Evaluation of nondepleted plasma multiprotein-based model for discriminating psychiatric disorders using multiple reaction monitoring-mass spectrometry: Proof of concept study

Psychiatric evaluation relies on subjective symptoms and behavioral observation, which sometimes lead to misdiagnosis. Although there have been efforts to utilize plasma proteins as objective markers, the depletion method is time-consuming. Therefore, this study aimed to enhance previous quantification methods and construct objective discriminative models for major psychiatric disorders using nondepleted plasma. Multiple reaction monitoring-mass spectrometry(MRM-MS) assays for quantifying 453 peptides in nondepleted plasma (samples of 132 individuals—35 major depressive disorder(MDD), 47 bipolar disorder(BD), 23 schizophrenia(SCZ) patients, and 27 healthy controls(HC)) was developed. Pairwise discriminative models for MDD, BD, and SCZ, and discriminative model between patients and HC were constructed by machine learning approaches. In addition, the proteins from nondepleted plasma based discriminative models were compared with previously developed depleted plasma based discriminative models. Discriminative models for MDD vs BD, BD vs SCZ, MDD vs SCZ, and patients vs HC were constructed with 11 to 13 proteins and showed reasonable performances(AUROC=0.890~0.959). Most of the shared proteins between nondepleted and depleted plasma models had consistent directions of expression levels and were associated with neural signaling, inflammatory, and lipid metabolism pathways. These results suggest that multiprotein markers from nondepleted plasma have a potential role in psychiatric evaluation.