Evidence map›Paper›PMID 42237602›Full record

ArticlePsychological medicine2026

Cell-type and spatiotemporal transcriptional signatures of white matter morphometric similarity network alterations in major depressive disorder.

Yue Wu, Jinglei Xu, Haolin Wang, Yulong Shen, Ying Zhai, Minghuan Lei, Zhihui Zhang, Qian Wu, Qi An, Wenjie Cai and 4 more

Abstract read
In one paragraph

Article in Psychological medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Yue WuDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
Jinglei XuDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
Haolin WangDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
Yulong ShenSchool of Laboratory Medicine, Division of Medical Technology, https://ror.org/02mh8wx89Tianjin Medical University, Tianjin, China.
Ying ZhaiDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
Minghuan LeiDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
Zhihui ZhangDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
Qian WuDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
Qi AnDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
Wenjie CaiDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
Libo SuSchool of Medical Technology, https://ror.org/02mh8wx89Tianjin Medical University, Tianjin, China.
Yanmin PengSchool of Medical Imaging and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, https://ror.org/02mh8wx89Tianjin Medical University, Tianjin, China.
Quan ZhangDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
Feng LiuDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.ORCID 0000-0002-3570-4222

Funding

National Natural Science Foundation of China 82572306
6 · The paper itself

Abstract

backgroundWhite matter (WM) abnormalities are implicated in major depressive disorder (MDD), yet the organization of white matter morphometric similarity networks (WM-MSNs) - which capture interregional similarity in voxel-wise WM morphology - and the transcriptional mechanisms associated with their disruption remain insufficiently understood.

methodsUsing T1-weighted MRI from a large multisite sample (1,154 individuals with MDD and 1,026 healthy controls), we constructed individualized WM-MSNs. Group differences were assessed at the edge, global, and nodal levels. To identify molecular pathways underlying these alterations, nodal abnormalities were linked to regional gene expression profiles from the Allen Human Brain Atlas using spatially informed transcriptomic association, followed by functional, cell-type-specific, and developmental enrichment analyses.

resultsMDD showed distributed but selective reorganization of WM-MSNs. Network-based statistics revealed two significant components, with 118 edges exhibiting increased morphometric similarity and 45 showing decreased similarity. Globally, MDD demonstrated higher small-worldness, clustering coefficient, global efficiency, and local efficiency, together with shorter characteristic path length. Nodal disruptions were concentrated in major commissural and association tracts - including the corpus callosum, cingulum, uncinate fasciculus, and tapetum. Transcriptomic integration indicated enrichment for gene signatures related to oligodendrocyte function, myelination, lipid metabolism, axonal organization, and cellular stress-related molecular processes, with implicated genes showing broad developmental-stage expression.

conclusionsMDD is associated with robust alterations in individualized WM-MSNs that converge with transcriptional signatures linked to myelination, metabolic processes, axonal structure, and cellular stress, linking macroscale network disruption to underlying molecular architecture and providing cross-scale insights into WM pathology in depression.

Indexed as

Major Depressive DisorderNerve NetTranscriptomeWhite MatterAdultFemaleGene Expression ProfilingHumansMagnetic Resonance ImagingMaleMiddle Agedmajor depressive disordernetwork neuroscienceoligodendrocyte and myelination pathwaystranscriptomic integrationwhite matter morphometric similarity networks

Identifiers

PMID42237602
PMCPMC13247791

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.