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Electroencephalographic biomarkers as predictors of methylphenidate response in attention-deficit/hyperactivity disorder

  • Martijn Arns*
  • , Madelon A. Vollebregt
  • , Donna Palmer
  • , Chris Spooner
  • , Evian Gordon
  • , Michael Kohn
  • , Simon Clarke
  • , Glen R. Elliott
  • , Jan K. Buitelaar
  • *Corresponding author for this work
  • Research Institute Brainclinics
  • Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
  • Brain Resource Ltd, San Francisco, CA, USA
  • Brain Dynamics Center, Sydney Medical School and Westmead Millenium Institute, University of Sydney, NSW, Australia
  • Brain Resource Ltd, Sydney, NSW, Australia
  • CRASH (Centre for Research into Adolescent'S Health) Westmead Hospital, Sydney Australia
  • Children's Health Council, Palo Alto, CA, USA
  • Department of Psychiatry and Behavioral Sciences, Stanford School of Medicine, CA, USA
  • Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
  • Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, The Netherlands

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

EEG biomarkers have shown promise in predicting non-response to stimulant medication in ADHD and could serve as translational biomarkers. This study aimed to replicate and extend previous EEG biomarkers. The international Study to Predict Optimized Treatment for ADHD (iSPOT-A), a multi-center, international, prospective open-label trial, enrolled 336 children and adolescents with ADHD (11.9 yrs; 245 males; prescribed methylphenidate) and 158 healthy children. Treatment response was established after six weeks using the clinician rated ADHD-Rating Scale-IV. Theta/Beta ratio (TBR) and alpha peak frequency (APF) were assessed at baseline as predictors for treatment outcome. No differences between ADHD and controls were found for TBR and APF. 62% of the ADHD group was classified as a responder. Responders did not differ from non-responders in age, medication dosage, and baseline severity of ADHD symptoms. Male-adolescent non-responders exhibited a low frontal APF (Fz: R = 9.2 Hz vs. NR = 8.1 Hz; ES = 0.83), whereas no effects were found for TBR. A low APF in male adolescents was associated with non-response to methylphenidate, replicating earlier work. Our data suggest that the typical maturational EEG changes observed in ADHD responders and controls are absent in non-responders to methylphenidate and these typical changes start emerging in adolescence. Clinical trials registration: www.clinicaltrials.gov; NCT00863499 (https://clinicaltrials.gov/ct2/show/NCT00863499).

Original languageEnglish
Pages (from-to)881-891
Number of pages11
JournalEuropean Neuropsychopharmacology
Volume28
Issue number8
DOIs
Publication statusPublished - 1 Aug 2018

Funding

MA reports research grants and options from Brain Resource (Sydney, Australia) and shares from neuroCare Group (Munich, Germany); DP has received income and stock options with the role of science and data processing manager as an employee with Brain Resource Ltd.; CS has received income and stock options with the role of software engineer as an employee with Brain Resource Ltd.; EG is founder and receives income as Chief Executive Officer and Chairman for Brain Resource Ltd. He has stock options in Brain Resource Ltd. In the past 3 years MRK has been a member of an advisory board for Shire. He has no other industry financial or material support, including expert testimony, patents, royalties. JKB has been in the past 3 years a consultant to/ member of advisory board of/ and/or speaker for Janssen Cilag BV, Eli Lilly, and Servier. He is not an employee of any of these companies, and not a stock shareholder of any of these companies. He has no other financial or material support, including expert testimony, patents, royalties. MV, SC and GE report no financial disclosures.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • ADHD
  • Alpha peak frequency
  • Biomarker
  • QEEG
  • Theta

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