key: cord-0788095-wd6jm2ms
authors: Mukhopadhyay, S.; Sinha, S.; Mohapatra, S. K.
title: Dynamic dysregulation of IL-6 and genes functional in NETosis, complement and coagulation in severe COVID-19 illness
date: 2020-10-14
journal: nan
DOI: 10.1101/2020.10.13.20211425
sha: bfe87a22bdc6f39767825d5be81ba78bb687c39b
doc_id: 788095
cord_uid: wd6jm2ms

Comprehensive and unbiased re-analysis of published blood transcriptome data from patients of COVID-19 reveals significant up-regulation of the gene set functional in NETosis, but no evidence of general cytokine storm. In severe COVID-19 illness, there is significant up-regulation of complement and coagulation pathway, and negative correlation between NETosis and respiratory function (oxygen saturation). Interestingly, there is an early spike in the level of IL-6 gene expression in severe illness compared to moderate illness. With passing days post-onset, the level of IL-6 expression in severe illness approaches that in moderate illness. The data are consistent with IL-6 acting as a driver of NETosis in the early phase of severe COVID-19 illness, that results in a vicious cycle of NETosis-complement/coagulation-respiratory dysfunction. This has important consequence for timing of rational therapy with anti-IL-6 and NETosis inhibitors in severe COVID-19 illness.

COVID-19 disease caused by SARS-CoV-2 has rapidly become a center of intense scientific investigation, with emphasis on unraveling the biology for actionable knowledge. While the majority of the infected subjects are asymptomatic or mildly ill, a small percentage are severely ill with respiratory distress [1] . However, at present, it is difficult to predict with certainty the patients at high-risk for clinical severity and poor outcome, although multiple pathophysiological processes have been proposed, such as, cytokine storm [2, 3] , coagulation and complement activation [4] , neutrophil extracellular trap -NETosis [5] . These studies have also led to predictive biomarkers, such as, neutrophil: lymphocyte ratio [6, 7] and interleukin 6 (IL-6) expression [2, 4] .

Insight into cytokine dysregulation has driven therapeutic advances, such as, anti-cytokine tocilizumab (IL-6 receptor antagonist) for severely ill patients of COVID-19 [8, 9] . Such treatment is premised on the induction of intra-pulmonary inflammation by SARS-Cov-2 infection that ultimately leads to severe local vascular dysfunction including micro-thrombosis, haemorrhage and pulmonary intravascular coagulopathy [10] . Therefore, it has been suggested to start tocilizumab early, in order to avoid mechanical ventilation [11] , although the best timing for the treatment is still being investigated [12] .

Therefore, it is important to understand the temporal and/or causal relationship of the cytokine upregulation with coagulopathy and respiratory dysfunction.

The prothrombotic state (contributing to pulmonary dysfunction in is explained in terms of Neutrophil extracellular traps (NETs) that originate from decondensed chromatin of neutrophils that can trigger immunothrombosis. Critically ill patients of COVID-19 show significantly higher plasma levels of MPO-DNA complex, a marker of NETosis. Factors triggering NETs were significantly increased in COVID-19 and pulmonary autopsies confirmed NET-containing microthrombi with neutrophil-platelet infiltration. The authors concluded that NETs triggering immunothrombosis may partly explain the prothrombotic clinical presentations in COVID-19 [5] .

In view of the pivotal role of cytokines (especially IL-6) and NETosis in biology of COVID-19 host response, we performed a deep and focussed investigation into IL-6, NETosis, complement and coagulation in published data from multiple patients of COVID-19 with varying illness severity. The primary goal was to dissect the transcriptomic dynamics of the functional modules and examine if there is a therapeutic window for drugs targeting specific pathophysiological mechanisms, such as IL-6 blockade or inhibition of NETosis.

Human transcriptomic data were extracted from published data sets of patients of COVID-19 from different tissues: whole blood (longitudinal sampling) [13] , peripheral blood mononuclear cells (PBMC) [14] , and lung tissue [15] . Whole blood was especially selected because it includes neutrophils that are directly responsible for formation of NETs.

Targeted analysis was performed to study the extent of differential expression of two gene sets in whole blood: cytokine genes and NETosis genes. NETosis gene set was significantly up-regulated in whole blood of patients of COVID- 19 [13] . Gene set enrichment analysis (permutation testing) revealed that the genes functional in NETosis were strongly up-regulated in the blood of COVID-19 patients compared to healthy subjects ( Figure 1A ). On the other hand, there was no evidence of broad up-regulation of cytokine gene set in the blood of the patients ( Figure 1B ). Calculation of the pathway score and the null-distribution of the cytokine gene set has been performed as mentioned for NETosis. As shown, there is no (p = 1) up-regulation of cytokine gene set in COVID-19.

(C) For validation of NETosis, gene expression data of healthy control (n=6) and COVID-19 (n=7) were extracted from an independent cohort [14] . Box plot shows up-regulation of NETosis genes in COVID-19 cases compared to the control group. Gene expression data were extracted from [13] for panels A and B;

and from [14] for panel C.

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As the heat map ( Figure 2A) shows, the magnitude of up-regulation is greater in the severe COVID-19 (Case 1) compared to cases with moderate illness (Cases 2 and 3). In general, more genes functional in NETosis are up-regulated (red cells) in severe illness compared to moderate illness. The genes shown in Figure 2A are shown in the bar graphs in Figure 2B . Average level of expression of each gene across all time points was compared between moderate illness (blue bar) and severe illness (red bar). For each of these genes, level of expression is higher (and for many of these genes, the difference is statistically significant) in severe illness compared to moderate illness ( Figure 2B ).

Further, level of gene expression was compared between severe and moderate illness for fixed time points . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

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The copyright holder for this preprint this version posted October 14, 2020. Error bar represents standard deviation of log-gene expression. Significance of up-regulation in severe illness was assessed by t-test and is indicated with an asterisk over the bars (* p < 0.1; ** p < 0.01). The genes functional in NETosis are up-regulated in the lungs of the patients with COVID-19.

Log (gene expression) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted October 14, 2020. . https://doi.org/10.1101/2020.10.13.20211425 doi: medRxiv preprint Up-regulation of NETosis is associated with higher neutrophil to lymphocyte ratio (NLR) NETosis up-regulation was associated with increased NLR in the blood. As shown in Figure 4A , there is up-regulation of genes functional in NETosis at a level higher in the severe case (red) compared to the moderate cases (blue). Additionally, NLR is higher in the blood of severe case compared to moderate cases. With time, both NLR and NETosis gene expression return to baseline in the severe case (red boxes and red bars respectively for case 1 in Figure 4A and 4B). . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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In the severely ill patient of COVID-19 line plot was drawn to show the reciprocal relationship of gene expression with oxygen saturation (%). As shown in Figure 5 , there is up-regulation of genes (functional in NETosis) at the time of low oxygen saturation and down-regulation otherwise. This is also proven by negative correlation coefficient for the genes ( . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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Genes belonging to the complement pathway were extracted and subjected to gene set enrichment analysis (permutation testing). As shown in Figure 6 , there is significant up-regulation of the genes functional in the complement pathway. Additionally, multiple genes functional in the coagulation cascade are also observed to be up-regulated (Figure 7 ). . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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Box plot of longitudinal IL-6 profiling in three groups of subjects (healthy control, moderate illness, severe illness) revealed that the magnitude of up-regulation is greatest early in the disease process [ Figure 9 ]. With increasing days post-onset, the level of expression in the severe illness approaches that in the moderate illness [16] . The reduction in IL-6 expression coincides with increase in the expression of genes functional in NETosis, such as CTSG and CEACAM8 (Figure 10 ). extracted from published data set [14] . Group-level expression (aggregate log counts) data are shown in the box plot, with monotonic up-regulation of CEACAM8 genes from the control group, to COVID-19

cases without ARDS (NonVent) and with ARDS. CEACAM8 up-regulation is a signature of immature or developing neutrophil, a neutrophil subtype associated with COVID-19

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In view of the role of DNASE1 in clearance of NETs, we explored the level of its expression in the patients of COVID-19 with varying illness severity. As shown in Figure 11 , there is significant downregulation of DNASE1 in the COVID-19 patients, with greater down-regulation in the patients with ARDS. Figure 11 : DNASE1 gene expression in PBMC of healthy control (n=6) and COVID-19 (n=7) were extracted from published data set [14] . Box plot of group-level gene expression (aggregate log counts) of DNASE1 shows monotonic down-regulation with increasing severity of illness in COVID-19 cases.

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The copyright holder for this preprint this version posted October 14, 2020. C3 engages complement receptors (CR1, CR3) on neutrophil and activates formation of NET [17] . The components of NET activate platelets which secrete HMGB1, inducing coagulation. Negatively charged NETs can bind and activate circulating glycoprotein FXII (a zymogen produced by liver) that induce coagulation. Plasmin cleaves C5 to active C5a which in turn activates Neutrophil by binding via C5R [17] . Activated platelets can engage with activated neutrophils through binding of P-selectin to PSGL-1 [17] .

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Unbiased analysis of transcriptome data reveals that gene set functional in NETosis is strongly upregulated in the blood of COVID-19 patients. The up-regulation is statistically significant and is higher in magnitude in severe illness than in moderate illness. Up-regulation of NETosis is most prominent in the early time points of illness, and with passing days, the level of gene expression approaches that in moderate illness. Paired testing reveals that from day 6 until day 9, there is significant and sustained elevation of gene expression functional in NETosis in severe illness compared to moderate illness.

Of note, death of the patients of COVID-19 occurs primarily due to the complications arising from SARS-CoV-2-associated acute respiratory distress syndrome. NETosis is known to cause immunothrombosis and respiratory dysfunction in COVID-19 [5] . We present transcriptional evidence of NETosis up-regulation in both peripheral blood and autopsied lung tissue of COVID-19 patients.

Additionally, time-course expression data from a case of severe COVID-19 reveal negative association of NETosis gene expression with respiratory function (oxygen saturation). Together, these findings are consistent with NETosis as an underlying mechanism for a pro-thrombotic state in blood leading to respiratory dysfunction.

Transcriptional profiling of nasopharyngeal swabs from COVID-19 patients have demonstrated upregulation of complement and coagulation pathway associated with mortality and morbidity [4] . Our analysis (of data from [13]) also revealed significant up-regulation of the complement pathway genes in severe COVID-19 illness. NETs act as scaffold for both thrombogenesis and complement activation; and the three pathways (NETosis, complement and coagulation) are considered a single coordinated biological process [17] . NETosing neutrophils have been shown to activate complement via alternative and non-alternative pathways [18] . Also, activated macrophages are known to cause induction of complement factors. The supernatant of macrophage that causes overexpression of the complement factors C3 and CFB are enriched in IL-6 [19] , which is consistent with our observation of segregation of complement factors C3 and CFB with IL-6 but not with the other pro-inflammatory cytokines (IL-8, IL-1 and TNF) in COVID-19 illness. While cooperation among different components of NETosiscomplement-coagulation consortium protects host against both haemorrhage and infection [17] , unchecked NETosis causes immunothrombosis and leads to acute respiratory distress in COVID-19

illness [5] .

By unsupervised clustering, we observed segregation of IL6 with the complement factors C3 and CFB, which are also up-regulated in the target tissue by IL-6-rich supernatant from activated macrophages [19] .

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The copyright holder for this preprint this version posted October 14, 2020. . https://doi.org/10.1101/2020.10.13.20211425 doi: medRxiv preprint Plasma from both COVID-19 patients [5] and patients of sickle cell disease (SCD) with vaso-occlusive crisis (but not from steady state plasma of SCD) cause significant increase in NETosis [20] . The level of IL-6 is observed to be high in the plasma from these patients. Up-regulation of IL-6 signaling has been observed in nasopharyngeal swab [4] , lung [15] and has been associated with poor outcome of COVID-19 [2, 4, 15] . Interestingly, Mann and colleagues [7] observed early rise of IL-6 level in critically ill patients of COVID-19, which progressively decreased over time even if the patient did not survive. In data from a different cohort, we also observed an early spike of blood expression of IL-6 in severe COVID-19 illness, which returns, over time, to levels comparable with moderate illness [16] . Together these findings support a dynamic shift in IL-6 level in severe illnesswith potential mechanistic and therapeutic significance of IL-6 in the early time window.

It seems likely that the spike in IL-6, secreted by the macrophages responding to the viral entry, triggers NETosis in the patients with severe COVID-19, leading to a complex interaction among NETosis, complement and coagulation pathways [17] , pulmonary immunothrombosis and acute respiratory distress.

IL-6 is known to stimulate thrombosis in platelet-dependent and platelet-independent manner [5, 21] .

With time, while IL-6 levels in patients with severe illness approach that of patients with moderate illness (Figure 8 ), NETosis and complement activation are sustained [17] . Therefore, inhibition of IL-6 signaling is most beneficial before sustained up-regulation of NETosis by a positive feedback loop ( Figure 12 ). In the later phase, IL-6 levels are similar in severe and moderate illness, but NETosis-complementcoagulation lead to immunothrombosis and acute respiratory distress in the severe cases. In this phase, a different strategy is called for, such as, inhibitor of complement and NETosis. Level of IL-6 upon admission can be used as a prognostic marker of outcome [2] and for prioritization of anti-IL-6 therapy.

Neutrophil to lymphocyte ratio (NLR) is proposed as a prognostic biomarker of disease severity and organ failure in COVID-19 [6] . In general, there is an increased number of neutrophils in blood, which, along with lymphopenia, contribute to high NLR. There is also increased neutrophil activation of genes functional in formation of NET. The gene expression in COVID-19 is consistent with neutrophilia commonly observed in severe COVID-19 illness resulting in increased formation of Neutrophil Extracellular Traps (NETs). Therefore, NETosis adequately explains the prognostic power of NLR, and extends itself as a fundamental dysregulation underlying COVID-19 disease severity, respiratory distress and mortality.

While there is increased number of neutrophil in the patients of COVID-19, it is not clear if these are the usual neutrophils of healthy blood. Wilk and colleagues [14] observed a novel kind of "developing neutrophil" in the blood of COVID-19 patients. These neutrophils express high level of CEACAM8, a marker of immature neutrophils that are higher in men and pregnant women compared to non-pregnant women [22] . Notably, mortality and morbidity in COVID-19 has been consistently associated with gender . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted October 14, 2020. . https://doi.org/10.1101/2020.10.13.20211425 doi: medRxiv preprint of the patients, with male patients at a higher risk of poor outcome [3, 23] . The role of any hormonal influence on neutrophil type and activation (and NETosis) in COVID-19 outcome remains to be elucidated.

Sepsis appears as the single most frequent factor associated with mortality in COVID-19 [24] . Similar to COVID-19, sepsis is also associated with coagulopathy [25, 26] . It is likely that the dynamic cytokine (IL-6) dysregulation induces NETosis and coagulation in other non-COVID causes of sepsis. Thus, temporal and precise mechanistic therapy targeting IL-6 and NETosis shall benefit critically ill patients of both COVID-19 and sepsis.

In this study, we present robust transcriptomic evidence of NETosis and complement activation in COVID-19. Level of IL-6 expression fluctuates, with a spike at the beginning that triggers NETosis in the severe cases of COVID-19. Therefore, anti-IL-6 therapy should be initiated as early as possible in severe cases. However, once the patient has entered a state of sustained NETosis-complement activation and immunothrombosis, blocking IL-6 signaling needs to be supplemented with additional measures such as inhibition of NETosis or complement pathway. Timing matters for initiation of the right therapy, and for the right patient.

Selection and preprocessing of the data:

Gene expression data of different covid-19 studies were downloaded from NCBI GEO [27] and ArrayExpress [28] data repository portals ( Table 1 ). The raw count matrix data were quantile normalised and log transformed where necessary before analysis. The normalised data were then stored as individual "expressionSet" objects and subjected to downstream analysis. All analyses were performed in the R programming language [29] .

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The copyright holder for this preprint this version posted October 14, 2020. . https://doi.org/10.1101/2020.10.13.20211425 doi: medRxiv preprint Table 1 : Study characteristics with sources for data sets used in the current study.Code and data availability Data and R code is available in github repository named covid-19 ("https://github.com/skm-lab/covid-19").

Any pathway with 10 or less number of genes was discarded from analysis. For each gene, t-statistic was computed to denote change in gene expression in case group compared to the control group. For each pathway, a score was calculated by weighted averaging (i.e., sum of the gene-level t-statistics divided by the square root of the number of genes in the pathway) of all gene-level t-statistics for the pathway.

Significance of the observed pathway score was calculated by permutation testing performed in the following manner. In each permutation, the samples were randomly re-labelled as case and control, with calculation of a simulated pathway score. This was done 10,000 times generating 10,000 simulated values representing the null distribution of the pathway score. Deviation of the observed pathway score from the null distribution was quantified by the fraction of times that the simulated score was more extreme than the observed score. This result was assigned as permutation p-value of the observed pathway score.

Pathway enrichment analysis was performed using code modified from the R function gseattperm() of the package Category [30] . 10.1038/s41586-020-2588-y . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

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The genes belonging to two groups were selected from relevant literature reviews on cytokine storm [31] and NETosis [17] .

We used the CIBERSORTx [32] for deconvolution of transcriptome data i.e., to find the cellular components in the sample through search for similarity of expression with reference expression values of specific cell types. A gene by sample expression matrix was created with the instructed format of the web portal guidelines. The reference immune cell gene expression was selected from the leukocyte signature matrix (LM22) [33] . The analysis was run without batch correction (only one dataset at a time) and normalisation (as instructed for RNAseq data) with 1000 permutations. The resulting sample by immune cell-fraction matrix was downloaded in comma separated values (.csv) file format and analysed to estimate neutrophil to lymphocyte ratio (NLR).

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Data and R code is available in github repository named covid-19

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The authors declare no conflict of interest.