Leveraging systems biology for predicting modulators of inflammation in patients with COVID-19
Leveraging systems biology for predicting modulators of inflammation in patients with COVID-19
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DOI：
10.1126/sciadv.abe5735
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发表时间：
2021-02-01
期刊：
影响因子：
13.6
通讯作者：
del Sol，Antonio
中科院分区：
文献类型：
--
作者：
Jung，Sascha;Potapov，Ilya;del Sol，Antonio
身体对病原体的炎症反应失调可能会发展为过度炎症状态，这种情况会因正反馈回路而放大，并与严重程度和死亡率增加相关。因此，需要确定治疗靶点来调节这种病理性免疫反应。在这里，我们提出了一种基于单细胞的计算方法，用于基于生理和病理条件的功能性细胞间通讯网络的重建和分析来预测调节失调的炎症反应的蛋白质。我们在 12 个人类疾病数据集中验证了所提出的方法，并对 2019 年冠状病毒病的轻度和重度症状患者进行了深入研究，以预测新的治疗靶点。结果，我们确定了细胞外基质蛋白多功能蛋白聚糖和 Toll 样受体 2 作为调节炎症反应的潜在靶标。总之，所提出的方法在系统地识别调节病理免疫反应的治疗靶点方面具有很大的实用性。
Dysregulations in the inflammatory response of the body to pathogens could progress toward a hyperinflammatory condition amplified by positive feedback loops and associated with increased severity and mortality. Hence, there is a need for identifying therapeutic targets to modulate this pathological immune response. Here, we propose a single cell–based computational methodology for predicting proteins to modulate the dysregulated inflammatory response based on the reconstruction and analysis of functional cell-cell communication networks of physiological and pathological conditions. We validated the proposed method in 12 human disease datasets and performed an in-depth study of patients with mild and severe symptomatology of the coronavirus disease 2019 for predicting novel therapeutic targets. As a result, we identified the extracellular matrix protein versican and Toll-like receptor 2 as potential targets for modulating the inflammatory response. In summary, the proposed method can be of great utility in systematically identifying therapeutic targets for modulating pathological immune responses.