Evidence map›Paper›PMID 40316994›Full record

ArticleJournal of translational medicine2025

Revealing multiple biological subtypes of schizophrenia through a data-driven approach.

Yuran Wang, Shixuan Feng, Yuanyuan Huang, Runlin Peng, Liqin Liang, Wei Wang, Minxin Guo, Baoyuan Zhu, Heng Zhang, Jianhao Liao and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Dissecting the Ecological Structure of Health and Disease in the Global Gut Microbiome.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  4. Article
  5. Review
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

16 authors.

Yuran WangSchool of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, 511442, China.
Shixuan FengDepartment of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China.
Yuanyuan HuangDepartment of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China.
Runlin PengSchool of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, 511442, China.
Liqin LiangSchool of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, 511442, China.
Wei WangSchool of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, 511442, China.
Minxin GuoSchool of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, 511442, China.
Baoyuan ZhuSchool of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, 511442, China.
Heng ZhangSchool of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, 511442, China.
Jianhao LiaoSchool of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, 511442, China.
Jing ZhouSchool of Material Science and Engineering, South China University of Technology, Guangzhou, 510006, China.
Hehua LiDepartment of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China.
Xiaobo LiDepartment of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA.
Yuping NingDepartment of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China.
Fengchun WuDepartment of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China. 2018760372@gzhmu.edu.cn.
Kai WuSchool of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, 511442, China. kaiwu@scut.edu.cn.ORCID 0000-0002-1363-0875

Funding

Basic and Applied Basic Research Foundation of Guangdong Province 2022A1515140142Guangdong Basic and Applied Basic Research Foundation Outstanding Youth Project 2021B1515020064Key Research and Development Program of Guangdong 2023B0303010003Key Research and Development Program of Guangdong 2023B0303020001Natural Science Foundation of China 72174082Natural Science Foundation of China 81971585Natural Science Foundation of China 82271953Natural Science Foundation of China 82301688Natural Science Foundation of Guangdong Province 2024A1515013058Science and Technology Program of Guangzhou 202201010093Science and Technology Program of Guangzhou 202206010034Science and Technology Program of Guangzhou 202206010077Science and Technology Program of Guangzhou 202206060005Science and Technology Program of Guangzhou 202206080005Science and Technology Program of Guangzhou 2023A03J0839Science and Technology Program of Guangzhou 2023A03J0856the National Key Research and Development Program of China 2023YFC2414500the National Key Research and Development Program of China 2023YFC2414504
6 · The paper itself

Abstract

introductionThe brain imaging subtypes of schizophrenia have been widely investigated using data-driven approaches. However, the heterogeneity of SZ in multiple biological data is largely unknown.

methodsA data-driven model was used to classify brain imaging, gut microbiota, and brain-gut fusion data obtained through a dot product fusion method, identifying significant subtypes and calculating their correlations with clinical symptoms and cognitive performance.

resultsThese subtypes remain relatively independent and demonstrate typical features and biomarkers, which are significantly associated with clinical symptoms and cognitive performance. Two brain subtypes with opposite structural and functional changes are identified: (1) a structural variant-dominant brain subtype with negative symptoms and cognitive deficits and (2) a functional alteration-dominant brain subtype with positive symptoms. The three gut subtypes include the following: (1) Collinsella-dominant; (2) Prevotella-dominant with positive symptoms; and (3) Streptococcus-dominant. Two brain-gut subtypes show different abnormalities in brain‒genus linkages: (1) strong connectivity of "brain function in the temporal and parietal lobes-Prevotella" with reduced attention scores and (2) strong connectivity of "brain structure and function in the frontal and parietal lobes-multiple genera" with positive symptoms. Notably, brain subtypes and brain-gut subtypes are most relevant to clinical symptoms, whereas gut subtypes reveal more cognitive biomarkers.

conclusionThese findings show the potential to identify multiple biological subtypes with distinct biomarkers, thereby suggesting the possibility of personalized and precise treatment for SZ patients.

Indexed as

SchizophreniaAdultBiomarkersBrainCognitionFemaleGastrointestinal MicrobiomeHumansMagnetic Resonance ImagingMaleBiomarkersBiomarkersBrain-gut axisBrain imagingData-drivenGut microbiotaSchizophreniaSubtypes

Identifiers

PMID40316994
PMCPMC12048963

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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.