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Combinatorial panel with endophenotypes from multilevel information of diffusion tensor imaging and lipid profile as predictors for depression.
Liu, Juan; Liu, Zhuang; Wei, Yange; Zhang, Yanbo; Womer, Fay Y; Jia, Duan; Wei, Shengnan; Wu, Feng; Kong, Lingtao; Jiang, Xiaowei; Zhang, Luheng; Tang, Yanqing; Zhang, Xizhe; Wang, Fei.
Afiliação
  • Liu J; Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China.
  • Liu Z; Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, PR China.
  • Wei Y; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, Jiangsu, PR China.
  • Zhang Y; School of Public health, China Medical University, Shenyang, Liaoning, PR China.
  • Womer FY; Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, PR China.
  • Jia D; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, Jiangsu, PR China.
  • Wei S; Department of Psychiatry, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Canada.
  • Wu F; Department of Psychiatry, Washington University School of Medicine, St. Louis, USA.
  • Kong L; Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, PR China.
  • Jiang X; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, Jiangsu, PR China.
  • Zhang L; Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China.
  • Tang Y; Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China.
  • Zhang X; Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China.
  • Wang F; Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China.
Aust N Z J Psychiatry ; 56(9): 1187-1198, 2022 09.
Article em En | MEDLINE | ID: mdl-35632993
OBJECTIVE: Clinical heterogeneity in major depressive disorder likely reflects the range of etiology and contributing factors in the disorder, such as genetic risk. Identification of more refined subgroups based on biomarkers such as white matter integrity and lipid-related metabolites could facilitate precision medicine in major depressive disorder. METHODS: A total of 148 participants (15 genetic high-risk participants, 57 patients with first-episode major depressive disorder and 76 healthy controls) underwent diffusion tensor imaging and plasma lipid profiling. Alterations in white matter integrity and lipid metabolites were identified in genetic high-risk participants and patients with first-episode major depressive disorder. Then, shared alterations between genetic high-risk and first-episode major depressive disorder were used to develop an imaging x metabolite diagnostic panel for genetically based major depressive disorder via factor analysis and logistic regression. A fivefold cross-validation test was performed to evaluate the diagnostic panel. RESULTS: Alterations of white matter integrity in corona radiata, superior longitudinal fasciculus and the body of corpus callosum and dysregulated unsaturated fatty acid metabolism were identified in both genetic high-risk participants and patients with first-episode major depressive disorder. An imaging x metabolite diagnostic panel, consisting of measures for white matter integrity and unsaturated fatty acid metabolism, was identified that achieved an area under the receiver operating characteristic curve of 0.86 and had a significantly higher diagnostic performance than that using either measure alone. And cross-validation confirmed the adequate reliability and accuracy of the diagnostic panel. CONCLUSION: Combining white matter integrity in corpus callosum, superior longitudinal fasciculus and corona radiata, and unsaturated fatty acid profile may improve the identification of genetically based endophenotypes in major depressive disorder to advance precision medicine strategies.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Transtorno Depressivo Maior / Substância Branca Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Aust N Z J Psychiatry Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Transtorno Depressivo Maior / Substância Branca Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Aust N Z J Psychiatry Ano de publicação: 2022 Tipo de documento: Article