Predictive diagnosis of major depression using NMR-based metabolomics and least-squares support vector machine.

Journal: Clinica chimica acta; international journal of clinical chemistry
Published Date: Jan 1, 2017

Abstract

BACKGROUND: Major depressive (MD) disorder is a serious psychiatric disorder that can result in suicidal behavior if not treated. The MD diagnosis using a standardized instrument instead of a structured interview will be advantageous for treatment and management of the MD, but so far no such technique exists. We developed an integrated analytical method of NMR-based metabolomics and least squares-support vector machine (LS-SVM) for predictive diagnosis of the MD.

Authors

  • Hong Zheng
    School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China.
  • Peng Zheng
    Department of Neurology, The First Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China.
  • Liangcai Zhao
    School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China.
  • Jianmin Jia
    School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China.
  • Shengli Tang
    School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China.
  • Pengtao Xu
    School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China.
  • Peng Xie
    New Cornerstone Science Laboratory, SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu 210096, China.
  • Hongchang Gao
    School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China. Electronic address: gaohc27@wmu.edu.cn.

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