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Series GSE197204 Query DataSets for GSE197204
Status Public on Feb 28, 2022
Title Transcriptomic clustering of critically-ill COVID-19 patients [Day 1-RNA-Seq]
Organism Homo sapiens
Experiment type Expression profiling by high throughput sequencing
Summary Infections caused by SARS-CoV-2 may cause a severe disease, termed COVID-19, with significant mortality. Host responses to this infection, mainly in terms of systemic inflammation, have emerged as key pathogenetic mechanisms, and their modulation is the only therapeutic strategy that has shown a mortality benefit. Herein, we used peripheral blood transcriptomes of critically-ill COVID-19 patients obtained at admission in an Intensive Care Unit, to identify two clusters that, in spite of no major clinical differences, have different gene expression profiles that reveal different underlying pathogenetic mechanisms and ultimately have different ICU outcome. A transcriptomic signature was used to identify these clusters in an external validation cohort, yielding a similar result. These results illustrate the potential of transcriptomic profiles to identify patient endotypes and point to relevant pathogenetic mechanisms in COVID-19.
 
Overall design Data from 56 patients was analyzed. Using peripheral blood transcriptomes, two different groups were identified by hyerarchical clustering.
 
Contributor(s) Albaiceta GM, Amado-Rodríguez L, López-Martínez C, López-Alonso I
Citation(s) 36104291
Submission date Feb 22, 2022
Last update date Jul 31, 2023
Contact name Guillermo M Albaiceta
E-mail(s) gma@crit-lab.org
Phone +34 985 652433
Organization name Instituto de Investigación Sanitaria del Principado de Asturias
Lab Laboratorio de Investigación Traslacional en el paciente crítico
Street address Avenida de Roma s/n
City Oviedo
ZIP/Postal code 33011
Country Spain
 
Platforms (1)
GPL24014 Ion Torrent S5 XL (Homo sapiens)
Samples (56)
GSM5910954 Patient 1 [CoV1]
GSM5910955 Patient 2 [CoV2]
GSM5910956 Patient 3 [CoV3]
This SubSeries is part of SuperSeries:
GSE197259 Transcriptomic clustering of critically-ill COVID-19 patients
Relations
BioProject PRJNA809356

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Supplementary file Size Download File type/resource
GSE197204_count_matrix.csv.gz 2.2 Mb (ftp)(http) CSV
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