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Previous studies have demonstrated significant associations of attention-deficit hyperactivity disorder (ADHD) with monoamine transporter genes, including dopamine transporter gene (DAT1), norepinephrine transporter gene (SLC6A2), and serotonin transporter gene (SLC6A4) as well as the important role of environmental factors in the pathogenesis of ADHD. Hence, investigating how genes and environments interact with each other may contribute to the understanding of the pathophysiological mechanisms of ADHD. In this 3-year project, investigators will explore the complex gene-environment interplay in ADHD with multimodal neurobiological approaches, including neuropsychology, neuroimaging, and metabolites, in order to identify the crucial pathophysiological pathways from genes to the brain.
In the present project, investigators aim to explore the complex gene-environment interplay in children with ADHD to identify the crucial pathophysiological pathways from genes to the brain. To achieve our objective, investigators will use multimodal neurobiological approaches to effectively resolve the four major challenges in exploring gene-environment interactions on ADHD.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| ADHD GROUP | Subjects with clinical diagnosis of ADHD according to the DSM-V criteria | ||
| TD GROUP | Typically development controls without lifetime diagnosis with ADHD |
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| Measure | Description | Time Frame |
|---|---|---|
| ADHD symptoms | Subjects will be interviewed by Chinese Version of the Kiddie Epidemiologic version of the Schedule for Affective Disorders and Schizophrenia (K-SADS-E) | 1 hour |
| Measure | Description | Time Frame |
|---|---|---|
| Neuropsychological testing | Subjects will be assessed by the Cambridge Neuropsychological Test Automated Battery (CANTAB) | 1.5 hours |
| Neuropsychological testing | Subjects will be assessed by the Continuous Performance Test |
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Inclusion Criteria:
Exclusion Criteria:
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120 drug-naïve patients with ADHD, aged 7-16, and 120 age- and sex-matched typically developing controls will be recruited in this project.
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| Name | Affiliation | Role |
|---|---|---|
| Susan Shur-Fen Gau, MD, PhD | Department of Psychiatry, National Taiwan University Hospital | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| National Taiwan University Hospital | Taipei | 110 | Taiwan | |||
| college of Medicine, National Taiwan University |
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DNA, plasma
| 15 mins |
| Metabolomics profiling | All the biomarkers are relative ratios. Although all the names of metabolites examined in this study cannot be listed due to the upper limitation of word number (999 characters), the metabolomics profiling includes Hydroxybutyric acid, Undecanedicarboxylic acid, Methyladenosine, Hydroxybutyric acid, Furoylglycine, Hydroxy, Hydroxybutyric acid, Hydroxycaproic acid,Oxoglutarate, Hydroxyisovaleric acid, Hydroxymethylglutaric acid,Indolepropionic acid, Methyladenine, Methylhistidine, Methylindole, Methylxanthine, Pyridylacetic acid, Guanidinobutanoic acid, Dihydrothymine, Aminolevulinic acid, Dodecenoic acid, Hydroxylysine P66-59, Methylcytidine, Acetoacetic acid, Acrylamide, Allose, AMP, Androstenedione, Aspartic acid, Betaine, Bradykinin, Carnitine, Cholic Acid, cis-Aconitate, cis-Fenpropimorph, citric acid, Corticosterone, Creatine, Creatinine, D-Arginine, Decanoylcarnitine, Dehydroascorbic acid, Deoxycholic acid, Deoxyribose, etc. | 10 mins |
| Brain imaging | Subjects will be assessed by structural and functional brain imaging, including xoxel-based morphometry, diffusion spectrum imaging, resting-state fMRI, and counting Stroop task fMRI | 1 hour |
| Taipei |
| Taiwan |