Modulatory effects of antidepressant classes on the innate and adaptive immune system in depression

Eyre, H.A., Lavretsky, H., Kartika, J., Qassim, A., and Baune, B.T. (2016) Modulatory effects of antidepressant classes on the innate and adaptive immune system in depression. Pharmacopsychiatry, 49 (3). pp. 85-96.

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Abstract

Current reviews exploring for unique immunemodulatory profiles of antidepressant classes are limited by focusing mainly on cytokine modulation only and neglecting other aspects of the innate and adaptive immune system. These reviews also do not include recent comparative clinical trials, immune-genetic studies and therapeutics with unique neurotransmitter profiles (e.g., agomelatine). This systematic review extends the established literature by comprehensively reviewing the effects of antidepressants classes on both the innate and adaptive immune system. Antidepressants appear, in general, to reduce pro-inflammatory factor levels, particularly C-reactive protein (CRP), tumour necrosis factor (TNF)-alpha, interleukin (IL)-1 beta and IL-6. We caution against conclusions as to which antidepressant possesses the greater anti-inflammatory effect, given the methodological heterogeneity among studies and the small number of comparative studies. The effects of antidepressant classes on adaptive immune factors are complex and poorly understood, and few studies have been conducted. Methodological heterogeneity is high among these studies (e.g., length of study, cohort characteristics, dosage used and immune marker analysis). We recommend larger, comparative studies - in clinical and pre-clinical populations.

Item ID: 45568
Item Type: Article (Research - C1)
ISSN: 1439-0795
Keywords: antidepressant, immune, innate, adaptive, inflammatory
Date Deposited: 22 Jun 2016 07:41
FoR Codes: 32 BIOMEDICAL AND CLINICAL SCIENCES > 3214 Pharmacology and pharmaceutical sciences > 321402 Clinical pharmacology and therapeutics @ 100%
SEO Codes: 92 HEALTH > 9202 Health and Support Services > 920209 Mental Health Services @ 100%
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