Evidence map›Paper›PMID 41039876›Full record

ArticlePsychological medicine2025

Network-dependent cortical thickness reductions following chronic methamphetamine use.

Yunkai Sun, Jun Wang, Jinsong Tang, Yanhui Liao

Abstract read
In one paragraph

Article in Psychological medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yunkai SunDepartment of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, P. R. China.
Jun WangDepartment of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, P. R. China.
Jinsong TangDepartment of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, P. R. China.
Yanhui LiaoDepartment of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, P. R. China.ORCID 0000-0003-4735-3252

Funding

National Natural Science Foundation of China U22A20302
6 · The paper itself

Abstract

backgroundCortical thickness reductions associated with chronic methamphetamine use exhibit a non-uniform spatial distribution across brain regions. A potential neurobiological mechanism underlying for this heterogeneous pattern may involve the structural and functional organization of cortical connectivity networks, which could mediate the propagation of neuroanatomical alterations. Here, we aimed to explore how brain network architecture constrains cortical thickness alterations and their clinical relevance.

methodsThe 3D-T1 images were acquired from 139 patients with methamphetamine use disorder (MUD) and 119 sex- and age-matched healthy controls. We first characterized distributed cortical thinning patterns in patients with MUD, then evaluated the relationships between regional atrophy and (1) multimodal nodal centrality measures (structural, morphological, and functional) and (2) atrophy profiles of structural connected neighbors. Individual network-weighted cortical abnormality maps were used to identify distinct MUD biotypes and related to clinical features through k-means clustering and partial least squares regression.

resultsCortical thinning patterns demonstrated significant associations with nodal centrality across all modalities, as well as cortical thinning of connected neighbors revealing a network-dependent atrophy architecture. Fronto-temporal regions emerged as critical epicenters, showing both high nodal centrality and strong correlations with connected neighbors' thinning severity. We found that the individual differences in network-weighted cortical abnormality corresponded to clinical symptom variability, and distinguished two MUD biotypes associated with drug use.

conclusionsOur findings suggest that cortical thinning in MUD is influenced by the brain connectome architecture, providing a mechanistic framework for understanding individual variability in addiction progression.

Indexed as

Amphetamine-Related DisordersBrain Cortical ThicknessCerebral CortexCerebral Cortical ThinningMethamphetamineNerve NetAdolescentAdultAtrophyCase-Control StudiesChinaChronic DiseaseClinical RelevanceFemaleHumansImaging, Three-DimensionalMethamphetamineaddictionbrain networkcortical thicknessmethamphetamineMRI

Identifiers

PMID41039876
PMCPMC12527499

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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.