Cytokine Storm—Definition, Causes, and Implications
Abstract
:1. Introduction
2. Pathophysiology of CS
3. Inflammation Due to Sepsis
4. Unleashing the Cytokine Cascade
4.1. Sepsis
4.2. Post-Cardiac Arrest Syndrome
4.3. Endotoxin
4.4. Post-Splenectomy Syndrome
4.5. Invasive Meningococcal Disease (IMD)
4.6. Viral and Parasitic Infections
4.7. Sterile Inflammation and Iatrogenic CS
5. After the Storm
6. Viral- vs. Non-Viral-Induced CS
7. Age-Related Changes of the Immune System
8. Endotypes, GWAS, and Transcriptome Analysis
9. Future Perspectives
- (a)
- Preclinical models for both basic and translational research need to be improved; current animal models do not adequately represent inflammation. New models are needed to comprehensively represent the complex processes and numerous feedback loops and redundant pathways should be considered. The individual reactions of the components of the immune system within different compartments need to be further elucidated. Local microenvironments with different molecular and cellular characteristics can result in different polarizations of the immune response in different tissues and organs as mentioned above. It has been shown that the ex vivo phenotype of leukocytes is strongly dependent on their compartment of origin. Blood leukocytes may show limited proliferation and secretion capacity, with reduced expression of HLA-DR mRNA in monocytes, while recruited monocytes in the lungs express greater than threefold more HLA-DR on their membrane [208,209]. Further, lung, spleen, and peritoneal macrophages have disparate transcriptomes and cell surface marker expression [210];
- (b)
- Development of a personalized approach combining clinical phenotypes, endotypes, and biomarkers, deciphered through the combination of “-omics” technologies and artificial intelligence (AI), is needed.
- (c)
- Further, there is a significant need for diagnostic testing procedures that can quickly and reliably help differentiate, for example, between bacterial and viral bases and, thus, possibly guide the use of anti-infectives and ultimately counteract the development of resistance. The current routine involves culture, isolation, and identification of pathogens from patient material—a time-consuming and not necessarily successful process. Contamination, mixed cultures, and unsuccessful cultivation are common risks. In addition, depending on the (presumed) focus, obtaining appropriate samples is not always without risk (intrapulmonary, cerebrospinal fluid). Although detection and cultivation conditions are constantly being developed, the method of direct detection, e.g., by PCR or immunoassays, also has limitations—previously unknown variants may evade detection and the method cannot reliably distinguish between already dysfunctional/dead pathogens and inflammatory-active material [216,217]. Further research and an increased understanding of the interrelationships between what has been considered viral and bacterial defense cascades may lead to further blurring of the boundaries and to therapeutic options in which the exact origin of inflammation may turn out to be less relevant [218,219].
10. Summary
- We support the comprehensive and clinical definition of CS that was recently suggested by Fajgenbaum and June [5]:
- (i)
- Elevated circulating cytokine levels;
- (ii)
- Acute systemic inflammatory symptoms;
- (iii)
- Severe secondary organ dysfunction.
- In CS, both excessive hyperinflammation and uncontrolled anti-inflammation occur simultaneously. Survivors of the initial phase often develop acquired immunosuppression, which is an additional risk factor for unfavorable outcomes and long-term morbidity;
- A wide array of infectious and non-infectious disease may cause CS; the most common cause is sepsis due to invasive microbial infection;
- The biomarker signature profiles of different types of CS are rather distinct. However, to use these signatures to diagnose the origin of CS is currently not yet feasible;
- CS characteristics differ between different compartments (blood, CSF, pleural effusion, lung tissue, etc.) In clinical routine, the blood compartment is almost exclusively used for analysis; this may lead to wrong conclusions and misconceptions of the underlying pathophysiology;
- The earliest possible detection of CS is of outstanding importance, as this may be related to therapeutic decisions and, ultimately, prognosis and outcome;
- Transcriptome analysis and GWAS represent promising opportunities for future development. These techniques enable improved knowledge of different phenotypes and may help to implement “precision medicine”, very similar to what is already done in modern oncology.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
AI | artificial intelligence |
ALL | acute lymphocytic leukemia |
AP-1 | activator protein-1 |
APC | antigen-presenting cell |
ARDS | acute respiratory distress syndrome |
BBB | blood–brain barrier |
CAM | cell adhesion molecule |
CARS | compensatory anti-inflammatory response syndrome |
CAR-T cell | chimeric antigen receptor-T cell |
CMV | cytomegalovirus |
COVID-19 | coronavirus disease 2019 |
CRP | C-reactive protein |
CRS | cytokine release syndrome |
CS | cytokine storm |
DAMP | damage-associated molecular pattern |
DIC | disseminated intravascular coagulation |
DNA | deoxyribonucleic acid |
EBV | Epstein–Barr virus |
fHbp | factor H-binding protein |
GWAS | genome-wide association studies |
GvHD | graft-versus-host disease |
HLA-DR | human leukocyte antigen-DR |
HLH | hemophagocytic lymphohistiocytosis |
ICU | intensive care unit |
IHCA | in-hospital cardiac arrest |
IFN | interferon |
IL | interleukin |
IMD | invasive meningococcal disease |
ISG | interferon-stimulated gene |
ISTH | International Society on Thrombosis and Haemostasis |
JAK | Janus kinase |
LOS | lipooligosaccharide |
LPS | lipopolysaccharide |
MAS | macrophage activation syndrome |
MDSC | myeloid-derived suppressor cell |
MHC II | major histocompatibility complex II |
MIF | migration inhibitory factor |
NET | neutrophil extracellular traps |
NHL | non-Hodgkin lymphoma |
NF-κ | nuclear factor kappa-light-chain-enhancer |
NK cell | natural killer cell |
OHCA | out-of-hospital cardiac arrest |
OPSI | overwhelming post-splenectomy infection |
PAMP | pathogen-associated molecular pattern |
PCAS | post-cardiac arrest syndrome |
PCI | persistent critical illness |
PCT | procalcitonin |
PICS | persistent inflammation, immunosuppression, and catabolism |
PRR | pattern recognition receptors |
PT-INR | prothrombin time-International Normalized Ratio |
ROSC | return of spontaneous circulation |
SARS-CoV-2 | severe acute respiratory syndrome coronavirus type 2 |
SIC | sepsis-induced coagulopathy |
SIRS | systemic inflammatory response syndrome |
STAT | signal transducer and activator of transcription |
T4P | type IV pili |
TF | tissue factor |
TFPI | tissue factor pathway inhibitor |
TGF-β | transforming growth factor β |
TIR | Toll–interleukin-1 receptor domain |
TLR | Toll-like receptor |
TNF | tumor necrosis factor |
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Mediator (Abbreviation) | Main Source | Major Function | |
---|---|---|---|
Cytokines | |||
IL-1 | macrophages, pyroptotic cells, epithelial cells | Proinflammatory; pyrogenic function; activation of macrophage and TH17 cells | |
IL-2 | T cells | Immune response; Teff and Treg cell growth factor; T-cell differentiation | |
IL-4 | TH2 cells, basophils, eosinophils, mast cells, NK cells | Anti-inflammatory; TH2 differentiation; adhesion; chemotaxis | |
IL-6 | T cells, macrophages, endothelial cells | Proinflammatory; pleiotropic; pyrogenic function; acute phase response; lymphoid differentiation; increased antibody production, | |
IL-9 | TH9 cells | Pleiotropic; stimulation of B, T, and NK cells; protection from helminth infections; activation of mast cells; association with type I interferon in COVID-19 | |
IL-10 | regulatory T cells, TH9 cells | Anti-inflammatory; inhibition of macrophage activation; inhibition of TH1 cells and cytokine release | |
IL-12 | dendritic cells, macrophages | Stimulation of T and NK cells; activation of TH1 pathway; induction of interferon-γ from TH1 cells; cytotoxic T cells and NK cells; acting in synergy with interleukin-18 | |
IL-13 | TH2 cells | Anti-inflammatory; differentiation of B cells; mediator of humoral immunity | |
IL-17 | TH17 cells, NK cells, group 3 innate lymphoid cells | Protection from bacterial and fungal infections; promotion of neutrophilic inflammation | |
IL-18 | monocytes, macrophages, dendritic cells | Proinflammatory; activation of TH1 pathway; synergistic with interleukin-12 | |
IL-31 | TH2 cells, macrophages, mast cells, dendritic cells | Proinflammatory; cell-mediated immunity | |
IL-33 | macrophages, dendritic cells, mast cells, epithelial cells | Proinflammatory; amplification of TH1 and TH2 cells; activation of cytotoxic T cells, NK cells, and mast cells | |
Type I Interferon | virtually all body cells | Dendritic cell activation/maturation/migration/survival; enhancement of the activity of NK and T/B cells; induction of antiviral effector molecules; antagonism to the action of interferon-γ | |
Interferon-γ(Type II IFN) | TH1 cells, cytotoxic T cells, group 1 innate lymphoid cells, NK cells | Proinflammatory; activation of monocytes and macrophages | |
Lymphotoxin α | activated lymphocytes | Pleiotropic; activation of NF-κB pathway | |
TGF-β | Treg cells, monocytes, macrophages, fibroblasts, epithelial cells, cancer cells | Immunosuppressive; regulation of proliferation, differentiation, apoptosis, and adhesion; inhibition of hematopoiesis | |
Tumor necrosis factor | T cells, NK cells, mast cells, macrophages | Pyrogenic; increasing vascular permeability | |
Chemokines | |||
MCP-1 | CCL2 | macrophages, dendritic cells, cardiac myocytes | Pyrogenic; recruitment of TH1 cells, NK cells, macrophages, eosinophils, and dendritic cells |
MIP-1α | CCL3 | monocytes, neutrophils, dendritic cells, NK cells, mast cells | Recruitment of TH1 cells, NK cells, macrophages, and dendritic cells |
MIP-1β | CCL4 | macrophages, neutrophils, endothelium | Recruitment of B cells, CD4+ T cells, and dendritic cells |
IL-8 | CXCL8 | macrophages, epithelial cells | Recruitment of neutrophils |
MIG | CXCL9 | monocytes, endothelial cells, keratinocytes | Interferon-inducible chemokine; recruitment of TH1 cells, NK cells, and plasmacytoid dendritic cells |
IP-10 | CXCL10 | monocytes, endothelial cells, keratinocytes | Interferon-inducible chemokine; recruitment of TH1 cells, NK cells, and macrophages |
BLC | CXCL13 | B cells, follicular dendritic cells | Recruitment of TH1 cells, monocytes, dendritic cells, and basophils |
Plasma proteins | |||
CRP | hepatocytes | Interleukin-6 increases CRP expression, interleukin-8 and MCP-1 secretion; | |
Complement | hepatocytes, other cells | In cytokine storm, activation of complement contributes to tissue damage, inhibition may reduce immunopathologic effects |
Study | Number of Patients | Diagnosis/Prediction | Commonly Used Markers/Comparators | New Biomarkers | Variables | AUC |
---|---|---|---|---|---|---|
Kweon et al. [11] | n = 118 (73 sepsis; 45 SIRS or healthy controls) | Sepsis | PCT IL-6 | sCD14-ST (Presepsin) | sCD14-ST PCT IL-6 hs-CRP | 0.937 0.915 0.869 0.853 |
Lu et al. [12] | 115 patients (72 sepsis; 43 SIRS or healthy controls) | Sepsis | PCT CRP | sCD14-ST (Presepsin) | sCD14-ST PCT CRP | 0.954 0.847 0.859 |
Aksaray et al. [13] | n = 90 (52 sepsis; 38 SIRS) | Differentiation Sepsis–SIRS | PCT APACHE II | sTREM-1 | sTREM-1 PCT APACHE II | 0.78 0.65 0.71 |
Brenner et al. [14] | n = 90 (60 septic shock; 30 healthy controls) | Septic shock | PCT IL-6 CRP | sTREM-1 | sTREM-1 IL-6 PCT CRP | 0.955 0.898 0.844 0.791 |
Khater et al. [15] | n = 80 (40 sepsis; 40 healthy controls) | Sepsis | Lactate | suPAR | suPAR Lactate | 0.99 0.84 |
Yin et al. [16] | n = 171 (151 sepsis; 20 healthy controls) | Sepsis | PCT CRP SOFA | CD64 | CD64 PCT SOFA CRP | 0.879 0.868 0.701 0.609 |
Larsson et al. [17] | n = 271 (77 sepsis; 194 non-sepsis) | Sepsis | PCT | Calprotectin | CaPT PCT | 0.67 0.55 |
Spoto et al. [18] | n = 159 (109 sepsis; 50 healthy controls) | Sepsis | PCT SOFA | MR-proADM | MR-proADM PCT SOFA | 0.817 0.884 0.774 |
Hamed et al. [19] | n = 290 (213 sepsis; 77 healthy controls) | Sepsis | PCT IL-6 CRP | PTX-3 | PTX-3 PCT IL-6 CRP | 0.92 0.92 0.91 0.82 |
Casagranda et al. [20] | n = 130 (Sepsis) | 28-day mortality | Lactate | suPAR | suPAR Lactate | 0.77 0.70 |
Chen et al. [21] | n = 66 (25 septic shock; 11 sepsis; 30 healthy controls) | 28-day mortality | APACHE II | HMGB-1 | HMGB-1 IL-10 APACHE II | 0.946 0.877 0.846 |
Andaluz-Ojeda et al. [22] | n = 326 (Sepsis) | 28-day mortality | PCT CRP Lactate SOFA | MR-proADM | MR-proADM SOFA Lactate PCT CRP | 0.79 0.75 0.71 0.61 0.54 |
Kim H et al. [23] | n = 215 (Sepsis) | 30-day mortality | SOFA | Bio-ADM | Bio-ADM SOFA | 0.827 0.830 |
Seol et al. [24] | n = 145 (Sepsis) | 28-day mortality | SOFA | Angiopoietin | SOFA Angpt2/1 ratio | 0.745 0.736 |
Fang et al. [25] | n = 388 (333 sepsis; 55 healthy controls) | 28-day mortality | PCT | Angiopoietin | Angpt2/1 ratio PCT | 0.845 0.732 |
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Jarczak, D.; Nierhaus, A. Cytokine Storm—Definition, Causes, and Implications. Int. J. Mol. Sci. 2022, 23, 11740. https://doi.org/10.3390/ijms231911740
Jarczak D, Nierhaus A. Cytokine Storm—Definition, Causes, and Implications. International Journal of Molecular Sciences. 2022; 23(19):11740. https://doi.org/10.3390/ijms231911740
Chicago/Turabian StyleJarczak, Dominik, and Axel Nierhaus. 2022. "Cytokine Storm—Definition, Causes, and Implications" International Journal of Molecular Sciences 23, no. 19: 11740. https://doi.org/10.3390/ijms231911740
APA StyleJarczak, D., & Nierhaus, A. (2022). Cytokine Storm—Definition, Causes, and Implications. International Journal of Molecular Sciences, 23(19), 11740. https://doi.org/10.3390/ijms231911740