Michael Maes, Mengqi Niu, Annabel Maes, Yiping Luo, Chenkai Yangyang, Abbas F. Almulla, Jin Li, Yingqian Zhang
BACKGROUND: Major depressive disorder (MDD) is a neuro-immune, oxidative, and nitrosative stress (NIMETOX) disorder, in which peripheral immune-redox pathways intersect with metabolic networks leading to neurotoxicity within the limbic-prefrontal affective circuits. Comprehensive metabolomics analysis in well-phenotyped patients is vital to elucidate their metabolic profile. OBJECTIVES: To identify metabolic abnormalities that differentiate in patients with severe MDD from healthy controls(HCs) through high-resolution, untargeted metabolomics. METHODS: Serum samples from 125 MDD inpatients and 40 HCs were analyzed utilizing liquid chromatography(LC) and mass spectrometry(MS). A meticulously regulated multistage machine-learning pipeline with leakage-prevention protocols was employed to analyze differences between MDD and controls and to predict phenome scores. RESULTS: Feature selection showed that 16 metabolites and 6 functional modules reliably distinguished MDD. The functional profile of the metabolites indicates a convergence of lipotoxicity, phospholipid(PL) remodeling, disruptions in fatty acid(FA) metabolism, mitochondrial redox imbalance, ether-lipid metabolism, and antioxidant depletion. This MDD metabotype was not affected by metabolic syndrome(MetS). A substantial portion of the variance in overall depression severity (72.5%), physiosomatic symptoms (55.8%), and suicidal ideation(SI) (23.6%) was accounted for by increased lipotoxicity, PL remodeling, and FA storage/signaling. The recurrence of illness (27.7%) was associated with a self-reinforcing lipid-redox-inflammatory module that maintains cellular stress. DISCUSSION: , and lipid-redox intersections might be important drug targets to treat MDD.