Abstract
Background
Altered brain structural connectivity has been implicated in the pathophysiology of
psychiatric disorders including schizophrenia (SZ), bipolar disorder (BD), and major
depressive disorder (MDD). However, it is unknown which part of these connectivity
abnormalities are disorder specific and which are shared across the spectrum of psychotic
and affective disorders. We investigated common and distinct brain connectivity alterations
in a large sample (N = 1743) of patients with SZ, BD, or MDD and healthy control (HC) subjects.
Methods
This study examined diffusion-weighted imaging-based structural connectome topology
in 720 patients with MDD, 112 patients with BD, 69 patients with SZ, and 842 HC subjects
(mean age of all subjects: 35.7 years). Graph theory–based network analysis was used
to investigate connectome organization. Machine learning algorithms were trained to
classify groups based on their structural connectivity matrices.
Results
Groups differed significantly in the network metrics global efficiency, clustering,
present edges, and global connectivity strength with a converging pattern of alterations
between diagnoses (e.g., efficiency: HC > MDD > BD > SZ, false discovery rate–corrected
p = .028). Subnetwork analysis revealed a common core of edges that were affected across
all 3 disorders, but also revealed differences between disorders. Machine learning
algorithms could not discriminate between disorders but could discriminate each diagnosis
from HC. Furthermore, dysconnectivity patterns were found most pronounced in patients
with an early disease onset irrespective of diagnosis.
Conclusions
We found shared and specific signatures of structural white matter dysconnectivity
in SZ, BD, and MDD, leading to commonly reduced network efficiency. These results
showed a compromised brain communication across a spectrum of major psychiatric disorders.
Keywords
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Article info
Publication history
Published online: June 21, 2022
Accepted:
May 31,
2022
Received in revised form:
May 27,
2022
Received:
November 15,
2021
Footnotes
JR and MG contributed equally to this work as joint first authors.
MvdH and UD contributed equally to this work as joint last authors.
Identification
Copyright
© 2022 Society of Biological Psychiatry.
