Increased Interleukin-6 and Macrophage Chemoattractant Protein-1 are associated with Respiratory Failure in COVID-19

doi:10.21203/rs.3.rs-39162/v1

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Research Article

Increased Interleukin-6 and Macrophage Chemoattractant Protein-1 are associated with Respiratory Failure in COVID-19

https://doi.org/10.21203/rs.3.rs-39162/v1

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posted 07 Jul, 2020

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Background: In SARS-CoV-2 infection there is an urgent need to identify patients that will progress to severe COVID-19 and may benefit from targeted treatment.

Objectives: Analyze plasma cytokines in COVID-19 patients and investigate their association with respiratory failure (RF) and treatment in Intensive Care Unit (ICU).

Method: Hospitalized patients (n=34) with confirmed COVID-19 were recruited into a prospective cohort study. Clinical data and blood samples were collected at inclusion and after 2-5 and 7-10 days. RF was defined as PaO2/FiO2 ratio (P/F) <40kPa. Plasma cytokines were analyzed by a Human Cytokine 27-plex assay.

Measurements and Results: COVID-19 patients with RF and/or treated in ICU showed overall increased systemic cytokine levels. Plasma IL-6, IL-8, G-CSF, MCP-1, MIP-1α levels were negatively correlated with P/F, whereas combinations of IL-6, IP-10, IL-1ra and MCP-1 showed the best association with RF in ROC analysis (AUC 0.79-0.80, p<0.05). During hospitalization the decline was most significant for IP-10 (P<0.001).

Conclusion: Elevated levels of pro-inflammatory cytokines were present in patients with severe COVID-19. IL-6 and MCP-1 were inversely correlated with P/F with the largest AUC in ROC analyses and should be further explored as biomarkers to identify patients at risk for severe RF and as targets for improved treatment strategies.

Immunology

COVID-19

inflammation

cytokines

IP-10

IL-6

MCP-1

Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2), identified as the causative agent of coronavirus disease (COVID-19) has quickly spread globally since first reported in December 2019 (1-4). The disease usually presents with pneumonia-like signs and symptoms (5). Most people infected with SARS-CoV-2 experience mild to moderate disease, but some may suffer severe respiratory failure (RF) and acute respiratory distress syndrome (ARDS) in need of mechanical ventilation (5). Clinical management of the disease is mainly supportive care, although despite limited evidence, a variety of anti-viral and immunomodulatory therapies have been suggested (6-8).

SARS-CoV-2 infection seems to cause a delayed but excessive production of inflammatory cytokines and chemokines that contributes to the pathogenesis (9, 10). Indeed, viral evasion of initial immune responses and a subsequent cytokine “storm” causing collateral tissue injury in infected organs seem to play major roles (11-14). Further, high levels of activated T cells producing pro-inflammatory cytokines may contribute to tissue damage in critically ill COVID-19 patients (15).

Lymphopenia, hyperferritinemia and increased D-dimer are associated with severe COVID- 19 (11) (16). Ferritin, potentially reflecting macrophage activation, seems to discriminate between mild and severe disease (17). However, although elevated ferritin seems to be involved in hyperinflammation in COVID-19, the association between ferritin and pro- inflammatory cytokines has not been established. The hyperinflammation seen in severe COVID-19 resembles other comparable conditions like macrophage activation syndrome and hemophagocytic lymphohistiocytosis (HLH) (18). Thus, treatment with immunomodulatory therapies targeting interleukin (IL)-6 or IL-1 receptors could possibly also be of value in COVID-19 (19, 20).

Deeper understanding of the pathogenesis of severe COVID-19 is of major importance for the development of targeted immune therapy. There is also an urgent need for prognostic biomarkers in order to early identify patients that will progress into critical COVID-19. Inflammatory mediators are operating in a complex network and the aim of the present study was to map and characterize this network, including interleukins, interferons, chemokines and growth factors, in plasma collected from patients with various severity of confirmed COVID-19. We explored their potential as prognostic biomarkers for RF, need of treatment in an intensive care unit (ICU) and their relation to routine biochemical and hematological markers of hyperinflammation.

Study design and population

Adult patients (≥18 years old) hospitalized between March 6th and April 14th with confirmed SARS-CoV-2 infection by positive real-time polymerase chain reaction test targeting the E- gene of SARS-CoV-2 were consecutively recruited from Oslo University Hospital, Ullevål and Drammen Hospital, Vestre Viken Hospital Trust, Norway to a multi-center prospective cohort study (Norwegian SARS-CoV-2 study; NCT04381819). Clinical information and laboratory samples were for most cases collected within 48 hours after hospitalization. Peripheral blood was drawn at inclusion, day 2-5 and day 7-10 during hospitalization.

Data collection

Clinical and routine diagnostics were abstracted from electronic medical records using a modified version of the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC, isaric.tghn.org) /World Health Organization (WHO) Clinical Characterization Protocol (CCP) and entered into a secure web-based REDCap database (Research Electronic Data Capture, Vanderbilt University, TN, hosted by University of Oxford, UK).

Clinical outcomes

Clinical outcomes were: 1) development of respiratory failure (RF) during hospitalization defined as an arterial partial pressure of oxygen (PaO2) to fraction of inspired oxygen (FiO2) ratio (P/F) of less than 40 kPa (<300 mm Hg), corresponding to the threshold-value for ARDS by the Berlin definition (21), and 2) need of treatment in ICU. Where PaO2 was not available from the records, PaO2 values were calculated from SaO2 (22).

Ethical considerations

Informed consents were obtained from all patients or patients' family members. The study was approved by the Regional Committee for Medical and Health Research Ethics in South- Eastern Norway (reference number 106624, clinicaltrial.gov NCT04381819).

Sample processing

Peripheral blood was collected into 4mL Vacuette ® (Greiner bio-one International) containing EDTA to avoid coagulation. Samples were immediately stored on ice, processed within 30 minutes and plasma were isolated by centrifugation at 2000g for 20 minutes at 4°C. Plasma were immediately frozen at - 80°C in several aliquots and thawed only once prior to multiplex analysis.

Multiplex analyses

EDTA plasma samples from 34 hospitalized patients (Drammen hospital [n=16] and Oslo University Hospital Ullevål [n=18] were analyzed using a multiplex cytokine assay (Bio-Plex Human Cytokine 27-Plex Panel; Bio-Rad Laboratories Inc., Hercules, CA) containing the following interleukins, chemokines and growth factors: Interleukin (IL)-1β, IL-1 receptor antagonist (IL1-ra), IL-2, IL-4, IL-5, IL-6, IL-7, IL-8/CXCL8, IL-9, IL-10, IL-12 (p70), IL-13, IL-15, IL-17, eotaxin/CXCL11, basic fibroblast growth factor (bFGF), granulocyte-colony stimulating factor (G-CSF), granulocyte macrophage colony stimulating factor (GM-CSF), interferon (IFN)-γ, interferon-inducible protein (IP-10)/CXCL10, monocyte chemotactic protein (MCP-1)/CCL2, macrophage inflammatory protein (MIP)-1α/CCL3, MIP-1β/CCL4, platelet derived growth factor-BB (PDGF-BB), regulated upon activation T cell expressed and secreted (RANTES)/CCL5, tumor necrosis factor (TNF), and vascular endothelial growth factor (VEGF). The samples were analyzed on a Multiplex Analyzer (Bio-Rad Laboratories) according to instructions from the manufacturer. Six of the 27 analytes were not detectable in more than 30% of the samples and were therefore excluded for further analysis (IL-5, IL-10, IL-15, GM-CSF, VEGF and INF-γ). A limited number of samples were below the lower detection limit and in the statistical analyses these were given a random number below the detection limit. The normal reference values for this 27-plax assay are indicated with red lines in Figure 1 (23).

Statistical analysis

Non-parametric testing was used to investigate differences between two or more groups. Mann-Whitney U test was used to compare two independent groups while Kruskal-Wallis was used comparing three groups. Friedman’s test was applied on longitudinal samples, investigating changes from baseline, day 2-5 and day 7-10. P-values were considered significant when <0.05. Due to the explorative nature of the study the statistical analyses were not corrected for multiple testing. The area under the receiver operating characteristics (ROC) curve (AUC) was estimated for patients with or without RF. Correlations were calculated using Spearman rank correlation coefficient. Statistical analysis was performed by SPSS statistical software (Macintosh version 26.0, IBM, Armonk, NY, USA).

Patient characteristics

Table 1 displays demographic and clinical characteristics of the COVID-19 patients included in this study (n=34). Median age was 58 years and 74% were men. Twenty-one of the 34 patients developed RF reflected in a P/F ratio <40 kPa. Ten patients, all with RF, were treated in the ICU including four patients that died during hospitalization. RF patients were mostly men (86%), had higher leucocyte count and higher D-dimer, ferritin, C-reactive protein (CRP) and bilirubin levels compared to the non-RF group. In contrast, the median number of days between the first onset of symptoms and admission to hospital were comparable and there were no differences in age, previous co-morbidities or kidney function (eGFR) between the two groups.

Elevated cytokine levels in COVID-19 patients with Respiratory Failure and in ICU

To investigate a potential dysregulated immune response in critically ill COVID-19 patients we analyzed plasma levels of 27 cytokines. All of the 21 cytokines with reliably detectable plasma levels (see Methods), showed higher levels in COVID-19 patients than in healthy controls (red line Figure 1) obtained from Hennø et al (23). Nine mediators (IL-1ra, IL-2, IL- 4, IL-6, FGF basic, IP-10, MCP-1, MIP-1α and TNF) were significantly higher in the RF group compared to non-RF patients at admission (Figure 1) and IL-6 (0.50, p<0.01), G-CSF (0.55, p<0.01), MCP-1 (0.45, p< 0.05) and MIP-1□ (0.49, p<0.05) levels showed a negative correlation with P/F ratio. We also investigated the relationship between RF and cytokine levels by ROC analysis (Figure 2). MCP-1 (0.79) and IL-6 (0.77) and the combinations of MCP-1 and IL-6 (0.79) and MCP-1 and IL-1ra 1 (0.81) demonstrated the largest, although modest, areas under the curve (AUC) (Figure 2B).

Further, when stratifying the patients dependent on the need of treatment in an ICU compared to regular ward we found significant higher levels of altogether 13 cytokines (IL-1ra, IL-2, IL-4, IL-6, IL-7, IL-8, IL-17A, FGF basic, G-CSF, IP-10, MCP-1, MIP-1α and TNF) in ICU compared to non-ICU patients (Figure 3).

Relationship between biochemical and hematological markers of inflammation and cytokine levels in patients with COVID-19

Since several cytokines were significantly elevated in COVID-19 patients with RF, we further investigated if any of these cytokines were associated with other biochemical and hematological markers of inflammation (Figure 4). IL-1ra, IL-6, IL-8, G-CSF, MCP-1, IP-10, MIP-1α showed a positive correlation with ferritin, whereas there were no correlations found between cytokines and leukocyte count, CRP or D-dimer. Only IL-9 showed a positive correlation with bilirubin.

Dynamic changes in cytokine levels in COVID-19 patients during hospitalization

Cytokine plasma levels were analyzed at several time points during hospitalization to explore their dynamics in COVID-19 (Supplementary Figure S1). Of the 15 patients with available longitudinal samples three were treated in ICU for the whole period, one was transferred to ICU at day 2-5, whereas another two patients were transferred to ICU after 7-10 days. Of the ten cytokines that were elevated in RF patients at baseline, only IL-1ra, MIP-1α, G-CSF and IP-10 displayed significant changes during follow-up (Figure 5). Overall, especially IP-10 levels were reduced for the majority of patients irrespective of P/F values at the last time point (p<0.001). Of note, for two of the three patients that were referred to ICU during hospitalization, there was a corresponding increase in plasma IL-1ra, MIP-1α, G-CSF and IP- 10 levels.

We present data from a Norwegian COVID-19 patient cohort where plasma cytokine levels at admission and follow up during the first ten days of hospitalization were related to disease severity expressed as RF and/or need of ICU treatment or signs of hyperinflammation in peripheral blood. We show that a broad network of pro-inflammatory cytokines is elevated in plasma from patients with COVID-19, especially pronounced in patients with severe RF and even more obvious in patients with need of ICU care. IL-6 and MCP-1 seemed to be of particular interest since they were markedly elevated in patients with RF, significantly inversely correlated with P/F ratio and showed modest, still the largest AUC in ROC analyses. Thus, our data demonstrates a marked dysregulation of the cytokine network in COVID-19 patients and for MCP-1 and IL-6, the levels were strongly correlated with the degree of RF.

Although inflammation is a protective process to clear any foreign pathogen, excessive inflammation can cause severe collateral tissue damage. Our findings of elevated cytokine levels in patients with RF, ICU and hyperinflammation are consistent with earlier reports of SARS-CoV (10), SARS-CoV-2 (12, 20) and for ARDS alone (24). The cytokine release syndrome has been suggested as an important cause of ARDS and RF in COVID-19 patients (12, 19, 20, 25). We demonstrated increased levels of a wide range of inflammatory cytokines in these patients such as IL-1ra, IL-6, IP-10, G-CSF, MCP-1, MIP-1α and TNF, all rapidly released upon innate immune activation and important for shaping the adaptive immune response and induce T cell activation (26). This may reflect systemic cytokine activation in the RF patients, contributing to immunopathology and pulmonary dysfunction in COVID-19. Of these cytokines, IL-6 and MCP-1 were consistently associated with RF. Several studies have suggested a link between high IL-6 levels and disease severity in COVID-19, potentially involving down-regulation of the anti-inflammatory angiotensin converting enzyme (ACE)2 pathway. Data on MCP-1 levels in severe SARS-CoV suggest that secretion of MCP-1 is associated with lung injury (10, 11, 27), and our finding indicates that this macrophage activating chemokine could play a pathogenic role in COVID-19 associated RF.

In addition to IL-6 and MCP-1, we show that the combinations of these cytokines with IL-1ra and IP-10 were equally good as predictors of COVID-19 severity. IL-1ra circulates in much higher levels than IL-1 itself, is involved in NLRP3 inflammasome activation and has been suggested as a reliable marker of IL-1 activity in COVID-19 disease (28). IP-10 is an important mediator of monocyte/macrophage-induced T cell activation also proposed to play a role in COVID-19 pathogenesis (29-31). IP-10 is markedly elevated both in blood and lung tissue from SARS-patients (32). It has recently been suggested that IL-1ra, IP-10 and MCP-3 could serve as predictive markers for disease progression in COVID-19 (29). Despite that plasma inflammatory cytokines are highly heterogeneous with a wide range of biological functions they serve as valuable biomarkers in the diagnosis, management and prognosis of several inflammatory diseases (33). We suggest that IL-6 and MCP-1 should be added to the list of candidate markers for disease prediction in COVID-19 patients with RF, as well as be further explored as targets for immune therapy with cytokine antagonists.

We found that the marked elevation of IP-10 levels correlating with COVID-19 severity declined throughout hospitalization, in line with a recently published study (29) and in previous studies in SARS (34). Interestingly, there was a corresponding increase in not only IP-10, but also IL-1ra, MIP-1a and G-CSF in patients transferred to ICU during hospitalization indicating a worsening of clinical condition.

Still, although the levels of pro-inflammatory cytokines seem to be increased in patients with severe COVID-19, the correlation between cytokines and clinical stage are far from consistent. IL-6 seems to play a central role in cytokine storm (35). However, several patients with severe disease have lower IL-6 levels compared to that seen in cases with a true cytokine storm (36). This also applies for patients with elevated ferritin. Most of the patients also lack some of the clinical hallmarks of systemic cytokine storms like hypotension, capillary leakage syndrome and multi-organ failure. These findings indicate that true cytokine storm is relatively rare and implies that only a minority of patients with severe RF will benefit from specific anti-cytokine treatment. In a recent single center study of 100 patients treated with the IL-6 blocker tocilizumab, 23 worsened in despite of treatment (37). Surprisingly, it seems like treatment failure was highest among patients with pronounced elevated ferritin. Currently, tocilizumab has been approved for a randomized controlled clinical trial to investigate efficacy and safety in treatment of COVID-19 (ChiCTR2000029765). However, accurate patient selection is necessary, as cytokine blockers are potent drugs with risk of adverse reactions (38, 39).

There are some limitations in this study with a small sample size, especially for longitudinal samples where plasma could not be obtained on all time-points for several patients due to logistic challenges. Thus, small differences may not be detected or could give false positive results indicating that the results and significance should be interpreted with caution. The results from the ROC analyses were also all modest. In addition, associations may not necessarily reflect any causal relationship. Finally, plasma isolated from peripheral blood may not fully reflect the immune responses taking place in the infected tissue.

In conclusion, we show that patients with RF, admitted to ICU and with biochemical signs of inflammation have increased cytokine production indicating a hyperinflammatory response. Specific prognostic biomarkers can facilitate rapid detection of critically ill COVID-19 patients and aid in targeted treatment strategies, resulting in improved outcome of disease. Although we did not find convincing evidence of a true cytokine storm, especially combinations of IL-6 and MCP-1 should be further explored as biomarkers in COVID-19 infection.

Acknowledgements

The staff at the laboratory and clinical wards of Deps. of Infectious Diseases at Oslo University Hospital, Ullevål and Drammen hospital for including the patients, blood sampling and processing of biobank.

Contributors

PA, JCH, AMDR, TEM and TU had the idea for and designed the study. LHe and AMDR set up the clinical cohorts at the respective hospitals. CS and SP performed the multiplex analyses. MJJ and EEC did the statistical analyses. MJJ, EEC, KT, ARH and AMDR interpreted the data and drafted the paper. JCH, SP and LGS established the ISARIC database. ARH, KT, EEC, SJ, MJJ, SN, AMDR, HO, TBE, RG, AH and LHe included patients, collected data, and acquired biobank patient samples. All authors critically reviewed the manuscript for important intellectual content and gave final approval for the version to be published. All authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Declaration of interests

TEM is a medical advisor for Ra Pharmaceutical producing complement inhibitors. All other authors declare no competing interests.

Funding

This project has received private funding from the Norwegian Research Council (RCN 312780) and a private donation from Vivaldi Invest A/S owned by Jon Stephenson von Tetzchner.

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Table 1 Patient characteristics

	Total (n=34)	RF (n=21)	Non-RF (n=13)	ICU (n=10)	Non-ICU (n=24)
Age	58 (27-91)	54 (45-91)	63 (27-91)	58 (46-91)	58 (27-91)
Sex, male	25 (74)	18 (86)*	7 (54)	9 (90)	16 (68)
RF	21 (62)	21 (100)	-	10 (100)	11 (46)
ICU	11 (32)	10 (48)	0	10 (100)a	-
Days (symptom to	10 (2-38)	10 (2-37)	10 (3-38)	9 (2-37)	10 (3-38)
hospital admission)
Co-morbidities
Hypertension	6 (15)	2 (10)	4 (30)	0 (0)	6 (26)
Diabetes	4 (12)	2 (10)	2 (15)	1 (10)	3 (13)
Chronic heart disease	8 (24)	4 (19)	4 (31)	4 (40)	4 (17)
Chronic lung disease	1 (3)	1 (5)	0	1 (10)	0
Chronic kidney	4 (12)	2 (10)	2 (15)	2 (20)	2 (8)
disease
Symptoms and O2 therapy
Fever	30 (88)	18 (86)	12 (92)	8 (80)	22 (92)
Cough	28 (82)	17 (81)	11 (85)	8 (80)	20 (83)
Sputum	11 (32)	8 (38)	3 (23)	2 (20)	9 (38)
Sore throat	10 (29)	5 (24)	5 (39)	1 (10)*	9 (38)
Dyspnoae	22 (65)	16 (76)	6 (46)	8 (80)	14 (58)
Respiratory rate > 22	22 (65)	15 (71)	7 (54)	9 (82)	12 (52)
(breaths per min)
Pa_O2 /Fi_O2 ratio	39 (8-66)	32 (8-45)§	46 (32-66)	28 (8-40)#	43 (23-66)
Oxygen therapy	28 (82)	20 (95)*	8 (62)	10 (100)	18 (75)
		Laboratory
Leucocytes (x109/L)	5.8 (2.6-	7.2 (3.8-	4.9 (2.6-8.1)	9.3 (3.8-	5.4 (2.6-
	19.0)	19.0)#		19.0)*	12.0)
Lymphocytes (x109/L)	1.1 (0.3-	1.0 (0.5-1.7)	1.2 (0.3-2.1)	1.1 (0.5-1.5)	1.1 (0.3-
	2.1)				2.1)
Platelets (x109/L)	192 (110-	201 (136-	186 (110-	192 (161-	193 (110-
	611)	611)	302)	611)	350)
Haemoglobin (g/dL)	13.4 (8.5-	13.6 (8.5-	13.2 (9.8-	12.8 (8.5-	13.4 (9.8-
	17.9)	17.9)	15.2)	17.9)	15.6)
D-dimer (mg/L)	0.80 (0.30-	1.2 (0.48-	0.55 (0.30-	1.60 (0.71-	0.76 (0.30-
	4.10)	4.10)*	4.0)	4.10)*	4.0)
Ferritin (𝜇g/L)	814 (105-	1114 (178-	455 (105-	1226 (178-	747 (105-
	2893)	2893)§	1609)	2893)	2777)
C-reactive protein,	67 (3-448)	117 (23-	46 (3-191)	151 (44-	47 (3-196)
(mg/L)		448)*		448)#
LDH (U/L)	322 (118-	350 (146-	274 (118-	441 (146-	283 (118-
	561)	561)	354)	561)*	479)
eGFR	86 (13-	86 (23-164)	79 (13-113)	81 (23-164)	91 (13-
(mL/min/1.73m3)	164)				120)
Bilirubin total, (𝜇mol/L)	10 (3-17)	11 (8-17)*	8 (3-17)	12 (8-17)	9 (3-17)

^a One patient who died was in need of ICU but was not transferred due to high age.

Data are given as median (range), n (%).

Significance indicated with *p<0.05, #p<0.01, §p<0.001

DatasupplementJrgensenet.al..pdf
Supplementary figure S1 longitudinal cytokine measurements during hospitalization. Cytokines measured in plasma for all patients at day of inclusion (n=30), day 2-5 (n=23) and day 7-10 (n=22) during hospitalization.

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Increased Interleukin-6 and Macrophage Chemoattractant Protein-1 are associated with Respiratory Failure in COVID-19

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Abstract

Figures

Introduction

Methods

Study design and population

Data collection

Clinical outcomes

Ethical considerations

Sample processing

Multiplex analyses

Statistical analysis

Results

Patient characteristics

Elevated cytokine levels in COVID-19 patients with Respiratory Failure and in ICU

Relationship between biochemical and hematological markers of inflammation and cytokine levels in patients with COVID-19

Dynamic changes in cytokine levels in COVID-19 patients during hospitalization

Discussion

Declarations

References

Tables

Table 1 Patient characteristics

Supplementary Files

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