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10.1126/scitranslmed.abj7521

http://scihub22266oqcxt.onion/10.1126/scitranslmed.abj7521
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34698500!ä!34698500

suck abstract from ncbi


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pmid34698500      Sci+Transl+Med 2022 ; 14 (628): eabj7521
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  • Identification of driver genes for critical forms of COVID-19 in a deeply phenotyped young patient cohort #MMPMID34698500
  • Carapito R; Li R; Helms J; Carapito C; Gujja S; Rolli V; Guimaraes R; Malagon-Lopez J; Spinnhirny P; Lederle A; Mohseninia R; Hirschler A; Muller L; Bastard P; Gervais A; Zhang Q; Danion F; Ruch Y; Schenck M; Collange O; Chamaraux-Tran TN; Molitor A; Pichot A; Bernard A; Tahar O; Bibi-Triki S; Wu H; Paul N; Mayeur S; Larnicol A; Laumond G; Frappier J; Schmidt S; Hanauer A; Macquin C; Stemmelen T; Simons M; Mariette X; Hermine O; Fafi-Kremer S; Goichot B; Drenou B; Kuteifan K; Pottecher J; Mertes PM; Kailasan S; Aman MJ; Pin E; Nilsson P; Thomas A; Viari A; Sanlaville D; Schneider F; Sibilia J; Tharaux PL; Casanova JL; Hansmann Y; Lidar D; Radosavljevic M; Gulcher JR; Meziani F; Moog C; Chittenden TW; Bahram S
  • Sci Transl Med 2022[Jan]; 14 (628): eabj7521 PMID34698500show ga
  • 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.
  • |*COVID-19[MESH]
  • |ADAM Proteins[MESH]
  • |Artificial Intelligence[MESH]
  • |Humans[MESH]
  • |Intensive Care Units[MESH]
  • |Membrane Proteins[MESH]
  • |Respiration, Artificial[MESH]


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