Evidence map›Paper›PMID 42386701›Full record

ArticleTranslational psychiatry2026

The distinct effects of metabolic syndrome on negative symptoms and on antipsychotic therapy of schizophrenia involve insular volume, functional connectivity, and genetic polymorphisms.

Jingyu Zhou, Mingjun Duan, Sisi Jiang, Huan Huang, Fei Wen, Yuling Luo, Yingjie Tang, Hui He, Qizhong Yi, María Luisa Bringas Vega and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Translational 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.

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

15 authors.

Jingyu Zhou *The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, 610056, China.ORCID http://orcid.org/0000-0002-6165-613X
Mingjun Duan *The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, 610056, China.
Sisi JiangThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, 610056, China.
Huan HuangThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, 610056, China.ORCID http://orcid.org/0000-0002-2035-6456
Fei WenThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, 610056, China.
Yuling LuoThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, 610056, China.
Yingjie TangThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, 610056, China.
Hui HeThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, 610056, China.
Qizhong YiPsychological Medicine Center, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, PR China.
María Luisa Bringas VegaChina-Cuba Belt and Road Joint Laboratory on Neurotechnology and Brain-Apparatus Communication, University of Electronic Science and Technology of China, Chengdu, 610054, P. R. China.
Lang ZhangThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, 610056, China.
Gang YaoThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, 610056, China.
Benjamin Klugah-BrownThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, 610056, China.
Dezhong YaoThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, 610056, China. dyao@uestc.edu.cn.ORCID http://orcid.org/0000-0002-8042-879X
Cheng LuoThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, 610056, China. chengluo@uestc.edu.cn.ORCID http://orcid.org/0000-0003-0524-5886

Funding

National Natural Science Foundation of China (National Science Foundation of China) 82371560
6 · The paper itself

Abstract

As a prevalent comorbidity in schizophrenia, metabolic syndrome (MetS) exerts complex influences on residual symptoms and therapeutic outcomes of antipsychotic treatment. This study investigates the underlying neuroimaging, physiological and genetic mechanisms. At baseline, 142 participants were categorized into four groups according to diagnoses of schizophrenia and MetS. During follow-up, schizophrenia patients with and without MetS (SCZ-MetS and SCZ-nMetS) underwent 4-week antipsychotic treatment. Functional and structural magnetic resonance images, metabolic indicators and clinical scales were collected to investigate effects of MetS on gray matter volume (GMV), functional connectivity (FC) of schizophrenia patients, and related clinical implications. Using cytochrome P450 2D6 (CYP2D6) polymorphisms and brain-wide gene expression profiles, we explored genetic mechanisms of the therapeutic link between MetS and schizophrenia. SCZ-MetS showed greater insular GMV atrophy and functional dysconnectivity. Indirect effects of fasting blood glucose (FBG) on negative symptoms via insular GMV atrophy were observed. However, during follow-up, we observed group × time interactions on GMV and FC in insula. Increased GMV of the right insula in SCZ-MetS was correlated with the remission rate of positive symptoms. A moderation effect of FBG on this correlation was revealed. Finally, CYP2D6 polymorphisms and gene expression related to antipsychotic-response explained group × time interaction of GMV. Collectively, glucose metabolism, insular volume and FC underlie two distinct effects of MetS on: residual negative symptoms and therapeutic outcomes of positive symptoms in schizophrenia. The genetic mechanisms linking MetS to therapeutic outcomes involve CYP2D6 polymorphisms and the expression of genes related to antipsychotic-response.

Indexed as

Antipsychotic AgentsInsular CortexMetabolic SyndromeSchizophreniaAdultBlood GlucoseCytochrome P-450 CYP2D6FemaleGray MatterHumansMagnetic Resonance ImagingMalePolymorphism, GeneticTreatment Effect HeterogeneityAntipsychotic AgentsBlood GlucoseCytochrome P-450 CYP2D6

Identifiers

PMID42386701
PMCPMC13594184

What Socratic holds

Textmetadata
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Registered trials

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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 Socratic graph.