The potential biomarker panels for identification of Major Depressive Disorder (MDD) patients with and without early life stress (ELS) by metabonomic analysis.

Lingjiang Li,Huafu Chen,Xinghua Ding,Wuju Li,Shuguang Yang,Zhiguo Li,Shaojun Liu,Yong Liu,Yan Zhang

doi:10.1371/journal.pone.0097479

Abstract

ObjectiveThe lack of the disease biomarker to support objective laboratory tests still constitutes a bottleneck in the clinical diagnosis and evaluation of major depressive disorder (MDD) and its subtypes. We used metabonomic techniques to screen the diagnostic biomarker panels from the plasma of MDD patients with and without early life stress (ELS) experience.MethodsPlasma samples were collected from 25 healthy adults and 46 patients with MDD, including 23 patients with ELS and 23 patients without ELS. Furthermore, gas chromatography/mass spectrometry (GC/MS) coupled with multivariate statistical analysis was used to identify the differences in global plasma metabolites among the 3 groups.ResultsThe distinctive metabolic profiles exist either between healthy subjects and MDD patients or between the MDD patients with ELS experience (ELS/MDD patients) and the MDD patients without it (non-ELS/MDD patients), and some diagnostic panels of feature metabolites' combination have higher predictive potential than the diagnostic panels of differential metabolites.ConclusionsThese findings in this study have high potential of being used as novel laboratory diagnostic tool for MDD patients and it with ELS or not in clinical application.

Highlights

Major depressive disorder (MDD) is a serious psychiatric mood disorder, resulting in several detrimental socioeconomic effects, including increased healthy care expenditures and suicide rates [1]
Several studies reported that the depression developed in relation to early life stress experiences (ELS/MDD) have a characteristic neuroendocrine alterations associated with the pathophysiologic mechanisms of ELS/MDD [4]
To explore the characteristic metabolic alterations of ELS/ MDD, we developed a metabonomics approach that uses gas chromatography/mass spectrometry (GC/MS) coupled with multivariate statistical analysis for identifying the differences in the global plasma metabolites and generating mathematic models for diagnosis

Summary

Introduction

Major depressive disorder (MDD) is a serious psychiatric mood disorder, resulting in several detrimental socioeconomic effects, including increased healthy care expenditures and suicide rates [1]. The studies in rodents and non-human primates reported that ELS induce persistent structural, functional, and epigenomic changes in some neural circuits These changes converged in increased endocrine and autonomic reactivity to stress, anxiety-like behavior, anhedonia, cognitive impairment, pain sensitivity, and altered sleep [8,9,10]. A group has conducted a series of clinical studies concerned whether early life adverse experience in humans is associated with neurobiological changes and whether the changes are related to depression These studies focused on studying alterations of the HPA axis in subjects with histories of ELS and the results suggested that the ELS contributes to the neuroendocrine features of depression [4]. Since the ELS/ MDD may be a biologically distinguishable subtype of depression, one major question for clinical research concerned is whether there are characteristic alterations in human blood which can generate a detectable molecular phenotype for diagnoses

Methods

Results

Conclusion