Studies have found evidence of dichotic listening, electrophysiologic (EEG/ERP), and neurocognitive abnormalities in depressed patients, which are related to clinical response to antidepressants. Measures of hemispheric asymmetry, quantitative EEG in alpha/theta bands and intensity-dependence of auditory event-related potentials (ERPs) show particular promise of being predictive of response to a selective serotonin reuptake inhibitor (SSRI). Sample size in most studies has, however, been small and little is known about the specificity of predictors to SSRI antidepressants. An upcoming dual therapy clinical trial offers an ideal opportunity to conduct a prospective study to assess the value of these electrophysiologic and cognitive measures as predictors of therapeutic response to the SSRI escitalopram (ESC) as opposed to the noradrenaline/dopamine reuptake inhibitor (NDRI) bupropion (BUP). Patients are randomly assigned to 12 weeks of treatment with ESC, BUP or a combination of these antidepressants (ESC + BUP). Unmedicated depressed patients and healthy controls will be tested at baseline on a battery of tests, including resting EEG, intensity-dependence of auditory ERPs, novelty oddball task, dichotic listening, and neurocognitive tests. Patients are retested on the EEG and auditory ERP measures after 1 week of treatment and again after 12 weeks, and controls are retested at the same intervals. This will enable us to examine whether these electrophysiologic measures change during treatment or are stable, state-independent markers. A preclinical study found that firing rates of serotonin neurons in the dorsal raphi nucleus were markedly increased after combined administration of ESC + BUP, but not after either drug alone, which could account for the more rapid and increased benefit of this dual treatment. If this translates to humans, ESC + BUP would be predicted to have acute and chronic effects on EEG and auditory ERP measures not seen for either antidepressant alone. Moreover, we will examine whether acute changes in EEG and auditory ERPs predict which patients will show remission of symptoms with combined treatment. The long-range goal of this project is to contribute toward the development of electrophysiologic and behavioral tests that could aid the clinician in choosing antidepressants that will most benefit a depressed patient.

Public Health Relevance

A clinical trial comparing treatment with an SSRI, bupropion or combined therapy offers an ideal opportunity to do a prospective study of the value of electrophysiologic and neurocognitive tests as predictors of therapeutic response to these antidepressants. This research could translate into development of clinical aides for selecting treatments for individual depressed patients.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH036295-27
Application #
8209198
Study Section
Neural Basis of Psychopathology, Addictions and Sleep Disorders Study Section (NPAS)
Program Officer
Muehrer, Peter R
Project Start
1982-09-28
Project End
2013-12-31
Budget Start
2012-01-01
Budget End
2013-12-31
Support Year
27
Fiscal Year
2012
Total Cost
$370,668
Indirect Cost
$147,918
Name
New York State Psychiatric Institute
Department
Type
DUNS #
167204994
City
New York
State
NY
Country
United States
Zip Code
10032
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Kayser, Jürgen; Tenke, Craig E (2015) On the benefits of using surface Laplacian (current source density) methodology in electrophysiology. Int J Psychophysiol 97:171-3
Tenke, Craig E; Kayser, Jürgen (2015) Surface Laplacians (SL) and phase properties of EEG rhythms: Simulated generators in a volume-conduction model. Int J Psychophysiol 97:285-98
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Bruder, Gerard E; Alvarenga, Jorge E; Alschuler, Daniel et al. (2014) Neurocognitive predictors of antidepressant clinical response. J Affect Disord 166:108-14
Alschuler, Daniel M; Tenke, Craig E; Bruder, Gerard E et al. (2014) Identifying electrode bridging from electrical distance distributions: a survey of publicly-available EEG data using a new method. Clin Neurophysiol 125:484-90
Tenke, C E; Kayser, J; Miller, L et al. (2013) Neuronal generators of posterior EEG alpha reflect individual differences in prioritizing personal spirituality. Biol Psychol 94:426-32
Bruder, Gerard E; Bansal, Ravi; Tenke, Craig E et al. (2012) Relationship of resting EEG with anatomical MRI measures in individuals at high and low risk for depression. Hum Brain Mapp 33:1325-33

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