Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 2 de 2
Add filters

Document Type
Year range
American Journal of Respiratory and Critical Care Medicine ; 205(1), 2022.
Article in English | EMBASE | ID: covidwho-1927857


Background: Latent class analyses in patients with acute respiratory distress syndrome (ARDS) have identified “hyper-inflammatory” and “hypo-inflammatory” phenotypes with divergent clinical outcomes and treatment responses. ARDS phenotypes are defined using plasma biomarkers and clinical variables. It is currently unknown if these phenotypes have distinct pulmonary biology and if pre-clinical models of disease replicate the biology of either phenotype. Methods: 45 subjects with ARDS (Berlin Definition) and 5 mechanically ventilated controls were selected from cohorts of mechanically ventilated patients at UCSF and ZSFG. Patients with COVID-19 were excluded from this analysis. A 3-variable classifier model (plasma IL-8, protein C, and bicarbonate;Sinha 2020) was used to assign ARDS phenotypes. Tracheal aspirate (TA) RNA was analyzed using established bulk and single-cell sequencing pipelines (Langelier 2018, Sarma 2021). Differentially expressed (DE) genes were analyzed using Ingenuity Pathway Analysis (IPA). Microbial community composition was analyzed with vegan. Fgsea was used to test for enrichment of gene sets from experimental ARDS models in genes that were differentially expressed between each phenotype and mechanically ventilated controls. Results: Bulk RNA sequencing (RNAseq) was available from 29 subjects with hypoinflammatory ARDS and 10 subjects with hyperinflammatory ARDS. 2,777 genes were differentially expressed between ARDS phenotypes. IPA identified several candidate upstream regulators of gene expression in hyperinflammatory ARDS including IL6, TNF, IL17C, and interferons (Figure 1A). 2,953 genes were differentially expressed between hyperinflammatory ARDS and 5 ventilated controls;in contrast, only 243 genes were differentially expressed between hypoinflammatory ARDS and controls, suggesting gene expression in the hypoinflammatory phenotype was more heterogeneous. Gene sets from experimental models of acute lung injury were enriched in hyperinflammatory ARDS but not in hypoinflammatory ARDS (Figure 1B). Single cell RNA sequencing (scRNAseq) was available from 6 additional subjects with ARDS, of whom 3 had hyperinflammatory ARDS. 14,843 cells passed quality control filters. Hyperinflammatory ARDS subjects had a markedly higher burden of neutrophils (Figure 1C), including a cluster of stressed neutrophils expressing heat shock protein RNA that was not present in hypoinflammatory ARDS. Expression of a Th1 signature was higher in T cells from hyperinflammatory ARDS. Differential expression analysis in macrophages identified increased expression of genes associated with mortality in a previous study of ARDS patients (Morell 2019). Conclusions: The respiratory tract biology of ARDS phenotypes is distinct. Hyperinflammatory ARDS is characterized by neutrophilic inflammation with distinct immune cell polarization. Transcriptomic profiling identifies candidate preclinical disease models that replicate gene expression observed in hyperinflammatory ARDS.