Inflammation and Depression: A Nervous Plea for Psychiatry to Not Become Immune to Interpretation

Konsman, Jan Pieter

doi:10.3390/ph12010029

Cited by 21 publications

(15 citation statements)

References 130 publications

(156 reference statements)

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“…Many of the non-inflammatory components contributing to fatigue are modulated by or modulate inflammatory processes. Regardless, inflammatory mediators are reported to affect different aspects that contribute to fatigue including motivation (53), sleepiness (54, 55), cognition (56), anxiety (57), depression (58, 59), and stress (60).…”

Section: Inflammationmentioning

confidence: 99%

Fatigue, Sleep, and Autoimmune and Related Disorders

2019

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Profound and debilitating fatigue is the most common complaint reported among individuals with autoimmune disease, such as systemic lupus erythematosus, multiple sclerosis, type 1 diabetes, celiac disease, chronic fatigue syndrome, and rheumatoid arthritis. Fatigue is multi-faceted and broadly defined, which makes understanding the cause of its manifestations especially difficult in conditions with diverse pathology including autoimmune diseases. In general, fatigue is defined by debilitating periods of exhaustion that interfere with normal activities. The severity and duration of fatigue episodes vary, but fatigue can cause difficulty for even simple tasks like climbing stairs or crossing the room. The exact mechanisms of fatigue are not well-understood, perhaps due to its broad definition. Nevertheless, physiological processes known to play a role in fatigue include oxygen/nutrient supply, metabolism, mood, motivation, and sleepiness—all which are affected by inflammation. Additionally, an important contributing element to fatigue is the central nervous system—a region impacted either directly or indirectly in numerous autoimmune and related disorders. This review describes how inflammation and the central nervous system contribute to fatigue and suggests potential mechanisms involved in fatigue that are likely exhibited in autoimmune and related diseases.

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Section: Inflammationmentioning

confidence: 99%

Fatigue, Sleep, and Autoimmune and Related Disorders

2019

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“…Decreased levels of serotonin in the hippocampus will cause an increased dopamine in mesolimbic dopamine neuronal cells. Increased mesolimbic dopamine will cause a decrease in dopamine in the mesocortical area so that it will cause the sufferer to experience a decrease in mood which results in depressive symptoms [7], [8], [9], [10].…”

Section: Discussionmentioning

confidence: 99%

Antidepressant Effect of Cinnamon (Cinnamomum burmannii) Bark Extract in Chronic Stress-Induced Rats

Parisa¹,

Hidayat²,

Maritska³

et al. 2020

Open Access Maced J Med Sci

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BACKGROUND: Depression is a psychiatric disorder that has become a serious health problem in the past decade. This disorder is characterized by prolonged dysphoric mood, and in more severe condition would result in decreased self-care and even life-threatening action. Serotonin is believed to play a role in the regulation of mood elation in depressive disorders. Decreased levels of serotonin in the hippocampus will cause an increased dopamine in mesolimbic dopamine neuronal cells. An effective and commonly used drug is the selective serotonin reuptake inhibitor, namely, fluoxetine. However, this agent has so many side effects, one of them is erectile dysfunction. In order to find the better treatment, exploration and discovery of therapeutic modalities need to pursued using natural materials. AIM: This study aimed to explore and evaluate antidepressant effects of cinnamon (Cinnamomum burmannii) extract (CE). METHODS: A total of 30 male Wistar rats were obtained from Eureka Research Laboratory (Palembang, Indonesia). Cinnamon simplisia was obtained from the Institute for Research and Testing of Traditional Medicine, Tawangmangu, Central Java, Indonesia. Rats were induced using chronic mild stress (CMS). CMS was a form of stress induction performed on experimental animals continuously, for 4 weeks. Forced swimming test (FST) was a test conducted to assess mobility in animal model. After induction for 4 weeks, rats were randomly divided into six groups which each contained five rats: Normal control group, CMS group (negative control), CMS + fluoxetin (Fluox 1: mg/kg), CMS + CE 25 mg/kg, the CMS + CE 50 mg/kg, and the CMS + CE 100 mg/kg. Treatment with fluoxetine or CE was given for 14 days intragastrically using gastric sonde. After treatment and FST, organ evacuation was performed and followed by immunohistochemistry and enzyme-linked immunosorbent examination. RESULTS: This study showed that CE with dose of 25 mg/kg BW to dose 100 mg/k BW could reduce the duration of immobility when compared to the CMS group. Clinically, CE possessed the potential to reduce the duration of immobility and potentially reduce symptoms of depression. Histologically, CE showed the potential to improve serotonin levels in the hippocampus with increasing doses. Tumor necrosis factor (TNF)-alpha expression in the hippocampus as a marker of inflammation had increased in the CMS group. CE was able to reduce the expression of TNF-alpha compared to the CMS group. CONCLUSION: CE possessed antidepressant efficacy by inhibiting the inflammatory process in the hippocampus so it was able to optimally increase serotonin levels in the hippocampus.

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“…First, many theories and hypotheses are described in terms of "inflammation" (e.g., Dooley et al, 2018;Miller et al, 2009;Moriarity et al, 2018;Slavich, 2020), not individual proteins, underscoring a disconnect between theory and analysis. Further, there are concerns about the degree to which any individual protein can be considered a true "biomarker" of inflammation (Konsman, 2019). This approach also invites concerns with multiple comparisons that could be addressed using composite variables.…”

Section: Introductionmentioning

confidence: 99%

A Physiometric Investigation of Inflammatory Composites: Comparison of “A Priori” Aggregates, Empirically-identified Factors, and Individual Proteins

et al. 2021

Preprint

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Much inflammation research examines individual proteins; however, some studies have used summed score composites of all available inflammatory markers without first investigating dimensionality. Using three different samples (MIDUS-2: N = 1,255 adults, MIDUS-R: N =863 adults, and ACE: N = 315 adolescents), this study investigates the dimensionality of eight inflammatory proteins (C-reactive protein (CRP), interleukin (IL)-6, IL-8, IL-10, tumor necrosis factor-a; (TNF-a;), fibrinogen, E-selectin, and intercellular adhesion molecule (ICAM)-1) and compares the resulting factor structure to a) an a priori factor structure in which all inflammatory proteins equally load onto a single dimension (a technique that has been used previously) and b) proteins modeled individually (i.e., no latent variable) in terms of model fit, replicability, reliability, temporal stability, and their associations with medical history and depression symptoms. A hierarchical factor structure with two first-order factors (Factor 1A: CRP, IL-6, fibrinogen; Factor 2A: TNFa;, IL-8, IL-10, ICAM-1, IL-6) and a second-order general inflammation factor was identified in MIDUS-2 and replicated in MIDUS-R and partially replicated in ACE (which unfortunately only had CRP, IL-6, IL-8, IL-10, and TNFa; but, unlike the other two, has longitudinal data). Both the empirically-identified structure and modeling proteins individually fit the data better compared to the one-dimensional a priori structure. Results did not clearly indicate whether the empirically-identified factor structure or the individual proteins modeled without a latent variable had superior model fit. Modeling the empirically-identified factors and individual proteins (without a latent factor) as outcomes of medical diagnoses resulted in comparable conclusions, but modeling empirically-identified factors resulted in fewer results lost to correction for multiple comparisons. Importantly, when the factor scores were recreated in a longitudinal dataset, none of the individual proteins, the a priori factor, or the empirically-identified general inflammation factor significantly predicted concurrent depression symptoms in multilevel models. However, both empirically-identified first-order factors were significantly associated with depression, in opposite directions. Measurement properties are reported for the different aggregates and individual proteins as appropriate, which can be used in the design and interpretation of future studies. These results indicate that modeling inflammation as a unidimensional construct equally associated with all available proteins does not fit the data well. Instead, empirically-supported aggregates of inflammation, or individual inflammatory markers, should be used in accordance with theory. Further, the aggregation of shared variance achieved by constructing empirically-supported aggregates might increase predictive validity compared to other modeling choices, maximizing statistical power.

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Inflammation and Depression: A Nervous Plea for Psychiatry to Not Become Immune to Interpretation

Cited by 21 publications

References 130 publications

Fatigue, Sleep, and Autoimmune and Related Disorders

Fatigue, Sleep, and Autoimmune and Related Disorders

Antidepressant Effect of Cinnamon (Cinnamomum burmannii) Bark Extract in Chronic Stress-Induced Rats

A Physiometric Investigation of Inflammatory Composites: Comparison of “A Priori” Aggregates, Empirically-identified Factors, and Individual Proteins

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