抑郁症是一种普遍存在的致残疾病,对全球发病率和死亡率有重大影响。尽管免疫系统在其发病机制中的作用日益被人们所认识,对于先天和适应性免疫细胞的参与缺乏全面的了解。为了解决这个差距,我们进行了一项多中心病例对照研究,纳入了性别和年龄相匹配的121名参与者.这些参与者有活动性(或当前)重度抑郁发作(MDE)(39例)或缓解的MDE(40例)。包括患有重度抑郁症或躁郁症的个体。我们将这79例患者与42例健康对照(HC)进行了比较,分析他们的免疫学特征。在血液样本中,我们使用流式细胞术测定了完整的细胞计数以及单核细胞亚型和淋巴细胞T细胞群.此外,我们测量了一组细胞因子,趋化因子,和血浆中的神经营养因子。与HC相比,支持当前MDE的人显示单核细胞增多症(p=0.001),高敏C反应蛋白(p=0.002),和红细胞沉降率(p=0.003),和特定单核细胞亚群的比例改变。CD4淋巴细胞呈现激活标志物CD69+(p=0.007)和耗尽标志物PD1+(p=0.013)和LAG3+(p=0.014)的中位数百分比增加,以及更高频率的CD4+CD25+FOXP3+调节性T细胞(p=0.003)。此外,患者显示血浆sTREM2水平升高(p=0.0089).这些变化更可能是状态标记,表明在活动性MDE期间存在持续的炎症反应。随机森林模型对MDE和MDE的分类精度达到了83.8%。HC和70%用于区分活跃和缓解的MDE。有趣的是,聚类分析在MDE患者中确定了三种不同的免疫学特征.第1簇的白细胞数量最高,主要由淋巴细胞计数增加和促炎细胞因子水平最低引起。第3组显示出最强烈的炎症模式,有高水平的TNFα,CX3CL1,IL-12p70,IL-17A,IL-23和IL-33与IL-10的最高水平以及β-NGF和BDNF的最低水平相关。该曲线还与循环单核细胞的最高绝对数量和百分比以及循环淋巴细胞的最低绝对数量和百分比有关。表示活跃的炎症过程。第2组有一些更急性炎症的主要迹象,如CCL2水平升高和促炎细胞因子如IL-1β水平升高,IFNγ,和CXCL8。同样,单核细胞的绝对数量更接近HC值,以及淋巴细胞的百分比,提示炎症过程可能开始。这项研究为免疫系统在MDE中的作用提供了新的见解,为可复制的前瞻性研究奠定了基础,这些研究旨在开发诊断和预后工具以及新的治疗靶标。
Depression is a prevalent and incapacitating condition with a significant impact on global morbidity and mortality. Although the immune system\'s role in its pathogenesis is increasingly recognized, there is a lack of comprehensive understanding regarding the involvement of innate and adaptive immune cells. To address this gap, we conducted a multicenter
case-control study involving 121 participants matched for sex and age. These participants had either an active (or current) major depressive episode (MDE) (39 cases) or a remitted MDE (40 cases), including individuals with major depressive disorder or bipolar disorder. We compared these 79 patients to 42 healthy controls (HC), analyzing their immunological profiles. In blood samples, we determined the complete cell count and the monocyte subtypes and lymphocyte T-cell populations using flow cytometry. Additionally, we measured a panel of cytokines, chemokines, and neurotrophic factors in the plasma. Compared with HC, people endorsing a current MDE showed monocytosis (p = 0.001), increased high-sensitivity C-reactive protein (p = 0.002), and erythrocyte sedimentation rate (p = 0.003), and an altered proportion of specific monocyte subsets. CD4 lymphocytes presented increased median percentages of activation markers CD69+ (p = 0.007) and exhaustion markers PD1+ (p = 0.013) and LAG3+ (p = 0.014), as well as a higher frequency of CD4+CD25+FOXP3+ regulatory T cells (p = 0.003). Additionally, patients showed increased plasma levels of sTREM2 (p = 0.0089). These changes are more likely state markers, indicating the presence of an ongoing inflammatory response during an active MDE. The Random Forest model achieved remarkable classification accuracies of 83.8% for MDE vs. HC and 70% for differentiating active and remitted MDE. Interestingly, the cluster analysis identified three distinct immunological profiles among MDE patients. Cluster 1 has the highest number of leukocytes, mainly given by the increment in lymphocyte count and the lowest proinflammatory cytokine levels. Cluster 3 displayed the most robust inflammatory pattern, with high levels of TNFα, CX3CL1, IL-12p70, IL-17A, IL-23, and IL-33, associated with the highest level of IL-10, as well as β-NGF and the lowest level for BDNF. This profile is also associated with the highest absolute number and percentage of circulating monocytes and the lowest absolute number and percentage of circulating lymphocytes, denoting an active inflammatory process. Cluster 2 has some cardinal signs of more acute inflammation, such as elevated levels of CCL2 and increased levels of proinflammatory cytokines such as IL-1β, IFNγ, and CXCL8. Similarly, the absolute number of monocytes is closer to a HC value, as well as the percentage of lymphocytes, suggesting a possible initiation of the inflammatory process. The study provides new insights into the immune system\'s role in MDE, paving the ground for replication prospective studies targeting the development of diagnostic and prognostic tools and new therapeutic targets.