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Large‐scale collaboration in ENIGMA‐EEG: A perspective on the meta‐analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity
BACKGROUND AND PURPOSE: The ENIGMA‐EEG working group was established to enable large‐scale international collaborations among cohorts that investigate the genetics of brain function measured with electroencephalography (EEG). In this perspective, we will discuss why analyzing the genetics of functio...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413828/ https://www.ncbi.nlm.nih.gov/pubmed/34291596 http://dx.doi.org/10.1002/brb3.2188 |
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author | Smit, Dirk J. A. Andreassen, Ole A. Boomsma, Dorret I. Burwell, Scott J. Chorlian, David B. de Geus, Eco J. C. Elvsåshagen, Torbjørn Gordon, Reyna L. Harper, Jeremy Hegerl, Ulrich Hensch, Tilman Iacono, William G. Jawinski, Philippe Jönsson, Erik G. Luykx, Jurjen J. Magne, Cyrille L. Malone, Stephen M. Medland, Sarah E. Meyers, Jacquelyn L. Moberget, Torgeir Porjesz, Bernice Sander, Christian Sisodiya, Sanjay M. Thompson, Paul M. van Beijsterveldt, Catharina E. M. van Dellen, Edwin Via, Marc Wright, Margaret J. |
author_facet | Smit, Dirk J. A. Andreassen, Ole A. Boomsma, Dorret I. Burwell, Scott J. Chorlian, David B. de Geus, Eco J. C. Elvsåshagen, Torbjørn Gordon, Reyna L. Harper, Jeremy Hegerl, Ulrich Hensch, Tilman Iacono, William G. Jawinski, Philippe Jönsson, Erik G. Luykx, Jurjen J. Magne, Cyrille L. Malone, Stephen M. Medland, Sarah E. Meyers, Jacquelyn L. Moberget, Torgeir Porjesz, Bernice Sander, Christian Sisodiya, Sanjay M. Thompson, Paul M. van Beijsterveldt, Catharina E. M. van Dellen, Edwin Via, Marc Wright, Margaret J. |
author_sort | Smit, Dirk J. A. |
collection | PubMed |
description | BACKGROUND AND PURPOSE: The ENIGMA‐EEG working group was established to enable large‐scale international collaborations among cohorts that investigate the genetics of brain function measured with electroencephalography (EEG). In this perspective, we will discuss why analyzing the genetics of functional brain activity may be crucial for understanding how neurological and psychiatric liability genes affect the brain. METHODS: We summarize how we have performed our currently largest genome‐wide association study of oscillatory brain activity in EEG recordings by meta‐analyzing the results across five participating cohorts, resulting in the first genome‐wide significant hits for oscillatory brain function located in/near genes that were previously associated with psychiatric disorders. We describe how we have tackled methodological issues surrounding genetic meta‐analysis of EEG features. We discuss the importance of harmonizing EEG signal processing, cleaning, and feature extraction. Finally, we explain our selection of EEG features currently being investigated, including the temporal dynamics of oscillations and the connectivity network based on synchronization of oscillations. RESULTS: We present data that show how to perform systematic quality control and evaluate how choices in reference electrode and montage affect individual differences in EEG parameters. CONCLUSION: The long list of potential challenges to our large‐scale meta‐analytic approach requires extensive effort and organization between participating cohorts; however, our perspective shows that these challenges are surmountable. Our perspective argues that elucidating the genetic of EEG oscillatory activity is a worthwhile effort in order to elucidate the pathway from gene to disease liability. |
format | Online Article Text |
id | pubmed-8413828 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84138282021-09-07 Large‐scale collaboration in ENIGMA‐EEG: A perspective on the meta‐analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity Smit, Dirk J. A. Andreassen, Ole A. Boomsma, Dorret I. Burwell, Scott J. Chorlian, David B. de Geus, Eco J. C. Elvsåshagen, Torbjørn Gordon, Reyna L. Harper, Jeremy Hegerl, Ulrich Hensch, Tilman Iacono, William G. Jawinski, Philippe Jönsson, Erik G. Luykx, Jurjen J. Magne, Cyrille L. Malone, Stephen M. Medland, Sarah E. Meyers, Jacquelyn L. Moberget, Torgeir Porjesz, Bernice Sander, Christian Sisodiya, Sanjay M. Thompson, Paul M. van Beijsterveldt, Catharina E. M. van Dellen, Edwin Via, Marc Wright, Margaret J. Brain Behav Methods BACKGROUND AND PURPOSE: The ENIGMA‐EEG working group was established to enable large‐scale international collaborations among cohorts that investigate the genetics of brain function measured with electroencephalography (EEG). In this perspective, we will discuss why analyzing the genetics of functional brain activity may be crucial for understanding how neurological and psychiatric liability genes affect the brain. METHODS: We summarize how we have performed our currently largest genome‐wide association study of oscillatory brain activity in EEG recordings by meta‐analyzing the results across five participating cohorts, resulting in the first genome‐wide significant hits for oscillatory brain function located in/near genes that were previously associated with psychiatric disorders. We describe how we have tackled methodological issues surrounding genetic meta‐analysis of EEG features. We discuss the importance of harmonizing EEG signal processing, cleaning, and feature extraction. Finally, we explain our selection of EEG features currently being investigated, including the temporal dynamics of oscillations and the connectivity network based on synchronization of oscillations. RESULTS: We present data that show how to perform systematic quality control and evaluate how choices in reference electrode and montage affect individual differences in EEG parameters. CONCLUSION: The long list of potential challenges to our large‐scale meta‐analytic approach requires extensive effort and organization between participating cohorts; however, our perspective shows that these challenges are surmountable. Our perspective argues that elucidating the genetic of EEG oscillatory activity is a worthwhile effort in order to elucidate the pathway from gene to disease liability. John Wiley and Sons Inc. 2021-07-21 /pmc/articles/PMC8413828/ /pubmed/34291596 http://dx.doi.org/10.1002/brb3.2188 Text en © 2021 The Authors. Brain and Behavior published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Smit, Dirk J. A. Andreassen, Ole A. Boomsma, Dorret I. Burwell, Scott J. Chorlian, David B. de Geus, Eco J. C. Elvsåshagen, Torbjørn Gordon, Reyna L. Harper, Jeremy Hegerl, Ulrich Hensch, Tilman Iacono, William G. Jawinski, Philippe Jönsson, Erik G. Luykx, Jurjen J. Magne, Cyrille L. Malone, Stephen M. Medland, Sarah E. Meyers, Jacquelyn L. Moberget, Torgeir Porjesz, Bernice Sander, Christian Sisodiya, Sanjay M. Thompson, Paul M. van Beijsterveldt, Catharina E. M. van Dellen, Edwin Via, Marc Wright, Margaret J. Large‐scale collaboration in ENIGMA‐EEG: A perspective on the meta‐analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity |
title | Large‐scale collaboration in ENIGMA‐EEG: A perspective on the meta‐analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity |
title_full | Large‐scale collaboration in ENIGMA‐EEG: A perspective on the meta‐analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity |
title_fullStr | Large‐scale collaboration in ENIGMA‐EEG: A perspective on the meta‐analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity |
title_full_unstemmed | Large‐scale collaboration in ENIGMA‐EEG: A perspective on the meta‐analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity |
title_short | Large‐scale collaboration in ENIGMA‐EEG: A perspective on the meta‐analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity |
title_sort | large‐scale collaboration in enigma‐eeg: a perspective on the meta‐analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity |
topic | Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413828/ https://www.ncbi.nlm.nih.gov/pubmed/34291596 http://dx.doi.org/10.1002/brb3.2188 |
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