SARS-CoV-2 RNAemia and proteomic trajectories inform prognostication in COVID-19 patients admitted to intensive care.
Adult
Animals
Antibodies, Neutralizing
/ immunology
Antigens, Neoplasm
/ metabolism
Biomarkers, Tumor
/ metabolism
C-Reactive Protein
/ metabolism
COVID-19
/ metabolism
Critical Care
/ statistics & numerical data
Female
HEK293 Cells
Humans
Kaplan-Meier Estimate
Male
Middle Aged
Proteomics
/ methods
RNA, Viral
/ blood
SARS-CoV-2
/ genetics
Serum Amyloid P-Component
/ metabolism
Spike Glycoprotein, Coronavirus
/ immunology
Viral Load
/ immunology
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
07 06 2021
07 06 2021
Historique:
received:
05
11
2020
accepted:
28
04
2021
entrez:
8
6
2021
pubmed:
9
6
2021
medline:
22
6
2021
Statut:
epublish
Résumé
Prognostic characteristics inform risk stratification in intensive care unit (ICU) patients with coronavirus disease 2019 (COVID-19). We obtained blood samples (n = 474) from hospitalized COVID-19 patients (n = 123), non-COVID-19 ICU sepsis patients (n = 25) and healthy controls (n = 30). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was detected in plasma or serum (RNAemia) of COVID-19 ICU patients when neutralizing antibody response was low. RNAemia is associated with higher 28-day ICU mortality (hazard ratio [HR], 1.84 [95% CI, 1.22-2.77] adjusted for age and sex). RNAemia is comparable in performance to the best protein predictors. Mannose binding lectin 2 and pentraxin-3 (PTX3), two activators of the complement pathway of the innate immune system, are positively associated with mortality. Machine learning identified 'Age, RNAemia' and 'Age, PTX3' as the best binary signatures associated with 28-day ICU mortality. In longitudinal comparisons, COVID-19 ICU patients have a distinct proteomic trajectory associated with mortality, with recovery of many liver-derived proteins indicating survival. Finally, proteins of the complement system and galectin-3-binding protein (LGALS3BP) are identified as interaction partners of SARS-CoV-2 spike glycoprotein. LGALS3BP overexpression inhibits spike-pseudoparticle uptake and spike-induced cell-cell fusion in vitro.
Identifiants
pubmed: 34099652
doi: 10.1038/s41467-021-23494-1
pii: 10.1038/s41467-021-23494-1
pmc: PMC8184784
doi:
Substances chimiques
Antibodies, Neutralizing
0
Antigens, Neoplasm
0
Biomarkers, Tumor
0
LGALS3BP protein, human
0
RNA, Viral
0
Serum Amyloid P-Component
0
Spike Glycoprotein, Coronavirus
0
spike protein, SARS-CoV-2
0
PTX3 protein
148591-49-5
C-Reactive Protein
9007-41-4
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
3406Subventions
Organisme : Department of Health
ID : CS-2016-16-011
Pays : United Kingdom
Organisme : British Heart Foundation
ID : RM/17/3/33381
Pays : United Kingdom
Organisme : British Heart Foundation
ID : RG/16/14/32397
Pays : United Kingdom
Organisme : British Heart Foundation
ID : CH/16/3/32406
Pays : United Kingdom
Organisme : British Heart Foundation
ID : FS/18/60/34181
Pays : United Kingdom
Organisme : British Heart Foundation
ID : RE/18/2/34213
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/V040162/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC/PC/15068
Pays : United Kingdom
Organisme : Wellcome Trust
ID : FC001093
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/R017751/1
Pays : United Kingdom
Organisme : British Heart Foundation
ID : FS/19/58/34895
Pays : United Kingdom
Organisme : British Heart Foundation
ID : RG/19/11/34633
Pays : United Kingdom
Organisme : British Heart Foundation
ID : PG/17/48/32956
Pays : United Kingdom
Organisme : British Heart Foundation
ID : FS/17/65/33481
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 106292/Z/14/Z
Pays : United Kingdom
Organisme : British Heart Foundation
ID : SP/17/10/33219
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Arthritis Research UK
ID : FC001093
Pays : United Kingdom
Organisme : Medical Research Council
ID : FC001093
Pays : United Kingdom
Organisme : Cancer Research UK
Pays : United Kingdom
Organisme : Cancer Research UK
ID : FC001093
Pays : United Kingdom
Organisme : British Heart Foundation
ID : CH/1999001/11735
Pays : United Kingdom
Références
Knaus, W. A., Draper, E. A., Wagner, D. P. & Zimmerman, J. E. APACHE II: a severity of disease classification system. Crit. Care Med. 13, 818–829 (1985).
pubmed: 3928249
doi: 10.1097/00003246-198510000-00009
Vincent, J. L. et al. The S. O. F. A. (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine. Intensive Care Med. 22, 707–710 (1996).
pubmed: 8844239
doi: 10.1007/BF01709751
Sinha, P. et al. Prevalence of phenotypes of acute respiratory distress syndrome in critically ill patients with COVID-19: a prospective observational study. Lancet Respir. Med. 8, 1209–1218 (2020).
Zou, X. et al. Acute physiology and chronic health evaluation II score as a predictor of hospital mortality in patients of coronavirus disease 2019. Crit. Care Med. 48, e657–e665 (2020).
pubmed: 32697506
pmcid: 7217128
doi: 10.1097/CCM.0000000000004411
Intensive Care National Audit And Research Centre. ICNARC Report on COVID-19 in Critical Care 31 July 2020. (2020).
Gupta, R. K. et al. Systematic evaluation and external validation of 22 prognostic models among hospitalised adults with COVID-19: an observational cohort study. Eur. Respir. J. https://doi.org/10.1183/13993003.03498-2020 (2020).
Andersson, M. I. et al. SARS-CoV-2 RNA detected in blood products from patients with COVID-19 is not associated with infectious virus. Wellcome Open Res 5, 181 (2020).
pubmed: 33283055
pmcid: 7689603
doi: 10.12688/wellcomeopenres.16002.2
Xu, D. et al. Relationship between serum SARS-CoV-2 nucleic acid(RNAemia) and organ damage in COVID-19 patients: a cohort study. Clin. Infect. Dis. https://doi.org/10.1093/cid/ciaa1085 (2020).
Fajnzylber, J. et al. SARS-CoV-2 viral load is associated with increased disease severity and mortality. Nat. Commun. 11, 5493 (2020).
pubmed: 33127906
pmcid: 7603483
doi: 10.1038/s41467-020-19057-5
Prebensen, C. et al. Severe acute respiratory syndrome coronavirus 2 RNA in plasma is associated with intensive care unit admission and mortality in patients hospitalized with coronavirus disease 2019. Clin. Infect. Dis. https://doi.org/10.1093/cid/ciaa1338 (2020).
Laing, A. G. et al. A dynamic COVID-19 immune signature includes associations with poor prognosis. Nat. Med. https://doi.org/10.1038/s41591-020-1038-6 (2020).
Carter, M. J. et al. Peripheral immunophenotypes in children with multisystem inflammatory syndrome associated with SARS-CoV-2 infection. Nat. Med. https://doi.org/10.1038/s41591-020-1054-6 (2020).
Seow, J. et al. Longitudinal observation and decline of neutralizing antibody responses in the three months following SARS-CoV-2 infection in humans. Nat. Microbiol. https://doi.org/10.1038/s41564-020-00813-8 (2020).
Chen, X. et al. Detectablevoronavirus 2 viral load (RNAemia) is closely correlated with drastically elevated interleukin 6 level in critically Ill patients with coronavirus disease 2019. Clin. Infect. Dis. https://doi.org/10.1093/cid/ciaa449 (2020).
Bermejo-Martin, J. F. et al. Viral RNA load in plasma is associated with critical illness and a dysregulated host response in COVID-19. Crit. Care 24, 691 (2020).
pubmed: 33317616
pmcid: 7734467
doi: 10.1186/s13054-020-03398-0
Veras, F. P. et al. SARS-CoV-2–triggered neutrophil extracellular traps mediate COVID-19 pathology. J. Exp. Med. 217, e20201129 (2020).
Zaid, Y. et al. Platelets can associate with SARS-Cov-2 RNA and are hyperactivated in COVID-19. Circ. Res. https://doi.org/10.1161/CIRCRESAHA.120.317703 (2020).
Zhang, S. et al. SARS-CoV-2 binds platelet ACE2 to enhance thrombosis in COVID-19. J. Hematol. Oncol. 13, 120 (2020).
pubmed: 32887634
pmcid: 7471641
doi: 10.1186/s13045-020-00954-7
Shen, B. et al. Proteomic and metabolomic characterization of COVID-19 patient sera. Cell 182, 59–72.e15 (2020).
pubmed: 32492406
pmcid: 7254001
doi: 10.1016/j.cell.2020.05.032
Messner, C. B. et al. Ultra-high-throughput clinical proteomics reveals classifiers of COVID-19 infection. Cell Syst. 11, 11–24.e4 (2020).
pubmed: 32619549
pmcid: 7264033
doi: 10.1016/j.cels.2020.05.012
Overmyer, K. A. et al. Large-scale multi-omic analysis of COVID-19 severity. Cell Syst. https://doi.org/10.1016/J.CELS.2020.10.003 (2020).
Di, B. et al. Identification and validation of predictive factors for progression to severe COVID-19 pneumonia by proteomics. Signal Transduct. Target. Ther. 5, 217 (2020).
pubmed: 33011738
pmcid: 7532335
doi: 10.1038/s41392-020-00333-1
Singer, M. et al. The third international consensus definitions for sepsis and septic shock (Sepsis-3). J. Am. Med. Assoc. 315, 801 (2016).
doi: 10.1001/jama.2016.0287
Shankar-Hari, M. et al. Developing a new definition and assessing new clinical criteria for septic shock: for the Third International Consensus definitions for sepsis and septic shock (Sepsis-3). J. Am. Med. Assoc. 315, 775–787 (2016).
doi: 10.1001/jama.2016.0289
Wilson, J. K. & Shankar-Hari, M. Immunological subpopulations within critically Ill COVID-19 patients. Chest https://doi.org/10.1016/j.chest.2021.01.023 (2021).
Gupta, A. et al. Extrapulmonary manifestations of COVID-19. Nat. Med. 26, 1017–1032 (2020).
doi: 10.1038/s41591-020-0968-3
pubmed: 32651579
Shankar-Hari, M. et al. Early PREdiction of sepsis using leukocyte surface biomarkers: the ExPRES-sepsis cohort study. Intensive Care Med. 44, 1836–1848 (2018).
pubmed: 30291379
doi: 10.1007/s00134-018-5389-0
Jones, T. K. et al. Plasma sRAGE acts as a genetically regulated causal intermediate in sepsis-associated acute respiratory distress syndrome. Am. J. Respir. Crit. Care Med. 201, 47–56 (2020).
pubmed: 31487195
pmcid: 6938154
doi: 10.1164/rccm.201810-2033OC
Jabaudon, M. et al. Plasma sRAGE is independently associated with increased mortality in ARDS: a meta-analysis of individual patient data. Intensive Care Med. 44, 1388–1399 (2018).
pubmed: 30051136
pmcid: 6132684
doi: 10.1007/s00134-018-5327-1
Jabaudon, M. et al. Soluble form of the receptor for advanced glycation end products is a marker of acute lung injury but not of severe sepsis in critically ill patients. Crit. Care Med. 39, 480–488 (2011).
pubmed: 21220996
doi: 10.1097/CCM.0b013e318206b3ca
Cuello, F. et al. Redox state of pentraxin 3 as a novel biomarker for resolution of inflammation and survival in sepsis. Mol. Cell. Proteom. 13, 2545–2557 (2014).
doi: 10.1074/mcp.M114.039446
Mauri, T. et al. Persisting high levels of plasma pentraxin 3 over the first days after severe sepsis and septic shock onset are associated with mortality. Intensive Care Med. 36, 621–629 (2010).
pubmed: 20119647
doi: 10.1007/s00134-010-1752-5
Muller, B. et al. Circulating levels of the long pentraxin PTX3 correlate with severity of infection in critically ill patients. Crit. Care Med. 29, 1404–1407 (2001).
pubmed: 11445697
doi: 10.1097/00003246-200107000-00017
Porte, R. et al. The long pentraxin PTX3 as a humoral innate immunity functional player and biomarker of infections and sepsis. Front. Immunol. 10, 794 (2019).
pubmed: 31031772
pmcid: 6473065
doi: 10.3389/fimmu.2019.00794
Williamson, E. J. et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature https://doi.org/10.1038/s41586-020-2521-4 (2020).
von Rhein, C. et al. Comparison of potency assays to assess SARS-CoV-2 neutralizing antibody capacity in COVID-19 convalescent plasma. J. Virol. Methods 114031 (2020). https://doi.org/10.1016/J.JVIROMET.2020.114031
Dupuis, N., Muller, S., Treiber, T. & Escher, C. Evaluation of PQ500, a 500-plasma protein blood panel in NSCLC subjects using high-throughput MRM mass spectrometry. J. Clin. Oncol. 37, 110–110 (2019).
doi: 10.1200/JCO.2019.37.8_suppl.110
Filbin, M. R. et al. Longitudinal proteomic analysis of plasma from patients with severe COVID-19 reveal patient survival-associated signatures, tissue-specific cell death, and cell-cell interactions. Cell Reports Med. 100287 (2021).
Ma, Y. J. et al. Heterocomplexes of mannose-binding lectin and the pentraxins PTX3 or serum amyloid P component trigger cross-activation of the complement system. J. Biol. Chem. 286, 3405–3417 (2011).
pubmed: 21106539
doi: 10.1074/jbc.M110.190637
Brunetta, E. et al. Macrophage expression and prognostic significance of the long pentraxin PTX3 in COVID-19. Nat. Immunol. 22, 19–24 (2021).
pubmed: 33208929
doi: 10.1038/s41590-020-00832-x
Ou, X. et al. Characterization of spike glycoprotein of SARS-CoV-2 on virus entry and its immune cross-reactivity with SARS-CoV. Nat. Commun. 11, 1620 (2020).
pubmed: 32221306
pmcid: 7100515
doi: 10.1038/s41467-020-15562-9
Xia, S. et al. Inhibition of SARS-CoV-2 (previously 2019-nCoV) infection by a highly potent pan-coronavirus fusion inhibitor targeting its spike protein that harbors a high capacity to mediate membrane fusion. Cell Res. 30, 343–355 (2020).
pubmed: 32231345
pmcid: 7104723
doi: 10.1038/s41422-020-0305-x
Buchrieser, J. et al. Syncytia formation by SARS‐CoV‐2‐infected cells. EMBO J. 39, e106267 (2020).
pubmed: 33051876
pmcid: 7646020
doi: 10.15252/embj.2020106267
Bussani, R. et al. Persistence of viral RNA, pneumocyte syncytia and thrombosis are hallmarks of advanced COVID-19 pathology. EBioMedicine 61, 103104 (2020).
pubmed: 33158808
pmcid: 7677597
doi: 10.1016/j.ebiom.2020.103104
Braga, L. et al. Drugs that inhibit TMEM16 proteins block SARS-CoV-2 spike-induced syncytia. Nature https://doi.org/10.1038/s41586-021-03491-6 (2021).
Lu, M. et al. Real-time conformational dynamics of SARS-CoV-2 spikes on virus particles. Cell Host Microbe 28, 880–891.e8 (2020).
pubmed: 33242391
pmcid: 7664471
doi: 10.1016/j.chom.2020.11.001
Vincent, J.-L. Endpoints in sepsis trials: More than just 28-day mortality? Crit. Care Med. 32, S209–S213 (2004).
pubmed: 15118519
doi: 10.1097/01.CCM.0000126124.41743.86
Pujadas, E. et al. SARS-CoV-2 viral load predicts COVID-19 mortality. Lancet Respir. Med. 8, e70 (2020).
Sánchez-Cerrillo, I. et al. COVID-19 severity associates with pulmonary redistribution of CD1c+ DC and inflammatory transitional and nonclassical monocytes. J. Clin. Investig. https://doi.org/10.1172/JCI140335 (2020).
Camporota, L. et al. Outcomes in mechanically ventilated patients with hypoxaemic respiratory failure caused by COVID-19. Br. J. Anaesth. 125, e480–e483 (2020).
pubmed: 32962855
doi: 10.1016/j.bja.2020.08.047
Fish, M. et al. Cellular and molecular mechanisms of IMMunE dysfunction and Recovery from SEpsis-related critical illness in adults: an observational cohort study (IMMERSE) protocol paper. J. Intensive Care Soc. https://doi.org/10.1177/1751143720966286 (2020).
ARDS Definition Task Force, R. et al. Acute respiratory distress syndrome: the Berlin Definition. J. Am. Med. Assoc. 307, 2526–2533 (2012).
Saha, R. et al. Impact of differences in acute respiratory distress syndrome randomised controlled trial inclusion and exclusion criteria: systematic review and meta-analysis. Br. J. Anaesth. https://doi.org/10.1016/J.BJA.2021.02.027 (2021).
Joshi, A., Rienks, M., Theofilatos, K. & Mayr, M. Systems biology in cardiovascular disease: a multiomics approach. Nat. Rev. Cardiol. https://doi.org/10.1038/s41569-020-00477-1 (2020).
Holter, J. C. et al. Systemic complement activation is associated with respiratory failure in COVID-19 hospitalized patients. Proc. Natl Acad. Sci. USA 117, 25018–25025 (2020).
pubmed: 32943538
doi: 10.1073/pnas.2010540117
pmcid: 7547220
Ramlall, V. et al. Immune complement and coagulation dysfunction in adverse outcomes of SARS-CoV-2 infection. Nat. Med. https://doi.org/10.1038/s41591-020-1021-2 (2020).
Gralinski, L. E. et al. Complement activation contributes to severe acute respiratory syndrome coronavirus pathogenesis. MBio 9, e01753-18 (2018).
Galbraith, M. D. et al. Seroconversion stages COVID19 into distinct pathophysiological states. Elife 10, e65508 (2021).
Risitano, A. M. et al. Complement as a target in COVID-19? Nat. Rev. Immunol. 20, 343–344 (2020).
pubmed: 32327719
doi: 10.1038/s41577-020-0320-7
Song, W.-C. & FitzGerald, G. A. COVID-19, microangiopathy, hemostatic activation, and complement. J. Clin. Investig. 130, 3950–3953 (2020).
pubmed: 32459663
pmcid: 7410042
Yu, J. et al. Direct activation of the alternative complement pathway by SARS-CoV-2 spike proteins is blocked by factor D inhibition. Blood 136, 2080–2089 (2020).
pubmed: 32877502
doi: 10.1182/blood.2020008248
Zhou, Y. et al. A single asparagine-linked glycosylation site of the severe acute respiratory syndrome coronavirus spike glycoprotein facilitates inhibition by mannose-binding lectin through multiple mechanisms. J. Virol. 84, 8753–8764 (2010).
pubmed: 20573835
pmcid: 2919028
doi: 10.1128/JVI.00554-10
Ip, W. K. E. et al. Mannose-binding lectin in severe acute respiratory syndrome coronavirus infection. J. Infect. Dis. 191, 1697–1704 (2005).
pubmed: 15838797
doi: 10.1086/429631
Polycarpou, A. et al. Rationale for targeting complement in COVID‐19. EMBO Mol. Med. 12, e12642 (2020).
Jordan, J. E., Montalto, M. C. & Stahl, G. L. Inhibition of mannose-binding lectin reduces postischemic myocardial reperfusion injury. Circulation 104, 1413–1418 (2001).
pubmed: 11560858
doi: 10.1161/hc3601.095578
Schafranski, M. D., Stier, A., Nisihara, R. & Messias-Reason, I. J. T. Significantly increased levels of mannose-binding lectin (MBL) in rheumatic heart disease: a beneficial role for MBL deficiency. Clin. Exp. Immunol. 138, 521–525 (2004).
pubmed: 15544631
pmcid: 1809230
doi: 10.1111/j.1365-2249.2004.02645.x
Deban, L. et al. Binding of the long pentraxin PTX3 to factor H: interacting domains and function in the regulation of complement activation. J. Immunol. 181, 8433–8440 (2008).
pubmed: 19050261
doi: 10.4049/jimmunol.181.12.8433
Braunschweig, A. & Józsi, M. Human pentraxin 3 binds to the complement regulator C4b-binding protein. PLoS ONE 6, e23991 (2011).
pubmed: 21915248
pmcid: 3161823
doi: 10.1371/journal.pone.0023991
Ma, Y. J. & Garred, P. Pentraxins in complement activation and regulation. Front. Immunol. 9, 3046 (2018).
pubmed: 30619374
pmcid: 6305747
doi: 10.3389/fimmu.2018.03046
Burnap, S. A. et al. A proteomics-based assessment of inflammation signatures in endotoxemia. Mol. Cell. Proteomics https://doi.org/10.1074/mcp.RA120.002305 (2020).
Gisby, J. et al. Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death. Elife 10, e64827 (2021).
Jaillon, S. et al. The humoral pattern recognition receptor PTX3 is stored in neutrophil granules and localizes in extracellular traps. J. Exp. Med. 204, 793–804 (2007).
pubmed: 17389238
pmcid: 2118544
doi: 10.1084/jem.20061301
Caniglia, J. L., Asuthkar, S., Tsung, A. J., Guda, M. R. & Velpula, K. K. Immunopathology of galectin-3: an increasingly promising target in COVID-19. F1000Research 9, 1078 (2020).
pubmed: 33082935
pmcid: 7536583
doi: 10.12688/f1000research.25979.2
Peng, G. et al. Crystal structure of bovine coronavirus spike protein lectin domain. J. Biol. Chem. 287, 41931–41938 (2012).
pubmed: 23091051
pmcid: 3516740
doi: 10.1074/jbc.M112.418210
Li, F. Receptor recognition mechanisms of coronaviruses: a decade of structural studies. J. Virol. 89, 1954–1964 (2015).
pubmed: 25428871
doi: 10.1128/JVI.02615-14
Sethi, A., Sanam, S., Munagalasetty, S., Jayanthi, S. & Alvala, M. Understanding the role of galectin inhibitors as potential candidates for SARS-CoV-2 spike protein: in silico studies. RSC Adv. 10, 29873–29884 (2020).
doi: 10.1039/D0RA04795C
pubmed: 35518264
pmcid: 9056307
Ullrich, A. et al. The secreted tumor-associated antigen 90K is a potent immune stimulator. J. Biol. Chem. 269, 18401–18407 (1994).
pubmed: 8034587
doi: 10.1016/S0021-9258(17)32322-0
Loimaranta, V., Hepojoki, J., Laaksoaho, O. & Pulliainen, A. T. Galectin‐3‐binding protein: a multitask glycoprotein with innate immunity functions in viral and bacterial infections. J. Leukoc. Biol. 104, 777–786 (2018).
pubmed: 29882603
doi: 10.1002/JLB.3VMR0118-036R
Denard, J. et al. Human galectin 3 binding protein interacts with recombinant adeno-associated virus type 6. J. Virol. 86, 6620–6631 (2012).
pubmed: 22496229
pmcid: 3393578
doi: 10.1128/JVI.00297-12
Wang, Q., Zhang, X., Han, Y., Wang, X. & Gao, G. M2BP inhibits HIV-1 virion production in a vimentin filaments-dependent manner. Sci. Rep. 6, 32736 (2016).
pubmed: 27604950
pmcid: 5015019
doi: 10.1038/srep32736
Chua, C. C., Rahimi, N., Forsten-Williams, K. & Nugent, M. A. Heparan sulfate proteoglycans function as receptors for fibroblast growth factor-2 activation of extracellular signal-regulated kinases 1 and 2. Circ. Res. 94, 316–323 (2004).
pubmed: 14684627
doi: 10.1161/01.RES.0000112965.70691.AC
Chang, H. C., Samaniego, F., Nair, B. C., Buonaguro, L. & Ensoli, B. HIV-1 Tat protein exits from cells via a leaderless secretory pathway and binds to extracellular matrix-associated heparan sulfate proteoglycans through its basic region. AIDS 11, 1421–1431 (1997).
pubmed: 9342064
doi: 10.1097/00002030-199712000-00006
Filbin, M. R. et al. Longitudinal proteomic analysis of plasma from patients with severe COVID-19 reveal patient survival-associated signatures, tissue-specific cell death, and cell-cell interactions. Cell Reports Med. 100287, https://doi.org/10.1016/j.xcrm.2021.100287 (2021).
Shankar-Hari, M. & Rubenfeld, G. D. Population enrichment for critical care trials: phenotypes and differential outcomes. Curr. Opin. Crit. Care 25, 489–497 (2019).
pubmed: 31335383
doi: 10.1097/MCC.0000000000000641
Rochwerg, B. et al. A living WHO guideline on drugs for covid-19. Br. Med. J. 370, m3379 (2020).
Liu, C. et al. Time-resolved systems immunology reveals a late juncture linked to fatal COVID-19. Cell 184, 1836–1857.e22 (2021).
pubmed: 33713619
pmcid: 7874909
doi: 10.1016/j.cell.2021.02.018
Ding, M. et al. An optimized sensitive method for quantitation of DNA/RNA viruses in heparinized and cyropreserved plasma. J. Virol. Methods 176, 1–8 (2011).
pubmed: 21645549
pmcid: 3143304
doi: 10.1016/j.jviromet.2011.05.012
Kaudewitz, D. et al. Impact of intravenous heparin on quantification of circulating microRNAs in patients with coronary artery disease. Thromb. Haemost. 110, 609–615 (2013).
pubmed: 23803974
doi: 10.1160/TH13-05-0368
Schulte, C. et al. Comparative analysis of circulating noncoding RNAs versus protein biomarkers in the detection of myocardial injury. Circ. Res. 125, 328–340 (2019).
pubmed: 31159652
pmcid: 6641471
doi: 10.1161/CIRCRESAHA.119.314937
Vogels, C. B. F. et al. Analytical sensitivity and efficiency comparisons of SARS-CoV-2 RT–qPCR primer–probe sets. Nat. Microbiol. https://doi.org/10.1038/s41564-020-0761-6 (2020).
Troyanskaya, O. et al. Missing value estimation methods for DNA microarrays. Bioinformatics 17, 520–525 (2001).
pubmed: 11395428
doi: 10.1093/bioinformatics/17.6.520
Ali, H. et al. Cellular TRIM33 restrains HIV-1 infection by targeting viral integrase for proteasomal degradation. Nat. Commun. 10, 926 (2019).
pubmed: 30804369
pmcid: 6389893
doi: 10.1038/s41467-019-08810-0
Saeys, Y., Inza, I. & Larranaga, P. A review of feature selection techniques in bioinformatics. Bioinformatics 23, 2507–2517 (2007).
doi: 10.1093/bioinformatics/btm344
pubmed: 17720704
Cortes, C. & Vapnik, V. Support-vector networks. Mach. Learn. 20, 273–297 (1995).
doi: 10.1007/BF00994018
Chawla, N. V., Bowyer, K. W., Hall, L. O. & Kegelmeyer, W. P. SMOTE: synthetic minority over-sampling technique. J. Artif. Intell. Res. 16, 321–357 (2002).
doi: 10.1613/jair.953
Pedregosa, F. et al. Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825–2830 (2011).
Ojala, M. & Garrica, G. C. Permutation tests for studying classifier performance. J. Mach. Learn. Res. 11, 1833–1863 (2010).