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Multi-omics personalized network analyses highlight progressive disruption of central metabolism associated with COVID-19 severity
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Rekke forfattare: 172022 (engelsk)Inngår i: Cell systems, ISSN 2405-4712, Vol. 13, nr 8, s. 665-681Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

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, immunophenotyping by flow cytometry, plasma metabolomics, and single-cell-type metabolo-mics of monocytes to identify the potential determinants of COVID-19 severity at personalized and group levels. Digital cell quantification and immunophenotyping of the mononuclear phagocytes indicated a sub-stantial role in coordinating the immune cells that mediate COVID-19 severity. Stratum-specific and person-alized genome-scale metabolic modeling indicated monocarboxylate transporter family genes (e.g., SLC16A6), nucleoside transporter genes (e.g., SLC29A1), and metabolites such as a-ketoglutarate, succi-nate, 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.

sted, utgiver, år, opplag, sider
2022. Vol. 13, nr 8, s. 665-681
Emneord [en]
COVID-19, similarity network fusion, personalized genome-scale metabolic model
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Identifikatorer
URN: urn:nbn:se:su:diva-209347DOI: 10.1016/j.cels.2022.06.006ISI: 000844051100002PubMedID: 35933992Scopus ID: 2-s2.0-85135506746OAI: oai:DiVA.org:su-209347DiVA, id: diva2:1696272
Tilgjengelig fra: 2022-09-16 Laget: 2022-09-16 Sist oppdatert: 2022-09-16bibliografisk kontrollert

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