Attention Deficit Hyperactivity Disorder (ADHD) is a complex behavioral disorder that affects an estimated 5-10% of children in the United States. Recent research in ADHD suggests it is a complex behavioral phenotype that is the result of genetic heterogeneity with sample differences likely reflecting variation in relative proportions of various susceptibility genes, their corresponding brain correlates, and background gene effects. Gene discovery and subsequent elucidation of gene to brain to behavior pathways can be facilitated if etiological heterogeneity is reduced (for example, through use of genetic isolates and/or selection through multiplex families) or if the phenotype can be refined into familial components that may be more closely linked to specific underlying risk genes (i.e. endophenotypes). The identification of risk genes and associated ADHD subtypes may eventually lead to improved diagnostic methods and treatment interventions for children with ADHD. The goal of the proposed research is to investigate electroencephalographic (EEC) measures as a biological endophenotype in ADHD and to use it in gene mapping investigations. The proposed research makes use of the ongoing UCLA ADHD Genetic Study to collect EEC data on a set of 200 affected sibling pairs (ASPs), their parents, and unaffected siblings for this investigation.
The specific aims of this grant are to: 1) identify specific EEG patterns as likely endophenotypes;2) characterize the EEG endophenotype relative to behavioral and cognitive variation associated with ADHD;and 3) test association and linkage of EEG endophenotypes in ADHD. We believe that combining behavioral, cognitive, EEG and genetic data will identify the most powerful endophentoypes for gene mapping studies in ADHD and yield important information regarding the gene-brain-behavior pathway. Innovative statistical strategies for combining these data and identifying underlying traits that are part of the genetic liability for ADHD will be used. The current study benefits greatly from this ongoing data collection because ASPs are routinely assessed using structured diagnostic interviews, neuropsychological testing, and blood draws for genotyping investigations. We are thus able to collect EEG data at a very low cost in a well characterized sample of ADHD ASPs upon which linkage studies (and candidate gene association work) are readily available.

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Research Project (R01)
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Child Psychopathology and Developmental Disabilities Study Section (CPDD)
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Mamounas, Laura
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University of California Los Angeles
Schools of Medicine
Los Angeles
United States
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Loo, Sandra K; McGough, James J; McCracken, James T et al. (2018) Parsing heterogeneity in attention-deficit hyperactivity disorder using EEG-based subgroups. J Child Psychol Psychiatry 59:223-231
Ellis, Alissa J; Kinzel, Chantelle; Salgari, Giulia C et al. (2017) Frontal alpha asymmetry predicts inhibitory processing in youth with attention deficit/hyperactivity disorder. Neuropsychologia 102:45-51
Morgan, Julia E; Lee, Steve S; Loo, Sandra K (2016) Fluid Reasoning Mediates the Association of Birth Weight With ADHD Symptoms in Youth From Multiplex Families With ADHD. J Atten Disord :
Loo, Sandra K; Cho, Alexander; Hale, T Sigi et al. (2013) Characterization of the theta to beta ratio in ADHD: identifying potential sources of heterogeneity. J Atten Disord 17:384-92
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Mick, Eric; McGough, James; Loo, Sandra et al. (2011) Genome-wide association study of the child behavior checklist dysregulation profile. J Am Acad Child Adolesc Psychiatry 50:807-17.e8
Lasky-Su, Jessica; Won, Sungho; Mick, Eric et al. (2010) On genome-wide association studies for family-based designs: an integrative analysis approach combining ascertained family samples with unselected controls. Am J Hum Genet 86:573-80
Hale, T Sigi; Smalley, Susan L; Walshaw, Patricia D et al. (2010) Atypical EEG beta asymmetry in adults with ADHD. Neuropsychologia 48:3532-9
Mick, Eric; Todorov, Alexandre; Smalley, Susan et al. (2010) Family-based genome-wide association scan of attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry 49:898-905.e3
Hale, T Sigi; Smalley, Susan L; Dang, Jeff et al. (2010) ADHD familial loading and abnormal EEG alpha asymmetry in children with ADHD. J Psychiatr Res 44:605-15

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