病毒感染患者的转录组扰动是影响症状和死亡率的一个经常出现的主题，然而对相关转录组的详细理解和鲁棒生物标志物的识别尚不完整。在本研究中，我们手动收集了23个与16种呼吸道病毒感染相关的数据集，涵盖了6197个血液转录组。我们应用了全面的系统生物学方法，从全血转录组开始，结合多层次的生物信息学分析，对表达、功能途径和蛋白-蛋白互作网络进行了表征，以识别鲁棒的生物标志物和疾病共病症。我们鉴定出了感染不同病毒的鲁棒基因标志物，可以准确地对正常和感染患者进行训练和验证队列的分类。不同病毒的生物过程(BP)表现出很大的相似性，并富集于感染和免疫反应途径。基于网络的分析揭示了各种病毒感染与神经系统疾病、肿瘤和代谢性疾病的相关性，并与脑组织显著相关。总之，我们手动收集的转录组和全面的分析揭示了病毒感染过程中的关键分子标志物和疾病共病症，这为呼吸道病毒感染后续公共卫生事件的预防提供了有价值的理论基础。

Perturbation of transcriptome in viral infection patients is a recurrent theme impacting symptoms and mortality, yet a detailed understanding of pertinent transcriptome and identification of robust biomarkers is not complete. In this study, we manually collected 23 datasets related to 6,197 blood transcriptomes across 16 types of respiratory virus infections. We applied a comprehensive systems biology approach starting with whole-blood transcriptomes combined with multilevel bioinformatics analyses to characterize the expression, functional pathways, and protein-protein interaction (PPI) networks to identify robust biomarkers and disease comorbidities. Robust gene markers of infection with different viruses were identified, which can accurately classify the normal and infected patients in train and validation cohorts. The biological processes (BP) of different viruses showed great similarity and enriched in infection and immune response pathways. Network-based analyses revealed that a variety of viral infections were associated with nervous system diseases, neoplasms and metabolic diseases, and significantly correlated with brain tissues. In summary, our manually collected transcriptomes and comprehensive analyses reveal key molecular markers and disease comorbidities in the process of viral infection, which could provide a valuable theoretical basis for the prevention of subsequent public health events for respiratory virus infections.