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10.1093/infdis/jiab568 http://scihub22266oqcxt.onion/10.1093/infdis/jiab568 34850892!8767880!34850892     free     free     free Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Infect+Dis 2023 ; 227 (3): 322-331 Nephropedia Template TP {{tp|p=34850892|t=2023. Gene Expression Risk Scores for COVID-19 Illness Severity |pdf=|usr=}}{{34850892}} gab.com Text Gene Expression Risk Scores for COVID-19 Illness Severity JO: J Infect Dis http://www.kidney.de/pget.php?&tw=1&pmid=34850892 #FOAvip BACKGROUND: The correlates of coronavirus disease 2019 (COVID-19) illness severity following infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are incompletely understood. METHODS: We assessed peripheral blood gene expression in 53 adults with confirmed SARS-CoV-2 infection clinically adjudicated as having mild, moderate, or severe disease. Supervised principal components analysis was used to build a weighted gene expression risk score (WGERS) to discriminate between severe and nonsevere COVID-19. RESULTS: Gene expression patterns in participants with mild and moderate illness were similar, but significantly different from severe illness. When comparing severe versus nonsevere illness, we identified >4000 genes differentially expressed (false discovery rate < 0.05). Biological pathways increased in severe COVID-19 were associated with platelet activation and coagulation, and those significantly decreased with T-cell signaling and differentiation. A WGERS based on 18 genes distinguished severe illness in our training cohort (cross-validated receiver operating characteristic-area under the curve [ROC-AUC] = 0.98), and need for intensive care in an independent cohort (ROC-AUC = 0.85). Dichotomizing the WGERS yielded 100% sensitivity and 85% specificity for classifying severe illness in our training cohort, and 84% sensitivity and 74% specificity for defining the need for intensive care in the validation cohort. CONCLUSIONS: These data suggest that gene expression classifiers may provide clinical utility as predictors of COVID-19 illness severity. Twit Text FOAVip Gene Expression Risk Scores for COVID-19 Illness Severity ????J Infect Dis http://www.kidney.de/pget.php?&tw=1&pmid=34850892 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34850892 #FOAvip English Wikipedia <ref>{{Cite pmid|34850892}}</ref> Gene Expression Risk Scores for COVID-19 Illness Severity #MMPMID34850892 Peterson DR; Baran AM; Bhattacharya S; Branche AR; Croft DP; Corbett AM; Walsh EE; Falsey AR; Mariani TJ J Infect Dis 2023[Feb]; 227 (3): 322-331 PMID34850892show ga BACKGROUND: The correlates of coronavirus disease 2019 (COVID-19) illness severity following infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are incompletely understood. METHODS: We assessed peripheral blood gene expression in 53 adults with confirmed SARS-CoV-2 infection clinically adjudicated as having mild, moderate, or severe disease. Supervised principal components analysis was used to build a weighted gene expression risk score (WGERS) to discriminate between severe and nonsevere COVID-19. RESULTS: Gene expression patterns in participants with mild and moderate illness were similar, but significantly different from severe illness. When comparing severe versus nonsevere illness, we identified >4000 genes differentially expressed (false discovery rate < 0.05). Biological pathways increased in severe COVID-19 were associated with platelet activation and coagulation, and those significantly decreased with T-cell signaling and differentiation. A WGERS based on 18 genes distinguished severe illness in our training cohort (cross-validated receiver operating characteristic-area under the curve [ROC-AUC] = 0.98), and need for intensive care in an independent cohort (ROC-AUC = 0.85). Dichotomizing the WGERS yielded 100% sensitivity and 85% specificity for classifying severe illness in our training cohort, and 84% sensitivity and 74% specificity for defining the need for intensive care in the validation cohort. CONCLUSIONS: These data suggest that gene expression classifiers may provide clinical utility as predictors of COVID-19 illness severity. |*COVID-19/genetics[MESH] |Adult[MESH] |Gene Expression[MESH] |Humans[MESH] |Patient Acuity[MESH] |Retrospective Studies[MESH] |Risk Factors[MESH] |SARS-CoV-2/genetics[MESH]Gene Expression Risk Scores for COVID-19 Illness Severity (epmc).pdf DeepDyve Pubget Overpricing