UT Southwestern Medical Center, Center for Depression Research and Clinical Care, Department of Psychiatry, Dallas, TX, USA.
UT Southwestern Medical Center, Center for Depression Research and Clinical Care, Department of Psychiatry, Dallas, TX, USA.
J Psychiatr Res. 2017 Nov;94:1-6. doi: 10.1016/j.jpsychires.2017.05.012. Epub 2017 May 26.
Animal and human studies suggest an association between depression and aberrant immune response. Further, common inflammatory markers may change during the course of antidepressant treatment in patients. The objective of this study was to evaluate changes in inflammatory markers and clinical outcomes from subjects enrolled in the Combining Medications to Enhance Depression Outcome (CO-MED) trial. At baseline and week 12 (treatment completion), plasma samples of 102 participants were analyzed via a multiplex assay comprised of inflammatory markers using a 27-plex standard assay panel plus a 4-plex human acute phase xMAP technology based platform. We carried out analyses in two steps. First, t-tests were used to identify inflammatory marker levels that changed between baseline and week 12. For markers that were altered, logistic regression models were then conducted to look for associated changes in remission at week 12. Among the 31 inflammatory markers analyzed, several cytokines (IL-5, IFN-γ, IL-13), two chemokines (Eotaxin-1/CCL11, RANTES) and an acute-phase reactant (serum amyloid P component) showed change from baseline to week 12. However, only two indicated differential remission responses. Interestingly, increased levels of Eotaxin-1/CCL11 correlated with remission at week 12, whereas decreased levels of IFN-γ correlated with non-remission at week 12. Results suggest that these inflammatory proteins may serve as predictors of treatment response.
动物和人体研究表明,抑郁与异常免疫反应之间存在关联。此外,在接受抗抑郁治疗的患者中,常见的炎症标志物可能会发生变化。本研究的目的是评估入组联合用药改善抑郁结局(CO-MED)试验的受试者的炎症标志物变化和临床结局。在基线和第 12 周(治疗完成时),通过 27 个指标的标准检测面板和基于 4 个指标的人类急性期 xMAP 技术的 27 指标多重分析试剂盒,分析了 102 名参与者的血浆样本。我们分两步进行分析。首先,采用 t 检验来确定基线和第 12 周之间发生变化的炎症标志物水平。对于发生变化的标志物,然后进行逻辑回归模型分析,以寻找第 12 周时缓解相关的变化。在分析的 31 个炎症标志物中,几种细胞因子(IL-5、IFN-γ、IL-13)、两种趋化因子(Eotaxin-1/CCL11、RANTES)和一种急性期反应物(血清淀粉样蛋白 P 成分)显示出从基线到第 12 周的变化。然而,只有两个指标表明缓解有差异。有趣的是,Eotaxin-1/CCL11 水平的升高与第 12 周时的缓解相关,而 IFN-γ 水平的降低与第 12 周时的非缓解相关。结果表明,这些炎症蛋白可能作为治疗反应的预测因子。