Evidence map›Paper›PMID 40340899›Full record

ArticleBMC psychiatry2025

Identifying serum lipidomic signatures related to prognosis in first-episode schizophrenia.

Mengyi Luo, Suzhen Zhang, Jingxin Xue, Tianhao Gao, Xuan Li, Zhaolin Zhai, Chang Lu, Yuke Dong, Kaiming Zhuo, Qiong Xiang and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

14 authors.

Mengyi Luo *Department of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China.
Suzhen Zhang *Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Jingxin Xue *Department of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China.
Tianhao GaoDepartment of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China.
Xuan LiDivision of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Zhaolin ZhaiDepartment of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China.
Chang LuDepartment of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China.
Yuke DongDepartment of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China.
Kaiming ZhuoDivision of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Qiong XiangDivision of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Qing KangDivision of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Shunying YuDivision of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Chunhong ShaoDepartment of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China. chunhongshao@fudan.edu.cn.
Dengtang LiuDepartment of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China. liudengtang@smhc.org.cn.

Funding

Dengtang Liu CRC2017ZD03, 82171496, 82371504, 20y11906300, 2022JC009, GWVI-11.2-YQ39, 22Y11903400, 23ZR1454700, YG2017ZD13, 19MC1911100, 13dz2260500, YG2024QNA55, 2024ZZ2058, 2024-YJ06.
6 · The paper itself

Abstract

backgroundAntipsychotic medications are crucial for alleviating symptoms of schizophrenia (SCZ). However, treatment responses vary across individuals, and few reliable biomarkers currently exist to predict the clinical outcome. Therefore, we aim to identify potential lipid markers for treatment outcomes in patients with first-episode SCZ.

methodsPre-treatment serum samples were obtained from 95 participants who underwent an 8-week treatment regimen with antipsychotic drugs. Untargeted liquid chromatography-mass spectrometry (LC-MS) was used to acquire serum lipidomic profiles, correlating them with treatment responses at 8 weeks to identify potential lipid signatures. The antipsychotic treatment response was quantified using the percentage change on the Positive and Negative Syndrome Scale (PANSS) scale.

resultsBy combining LASSO regression and Random Forest regression, we identified 8 positively associated and 2 negatively associated baseline lipids related to the PANSS reduction rate. In the further analysis of logistic regression, we identified three candidate lipids, PC (18:2e_19:0), PE (53:7), and TG (16:2e_19:0_20:5), which could together distinguish poor and good responders, with an AUC of 0.805 (95% CI, 0.715-0.894).

conclusionsOur findings suggest that this set of lipid biomarkers may have the potential to predict the outcome of antipsychotic drug treatment. Further validation and larger studies are needed to evaluate their potential for clinical applications. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Antipsychotic AgentsLipidomicsLipidsSchizophreniaAdultBiomarkersChromatography, LiquidFemaleHumansMalePrognosisTreatment OutcomeYoung AdultAntipsychotic AgentsBiomarkersLipidsBiomarkerLipidomic profilingPrognosisSchizophrenia

Identifiers

PMID40340899
PMCPMC12060530

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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.