Abstract

Background

   Dexamethasone improves the survival of COVID-19 patients in need of
   supplemental oxygen therapy. Although its broad immunosuppressive
   effects are well-described, the immunological mechanisms modulated by
   dexamethasone in patients hospitalized with COVID-19 remain to be
   elucidated.

Objective

   We combined functional immunological assays and an omics-based approach
   to investigate the in vitro and in vivo effects of dexamethasone in the
   plasma and peripheral blood mononuclear cells (PBMCs) of COVID-19
   patients.

Methods

   Hospitalized COVID-19 patients eligible for dexamethasone therapy were
   recruited from the general care ward between February and July, 2021.
   Whole blood transcriptomic and targeted plasma proteomic analyses were
   performed before and after starting dexamethasone treatment. PBMCs were
   isolated from healthy individuals and COVID-19 patients and stimulated
   with inactivated SARS-CoV-2 ex vivo in the presence or absence of
   dexamethasone and transcriptome and cytokine responses were assessed.

Results

   Dexamethasone efficiently inhibited SARS-CoV-2-induced in vitro
   expression of chemokines and cytokines in PBMCs at the transcriptional
   and protein level. Dexamethasone treatment in COVID-19 patients
   resulted in down-regulation of genes related to type I and II
   interferon (IFN) signaling in whole blood immune cells. In addition,
   dexamethasone attenuated circulating concentrations of secreted
   interferon-stimulating gene 15 (ISG15) and pro-inflammatory cytokines
   and chemokines correlating with disease severity and lethal outcomes,
   such as tumor necrosis factor (TNF), interleukin-6 (IL-6), chemokine
   ligand 2 (CCL2), C-X-C motif ligand 8 (CXCL8), and C-X-C motif
   chemokine ligand 10 (CXCL10). In PBMCs from COVID-19 patients that were
   stimulated ex vivo with multiple pathogens or Toll-like receptor (TLR)
   ligands, dexamethasone efficiently inhibited cytokine responses.

Conclusion

   We describe the anti-inflammatory impact of dexamethasone on the
   pathways contributing to cytokine hyperresponsiveness observed in
   severe manifestations of COVID-19, including type I/II IFN signaling.
   Dexamethasone could have adverse effects in COVID-19 patients with mild
   symptoms by inhibiting IFN responses in early stages of the disease,
   whereas it exhibits beneficial effects in patients with severe clinical
   phenotypes by efficiently diminishing cytokine hyperresponsiveness.

   Keywords: COVID-19, SARS-CoV-2, dexamethasone, cytokine storm,
   interferon, ISG15

Introduction

   The coronavirus disease 2019 (COVID-19) pandemic remains a significant
   threat to human health, resulting in more than 6.7 million deaths as of
   January 2023 ([53]1). The majority of individuals infected with severe
   acute respiratory syndrome coronavirus 2 (SARS-CoV-2) develop mild
   COVID-19 with symptoms of cough, fever and dyspnea, or remain
   asymptomatic ([54]2). However, an important minority of COVID-19
   patients develop severe forms of COVID-19, characterized by
   life-threatening pneumonia, leading to acute respiratory distress
   syndrome (ARDS) and/or respiratory failure, often necessitating
   cardiopulmonary monitoring and mechanical ventilation in the Intensive
   Care Unit (ICU) ([55]2, [56]3).

   Immunological studies have indicated that severe COVID-19 is hallmarked
   by an initial failure to control viral replication, followed by a
   dysregulated hyperinflammatory response leading to cytopathic damage of
   the respiratory epithelium ([57]4, [58]5). The hyperinflammatory
   response involves the excessive induction of several anti-viral and
   pro-inflammatory cytokines and chemokines ([59]3–[60]8), which trigger
   immune cell recruitment, cell damage (lung epithelium), microvascular
   thrombosis and hyperpermeability, and systemic inflammation with
   multiorgan damage ([61]9).

   The treatments that have so far proven most successful in severe or
   critically ill patients are mostly already known immunomodulatory
   drugs, with corticosteroids remaining the standard of care ([62]10).
   The landmark RECOVERY trial revealed that treatment with dexamethasone,
   a synthetic corticosteroid that is considered as an immunosuppressive
   drug, reduced mortality of patients with severe COVID-19 ([63]11). The
   greatest benefit was shown for patients receiving invasive mechanical
   ventilation compared to those on non-invasive oxygen support. A
   meta-analysis of the RECOVERY trial and subsequent studies support the
   beneficial effect on survival and ventilator-free days in patients with
   severe disease ([64]12), but suggest that dexamethasone treatment in
   patients without oxygen support may be harmful ([65]13).

   An in-depth understanding of the immunological effects of dexamethasone
   in COVID-19 aids in the identification of immunological profiles in
   patients that will either likely benefit from this therapy or from
   additional immunomodulatory treatment, or on the contrary could be more
   prone to the adverse effects of the immunosuppressive effects,
   including secondary infections. To this end, we applied functional
   immunological assays and omics-based approaches to assess the in vivo
   immunological effects of dexamethasone in patients hospitalized with
   COVID-19, by comparing whole-blood and peripheral blood mononuclear
   cell (PBMC) transcriptome and plasma inflammatory proteins before and
   during treatment. In addition, we performed in vitro experiments to
   study the effects of dexamethasone on the immune response in PBMCs from
   COVID-19 patients challenged with various inflammatory stimuli and
   pathogens.

Materials and methods

Study design and ethical approval

   This prospective, low-intervention study was conducted at Radboudumc,
   Nijmegen, the Netherlands and two medical centers in Greece (Thoracic
   Diseases General Hospital ‘Sotiria’, Athens, Greece and Alexandra
   General Hospital, Athens, Greece). There was no formal study
   intervention, but all patients included in the study received
   dexamethasone based on clinical indication according to the local
   treatment guidelines. The study protocol was approved by the local
   medical ethics committee of the Radboudumc and the National Ethics
   Committee of Greece (approval 38/20) and was conducted in accordance
   with Good Clinical Practice Guidelines and the Declaration of Helsinki.
   Verbal informed consent was obtained from all participants and
   documented in the medical records of the respective hospitals to which
   they were admitted.

Patients, participants, and clinical data collection

   After admission to the general care wards, patients were considered
   eligible for inclusion if 1) they had been admitted to the hospital
   with reverse transcriptase polymerase chain reaction (RT-PCR)-confirmed
   or high suspicion of COVID-19, and 2) there was an indication to start
   dexamethasone treatment according to WHO treatment guidelines, but they
   had not started this treatment yet. Patients who had already started
   dexamethasone treatment or had been treated with corticosteroids or
   other immunomodulatory drugs (e.g., TNF blockers, inhibitors of
   interleukin -1 or 6) within 30 days prior to screening were excluded
   from participation. RT-PCR was performed for all patients and
   negatively tested patients were to be excluded from the study. As
   controls, samples of healthy individuals who did not report or present
   with any clinical signs of SARS-CoV-2 infection were used; their
   characteristics are detailed in [66]Supplementary Table 1 . These
   samples were collected within the 200FG cohort of the Human Functional
   Genomics project ([67]http://www.humanfunctionalgenomics.org). ([68]14,
   [69]15).

Interventions and sampling

   The COVID-19 patients included in the study were treated with
   dexamethasone administered daily in a 6 mg dose, as recommended by
   COVID-19 treatment guidelines ([70]12, [71]16). Dexamethasone was
   administered in a clinical treatment setting and was not considered a
   study intervention. Study samples were taken at two timepoints, just
   before and between three to four days after starting dexamethasone
   treatment (which were designated in analyses and figures as pre-Dex and
   post-Dex, respectively). Venous blood was collected into 3 x 10 mL
   sterile Ethylenediaminetetraacetic acid (EDTA) tubes, and an additional
   volume of 2.5 mL blood was transferred into a PAXgene Blood RNA tube
   (BD Biosciences) and remained at room temperature for a minimum of two
   hours before being stored at − 80°C.

Plasma samples and PBMC isolation

   EDTA anticoagulated blood was centrifuged at 2000 x g at room
   temperature for 10 min and plasma was stored at −80°C until analysis.
   PBMCs were obtained by individuals with gradient centrifugation over
   Ficoll-Paque Plus (GE Healthcare) in SepMate tubes (STEMCELL
   Technology) and immediately freshly used for ex vivo functional assays
   or lysed in RLT buffer (Qiagen) and stored at −80°C for subsequent RNA
   isolation.

Ex vivo stimulation experiments

   PBMCs were counted and resuspended in Dutch modified Roswell Park
   Memorial Institute (RPMI) medium (Life Technologies), supplemented with
   50 µg/mL gentamicin (Thermo Fisher Scientific), 1 mM sodium pyruvate
   (Thermo Fisher Scientific), and 2 mM Glutamax (Thermo Fisher
   Scientific). 5 x 10^5 PBMCs were cultured in a final volume of 200
   μL/well in round bottom 96-well plates (Greiner Bio-one) and stimulated
   with of heat-inactivated SARS-CoV-2 Wuhan-Hu-1 virus variant (1.19 x
   10^4 TCID50/ml; NRW-42 isolate, kindly provided by Heiner Schaal,
   University Hospital Düsseldorf, Germany) ([72]17), heat-inactivated
   Staphylococcus aureus (1 x 10^6 CFU/mL; clinical isolate),
   heat-inactivated influenza virus H1N1 (3.2 x 10^5 K/mL, kindly provided
   by Ortwin Adams, University Hospital Düsseldorf, Germany),
   Imiquimod/R837 (10 µg/ml; InvivoGen), Poly (I:C) (10 µg/mL; InvivoGen),
   R848 (10 µg/mL; InvivoGen), purified lipopolysaccharide (LPS) derived
   from Escherichia coli O55:B5 (10 ng/mL; Sigma-Aldrich), or recombinant
   human interleukin-1 alpha (IL-1α) (10 ng/mL; R&D Systems), in the
   presence of dexamethasone (10 nM or otherwise stated; Sigma-Aldrich) or
   vehicle control (dimethyl sulfoxide; DMSO). After 4h cells were lysed
   in RLT buffer (Qiagen) and stored at −80°C for subsequent RNA
   isolation. After 24 h or 7 days, supernatants were collected and stored
   at –80°C until analysis.

RNA isolation, RNA-sequencing, and data processing

   Total RNA was extracted from whole blood collected in PAXgene^® tubes
   (BD Biosciences) using PAXgene Blood RNA kit (QIAGEN) following the
   manufacturer’s instructions. Frozen PAXgene tube samples were thawed at
   room temperature overnight before RNA isolation steps to ensure
   complete lysis of red blood cells and precipitation of RNA. Total RNA
   was isolated from PBMCs, and on column DNase (QIAGEN) treated, using
   the RNeasy mini kit (QIAGEN) by following the manufacturer’s
   instructions. RNA concentrations and purity were assessed with NanoDrop
   spectrophotometer (Thermo Fisher Scientific). Samples were submitted to
   Beijing Genomics Institute (BGI), and RNA integrity was further
   evaluated with the Agilent 4200 system (Agilent Technologies).

   The RNA-Sequencing library was prepared by using the MGIEasy RNA
   Library Prep kit (MGI Tech). Strand specific RNA sequencing was
   performed on a DNBSEQ platform (paired-end, read length 100 pb) and at
   least 30 million clean reads were generated per sample. After
   sequencing, raw reads were filtered using SOAPnuke ([73]18). Filters
   include the removal of the adapter sequence, contamination check, and
   removal of low-quality reads (Q ≥ 33). Thereafter, processed data was
   assessed for quality control using FastQC ([74]19) (version 0.11.9) and
   MultiQC ([75]20) (version 1.14). Next, the remaining filtered data were
   aligned to the human genome GENCODE Release 39 (GRCh38.p13) using the
   STAR ([76]21) (version 2.7.10a) aligner with STAR’s default parameters.
   The quantification of read counts per gene was performed using the
   –quantMode GeneCounts from STAR.

ELISA measurements

   Production of secreted cytokines in PBMC culture supernatants was
   measured using ELISA. IL-1β, IL-6, TNF, CXCL10, interleukin-10 (IL-10),
   interleukin-1 receptor antagonist (IL-1Ra), and interferon-gamma
   (IFN-γ) concentrations were determined with duoSet ELISA kits (R&D
   Systems). The VeriKine Human Interferon Alpha ELISA Kit (PBL Assay
   Science) was used to measure interferon-alfa (IFN-α). Supernatants from
   7-day cultures were used for IFN-γ measurements, whereas the remaining
   cytokines were measured in 24-hour culture supernatants. Plasma
   concentrations of Interferon Stimulated Gene 15 (ISG15) were measured
   using the Human ISG15 ELISA kit from Elabscience (Elabscience). All
   tests were performed according to the instructions of the manufacturer.

Multiplex cytokine assay

   Plasma concentrations of IFN-γ, IL-6, TNF, CXCL8, IL-10, IL-1Ra,
   CXCL10, CCL2 were measured in Luminex MAGPIX system and performed using
   the Milliplex human cytokine/chemokine magnetic bead panel kit
   according to manufacturer’s instructions (Milliplex; Millipore). Data
   were analyzed with the Milliplex analyst software (Millipore).

OLINK proteomic analysis

   Inflammatory biomarkers were measured in EDTA plasma using the Olink
   Target 96 Inflammation panel (Olink Proteomics AB). This panel uses a
   proximity extension assay (PEA) developed by Olink Proteomics,
   containing 96 protein targets relating to inflammatory response
   ([77]22). Olink’s PEA defines proteome expression in an arbitrary unit
   called normalized protein expressions (NPX), which are calculated from
   the inverse of cycle threshold (Ct) values required to detect specific
   proteins included in the assay. This value can be used for relative
   quantification of protein expression within a cohort measured at the
   same occasion. Because the samples were taken from COVID-19 patients,
   45 µL of each sample was inactivated with 5 µL of a 10% TritonX-100
   solution. Olink data were analyzed using RStudio (version 2021.09.1
   Build 372, RStudio).

Differential expression analysis, functional pathway analysis, and data
visualization

   The R package DESeq2 ([78]23) package (version 1.38.1, RStudio) was
   utilized for differential expression analysis. We filtered lowly
   expressed genes by removal of genes with less than 5 read counts across
   all samples in each comparison. Thereafter, filtered counts were
   normalized using the DESeq2 method which directly accounts for
   differences in the library size. Samples were analyzed using paired
   comparisons between experimental groups and differentially expressed
   genes (DEGs) were determined by the Wald test using the
   Benjamini-Hochberg correction (FDR) < 0.05. Visualization of DEGs was
   done using Volcano plots which were generated using the R package
   Enhancedvolcano (version 1.16.0). Finally, the normalized counts were
   Log[2] transformed and used for visualization and downstream analyses.
   Functional enrichment was performed using the R packages
   ClusterProfiler ([79]24) (4.6.0) and enrichR ([80]25) (version 3.1)
   based on information from GO terms or Reactome databases. Hierarchical
   clustering and generation of heatmaps were performed using the
   ComplexHeatmap ([81]26) (version 2.14.0) and pheatmap packages in R
   (version 1.0.12). Other visualizations were created using ggplot2
   (version 3.4.0) or Graph Prism 9 (GraphPad software).

Statistical analysis

   For descriptive statistics, demographic data were analyzed in SPSS
   Statistics (version 28.0.1.0., IBM software). Statistical analyses of
   multiplex cytokine assay and the ELISA data were performed in Graph
   Prism 9 (GraphPad software). Two-way ANOVA followed by Tukey’s multiple
   comparison test was used for multiple group comparisons. Wilcoxon
   signed-rank test was used for paired and Mann–Whitney U test was used
   for unpaired comparisons. A P value < 0.05 was considered to be
   statistically significant.

Results

Dexamethasone alters the transcriptome of SARS-CoV-2-stimulated PBMCs in
vitro

   First, we explored the direct in vitro effects of dexamethasone in
   SARS-CoV-2-stimulated leukocytes. To this end, PBMCs isolated from five
   healthy volunteers ([82] Supplementary Table 1 ) were exposed to
   inactivated SARS-CoV-2 for four hours before analyzing their
   transcriptome profile ([83] Figure 1A ). Heat-inactivated SARS-CoV-2
   was able to induce marked alterations in gene expression. Specifically,
   a total of 1546 genes underwent statistically significant upregulation,
   whereas 1034 genes were downregulated ([84] Figure 1B ). A list of all
   significant DEGs is shown in the supplementary data ([85] Supplementary
   File 1 ). Pathway enrichment analysis revealed that SARS-CoV-2
   stimulation resulted in upregulation of genes involved in inflammatory
   responses such as leukocyte locomotion and migration, as well as
   cytokine production and cytokine-mediated signaling ([86] Figure 1C ).
   Transcripts of several proinflammatory cytokines and chemokines were
   elevated ([87] Figure 1D ), among which mediators related to COVID-19
   disease severity that can be medically targeted ([88]27, [89]28).

Figure 1.

   [90]Figure 1
   [91]Open in a new tab

   Dexamethasone alters the transcriptome of SARS-CoV-2 stimulated PBMCs
   in vitro. (A) Experimental in vitro setup for profiling the
   transcriptome and cytokine responses of PBMCs derived from healthy
   individuals stimulated with heat-inactivated SARS-CoV-2 in the absence
   (vehicle control DMSO) or presence of dexamethasone. (B) Volcano plot
   depicting the distribution of the adjusted P values (-Log[10] P) and
   the fold changes (Log[2] fold change) of differentially expressed genes
   in heat-inactivated SARS-CoV-2-treated PBMCs as compared to
   unstimulated cells 4h after exposure. Significantly altered genes are
   colored red (n=5 healthy individuals; FDR < 0.05). (C) Gene set
   enrichment analysis of top altered pathways in heat-inactivated
   SARS-CoV-2-treated PBMCs, as compared to unstimulated cells 4h after
   exposure. The counts indicate the total number of DEGs in the enriched
   pathway, whereas the color indicates the P value (n=5 healthy
   individuals; FDR < 0.05).(D) Heatmap showing statistically significant
   differentially expressed cytokine transcripts in PBMCs stimulated with
   heat-inactivated SARS-CoV-2, as compared to unstimulated cells 4h after
   exposure. Colors indicate the z-scores calculated per gene from the
   Log[2] normalized counts (n=5 healthy individuals; red increased, blue
   decreased; FDR < 0.05). (E) Volcano plot depicting the distribution of
   the adjusted P values (-Log[10] P) and the fold changes (Log[2] fold
   change) of differentially expressed genes in heat-inactivated
   SARS-CoV-2-treated PBMCs as compared to cells treated with
   dexamethasone (10nM) 4h after exposure. Significantly altered genes are
   colored red (n=5 healthy individuals; FDR < 0.05). (F) Heatmap showing
   differentially expressed genes between untreated (DMSO) or
   dexamethasone (10nM)-treated PBMCs stimulated with heat-inactivated
   SARS-CoV-2 for 4h. Colors indicate the z-scores calculated per gene
   from the Log[2] normalized counts (n=5 healthy individuals; red
   increased, blue decreased; FDR < 0.05).

   We subsequently evaluated the in vitro anti-inflammatory activity of
   dexamethasone in PBMCs stimulated with SARS-CoV-2 and detected 42
   upregulated DEGs after four hours exposure to the heat-inactivated
   virus, while 31 genes were downregulated ([92] Figure 1E ).
   Dexamethasone attenuated the expression of multiple genes previously
   observed to be upregulated in response to SARS-CoV-2, including several
   transcripts related to chemotaxis like CCL2, CXCL1, CXCL3, CXCL5, and
   CXCL8, as well as cytokine genes CSF1, TNFSF15, and IL1RN, and
   metabolic genes related to the immune response such as PTGS2 and ACOD1
   ([93]29, [94]30) ([95] Figure 1F ). Dexamethasone-treated cells
   additionally exhibited increased expression of genes with
   anti-inflammatory actions such as the decoy interleukin-1 receptor
   IL1R2, the product of which can reduce the activity of IL-1β ([96]31),
   and DUSP1, which is implicated in the inhibition of proinflammatory
   signaling pathways ([97]32–[98]34) ([99] Figure 1F ).

   These in vitro immune profiling data indicate that heat-inactivated
   SARS-CoV-2 can induce a potent transcriptional inflammatory response
   characterized by marked alterations in chemotaxis and cytokine
   responses, which is partially counteracted by dexamethasone treatment.

Cytokine responses are inhibited by dexamethasone in PBMCs stimulated with
SARS-CoV-2 in vitro

   Given the excessive cytokine secretion in immune hyperactivation and
   COVID-19 severity ([100]35), we investigated the in vitro effects of
   dexamethasone on SARS-CoV-2-induced cytokine production in PBMCs
   isolated from healthy individuals ([101] Supplementary Table 1 ).
   SARS-CoV-2 stimulation alone led to a significant increase in the
   production of IL-1β, IL-6, and IL-1Ra, but not TNF, in healthy PBMCs
   ([102] Figure 2A ). As expected, dexamethasone diminished the
   production of IL-1β, IL-6, and IL-1Ra in a dose-dependent manner
   (1nM-100nM) and almost completely inhibited their production at the
   highest concentrations (100nM) ([103] Figure 2A ). Compared to
   heat-inactivated SARS-CoV-2, stimulation with other pathogens such as
   heat-inactivated influenza H1N1 or heat-inactivated S. aureus displayed
   stronger in vitro cytokine responses than with SARS-CoV-2, and these
   were also significantly decreased by dexamethasone ([104] Figures 2B, C
   ). Additionally, effective attenuation of the production of the
   anti-viral type-I and II IFNs, IFN-α and IFN-γ, respectively, was
   observed upon dexamethasone treatment in PBMCs stimulated with
   SARS-CoV-2 ([105] Figures 2D, E ).

Figure 2.

   [106]Figure 2
   [107]Open in a new tab

   Dexamethasone efficiently inhibits cytokine responses in PBMCs upon
   stimulations with SARS-CoV-2, influenza H1N1 or S. aureus in vitro. (A)
   PBMCs were stimulated in vitro with heat-inactivated SARS-CoV-2 or left
   unstimulated for 24h in the absence (DMSO) or presence of different
   concentrations of dexamethasone, and the production of IL-1β, IL-6, TNF
   and IL-1Ra were assessed in supernatants (n=6 healthy individuals). (B,
   C) PBMCs were stimulated in vitro with heat-inactivated influenza H1N1
   (B), heat-inactivated S. aureus (C), or left unstimulated for 24h in
   the absence (DMSO) or presence of dexamethasone (100nM) for 24h, and
   the production of IL-1β, IL-6, TNF and IL-1Ra were assessed in
   supernatants (n=6 healthy individuals). (D) PBMCs were stimulated in
   vitro with heat-inactivated SARS-CoV-2 or left unstimulated for 24h in
   the absence (DMSO) or presence of different concentrations of
   dexamethasone, and IFN-α was assessed in supernatants (n=4 healthy
   individuals). (E) PBMCs were stimulated in vitro with heat-inactivated
   SARS-CoV-2 or left unstimulated for 7d in the absence (DMSO) or
   presence of different concentrations of dexamethasone, and IFN-γ was
   assessed in supernatants (n=4 healthy individuals). Data are presented
   as mean ± SEM. Two-way ANOVA followed by Tukey’s multiple comparison
   test. *: P value < 0.05, **: P value < 0.01, ***: P value < 0.001, ns =
   not significant.

COVID-19 patient recruitment and characteristics

   As dexamethasone exhibited direct in vitro anti-inflammatory effects in
   SARS-CoV-2-stimulated PBMCs, its efficiency in attenuating
   hyperinflammatory responses in COVID-19 patients was subsequently
   investigated. Thirteen patients hospitalized with COVID-19 were
   recruited in three participating medical centers in the Netherlands and
   Greece between the 4^th of February and the 1^st of July 2021. All
   patients were tested positive for SARS-CoV-2 by RT-PCR. None of the
   patients had been vaccinated against SARS-CoV-2. All patients required
   supplemental oxygen treatment and scored a 5 on the WHO clinical
   progression scale (WHO-CPS) at the time of enrolment, corresponding
   with moderate disease severity ([108]36) ([109] Supplementary Table 2
   ). No secondary infections were reported and all patients included in
   the study survived. One patient required admission to the intensive
   care unit (ICU) and subsequently recovered.

   Nine patients were enrolled and investigated before (pre-Dex) and three
   to four days after (post-Dex) starting dexamethasone treatment. Their
   demographic and clinical characteristics are summarized in [110]Table 1
   . Mean age was 60.8 ( ± 6.9) and the majority of patients were men
   (77.8%). Patients were recruited a mean of 9.0 days ( ± 2.9) after the
   onset of symptoms. One patient was excluded from analyses because of
   inconsistent dosage of dexamethasone on one of the treatment days.

Table 1.

   Patient characteristics.
   Patient characteristics Expressed as
   Demographic characteristics
    Sex
    Female Frequency 2 (22.2%)
    Male Frequency 7 (77.8%)
    Age (years) Mean ± SD 60.8 ± 6.9
    Length (cm) Mean ± SD 175.8 ± 9.3
    Weight (kg) Mean ± SD 85.2 ± 15.4
    BMI (kg/m2) Mean ± SD 27.5 ± 4.9
   Clinical characteristics Timepoints
   Screening Timepoint 1 Timepoint 2
    Systolic blood pressure (mmHg) Mean ± SD 137.1 ± 14.6 N.A. N.A.
    Diastolic blood pressure (mmHg) Mean ± SD 80.4 ± 8.8 N.A. N.A.
    qSOFA score Median (range) 0 (0–1) N.A. N.A.
    Respiratory rate Mean ± SD 20.8 ± 3.3 20.8 ± 3.3 18.9 ± 2.2
    Duration of illness Mean ± SD 9.0 ± 2.9 9.1 ± 2.9 11.8 ± 3.4
    Supplemental oxygen volume (L/min) Mean ± SD 4.1 ± 3.4 4.4 ± 3.5 4.6 ±
   5.2
    Type of supplemental oxygen
    Nasal cannula Frequency 7 (77.8%) 6 (66.7%) 6 (66.7%)
    Venturi mask (40%) Frequency 0 (0%) 1 (11.1%) 2 (22.2%)
    Venturi mask (60%) Frequency 2 (22.2%) 2 (22.2%) 0 (0%)
    Non-rebreathing mask Frequency 0 (0%) 0 (0.0%) 0 (0%)
    High-flow nasal cannula/Non-invasive ventilation mask Frequency 0 (0%)
   0 (0%) 1 (11.1%)
    Mechanical ventilation Frequency 0 (0%) 0 (0%) 0 (0%)
   Comedications during hospitalization
    Remdesivir Frequency 5 (55.6%)
    Anakinra Frequency 1 (11.1%)
    Tocilizumab Frequency 1 (11.1%)
    Baricitinib Frequency 1 (11.1%)
   Clinical outcome
    Length of hospital stay (days) Mean ± SD 8.8 ± 3.6
    Required ICU admission Frequency 0 (0%)
    In-hospital mortality Frequency 0 (0%)
   [111]Open in a new tab

Whole-blood transcriptome of COVID-19 patients treated with dexamethasone

   To delineate the molecular mechanisms underlying the immunomodulatory
   effects of dexamethasone in patients hospitalized with COVID-19, we
   performed whole-blood bulk RNA sequencing in nine patients, before and
   after dexamethasone treatment ([112] Figure 3A ). Unsupervised
   clustering using Principal Component Analysis (PCA) showed clear
   separation of the samples before and after treatment ([113] Figure 3B
   ). We detected 350 upregulated and 714 downregulated transcripts that
   were significantly differentially expressed after dexamethasone
   administration ([114] Figure 3C ; [115]Supplementary File 2 ). Pathway
   enrichment analysis revealed that dexamethasone mostly affected
   pathways related to cytokine and IFN signaling as well as downstream
   IFN-stimulated pathways such as ISG15 and 2′-5′-Oligoadenylate
   Synthetase (OAS) antiviral responses ([116] Figure 3D ).

Figure 3.

   [117]Figure 3
   [118]Open in a new tab

   Whole blood transcriptome profile before and after dexamethasone
   treatment in hospitalized COVID-19 patients. (A) Schematic presentation
   of the study design. COVID-19 patients eligible for dexamethasone
   treatment were analyzed before and 3-4 days after starting
   dexamethasone treatment (n=9 COVID-19 patients). (B) Principal
   component analysis (PCA) plot of whole blood expressed genes in
   COVID-19 patients before (Pre-Dex) and after dexamethasone treatment
   (Post-Dex). The ellipses indicate the 95% confidence intervals (CI).
   (C) Volcano plot depicting the distribution of the adjusted P values
   (-Log[10] P) and the fold changes (Log[2] fold change) of whole blood
   DEGs in COVID-19 patients before and after dexamethasone treatment.
   Significantly altered genes are colored red (FDR < 0.05). (D) Gene set
   enrichment analysis of top altered pathways in whole blood
   transcriptome before versus after dexamethasone treatment. The counts
   indicate the total number of DEGs in the enriched pathway, whereas the
   color indicates the P value (FDR < 0.05). (E) Top 15 significantly
   upregulated protein-coding genes in whole blood transcriptome before
   versus after dexamethasone treatment. The y-axis indicates the Log[2]
   normalized counts. (F) Top 15 significantly downregulated
   protein-coding genes in whole blood before versus after dexamethasone
   treatment. The y-axis indicates the Log[2] normalized counts. (G-J)
   Heatmaps showing differentially expressed genes after dexamethasone
   treatment of IFN α/β signaling (P value = 1.41·10^-20) (G), IFN-γ
   signaling (P value = 6.42·10^−15) (H), ISG15 antiviral mechanism (P
   value = 7.42·10^−04) (I), or OAS antiviral response (P value =
   7.95·10^−03) (J). Row scaling has been applied to each row (gene). The
   colors indicate the z-scores from the Log[2] normalized counts (red
   increased, blue decreased; FDR < 0.05).

   VSIG4, which promotes phagocytosis and acts as a negative regulator of
   T-cell and macrophage activation, was the most significantly induced
   gene upon dexamethasone treatment ([119]37, [120]38) ([121] Figure 3E
   ). Among the most strongly upregulated DEGs were other negative
   regulators of inflammation like MAOA ([122]39), genes related to lipid
   metabolism (LPL, OLAH, ALOX15B) ([123]40), epithelial-to-mesenchymal
   transition (EMT) (SHROOM2, ARGHAP29, FILIP1L) ([124]41, [125]42),
   dendritic cell differentiation (VENTX) ([126]43) and vascular stability
   (BMF) ([127] Figure 3E ; [128]Supplementary File 2 ). Genes related to
   phagocytosis and B-cell activation were also upregulated ([129]
   Supplementary File 2 ).

   Late in the clinical course of COVID-19, sustained IFN secretion
   correlates with worse disease outcomes ([130]7, [131]44, [132]45).
   Pathway enrichment analysis indicated that interferon-stimulated genes
   (ISGs) ([133]44) were strongly modulated by dexamethasone. The top
   downregulated DEGs mostly included genes involved in type-I
   IFN-signaling such as ISG15, IRF7, RSAD2, USP18, and IFIT3 ([134]
   Figure 3F ). Both type-I and II IFN-related genes and genes related to
   upstream signaling such as IRF7 and STAT2 were consistently
   downregulated among patients treated with dexamethasone ([135]
   Figure 3G, H ). Additionally, gene clusters that constitute important
   pathways in the host defense against SARS-CoV-2, such as TLR7 and
   IFIH1/MDA5 signaling pathways were inhibited by dexamethasone ([136]
   Supplementary File 2 ). ISG15 is implicated in antiviral responses by
   conjugating to viral proteins and additionally functioning as a
   cytokine ([137]46), and several genes related to ISG15 antiviral
   response were decreased ([138] Figure 3I ). Of note, the top DEGs
   included genes related to ISG15-mediated antiviral signaling as well as
   the restriction of viral replication through OAS enzymes ([139]
   Figures 3F, I, J ) ([140]47). Collectively, whole blood transcriptome
   analysis showed that dexamethasone predominantly affected IFN-related
   responses.

Plasma cytokine and chemokine concentrations in COVID-19 patients treated
with dexamethasone

   To assess the effects of dexamethasone on inflammatory biomarkers in
   vivo, we performed targeted proteomic analyses on EDTA plasma collected
   from nine COVID-19 patients before and after dexamethasone treatment by
   using the Olink Target 96 Inflammation panel ([141] Figure 3A ). A
   total of 80 of the 92 proteins included in the panel were detectable in
   >75% of all samples. The normalized protein expression (NPX) values of
   these 80 proteins were then compared pairwise between each timepoint
   for each patient. COVID-19 patients exhibited a distinct inflammatory
   biomarker profile upon dexamethasone treatment ([142] Figure 4A ). We
   observed 20 inflammatory proteins significantly decreased after
   dexamethasone treatment, including the cytokines IL-6, interleukin-17A
   (IL-17A), interleukin-12B (IL-12B), and IFN-γ, the chemokines CCL2,
   CXCL8, chemokine ligand 19 (CCL19), chemokine ligand 20 (CCL20), and
   CXCL10/IP-10, the proteases matrix metalloprotein-10 (MMP-10) and
   urokinase plasminogen activator (uPA), and the hematopoietic cytokines
   Fms-related tyrosine kinase 3 ligand (FLT3L) and colony stimulating
   factor 1 (CSF-1) ([143] Figure 4B ). Many of these mediators have
   previously been shown to correlate with COVID-19 disease severity
   ([144]6, [145]48–[146]53).

Figure 4.

   [147]Figure 4
   [148]Open in a new tab

   Dexamethasone treatment diminishes circulating inflammatory proteins in
   hospitalized COVID-19 patients. (A) PCA plot of normalized protein
   expression (NPX) values of circulating plasma proteins (inflammatory
   Olink panel) before (Pre-Dex) and 3-4 days after starting dexamethasone
   treatment (Post-Dex). The ellipses indicate the 95% CIs (n=9 COVID-19
   patients). (B) Volcano plot depicting the distribution of the FDR and
   Log[2] fold change in normalized protein expression values of
   inflammatory plasma proteins (inflammatory OLINK panel) in COVID-19
   patients before versus after dexamethasone treatment. Significantly
   altered proteins (FDR < 0.05) are plotted in red (n=9, Wilcoxon
   signed-rank test). (C) Plasma concentrations of selected cytokines in
   COVID-19 patients before and after dexamethasone treatment as
   determined by Luminex multiplex assay (n=8-9). *: P value < 0.05, **: P
   value < 0.01, Wilcoxon signed-rank test. (D) Plasma concentrations of
   ISG15 in healthy individuals and in COVID-19 patients before and after
   dexamethasone treatment as determined by ELISA (n=8 healthy volunteers,
   n=9 patient samples before and after treatment). *: P value < 0.05, **:
   P value < 0.01, Mann-Whitney U test (healthy vs COVID-19 patients);
   Wilcoxon signed-rank test (pre-Dex vs post-Dex).

   We further validated the relative expression results from Olink by
   using multiplex ELISA to measure patient plasma concentrations of key
   cytokines and chemokines strongly related to disease severity.
   Significant decreases in plasma concentrations of the pro-inflammatory
   cytokines IL-6, TNF, and IFN-γ, the leukocyte chemoattractants CXCL8,
   CXCL10, and CCL2, and the anti-inflammatory cytokines IL-10 and IL-1Ra
   were observed in COVID-19 patients during dexamethasone treatment
   ([149] Figure 4C ). Plasma concentrations of secreted ISG15, which were
   elevated in COVID-19 patients as compared to healthy volunteers, were
   significantly inhibited by dexamethasone ([150] Figure 4D ) ([151]47).

The effects of dexamethasone on ex vivo responses of PBMCs derived from
COVID-19 patients

   To further expand our understanding of the immunomodulatory effects of
   dexamethasone in COVID-19, we investigated the transcriptomic and
   cytokine profiles of ex vivo stimulated PBMCs derived from COVID-19
   patients ([152] Figure 5A ; [153]Supplementary Table 3 ). We first
   evaluated the effects of dexamethasone on the transcriptome of
   SARS-CoV-2-stimulated cells. The Venn diagram in [154]Figure 5B
   displays the overlap and differences in the significantly altered
   transcripts upon treatment with dexamethasone in SARS-CoV-2-stimulated
   PBMCs derived from COVID-19 patients as compared to healthy individuals
   (previously described in [155]Figure 1F ). A total of 19 DEGs were
   significantly affected in PBMCs from both healthy individuals and
   COVID-19 patients, while 54 and 83 transcripts were only significantly
   altered in PBMCs from healthy volunteers and COVID-19 patients,
   respectively ([156] Figure 5B ).

Figure 5.

   [157]Figure 5
   [158]Open in a new tab

   Ex vivo effects of dexamethasone in stimulated PBMCs derived from
   COVID-19 patients. (A) Experimental setup for profiling the ex vivo
   transcriptome and cytokine responses of stimulated PBMCs derived from
   COVID-19 patients in the absence (DMSO) or presence of dexamethasone.
   (B) PBMCs derived from COVID-19 patients or healthy individuals were
   stimulated ex vivo with heat-inactivated SARS-CoV-2 for 4h in the
   absence (DMSO) or presence of dexamethasone and analyzed for their
   transcriptome profile. In the Venn diagram the genes significantly
   altered by dexamethasone only in PBMCs from COVID-19 patients are
   depicted with purple whereas the genes significantly altered by
   dexamethasone only in PBMCs from healthy individuals (as referred in
   [159]Figure 1F ) are depicted with green. Gene upregulation or
   downregulation is indicated by the respective arrowheads. (n=5 COVID-19
   patients, n=5 healthy individuals, FDR < 0.05). (C) PBMCs derived from
   COVID-19 patients were challenged ex vivo with heat-inactivated
   SARS-CoV-2, heat-inactivated influenza H1N1, heat-inactivated S.
   Aureus, the TLR ligands Imiquimod, R848, LPS or Poly I:C, the
   pro-inflammatory cytokine IL-1α, or left unstimulated for 24h in the
   absence (DMSO) or presence of dexamethasone (10nM), and the production
   of IL-1β, IL-6, TNF, CXCL10, IL-10 and IL-1Ra was assessed in
   supernatants after 24h (n=13 COVID-19 patients). The production of
   IFN-γ was assessed in the supernatants after 7d culture (n=12 COVID-19
   patients). *: P value < 0.05, **: P value < 0.01, ***: P value < 0.001,
   Wilcoxon signed-rank test.

   Of the DEGs that overlapped between healthy and COVID-19 PBMCs, 17 were
   upregulated, among which IL1R2, whereas the genes encoding for the
   cytokine tumor necrosis factor superfamily member 15 (TNFSF15) and
   ACOD1 were downregulated by dexamethasone ([160]29, [161]54, [162]55).
   Of note, several chemokines were not significantly affected by
   dexamethasone in PBMCs from COVID-19 patients as compared to healthy
   individuals. Among others, cytokine-related genes IL12B and TNFSF10 and
   members of the Krüppel-like factors (KLF) and CCAAT/enhancer-binding
   protein (CEBP) family of transcription factors as well as transcription
   factor 7 (TCF7) were affected only in COVID-19-derived PBMCs ([163]
   Figure 5B ).

   We further evaluated the effects of dexamethasone in PBMCs from
   COVID-19 patients by examining their cytokine responses to several
   pathogens and inflammatory stimuli. To this end, PBMCs isolated from
   COVID-19 patients before receiving their first dose of dexamethasone,
   were exposed ex vivo to heat-inactivated SARS-CoV-2, heat-inactivated
   H1N1 Influenza, heat-inactivated S. aureus, the TLR4 ligand LPS, the
   TLR3 ligand poly I:C, the TLR7 ligand imiquimod, the TLR7/8 ligand
   R848, or the tissue damage-related cytokine IL-1α in the presence or
   absence of dexamethasone. The concentrations of IL-1β, IL-6, TNF,
   CXCL10, IL-10, IL-1Ra, and IFN-γ were evaluated in supernatants ([164]
   Figure 5C ). Dexamethasone was unable to significantly reduce the basal
   production of most tested cytokines except for CXCL10. Dexamethasone
   generally diminished IL-1β, IL-6, and IL-1Ra responses to all the
   tested stimuli, and was able to reduce the production of all cytokines
   when stimulated with S. aureus or R848 and IL-1β, IL-6, IL-1Ra, and
   IFN-γ in SARS-CoV-2- and influenza-stimulated cells. TNF, IL-10 and
   CXCL10 were not significantly modulated by dexamethasone in
   SARS-CoV-2-stimulated cells. Taken together, dexamethasone efficiently
   inhibited most cytokine responses in PBMCs isolated from SARS-Cov-2
   infected individuals when exposed to various inflammatory stimuli.

Discussion

   The current study provides insights in the immunomodulatory mechanisms
   of dexamethasone in the context of COVID-19 and suggests that while
   dexamethasone can efficiently abrogate the immune hyperresponsiveness
   observed in hospitalized COVID-19 patients with increasing disease
   severity through the modulation of IFN-related signaling and cytokine
   secretion, the inhibition of IFN responses in early stages of the
   disease could have adverse effects in COVID-19 patients with mild
   symptoms.

   Dysregulation of the IFN pathways is an important determinant of
   COVID-19 severity. A robust early IFN response is crucial to curb the
   progression of SARS-CoV-2 infection. SARS-CoV-2 actively interferes
   with its recognition by innate immune cells and subsequent IFN
   signaling and production ([165]56) and elicits a lower type I IFN
   response compared to other viruses such as influenza ([166]44,
   [167]57). The importance of intact type I and III IFN signaling is
   further illustrated by the observations that patients with inborn
   errors of TLR3 and TLR7 signaling or neutralizing antibodies against
   IFN-α and IFN-ω have an increased risk of developing severe disease
   ([168]58–[169]61). During later phases of the disease, when the viral
   activity has decreased, enhanced IFN signaling predominantly in the
   myeloid compartment contributes to the hyperinflammatory responses that
   characterize severe/critical COVID-19 and correlate with worse outcomes
   ([170]7, [171]44, [172]45, [173]62). Interestingly, glucocorticoids
   have been shown to inhibit components of IFN signaling ([174]63),
   although data from human studies is sparse. One of the underlying
   immunological mechanisms could be that plasmacytoid dendritic cells
   (pDCs) infiltrating the lungs during severe infection prime macrophages
   to become hyperresponsive by inducing pro-inflammatory transcriptional
   and epigenetic changes ([175]64).

   In the present study, we observed a strong modulation of type I and II
   IFN signaling in hospitalized COVID-19 patients treated with
   dexamethasone. In addition, dexamethasone was shown to inhibit
   circulating concentrations of IFN-inducible CXCL10, as wells as the
   production of IFN-α and IFN-γ by PBMCs upon in vitro stimulation with
   SARS-CoV-2. These findings align with a recent study showing
   suppression of IFN signaling by dexamethasone in neutrophils of
   patients with severe COVID-19, with IFITM1, IFIT1 and ISG15 as top
   downregulated genes similar to our data ([176]65).

   In hospitalized COVID-19 patients, ISG15 is among the strongest
   up-regulated genes in immune cells ([177]52, [178]62, [179]66, [180]67)
   as well as in respiratory epithelial cells ([181]68) and appears to be
   an important orchestrator of inflammation. Specifically in SARS-CoV-2
   infection, secreted non-conjugated ISG15 acts as a cytokine that leads
   to sustained exacerbated inflammation ([182]69). Through an increased
   concentration of non-conjugated ISG15 in macrophages, SARS-CoV-2 has
   been shown to induce a pro-inflammatory response that could contribute
   to the excessive proinflammatory cytokine response and related
   immunopathogenesis in severe COVID-19. Furthermore, it has been shown
   in patients, as well as a mouse model of ISG15 deficiency, that
   extracellular ISG15 is critically involved in the production of IFN-γ
   that confers resistance to tuberculosis ([183]70, [184]71).
   Dexamethasone strongly inhibited plasma ISG15 concentration in patients
   with COVID-19, and thus demonstrated the capability of modulating
   cytokines and transcription factors that play a role in the antiviral
   host response but are also linked to cytokine hyperresponsiveness.

   Subsequently, we observed that dexamethasone treatment attenuated
   plasma cytokine concentrations that were previously identified as
   strong independent predictors of disease severity and survival,
   including IL-6, CXCL8, and TNF ([185]6, [186]52). Dexamethasone also
   inhibited the production of mediators associated with increased viral
   load and lung injury, such as CXCL10 and CCL7 ([187]67, [188]72).
   Additionally, dexamethasone could effectively inhibit excessive
   leukocyte recruitment and influx as concentrations of key leukocyte
   chemokines such as CCL2, CXCL8 and CXCL10 were diminished. In contrast
   to the in vivo anti-inflammatory effects of dexamethasone in the
   systemic regulation of TNF, IL-10, and CXCL10, no direct effects were
   observed for these cytokines in ex vivo SARS-CoV-2 stimulated PBMCs,
   pointing out the regulatory role of dexamethasone in pathways induced
   by other inflammatory mediators or the involvement of other cell types.
   Interestingly, in a human model of endotoxin-induced pulmonary
   inflammation dexamethasone strongly inhibited systemic IL-6
   concentrations, yet failed to inhibit local pulmonary IL-6 secretion
   ([189]73). A previous bioinformatic analysis demonstrated that IL-6 is
   not a direct target of dexamethasone treatment in the context of
   COVID-19 ([190]74). Similar to other studies we observed an
   anti-inflammatory systemic effect of IL-6 regulation by dexamethasone
   in COVID-19 ([191]6, [192]12) but dexamethasone has also been shown to
   fail in the inhibition of IL-6, TNF and CXCL10 expression in the lung
   microenvironment ([193]75), pointing out a possible inefficiency of
   regulating local hyperinflammatory response in the lungs.

   Following the landmark RECOVERY trial that demonstrated a reduce in
   28-day mortality in patients receiving supplemental oxygen in 2020
   ([194]11), dexamethasone has been a cornerstone in the treatment of
   severe COVID-19. Subsequent studies have confirmed its beneficial
   effects on ventilator-free days in critically ill patients, but not on
   mortality ([195]12, [196]76, [197]77). Although dexamethasone is known
   to have broad immunosuppressive effects, treatments targeting only
   specific cytokines, such as IL-1 or IL-6 have also been used with
   clinical benefit ([198]27, [199]28, [200]49, [201]50, [202]78). In our
   study, we show in vivo and ex vivo effects of dexamethasone on
   inflammatory pathways that are linked to COVID-19 disease severity,
   both on the transcriptomic and protein level. Dexamethasone decreased
   plasma concentrations of the IL-1 receptor antagonist IL-1Ra after in
   vivo treatment, while ex vivo dexamethasone treatment similarly led to
   downregulation of IL1RN transcripts while upregulating the IL1R2 gene,
   which encodes for a decoy receptor for IL-1. In addition, ex vivo
   dexamethasone treatment downregulated the ACOD1 gene in PBMCs derived
   from both healthy individuals and COVID-19 patients. Expression of
   ACOD1 is specific to the monocyte-macrophage cell lineage and is
   modified through both the glucocorticoid receptor to which
   dexamethasone binds, and the JAK/STAT pathway ([203]79).

   It is currently unclear whether these observations would also extend to
   a decreased incidence of long COVID, which is characterized by
   persistently activated innate and adaptive immune cells, T cell
   exhaustion, as well as elevated levels of circulating cytokines such as
   type I and III IFNs ([204]80, [205]81). A recent preprint study has
   observed that prior treatment with dexamethasone decreased persistent
   symptoms in hospitalized COVID-19 after 8 months of follow-up compared
   to a non-treated control group ([206]82). It would therefore be of
   interest for further studies to interrogate whether dexamethasone
   treatment in patients with moderate-to-severe COVID-19 could limit the
   post-acute immunological sequelae observed in long COVID-19.

   Despite the proven efficacy of dexamethasone in lowering mortality
   predominantly in severe or critical COVID-19 patients, a large
   observational cohort study has demonstrated that dexamethasone
   treatment had no mortality benefit on those receiving supplemental
   oxygen via low-flow nasal cannula in the first 48 hours, while it
   increased mortality in patients not receiving oxygen ([207]13).
   Moreover, dexamethasone has treatment-related adverse events, including
   hyperglycemia, cardiovascular events, and bacterial superinfections
   ([208]83, [209]84). These observations call for awareness of the
   risk-to-benefit ratio in initiating dexamethasone treatment in
   COVID-19. While dexamethasone is capable of reducing mortality risk
   when there is underlying inflammatory hyperresponsiveness, treatment
   could prove detrimental if started too early during the viral
   replication phase and when inflammation is not the predominant feature
   of the disease. The correct timing for corticosteroid treatment has
   also been a debated topic in other severe respiratory infectious
   diseases ([210]85, [211]86). These findings underline the importance of
   patient selection and timing when initiating dexamethasone treatment in
   COVID-19 patients, while prompting the need for a deeper understanding
   of the molecular and cellular mechanisms underlying both its beneficial
   and detrimental effects.

   This study has several limitations. First, the sample size of our
   patient cohort was relatively small. Still, we believe the results
   point to a set of consistent mechanisms. Second, our study lacked a
   control group for the in vivo experiments, since dexamethasone
   treatment was standard of care when this study was conducted and we
   could not ethically withhold an effective treatment from hospitalized
   COVID-19 patients. Therefore, we could not exactly distinguish whether
   changes observed before and after dexamethasone treatment of
   hospitalized patients were attributable solely to the immunomodulatory
   effects of dexamethasone itself and to what extent the natural clinical
   course of COVID-19 contributed. Additionally, even though healthy
   donors did not have COVID-19 symptoms and no proinflammatory phenotypes
   were observed at the molecular level, we cannot rule out the
   possibility of an asymptomatic infection since they were not tested for
   SARS-CoV-2 negativity with a RT-PCR test. Despite these limitations, we
   observed significant and biologically relevant results in the
   inflammatory proteome and transcriptome of patients before and after in
   vivo dexamethasone treatment and support the role of dexamethasone in
   these observed effects with in vitro experimental data.

   Collectively, the current findings represent a molecular basis to
   support the notion of dexamethasone treatment to attenuate the
   inflammatory hyperresponsiveness underlying clinical disease in
   moderate to severe COVID-19 patients, while its detrimental effects
   mechanisms that are key to controlling viral replication call for
   caution when considering the treatment of mild COVID-19 patients or at
   an early stage of the disease.

Data availability statement

   The datasets presented in this study can be found in online
   repositories. The repository is publicly accessible and can be found
   through accession number [212]GSE227585 or via this link:
   [213]https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE227585.

Ethics statement

   The studies involving human participants were reviewed and approved by
   CMO Radboudumc en METC Oost-Nederland and the National Ethics Committee
   of Greece. Written informed consent for participation was not required
   for this study in accordance with the national legislation and the
   institutional requirements.

Author contributions

   Conceptualization: FV, MN, AZ. Data curation: JE, CM, NK, VK, AZ.
   Formal analysis: JE, CM, NK, VK, AZ. Funding acquisition: VK, FV, MN.
   Investigation: JE, CM, TS, RR, GD, HD, HL, AZ. Methodology: JE, CM, NK,
   VK, AZ. Project administration: AZ. Resources: JE, CM, SI, GP, EG-B,
   MN, AZ. Software: NK, VK. Supervision: FV, MN, AZ. Validation: FV, MN,
   AZ. Visualization: JE, CM, NK, AZ. Writing – Original draft
   preparation: JE, CM, AZ. Writing – Review & editing: All authors. All
   authors contributed to the article and approved the submitted version.

Acknowledgments