Abstract

It is well known that depressive disorder is heterogeneous, yet little is known about its neurophysiological subtypes. In the present study, we identified neurophysiological subtypes of depression related to specific neural substrates. We performed cluster analysis for 134 subjects (67 depressive subjects and 67 controls) using a high-dimensional dataset consisting of resting state functional connectivity measured by functional MRI, clinical questionnaire scores, and various biomarkers. Applying a newly developed, multiple co-clustering method to this dataset, we identified three subtypes of depression that are characterized by functional connectivity between the right Angular Gyrus (AG) and other brain areas in default mode networks, and Child Abuse Trauma Scale (CATS) scores. These subtypes are also related to Selective Serotonin-Reuptake Inhibitor (SSRI) treatment outcomes, which implies that we may be able to predict effectiveness of treatment based on AG-related functional connectivity and CATS.

Details

Title
Identification of depression subtypes and relevant brain regions using a data-driven approach
Author
Tokuda, Tomoki 1 ; Yoshimoto, Junichiro 2 ; Shimizu, Yu 1 ; Okada, Go 3 ; Takamura, Masahiro 3   VIAFID ORCID Logo  ; Okamoto, Yasumasa 3 ; Yamawaki, Shigeto 3 ; Doya, Kenji 1   VIAFID ORCID Logo 

1  Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan 
2  Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan; Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan 
3  Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan 
Pages
1-13
Publication year
2018
Publication date
Sep 2018
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41598-018-32521-z
ProQuest document ID
2110238904
Copyright
© 2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.