key: cord-0956830-fhtd0xvt
authors: Lévy, Yves; Wiedemann, Aurélie; Hejblum, Boris P.; Durand, Mélany; Lefebvre, Cécile; Surénaud, Mathieu; Lacabaratz, Christine; Perreau, Matthieu; Foucat, Emile; Déchenaud, Marie; Tisserand, Pascaline; Blengio, Fabiola; Hivert, Benjamin; Gauthier, Marine; Cervantes-Gonzalez, Minerva; Bachelet, Delphine; Laouénan, Cédric; Bouadma, Lila; Timsit, Jean-François; Yazdanpanah, Yazdan; Pantaleo, Giuseppe; Hocini, Hakim; Thiébaut, Rodolphe
title: CD177, a specific marker of neutrophil activation, is associated with COVID-19 severity and death
date: 2021-06-10
journal: iScience
DOI: 10.1016/j.isci.2021.102711
sha: 194e102c4b84c73ea93674276db1b4783c17faec
doc_id: 956830
cord_uid: fhtd0xvt

The identification of COVID-19 patients with high-risk of severe disease is a challenge in routine care. We performed cell phenotypic, serum and RNA-seq gene expression analyses in severe hospitalized patients (n = 61). Relative to healthy donors, results showed abnormalities of 27 cell populations and an elevation of 42 cytokines, neutrophil chemo-attractants, and inflammatory components in patients. Supervised and unsupervised analyses revealed a high abundance of CD177, a specific neutrophil activation marker, contributing to the clustering of severe patients. Gene abundance correlated with high serum levels of CD177 in severe patients. Higher levels were confirmed in a second cohort and in ICU than non-ICU patients (P< 0.001). Longitudinal measurements discriminated between patients with the worst prognosis, leading to death, and those who recovered (P = 0.01). These results highlight neutrophil activation as a hallmark of severe disease and CD177 assessment as a reliable prognostic marker for routine care.

The Coronavirus Disease 2019 (COVID-19) pandemic is caused by a newly described highly 57 pathogenic beta coronavirus, Severe Acute Respiratory Syndrome coronavirus 2 (SARS-58

CoV-2) (Coronaviridae Study Group of the International Committee on Taxonomy of, 2020; We used a systems immunology approach to identify host factors that were significantly 93 associated with the time to illness onset, severity of the disease (ICU or transfer to ICU), and 94 mortality of COVID-19 patients enrolled in the multicentric French COVID cohort 95 (Yazdanpanah, 2020) . In addition to the depletion of T cells and mobilization of B cells, 96 neutrophil activation, and severe inflammation, we show upregulation of CD177 gene 97 expression and protein levels in the blood of COVID-19 patients in both the COVID-19 cohort 98 and a "confirmatory" cohort, i.e., Swiss cohort, relative to healthy subjects. CD177, a 99 neutrophil activation marker, characterized critically ill patients and marked disease 100 progression and death. Our finding highlights the major role of neutrophil activation through 101 CD177 over-expression in the critical clinical transition point in the trajectory of COVID-19 102 patients. 103 Table 1 . All patients from this cohort were stratified as severe according to criteria of the 109 French COVID cohort (clinicaltrials.gov NCT04262921) (Yazdanpanah, 2020) , with 53 (87%) 110 hospitalized in an ICU (either initially or after clinical worsening or death) and eight not. The [0.4-0.8]) (P < 0.001). Total NK-cell frequencies, more precisely those of the CD56 bright and 129 CD56 dim CD57 -NK-cell subpopulations, were lower than in HDs (P = 0.017, P < 0.001, and P 130 to HD) ( Figure 1C ). In addition, COVID 19-patients showed significantly smaller classical 134 (CD14 + CD16 -), intermediate (CD14 + CD16 + ), and non-classical (CD14 -CD16 + ) monocyte 135 subpopulations than HDs (P = 0.013, P = 0.017, P < 0.001, respectively) ( Figure 1D ). 136

Interestingly, COVID-19 patients tended to exhibit a higher frequency of γδ T cells than HDs 137 (median 10.4% [7.5-16.1] vs 7.3% [6-10] in HDs; P = 0.068) ( Figure 1E) , with a significant 138

proportion of γδ T cells showing higher expression of the activation marker CD16 (P = 0.01) 139

and lower expression of the inhibitory receptor NKG2A (P < 0.001) than HDs ( Figure 1E ). 140

Finally, we observed markedly smaller frequencies of dendritic cells (DCs) for all populations 141 studied (pre-DC, plasmacytoid DC (pDC), and conventional DC (cDC1 and cDC2) in COVID-142 19 patients than in HDs (P < 0.001, for all comparisons) ( Figure 1F ). Neutrophils count were 143 available in 44 patients and the concentration was more elevated in COVID19 patients 144 belonging to group 2 and group 3 compared to group 1 (8.109/L vs 3.109/L, p<0.03). It was 145 also more elevated in patients hospitalized in ICU (8.109/L vs 2.109/L, p<0.009). 146

We then evaluated the levels of 71 serum cytokines, chemokines, and inflammatory factors 147 in 33 COVID-19 patients and 5 HDs. Forty-four analytes differed significantly (Wilcoxon test 148 adjusted for multiple comparisons) between the COVID-19 patients and HDs (shown in the 149 heatmap in Figure 2 and detailed in Figure S3 ). The levels of 42 factors were higher, among 150 them, pro-inflammatory factors (IL-1a, IL-6, IL-18, tumor necrosis factor-α and β (TNF-α, 151 TNF-β), IL-1ra, ST2/IL-1R4, the acute phase protein lipopolysaccharide binding protein LBP, 152 IFN-a2); Th1 pathway factors (IL-12 (p70), IFN-, IP-10, IL-2Ra); Th2/regulatory cytokines 153 (IL-4, IL-10, IL-13); IL-17, which also promotes granulocyte-colony stimulating factor (G-154 CSF)-mediated granulopoiesis and recruits neutrophils to inflammatory sites; T-cell 155 proliferation and activation factors (IL-7, IL-15); growth factors (SCF, SCGF-b, HGF, b-FGF, 156 b-NGF); and a significant number of cytokines and chemokines involved in macrophage and usually not detectable in the serum, which enhances the recruitment and migration of 161 inflammatory cells and contributes to tissue damage (Cai et al., 2020) . In parallel, Granzyme 162 B and IL-21 levels were significantly lower in COVID-19 patients than HDs (P = 0.007 and P 163 = 0.004, respectively) ( Figure S3 ). 164

Whole blood gene expression profiles show a specific signature for COVID-19 patients 165

The comparison of gene abundance in whole blood between COVID-19 patients (n = 44) and 166

HDs (n = 10) showed 4,079 differentially expressed genes (DEG) with an absolute fold 167 change ≥ 1.5, including 1,904 that were upregulated and 2,175 that were downregulated 168 inducible T-cell co-stimulator/ICOSL axis (z-score = -4.5) ( Figure S4 ). In contrast to the 189 results for T cells, the peripheral expansion of memory B cells and plasmablasts was 190 associated with broad expansion of the B-Cell Receptor (BCR) ( Figure 3F and Table S2 ). 191

We also observed genes belonging to several crucial pathways and biological processes that 192

had not been previously reported to characterize COVID-19 patients to be underrepresented. 193

These included eIF2 signaling, with many downregulated genes, such as ribosomal proteins 194 (RP) and eukaryotic translation initiation factors (EIFs) ( Figure S4A ), common targets of the 195 integrated stress response (ISR), including antiviral defense (Levin and London, 1978; 196 Pakos-Zebrucka et al., 2016). In addition, we also found genes involved in signaling through 197 mTOR ( Figure S4B ), a member of the phosphatidylinositol 3-kinase-related kinase family of 198 protein kinases. Prediction analysis using Ingenuity pathways showed both lower eIF2 (z-199 score = -6.8) and mTOR (z-score = -2.2) signaling in COVID-19 patients than HDs. Detailed patient characteristics according to group are presented in Table S1 . Among a large 205 set of clinical and biological characteristics, the analysis showed the differential clustering to (Table S1 ). 216

Analysis of the genes contributing to the differences between groups confirmed and 217 extended the findings described above (Figure 3 and Figure S4 ). Several pathways were 218 highly represented in sectors of the heatmap defined according to gene abundance across 219 patient groups. For example, 97% of the genes making up the BCR and 65% of those 220 involved in neutrophil responses were represented among the genes showing a greater 221 abundance in COVID-19 groups 2 and 3 than group 1 and HDs ( Figure 4 ). Other pathways, 222 such as those for interferon (64%), TCR (100%), iCOS-iCOS-L (88%), mTOR (81%), and 223 eIF2 signaling (92%) were also highly represented. The interferon signaling genes, such as 224 IFI44L, IFIT2, and IRF8, a regulator of type I Interferon (α, β), were significantly more 225 abundant at earlier stages (in patients from group 2) and tended to be less abundant in group 226 3, at more advanced stages of the disease. Finally, the abundance of genes belonging to T-227 cell pathways (TCR, iCOS-iCOSL signaling) or mTOR and eIF2 signaling was lower in group 228 3, that is to say, those who were analyzed after a longer time from symptom onset to the 229 admission. The findings described above highlight the heterogeneity of COVID-19 patients. 230

We performed an integrative analysis using all available data to disentangle the relative 233 contribution of the various markers at the scale of every patient. We thus pooled the data for group was again clearly apparent ( Figure S4 ). An additional cell-type specific significance 260 analysis (csSAM) has been performed to check the robustness of the CD177 differential 261 expression according to the cell-type frequencies (Shen-Orr et al., 2010). We found that 262 CD177 differential expression between COVID-19 and HD patients was not fully explained by 263 population variations. Indeed, it remained significant after deconvolution in several 264 leucocytes subpopulations (notably FDR of 0.04 within T-cells and 0.03 within Monocytes). 265

Given the contribution of the neutrophil activation pathway in the clustering of COVID-19 269 patients, we sought neutrophil-activation features that could act as possible reliable markers 270 of disease evolution. We focused on CD177 because: i) it is a neutrophil-specific marker 271

representative of neutrophil activation, ii) it was the most highly differentially expressed gene 272 in patients, and iii) the protein can be measured in the serum, making its use as a marker 273 clinically applicable. Thus, we used an ELISA to quantify CD177 in the serum of 203 COVID-274 19 patients (115 patients from the French cohort and 88 patients from the Swiss COVID-19 275 cohort that we used as "a confirmatory" cohort, patient characteristics are described in Table  276 2), 21% of whom the measurements were repeated (from 2 to 10 measurements per ( Figure 6C ) and was higher for patients hospitalized in an ICU (6.0 ng/ml [3.5-9.4] vs 3.3 286 ng/ml [1.5-5.6], P < 0.001) ( Figure 6D ). The association between serum CD177 levels and 287 hospitalization in an ICU was independent of the usual risk factors, such as age, sex, chronic 288 cardiac or pulmonary diseases, or diabetes (multivariable logistic regression, adjusted odds 289 ratio 1.14 per unit increase, P < 0.001). We observed a trend towards a positive association 290 with the SOFA and SAPS2 risk scores that was not statistically significant (P = 0.17 and P = 291 0.074, respectively) ( Figure S6A and B). CD177 levels were not associated with other 292

conditions that contribute to a high risk of severe disease, such as diabetes (P = 0.632), 293 patient (P = 0.83). 295

We then examined the dynamics of the CD177 concentration in 172 COVID-19 patients, with 296 longitudinal serum samples, using all available measurements ( Figure 6E ). At the first 297 measurement, the average concentration of CD177 was not significantly different between 298 the patients who died and those who recovered (5.93 vs 5.06, P= 0.26, Wald test). When 299 looking at the change of CD177 concentration over time, it appears clearly that the 300 concentration was decreasing in those who recovered (-0.22 ng/mL/day, 95% CI -0.307; -301 0.139) whereas it was stable in those who died later on (+0.10 ng/mL/day, 95% CI -0.014; 302 +0.192). These results show that the stability of CD177 protein levels in severe COVID-19 303 patients during the course of the disease is a hallmark of a worse prognosis, leading to 304

Here, we investigated factors that influence the clinical outcomes of severe COVID-19 307 patients involved in a multicentric French cohort combining standardized whole-blood RNA-308 showing that CD177 is increased both at the level of coding RNA and at the protein level. 348

Moreover, we show also that CD177 is not only a marker of severity but also of death as 349 revealed by the longitudinal analysis which was confirmed in a second cohort. 350

Although, it is difficult to formally conclude whether CD177 is a causal factor of disease 351 progression or a consequence of the severity of the disease, our data strongly show that 352 represented in S-specific SARS-CoV-2 sequences (Brouwer et al., 2020) . We also found 388 enrichment of VH3-33, previously described in a set of clonally related anti-SARS-CoV-2 389 receptor-binding domain antibodies (Barnes et al., 2020b) . 390

Globally, these results show that the defense against SARS-CoV-2 following pathogen 391 recognition triggers a fine-tuned program that not only includes the production of antiviral 392 (Interferon signaling) and pro-inflammatory cytokines but also signals the cessation of the 393 response and a strong disturbance of adaptive immunity. 394

The same pathways (immune and stress responses through eIF2 signaling, neutrophil and 395

Interferon signaling, T-and B-cell receptor responses, and mTOR pathways) contributed to 396 the ability to discriminate between three groups of severe COVID-19 patients in an 397 unsupervised analysis. One limitation of our study was that we did not repeat the RNA-seq 398 analyses in these specific groups of patients. Nonetheless, it is noteworthy that these groups 399 

None of the authors has any conflict of interest to declare. 452 relative to HD, green symbols represent underabundant genes. See also Figure S4 and 484 

Further information and requests for resources should be directed to and will be fulfilled by 525 the lead contact, Yves Lévy (yves.levy@aphp.fr). 526

No materials were newly generated for this paper. 528

RNA sequencing data that support the findings of this study have been deposited in Gene 530

Expression Omnibus (GEO) repository with the accession codes GSE171110. Further 531 information and requests for resources and reagents should be directed to and will be fulfilled 532 by the Lead Contact: Yves Lévy (yves.levy@aphp.fr) 533

We enrolled a subgroup of COVID19 patients of the prospective French COVID cohort in this 536 immunological study which is part of the cohort main objectives. Median age of COVID19 537 patients was 60 years [50-69], 80% were male. Ethics approval was given on February 5th 538 by the French Ethics Committee CPP-Ile-de-France VI (ID RCB: 2020-A00256-33). Eligible 539 patients were those who were hospitalized with virologically confirmed COVID-19. Briefly, 540 nasopharyngeal swabs were performed on the day of inclusion for SARS-CoV-2 testing 541 according to WHO or French National Health Agency guidelines. Viral loads were quantified 542 by real-time semi-quantitative reverse transcriptase polymerase chain reactions (RT-PCR) 543 using either the Charité WHO protocol (testing the E gene and RdRp) or the Pasteur institute 544 assay (testing the E gene and two other RdRp targets, IP2 and IP4). The study was 545 conducted with the understanding and the consent of each participant or its surrogate 546 covering the sampling, storage, and use of biological samples. The time from symptom onset 547 to the admission has been retrospectively collected by the interview of patients enrolled in 548 commission (CER-VD; Swiss ethics protocol ID: 2020-00620) and all subjects provided 550 written informed consent. Blood from healthy donors was collected from the French Blood 551

Donors Organization (Etablissement Français du sang (EFS)) before the COVID-19 552 outbreak. HD characteristics are shown in Table S3 . 553

In total, 71 analytes were quantified in heat-inactivated serum samples by multiplex magnetic 556 bead assays or ELISA. Serum samples from five healthy donors were also assayed as 557 controls. The following kits were used according to the manufacturers' recommendations: Immune-cell phenotyping was performed using an LSR Fortessa 4-laser (488, 640, 561, and 576 405 nm) flow cytometer (BD Biosciences) and Diva software version 6.2. FlowJo software 577 version 9.9.6 (Tree Star Inc.) was used for data analysis. CD4+ and CD8+ T cells were 578 analyzed for CD45RA and CCR7 expression to identify the naive, memory, and effector cell 579 subsets for co-expression of activation (HLA-DR and CD38) and exhaustion/senescence 580 (CD57and PD1) markers. CD19+ B-cell subsets were analyzed for the markers CD21 and 581 CD27. ASC (plasmablasts) were identified as CD19+ cells expressing CD38 and CD27. We 582 used CD16, CD56, and CD57 to identify NK-cell subsets. γδ T cells were identified using an 583 anti-TCR γδ antibody. HLA-DR, CD33, CD45RA, CD123, CD141, and CD1c were used to 584 identify dendritic cell (DC) subsets, as previously described (See et al., 2017) . Extracellular 585 labelling was performed for all antibodies except for Ki 67 for which an intracellular labelling 586 was performed with the BD cytofix/cytoperm kit (BD Biosciences). 587

Total RNA was purified from whole blood using the Tempus™ Spin RNA Isolation Kit 589 

Sources 692 of Type I Interferons in Infectious Immunity

Driver's Seat. Frontiers in Immunology 10

Multi-omics profiling of 696 mouse gastrulation at single-cell resolution

Systems biological assessment of 699 immunity to mild versus severe COVID-19 infection in humans

Disease 702 severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients

Resident pulmonary lymphocytes expressing 705 the gamma/delta T-cell receptor

Targeting 708 potential drivers of COVID-19: Neutrophil extracellular traps

Structures of Human Antibodies Bound to SARS-CoV-2 Spike Reveal Common Epitopes and 713

Autoantibodies against type I IFNs in 716 patients with life-threatening COVID-19

Neutrophil Transmigration Mediated by the Neutrophil-Specific Antigen CD177 Is Influenced 719 by the Endothelial S536N Dimorphism of Platelet Endothelial Cell Adhesion Molecule-1. The 720

Imbalanced Host Response to SARS

CoV-2 Drives Development of COVID-19

Immune Alterations in a Patient 726 with SARS-CoV-2-Related Acute Respiratory Distress Syndrome

Increased Plasma PCSK9 Levels Are Associated with Reduced Endotoxin Clearance and 729 the Development of Acute Organ Failures during Sepsis

A systems analysis 731 identifies a feedforward inflammatory circuit leading to lethal influenza infection

Potent neutralizing 735 antibodies from COVID-19 patients define multiple targets of vulnerability

Diagnostic and prognostic potential of 738 the macrophage specific receptor CD163 in inflammatory diseases

Multiple 741 pathophysiological roles of midkine in human disease

Epidemiological and clinical characteristics of 99 cases of 2019 novel 747 coronavirus pneumonia in Wuhan, China: a descriptive study

Lung-resident gammadelta T cells and their roles in lung 749 diseases

The 751 species Severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and 752 naming it SARS-CoV-2

Tissue factor-positive 755 neutrophils bind to injured endothelial wall and initiate thrombus formation

Marked T cell activation, senescence, 759 exhaustion and skewing towards TH17 in patients with COVID-19 pneumonia

Identification of CD177 as the most 763 dysregulated parameter in a microarray study of purified neutrophils from septic shock 764 patients

Mapping identifiers for the 766 integration of genomic datasets with the R/Bioconductor package biomaRt

Differential Expression of PCSK9 Modulates Infection, Inflammation, 770 and Coagulation in a Murine Model of Sepsis

clinical implication of dynamic neutrophil to lymphocyte ratio and D-dimer in COVID-19: A 773 retrospective study in Suzhou China

Dengue virus induces PCSK9 expression to alter antiviral responses and 776 disease outcomes

dearseq: a variance 778 component score test for RNA-Seq differential analysis that effectively controls the false 779 discovery rate

Complex Immune Dysregulation in COVID-19 Patients with Severe Respiratory Failure

Impaired type I interferon activity and 786 inflammatory responses in severe COVID-19 patients

Clinical features of patients infected with 2019 novel coronavirus in

Association between maternal age and outcomes in Kawasaki disease patients. Pediatr 792 Rheumatol 17

Neutrophil extracellular 794 trap from Kawasaki disease alter the biologic responses of PBMC

Acute Respiratory Distress Syndrome 797

Regulatory effects of mTORC2 complexes in type I IFN signaling and in the 801 generation of IFN responses

Interleukin-32: a 804 cytokine and inducer of TNFalpha

Genome-wide transcriptome analysis to further understand 807 neutrophil activation and lncRNA transcript profiles in Kawasaki disease

Immunologic 810 perturbations in severe COVID-19/SARS-CoV-2 infection

A dynamic COVID-19 813 immune signature includes associations with poor prognosis

A new Simplified Acute Physiology Score (SAPS II) based on a

American multicenter study

Regulation of protein synthesis: activation by double-818 stranded RNA of a protein kinase that phosphorylates eukaryotic initiation factor 2

Longitudinal analyses reveal immunological misfiring 822 in severe COVID-19

Deep immune profiling of

COVID-19: consider cytokine storm syndromes and immunosuppression

The IL-1 family 831 cytokines and receptors in autoimmune diseases

Excessive neutrophils and neutrophil extracellular traps 834 contribute to acute lung injury of influenza pneumonitis

A Dynamic Immune Response

Shapes COVID-19 Progression

The integrated stress response

Salmon provides 841 fast and bias-aware quantification of transcript expression

The Novel Coronavirus Originating in

Challenges for Global Health Governance

Biomarkers 845 associated with COVID-19 disease progression

Corticosteroids in COVID-19 ARDS

Dysregulation of immune response in patients with COVID-19 in

Inhibition of the 857 integrated stress response by viral proteins that block p-eIF2-eIF2B association

Phagocyte-specific S100 proteins: a 860 novel group of proinflammatory molecules

Mapping the human DC lineage through the 866 integration of high-dimensional techniques

Cell type-specific gene expression 869 differences in complex tissues

Myeloid Cell Subsets Discriminate Severe from Mild COVID-19

Association Between 875 Administration of Systemic Corticosteroids and Mortality Among Critically Ill Patients With 876 COVID-19

Neutrophils-related host factors associated with severe 879 disease and fatality in patients with influenza infection

Haptoglobin is synthesized during granulocyte differentiation, 881 stored in specific granules, and released by neutrophils in response to activation

Kawasaki-like multisystem inflammatory 885 syndrome in children during the covid-19 pandemic

Use of the SOFA score to assess the incidence of 889 organ dysfunction/failure in intensive care units

Kawasaki-like disease: emerging complication during 891 the COVID-19 pandemic

A single-cell atlas of the peripheral 894 immune response in patients with severe COVID-19

Characteristics of and Important Lessons From the

COVID-19) Outbreak in China Summary of a

Cases From the Chinese Center for Disease Control and Prevention

Suppressed T cell-mediated immunity in patients with COVID-19: A clinical 901 retrospective study in Wuhan

Impact on disease mortality of clinical, biological, and virological 903 characteristics at hospital admission and overtime in COVID-19 patients

Gene Expression Signatures Diagnose 907 Influenza and Other Symptomatic Respiratory Viral Infections in Humans

Clinical 910 significance of sCD163 and its possible role in asthma (Review)

Heightened Innate Immune Responses in the Respiratory Tract of COVID