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000164649 0247_ $$2doi$$a10.1016/j.xcrm.2022.100652
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000164649 1001_ $$0P:(DE-2719)9001365$$aFrishberg, Amit$$b0$$eFirst author$$udzne
000164649 245__ $$aMature neutrophils and a NF-κB-to-IFN transition determine the unifying disease recovery dynamics in COVID-19
000164649 260__ $$aMaryland Heights, MO$$bElsevier$$c2022
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000164649 520__ $$aDisease recovery dynamics are often difficult to assess, as patients display heterogeneous recovery courses. To model recovery dynamics, exemplified by severe COVID-19, we apply a computational scheme on longitudinally sampled blood transcriptomes, generating recovery states, which we then link to cellular and molecular mechanisms, presenting a framework for studying the kinetics of recovery compared with non-recovery over time and long-term effects of the disease. Specifically, a decrease in mature neutrophils is the strongest cellular effect during recovery, with direct implications on disease outcome. Furthermore, we present strong indications for global regulatory changes in gene programs, decoupled from cell compositional changes, including an early rise in T cell activation and differentiation, resulting in immune rebalancing between interferon and NF-κB activity and restoration of cell homeostasis. Overall, we present a clinically relevant computational framework for modeling disease recovery, paving the way for future studies of the recovery dynamics in other diseases and tissues.
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000164649 650_7 $$2Other$$aCOVID-19
000164649 650_7 $$2Other$$acell deconvolution
000164649 650_7 $$2Other$$adisease modeling
000164649 650_7 $$2Other$$adisease recovery
000164649 650_7 $$2Other$$agene regulation
000164649 650_7 $$2Other$$aimmunology
000164649 650_7 $$2Other$$amedicine
000164649 650_7 $$2Other$$asystems biology
000164649 650_7 $$2Other$$aviral infection
000164649 650_7 $$2NLM Chemicals$$aNF-kappa B
000164649 650_7 $$09008-11-1$$2NLM Chemicals$$aInterferons
000164649 650_2 $$2MeSH$$aCOVID-19
000164649 650_2 $$2MeSH$$aCell Differentiation
000164649 650_2 $$2MeSH$$aHumans
000164649 650_2 $$2MeSH$$aInterferons: metabolism
000164649 650_2 $$2MeSH$$aNF-kappa B: genetics
000164649 650_2 $$2MeSH$$aNeutrophils: metabolism
000164649 650_2 $$2MeSH$$aSignal Transduction
000164649 7001_ $$aKooistra, Emma$$b1
000164649 7001_ $$00000-0002-9873-8737$$aNuesch-Germano, Melanie$$b2
000164649 7001_ $$aPecht, Tal$$b3
000164649 7001_ $$aMilman, Neta$$b4
000164649 7001_ $$0P:(DE-2719)9000843$$aReusch, Nico$$b5$$udzne
000164649 7001_ $$0P:(DE-2719)9001511$$aWarnat-Herresthal, Stefanie$$b6$$udzne
000164649 7001_ $$aBruse, Niklas$$b7
000164649 7001_ $$0P:(DE-2719)2812735$$aHändler, Kristian$$b8$$udzne
000164649 7001_ $$0P:(DE-2719)2812165$$aTheis, Heidi$$b9$$udzne
000164649 7001_ $$0P:(DE-2719)9000840$$aKraut, Michael$$b10$$udzne
000164649 7001_ $$avan Rijssen, Esther$$b11
000164649 7001_ $$00000-0001-5135-1183$$avan Cranenbroek, Bram$$b12
000164649 7001_ $$aKoenen, Hans JPM.$$b13
000164649 7001_ $$aHeesakkers, Hidde$$b14
000164649 7001_ $$avan den Boogaard, Mark$$b15
000164649 7001_ $$aZegers, Marieke$$b16
000164649 7001_ $$aPickkers, Peter$$b17
000164649 7001_ $$0P:(DE-2719)2812750$$aBecker, Matthias Kai Holger$$b18$$udzne
000164649 7001_ $$0P:(DE-2719)2812913$$aAschenbrenner, Anna Christin$$b19$$udzne
000164649 7001_ $$0P:(DE-2719)9000845$$aUlas, Thomas$$b20$$udzne
000164649 7001_ $$00000-0002-2419-1943$$aTheis, Fabian J.$$b21
000164649 7001_ $$aShen-Orr, Shai S.$$b22
000164649 7001_ $$0P:(DE-2719)2811660$$aSchultze, Joachim$$b23$$udzne
000164649 7001_ $$aKox, Matthijs$$b24
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