Evidence map›Paper›PMID 42339646›Full record

ArticlePsychological medicine2026

Adversity as the key feature: neuroimaging profiles of subtypes from multiple depression risk factors.

Jingying Zhou, Yaoyao Sun, Guorui Zhao, Junyuan Sun, Zhe Lu, Zhewei Kang, Yunqing Zhu, Rui Yuan, Jing Guo, Yuyanan Zhang and 2 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

12 authors.

Jingying Zhouhttps://ror.org/02v51f717School of Nursing, Peking University, Beijing, China.
Yaoyao SunPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), https://ror.org/05rzcwg85National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Guorui ZhaoPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), https://ror.org/05rzcwg85National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Junyuan SunPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), https://ror.org/05rzcwg85National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Zhe LuPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), https://ror.org/05rzcwg85National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Zhewei KangPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), https://ror.org/05rzcwg85National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Yunqing ZhuPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), https://ror.org/05rzcwg85National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Rui YuanPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), https://ror.org/05rzcwg85National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Jing GuoPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), https://ror.org/05rzcwg85National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Yuyanan ZhangPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), https://ror.org/05rzcwg85National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Wenjian BiDepartment of Medical Genetics, School of Basic Medical Sciences, https://ror.org/02v51f717Peking University, Beijing, China.
Weihua YuePeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), https://ror.org/05rzcwg85National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.ORCID 0000-0002-1201-8465

Funding

National Postdoctoral Program for Innovative Talents BX20240029
6 · The paper itself

Abstract

backgroundDepression arises from diverse environmental and psychosocial risk factors, yet how these factors co-occur within individuals remains unclear. This study identifies profiles of multiple depression risk factors and examines their clinical and neuroimaging correlates.

methodsAmong 157,317 UK Biobank participants completing the mental health questionnaire, 24 psychological, environmental, and lifestyle factors were assessed using latent class analysis. Logistic regression evaluated associations between profiles and depression outcomes; linear models examined neuroimaging differences. Imaging transcriptomics and gene-set enrichment analyses contextualized neural findings.

resultsThree latent profiles emerged: low risk profile (81.09%), childhood adversity-related profile (CA; 10.95%), and adulthood adversity-related profile (AA; 7.97%). Both the CA profile and AA profile show significantly higher depression risk than the low risk profile. Compared with the low risk profile, the AA profile shows a 2.7-fold increase in depression risk (OR = 3.701, 95%CI: 3.532~3.881), with appetite change and psychomotor symptoms being more prominent. The CA profile shows a 2.5-fold increase in depression risk (OR = 3.507, 95%CI: 3.353~3.607), with worthlessness, sleep problems, and suicidal ideation being more prominent. Both adversity profiles showed lower white-matter FA in cerebellar-thalamic and associative pathways. The CA profile additionally showed reduced FA in occipital tracts, whereas the AA profile showed greater reductions in prefrontal pathways and lower GMV in insula, amygdala, and cerebellar lobules VIIIb/IX, alongside higher occipital pole GMV. The most pronounced nominally significant difference between CA and AA centered on the right amygdala. Genes overlapping subcortical GMV differences were enriched for psychiatric disorders.

conclusionsLife-course adversity may be a key feature associated with distinct clinical and neural signatures, helping identify subgroups with co-occurring vulnerabilities. These patterns warrant further investigation in future studies.

Indexed as

Adverse Childhood ExperiencesBrainDepressionAdultAgedFemaleHumansLatent Class AnalysisMagnetic Resonance ImagingMaleMiddle AgedNeuroimagingRisk FactorsUK BiobankUnited Kingdomadulthood adversitychildhood adversitydepressiondepressive symptomsgray matter volumelatent class analysisneuroimaging featurerisk factorswhite matter integrity

Identifiers

PMID42339646
PMCPMC13319489

What Socratic holds

Textmetadata
LicenceCC BY-NC-SA
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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 Socratic graph.