Identifying serum lipidomic signatures related to prognosis in first-episode schizophrenia
Abstract Background Antipsychotic 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 trea...
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BMC
2025-05-01
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| Series: | BMC Psychiatry |
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| Online Access: | https://doi.org/10.1186/s12888-025-06802-7 |
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| author | Mengyi Luo Suzhen Zhang Jingxin Xue Tianhao Gao Xuan Li Zhaolin Zhai Chang Lu Yuke Dong Kaiming Zhuo Qiong Xiang Qing Kang Shunying Yu Chunhong Shao Dengtang Liu |
| author_facet | Mengyi Luo Suzhen Zhang Jingxin Xue Tianhao Gao Xuan Li Zhaolin Zhai Chang Lu Yuke Dong Kaiming Zhuo Qiong Xiang Qing Kang Shunying Yu Chunhong Shao Dengtang Liu |
| author_sort | Mengyi Luo |
| collection | DOAJ |
| description | Abstract Background Antipsychotic 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. Methods Pre-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. Results By 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). Conclusions Our 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. |
| format | Article |
| id | doaj-art-e4d980dc9db247daa7ae1a91ca550ee2 |
| institution | OA Journals |
| issn | 1471-244X |
| language | English |
| publishDate | 2025-05-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Psychiatry |
| spelling | doaj-art-e4d980dc9db247daa7ae1a91ca550ee22025-08-20T02:15:12ZengBMCBMC Psychiatry1471-244X2025-05-0125111010.1186/s12888-025-06802-7Identifying serum lipidomic signatures related to prognosis in first-episode schizophreniaMengyi Luo0Suzhen Zhang1Jingxin Xue2Tianhao Gao3Xuan Li4Zhaolin Zhai5Chang Lu6Yuke Dong7Kaiming Zhuo8Qiong Xiang9Qing Kang10Shunying Yu11Chunhong Shao12Dengtang Liu13Department of Psychiatry, Huashan Hospital, Fudan UniversityDivision of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of MedicineDepartment of Psychiatry, Huashan Hospital, Fudan UniversityDepartment of Psychiatry, Huashan Hospital, Fudan UniversityDivision of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of MedicineDepartment of Psychiatry, Huashan Hospital, Fudan UniversityDepartment of Psychiatry, Huashan Hospital, Fudan UniversityDepartment of Psychiatry, Huashan Hospital, Fudan UniversityDivision of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of MedicineDivision of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of MedicineDivision of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of MedicineDivision of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of MedicineDepartment of Psychiatry, Huashan Hospital, Fudan UniversityDepartment of Psychiatry, Huashan Hospital, Fudan UniversityAbstract Background Antipsychotic 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. Methods Pre-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. Results By 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). Conclusions Our 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.https://doi.org/10.1186/s12888-025-06802-7SchizophreniaPrognosisLipidomic profilingBiomarker |
| spellingShingle | Mengyi Luo Suzhen Zhang Jingxin Xue Tianhao Gao Xuan Li Zhaolin Zhai Chang Lu Yuke Dong Kaiming Zhuo Qiong Xiang Qing Kang Shunying Yu Chunhong Shao Dengtang Liu Identifying serum lipidomic signatures related to prognosis in first-episode schizophrenia BMC Psychiatry Schizophrenia Prognosis Lipidomic profiling Biomarker |
| title | Identifying serum lipidomic signatures related to prognosis in first-episode schizophrenia |
| title_full | Identifying serum lipidomic signatures related to prognosis in first-episode schizophrenia |
| title_fullStr | Identifying serum lipidomic signatures related to prognosis in first-episode schizophrenia |
| title_full_unstemmed | Identifying serum lipidomic signatures related to prognosis in first-episode schizophrenia |
| title_short | Identifying serum lipidomic signatures related to prognosis in first-episode schizophrenia |
| title_sort | identifying serum lipidomic signatures related to prognosis in first episode schizophrenia |
| topic | Schizophrenia Prognosis Lipidomic profiling Biomarker |
| url | https://doi.org/10.1186/s12888-025-06802-7 |
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