An immunological age index in bipolar disorder: A confirmatory factor analysis of putative immunosenescence markers and associations with clinical characteristics.

OBJECTIVES: The study aims to generate an immunological age (IA) trait on the basis of immune cell differentiation parameters, and to test whether the IA is related to age and disease characteristics. METHODS: Forty-four euthymic type I bipolar disorder patients were included in this study. Five immunosenescence-related parameters were assessed: proportions of late-differentiated cells (e.g., CD3+CD8+CD28-CD27- and CD3-CD19+IgD-CD27-), and the expression of CD69, CD71, and CD152 after stimulation. Confirmatory factor analysis was applied to generate an IA trait underling the 5 measures. RESULTS: The best-fit model was constituted by 4 parameters that were each related to an underlying IA trait, with 1 cell population positively correlated (CD3+CD8+CD28-CD27- [λ = 0.544, where λ represents the loading of the parameter onto the IA trait] and 3 markers negatively correlated (CD69 [λ = -0.488], CD71 [λ = -0.833], and CD152 [λ = -0.674]). The IA trait was associated with chronological age (ß = 0.360, p = .013) and the number of previous mood episodes (ß = 0.426, p = .006). In a mediation model, 84% of the effect between manic episodes, and IA was mediated by body mass index. CONCLUSION: In bipolar disorder type I, premature aging of the immune system could be reliably measured using an index that validated against chronological age, which was related to adverse metabolic effects of the disease course.

1H-NMR, 1H-NMR T2-edited, and 2D-NMR in bipolar disorder metabolic profiling.

BACKGROUND: The objective of this study was to identify molecular alterations in the human blood serum related to bipolar disorder, using nuclear magnetic resonance (NMR) spectroscopy and chemometrics. METHODS: Metabolomic profiling, employing 1H-NMR, 1H-NMR T2-edited, and 2D-NMR spectroscopy and chemometrics of human blood serum samples from patients with bipolar disorder (n = 26) compared with healthy volunteers (n = 50) was performed. RESULTS: The investigated groups presented distinct metabolic profiles, in which the main differential metabolites found in the serum sample of bipolar disorder patients compared with those from controls were lipids, lipid metabolism-related molecules (choline, myo-inositol), and some amino acids (N-acetyl-L-phenyl alanine, N-acetyl-L-aspartyl-L-glutamic acid, L-glutamine). In addition, amygdalin, α-ketoglutaric acid, and lipoamide, among other compounds, were also present or were significantly altered in the serum of bipolar disorder patients. The data presented herein suggest that some of these metabolites differentially distributed between the groups studied may be directly related to the bipolar disorder pathophysiology. CONCLUSIONS: The strategy employed here showed significant potential for exploring pathophysiological features and molecular pathways involved in bipolar disorder. Thus, our findings may contribute to pave the way for future studies aiming at identifying important potential biomarkers for bipolar disorder diagnosis or progression follow-up.