Multi-omics personalized network analyses highlight progressive disruption of central metabolism associated with COVID-19 severity
Cell Systems, 2022
Ambikan A., Yang H., Krishnan S., Svensson Akusjärvi S., Gupta S., Lourda M., Sperk M., Arif M., Zhang C., Nordqvist H., Ponnan S., Sönnerborg A., Treutiger C., O’Mahony L., Mardinoglu A., Benfeitas R., Neogi U.
| Disease area | Application area | Sample type | Products |
|---|---|---|---|
Infectious Diseases | Pathophysiology | Plasma |  Olink Target 96 |
Abstract
The clinical outcome and disease severity in coronavirus disease-2019 (COVID-19) are heterogeneous, and the progression or fatality of the disease cannot be explained by a single factor like age or comorbidities. In this study, we used system-wide network-based system biology analysis using whole blood RNA sequencing, immune-phenotyping by flow cytometry, plasma metabolomics, and single cell-type metabolomics of the monocytes to identify the potential determinants of COVID-19 severity at the personalized and group level. Digital cell quantification and immune-phenotyping of the mononuclear phagocytes indicated a substantial role in coordinating the immune cells that mediate the COVID-19 severity. Stratum-specific and personalized genome-scale metabolic modeling indicated monocarboxylate transporter family genes (e.g., SLC16A6), nucleoside transporter genes (e.g., SLC29A1), and metabolites such as α-ketoglutarate, succinate, malate, and butyrate, could play a crucial role in COVID-19 severity. Metabolic perturbations targeting the central metabolic pathway (TCA-cycle) can be an alternate treatment strategy in severe COVID-19.