An investigation of EEG, genetic and cognitive markers of treatment response to antidepressant medication in patients with major depressive disorder: A pilot study

Spronk, Desirée; Arns, Martijn; Barnett, Kylie J.; Cooper, Nicholas; Gordon, Evian

doi:10.1016/j.jad.2010.06.021

Cited by 136 publications

(78 citation statements)

References 49 publications

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“…Seemingly contrary to this, Spronk et al [109] reported that low theta activity at the frontal midline was associated with non-response. Note that several authors [96,106,107] reported on widespread frontal (not midline) theta activity, most likely a reflection of ‘drowsiness' theta power as discussed above (see EEG Vigilance) on vigilance [37], whereas Spronk and colleagues found the opposite pattern for frontal midline theta activity.…”

Section: Biomarkersmentioning

confidence: 91%

Personalized Medicine: Review and Perspectives of Promising Baseline EEG Biomarkers in Major Depressive Disorder and Attention Deficit Hyperactivity Disorder

2015

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Personalized medicine in psychiatry is in need of biomarkers that resemble central nervous system function at the level of neuronal activity. Electroencephalography (EEG) during sleep or resting-state conditions and event-related potentials (ERPs) have not only been used to discriminate patients from healthy subjects, but also for the prediction of treatment outcome in various psychiatric diseases, yielding information about tailored therapy approaches for an individual. This review focuses on baseline EEG markers for two psychiatric conditions, namely major depressive disorder and attention deficit hyperactivity disorder. It covers potential biomarkers from EEG sleep research and vigilance regulation, paroxysmal EEG patterns and epileptiform discharges, quantitative EEG features within the EEG main frequency bands, connectivity markers and ERP components that might help to identify favourable treatment outcome. Further, the various markers are discussed in the context of their potential clinical value and as research domain criteria, before giving an outline for future studies that are needed to pave the way to an electrophysiological biomarker-based personalized medicine.

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Section: Biomarkersmentioning

confidence: 91%

Personalized Medicine: Review and Perspectives of Promising Baseline EEG Biomarkers in Major Depressive Disorder and Attention Deficit Hyperactivity Disorder

2015

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“…More recently, Iosifescu et al 27 found that the relative theta power was lower in responders to SSRI or venlafaxine. Contrary to their results, Spronk et al 13 reported that better treatment response of 25 depressed patients treated with SSRI and SNRI was associated with higher absolute theta power. In the present study no difference in theta power or asymmetry was found.…”

Section: Discussionmentioning

confidence: 67%

“…of vigilance were selected for further processing. Spectral analysis was performed by Fast-Fourier Transform (FFT) in the following frequency bands: delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), beta (12)(13)(14)(15)(16)(17)(18)(19)(20). For each subject the mean and total alpha powers (in μV²), the alpha asymmetry (in %), the mean and total theta power (in μV²) and the theta asymmetry (in %) were calculated at eight electrode sites (F3, F4, C3, C4, P3, P4, O1, O2) using the Neurosoft ω software v 1.6.4.3.…”

Section: Methodsmentioning

confidence: 99%

“…[7][8][9] The earliest studies found increased alpha power in responders compared to non-responders 10,11 as well as greater alpha over the right compared to the left occipital sites. 12 Although some authors researching the predictive potential of the theta frequency band showed that higher absolute theta was associated with better response 13 , the majority of the studies found lower relative theta power in the groups of responders. 11,14,15 In several other QEEG studies, there was no pretreatment difference in alpha and theta powers between responders and non-responders to various antidepressants.…”

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confidence: 99%

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Response to Pharmacological Treatment in Major Depression Predicted by Electroencephalographic Alpha Power – a Pilot Naturalistic Study

et al. 2017

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Background: Pharmacological treatment of depression is currently led by the trial and error principle mainly because of lack of reliable biomarkers. Earlier fi ndings suggest that baseline alpha power and asymmetry could diff erentiate between responders and non-responders to specifi c antidepressants. Aim: The current study investigated quantitative electroencephalographic (QEEG) measures before and early in treatment as potential response predictors to various antidepressants in a naturalistic sample of depressed patients. We were aiming at developing markers for early prediction of treatment response based on diff erent QEEG measures. Materials and methods: EEG data from 25 depressed subjects were acquired at baseline and after one week of treatment. Mean and total alpha powers were calculated at eight electrode sites F3, F4, C3, C4, P3, P4, O1, O2. Response to treatment was defi ned as 50% decrease in MADRS score at week 4. Results: Mean P3 alpha predicted response with sensitivity and specifi city of 80%, positive and negative predictive values of 92.31% and 71.43%, respectively. The combined model of response prediction using mean baseline P3 alpha and mean week 1 C4 alpha values correctly identifi ed 80% of the cases with sensitivity of 84.62%, and specifi city of 71.43%. Conclusions: Simple QEEG measures (alpha power) acquired before initiation of antidepressant treatment could be useful in outcome prediction with an overall accuracy of about 80%. These fi ndings add to the growing body of evidence that alpha power might be developed as a reliable biomarker for the prediction of antidepressant response.

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“…Although there are reports relating amplitude of auditory ERPs (e.g., N1, P2) and antidepressant response (Bruder et al, 2012;Spronk et al, 2011;Vandoolaeghe et al, 1998), the most replicated finding has come for loudness dependency of auditory evoked potentials (LDAEPs). Increases in tone intensity from 60 to 100 dB are known to result in a monotonic increase in N1 and P2 amplitude.…”

Section: Auditory Evoked Potentials and Treatment Responsementioning

confidence: 99%

Electrophysiological predictors of clinical response to antidepressants

Bruder¹,

Tenke²,

Kayser³

2013

Clinical Handbook for the Management of Mood Disorders

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An investigation of EEG, genetic and cognitive markers of treatment response to antidepressant medication in patients with major depressive disorder: A pilot study

Cited by 136 publications

References 49 publications

Personalized Medicine: Review and Perspectives of Promising Baseline EEG Biomarkers in Major Depressive Disorder and Attention Deficit Hyperactivity Disorder

Personalized Medicine: Review and Perspectives of Promising Baseline EEG Biomarkers in Major Depressive Disorder and Attention Deficit Hyperactivity Disorder

Response to Pharmacological Treatment in Major Depression Predicted by Electroencephalographic Alpha Power – a Pilot Naturalistic Study

Electrophysiological predictors of clinical response to antidepressants

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