Patient phenotypes and their relation to TNFα signaling and immune cell composition in critical illness and autoimmune disease
Krishna, V.; Banie, H.; Conceicao-Neto, N.; Murata, Y.; Verbrugge, I.; Trifonov, V.; Martinez, R.; Murali, V.; Lee, Y.-c.; May, R. D.; Najera, I.; Fowler, A.; Li, C. K. F.
Show abstract
RationaleTNF inhibitors have shown promise in reducing mortality in hospitalized COVID-19 patients; one hypothesis explaining the limited clinical efficacy is patient heterogeneity in the TNF pathway. MethodsWe evaluated the effect of TNF inhibitors in a mouse model of LPS-induced acute lung injury. Using machine learning we attempted predictive enrichment of TNF signaling in patients with either ARDS or sepsis. We examined biological factors that drive heterogeneity in host responses to critical infection and their relation to clinical outcomes. ResultsIn mice, LPS induced TNF-dependent neutrophilia, alveolar permeability and endothelial injury. In humans, TNF pathway activation was significantly increased in peripheral blood of patients with critical illnesses and associated with the presence of mature neutrophils across critical illnesses and several autoimmune conditions. Machine learning using a gene signature separated patients into 5 phenotypes; one was a hyper-inflammatory, interferon-associated phenotype enriched for increased TNF pathway activation and conserved across critical illnesses and autoimmune diseases. Cell subset profiles segregated severely ill patients into neutrophil-subset-dependent groups that were enriched for disease severity, demonstrating the importance of neutrophils in the immune response in critical illness. ConclusionsTNF signaling and mature neutrophils are associated with a hyper-inflammatory phenotype of patients, shared across critical illness and autoimmune disease. This phenotyping provides a personalized medicine hypothesis to test anti-TNF therapy in severe respiratory illness. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC="FIGDIR/small/564631v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1e25724org.highwire.dtl.DTLVardef@c708bcorg.highwire.dtl.DTLVardef@10e7531org.highwire.dtl.DTLVardef@3014b8_HPS_FORMAT_FIGEXP M_FIG C_FIG
Matching journals
The top 11 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- ScRNA-Seq study of neutrophils reveals vast heterogeneity and breadth of inflammatory responses in severe COVID-19 patients 96%
- Prognostic peripheral blood biomarkers at ICU admission predict COVID-19 clinical outcomes 96%
- Dysregulated immune responses in COVID-19 patients correlating with disease severity and invasive oxygen requirements 95%
Similar papers in this journal
- Blood immune profiles reveal a CXCR3/CCR5 axis of dysregulation in early sepsis 96%
- Dynamic changes in human single cell transcriptional signatures during fatal sepsis 95%
- Panton-Valentine leukocidin-induced neutrophil extracellular traps lack antimicrobial activity and are readily induced in patients with recurrent PVL+-Staphylococcus aureus infections 94%
Similar papers in this journal
- Multi-omics identify LRRC15 as a COVID-19 severity predictor and persistent pro-thrombotic signals in convalescence 95%
- Immunophenotyping and machine learning identify distinct immunotypes that predict COVID-19 clinical severity 95%
- Whole blood immunophenotyping uncovers immature neutrophil-to-VD2 T-cell ratio as an early prognostic marker for severe COVID-19 95%
Similar papers in this journal
- Early IFNβ secretion determines variable downstream IL-12p70 responses upon TLR4 activation in health and disease 94%
- Distinctive features of SARS-CoV-2-specific T cells predict recovery from severe COVID-19 94%
- Sca-1 expression depicts pro-inflammatory murine neutrophils under steady state and pathological conditions 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.