Open Access

Thrombocytopenia in COVID‑19 and vaccine‑induced thrombotic thrombocytopenia

  • Authors:
    • Styliani A. Geronikolou
    • Işil Takan
    • Athanasia Pavlopoulou
    • Marina Mantzourani
    • George P. Chrousos
  • View Affiliations

  • Published online on: January 21, 2022
  • Article Number: 35
  • Copyright: © Geronikolou et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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The highly heterogeneous symptomatology and unpredictable progress of COVID‑19 triggered unprecedented intensive biomedical research and a number of clinical research projects. Although the pathophysiology of the disease is being progressively clarified, its complexity remains vast. Moreover, some extremely infrequent cases of thrombotic thrombocytopenia following vaccination against SARS‑CoV‑2 infection have been observed. The present study aimed to map the signaling pathways of thrombocytopenia implicated in COVID‑19, as well as in vaccine‑induced thrombotic thrombocytopenia (VITT). The biomedical literature database, MEDLINE/PubMed, was thoroughly searched using artificial intelligence techniques for the semantic relations among the top 50 similar words (>0.9) implicated in COVID‑19‑mediated human infection or VITT. Additionally, STRING, a database of primary and predicted associations among genes and proteins (collected from diverse resources, such as documented pathway knowledge, high‑throughput experimental studies, cross‑species extrapolated information, automated text mining results, computationally predicted interactions, etc.), was employed, with the confidence threshold set at 0.7. In addition, two interactomes were constructed: i) A network including 119 and 56 nodes relevant to COVID‑19 and thrombocytopenia, respectively; and ii) a second network containing 60 nodes relevant to VITT. Although thrombocytopenia is a dominant morbidity in both entities, three nodes were observed that corresponded to genes (AURKA, CD46 and CD19) expressed only in VITT, whilst ADAM10, CDC20, SHC1 and STXBP2 are silenced in VITT, but are commonly expressed in both COVID‑19 and thrombocytopenia. The calculated average node degree was immense (11.9 in COVID‑19 and 6.43 in VITT), illustrating the complexity of COVID‑19 and VITT pathologies and confirming the importance of cytokines, as well as of pathways activated following hypoxic events. In addition, PYCARD, NLP3 and P2RX7 are key potential therapeutic targets for all three morbid entities, meriting further research. This interactome was based on wild‑type genes, revealing the predisposition of the body to hypoxia‑induced thrombosis, leading to the acute COVID‑19 phenotype, the ‘long‑COVID syndrome’, and/or VITT. Thus, common nodes appear to be key players in illness prevention, progression and treatment.


The current SARS-CoV-2-induced pandemic has raised a number of public health policy and scientific queries, related to the virus origin, transmission, activity, contamination, pathophysiologic effects and treatment. As of May 3, 2021, almost 188 million cases had been confirmed, while 4.05 million deaths had been registered under the cause of death: 'COVID-19'. Although this may underline an apogee of the third phase of the pandemic in some countries, or may have been the result of certain interventions. Public health policy approaches, communication campaigns, pharmacological approaches, surveillance, and prevention practices have been suggested.

The highly varying symptomatology and the unpredictable global progress of COVID-19 have triggered an unprecedentedly intensive activity in biomedical research and public policy decisions. Furthermore, although the pathophysiology of the disease is being progressively clarified, its complexity remains vast, and preventive care approaches or treatments, although both have significantly improved, remain unsatisfactory.

Notably, the extremely rare yet highly unpredictable and occasionally lethal vaccination-induced thrombotic thrombocytopenia (VITT) syndrome has emphasized the gaps in the current knowledge of certain unsuspected pathophysiological pathways. The VITT morbid entity is of particular importance given the generally mild and to a certain extent expected vaccination side-effects, namely chills, fever, diarrhea, fatigue, muscle pain, headache and mildly increased blood coagulability (1,2). As of April 2021, 16 vaccination options were available: Two RNA vaccines [BNT162b2 (Comirnaty) by Pfizer-BioNTech, mRNA.1273 (Spikevax) by Moderna], seven conventional inactivated ones (CoronaVac, Covaxin, BBIBP-CorV, WIBP-CorV, Minhai-Kangtai, QazVac, CovIran Bakerat), five viral vector-employing ones (Covishield and Vaxzevria by Oxford Astra-Zeneca, the Janssen COVID-19 vaccine by Johnson & Johnson, the Sputnik V and Sputnik Light by the Gamaleya Research Institute of Epidemiology and Microbiology in Russia, and the AD5-nCOV-Convidencia by CanSino Biologics Inc.), and two protein subunit vaccines (EpiVacCorona and RDB-dimer). Vaccination programs have been implemented so as to reach 'herd immunity', in every country. According to national health authority reports, as of August 30, 2021, 5.27 billion doses had been administered globally. This is equal to 39.7% of the population on the planet (where, however, only 1.6% of individuals in the low-income countries had received at least one dose), having been fully vaccinated (3). As of August 30, 2021, 55.15% of the Greek population had been fully vaccinated (3).

The aim of the present study was to illustrate the signaling pathways implicated in SARS-CoV-2 infection, including those of the extremely rare, yet severe VITT syndrome.

Data and methods

The scientific literature database, MEDLINE/PubMed (, was searched thoroughly for genes or gene products implicated in COVID-19 infection and VITT syndrome. Searches were conducted in the PubTator article collection (4) ( from the LitCovid database (5), using i) ('COVID19' OR 'SARS-CoV-2') AND ('VITT' OR 'vaccine-induced thrombotic thrombocytopenia'); ii) ('COVID19' OR 'SARS-CoV-2') AND ('thrombocytopenia' OR 'thrombopenia') key words to obtain relevant articles. Of the 495 candidate articles, 190 met the inclusion criteria which were as follows: i) written in English; ii) include an abstract; and iii) contain adequate information in their text for processing (Fig. 1).

The natural language toolkit (NLTK:, a freely accessible Python platform, was used for text processing, including tokenization, parsing and stemming. Word2vec embeddings module in the open-source Python library Gensim ( was implemented to train word vectors of processed text. A list of all word-to-word distances was extracted. To calculate the similarity distances between each word pair, the Word2Vec.most_similar function in Gensim Word2vec model was used. The top 50 detected entries were included in the present study. The work flow is presented in Fig. 1. The search results are illustrated in Fig. 2.

Furthermore, the interactions among the retrieved genes/proteins were investigated by employing the Search Tool for Retrieval of Interacting Genes/Proteins (STRING) database v11.0 (6,7), a database containing both primary and predicted, physical and functional association data among genes or proteins. These data are collected from diverse resources, such as documented pathway knowledge, high-throughput experimental studies, cross-species extrapolated information, automated text mining results, computationally predicted interactions, etc. The confidence threshold value for displaying interactions was set to 'high' (i.e., 0.7). The interactions in the generated network were manipulated and visualized through Cytoscape ( (8), a software platform for network processing and statistical analyses; the Edge Betweenness mode was used to detect the number of the shortest paths that pass-through a given edge in the COVID-19 network.


Main findings

The constructed networks presented in Fig. 2 provide noteworthy information on how diverse terms are closely interlinked within the context of thrombocytopenia induced by SARS-CoV-2 infection or through vaccination. The term thrombocytopenia appears with a rather high frequency in the COVID-19/VITT network (Fig. 2A). Similarly, the term VITT is included in the COVID-19/thrombocytopenia network (Fig. 2B). COVID-19 and VITT share several comorbidities implicating vascular and epithelial dysfunction and thrombocytopenia. The nodes represent the top 50 words with a cosine similarity score of each word vector >0.9.

Interactome construction

Subsequently, two interactomes were constructed: The first one involving 119 nodes is described in Table I and illustrated in Fig. 3. Collectively, 119 nodes are involved in COVID-19, while 57 are implicated in thrombocytopenia [the latter profits from an unpublished work of ours (unpublished data). Of these, 14 nodes were common in both entities (Figs. 3 and 4), namely AIM2, IFI16, NOD2, CD8A, IL-1B, 1L-6, JAK2, NCAM1, HLA-DRB1, SERPINE1, TGFB1, TLR2, TNF and VWF. The major hubs detected are displayed in the center of the constructed circular network, while the less connected nodes are shown at the periphery of the circle (Fig. 3). The thrombocytopenia-related nodes are represented in square bullets, and the COVID-19-related ones are presented in circles, whilst the common nodes are depicted in rhomboids. The calculated average node degree of the entire interactome was extremely high (11.9).

Table I

Genes included in the molecular networks depicted in Figs. 3 and 4.

Table I

Genes included in the molecular networks depicted in Figs. 3 and 4.

Gene symbolGene nameMain function with brief description (Refs.)Figure(s)Entitya
ACE2Angiotensin I converting enzyme 2Transmembrane protein-entry point of SARS-CoV-2 (22-24,28)3C
ADAM10ADAM metallopeptidase domain 10Sheddase with strong specificity for peptide hydrolysis reactions (68-70)3T
ADAM17ADAM metallopeptidase domain 17Sheddase triggering release of cytokines receptors, ligands, etc. (68,69,71)3,4V, T
ADAMTS13ADAM metallopeptidase with throm bospondin type 1 motif 13Enzyme that cleaves von Willebrand factor (68,69)3,4V, T
ADRA2CAdrenoceptor alpha 2CMediators in catecholamine-induced inhibition of adenylate cyclase through the action of G proteins (72)3C
ADRB1Adrenoceptor beta 1Renin release/lipolysis/Increases heart rate with chrono/inotropic effect (73)3C
ADRB2Adrenoceptor beta 2Facilitating respiration (74)3C
AGERAdvanced glycosylation end-product specific receptorMediates interactions of advanced glycosylation end products (75)3C
AIM2 Interferon-inducible protein AIM2AIM2 inflammasome plays a crucial role in the defense against viral infection (76)3C, T
ANGPT1Angiopoietin 1Receptor of advanced glycosylation end products of proteins, mediating amyloid beta peptide effect on neurons and microglia (77)3C
ANGPT2Angiopoietin 2Binds to TEK/TIE2, competing for the ANGPT1 binding site, and modulating ANGPT1 signaling (78)3C
AURKA Serine/threonine-protein kinase 6Orchestrate an exit from mitosis by contributing to the completion of cytokinesis the process through which the cytoplasm of the parent cell is split into two daughter cells (79)4V
C4BComplement C4B (Chido blood group)Mediator of local inflammatory process, inducing the contraction of smooth muscle, increasing vascular permeability and causing histamine release from mast cells and basophilic leukocytes (80)3,4V, T
C5Complement C5Involved in the complement system (81)3,4V, T
C6Complement C6Causes cell lysis (82)3,4V, T
C7Complement C7Creates a hole on pathogen surfaces leading to cell lysis (82)3,4V, T
C9Complement C9Cell lysis and death contributor (82)3,4V, T
CASP1Caspase 1Inflammatory response initiator (83)3,4C, V
CASP10Caspase 10Cell apoptosis (84)3C
CASP9Caspase 9Innate immunity, mitochondrial apoptosis (85)3C
CCL2C-C motif chemokine ligand 2Induces a strong chemotactic response and mobilization of intracellular calcium ions (86,87)3C
CCL3Chemokine (C-C motif) ligand 3Pyrogenic, attracting macrophages, monocytes and neutrophils (88)3C
CCN2Cellular communication network factor 2Cell adhesion, apoptosis, migration, proliferation, differentiation, apoptosis, survival and senescence (89)3C
CD3DCD3d moleculeCell differentiation and adaptive immune response (90)3C
CD3ECD3e moleculeCell differentiation and adaptive immune response (90)3C
CD3GCD3g moleculeCell differentiation and adaptive immune response (90)3C
CD4CD4 moleculeCell differentiation and adaptive immune response (91)3C
CD40LGCD40 ligandActs as a ligand for integrins which have cell-type dependent effects, such as B-cell activation, NF-κB signaling and anti-apoptotic signaling (92,93)3T
CD8ACD8a moleculeMultiple functions in responses against both ex/internal offenses (91)3C, T
CD19B-lymphocyte antigen CD19Decreases B-cell receptor pathways (94,95)4V
CD40LGCluster of differentiation 40Mediates many immune and inflammatory responses including T-cell-dependent immunoglobulin class switching, memory B cell development, and germinal center formation (96)3,4T, V
CD46CD46 complement regulatory proteinActivates T-lymphocytes following vaccination (97,98)4V
CDC20Cell division cycle 20Regulates the formation of synaptic vesicle clustering at active zone to the presynaptic membrane in post-mitotic neurons; Cdc20-apc/ c-induced degradation of neurod2 induces presynaptic differentiation (91)3,4V, T
CDCA3Cell division cycle associated 3Involves in protein ubiquitination (99)3,4V, T
CRPC-reactive proteinMitotic initiator (100)3C
CSF1RColony stimulating factor 1 receptorControls the production, differentiation, and function macrophages (93,101)3,4V, T
CSF2Colony stimulating factor 2Cytokine affecting mostly eosinophils and macrophages (102)3,4V, T
CXCL10C-X-C motif chemokine ligand 10Chemoattraction for T- and NK cells, monocytes (87,93,103,104)3C
CXCL8C-X-C motif chemokine ligand 8Neutrophil chemotactic factor increasing respiratory burst (87,105)3,4C, V
CYP11B2Cytochrome P450 family 11 subfamily B member 2Aldosterone synthesis (87,106)3C
CYP2C19Cytochrome P450 family 2 subfamily C member 19Part of cytochrome P450, involved in drug and lipid metabolism (107)3 C
CYP2C9Cytochrome P450 family 2 subfamily C member 9Part of cytochrome P450, involved in drug and lipid metabolism (107)3 C
DDX58Retinoic acid-inducible gene IActivates interferon and cytokines production after viral infection (108)3C
EDN1Endothelin 1Potent vasoconstrictor (106,109)3C
EPOErythropoietinStimulation of erythropoiesis, vasoconstriction, angiogenesis (106)3,4V, T
F2Coagulation factor II, thrombinActivates the coagulation cascade inhibition (110)3,4V, T
FCGR1AFc fragment of IgG receptor IaComplex activation or inhibitory effects on cell functions (111)3,4V, T
FCGR1BFc fragment of IgG receptor IbHumoral immune response (112)3,4V, T
FCGR2AFc fragment of IgG receptor IIaHumoral immune response to pathogens, phagocytosis of opsonized antigens (113)3,4V, T
FCGR2BFc fragment of IgG receptor IIbPhagocytosis of immune complexes and regulation of antibody production (114)3,4V, T
FCGR3AFc fragment of IgG receptor IIIaMediates antibody-dependent cellular cytotoxicity and phagocytosis (115)3,4V, T
FCGR3BFc fragment of IgG receptor IIIbCaptures immune complexes in the peripheral circulation (116)3,4V, T
FGF7Fibroblast growth factor 7Cell growth, morphogenesis and tissue repair (117)3,4C, V
FKBP1AFKBP prolyl isomerase 1AImmunoregulation and basic cellular processes involving protein folding and trafficking (118)3,4V, T
FN1Fibronectin 1Cell growth, morphogenesis and tissue repair (70)3C
FOSFos proto-oncogene, AP-1 transcription factor subunitSignal transduction, cell proliferation and differentiation (119)3C
GNB3G protein subunit beta 3Integrates signals between receptor and effector proteins (120)3C
GZMAGranzyme ACommon component necessary for lysis of target cells by cytotoxic T-lymphocytes and natural killer cells (24)3C
GZMBGranzyme BRecognize specific infected target cells (121)3C
GZMHGranzyme HSuppresses viral replication (122)3C
HLA-AMajor histocompatibility complex, class I, ASole link between the immune system and what happens inside cells (123)3,4C, V
HLA-BMajor histocompatibility complex, class I, BHelps the immune system distinguish the endo-from exogenous proteins (123)3,4C, V
HLA-DRB1HLA class II histocompatibility antigen, DRB1 beta chainTriggers response to viral infections (41)3,4C, V, T
ICAM1Intercellular adhesion molecule 1Signal transduction (92,93)3,4V, T
IFI16Interferon gamma inducible protein 16Recognizes RNA viral infection, enhancing DDX58 production (124)3C, T
IFNA1Interferon alpha 1Antiviral and immunomodulator (125)3C
IFNG (IFN-γ)Interferon gammaAntiviral antibacterial and immunomodulatory effects (104)3,4V, T
IFNL1Interferon lambda 1Antiviral antibacterial and immunomodulatory effects (126)3C
IFNL2Interferon lambda 2Antiviral antibacterial and immunomodulatory effects (126)3C
IFNL3Interferon lambda 3Antiviral antibacterial and immunomodulatory effects (126)3C
IFNLR1Interferon lambda receptor 1Antiviral antibacterial and immunomodulatory effects (126)3C
IKBKGInhibitor of nuclear factor kappa B kinase regulatory subunit gammaAntiviral activity through JAK/STAT signaling activation (127)3C
IL10Interleukin 10Multiple, pleiotropic effects in immunoregulation, limits excessive infected tissue disruption (92)3C
IL10RBInterleukin 10 receptor subunit betaJAK1 and STAT2-mediated phosphorylation of STAT3 (128)3C
IL12AInterleukin 12AInduces IFNG (92)3C
IL12BInterleukin 12BInduces IFNG by resting PBMC (92)3C
IL17AInterleukin 17AMediates protective innate immunity to pathogens or contributes to pathogenesis of inflammatory diseases (87)3C
IL18Interleukin 18Potent inducer of inflammatory cytokines, especially IFNG (129)3C
IL1AInterleukin 1 alphaPromotion of intimal inflammation, fever, sepsis and atherogenesis (41)3C
IL1BInterleukin 1 betaPromotion of fever, development of diabetes mellitus, apoptosis of pancreatic β-cells (87,105)3,4C, V, T
IL1RAPInterleukin 1 receptor accessory proteinInduces synthesis of acute phase and proinflammatory proteins during infection, tissue damage, or stress (130)3C
IL3Interleukin 3Growth and differentiation of hematopoietic progenitor cells regulator and functional activator of mature neutrophils or macrophages (131)3,4V, T
IL33Interleukin 33Gene transcription regulator, released after cell necrosis triggering immune response and stress (132)3C
IL36GInterleukin 36 gammaInflammasome dependent, involved in systemic inflammation (133)3C
IL4Interleukin 4Hematopoiesis, antibody production, inflammation response (117)3,4V, T
IL5Interleukin 5Eosinophil migration, activation survival (134)3,4V, T
IL6Interleukin 6Innate and adaptive immune response to infections (135)3,4C, V, T
INSInsulinBlood sugar regulator (136)3C
ITGA2BIntegrin subunit alpha 2bCoagulation (137,138)3,4V, T
JAK1Janus kinase 1Cell growth survival, development differentiation of various cell types (139)3C
JAK2Janus kinase 2Cell growth and proliferation (139)3C, T
JUNJun proto-oncogene, AP-1 transcription factor subunitGene expression regulator (92)3C
KCNE1Potassium voltage-gated channel subfamily E regulatory subunit 1Potassium channels regulator (140,141)3C
KCNH2Potassium voltage-gated channel subfamily H member 2Electrical signals transmission (141)3C
KCNJ2Potassium inwardly rectifying channel subfamily J member 2Muscle movement (heart or skeletal) (142)3C
KCNQ1Potassium voltage-gated channel subfamily Q member 1Electrical signals generation and transmission (143)3C
LCN2Lipocalin 2Sequesters iron and preventing its use by bacteria, thus limiting their growth (144)3C
MMP1Matrix metallopeptidase 1Degrades collagen type I and II (145,146)3C
MMP2Matrix metallopeptidase 2Extracellular matrix (146)3C
MPLMPL proto-oncogene, thrombopoietin receptorProliferator of cells involved in blood clotting (147)3,4V, T
MS4A1Membrane spanning 4-domains A1Regulator of cellular calcium influx necessary for the B-lymphocytes activation (148)3,4C, V
MS4A3Membrane spanning 4-domains A3Marker of immature circulating neutrophils, a cellular population associated to COVID-19 severe disease (148)3C
MUC1Mucin 1, cell surface associatedHigh viscosity of airway mucus and sputum retention in the small airway of COVID-19 patients (149)3C
MYD88MYD88 innate immune signal transduction adaptorInitiates early immune responses (150)3C
NCAM1Neural cell adhesion molecule 1Molecular mimicry between NCAM-1 and the SARS-CoV-2 envelope protein (151)3C, T
NFAT5Nuclear factor of activated T-cells 5Protects cells against harmful effects of stress (137)3C
NFATC1Nuclear factor of activated T-cells 1Transcription factor (137)3,4C, V
NFATC2Nuclear factor of activated T-cells 2Neuroinflammatory factor (137)3C
NFATC3Nuclear factor of activated T-cells 3Involved in proliferation of human pulmonary fibroblasts after hypoxic stimulus (137)3C
NFATC4Nuclear factor of activated T-cells 4Transcriptional regulator in naive T-cells and differentiated effector T-cells, dependent on calcium/PLCγ/calmodulin/calcineurin signaling (137)3C
NFKB1Nuclear factor kappa B subunit 1Activated by various intra/extra-cellular stimuli as viruses (92)3,4C, V
NLRP3NLR family pyrin domain containing 3Intracellular sensor that detects a broad range of pathogen motifs (59)3,4C, V
NOD2Inflammatory bowel disease protein 1Activates NFKB1, negatively regulates TLR2 (152,153)3C, T
NOS1Nitric oxide synthase 1Chemical messenger (154,155)3C
NOS1APNitric oxide synthase 1 adaptor proteinInhibitor of Nnos (156)3C
NOS3Nitric oxide synthase 3Regulating vascular tone, cellular proliferation leucocyte adhesion and platelet aggregation (157,158)3C
NTRK1Neurotrophic receptor tyrosine kinase 1Development and survival of neurons (159)3,4V, T
NTRK2Neurotrophic receptor tyrosine kinase 2Development and maturation of the central and the peripheral nervous systems (159)3,4V, T
NTRK3Neurotrophic receptor tyrosine kinase 3Development of heart and nervous (159)3,4V, T
OLFM4Olfactomedin 4Facilitates cell adhesion, most probably through interaction with cell surface lectins and cadherin (160)3C
P2RX1Purinergic receptor P2X 1Ligand-gated ion channel with relatively high calcium permeability (161)3C
P2RX7Purinergic receptor P2X 7Receptor for ATP that acts as a ligand-gated ion channel (162)3,4C, V
PDGFAPlatelet derived growth factor subunit AWound healing (163)3C
PECAM1Platelet and endothelial cell adhesion molecule 1Cell adhesion (164)3C
PLAURPlasminogen activator, urokinase receptorLocalizing and promoting plasmin formation (165)3C
PPP3CBProtein phosphatase 3 catalytic subunit betaTransduction of intracellular Ca(2+)-mediated signals (166)3C
PRF1Perforin 1Defense against virus-infected cells (122)3C
PTGS2 Prostaglandin-endoperoxide synthase 2Role in the inflammatory response (167)3C
PTPN11Protein tyrosine phosphatase non-receptor type 11Positively regulates MAPK signal transduction pathway (168,169)3C
PYCARDPYD and CARD domain containingKey mediator in apoptosis and inflammation (170,171)3,4C, V
RENReninAngiotensin I from angiotensinogen generator in the plasma, initiating a cascade of reactions that produce an elevation of blood pressure and increased sodium retention by the kidney (172,173)3C
SCL11A2Natural resistance-associated macrophage protein 2Important in metal transport and their insertion into mitochondria (174)3,4V, T
SCN5ASodium voltage-gated channel alpha subunit 5Responsible for the initial upstroke of the action potential in an electrocardiogram (175)3C
SELESelectin EImmunoadhesion (176)3,4V, T
SELPSelectin PMediates rapid rolling of leukocyte rolling over vascular surfaces during the initial steps in inflammation through interaction with SELPLG (177)3,4V, T
SERPINE1Serpin family E member 1Alveolar type 2 cells senescence in the lung (178)3C, T
SERPINE2Serpin family E member 2Serine protease inhibitor with activity toward thrombin, trypsin, and urokinase (40)3C
SFTPCSurfactant protein CLowering the surface tension at the air-liquid interface in the peripheral air spaces (179)3C
SFTPDSurfactant protein DMay participate in the extracellular reorganization or turnover of pulmonary surfactant, regulates immune response (180)3C
SHC1SHC adaptor protein 1Signaling adapter that couples activated growth factor receptors to signaling pathways (181)3T
SIGIRRSingle Ig and TIR domain containingInflammation immune, response modulator (182)3C
SLC11A2Solute carrier family 11-member 2Metal transporter (183)3T
SOCS1Suppressor of cytokine signaling 1Exerts the viral virulence effect via inhibition of type I and type II interferon (IFN) function (184)3,4V, T
STXBP2Syntaxin binding protein 2Involved in cytolytic pathway (185)3T
TBK1TANK binding kinase 1Regulator of inflammatory responses to foreign agents (186)3C
TFTransferrinTransports of iron from sites of absorption and heme degradation to those of storage and utilization (187)3,4V, T
TFPITissue factor pathway inhibitorAnticoagulant protein blocking the initiation of blood coagulation by inhibiting TF-f VIIa and early forms of prothrombinase (188)3,4V, T
TFRCTransferrin receptorErythropoiesis and neurologic development (189)3,4V, T
TGFB1Transforming growth factor beta 1Gene expression proliferation (70)3C, T
THPOThrombopoietinRegulates platelets and macrophages differentiation (190)3,4V, T
TICAM1Toll-like receptor adaptor molecule 1Native immunity against invading pathogens (191)3C
TLR2Toll-like receptor 2Pathogen recognition-potential therapeutic target (192-194)3C, T
TLR4Toll-like receptor 4Upregulated after SARS-CoV-2 infection (195)3C
TNFTumor necrosis factorBiomarker of COVID-19 severity (104)3,4C, V, T
TNFRSF1ATNF receptor superfamily member 1AContributes to the induction of non-cytocidal TNF effects including anti-viral state and activation of the acid sphingomyelinase (93,104)3C
TNFRSF1BTNF receptor superfamily member 1BRegulates TNF-α function by antagonizing its biological activity (93,104)3C
TRAF3TNF receptor associated factor 3Regulates pathways leading to a NFKB and MAP kinases activation, and B-cell survival (196)3C
TYK2Tyrosine kinase 2Antiviral activity (197)3C
VCAM1Vascular cell adhesion molecule 1Mediates the adhesion of lymphocytes, monocytes, eosinophils and basophils to vascular endothelium (198)3,4V, T
VEGFAVascular endothelial growth factor ADominant inducer to blood vessels growth (increases their permeability) (199)3C
VKORC1Vitamin K epoxide reductase complex subunit 1Reduces inactive vitamin K 2,3-epoxide to active vitamin K (200)3C
VWFvon Willebrand factorInvolved in hemostasis and thrombosis (201)3,4C, V, T

a Entities: C, COVID-19; V, vaccine-induced thrombotic thrombocytopenia; T, thrombocytopenia.

The second one including 61 molecules, is described in Table I and illustrated in Fig. 5. Of these, 47 are common with thrombocytopenia (indicated by a polygon), and 16 with COVID-19 (represented by circles). The VITT-related molecules are denoted with triangles.

Venn diagrams were further created to illustrate the nodes that are common between thrombocytopenia and COVID-19 or VITT (Fig. 4A and B, respectively), between COVID-19 and VITT (Fig. 4C), and amid the three morbid entities (Fig. 4D). The common nodes are listed in each diagram in detail.

All included molecules herein are listed in Table I. The figure (network) in which each molecule is implicated is also noted in a separate column in Table I.


Epidemics were already identified as entities in antiquity by Hippocrates and named by him in his Treatises 'On Epidemics' (9,10). Viral epidemics were described therein and in other works of the Hippocratic Corpus (11,12). On the other hand, Aristotle, the ancient Greek physician and philosopher (4th century B.C.) wrote that 'the creativeness of nature focuses on qualities rather than quantities and description rather than measurements' (13,14). This concept was rejected by Newton's determinism and reductionism and was since forgotten, until it was re-established by Wulff in 1999 (15). Indeed, subtle change in qualities may trigger phase shift alterations with unpredictable consequences, as the Chaos theory of dynamic systems recently confirmed (16). According to this concept, the systems theory was coined as representing a rapid, cost and time-effective method of research (17). It may integrate basic, preclinical and clinical research, and both human and animal results to unravel new insights in complex and often unpredictable issues. In the case of the COVID-19 pandemic, the urgency, and certain ethical issues, make such an in silico approach a sine qua non research method.

The human-to-human transmission of SARS-CoV-2 is either mediated by respiratory droplets via sneezing/coughing or even just breathing, while the disease demonstrates an incubation period of 5-7 days (18). The clinical outcomes range from asymptomatic to influenza-like, or to even pneumonia and severe acute respiratory distress syndrome (ARDS) (19), and thromboembolic events (20,21), pointing to the lung tropism of this virus. Dissimilarities in patients' profiles are attributed to genetic and/or epigenetic variations and underlying pathologies. Dissimilarities in severity may be attributed to the aforementioned factors, but also to the size of the viral inoculum and/or viral mutations.

COVID-19 and the thrombocytopenia interactions network

Ariadne's thread appears to be the angiotensin I converting enzyme 2 (ACE2), which clearly plays a crucial role. SARS-CoV-2, via its spike S protein, a surface glycoprotein that surrounds the spherical virus, is attached to ACE2 and this is followed by entry into cells of the host (22-27). ACE2 is expressed in cells of a number of human organs (including the skin, nasal and oral mucosa, lung, nasopharynx, brain, lymph nodes, thymus, stomach, small intestine, colon, bone marrow, spleen, liver and kidneys). Additionally, its expression in lung alveoli (type 2 pneumonocytes) and small intestine endothelium, as well as in the arterial and other tissue smooth muscle epithelium (28), may trigger the release of anaphylatoxin (29). There is clinical evidence to confirm the aforementioned knowledge of COVID-19 (29).

In the generated network illustrated in Fig. 2, ACE2 interacts with CYP11B2 and with IL-6. The latter is the greatest hub in this vastly interconnected network, with 63 interactions, confirming that the progress of SARS-CoV-2-induced infection would profit from therapeutic blockade of IL-6. As noted by Mazzoni et al (24), blocking this mechanism would 'suppress noxious systemic inflammation but also restore the protective antiviral potential'. It has been established that innate immunity via natural killer (NK) cells exerts the frontline defense, with CD8+ T-lymphocytes being important for the long-term surveillance against viruses, while adaptive immune responses play a key role in the control of viral infections (28). Both responses are mediated either via cytotoxicity or by IF-γ, IL-12 and IL-18. Virus-induced cytotoxicity is primarily moderated by perforin and granzymes. Increased severity in viral infections may lead to dysregulated immunity and tissue/organ damage (30). Clinical evidence in SARS-CoV-2 infection has demonstrated that high IL-6 levels in patients in intensive care units, are inversely associated with the concentration of NK cells (24,31).

The network included dense interactions illustrating clearly that SARS-CoV-2-specific T-cells are critical for the extended damage caused by the 'cytokine storm' (or 'cytokine release syndrome') (30,32) (Fig. 3). This excessive inflammatory response may be lethal for some patients (29,33). Although the phenomenon may manifest in other inflammatory conditions, including bacterial sepsis, pneumonia, sterile inflammation, etc., the extent in the secretion of several specific cytokines is different in COVID-19-related storm (29). Of note, COVID-19 infection has been associated with changes in the blood coagulation mechanisms, with differing manifestations in different patients, in distinct phases of the disease, and independently of disease severity.

Autoimmune destruction of platelets, cytokine release and high consumption of coagulation factors and platelets have been observed in patients with SARS-CoV-2 infection (Geronikolou et al, unpublished data) and initial hypercoagulability (34). Thromboembolic events increase by 31% in patients with COVID-19 admitted in intensive care units (35,36); the phenomenon may be interpreted by the 'two way activation theory' (20,37), i.e., thrombogenesis via inflammation-relevant pathways, with parallel occurrence of release of VWF large polymers. The coagulation and platelet profiles of patients with COVID-19 are then rather normal, unlike in patients with sepsis where platelets are activated and consumed, with the occurrence of thrombocytopenia (38). Only a few patients may then survive, particularly of those with extensive disseminated intravascular coagulation (38). Thrombosis has been observed in situ in the lungs, as well as in a systemic manner, in a similar fashion with classic sepsis and acute respiratory distress syndrome. Reported thromboembolic complications include mostly venous pulmonary embolism (38), aortic graft thrombosis, and mesenteric ischemia; coronary and cerebral thrombosis cases have been reported, although these are rare. The so-called 'COVID toe' is a sign of thrombosis accompanied by arterial and venous clots, urgent oxygen demand and multiple organ dysfunction (20,36,39).

COVID-19 and thrombocytopenia interactomes share only 14 nodes (AIM2, IFI16, TLR2, NOD2, NKAM1, IL-6, TNF, JAK2, IL-1B, SERPINE1, HLA-DRB1, TGFB1, CD8A, and VWF) (Fig. 3), most of which serve as major hubs (IL-6, TNF, JAK2, IL-1B, SERPINE1, TGFB1, CD8A and VWF) in the herein presented interactome (Figs. 1 and 2).

Cytokines, such as IL-1B, 1L-6 and TNF contribute to the so-called cytokine storm, as aforementioned. Moreover, JAK2 is a kinase suspected to be implicated in thrombocytopenia via reduced levels of thrombopoietin or via decreased expression levels of their cognate receptors (cMpl receptors). JAK2 mutations (V617F) that are present in the majority of patients with myeloproliferative disease, may increase hematopoietic cell sensitivity to erythropoietin and thrombopoietin. NKAM1 or CD56 is a homophilic binding glycoprotein expressed on the surface of neurons, glia cells and skeletal muscles. NKAM1 is a prototypic marker of NK cells, also present in CD8+ T-cells. These cell types exhibit diminished antiviral ability and cytotoxic impairment during COVID-19 infection (24). CD8A1 is a cytotoxic marker for T-cell populations. SERPINE1 or plasminogen activator inhibitor-1 is a protein encoded by the SERPINE1 gene, which participates in both thrombosis and atherogenesis (40).

TGFB1 is a multifunctional peptide, with diverse activities, including the control of cell growth, proliferation, differentiation, and apoptosis. It can also down-regulate the activity of immune cells via decreasing the expression levels of cytokine receptors, such as that of IL-2. Several types of T-cells secrete TGFB1, so as to inhibit cytotoxicity and the secretion of certain cytokines, such as interferon-γ, TNF-α and various interleukins, such as IL-6. This makes this molecule a potential target of therapeutic value. On the other hand, the hemostatic VWF is detected in blood plasma, endothelium and megakaryocytes, as well as in subendothelial connective tissue. This factor appears to be also increased and implicated in autoimmune diseases, such as thrombotic thrombocytopenic purpura, as well as in stroke and atrial fibrillation, due to the platelet clots that are potentially formed when its levels are elevated.

Recent literature has further revealed that an HLA class I and II molecule, that is, HLA-DRB1, which is common in COVID-19 and in thrombocytopenia networks (Fig. 2), may play a role in the observed COVID-19 individual and ethnic diversity in clinical severity and/or response to therapy or vaccination (41-44). Of note, HLA-DRB1 is interconnected with the lymphocyte function markers CD3D, CD3E, CD3G, CD4, lymphocyte regulation positive FCGR1A, FCGR1B, HLA class I and II molecules, such as HLA-A, HLA-B, similar to the NCAM1, PTPN1, SHC1 and VCAM1 molecules that have been implicated in thrombosis and atherosclerosis. NCAM1 is involved in cell-cell adhesion in neural-muscle cells in the embryonic phase and later, and more notably, in the responsiveness to viral infections (rabies virus and papilloma virus) (45). PTPN1 is a potential therapeutic target of obesity and type 2 diabetes mellitus as well (46); SHC1 is implicated in reactive oxygen species regulation, thus, in the oxidative stress response (47), while VCAM1 is directly involved in thrombosis and atherogenesis and acute respiratory syndrome (48-51).

VITT and thrombocytopenia interactome

Various coagulation mechanisms have been implicated in VITT: High levels of D-dimers and low levels of fibrinogen have been observed in patients (2,52,53). On the other hand, early reports of VITT described a higher incidence of the syndrome in young women, exhibiting both age-dependence and sexual dimorphism. VITT, though very rare, is of utmost importance. Yet, in March, 2021, the European Medicines Agency (EMA) issued a statement noting that the thromboembolic events of VITT in vaccinated populations were not higher than in general population (54). Subsequently, the 'risk vs. benefit' equilibrium was weighed by the World Health Organization (WHO), promoting the benefit of the vaccination vs. the extremely low risk of thromboembolic risk of VITT in the general population (55).

VITT is currently termed 'thrombosis with thrombocytopenia syndrome (TTS)' by the Centers for Disease Control and Prevention (CDC) and the US Food and Drug Administration (FDA) (56), and is characterized by arterial and venous thrombosis at unexpected sites (i.e., cerebral venous sinuses, splanchnic vessels of variant severity and/or positive platelet factor (PF) 4-heparin ELISA ('HIT' ELISA) syndrome (52), exhibiting both age dependence and sexual dimorphism (more frequent in individuals <50 years old and of the female sex) (2). The laboratory and clinical features of this syndrome are similar to those of the heparin-induced thrombocytopenia (HIT) syndrome and/or the HIT-like autoimmune thrombosis with thrombocytopenia syndrome (2,52,53), both of which have already been reported following surgery, the uptake of certain pharmaceuticals, or during some infections in patients that are not being treated with heparin. The therapeutic suggestions of this recently coined syndrome include early initiation of non-heparin anticoagulation, high-dose IVIG, and/or prednisolone (57).

The genetic basis of the VITT syndrome appears to be closely intertwined with that of the COVID-19 disease and, as such, they share 16 nodes: CASP1, CXCL8, FGF7, HLA-A, HLA-B, IL1B, IL6, MS4A1, NFATC1, NFKB1, NLP3, P2RX7, PYCARD, TNF, TFP1, VWF (Figs. 3Figure 4-5). The purpose of the vaccine is to inhibit pathways that mediate this condition (52,58). More importantly, the relevant research is ongoing with the extremely rare cases of this syndrome, as VITT incidence is ~0.74-1 cases per 100,000 vaccinated subjects (52). Of note, the anti-COVID-19 vaccines do not cause illness and the two morbid entities (COVID-19 and VITT) are by no means identical, with the etiopathology of the latter being actually autoimmune, with auto-antibodies against platelet factor 4. More explicitly, COVID-19 network shares 14 nodes with thrombocytopenia (AIM2, CD8A, HLA-DRB1, IFI16, IL1B, IL6, JAK2, NCAM1, NOD2, SERPINE1, TGFB1, TLR2, TNF and VWF), while VITT (which is a type of thrombocytopenia) shares 46 nodes with thrombocytopenia (Figs. 3Figure 4-5). Notably, SHC1, STXBP2, CDC20 and ADAM10 are silenced in VITT, while AURKA, CD46, CD19 are uniquely expressed following vaccination (apparently not expressed in common thrombocytopenia or in COVID-19) (Figs. 3Figure 4-5). These molecules were not previously identified as VITT-related and are, thus, a novel finding, at least to the best of our knowledge.

It is known that the NLP3 inflammasome is implicated in both COVID-19 and VITT, apart from its participation in other inflammatory reactions (59). It has also been previously demonstrated that acute thrombotic events may manifest during hypoxia, as shown in COVID-19, due to an early proinflammatory state in the venous milieu, mediated by a HIF-induced NLP3 inflammasome complex (60,61). In the network constructed in the present study, NLP3 connects with CASP1, IL-IB, IL17A, CXCL8, IL-6, MYD88, NFKB1, P2RX7, PYCARD and TNF.

P2RX7 exhibits sexually dimorphic and contrasting roles in the pathogenesis of thrombosis, depending on the pathogen type, the severity of infection, the cell type infected and the level of tissue activation (62). In the thrombocytopenia/ COVID-19/VITT cases, the viral load, the cell-type infected and the infecting virus strain or certain vaccine types have been associated with NLP3 hyperactivation, which in the presence of comorbidities, such as liver, renal, gut or respiratory tract illnesses, diabetes mellitus, previous infections, exposure to pollutants, and/or lifestyle factors, such as smoking and obesity, may upend the roles of P2RX7 and PYCARD to those of tissue-damaging, or even lethal factors (62,63). More importantly, the persistent neurological effects ('long-COVID-19') observed in a large percentage of patients with COVID-19 may be explained via the activation of these pathways. Thus, P2RX7 antagonists may be promising therapeutics in the management of both VITT and 'long-COVID-19' (62,64), as P2RX7 receptor stimulation has been implicated in lung damage, psychiatric disorders and pathological inflammation (65,66). In the COVID-19 interactome, P2RX7 directly interacts with NLP3, CASP1 and P2RX1. On the contrary, in the VITT network, P2RX7 directly interacts only with NLP3, IL1B and CASP1. Accordingly, PYCARD interacts with NLP3, CASP1, IL1B, IL18 and IKBKG in COVID-19, and with NLP3, CASP1 and IL1B in the VITT syndrome (Table II). The common node in all possible combinations, as shown in Table II, is CASP1, a downstream event of the NLP3 inflammasome; CASP1 activation promotes IL1B production, which may be prevented by a pan-caspase inhibitor or by glyburide treatment (67).

Table II

Common direct connections between 'PYCARD' or 'P2RX7' and 'COVID-19' or 'VITT'.

Table II

Common direct connections between 'PYCARD' or 'P2RX7' and 'COVID-19' or 'VITT'.

GeneCOVID-19VITTCOMMON direct connections
COMMON direct connectionsNLP3, CASP1CASP1, IL1BCASP1

To this end, the present study investigated the aforementioned issues through the construction of molecular networks and the detection of at least one known COVID/VITT/thrombocytopenia molecule that confirmed that endothelial dysfunction and blood thrombosis are the key players of both COVID-19 and VITT morbid entities. One limitation of the present study is that it included only wild-type genes and their products. To the best of our knowledge, however, this is the first effort made at providing a comprehensive network map of the molecules involved in the underlying mechanisms of COVID-19, long COVID-19 and/or VITT pathophysiology.

In conclusion, the interactomes presented herein revealed therapeutic and vaccination modification targets (i.e., SHC1, NCAM1, HLAs, CD8A, PTPN1, VWF and TBP1). It was also demonstrated that: i) NCAM1 is involved in SARS-CoV-2 infection responsiveness, apart from papilloma and rabies virus infections, and may be responsible for relevant vaccination side effects; ii) NLP3, P2RX7 and PYCARD contribution may help explain (partly or mostly) VITT and/or 'long COVID-19 side-effects'; iii) furthermore, the antagonism of these latter nodes should focus on potential pharmacological targets in the context of SARS-CoV-2 infection and/or vaccine immunization responsiveness. In conclusion, network construction is a powerful tool, which may be used to elucidate the physiology and pathophysiology of different states in clinical investigation. The highly interconnected network presented herein highlights the complexity of COVID-19/VITT pathophysiology, mapping the key role of cytokines, enzymes and immune response markers (lymphocyte regulators and human leucocyte antigens) that may be potential drug or vaccine targets. It was constructed using wild-type genes and gene products, revealing the body's predisposition to COVID-19 infection or VITT. Of note, the COVID-19 and thrombocytopenia common nodes appear to be key players in the natural history of the illness.

Availability of data and materials

The datasets used and/or analyzed during the current study are available throughout the manuscript.

Authors' contributions

SAG and MM were involved in the conceptualization of the study. SAG was involved in the study methodology. SAG, AP and MM were involved in data validation. SAG and AP was involved in formal analysis and in the investigative aspects of the study. SAG was involved in the provision of resources (study material). SAG, IT and AP was involved in data curation. IT provided the software used in this study. SAG, IT, GPC and AP were involved in the interpretation of the data, and in the writing and preparation of the original draft. SAG, AP, MM and GPC were involved in the writing, reviewing and editing of the manuscript. MM and GPC supervised the study. SAG and GPC were involved in project administration. All authors confirm the authenticity of the raw data and have read and agreed to the published version of the manuscript.

Ethics approval and consent to participate

Not applicable.

Patient consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.


Not applicable.


No funding was received.



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Volume 49 Issue 3

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Geronikolou SA, Takan I, Pavlopoulou A, Mantzourani M and Chrousos GP: Thrombocytopenia in COVID‑19 and vaccine‑induced thrombotic thrombocytopenia. Int J Mol Med 49: 35, 2022
Geronikolou, S.A., Takan, I., Pavlopoulou, A., Mantzourani, M., & Chrousos, G.P. (2022). Thrombocytopenia in COVID‑19 and vaccine‑induced thrombotic thrombocytopenia. International Journal of Molecular Medicine, 49, 35.
Geronikolou, S. A., Takan, I., Pavlopoulou, A., Mantzourani, M., Chrousos, G. P."Thrombocytopenia in COVID‑19 and vaccine‑induced thrombotic thrombocytopenia". International Journal of Molecular Medicine 49.3 (2022): 35.
Geronikolou, S. A., Takan, I., Pavlopoulou, A., Mantzourani, M., Chrousos, G. P."Thrombocytopenia in COVID‑19 and vaccine‑induced thrombotic thrombocytopenia". International Journal of Molecular Medicine 49, no. 3 (2022): 35.