinal research has shown that ADHD symptoms frequently persist into adolescence and adulthood. Although previously overshadowed in the research literature, more attention is now being given to the connection between ADHD and romantic relationships in adults. This inattention can be attributed to the prioritization of child and adolescent populations and the emphasis on psychoeducational, cognitive, and behavioural problems. However, with the emergence of executive function (EF) models, more researchers are exploring the breadth of possible ADHD-related problems. In the past five years especially, studies have been pursuing the relational and emotional challenges faced by those with ADHD and their partners. Given the prevalence and extent of ADHD-related challenges, it is vital to identify how relationship problems emerge and provide effectivepsychosocial coping strategies for romantic partners to mitigate relationship dissatisfaction and turnover. This literature review evaluates research studies on ADHD and romantic relationships by exploring factors such as divorce rates, marital satisfaction, relationship length, negative emotions and habits, and distinctions between ADHD subtypes. This analysis identifies potential gaps in the literature and problems concerning replicability, generalizability, and sample representation in ADHD-related research studies. It then concludes by providing intervention suggestions for those involved in ADHD relationships.

School attendance problems in adolescent with attention deficit hyperactivity disorder.

Introduction: A link between having a neurodevelopmental disorder, such as attention deficit hyperactivity disorder (ADHD) and school absenteeism, has been found in previous studies. Why ADHD poses a risk for absenteeism remains unclear, and insight into the mechanisms of the association is needed. The aim of the present study was to investigate school attendance problems (SAP) and both the symptoms related and the perceived reasons for them, as reported by adolescents with ADHD (n = 95), compared with neurotypical adolescents (n = 1,474). Method: The current study (N = 1,569) was part of the School absence in Finland-project. SAPs were measured with the Inventory of School Attendance Problems (ISAP). The ISAP questionnaire contains a symptom scale (ISAP S) and a function scale (ISAP F), which shows if and how the symptoms impacts school attendance. A linear mixed effects model was used to analyze outcomes on the ISAP factors, controlling for background variables living status, gender, other diagnoses, highest level of education for the parent and age. Results: Results show that adolescents with ADHD had been more absent from school compared to neurotypical adolescents during the prior 12-weeks. Adolescents with ADHD showed significantly more symptoms of agoraphobia/panic, problems within the family and problems with parents than neurotypical peers. The symptoms separation anxiety, agoraphobia/panic, aggression, problems within the family and problems with parents more often were perceived as the reason for SAP (ISAP F). Discussion: The results are in line with our initial hypotheses and previous studies. Because of the low response rate on the ISAP F scale, the results regarding reasons for SAPs should be interpreted with caution. Future research could examine specific preventive actions of SAPs for adolescents with ADHD, and different subtypes of ADHD.

Characteristics of Attention-Deficit/Hyperactivity Disorder Subtypes in Children Classified Using Quantitative Electroencephalography.

This study used quantitative electroencephalography (QEEG) to investigate the characteristics of attention-deficit/hyperactivity disorder (ADHD) subtypes in children. There were 69 subjects (42 with ADHD and 27 neurotypical (NT)) in this study. A semi-structured interview was conducted with each participant for psychiatric diagnostic evaluation. We measured the absolute and relative power in 19 channels and analyzed QEEG using the following frequency ranges: delta (1-4 Hz), theta (4-8 Hz), alpha 1 (8-10 Hz), alpha 2 (10-12 Hz), beta 1 (12-15 Hz), beta 2 (15-20 Hz), beta 3 (20-30 Hz), and gamma (30-45 Hz). Group analyses and EEG noise preprocessing were conducted using iSyncBrain, a cloud-based, artificial intelligence EEG analysis platform. Analysis of covariance adjusted for IQ, age, and sex was used. QEEG analysis revealed three ADHD subtypes, characterized by (A) elevated relative fast alpha and beta power, (B) elevated absolute slow frequency (delta and theta power), or (C) elevated absolute and relative beta power. A significant difference was found in the Korean ADHD Rating Scale (K-ARS) among the four groups (df=3, F=8.004, p<0.001); group C had the highest score (25.31±11.16), followed by group A (21.67±13.18). The score of group B (12.64±7.84) was similar to that of the NT group (11.07±6.12) and did not reach the cut-off point of the K-ARS. In the Wender-Utah Rating Scale (WURS), group B score (55.82±23.17) was significantly higher than the NT group score (42.81±13.26). These results indicate that children with ADHD do not constitute a neurophysiologically homogenous group. Children with QEEG subtype B (elevated slow frequency) may be difficult to distinguish from normal children using the K-ARS, which is the most common screening tool for ADHD. Moreover, parents of children with this subtype may be less sensitive to observing ADHD symptoms.