Bipolar disorder (BD) is a severe chronic psychiatric disorder that has been associated with cellular dysfunctions related to mitochondria, neurotrophin levels, and oxidative stress. Evidence has shown that endoplasmic reticulum (ER) stress may be a common pathway of the cellular changes described in BD. In the present study we assessed unfolded protein response (UPR) and the effects of this cellular process on lymphocytes from patients with BD. We also evaluated whether the stage of chronicity of BD was associated with changes in UPR parameters. Cultured lymphocytes from 30 patients with BD and 32 age- and sex-matched controls were treated with tunicamycin, an ER stressor, for 12 or 24 h to measure levels of UPR-related proteins (GRP78, eIF2α-P, and CHOP) using flow cytometry, and for 48 h to analyse ER stress-induced cell death. In healthy controls but not in patients we found an increase in levels of GRP78, eIF2α-P, and CHOP after ER stress induction. In addition, tunicamycin-induced cell death was significantly higher in patients compared to controls. More importantly, early-stage patients did not differ from controls while the late-stage patients showed an impaired ER stress response. Thus, dysfunction in ER-related stress response may be associated with decreased cellular resilience in BD and illness progression.

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Background/Aims: Hippocampal atrophy is a recognized biomarker of Alzheimer disease (AD) pathology. Serum brain-derived neurotrophic factor (BDNF) reduction has been associated with neurodegeneration. We aimed to evaluate BDNF serum levels and hippocampal volume in clinical AD (dementia and mild cognitive impairment [MCI]). Methods: Participants were 10 patients with MCI and 13 with dementia due to AD as well as 10 healthy controls. BDNF serum levels were determined by ELISA and volumetric measures with NeuroQuant®. Results: MCI and dementia patients presented lower BDNF serum levels than healthy participants; dementia patients presented a smaller hippocampal volume than MCI patients and healthy participants. Discussion: The findings support that the decrease in BDNF might start before the establishment of neuronal injury expressed by the hippocampal reduction.

Meta-analytical evidence suggests that brain-derived neurotrophic factor (BDNF) is altered in various psychiatric disorders. However, meta-analyses may be hampered by the heterogeneity of BDNF assays, lack of BDNF standard values and heterogeneity among the populations included in the studies. To address these issues, our study aimed to test, in a ‘true-to-life' setting, the hypothesis that the serum BDNF level is nonspecifically reduced in acute severe mental illness (SMI) patients and increases during inpatient treatment. Consecutive samples of 236 inpatients with SMI and 100 healthy controls were recruited. SMI includes schizophrenia and severe mood disorders, and is characterized in the sample by the presence of at least 2 years of psychiatric treatment and disability. Generalized estimating equations were used to analyze BDNF serum levels at admission and upon discharge controlled by confounding factors. BDNF levels increased significantly between admission and discharge in SMI patients. BDNF levels showed significant reductions compared with controls both at admission and upon discharge. In addition, BDNF levels showed no difference among SMI patient diagnostic subgroups (unipolar depression, bipolar depression, schizophrenia and manic episode). The increase but non-restoration of BDNF levels, even with the general acute improvement of clinical scores, may reflect the progression of the disorder characteristically seen in these patients. BDNF levels could be considered as a marker for the presence of a nonspecific psychiatric disorder and possibly a transdiagnostic and nonspecific marker of disease activity.

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Background Innate immune system dysfunction has been recognized as an important element in the pathophysiology of bipolar disorder (BD). We aimed to investigate whether there are differences in the response of macrophages derived from patients in the early stages and late stages of BD and healthy subjects. Methods Human monocytes purified from peripheral blood mononuclear cells (PBMCs) of patients with BD type I (n = 18)—further classified into early- and late stage BD patients according to their functioning- and from healthy individuals (n = 10) were differentiated into macrophages in vitro. Monocyte-derived macrophages (M) were exposed to IFNγ plus LPS-M(IFNγ + LPS)- or IL-4-M(IL-4)—to induce their polarization into the classical (also called M1) or alternative (also called M2) activation phenotypes, respectively; or either M ψ were not exposed to any stimuli characterizing the resting state (denominated M0). In vitro secretion of cytokines, such as IL-1β, IL-6, IL-10, and TNF-α, was used as an index of macrophage activity. Results M(IFNγ + LPS) from late-stage BD patients produced less amount of IL-1β, IL-6, and IL-10 when compared to early-stage BD patients and healthy controls. Following alternative activation, M(IL-4) derived from late-stage patients secreted less IL-6 compared to the other groups. TNFα was less secreted by all macrophage phenotypes derived from late-stage patients when compared to healthy controls only (p < 0.005). M ψ from late-stage patients exhibited lower production of IL-1β and IL-10 compared to macrophages from healthy subjects and early-stage patients respectively. Interestingly, cytokines secretion from M(IFNγ + LPS), M(IL-4) and M ψ were similar between early-stage patients and healthy controls. Conclusion Our results suggest a progressive dysfunction in the response of peripheral innate immune cells of BD patients in the late stages of the illness. This failure in the regulation of the immune system function may be implicated in the multisystemic progression of BD.

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Objective: This study used machine learning techniques combined with peripheral biomarker measurements to build signatures to help differentiating (1) patients with bipolar depression from patients with unipolar depression, and (2) patients with bipolar depression or unipolar depression from healthy controls. Methods: We assessed serum levels of interleukin-2, interleukin-4, interleukin-6, interleukin-10, tumor necrosis factor-α, interferon-γ, interleukin-17A, brain-derived neurotrophic factor, lipid peroxidation and oxidative protein damage in 54 outpatients with bipolar depression, 54 outpatients with unipolar depression and 54 healthy controls, matched by sex and age. Depressive symptoms were assessed using the Hamilton Depression Rating Scale. Variable selection was performed with recursive feature elimination with a linear support vector machine kernel, and the leave-one-out cross-validation method was used to test and validate our model. Results: Bipolar vs unipolar depression classification achieved an area under the receiver operating characteristics (ROC) curve (AUC) of 0.69, with 0.62 sensitivity and 0.66 specificity using three selected biomarkers (interleukin-4, thiobarbituric acid reactive substances and interleukin-10). For the comparison of bipolar depression vs healthy controls, the model retained five variables (interleukin-6, interleukin-4, thiobarbituric acid reactive substances, carbonyl and interleukin-17A), with an AUC of 0.70, 0.62 sensitivity and 0.7 specificity. Finally, unipolar depression vs healthy controls comparison retained seven variables (interleukin-6, Carbonyl, brain-derived neurotrophic factor, interleukin-10, interleukin-17A, interleukin-4 and tumor necrosis factor-α), with an AUC of 0.74, a sensitivity of 0.68 and 0.70 specificity. Conclusion: Our findings show the potential of machine learning models to aid in clinical practice, leading to more objective assessment. Future studies will examine the possibility of combining peripheral blood biomarker data with other biological data to develop more accurate signatures.