Gray matter networks associated with attention and working memory deficit in ADHD across adolescence and adulthood

Ghozy

et al. 2022

Preprint

Purpose Adult ADHD is one of the most undiagnosed diseases mainly because of the misperception that ADHD is a childhood disease. In this study, we assess the characteristic features of adult ADHD using clinical assessment and structural Magnetic resonance imaging (sMRI) Methods We obtained structural MRI data from the UCLA Consortium for Neuropsychiatric Phenomics for 21 untreated adult ADHD patients and 21 age and gender propensity-matched control patients. For clinical assessment, we compared the scores of Barrat's impulsivity score, Dickman impulsivity inventory II, and Eysenck's Impulsivity Inventory. We then compared grey matter volume (GMV) between ADHD and control patients using a two-sample t-test. We also assessed the correlation between different clinical assessments and GMV. Results Based on our results, adult ADHD showed significantly higher impulsivity scores, however, no significant difference in functional impulsivity scores or empathy summary scores. For sMRI, there was a significant decrease of GMV of the left cuneus in female ADHD patients. For clinical assessment scales, only the motor impulsiveness subdomain showed a significant positive correlation with the GMV of the left precuneus. Conclusions In this study, we assessed the characteristic sMRI features and clinical assessment scores for untreated adult ADHD. Our results show that a study with a bigger sample size can identify diagnostic features for adult ADHD.

Section: Discussionsupporting

confidence: 92%

Clinical assessment and voxel-based morphometry study of untreated Adult Attention deficit hyperkinetic disorders patients

Ghozy

et al. 2022

Preprint

“…It has been suggested that the number of adults with ADHD has increased over the past 20 years, and some of this increase is explained by the persistence of ADHD symptoms in adulthood (Núñez-Jaramillo et al, 2021 ). As developmental brain processes alleviate some of the consequences of ADHD with neural normalization, the symptoms of hyperactivity disappear wherever they are in adulthood, but the persistence of the symptoms of inattention from childhood to adulthood is emphasized (Duan et al, 2021 ). As well as changes in ADHD symptoms throughout life, the variable and complex interaction of genetic and environmental factors is believed to play a role in the continuity of the disorder (Caye, et al, 2016 ).…”

mentioning

confidence: 99%

New Hematological Parameters as Inflammatory Biomarkers: Systemic Immune Inflammation Index, Platerethritis, and Platelet Distribution Width in Patients with Adult Attention Deficit Hyperactivity Disorder

Ceyhun

Gürbüzer

2022

Adv Neurodev Disord

Objectives The potential role of neuroinflammation in adult attention deficit hyperactivity disorder (ADHD) patients has been investigated with peripheral hemogram-related inflammatory markers. Systemic immune inflammation index (SII) is defined as a new index that has been developed for the balance of inflammatory and immune status. Methods Our study was based on a prospective routine complete blood count(CBC) analysis of 74 Adult ADHD patients and 70 healthy participants. The DSM-5-Clinician version and Barratt impulsivity scale-11 were used to evaluate the participants. Results There was no statistical difference in the comparison of the SII ratios, platelet distribution width (PDW), and plateretritis (PCT) ( p >0.05 for each) in a group of a young adults with ADHD and in a comparison control group. These inflammatory indicators were found to be similar between patients newly diagnosed with ADHD ( n =40) and patients using methylphenidate ( n =34) ( p >0.05 for each). The relationship between ADHD clinical symptoms and severity and inflammation was evaluated. A significant negative correlation was observed between attention deficit scores and PCT ( r =−0.301, p =0.009). A positive significant correlation was found between hyperactivity scores and SII ( r =0.247, p =0.034). A significant positive correlation was found between Barrat motor scores and PDW( r =241, p =0.038). In the regression analysis, the PCT variable changed the attention deficit variable ( β =.33, t (70)= −2.703, p =.009, pr 2 = .094) predicted negatively and significantly. Conclusions We demonstrated the association of SII, which is independently associated with adverse outcomes in many diseases, and the severity of hyperactivity symptoms in adult ADHD. The fact that PCT predicts attention deficit negatively and decisively shows the importance of inflammatory assessments specific to clinical presentations. The critical importance of platelets in inflammatory processes in ADHD has been demonstrated once again with inflammatory markers such as SII, PLT, and PDW, which can be accessed by an easily applicable complete blood count method.

“…In addition, the age difference between used subjects may also lead to such inconsistency. Duan et al investigated GM networks of two cohorts (adults and adolescents) and found that adolescent patients showed different GM volume changes than that of adult patients ( 11 ).…”

Section: Discussionmentioning

confidence: 99%

“…Focusing on abnormalities of ADHD-related neural networks rather than discrete neural substrates coincides with the development trend of the neuroimaging research. For adults and adolescents, GM network identified in adults compromising the bilateral cerebellar tonsil and culmen and GM network identified in adolescents compromising the left cerebellar region were significantly associated with inattention ( 11 ). Yet, few sMRI studies have investigated the brain network changes based on GM in children with ADHD, which may uncover the neural mechanism of ADHD and provide an objective basis for the diagnosis of ADHD.…”

Section: Introductionmentioning

confidence: 99%

Gray Matter Network Associated With Attention in Children With Attention Deficit Hyperactivity Disorder

Wang

Yang

et al. 2022

Front. Psychiatry

BackgroundAttention deficit hyperactivity disorder (ADHD) is one of the most prevalent childhood-onset neurodevelopmental disorders; however, the underlying neural mechanisms for the inattention symptom remain elusive for children with ADHD. At present, the majority of studies have analyzed the structural MRI (sMRI) with the univariate method, which fails to demonstrate the interregional covarying relationship of gray matter (GM) volumes among brain regions. The scaled subprofile model of principal component analysis (SSM-PCA) is a multivariate method, which can detect more robust brain-behavioral phenotype association compared to the univariate analysis method. This study aims to identify the GM network associated with attention in children with ADHD by applying SSM-PCA to the sMRI.MethodsThe sMRI of 209 children with ADHD and 209 typically developing controls (TDCs) aged 7–14 years from the ADHD-200 dataset was used for anatomical computation, and the GM volume in each brain region was acquired. Then, SSM-PCA was applied to the GM volumes of all the subjects to capture the GM network of children with ADHD (i.e., ADHD-related pattern). The relationship between the expression of ADHD-related pattern and inattention symptom was further investigated. Finally, the influence of sample size on the analysis of this study was explored.ResultsThe ADHD-related pattern mainly included putamen, pallium, caudate, thalamus, right accumbens, superior/middle/inferior frontal cortex, superior occipital cortex, superior parietal cortex, and left middle occipital cortex. In addition, the expression of the ADHD-related pattern was related to inattention scores measured by the Conners’ Parent Rating Scale long version (CPRS-LV; r = 0.25, p = 0.0004) and the DuPaul ADHD Rating Scale IV (ADHD-RS; r = 0.18, p = 0.03). Finally, we found that when the sample size was 252, the results of ADHD-related pattern were relatively reliable. Similarly, the sample size needed to be 162 when exploring the relationship between ADHD-related pattern and behavioral indicator measured by CPRS-LV.ConclusionWe captured a GM network associated with attention in children with ADHD, which is different from that in adolescents and adults with ADHD. Our findings may shed light on the diverse neural mechanisms of inattention and provide treatment targets for children with ADHD.