Personalized medicine in ADHD and depression : a quest for EEG treatment predictors

Research output: ThesisDoctoral ThesisExternal

Abstract

The primary aim of this thesis was to investigate the value of neurophysiological techniques such as EEG and ERPs in predicting treatment outcome in ADHD and depression. The treatment modalities investigated in this thesis were stimulant medication, antidepressants, neurofeedback in ADHD and rTMS for depression. The main findings related to predicting non-response are summarized below. Impaired vigilance regulation: was found to be a core feature in ADHD, explaining the symptoms of ADHD and also explaining why psychostimulants provide clinical benefit in ADHD - in line with the EEG vigilance model - by its vigilance stabilizing properties. In this case this concerns a predictor for favorable treatment outcome to psychostimulants. In a sub-group of non-responders to various antidepressant treatments (antidepressants and rTMS), suggestions for this same impaired vigilance regulation (excess theta) were obtained. Several studies in the literature have demonstrated that this subgroup of patients (with excess theta) respond well to stimulant medication which is usually prescribed in ADHD. It is speculated that the core-pathophysiology of this specific ‘excess theta’ sub-type lies in sleep problems such as sleep onset insomnia and delayed circadian phase, resulting in impaired vigilance regulation during daytime. Psychostimulants have been found to be effective for this EEG subtype in both ADHD and depression, however these exert their effects by increasing daytime vigilance and result in ‘symptom suppression’, not affecting the core pathophysiology, namely the sleep problems and circadian phase. Therefore, future studies should investigate further if treatments hypothesized to directly improve sleep onset insomnia and circadian phase, indeed improve ADHD and depressive symptoms, such as melatonin and SMR neurofeedback. Such treatments should also specifically aim to find interventions resulting in long term effects. Individual alpha peak frequency (iAPF): An often-overlooked feature of the EEG, namely the presence of a slow iAPF was found to be a solid predictor of non-response to various treatments such as psychostimulants in ADHD, rTMS in depression as well as antidepressants. A slowed iAPF predictive of non-response is present in approximately 28% of children with ADHD and in 17% of patients with depression, hence comprising a substantial group. Given the high heritability of the iAPF, the stability of this measure over time, its clear relation to cerebral blood flow and its substantial prevalence in ADHD and depression, this measure can be considered an endophenotype associated with non-response for conventional treatments in ADHD and depression. Future research should investigate further to what treatments patients with this endophenotype do respond. Further studies should confirm that this endophenotype is specific enough to reliably select patients who will not respond to treatment before treatment is initiated. Possibly, this endophenotype can stimulate new research into biomarker-based treatment and lead to new treatments.
Original languageEnglish
Award date23 Dec 2011
Publisher
Print ISBNs978-94-6191-098
Publication statusPublished - 23 Dec 2011
Externally publishedYes

Keywords

  • ADHD
  • Depression
  • Personalized Medicine
  • QEEG
  • rTMS
  • Neurofeedback
  • antidepressants
  • psychostimulants
  • alpha

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