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一种miRNA宿主反应特征可准确区分急性呼吸道感染的病因。

A miRNA Host Response Signature Accurately Discriminates Acute Respiratory Infection Etiologies.

作者信息

Poore Gregory D, Ko Emily R, Valente Ashlee, Henao Ricardo, Sumner Kelsey, Hong Christopher, Burke Thomas W, Nichols Marshall, McClain Micah T, Huang Erich S, Ginsburg Geoffrey S, Woods Christopher W, Tsalik Ephraim L

机构信息

Department of Biomedical Engineering, Duke University, Durham, NC, United States.

Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United States.

出版信息

Front Microbiol. 2018 Dec 11;9:2957. doi: 10.3389/fmicb.2018.02957. eCollection 2018.

Abstract

Acute respiratory infections (ARIs) are the leading indication for antibacterial prescriptions despite a viral etiology in the majority of cases. The lack of available diagnostics to discriminate viral and bacterial etiologies contributes to this discordance. Recent efforts have focused on the host response as a source for novel diagnostic targets although none have explored the ability of host-derived microRNAs (miRNA) to discriminate between these etiologies. In this study, we compared host-derived miRNAs and mRNAs from human H3N2 influenza challenge subjects to those from patients with pneumonia. Sparse logistic regression models were used to generate miRNA signatures diagnostic of ARI etiologies. Generalized linear modeling of mRNAs to identify differentially expressed (DE) genes allowed analysis of potential miRNA:mRNA relationships. High likelihood miRNA:mRNA interactions were examined using binding target prediction and negative correlation to further explore potential changes in pathway regulation in response to infection. The resultant miRNA signatures were highly accurate in discriminating ARI etiologies. Mean accuracy was 100% [88.8-100; 95% Confidence Interval (CI)] in discriminating the healthy state from pneumonia and 91.3% (72.0-98.9; 95% CI) in discriminating pneumonia from influenza infection. Subsequent differential mRNA gene expression analysis revealed alterations in regulatory networks consistent with known biology including immune cell activation and host response to viral infection. Negative correlation network analysis of miRNA:mRNA interactions revealed connections to pathways with known immunobiology such as interferon regulation and MAP kinase signaling. We have developed novel human host-response miRNA signatures for bacterial and viral ARI etiologies. miRNA host response signatures reveal accurate discrimination between pneumonia and influenza etiologies for ARI and integrated analyses of the host-pathogen interface are consistent with expected biology. These results highlight the differential miRNA host response to bacterial and viral etiologies of ARI, offering new opportunities to distinguish these entities.

摘要

尽管在大多数情况下急性呼吸道感染(ARI)的病因是病毒,但它却是抗菌药物处方的主要指征。缺乏能够区分病毒和细菌病因的诊断方法导致了这种不一致。最近的研究致力于将宿主反应作为新型诊断靶点的来源,尽管尚未有人探索宿主来源的微小RNA(miRNA)区分这些病因的能力。在本研究中,我们比较了人类H3N2流感感染受试者与肺炎患者的宿主来源的miRNA和mRNA。使用稀疏逻辑回归模型生成诊断ARI病因的miRNA特征。对mRNA进行广义线性建模以识别差异表达(DE)基因,从而能够分析潜在的miRNA与mRNA的关系。使用结合靶点预测和负相关性来检查高可能性的miRNA与mRNA相互作用,以进一步探索感染后通路调节的潜在变化。所得的miRNA特征在区分ARI病因方面具有高度准确性。在区分健康状态与肺炎时,平均准确率为100%[88.8 - 100;95%置信区间(CI)],在区分肺炎与流感感染时,平均准确率为91.3%(72.0 - 98.9;95%CI)。随后的差异mRNA基因表达分析揭示了与已知生物学一致的调节网络变化,包括免疫细胞激活和宿主对病毒感染的反应。miRNA与mRNA相互作用的负相关网络分析揭示了与已知免疫生物学通路的联系,如干扰素调节和丝裂原活化蛋白激酶信号传导。我们已经开发出用于细菌和病毒ARI病因的新型人类宿主反应miRNA特征。miRNA宿主反应特征揭示了ARI的肺炎和流感病因之间的准确区分,并且宿主 - 病原体界面的综合分析与预期生物学一致。这些结果突出了miRNA宿主对ARI细菌和病毒病因的差异反应,为区分这些病原体提供了新的机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2975/6298190/395a84aae0e5/fmicb-09-02957-g001.jpg

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