| Literature DB >> 34698500 |
Raphael Carapito1,2,3, Richard Li4, Julie Helms1,3,5, Christine Carapito3,6, Sharvari Gujja4, Véronique Rolli1,2,3, Raony Guimaraes4, Jose Malagon-Lopez4, Perrine Spinnhirny1,3, Alexandre Lederle1,3, Razieh Mohseninia7, Aurélie Hirschler3,6, Leslie Muller3,6, Paul Bastard8,9,10, Adrian Gervais9,10, Qian Zhang8,9,10, François Danion1,3,11, Yvon Ruch3,11, Maleka Schenck3,12, Olivier Collange3,13, Thiên-Nga Chamaraux-Tran3,14, Anne Molitor1,3, Angélique Pichot1,3, Alice Bernard1,3, Ouria Tahar2,3, Sabrina Bibi-Triki1,3, Haiguo Wu4, Nicodème Paul1,3, Sylvain Mayeur1,3, Annabel Larnicol1,3, Géraldine Laumond1,3, Julia Frappier1,3, Sylvie Schmidt1,3, Antoine Hanauer1,3, Cécile Macquin1,3, Tristan Stemmelen1,2,3, Michael Simons15, Xavier Mariette16,17, Olivier Hermine10,18, Samira Fafi-Kremer1,3,19, Bernard Goichot3,20, Bernard Drenou21, Khaldoun Kuteifan22, Julien Pottecher3,14, Paul-Michel Mertes3,13, Shweta Kailasan23, M Javad Aman23, Elisa Pin24, Peter Nilsson24, Anne Thomas25, Alain Viari25, Damien Sanlaville25, Francis Schneider3,12, Jean Sibilia1,3,26, Pierre-Louis Tharaux27, Jean-Laurent Casanova8,9,10,28, Yves Hansmann3,11, Daniel Lidar7,29, Mirjana Radosavljevic1,2,3, Jeffrey R Gulcher4, Ferhat Meziani3,5, Christiane Moog1,3, Thomas W Chittenden4,30, Seiamak Bahram1,2,3.
Abstract
The drivers of critical coronavirus disease 2019 (COVID-19) remain unknown. Given major confounding factors such as age and comorbidities, true mediators of this condition have remained elusive. We used a multi-omics analysis combined with artificial intelligence in a young patient cohort where major comorbidities were excluded at the onset. The cohort included 47 “critical” (in the intensive care unit under mechanical ventilation) and 25 “non-critical” (in a non-critical care ward) patients with COVID-19 and 22 healthy individuals. The analyses included whole-genome sequencing, whole-blood RNA sequencing, plasma and blood mononuclear cell proteomics, cytokine profiling, and high-throughput immunophenotyping. An ensemble of machine learning, deep learning, quantum annealing, and structural causal modeling were used. Patients with critical COVID-19 were characterized by exacerbated inflammation, perturbed lymphoid and myeloid compartments, increased coagulation, and viral cell biology. Among differentially expressed genes, we observed up-regulation of the metalloprotease ADAM9. This gene signature was validated in a second independent cohort of 81 critical and 73 recovered patients with COVID-19 and was further confirmed at the transcriptional and protein level and by proteolytic activity. Ex vivo ADAM9 inhibition decreased severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uptake and replication in human lung epithelial cells. In conclusion, within a young, otherwise healthy, cohort of individuals with COVID-19, we provide the landscape of biological perturbations in vivo where a unique gene signature differentiated critical from non-critical patients. We further identified ADAM9 as a driver of disease severity and a candidate therapeutic target.Entities:
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Year: 2022 PMID： 34698500 DOI： 10.1126/scitranslmed.abj7521
Source DB: PubMed Journal: Sci Transl Med ISSN： 1946-6234 Impact factor: 17.956