tetano
Editor, Senior Moderator
Sci Adv
. 2021 Feb 3;7(6):eabe5735.
doi: 10.1126/sciadv.abe5735. Print 2021 Feb.
Leveraging systems biology for predicting modulators of inflammation in patients with COVID-19
Sascha Jung[SUP] 1 [/SUP], Ilya Potapov[SUP] 2 [/SUP], Samyukta Chillara[SUP] 1 [/SUP], Antonio Del Sol[SUP] 3 2 4 [/SUP]
Affiliations
Abstract
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.
. 2021 Feb 3;7(6):eabe5735.
doi: 10.1126/sciadv.abe5735. Print 2021 Feb.
Leveraging systems biology for predicting modulators of inflammation in patients with COVID-19
Sascha Jung[SUP] 1 [/SUP], Ilya Potapov[SUP] 2 [/SUP], Samyukta Chillara[SUP] 1 [/SUP], Antonio Del Sol[SUP] 3 2 4 [/SUP]
Affiliations
- PMID: 33536217
- DOI: 10.1126/sciadv.abe5735
Abstract
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.