Center for Applied Genomics and Precision Medicine, Duke University, Durham, North Carolina; Division of Infectious Diseases, Duke University Medical Center, Durham, North Carolina.
Division of Infectious Diseases, Duke University Medical Center, Durham, North Carolina.
Transl Res. 2020 May;219:1-12. doi: 10.1016/j.trsl.2020.02.005. Epub 2020 Feb 20.
Invasive aspergillosis (IA) is a major cause of critical illness in immunocompromised (IC) patients. However, current fungal tests are limited. Disease-specific gene expression patterns in circulating host cells show promise as novel diagnostics, however it is unknown whether such a 'signature' exists for IA and the effect of iatrogenic immunosuppression on any such biomarkers. Male BALB/c mice were separated into 6 experimental groups based on Aspergillus fumigatus inhalational exposure and IC status (no immunosuppression, cyclophosphamide, and corticosteroids). Mice were sacrificed 4 days postinfection. Whole blood was assayed for transcriptomic responses in peripheral white blood cells via microarray. An elastic net regularized logistic regression was employed to develop classifiers of IA based on gene expression. Aspergillus infection triggers a powerful response in non-IC hosts with 2718 genes differentially expressed between IA and controls. We generated a 146-gene classifier able to discriminate between non-IC infected and uninfected mice with an AUC of 1. However, immunosuppressive medications exhibited a confounding effect on this transcriptomic classifier. After controlling for the genomic effects of immunosuppression, we were able to generate a 187-gene classifier with an AUC of 0.92 in the absence of immunosuppression, 1 with cyclophosphamide, and 0.9 with steroids. The host transcriptomic response to IA is robust and conserved. Pharmacologic perturbation of the host immune response has powerful effects on classifier performance and must be considered when developing such novel diagnostics. When appropriately designed, host-derived peripheral blood transcriptomic responses demonstrate the ability to accurately diagnose Aspergillus infection, even in the presence of immunosuppression.
侵袭性曲霉病（IA）是免疫功能低下（IC）患者发生重症的主要原因。然而，目前的真菌检测方法有限。循环宿主细胞中特定疾病的基因表达模式具有成为新型诊断方法的潜力，但是否存在用于 IA 的此类“特征”以及此类生物标志物是否受到医源性免疫抑制的影响尚不清楚。雄性 BALB/c 小鼠根据烟曲霉吸入暴露和 IC 状态（无免疫抑制、环磷酰胺和皮质类固醇）分为 6 个实验组。感染后 4 天处死小鼠。通过微阵列检测外周血白细胞中的转录组反应。采用弹性网络正则化逻辑回归方法，基于基因表达开发 IA 的分类器。曲霉感染在非 IC 宿主中引发强烈反应，IA 与对照组之间有 2718 个基因表达差异。我们生成了一个 146 基因的分类器，能够区分非 IC 感染和未感染的小鼠，AUC 为 1。然而，免疫抑制药物对这种转录组分类器有混杂影响。在控制免疫抑制的基因组效应后，我们能够在无免疫抑制、使用环磷酰胺和使用类固醇的情况下分别生成 AUC 为 0.92、1 和 0.9 的 187 基因分类器。宿主对 IA 的转录组反应是强大且保守的。宿主免疫反应的药物干扰对分类器性能有强大影响，在开发此类新型诊断方法时必须加以考虑。当适当设计时，源自宿主的外周血转录组反应能够准确诊断曲霉感染，即使在存在免疫抑制的情况下也是如此。
