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已发表论文
利用非靶向脂质代谢组学鉴定未治疗精神分裂症患者的血浆生物标志物
Authors Wang Z , Wang Y, Jiang H , Chen L, Zhang X
Received 30 April 2025
Accepted for publication 29 October 2025
Published 3 December 2025 Volume 2025:21 Pages 2721—2732
DOI https://doi.org/10.2147/NDT.S537721
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Professor Taro Kishi
Zhiqiang Wang,1– 4 Yanyu Wang,1– 4 Haonan Jiang,1– 4 Long Chen,2– 4 Xulai Zhang1– 4
1School of Mental Health and Psychological Science, Anhui Medical University, Hefei, Anhui, People’s Republic of China; 2Anhui Clinical Centre for Mental and Psychological Diseases, Hefei Fourth People’s Hospital, Hefei, Anhui, People’s Republic of China; 3Affiliated Psychological Hospital of Anhui Medical University, Hefei Fourth People’s Hospital, Hefei, Anhui, People’s Republic of China; 4Anhui Mental Health Center, Hefei Fourth People’s Hospital, Hefei, Anhui, People’s Republic of China
Correspondence: Xulai Zhang, Anhui Mental Health Centre, Hefei Fourth People’s Hospital, Hefei, Anhui, People’s Republic of China, Email xulaizhang@163.com
Purpose: Schizophrenia (SCZ) is a profound psychosomatic illness with an unidentified cause and no definitive biomarkers. This study sought to investigate plasma biomarkers linked to schizophrenia by untargeted metabolomics.
Patients and Methods: A total of 50 medication-naïve SCZ patients and 25 healthy controls were eligible and participated in this study. Psychiatric symptomatology was evaluated employing the Positive and Negative Syndrome Scale. We quantified the concentration of lipid metabolites in plasma from all participants using untargeted metabolomics and classified metabolites that were significantly different between both groups. We subsequently assessed the diagnostic potential of metabolites on the basis of receiver operating characteristic curves and examined metabolites affiliated with psychotic symptomatology in SCZ patients.
Results: Fourteen metabolites exhibited compelling disparities in schizophrenia patients relative to healthy controls. Eight metabolites, including methylphosphatidylcholine, acylcarnitine, sphingomyelin, and (O-acyl)-1-hydroxy fatty acids (38:4), could significantly distinguish between schizophrenia and healthy controls, with all their areas under the curve (AUC) exceeding 0.7. The peak area under the curve (CV-AUC) for AcCa(20:4) was 0.92 ± 0.03. In schizophrenia patients, negative symptoms exhibited a negative correlation with acylcarnitines, while cognitive symptoms had a substantial positive correlation with methylphosphatidylcholine and phosphatidylcholine.
Conclusion: The findings reveal lipid metabolism dysregulation as a potential pathophysiological mechanism of schizophrenia. The identified metabolites, such as AcCa and phosphatidylcholine, serve as promising biomarkers for the diagnosis and symptom evaluation, suggesting their direct involvement in the disease’s pathogenesis.
Keywords: schizophrenia, metabolomics, plasma, biomarker, phosphatidylcholines
1School of Mental Health and Psychological Science, Anhui Medical University, Hefei, Anhui, People’s Republic of China; 2Anhui Clinical Centre for Mental and Psychological Diseases, Hefei Fourth People’s Hospital, Hefei, Anhui, People’s Republic of China; 3Affiliated Psychological Hospital of Anhui Medical University, Hefei Fourth People’s Hospital, Hefei, Anhui, People’s Republic of China; 4Anhui Mental Health Center, Hefei Fourth People’s Hospital, Hefei, Anhui, People’s Republic of China
Correspondence: Xulai Zhang, Anhui Mental Health Centre, Hefei Fourth People’s Hospital, Hefei, Anhui, People’s Republic of China, Email xulaizhang@163.com
Purpose: Schizophrenia (SCZ) is a profound psychosomatic illness with an unidentified cause and no definitive biomarkers. This study sought to investigate plasma biomarkers linked to schizophrenia by untargeted metabolomics.
Patients and Methods: A total of 50 medication-naïve SCZ patients and 25 healthy controls were eligible and participated in this study. Psychiatric symptomatology was evaluated employing the Positive and Negative Syndrome Scale. We quantified the concentration of lipid metabolites in plasma from all participants using untargeted metabolomics and classified metabolites that were significantly different between both groups. We subsequently assessed the diagnostic potential of metabolites on the basis of receiver operating characteristic curves and examined metabolites affiliated with psychotic symptomatology in SCZ patients.
Results: Fourteen metabolites exhibited compelling disparities in schizophrenia patients relative to healthy controls. Eight metabolites, including methylphosphatidylcholine, acylcarnitine, sphingomyelin, and (O-acyl)-1-hydroxy fatty acids (38:4), could significantly distinguish between schizophrenia and healthy controls, with all their areas under the curve (AUC) exceeding 0.7. The peak area under the curve (CV-AUC) for AcCa(20:4) was 0.92 ± 0.03. In schizophrenia patients, negative symptoms exhibited a negative correlation with acylcarnitines, while cognitive symptoms had a substantial positive correlation with methylphosphatidylcholine and phosphatidylcholine.
Conclusion: The findings reveal lipid metabolism dysregulation as a potential pathophysiological mechanism of schizophrenia. The identified metabolites, such as AcCa and phosphatidylcholine, serve as promising biomarkers for the diagnosis and symptom evaluation, suggesting their direct involvement in the disease’s pathogenesis.
Keywords: schizophrenia, metabolomics, plasma, biomarker, phosphatidylcholines