Background Depressive symptoms are often seen in schizophrenia. The overlap in presentation makes it difficult to distinguish depressive symptoms from the negative symptoms of schizophrenia. The adipokine leptin was f...Background Depressive symptoms are often seen in schizophrenia. The overlap in presentation makes it difficult to distinguish depressive symptoms from the negative symptoms of schizophrenia. The adipokine leptin was found to be altered in both depression and schizophrenia. There are few studies focusing on the prediction of leptin in diagnosis and evaluation of depressive symptoms in schizophrenia.ObjectiveAims To assess the plasma leptin level in patients with schizophrenia and its relationships with depressive symptoms.Methods Cross-sectional studies were applied to(1) compare the levels of plasma leptin between schizophrenia(n=74) and healthy controls(n=50); and(2)investigate the relationship between plasma leptin levels and depressive subscores.Results(1) Plasma leptin levels were significantly higher in patients with schizophrenia than in healthy controls.(2) Correlation analysis revealed a significant negative association between leptin levels and the depressed factor scores on the Positive and Negative Syndrome Scale(PANSS).(3) Stepwise multiple regression analyses identified leptin as an influencing factor for depressed factor score on PANSS.Conclusion Leptin may serve as a predictor for the depressive symptoms of chronic schizophrenia.展开更多
A systematic characterization of the similarities and differences among different methods for detecting structural brain abnormalities in schizophrenia,such as voxel-based morphometry(VBM),tensor-based morphometry(TBM...A systematic characterization of the similarities and differences among different methods for detecting structural brain abnormalities in schizophrenia,such as voxel-based morphometry(VBM),tensor-based morphometry(TBM),and projection-based thickness(PBT),is important for understanding the brain pathology in schizophrenia and for developing effective biomarkers for a diagnosis of schizophrenia.However,such studies are still lacking.Here,we performed VBM,TBM,and PBT analyses on T1-weighted brain MR images acquired from 116 patients with schizophrenia and 116 healthy controls.We found that,although all methods detected wide-spread structural changes,different methods captured different information-only 10.35%of the grey matter changes in cortex were detected by all three methods,and VBM only detected 11.36%of the white matter changes detected by TBM.Further,pattern classification between patients and controls revealed that combining different measures improved the classification accuracy(81.9%),indicating that fusion of different structural measures serves as a better neuroimaging marker for the objective diagnosis of schizophrenia.展开更多
基金The National Key Research and Development Program(2017YFC0909200)National Natural Science Foundation of China(NSFC,81171266,81271481,81571326,81500976)+2 种基金Ministry of Science and Technology Precision Medicine ProjectShanghai Key Laboratory of Psychotic Disorders(13dz2260500)Shanghai Municipal Planning Commission of Science and Research Fund(20154Y0194)
基金supported by grants from the National Key R&D Program of China(2017YFC0909200)the National Science Foundation of China(NSFC+4 种基金81171266,81271481,81671336 and 81500976)the China and National Key Research and Development Program(2017YFC0909200)the Shanghai Key Laboratory of Psychotic Disorders(13dz2260500)the Shanghai Municipal Planning Commission of Science and Research Fund(20154Y0194)the Canadian Institutes of Health Research(project grant PJT-156116)
文摘Background Depressive symptoms are often seen in schizophrenia. The overlap in presentation makes it difficult to distinguish depressive symptoms from the negative symptoms of schizophrenia. The adipokine leptin was found to be altered in both depression and schizophrenia. There are few studies focusing on the prediction of leptin in diagnosis and evaluation of depressive symptoms in schizophrenia.ObjectiveAims To assess the plasma leptin level in patients with schizophrenia and its relationships with depressive symptoms.Methods Cross-sectional studies were applied to(1) compare the levels of plasma leptin between schizophrenia(n=74) and healthy controls(n=50); and(2)investigate the relationship between plasma leptin levels and depressive subscores.Results(1) Plasma leptin levels were significantly higher in patients with schizophrenia than in healthy controls.(2) Correlation analysis revealed a significant negative association between leptin levels and the depressed factor scores on the Positive and Negative Syndrome Scale(PANSS).(3) Stepwise multiple regression analyses identified leptin as an influencing factor for depressed factor score on PANSS.Conclusion Leptin may serve as a predictor for the depressive symptoms of chronic schizophrenia.
基金This work was supported by the National Key Research and Development Program of China(2017 YFC0909201 and 2018YFC1314300)the National Natural Science Foundation of China(81571659,81971694,81971599,81771818,81425013,and 81871052)and the Tianjin Key Technology R&D Program(17ZXMFSY00090).
文摘A systematic characterization of the similarities and differences among different methods for detecting structural brain abnormalities in schizophrenia,such as voxel-based morphometry(VBM),tensor-based morphometry(TBM),and projection-based thickness(PBT),is important for understanding the brain pathology in schizophrenia and for developing effective biomarkers for a diagnosis of schizophrenia.However,such studies are still lacking.Here,we performed VBM,TBM,and PBT analyses on T1-weighted brain MR images acquired from 116 patients with schizophrenia and 116 healthy controls.We found that,although all methods detected wide-spread structural changes,different methods captured different information-only 10.35%of the grey matter changes in cortex were detected by all three methods,and VBM only detected 11.36%of the white matter changes detected by TBM.Further,pattern classification between patients and controls revealed that combining different measures improved the classification accuracy(81.9%),indicating that fusion of different structural measures serves as a better neuroimaging marker for the objective diagnosis of schizophrenia.
