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The treatment of major depressive disorder (MDD) is hampered by low chances of treatment response in each treatment step, which is partly due to a lack of firmly established outcome-predictive biomarkers. Here, we hypothesize that polygenic-informed EEG biomarkers may help predict differential antidepressant treatment response. Using a polygenic-informed electroencephalography (EEG) data-driven, data-reduction approach, we identify a functional brain network that is sex-specifically associated with polygenic risk for MDD in psychiatric patients (N=1,123). Subsequently, we demonstrate the utility of this network in predicting response to transcranial magnetic stimulation (TMS) and antidepressant medication in two independent datasets (N=196 and N=1,008). A simulation aimed at stratifying patients to TMS, sertraline or escitalopram/venlafaxine based on only this EEG component yields up to >30% improved remission rates. Overall, our findings highlight the power and utility of a combined polygenic and neurophysiological approach in the search for clinically-relevant biomarkers in psychiatric disorders.
Keywords
biomarker, predictive markers, depression
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Yes there is potential Competing Interest. MA is unpaid chairman of the Brainclinics Foundation, a minority shareholder in neuroCare Group (Munich, Germany), and a co-inventor on 4 patent applications related to EEG, neuromodulation and psychophysiology, but receives no royalties related to these patents; Research Institute Brainclinics received research funding from Brain Resource (Sydney, Australia), Urgotech (France) and neuroCare Group (Munich, Germany), and equipment support from Deymed, neuroConn and Magventure. EG is founder and receives income as CEO and chairman for Brain Resource Ltd. and he has stock options in Brain Resource Ltd. Additional funding for this project was obtained through a personal UMC Utrecht Brain Center Rudolf Magnus Young Talent Fellowship (H150) to JL. The remaining authors, HM, BL, GvW, DD, BdW, JvH, PN and, KvE, declare no competing financial or non-financial interest.
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Article
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
View the published article at Brain Stimulation.
No community comments so far
Version 1
Posted 05 Feb, 2021
No comments provided
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Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at Brain Stimulation.
The treatment of major depressive disorder (MDD) is hampered by low chances of treatment response in each treatment step, which is partly due to a lack of firmly established outcome-predictive biomarkers. Here, we hypothesize that polygenic-informed EEG biomarkers may help predict differential antidepressant treatment response. Using a polygenic-informed electroencephalography (EEG) data-driven, data-reduction approach, we identify a functional brain network that is sex-specifically associated with polygenic risk for MDD in psychiatric patients (N=1,123). Subsequently, we demonstrate the utility of this network in predicting response to transcranial magnetic stimulation (TMS) and antidepressant medication in two independent datasets (N=196 and N=1,008). A simulation aimed at stratifying patients to TMS, sertraline or escitalopram/venlafaxine based on only this EEG component yields up to >30% improved remission rates. Overall, our findings highlight the power and utility of a combined polygenic and neurophysiological approach in the search for clinically-relevant biomarkers in psychiatric disorders.
Figure 1
Figure 2
Figure 3
Figure 4
Yes there is potential Competing Interest. MA is unpaid chairman of the Brainclinics Foundation, a minority shareholder in neuroCare Group (Munich, Germany), and a co-inventor on 4 patent applications related to EEG, neuromodulation and psychophysiology, but receives no royalties related to these patents; Research Institute Brainclinics received research funding from Brain Resource (Sydney, Australia), Urgotech (France) and neuroCare Group (Munich, Germany), and equipment support from Deymed, neuroConn and Magventure. EG is founder and receives income as CEO and chairman for Brain Resource Ltd. and he has stock options in Brain Resource Ltd. Additional funding for this project was obtained through a personal UMC Utrecht Brain Center Rudolf Magnus Young Talent Fellowship (H150) to JL. The remaining authors, HM, BL, GvW, DD, BdW, JvH, PN and, KvE, declare no competing financial or non-financial interest.
This is a list of supplementary files associated with this preprint. Click to download.
- GeneticsinformedEEGbiomarkersupplementary.docx
Supplementary Information
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