EEG-Based Effective Connectivity Analysis for Attention Deficit Hyperactivity Disorder Detection Using Color-Coded Granger-Causality Images and Custom Convolutional Neural Network

Prospective Follow-up Studies of ADHD: Helping Establish a Valid Diagnosis in Adults

Can Guidelines Help Reduce the Medicalization of Early Childhood?

Bronchial asthma is closely related to the occurrence of attention-deficit hyperactivity disorder (ADHD) in children, which can easily have adverse effects on children's learning and social interactions. Studies have shown that childhood asthma can increase the risk of ADHD and the core symptoms of ADHD. Compared with children with ADHD alone, children with asthma and ADHD are more likely to show high levels of hyperactivity, hyperactive-impulsive and other externalizing behaviors and anxiety in clinical practice and have more symptoms of somatization and emotional internalization. To explore the relationship between ADHD in children and bronchial asthma and to analyze its influencing factors. This retrospective cohort study was conducted at Dongying People's Hospital from September 2018 to August 2023. Children diagnosed with ADHD at this hospital were selected as the ADHD group, while healthy children without ADHD who underwent physical examinations during the same period served as the control group. Clinical and parental data were collected for all participating children, and multivariate logistic regression analysis was employed to identify risk factors for comorbid asthma in children with ADHD. Significant differences were detected between the ADHD group and the control group in terms of family history of asthma and allergic diseases, maternal complications during pregnancy, maternal use of asthma and allergy medications during pregnancy, maternal anxiety and depression during pregnancy, and parental relationship status (P < 0.05). Out of the 183 children in the ADHD group, 25 had comorbid asthma, resulting in a comorbidity rate of 13.66% (25/183), compared to the comorbidity rate of 2.91% (16/549) among the 549 children in the control group. The difference in the asthma comorbidity rate between the two groups was statistically significant (P < 0.05). The results of the multivariate logistic regression analysis indicated that family history of asthma and allergic diseases, maternal complications during pregnancy, maternal use of asthma and allergy medications during pregnancy, maternal anxiety and depression during pregnancy, and parental relationship status are independent risk factors increasing the risk of comorbid asthma in children with ADHD (P < 0.05). Children with ADHD were more likely to have comorbid asthma than healthy control children were. A family history of asthma, adverse maternal factors during pregnancy, and parental relationship status were identified as risk factors influencing the comorbidity of asthma in children with ADHD. Clinically, targeted interventions based on these factors can be implemented to reduce the risk of comorbid asthma. This information is relevant for results sections of abstracts in scientific articles.

Diagnosis of Attention Deficit Hyperactivity Disorder by Using MR Imaging and Radiomics: A Potential Tool for Clinicians.

Development of attentional processes in ADHD and normal children

Family, twin, and adoption studies show attention deficit hyperactivity disorder (ADHD) to have a substantial genetic component, and some studies have reported an association between ADHD and the dopamine D4 (DRD4) gene. The authors recruited 27 triads that comprised an ADHD adult, his or her spouse, and their ADHD child. These triads were assessed for ADHD, and their DNA was genotyped for DRD4 alleles. A multiallelic transmission disequilibrium test suggested an association between ADHD and the DRD4 7-repeat allele. Among family members, the number of 7-repeat alleles predicted the diagnosis of ADHD. Prior reports of an association between ADHD and DRD4 generalize to families recruited through clinically referred ADHD adults. However, because there are some conflicting studies, further work is needed to clarify the role of DRD4 in the etiology of the disorder.

FIGURE 1. Changes in cortical thickness provide one measure of brain maturation. A large longitudinal study found that for most areas of cortex, children with attention deficit hyperactivity disorder (ADHD) reach peak cortical thickness several years later than typically developing children, supporting presence of developmental delay. The rate of cortical thinning also differed between the group who continued to meet diagnostic criteria into adulthood (persistent ADHD) and those who did not (remitted ADHD). Areas of cortex in which the rate of thinning correlated with adult symptom level (green, more symptoms associated with more thinning) are approximated on medial and lateral simplified representations of cortex. An earlier study also identified multiple areas in which cortex was thinner in adults with persistent ADHD compared with controls (orange). In addition, this study noted some areas of thicker cortex in remitted ADHD when compared with persistent ADHD (blue).

Background:Attention deficit hyperactivity disorder (ADHD) is the most common behavioral disorders in children and recent studies reported a relationship between low levels of Vitamin D and incidence of ADHD.Aim:The aim of this study was to investigate the association between vitamin D deficiency and attention deficit hyperactivity disorder (ADHD). Also, to study the impact and role of vitamin D on the development of ADH in children.Design:This is a case-control study which was conducted in children below 18 years of age from June 2011 to May 2013 at the School Health and Primary Health care Clinics, Qatar.Methods and subjects:The study was based on 1,331 cases and 1,331 controls. The data collection instrument included socio-demographic & clinical data, physician diagnosis family history, BMI, and serum 25(OH) vitamin D, calcium, albumin, billirubin, magnesium, calcium, cholesterol, urea, triglyceride and phosphorus. Descriptive and univariate statistical analysis were performed.Results:Of the total number of 3470 children surveyed, 1331 of ADHD and 1,331 of healthy children gave their consent to participate in this study. The mean age (± SD, in years) for ADHD versus control children was 10.63±3.4 vs. 10.77±3.4. Overweight (7.7% vs 9.4%) and obesity (4.6% vs 7.7%) were significantly lower in ADHD children compared to their counterparts (P=0.001). Vitamin D deficiency was considerably higher in ADHD children compared to healthy children. The mean value of vitamin D in ADHD children was much lower than the normal value and there was a significant difference found in the mean values of vitamin D between ADHD (16.6±7.8 with median 16) and control children (23.5±9.9) (p<0.0001) and with median 23 (p = 0.006). Mean values of Calcium and phosphorous were significantly higher in control compared to ADHD children (p<0.001). 1331 of all ADHD children had 19.1% had severe vitamin D deficiency (< 10 ng/ml), 44.9% has moderate insufficient levels (between 10-20 ng/ml), 27.3% has mild insufficient levels (between 20-30 ng/ml) and only 8.1% of ADHD had sufficient serum vitamin D levels (>30 ng/ml). Multivariate logistic regression analysis revealed that household income, poor relationship between parents, mothers’ occupation, consanguinity, BMI in percentiles, low duration of time under sun light, physical activity, low serum calcium level and low vitamin D level were considered as the main risk factors associated with the ADHD after adjusting for age, gender and other variables.Conclusion:The study showed that vitamin D deficiency was higher in ADHD children compared to healthy children. Supplementing infants with vitamin D might be a safe and effective strategy for reducing the risk of ADHD, but, further genomic and some other test and relevant studies need to be done.

Functional MRI revealed differences between children with Attention Deficit Hyperactivity Disorder (ADHD) and healthy controls in their frontal-striatal function and its modulation by methylphenidate during response inhibition. Children performed two go/no-go tasks with and without drug. ADHD children had impaired inhibitory control on both tasks. Off-drug frontal-striatal activation during response inhibition differed between ADHD and healthy children: ADHD children had greater frontal activation on one task and reduced striatal activation on the other task. Drug effects differed between ADHD and healthy children: The drug improved response inhibition in both groups on one task and only in ADHD children on the other task. The drug modulated brain activation during response inhibition on only one task: It increased frontal activation to an equal extent in both groups. In contrast, it increased striatal activation in ADHD children but reduced it in healthy children. These results suggest that ADHD is characterized by atypical frontal-striatal function and that methylphenidate affects striatal activation differently in ADHD than in healthy children.

Objective To explore the changes in brain structure network connection in children with attention deficit hyperactivity disorder(ADHD), and to provide novel markers for early identification of ADHD in clinical practice. Methods Deterministic diffusion-tensor tractography and graph theory approaches were used to investigate the topologic organization of the brain structural connectome in 25 children with ADHD and 23 healthy control children from May 2017 to May 2018, at Children′s Hospital of Xuzhou Medical University.Individual white matter networks were constructed for each participant, then the global properties, nodal properties and edge-wise distributions were compared between the two groups. Results (1)The global efficiency of the ADHD group (0.30±0.13) was significantly lower than that of the healthy control group (0.38±0.11), but the clustering coefficient (0.35±0.28) and the characteristic path length (2.94±0.38) were significantly higher than those of the healthy control group (0.28±0.10, 2.65±0.37), and the differences were statistically significant (t=-2.41, 2.31, 2.62, all P<0.05). (2)In the ADHD group, the nodal efficiency of the left inferior frontal gyrus, triangular part (0.13±0.06), left supramarginal gyrus (0.30±0.10), left inferior parietal, angular gyri (0.29±0.10), left precuneus (0.26±0.12)were significantly lower than the healthy control group(0.17±0.07, 0.38±0.10, 0.40±0.12, 0.35±0.12), while the nodal efficiency of the right superior frontal gyrus, orbital part and right paracentral lobule were significantly higher than the healthy control group(0.49±0.17, 0.43±0.14), and the differences were statistically significant[t=-2.52, -2.62, -3.11, -2.77, 2.34, 2.79, all P<0.05, false discovery rate(FDR) corrected]. (3)A disrupted subnetwork was observed that consisted of left frontoparietal areas, basal ganglia, thalamus and insular network (P<0.05, FDR corrected), which has the potential to discriminate individuals with ADHD from healthy control children(area under receiver operating characteristic curve was 0.78). (4)Diminished strength of the subnet work connections was correlated with the attention defect in patients with ADHD(r=-0.607, P=0.003). Conclusions Using magnetic resonance diffusion tensor imaging, with the help of graph theory analysis technology, ADHD children can be observed changes in brain structure network at multiple levels.The distribution pattern of brain network structure connection changes is expected to become a new marker for identifying ADHD. Key words: Attention deficit hyperactivity disorder; Diffusion tensor image; Graph theory; Structural network

BackgroundFibromyalgia (FM) and attention deficit hyperactivity disorder (ADHD) share some clinical features, and a reduced dopamine function has been proposed for both disorders. ADHD is a chronic condition, marked by...

Dear Editor, Attention deficit hyperactivity disorder (ADHD), is a common, highly heritable childhood-onset psychiatric disorder affecting 2% – 6% of children worldwide. The recent paper examines the effects of child and adult ADHD symptoms in adults among male students on adult addiction acknowledgment and alcoholism potential (1). This article is an original study which provides that adult ADHD and child ADHD predict addiction acknowledgment while child ADHD and impulsivity predict alcohol potential. These findings add new evidence about prediction of adolescent and adult drug abuse and use by early ADHD. However, the biological mechanism of the relationship between ADHD and substance problems is still unclear. One of the important mechanisms is genetic correlation due to shared genetic loci. First, it has been shown that both ADHD and alcohol dependence have strong genetics components. Twin and adoption studies have indicated that ADHD has high heritability in the range of 75% – 91% (2), while family, twin, and adoption studies have revealed that genetic and environmental factors and their interactions contribute to the development of alcohol dependence, with a heritability of more than 50% (3). Second, ADHD has been found to be highly comorbid with nicotine dependence and alcohol dependence. Segregation analysis has provided multigenerational evidence of cosegregation among ADHD, nicotine dependence, and alcohol dependence, while linkage analysis has suggested several regions on human chromosomes with pleiotropic effects on ADHD and alcohol dependence (4). For example, significant linkages at 4q13.1 - 13.2 and 5q31 - 33 for ADHD has been implicated in alcohol dependence and nicotine dependence (4). Third, genetic association studies have suggested several genes which are responsible for both ADHD and alcohol dependence. For example, it has been reported associations between the dopamine transporter (DAT) gene polymorphisms and human disorders including ADHD and alcohol dependence (5). The variants of the dopamine D2 receptor gene (DRD2) has been found to be associated with alcoholism, drug dependency, obesity, smoking, pathological gambling, ADHD, Tourette syndrome, as well as other related compulsive behaviors (6). The tachykinin receptor 1 (TACR1) gene has been reported to be associated with bipolar disorder and alcoholism as well as ADHD (2). However, parts of the associations are not strong and the results are not always consistent due to biologic mechanisms (genetic heterogeneity, gene-gene interactions and gene-environment interactions etc.) and spurious mechanisms (inadequacies of genomic markers, type 1 error, limited sample sizes and power, cohort and age effects, and bias etc.). In addition, some other genes, such as the nicotinic receptor CHRNA5-A3-B4 subunit genes, do not contribute to the common genetic predisposition of ADHD and alcohol dependence (2, 7). In short, the current results not only support previous studies about the relationship between ADHD and alcohol and drug dependence but also provide further evidence on prediction of future substance dependence in adulthood through early ADHD (1). However, the sample size for the current study is relative small; therefore the results need further investigation using large sample and confirmation in other populations. In addition, further genetic and epigenetic study to identify the disease-causing variants including gene-environment interactions in ADHD and alcohol dependence would have promise for understanding the pathogenesis of these comorbity psychiatric disorders, predicting the risks and developing potential treatments for ADHD and alcohol dependence.

Treatment Controversies in Adult ADHD.

Objective: To compare brain electrical cognitive tasks and brain development between study about 7 to 12 years old attention deficit hyperactivity disorder (ADHD) and normal children. Method: Prospectic case-control study was used. A total of 110 children with ADHD (63 boys and 47 girls) and 116 normal children (66 boys and 50 girls), were enrolled in this study. The electroencephalogram (EEG) was recorded when attention tasks were conducted, the EEG power was extracted from the original data and comparatively analyzed the absolute power (θ, α, β spectrum) and relative power (θ/total, α/total, θ/α, θ/β). Result: (1) Absolute power: ADHD children θ absolute power was higher than that of normal children in Pz lead ((52±28)vs. (40±30)μV2, t=3.906, P<0.05), with statistical significance. (2) Relative power: θ/total, θ/α, θ/β in ADHD are higher than normal children(0.23±0.07 vs. 0.20±0.05, 1.35±0.76 vs. 1.00±0.56, 4.75±2.49 vs. 3.56±2.08, t=2.900 and 3.954 and 3.901, P=0.004 and 0.000 and 0.000), α/total in ADHD is lower (0.21±0.09 vs. 0.24±0.10, t=-2.517, P=0.013). (3) The comparative study of the development of EEG power θ/β between ADHD and normal children showed age-related correlation in both groups (r=-0.378 and -0.398, P=0.000 for both). Conclusion: ADHD children's EEG power on slow spectrum was higher than that of the normal children, it was more significant in the parietal region than in frontal region. With the increase of age, the θ relative power in ADHD and normal children gradually declined, in the normal children it linearly related, but in ADHD there was no significant regularity. θ/β can be used as a sensitive index to assess ADHD children's cognitive function.

Background &amp; Aim: Attention deficit hyperactivity disorder (ADHD) is the most common mental health disorder among young children that affects the mothers’ lifestyles The aim of the present study was to consider the quality of life in Iranian mothers with ADHD children. Objective: In this comparative study, we compared the quality of life between mothers of ADHD children and mothers of normal children. Methods: In this descriptive study (2018-2019), a total of 75 mothers with ADHD children and 75 mothers with normal children, who were referred to referral educational hospital (Rasoul Hospital; Tehran, Iran) were evaluated. ADHD criteria were assessed by means of the SNAP-IV questionnaire, while the quality of life was evaluated by the SF-36 questionnaire. All data were analyzed by SPSS software. The environmental, mental, social physical, health and quality of life were compared between 2 groups. Results: The economic situation of mothers with normal children was average (73.3%) to good (16%), while in mothers with ADHD children the economic situation was average (45.3%) to poor (37.3%). Mothers’ employment in normal children group was 41.3%, but it was 14.6% in mothers with ADHD children. A significant difference was reported between two groups in the mean of environmental health score (p&lt;0.05), social relationships (p&lt;0.05), mental health (p&lt;0.05), physical health (p&lt;0.01) and quality of life (p&lt;0.01). The mean score of environmental health, social relationships, mental health, physical health and quality of life in ADHD mothers was significantly lower than mothers with normal children. Conclusion: The difficulties in the management of ADHD children negatively affect the quality of mothers’ lifestyles. Therefore, preventive, educational and therapeutic interventions are recommended to improve the mental health and the quality of life of mothers.