Olink proteomics analysis uncovers inflammatory proteins in patients with different states of bipolar disorder

Study Design: A prospective study. Background: This study aims to investigate the relationship between different states of bipolar disorder (BD) and plasma inflammatory proteins, which may be used as their biomarkers. Materials and methods: We totally collected admission plasma from 16 healthy subjects and 32 BD patients, including 16 patients with BD manic episodes (BD-M) and 16 patients with BD depressive episodes (BD-D). Ten samples in each group were analyzed by proximity extension assays of 92 inflammation-related proteins, and all samples were verified by ELISA. Receiver-operating characteristic (ROC) curve analysis was performed to identify the diagnostic ability and cut-off values of potential biomarkers. Results: Our findings showed that BD patients had significantly higher levels of IL6, MCP-1, TGF-alpha, IL8, and IL10RB in comparison with healthy subjects, and their cut-off values were 0.531 pg/ml, 0.531 pg/ml, 0.469 pg/ml, 0.406 pg/ml, and 0.406 pg/ml, respectively. The levels of IL6, MCP-1, TGF-alpha, and IL8 in BD-M patients were significantly greater than in healthy individuals, and their cut-off values were 0.813 pg/ml, 0.688 pg/ml, 0.438 pg/ml, and 0.625 pg/ml, respectively. Moreover, we found cut-off values of 0.500 pg/mL and 0.688 ng/mL for TGF-alpha and beta-NGF, respectively, even though the levels in the BD-D group were much higher than in the control group. Furthermore, BD-M patients had significantly higher levels of IL6, FGF-19, IFN-gamma, and IL-17C in comparison with BD-D patients. Likewise, 0.687 pg/ml, 0.500 pg/ml, 0.438 pg/ml, and 0.375 pg/ml were their cutoff values, respectively. Our findings also showed that the combination of these proteins had the highest diagnostic accuracy. Conclusions: Our findings showed that plasma inflammatory proteins were related to BD and its subtypes, which may be utilized as potential biomarkers of different stages of BD. Furthermore, we also found their cut-off values and their combinations to have the highest diagnostic accuracy, providing clinicians with a new method to rapidly differentiate BD and its subtypes and manage early targeted interventions.