双相抑郁及单相抑郁的免疫及应激相关因子的特征比较
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北京市医院管理中心临床医学发展专项“扬帆”计划临床技术创新项目(XMLX202128)


Comparison of immune and stress-related indicators between patients with bipolar depression and unipolar depression
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    摘要:

    目的 比较双相抑郁及单相抑郁在免疫及应激相关因子方面的差异,探索鉴别单相抑郁 与双相抑郁潜在的外周血生物标志物。方法 选取首都医科大学附属北京安定医院 2018 年 1— 12 月 的住院患者作为研究对象,本研究纳入单相抑郁患者 933 例,双相抑郁患者 546 例。对两组人群的一般 人口学资料及生物指标进行比较,生物指标包括 C 反应蛋白(CRP)、补体 3(C3)、补体 4(C4)、免疫球蛋白 G(IgG)、免疫球蛋白 M(IgM)、免疫球蛋白 A(IgA)、促肾上腺皮质激素(ACTH)及皮质醇。应用 Logistic 回 归分析控制混杂因素,明确两种抑郁类型与各生物指标的相关性,并采用受试者工作特征(ROC)曲线 分析上述与双相抑郁相关的人口学及生物学指标对双相抑郁的预测价值。结果 双相抑郁及单相抑郁 在 C3(Z=3.41,P=0.001)、IgG(Z=-2.04,P=0.041)、IgA(Z=-4.30,P< 0.001)、ACTH(Z=2.03,P=0.042)生物 指标方面差异有统计学意义(P< 0.05)。Logistic 回归分析显示,年龄(OR=0.98,95%CI=0.97~0.98)、性 别(OR=0.62,95%CI=0.49~0.78)、C3(OR=3.45,95%CI=1.90~6.27)和 IgA(OR=0.80,95%CI=0.71~0.91) 与双相抑郁相关。ROC 曲线分析示,C3、IgA 及年龄单独对双相抑郁及单相抑郁分类的准确性较差, 曲线下面积(AUC)为 0.55~0.63,将上述指进行 Logistic 回归建模后,其对双相抑郁预测的 AUC 为 0.66 (P< 0.05),灵敏度为 65%,特异度为 63%。结论 年龄偏小、C3 水平升高及 IgA 水平偏低是双相抑郁的 相关影响因素;与单个生物指标相比,纳入 C3、IgA、性别、年龄的联合诊断模型在区分单相抑郁及双相 抑郁方面更有效。

    Abstract:

    Objective To compare the differences of immune and stress related factors between bipolar depression and unipolar depression, and to further explore potential peripheral blood biomarkers of these two kinds of depressions. Methods The inpatients of Beijing Anding Hospital Affiliated to Capital Medical University from January to December 2018 were selected as the research objects. 933 patients with monophasic depression and 546 patients with bipolar depression were included in this study. Demographic data and biochemical indicators were compared between the two groups. The biochemical indicators included C-reactive protein (CRP), complement 3 (C3), complement 4 (C4), immunoglobulin M (IgM), immunoglobulin G (IgG), immunoglobulin A (IgA), adrenocorticotropic hormone (ACTH) and cortisol. Logistic regression analysis was used to control the confounding factors and clarify the correlation between the two types of depression and various biological indexes. Receiver operating characteristic (ROC) curve was used to analyze the predictive value of the above demographic and biological indexes related to bipolar depression. Results Bipolar depression and unipolar depression were different in the terms of C3 (Z=3.41, P=0.001), IgG (Z=-2.04, P=0.041), IgA (Z= -4.30, P< 0.001) and ACTH (Z=2.03, P=0.042), with statistical significance (P< 0.05). Logistic regression analysis showed that age (OR=0.98, 95%CI=0.97-0.98), gender (OR=0.62, 95%CI=0.49-0.78), C3 (OR=3.45, 95%CI=1.90-6.27) and IgA (OR=0.80, 95%CI=0.71-0.91) were associated with bipolar depression. ROC analysis showed that C3, IgA and age alone had poor accuracy in the classification of bipolar depression and monophasic depression, and the area under the curve (AUC) was 0.55-0.63. After logistic regression modeling, the AUC of predicting bipolar depression was 0.66 (P< 0.05), the sensitivity was 65%, and the specificity was 63%. Conclusions Younger age, higher levels of C3, and lower levels of IgA are related factors of bipolar depression. Compared with a single biological index, the combined diagnostic model including C3, IgA, gender and age is more effective in distinguishing monophasic depression from bipolar depression.

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赵茜,尹利,付冰冰,杨帆,吕楠.双相抑郁及单相抑郁的免疫及应激相关因子的特征比较[J].神经疾病与精神卫生,2022,22(3):
DOI :10.3969/j. issn.1009-6574.2022.03.005.

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  • 在线发布日期: 2022-03-28