Because major depressive disorder (MDD) and bipolar disorder (BD) manifest with similar symptoms and are diagnosed by subjective observations, misdiagnosis is a persistent issue, necessitating their differentiation through objective methods. In response, researchers have begun to discriminate between MDD and BD via proteomic approaches. This study used a multiple reaction monitoring-mass spectrometry (MRM-MS)-based targeted proteomic approach in differentiating between these disorders.

MRM-MS analysis was performed to quantify potential targets (210 proteins) in 90 MDD patients, 90 BD patients, and 90 healthy controls (HCs), aged 19 to 65 years. The light-to-heavy peptide peak area ratios (PARs) of 210 proteins were calculated and these PARs were used to develop a multiprotein model for discriminating MDD and BD. After the training and test sets were designated by random splitting, the least absolute shrinkage and selection operator (LASSO) regression with 100 repeated 10-fold crossvalidation, feature extraction, and model averaging was applied to the training set to develop a generalizable model. The model was evaluated using a test set.

Total 270 individual plasma samples. The final cohort was composed of MDD (n=90), BD (n=90) consisted of 43 BD-1, 43 BD-2, and 4 BD-NOS, and HCs (n=90).