Polyunsaturated fatty acids metabolism, purine metabolism and inosine as potential independent diagnostic biomarkers for major depressive disorder in children and adolescents.
Xinyu ZhouLanxiang LiuXinghui LanDavid CohenYuqing ZhangArun V RavindranShuai YuanPeng ZhengDavid CoghillLining YangSarah E HetrickXiaofeng JiangJean-Jacques BenolielAndrea CiprianiPeng XiePublished in: Molecular psychiatry (2018)
Major depressive disorder (MDD) in children and adolescents is a recurrent and disabling condition globally but its pathophysiology remains poorly elucidated and there are limited effective treatments available. We performed metabolic profiling of plasma samples based on ultra-high-performance liquid chromatography equipped with quadrupole time-offlight mass spectrometry to explore the potential biomarkers of depression in children and adolescents with MDD. We identified several perturbed pathways, including fatty acid metabolism-particularly the polyunsaturated fatty acids metabolism, and purine metabolism-that were associated with MDD in these young patients. In addition, inosine was shown as a potential independent diagnostic biomarker for MDD, achieving an area under the ROC curve of 0.999 in discriminating drug-naive MDD patients and 0.866 in discriminating drug-treated MDD from healthy controls. Moreover, we found evidence for differences in the pathophysiology of MDD in children and adolescents to that of adult MDD, specifically with tryptophan metabolism. Through metabolomic analysis, we have identified links between a framework of metabolic perturbations and the pathophysiology and diagnostic biomarker of child and adolescent MDD.
Keyphrases
- major depressive disorder
- bipolar disorder
- mass spectrometry
- end stage renal disease
- newly diagnosed
- chronic kidney disease
- ejection fraction
- tandem mass spectrometry
- liquid chromatography
- prognostic factors
- fatty acid
- mental health
- young adults
- simultaneous determination
- emergency department
- high performance liquid chromatography
- risk assessment
- physical activity
- electronic health record
- human health
- data analysis