Cargando…

Functional connectivity analysis on electroencephalography signals reveals potential biomarkers for treatment response in major depression

BACKGROUND: The treatment efficacy varies across individual patients with major depressive disorder (MDD). It lacks robust electroencephalography (EEG) markers for an antidepressant-responsive phenotype. METHOD: This is an observational study enrolling 28 patients with MDD and 33 healthy controls (m...

Descripción completa

Detalles Bibliográficos
Autores principales: Huang, Shiau-Shian, Yu, Yu-Hsiang, Chen, His-Han, Hung, Chia-Chun, Wang, Yao-Ting, Chang, Chieh Hsin, Peng, Syu-Jyun, Kuo, Po-Hsiu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10394892/
https://www.ncbi.nlm.nih.gov/pubmed/37528355
http://dx.doi.org/10.1186/s12888-023-04958-8
_version_ 1785083472212131840
author Huang, Shiau-Shian
Yu, Yu-Hsiang
Chen, His-Han
Hung, Chia-Chun
Wang, Yao-Ting
Chang, Chieh Hsin
Peng, Syu-Jyun
Kuo, Po-Hsiu
author_facet Huang, Shiau-Shian
Yu, Yu-Hsiang
Chen, His-Han
Hung, Chia-Chun
Wang, Yao-Ting
Chang, Chieh Hsin
Peng, Syu-Jyun
Kuo, Po-Hsiu
author_sort Huang, Shiau-Shian
collection PubMed
description BACKGROUND: The treatment efficacy varies across individual patients with major depressive disorder (MDD). It lacks robust electroencephalography (EEG) markers for an antidepressant-responsive phenotype. METHOD: This is an observational study enrolling 28 patients with MDD and 33 healthy controls (mean age of 40.7 years, and 71.4% were women). Patients underwent EEG exams at baseline (week0) and week1, while controls’ EEG recordings were acquired only at week0. A resting eye-closing EEG segment was analyzed for functional connectivity (FC). Four parameters were used in FC analysis: (1) node strength (NS), (2) global efficiency (GE), (3) clustering coefficient (CC), and (4) betweenness centrality (BC). RESULTS: We found that controls had higher values in delta wave in the indices of NS, GE, BC, and CC than MDD patients at baseline. After treatment with antidepressants, patients’ FC indices improved significantly, including GE, mean CC, and mean NS in the delta wave. The FC in the alpha and beta bands of the responders were higher than those of the non-responders. CONCLUSIONS: The FC of the MDD patients at baseline without treatment was worse than that of controls. After treatment, the FC improved and was close to the values of controls. Responders showed better FC in the high-frequency bands than non-responders, and this feature exists in both pre-treatment and post-treatment EEG. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12888-023-04958-8.
format Online
Article
Text
id pubmed-10394892
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-103948922023-08-03 Functional connectivity analysis on electroencephalography signals reveals potential biomarkers for treatment response in major depression Huang, Shiau-Shian Yu, Yu-Hsiang Chen, His-Han Hung, Chia-Chun Wang, Yao-Ting Chang, Chieh Hsin Peng, Syu-Jyun Kuo, Po-Hsiu BMC Psychiatry Research BACKGROUND: The treatment efficacy varies across individual patients with major depressive disorder (MDD). It lacks robust electroencephalography (EEG) markers for an antidepressant-responsive phenotype. METHOD: This is an observational study enrolling 28 patients with MDD and 33 healthy controls (mean age of 40.7 years, and 71.4% were women). Patients underwent EEG exams at baseline (week0) and week1, while controls’ EEG recordings were acquired only at week0. A resting eye-closing EEG segment was analyzed for functional connectivity (FC). Four parameters were used in FC analysis: (1) node strength (NS), (2) global efficiency (GE), (3) clustering coefficient (CC), and (4) betweenness centrality (BC). RESULTS: We found that controls had higher values in delta wave in the indices of NS, GE, BC, and CC than MDD patients at baseline. After treatment with antidepressants, patients’ FC indices improved significantly, including GE, mean CC, and mean NS in the delta wave. The FC in the alpha and beta bands of the responders were higher than those of the non-responders. CONCLUSIONS: The FC of the MDD patients at baseline without treatment was worse than that of controls. After treatment, the FC improved and was close to the values of controls. Responders showed better FC in the high-frequency bands than non-responders, and this feature exists in both pre-treatment and post-treatment EEG. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12888-023-04958-8. BioMed Central 2023-08-01 /pmc/articles/PMC10394892/ /pubmed/37528355 http://dx.doi.org/10.1186/s12888-023-04958-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Huang, Shiau-Shian
Yu, Yu-Hsiang
Chen, His-Han
Hung, Chia-Chun
Wang, Yao-Ting
Chang, Chieh Hsin
Peng, Syu-Jyun
Kuo, Po-Hsiu
Functional connectivity analysis on electroencephalography signals reveals potential biomarkers for treatment response in major depression
title Functional connectivity analysis on electroencephalography signals reveals potential biomarkers for treatment response in major depression
title_full Functional connectivity analysis on electroencephalography signals reveals potential biomarkers for treatment response in major depression
title_fullStr Functional connectivity analysis on electroencephalography signals reveals potential biomarkers for treatment response in major depression
title_full_unstemmed Functional connectivity analysis on electroencephalography signals reveals potential biomarkers for treatment response in major depression
title_short Functional connectivity analysis on electroencephalography signals reveals potential biomarkers for treatment response in major depression
title_sort functional connectivity analysis on electroencephalography signals reveals potential biomarkers for treatment response in major depression
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10394892/
https://www.ncbi.nlm.nih.gov/pubmed/37528355
http://dx.doi.org/10.1186/s12888-023-04958-8
work_keys_str_mv AT huangshiaushian functionalconnectivityanalysisonelectroencephalographysignalsrevealspotentialbiomarkersfortreatmentresponseinmajordepression
AT yuyuhsiang functionalconnectivityanalysisonelectroencephalographysignalsrevealspotentialbiomarkersfortreatmentresponseinmajordepression
AT chenhishan functionalconnectivityanalysisonelectroencephalographysignalsrevealspotentialbiomarkersfortreatmentresponseinmajordepression
AT hungchiachun functionalconnectivityanalysisonelectroencephalographysignalsrevealspotentialbiomarkersfortreatmentresponseinmajordepression
AT wangyaoting functionalconnectivityanalysisonelectroencephalographysignalsrevealspotentialbiomarkersfortreatmentresponseinmajordepression
AT changchiehhsin functionalconnectivityanalysisonelectroencephalographysignalsrevealspotentialbiomarkersfortreatmentresponseinmajordepression
AT pengsyujyun functionalconnectivityanalysisonelectroencephalographysignalsrevealspotentialbiomarkersfortreatmentresponseinmajordepression
AT kuopohsiu functionalconnectivityanalysisonelectroencephalographysignalsrevealspotentialbiomarkersfortreatmentresponseinmajordepression