ContextChronic systemic inflammation in obesity originates from local immune responses in visceral adipose tissue. However, assessment of a broad range of inflammation-mediating cytokines and their relationship to physical activity and adipometrics has scarcely been reported to date.ObjectiveTo characterize the profile of a broad range of pro- and anti-inflammatory cytokines and the impact of physical activity and energy expenditure in individuals with general obesity, central obesity, and non-obese subjects.Design, Setting, and ParticipantsA cross-sectional study comprising 117 obese patients (body mass index (BMI) ≥ 30) and 83 non-obese community-based volunteers.Main Outcomes MeasuresSerum levels of interleukin (IL)-2, IL-4, IL-5, IL-10, IL-12, IL-13, granulocyte-macrophage colony-stimulating factor (GM-CSF), interferon (IFN)-γ and tumor necrosis factor (TNF)-α were measured. Physical activity and energy expenditure (MET) were assessed with actigraphy. Adipometrics comprised BMI, weight, abdominal-, waist- and hip-circumference, waist to hip ratio (WHR), and waist-to-height-ratio (WHtR).ResultsGeneral obesity was associated with significantly elevated levels of IL-5, IL-10, IL-12, IL-13, IFN-γ and TNF-α, central obesity with significantly elevated IL-5, IL-10, IL-12, IL-13 and IFN-γ-levels. In participants with general obesity, levels of IL-4, IL-10 and IL-13 were significantly elevated in participants with low physical activity, even when controlled for BMI which was negatively associated with physical acitivity. Cytokines significantly correlated with adipometrics, particularly in obese participants.ConclusionsResults confirm up-regulation of certain pro- and anti-inflammatory cytokines in obesity. In obese subjects, physical activity may lower levels and thus reduce pro-inflammatory effects of cytokines that may link obesity, insulin resistance and diabetes.

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Weight gain and metabolic disturbances are common side effects during psychopharmacological treatment with specific antipsychotics and antidepressants. The antipsychotics clozapine and olanzapine, and antidepressants tricyclics and mirtazapine have a high risk of inducing weight gain. Recently discovered pathophysiological mechanisms include antihistaminergic effects, activation of hypothalamic adenosine monophosphate-activated protein kinase (AMPK), modulation of hormonal signaling of ghrelin and leptin, changes in the production of cytokines such as tumor necrosis factor-alpha (TNF)-alpha and adipokines such as adiponektin, and the impact of genes, in particular the melanocortin 4 receptor (MC4R), serotonin 2C receptor (HTR2C), leptin, neuropeptide Y (NPY) and cannabinoid receptor 1 (CNR1) genes. Metabolic changes associated with weight gain include disturbances of glucose and lipid metabolism. Clozapine and olanzapine may, in addition to mechanisms resulting from weight gain, impair glucose metabolism by blockade of the muscarinic M3 receptor (M3R). Antidepressants associated with weight gain appear to have fewer unfavourable effects on glucose and lipid metabolism than the second-generation antipsychotics clozapine and olanzapine. To assess the risk of weight gain and its consequences for the patient's health, assessing body weight changes and metabolic monitoring in the first week of treatment as well as in long-term treatment is recommended.

Background/Aim: Recently, a framework has been presented that links vigilance regulation, i.e. tonic brain arousal, with clinical symptoms of affective disorders. Against this background, the aim of this study was to deepen the knowledge of vigilance regulation by (1) identifying different patterns of vigilance regulation at rest in healthy subjects (n = 141) and (2) comparing the frequency distribution of these patterns between unmedicated patients with major depression (MD; n = 30) and healthy controls (HCs; n = 30). Method: Each 1-second segment of 15-min resting EEGs from 141 healthy subjects was classified as 1 of 7 different vigilance stages using the Vigilance Algorithm Leipzig. K-means clustering was used to distinguish different patterns of EEG vigilance regulation. The frequency distribution of these patterns was analyzed in independent data of 30 unmedicated MD patients and 30 matched HCs using a χ² test. Results: The 3-cluster solution with a stable, a slowly declining and an unstable vigilance regulation pattern yielded the highest mathematical quality and performed best for separation of MD patients and HCs (χ² = 13.34; p < 0.001). Patterns with stable vigilance regulation were found significantly more often in patients with MD than in HCs. Conclusion: A stable vigilance regulation pattern, derived from a large sample of HCs, characterizes most patients with MD and separates them from matched HCs with a sensitivity between 67 and 73% and a specificity between 67 and 80%. The pattern of vigilance regulation might be a useful biomarker for delineating MD subgroups, e.g. for treatment prediction.

Background: In major depressive disorder (MDD), findings include hyperstable regulation of brain arousal measured by electroencephalography (EEG) vigilance analysis and alterations in serum levels of cytokines. It is also known that cytokines affect sleep-wake regulation. This study investigated the relationship between cytokines and EEG vigilance in participants with MDD and nondepressed controls, and the influence of cytokines on differences in vigilance between the two groups. Methods: In 60 patients with MDD and 129 controls, 15-min resting-state EEG recordings were performed and vigilance was automatically assessed with the VIGALL 2.0 (Vigilance Algorithm Leipzig). Serum levels of the wakefulness-promoting cytokines interleukin (IL)-4, IL-10, IL-13 and somnogenic cytokines tumor necrosis factor-α, interferon-γ and IL-2 were measured prior to the EEG. Results: Summed wakefulness-promoting cytokines, but not somnogenic cytokines, were significantly associated with the time course of EEG vigilance in the MDD group only. In both groups, IL-13 was significantly associated with the course of EEG vigilance. In MDD compared to controls, a hyperstable EEG vigilance regulation was found, significant for group and group × time course interaction. After controlling for wakefulness-promoting cytokines, differences in vigilance regulation between groups remained significant. Conclusions: The present study demonstrated a relationship between wakefulness-promoting cytokines and objectively measured EEG vigilance as an indicator for brain arousal. Altered brain arousal regulation in MDD gives support for future evaluation of vigilance measures as a biomarker in MDD. Since interactions between cytokines and EEG vigilance only moderately differed between the groups and cytokine levels could not explain the group differences in EEG vigilance regulation, cytokines and brain arousal regulation are likely to be associated with MDD in independent ways.