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Related Concept Videos

Attention-Deficit/Hyperactivity Disorder01:30

Attention-Deficit/Hyperactivity Disorder

67
Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by persistent inattention, hyperactivity, and impulsivity. It affects approximately 5-8% of children globally, with around 60-70% of cases persisting into adulthood. ADHD has significant implications for educational attainment, social interactions, and occupational success.
Diagnostic Criteria and Symptoms
To diagnose ADHD, symptoms must manifest before age 12 and be evident across multiple settings....
67

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Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
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Human transcriptome array analysis and diffusion tensor imaging in attention-deficit/hyperactivity disorder.

Liang-Jen Wang1, Sung-Chou Li2, Wen-Jiun Chou1

  • 1Department of Child and Adolescent Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan.

Journal of Psychiatric Research
|February 27, 2024
PubMed
Summary
This summary is machine-generated.

Researchers identified seven key mRNA markers in children with attention-deficit hyperactivity disorder (ADHD) using gene expression analysis. These markers, combined with diffusion tensor imaging (DTI), help predict ADHD and reveal insights into white matter changes.

Keywords:
ADHDBrain imagingDTITranscriptomeWhite mattermRNA

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Area of Science:

  • Neuroscience
  • Genetics
  • Biomarkers

Background:

  • Attention-deficit hyperactivity disorder (ADHD) is a complex neurodevelopmental disorder with unclear pathophysiology.
  • Genetic and microstructural brain alterations are implicated in ADHD, but specific biomarkers are needed.

Purpose of the Study:

  • To identify novel mRNA markers for attention-deficit hyperactivity disorder (ADHD) using microarray analysis.
  • To validate the diagnostic potential of selected mRNA markers via quantitative polymerase chain reaction (qRT-PCR).
  • To investigate the relationship between white matter microstructural integrity, assessed by diffusion tensor imaging (DTI), and ADHD-related gene expression.

Main Methods:

  • Microarray analysis of leukocyte RNA from ADHD patients and controls to identify candidate genes.
  • Real-time quantitative polymerase chain reaction (qRT-PCR) to validate differential expression of seven genes (COX7B, CYCS, TFAM, UTP14A, ZNF280C, IFT57, NDUFB5).
  • Development of an ADHD prediction model using gene expression data and diffusion tensor imaging (DTI) analysis of white matter tracts.

Main Results:

  • Seven genes (COX7B, CYCS, TFAM, UTP14A, ZNF280C, IFT57, NDUFB5) showed differential expression between ADHD patients and controls.
  • A prediction model based on these seven genes achieved high accuracy (AUROC = 0.98) in initial testing and (AUROC = 0.91) in validation.
  • Diffusion tensor imaging (DTI) revealed increased fractional anisotropy (FA) in specific white matter tracts in ADHD patients, with correlations between FA and specific gene expression levels.

Conclusions:

  • The identified seven mRNA markers show significant potential for ADHD diagnosis and prediction.
  • Gene expression patterns are linked to white matter microstructural abnormalities in ADHD.
  • This study provides a genetic profile that may aid in understanding the pathogenesis of ADHD.