Evidence map›Paper›PMID 42218337›Full record

ArticleMolecular psychiatry2026

A hierarchical multi-scale framework for schizophrenia: integrating symptom networks, functional circuits, and molecular pathways.

Peng Cheng, Zhening Liu, Xue Li, Feiwen Wang, Xingang Chen, Wenqiang Li, Chuansheng Wang, Yuchao Jiang, Jianfeng Feng, Yongfeng Yang and 1 more

Abstract read
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In one paragraph

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

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Peng ChengDepartment of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
Zhening LiuDepartment of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.ORCID http://orcid.org/0000-0001-6893-2427
Xue LiHenan Collaborative Innovation Center of Prevention and Treatment of Mental Disorders, the Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China.
Feiwen WangDepartment of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
Xingang ChenHenan Collaborative Innovation Center of Prevention and Treatment of Mental Disorders, the Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China.
Wenqiang LiHenan Collaborative Innovation Center of Prevention and Treatment of Mental Disorders, the Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China.ORCID http://orcid.org/0000-0002-0833-246X
Chuansheng WangHenan Collaborative Innovation Center of Prevention and Treatment of Mental Disorders, the Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China.
Yuchao JiangSchool of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China.ORCID http://orcid.org/0000-0001-7012-0559
Jianfeng FengInstitute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.ORCID http://orcid.org/0000-0001-5987-2258
Yongfeng YangHenan Collaborative Innovation Center of Prevention and Treatment of Mental Disorders, the Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China. yongfeng_200888@126.com.
Jie YangDepartment of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China. yang0826@csu.edu.cn.ORCID http://orcid.org/0000-0001-7561-9076

Funding

National Natural Science Foundation of China (National Science Foundation of China) 82071506National Natural Science Foundation of China (National Science Foundation of China) 82201663
6 · The paper itself

Abstract

Schizophrenia is characterized by striking symptom heterogeneity, yet the mapping between specific clinical phenotypes and their underlying biological substrates remains elusive. To bridge this gap, we applied an integrative, multi-scale framework combining symptom network analysis, connectome-based predictive modeling (CPM), and transcriptomic mapping in a multi-center cohort of schizophrenia patients. This approach revealed a hierarchical dissociation between phenotypic topology and underlying biological mechanisms among the identified high-centrality core symptoms: Conceptual Disorganization, Unusual Thought Content, and Blunted Affect. While Conceptual Disorganization and Unusual Thought Content exhibited clinical coherence as psychosis-related features, CPM uncovered a divergence in their neural substrates. Conceptual Disorganization shared greater neurofunctional isomorphism with Blunted Affect-characterized by converging dysconnectivity within the Somatomotor Network (SMN) and subcortical circuits-whereas Unusual Thought Content displayed a distinct architecture driven by prominent Default Mode Network regulation beyond the shared sensorimotor substrate. Transcriptomic annotation further stratified these dimensions: psychosis-related networks were underpinned by synaptic regulatory genes, whereas Blunted Affect was enriched for intracellular MAPK signaling and metabolic processes. These findings delineate a hierarchical model in which distinct molecular etiologies-synaptic versus metabolic-cascade into shared systems-level failures at the "somato-cognitive interface". We conclude that while symptoms may group clinically, their treatment requires targeting separable molecular pathways that converge on common circuit bottlenecks. This framework reconciles symptom heterogeneity with overlapping biological substrates, advocating for a mechanism-based stratification of schizophrenia.

Indexed as

SchizophreniaBrainCohort StudiesConnectomeFemaleHumansMaleNerve NetNeural PathwaysSchizophrenic PsychologyTranscriptome

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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.