海洛因使用障碍患者的血清细胞因子和炎症标记物:诊断和疾病严重程度的潜在生物标记物

Eduardo R. Butelman, Yuefeng Huang, Flurin Cathomas, Pierre-Olivier Gaudreault, Panos Roussos, Scott J. Russo, Rita Z. Goldstein, Nelly Alia-Klein
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引用次数: 0

摘要

阿片类药物使用障碍会导致严重的发病率和死亡率,因此迫切需要新的机理靶点和生物标志物来进行诊断和预后。接触μ阿片受体(MOR)激动剂会导致外周血细胞因子和炎症蛋白网络以及大脑胶质细胞和神经元发生变化。海洛因使用障碍(iHUD)患者血液中多种细胞因子水平失调。然而,有关 iHUD 与健康对照组(HC)中此类标记物的综合数据,尤其是作为多目标生物标记物的数据十分有限。我们采用一种经过验证的近距离延伸测定法,对接受药物辅助治疗的 iHUD(21 人)与健康对照组(24 人)血清中的 92 种细胞因子和炎症蛋白进行了相对定量。经多重比较校正(P=0.05)后,29 个靶标显示出明显的组间差异(主要是 iHUD>HC)。其中包括 19 个典型细胞因子家族成员,包括特异性趋化因子、白细胞介素、生长因子和肿瘤坏死因子 (TNF) 相关蛋白。为了降维,将这 19 种细胞因子的数据输入主成分(PC)分析,PC1 得分为 iHUD>HC(p<0.0001)。接受者操作特征(ROC)曲线分析得出 AUROC=91.7% (p<0.0001)。在包括人口学/临床变量在内的多变量逻辑回归中,PC1 评分仍然是 HUD 组的积极预测因子。总之,这项研究显示了 iHUD 和 HC 之间存在显著差异的细胞因子,并提供了一个多目标 "细胞因子生物标志物评分",用于潜在的诊断目的和疾病严重程度的检查。
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Serum cytokine and inflammatory markers in individuals with heroin use disorder: potential biomarkers for diagnosis and disease severity
Opioid use disorders cause major morbidity and mortality, and there is a pressing need for novel mechanistic targets and biomarkers for diagnosis and prognosis. Exposure to mu-opioid receptor (MOR) agonists causes changes in cytokine and inflammatory protein networks in peripheral blood, and also in brain glia and neurons. Individuals with heroin use disorder (iHUD) show dysregulated levels of several cytokines in blood. However, there is limited data on a comprehensive panel of such markers in iHUD versus healthy controls (HC), especially as a multi-target biomarker. We used a validated proximity extension assay for relative quantification of 92 cytokines and inflammatory proteins in serum of iHUD on medication assisted therapy (MAT; n=21), versus HC (n=24). Twenty-nine targets showed significant group differences (primarily iHUD>HC), surviving multiple comparison correction (p=0.05). This included 19 members of canonical cytokine families, including specific chemokines, interleukins, growth factors, and tumor necrosis factor (TNF)-related proteins. For dimensionality reduction, data from these 19 cytokines were entered into a principal component (PC) analysis, and PC1 scores were iHUD>HC (p<0.0001). A receiver-operating characteristic (ROC) curve analysis yielded an AUROC=91.7% (p<0.0001). This PC1 score remained a positive predictor of being in the HUD group in a multivariable logistic regression, which included demographic/clinical variables. Overall, this study shows a panel of cytokines that differ significantly between iHUD and HC, and provides a multi-target “cytokine biomarker score” for potential diagnostic purposes, and examination of disease severity.
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