Availability of dopamine transporters and auditory P300 abnormalities in adults with attention-deficit hyperactivity disorder: preliminary results

CNS Spectrums ◽  
2017 ◽  
Vol 23 (4) ◽  
pp. 264-270 ◽  
Author(s):  
Ching-Lin Chu ◽  
I Hui Lee ◽  
Mei Hung Chi ◽  
Kao Chin Chen ◽  
Po See Chen ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Attention Deficit ◽  
Photon Emission ◽  
Event Related Potentials ◽  
P300 Amplitude ◽  
Emission Computed Tomography ◽  
Adhd Group ◽  
Hyperactivity Disorder ◽  
Auditory P300 ◽  
Related Potentials

ObjectivePrevious studies have indicated that there is dopamine transporter (DAT) dysregulation and P300 abnormality in adults with attention-deficit hyperactivity disorder (ADHD); however, the correlations among the three have not been fully explored.MethodsA total of 11 adults (9 males and 2 females) with ADHD and 11 age-, sex-, and education-level-matched controls were recruited. We explored differences in DAT availability using single-photon emission computed tomography and P300 wave of event-related potentials between the two groups. The correlation between DAT availability and P300 performance was also examined.ResultsDAT availability in the basal ganglia, caudate nucleus, and putamen was significantly lower in the ADHD group. Adults with ADHD had lower auditory P300 amplitudes at the Pz and Cz sites, as well as longer Fz latency than controls. DAT availability was negatively correlated to P300 latency at Pz and Fz.ConclusionsAdults with ADHD had both abnormal DAT availability and P300 amplitude, suggesting that ADHD is linked to dysfunction of the central dopaminergic system and poor cognitive processes related to response selection and execution.

scholarly journals Estimating the Biological Validity of the DSM for Attention Deficit/Hyperactivity Disorder Using Multivariate Analysis for Small Samples

2017 ◽  
Author(s):  
Dimitri M. Abramov ◽  
Evelyne Vigneau ◽  
Saint-Clair Gomes-Junior ◽  
Carlos Alberto Mourão-Júnior ◽  
Monique Castro-Pontes ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Multivariate Analysis ◽  
Attention Deficit ◽  
Latent Variables ◽  
Event Related Potentials ◽  
Small Samples ◽  
Large Dataset ◽  
Adhd Diagnosis ◽  
Hyperactivity Disorder ◽  
Related Potentials

AbstractBackground.Psychiatric nosology lacks objective biological foundation, as well as typical biomarkers for diagnoses, which raises questions about its validity. The problem is particularly evident concerning Attention Deficit/Hyperactivity Disorder (ADHD). The objective of this study is to estimate whether the “Diagnostic and Statistical Manual of Mental Disorders” (DSM) is biologically valid for ADHD diagnosis using a multivariate analysis for small samples from a large dataset concerning neurophysiological, behavioral, and psychological variables.Methods:Twenty typically developing boys and 19 boys diagnosed with ADHD, aged 10-13 years, were examined using the Attentional Network Test (ANT) with records of event-related potentials (ERPs). From 815 variables, a reduced number of latent variables (LVs) were extracted with a clustering method, for further reclassification of subjects using the k-means method. This approach allowed multivariate analysis to be applied to a significantly larger number of variables than the number of cases (E. Wigneau et al., 2003, 2015)Results:From datasets including ERPs from the mid-frontal, mid-parietal, right frontal, and central channels, only seven subjects were miss-reclassified by the LVs. An estimated specificity of 75.00% and sensitivity of 89.47% for DSM were found in the reclassification. The kappa index between DSM and behavioral/psychological/neurophysiological data was 0.75, which is regarded as a “substantial level of agreement”.Discussion:Results showed that CLV is a useful method for diagnostic classification using a large dataset of small samples, suggesting the biological validity of DSM for ADHD diagnosis, in accordance to alterations in fronto-striatal networks previously related to ADHD.

scholarly journals Estimating biological accuracy of DSM for attention deficit/hyperactivity disorder based on multivariate analysis for small samples

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7074 ◽  
Author(s):  
Dimitri M. Abramov ◽  
Vladimir V. Lazarev ◽  
Saint Clair Gomes Junior ◽  
Carlos Alberto Mourao-Junior ◽  
Monique Castro-Pontes ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Multivariate Analysis ◽  
Attention Deficit ◽  
Latent Variables ◽  
Event Related Potentials ◽  
Small Sample ◽  
Special Method ◽  
Kappa Index ◽  
Hyperactivity Disorder ◽  
Related Potentials

Objective To estimate whether the “Diagnostic and Statistical Manual of Mental Disorders” (DSM) is biologically accurate for the diagnosis of Attention Deficit/ Hyperactivity Disorder (ADHD) using a biological-based classifier built by a special method of multivariate analysis of a large dataset of a small sample (much more variables than subjects), holding neurophysiological, behavioral, and psychological variables. Methods Twenty typically developing boys and 19 boys diagnosed with ADHD, aged 10–13 years, were examined using the Attentional Network Test (ANT) with recordings of event-related potentials (ERPs). From 774 variables, a reduced number of latent variables (LVs) were extracted with a clustering of variables method (CLV), for further reclassification of subjects using the k-means method. This approach allowed a multivariate analysis to be applied to a significantly larger number of variables than the number of cases. Results From datasets including ERPs from the mid-frontal, mid-parietal, right frontal, and central scalp areas, we found 82% of agreement between DSM and biological-based classifications. The kappa index between DSM and behavioral/psychological/neurophysiological data was 0.75, which is regarded as a “substantial level of agreement”. Discussion The CLV is a useful method for multivariate analysis of datasets with much less subjects than variables. In this study, a correlation is found between the biological-based classifier and the DSM outputs for the classification of subjects as either ADHD or not. This result suggests that DSM clinically describes a biological condition, supporting its validity for ADHD diagnostics.

Sign in / Sign up

Export Citation Format

Share Document