Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1 + 4536 word(s) 4536 2021-11-16 04:28:55 |
2 format correction Meta information modification 4536 2021-11-17 03:17:32 | |
3 subject change Meta information modification 4536 2021-11-17 06:48:51 |

Video Upload Options

Do you have a full video?


Are you sure to Delete?
If you have any further questions, please contact Encyclopedia Editorial Office.
Maes, M. Drug Targets to Prevent Death Due to Stroke. Encyclopedia. Available online: (accessed on 24 June 2024).
Maes M. Drug Targets to Prevent Death Due to Stroke. Encyclopedia. Available at: Accessed June 24, 2024.
Maes, Michael. "Drug Targets to Prevent Death Due to Stroke" Encyclopedia, (accessed June 24, 2024).
Maes, M. (2021, November 17). Drug Targets to Prevent Death Due to Stroke. In Encyclopedia.
Maes, Michael. "Drug Targets to Prevent Death Due to Stroke." Encyclopedia. Web. 17 November, 2021.
Drug Targets to Prevent Death Due to Stroke

Acute ischemic stroke (IS) is one of the most prevalent major health problems worldwide, which frequently causes severe functional disabilities and mortality. Protein-protein interaction (PPI) network analysis revealed that the backbone of the highly connective network of IS death consisted of IL6, ALB, TNF, SERPINE1, VWF, VCAM1, TGFB1, and SELE. Cluster analysis revealed immune and hemostasis subnetworks, which were strongly interconnected through the major switches ALB and VWF. Enrichment analysis revealed that the PPI immune subnetwork of death due to IS was highly associated with TLR2/4, TNF, JAK-STAT, NOD, IL10, IL13, IL4, and TGF-β1/SMAD pathways. The top biological and molecular functions and pathways enriched in the hemostasis network of death due to IS were platelet degranulation and activation, the intrinsic pathway of fibrin clot formation, the urokinase-type plasminogen activator pathway, post-translational protein phosphorylation, integrin cell-surface interactions, and the proteoglycan-integrin extracellular matrix complex (ECM). Regulation Explorer analysis of transcriptional factors shows: (a) that NFKB1, RELA and SP1 were the major regulating actors of the PPI network; and (b) hsa-mir-26-5p and hsa-16-5p were the major regulating microRNA actors. 

stroke inflammation neuroimmune cytokines hemostasis coagulation protein-protein interactions

1. Introduction

Acute ischemic stroke (IS) is one of the most prevalent major health problems worldwide, which frequently causes severe functional disabilities and mortality [1][2]. IS risk factors comprise unmodifiable factors including age, sex and ethnicity, and modifiable factors including diabetes mellitus, increased systolic blood pressure (≥140 mm Hg), increased body mass index or body weight, heart diseases, atrial fibrillation, transient ischemic attack (TIA), metabolic syndrome, smoking, sedentary life style, alcohol dependence, genetics and nutritional factors [1][2][3][4]. IS the consequence of blood vessel clots in the brain which interrupt blood flow and lead to lack of oxygen, causing cellular damage and neuronal cell death with neurodegenerative processes [5]. When vessels are occluded, inflammatory mediators are locally generated and propagated throughout the brain and peripheral, circulating blood, leading to neuroinflammatory processes and a systemic immune-inflammatory response [6].
Apart from being a neurodegenerative and neuroinflammatory disorder, IS also an atherothrombotic disease with activation of hemostasis, coagulation, fibrin clotting, and fibrinolysis cascades coupled with endothelial dysfunctions [7][8]. Thus, reduced levels of natural anticoagulants including protein C (PROC), protein S (PROS1), and antithrombin (SERPINC1), are not only associated with an increased risk of venous thrombosis, but also with the progression, outcome and prognosis of IS [8][9][10][11][12]. Major adhesion molecules, including vascular cellular adhesion molecule-1 (VCAM-1) and E-selectin (endothelial-leukocyte adhesion molecule 1/SELE) facilitate migration of leukocytes towards inflammatory regions and play a role in the outcome of IS [8].
The mean carotid intima media thickness (cIMT), as measured through carotid Doppler ultrasonography, is a marker of severity of atherosclerosis and is associated with the severity and outcome of IS [8][13]. The baseline IS severity and IS-induced disabilities may be assessed using the National Institutes of Health Stroke Scale (NIHSS) and the modified Rankin score (mRS) [14][15], respectively. Both scales are also useful to predict the functional outcome of IS, in terms of either short-term (three months) or long-term (one year) outcome [16][17][18][19].
IS the second leading cause of mortality, and around one-third of IS patients may die within the first few months after the ischemic event [20][21]. The cumulative risk for death at 28 days after IS (labeled as “28 days fatality” or “deaths from stroke”) is around 28%, and the risks at 1 and 5 years are 41% and 60%, respectively [22][23][24]. In nonfatal IS, the risk of death within the first year after the index stroke is 5 times higher than in a nonstroke population. In patients with initially nonfatal IS, the subsequent increased mortality rate is ascribed to vascular diseases, especially cerebrovascular and ischemic heart disease, neoplasms, infectious disease, diseases of the respiratory system, accidents and suicide [23].
Risk factors of increased mortality due to IS comprise increased age, increased cIMT scores, previous stroke and TIA, diabetes mellitus, heart disease, atrial fibrillation, increased baseline NIHSS and mRS scores, fever, and size of lesion [8][13][25][26][27][28][29]. Post IS death (three months and one year after admission) is predicted (in comparison with surviving IS patients) by different baseline blood-based biomarkers: (1) increased levels of glucose, but reduced levels of high-density lipoprotein (HDL) cholesterol and 25-hydroxyvitamin D [25(OH)D]; (2) reduced levels of the natural anticoagulants PROC, PROS1, and SERPINC1, and increased levels of Von Willebrand Factor (VWF), fibrinogen (FBG), and Factor 8 (F8); (3) increased levels of immune-inflammatory factors including white blood cell counts (WBC), interleukin (IL)-6, IL-10, tumor necrosis factor (TNF)-α, high sensitivity C-reactive protein (hsCRP), and ferritin; and lowered levels of transforming growth factor (TGF)-β1 and albumin (ALB); and (4) increased levels of the adhesion molecules SELE and VCAM-1 [8]. In fact, in machine learning models, different combinations of increased cIMT and NIHSS scores and these mentioned biomarkers yield the most accurate prediction of short- and long-term mortality due to IS [8][13].
A review of the existing literature shows that a number of genes may increase risk of mortality due to IS, including SERPINE1 (serine protein inhibitor E1) or plasminogen activator inhibitor 1 (PAI-1), ITGB3 (integrin beta-3), MPG (DNA-3-methyladenine glycosylase), PROCR gene (soluble endothelial protein C receptor), HABP2 (Hyaluronan Binding Protein 2), COL3A1 (type III collagen), FBG, RETN (resistin), VKORC1 (Vitamin K epoxide reductase complex subunit 1), INADL (InaD-Like Protein, PALS1-Associated Tight Junction Protein), and FXIIIA Val34Leu genetic variant [30][31][32][33][34][35][36][37][38][39][40] Moreover, the micro-RNA (miR)-10a rs3809783 A>T (MIR10A) and miR-34b/c rs4938723 T>C genetic variant (MIR34B) and the long noncoding RNA (lncRNA) AL110200 are associated with increased mortality rates due to IS [41][42].
Although risk factor control, antithrombotic treatment, and revascularization have been widely applied in clinical practice, IS still a main cause of death [43]. The state-of-the-art management of IS comprises treatments targeting stroke-induced neurological damage and restoring the blood flow to the brain, including treatment with recombinant tissue plasminogen activator (tPA) IV [2]. Surgical decompression reduces risk of mortality, although in elderly patients, decompression may be accompanied by an increased risk of long-term dependency [44]. The Action Plan for Stroke in Europe considers that considerable effort should be focused on neuroimmune, neuroprotective, and vascular pathways [45].

2. The Networks and Subnetworks of Death Due to Stroke

The first major finding of this study is that the PPIs network of DEPs and DEPs/genes of death from IS versus stroke survival show a high connectivity and two interconnected subnetworks, namely, a first which is centered around immune genes and a second which is centered around hemostasis-coagulation genes. All query DEPs/genes participated in these networks except INADL. The backbone of this network consists of DEPs/genes which contribute to both subnetworks, namely IL6, TNF, TGFB1, VCAM, and SELE as authorities in the immune subnetwork, and ALB, SERPINE1, and VWF in the hemostasis subnetwork. Moreover, ALB ad VWF are important switches that connect both subnetworks because these DEPs show many significant interactions with proteins in both communities. Therefore, it appears that death due to IS predicted by an integrated response in a network which comprises strongly interconnected immune and hemostasis subnetworks. This indicates that both the immune response (as indicated by increased IL-6, IL-10, TNF-α, VCAM-1, SELE, and CRP but lowered TGF-β1 and ALB) and the activated hemostasis, thrombosis and coagulation pathways (as indicated by increased F8, VWF, and FBG but lowered PROC, PROS1, SERPINC1 and ALB levels) are intertwined phenomena leading to death from IS. The strong interconnections among the immune and hemostasis subnetworks have probably an evolutionary origin [46]. We will now discuss both the significant biological functions, paths, molecular complexes, and transcriptional factors enriched in the networks.

3. Terms Over-Represented in the Immune Subnetwork

The second major finding of this study is that the most significant paths and functions enriched in the networks of death due to IS were the inflammatory and NF-κB signaling pathways, NFKB1/RELA transcriptional factors, TNF-α and IL-17 signaling, and the TLR, TGF-β1, nucleotide-binding and oligomerization domain (NOD) and JAK-STAT pathways. These results indicate that altered expression of these pathways, and transcriptional factors, may lead to death due to IS.
There is now evidence that in IS, NF-κB may be a key factor for the transcriptional induction of cellular adhesion molecules, including SELE and VCAM-1, proinflammatory cytokines, including IL-6 and TNF-α, CRP, and FTH1, growth factors including TGF-β1, and coagulation factors including F8, PAI1, uPA, tissue factor and fibronectin [46][47]. Transient focal cerebral ischemia is accompanied by NF-κB activation in the nuclei of striatal and cortical neurons in the ischemic hemisphere [48]. It is important to note that ischemia-induced astroglial NF-κB may have neurodegenerative effects, whereas constitutive neuronal nuclear factor kappa B subunit 1 (NFΚB1) may have neuroprotective effects [49].
In animal models of middle cerebral artery occlusion, activation of astroglial NF-κB is downstream of TLR2 activation and a deficiency in TLR2/4 reduces the neurodeficit and IS size [49]. Moreover, models of focal cerebral ischemia show that increased NF-κB is associated with IS severity and size, and that there may be a causative association between both factors, whereby induced reductions in NF-κB levels are accompanied with lowered IS size and neurodeficit [47][50]. Inhibition of NF-κB (through administration of caffeic acid phenethyl ester, mycophenolate, atorvastatin, and cephalexin may attenuate oxidative stress and neurodegeneration due to middle cerebral artery occlusion [51]. Moreover, the promoter variant (rs11940017, -1727 C>T) of the NFKB1 gene may affect IS susceptibility in the Korean population [52].
Furthermore, there is evidence that in IS the deleterious effects of increased NF-κB are associated with RELA activation [47], which is the second transcription factor which is highly significantly enriched in our PPI network. RELA plays a key role in the activation of NF-κB and the translocation of the latter to the nucleoplasm, while the RELA-NFKB1 complex mediates gene expression of many cytokines (UniPro UniProtKB—Q04206 (TF65_HUMAN) ( (accessed on 19 September 2021). Moreover, the apoptotic responses caused by NF-κB are dictated by acetylation of RELA in Lys310, and RELA, but not p50, knockouts show a decreased infarct size [53][54].
The TLR2/4 complexes play a key role in IS with increased expression of both receptors being associated with the inflammatory response and progression of infarct volume and ischemic damage [55]. Both TLR levels (as assessed in peripheral blood monocytes using flow cytometry) are associated with increased plasma levels of IL-6, TNF-α, VCAM-1, and the clinical outcome and lesion volume [56]. It is interesting to note that in IS patients, serum levels of fibronectin, heat shock protein (HSP)60 and HSP70 are endogenous ligands leading to TLR2/4 activation [56]. Likewise, the inflammatory response during stroke is attenuated by blockade of the TLR2/4 complexes and cellular fibronectin. In TLR4 knockout mice, smaller stroke sizes and better neurocognitive functions are observed [57][58]. All TLR pathways activate NF-κB [55][59], indicating that activation of the TLR2/4 pathways and NF-κB signaling are interrelated phenomena. This suggests that the cumulative effects of both TLR2/4 and NF-κB signaling pathways may confer risk towards death due to IS. There are also reports that TLR4 genetic variants (e.g., TLR4-119A allele) are associated with an increased risk of IS [60]. Moreover, it is important to note that vitamin D3, which in our studies was associated with death due to IS, attenuates TLR2/4 expression and signaling, thereby preventing the translocation of p65 to the nucleus, and consequently, attenuating inflammatory responses [55].
Soon after IS onset, microglia cells and circulating monocytes are activated and consequently, increased release of TNF-α and IL-6 may be detected in the brain, cerebrospinal fluid, and bloodstream [8]. Increased TNF-α levels in CSF and blood are significantly associated with stroke outcome assessments including the Barthel Index and Scandinavian Stroke Scale (SSS) [61]. The plasma levels of TNF-α, which are observed in IS patients, may impact neuronal function and viability, even leading to neuronal death [62]. A recent meta-analysis shows that TNF-α is increased in Asian and Caucasian IS patients (overall SMD = 0.65, 95% CI = 0.29, 1.01), and that the TNF-α-308 G > A (rs1800629) genetic variant is associated with increased risk of IS [63]. IS is accompanied by an increased expression of IL-17 and IL-17RC in the serum in association with increased IL-6 and granulocyte-monocyte colony-stimulating factor (GM-CSF) and granulocyte colony-stimulating factor (G-CSF) [64]. It is thought that the IL-17-IL-17R pathway plays a key role in secondary poststroke damage via (a) effects on neutrophil infiltration in cerebral parenchyma, thereby promoting damage and thrombosis; (b) effects on tight junctions with blood-brain-barrier (BBB) breakdown and induction of neuronal apoptosis, and (c) synergistic effects with IL-6 [65]. Moreover, a polymorphism of the IL17RC gene is associated with a poorer prognosis of IS [64].
There are now some reports that in experimental models of IS, the JAK2-STAT3 pathway is activated and contributes to neuronal damage [66][67][68][69]. Middle cerebral artery occlusion is accompanied by increased concentrations of TNF-α, high mobility group box B1 (HMGB1), and phosphorylated JAK2/JAK2 and STAT3/STAT3 in the brain. Blocking JAK2, STAT3 and the JAK2/STAT3 signaling pathway significantly reduces IS-associated inflammatory responses [70]. Additionally, Wang and coworkers reported that in an IS model attenuation of the JAK-STAT pathway reduces apoptosis in neuronal cells and loss of neurological functions [71]. Cytokines including IL-6 and IL-10 activate Janus kinases causing translocation of STAT to the nucleus which, in turn, leads to changes in expression of a great number of immune and wound-healing genes [72].
NOD-like receptors are a family of cytoplasmic receptors which sense bacterial motifs and danger signals (including uric acid and ATP) and trigger an innate immune response by activating NF-κB and mitogen-activated protein kinase (MAPK) [73][74]. In the middle cerebral artery-occlusion model, the expression of NOD2 is significantly elevated, and ablation of the NOD2 gene reduces stroke size and inflammation as indicated by lowered expression of NF-κB, MAPK, IL-6, and TNF-α [74].
Our REACTOME path classifications revealed that our DEP network was highly significantly associated with IL-10, IL-4, and IL-13 pathways. We discussed before that increased activity of the IL-10 pathway in nonsurvivors may be part of a compensatory immune-regulatory mechanism which counterbalances an overzealous inflammatory response [8]. Elevated levels of IL-10 are often associated with a better functional outcome. For example, subjects with reduced plasma IL-10 in the first hours after IS have an increased risk of developing neurological symptoms two days later [75]. Some IL10 genetic variants are associated with increased risk of IS, including the IL-10 rs1800896 variant [76]. IL-4 also has anti-inflammatory effects and drives macrophages from a M1 proinflammatory phenotype to a M2 phenotype with homeostatic, repair and immune regulatory properties, explaining how IL-4 administration may improve recovery in a mouse stroke model [77]. IL4 KO mice show a worsened neurological outcome and increased brain damage following cerebral ischemia [78]. In IS, intracerebral delivery of IL-13, an anti-inflammatory cytokine, drives macrophages and microglia into the alternative activation state [79]. Nevertheless, high levels of anti-inflammatory cytokines such as IL-10 may sometimes be accompanied by a less favorable outcome, including increased risk of infections [80].
One of the major bottlenecks in the PPI network is TGF-β. This cytokine is elevated in the brain following IS and may exert anti-inflammatory, antiapoptotic and neuroprotective effects, thereby improving repair mechanisms and favoring nerve regeneration [81][82][83]. There are now some publications showing that genetic TGFB1 variants are associated with IS [84]. Moreover, the effects of TGF-β1 on multiple target genes (including ECM) are mediated via the SMAD signaling pathway [85][86], which was significantly enriched in the hemostasis subnetwork list, albeit SMAD/MAD did not make the top five. Importantly, the TGF-β/SMAD2/3 signaling pathway has neuroprotective properties, for example by elevating Bcl-2 and lowering caspase-3 expression and decreasing microglial activation via NF-κB inhibition [87][88].
In a rat model of cerebral ischemia/reperfusion, SMAD3 administration may downregulate inflammatory and proapoptotic genes, suggesting that the TGF-β/SMAD pathway is a possible drug target [87]. All in all, the lowered levels of TGF-β1 in IS nonsurvivors versus survivors may contribute to the pathways leading to death due to IS.
VCAM-1, another hotspot of the backbone of the PPI network, plays a critical role in the inflammatory response following IS, for example through adhesion of leukocytes to endothelial cells and transendothelial migration via interactions with integrin subunits [89][90]. Due to a fenestrated endothelium, the choroid plexus is the entry site for patrolling lymphocytes—mostly CD4+ central memory T cells—in the healthy brain [91]. To promote leukocyte trafficking, the choroid plexus epithelium constitutively expresses intercellular adhesion molecule (ICAM)-1 and VCAM-1, which, together with the mucosal vascular addressin cell-adhesion molecule, are upregulated in stroke [48]. In IS, intracranial VCAM-1 levels are associated with infarct and edema size [92]. Cell-adhesion molecules (CAM) KO models show a reduced infarct size, and administration of anti-CAM antibodies may decrease infarct size [93]. Increased levels of VCAM-1 and IL-6 predict a new vascular incident, and thus may increase risk of death due to IS [94].

4. Terms and Functions Over-Represented in the Hemostasis Subnetwork

The second most important subnetwork in death due to IS was centered around hemostasis, thrombosis and coagulation genes, which were enriched especially in fibrin clotting or the clotting cascade, TGF-β binding, the uPA and uPAR-mediated (PID-uPA-uPAR) signaling pathways, ECM proteoglycans, integrin cell-surface interactions and platelet activation, aggregation and degranulation. Although abnormalities in the hemostasis axis are not a common cause of IS [95][96][97], perturbations are seen following stroke onset, and these may aid as biomarkers in diagnosis and severity of IS and prediction of the treatment response. This is further substantiated by our findings that a response to wounding is over-represented in the hemostasis subnetwork. It could be argued that a combined deficiency in the PROC, PROS1 and SERPINC1 proteins in the hemostasis network may contribute to the response to wounding. Nevertheless, deficits in these proteins are not a common cause of IS [98], although our studies suggest that they may contribute to death due to IS.
One major hotspot of the backbone of the PPII network and a major connector of both subnetworks is VWF, which shows many interactions with genes from both the immune and hemostasis networks. Such data agree with the view that VWF mediates the crosstalk between immune cells and hemostasis mechanisms and contributes to inflammation, including vascular inflammation [99][100]. The VWB factor is released during the rupture of the endothelial layer of the vessels, whereby the consequent exposure of collagen to platelets leads to clot formation [101]. Consequently, endothelial cells release VWF, P-selectin, SELE, and inflammatory mediators [102]. VWF promotes platelet adhesion to the damaged site by forming a molecular bridge between the subendothelial collagen matrix and the platelet surface receptor complex GPIb-IX-V [100]. VWF levels are increased in IS patients and are associated with the cardioembolic and large-vessel disease subtypes [103]. Additionally, VWF levels are associated with severity of arterial thrombus formation and poor functional outcomes [104][105]. Furthermore, VWF may function as a biomarker of the response to thrombolytic or endovascular treatment in IS patients [105][106]. Variations in the VWF gene (Sma I) may be associated with an increased risk of IS [107]. Preclinical and clinical studies using VWF antagonists and combining the latter with tPA could prevent microvascular thrombus formation, thereby attenuating the progression of IS [105]. Additionally, other authors proposed that targeting VWF-mediated platelet activation and adhesion is a new drug target to treat IS [108].
Fibrinogen (FBG) is one of the hemostasis biomarkers with an essential role in the thrombosis process because it is related to platelet aggregation after injury and inflammation [109][110]. FBG is released from the liver into the bloodstream and is cleaved by thrombin at the damaged site, resulting in fibrin formation. Fibrin is one of the main constituents of blood clots and provides remarkable biochemical and mechanical stability [110]. FBG and CRP levels can independently predict the risk of early death in middle-aged IS patients, emphasizing the role of inflammation and coagulation in the evolution of IS. For each 10 mg/dL increase in FBG levels there was a 18% higher risk of dying, while for 1 mg/L increase in CRP the additive risk was 18%. FBG levels >490 mg/dL and CRP levels >18 mg/L were the optimal points that discriminated those who died from survivors [111]. Another study showed that hyperfibrinogenemia, defined as a plasma FBG concentration >350 mg/dL, predicts the long-term risk of death in IS patients [112]. Moreover, FBG has been used to evaluate the long-term outcome and the size of the clot burden in patients after IS [113][114]. Furthermore, an increase in FBG levels is observed after IS and is associated with infarct size and outcome [115][116][117]. Elevated hemostatic markers after acute IS stroke identify patients with increased risk for mortality independently of IS severity or stroke type [118]. Higher concentrations of fibrinopeptide A, b-thromboglobulin, prothrombin fragments 1 and 2, thrombin-antithrombin complexes, platelet factor four and VWB factor have all been associated with a worse clinical course in IS and increased mortality [118][119][120]. In addition, patients with high PAI-1 levels are less likely to achieve recanalization after receiving tPA, and experience poorer outcomes [121].
Another possible major pathway which was found using enrichment analysis is the uPA-uPAR pathway. This pathway is activated in the periphery of growth cones of the injured neurons in IS brains, where it induces repair mechanisms [122]. The binding of uPA to its receptor promotes β1-integrin recruitment to the plasma membrane with consequent activation of “small Rho GTPase Rac1 and Rac1-induced axonal regeneration” [122]. Since this process is regulated by the low-density lipoprotein receptor (LRP1), it was proposed that the uPA-uPAR-LRP1 axis is another possible drug target in IS and by inference may be a new drug target to prevent death due to IS. Moreover, recombinant uPA may protect the integrity of pre- and post-synaptic terminals and astrocytic elongations against the detrimental effects of IS [123]. Unfortunately, uPA also increases the production of reactive oxygen species and NADH oxidases (Nox1 and Nox4) and enhances superoxide production by neutrophils, findings which suggest that reducing uPA functions may be beneficial [124].
Our enrichment and annotation analyses revealed that the hemostasis subnetwork genes were significantly associated with ECM proteoglycans and integrin cell surface interactions, which are components of the BBB. These functions are impacted by IS, the consequent vasogenic edema, early angiogenesis, inflammation, and reperfusion injury [125][126][127][128]. These IS-induced processes strongly impact the BBB, resulting in breakdown of the tight junctions and paracellular barrier and increased BBB permeability, which may further worsen vasogenic edema and neuroinflammation through increased entry of inflammatory mediators and activated T cells into the brain [129][130]. As observed in our paper and previously, such processes may lead to increased mortality due to IS. Moreover, proteoglycans, integrins and fibronectin are key ECM adhesion receptors which integrate external and internal signals, and regulate global cellular processes, cellular signaling, and cell growth, proliferation, migration, and survival [125]. The ECM regulates the tight junctions, neurons, astrocytes, and the vasculature and plays a key role in wound healing, cell homeostasis, and tissue and neuronal regeneration [131]. Importantly, the proteoglycan-integrin-ECM complex and related BBB functions including tight junctions are now considered to be new drug targets in the treatment of IS, for example by targeting integrins and MMPs [127][128].

5. Interactions, Pathways, and Functions Which Bridge the Immune and Hemostasis Subdomains

Our network analyses showed that not only the VWF (as discussed in the previous section) but also ALB is a major controller gene between both subnetworks of death due to IS and, consequently, that ALB may also be an important drug target. ALB has anti-inflammatory, antioxidant and neuroprotective capacities and thus plays a role in the immune subnetwork, although a second clustering analysis performed in our study allocated ALB into the hemostasis network. ALB also shows antiplatelet aggregability and is a carrier for two anticlotting compounds, namely heparin cofactor and SERPINC1 [132][133]. Subjects with low ALB display increased primary hemostasis, and enhanced platelet aggregation and clot formation, explaining how low ALB levels observed in nonsurvivor IS patients may increase the vulnerability to develop venous thromboembolism [132]. Importantly, reduced baseline ALB levels reflect a chronic inflammatory state, which is already present weeks before the IS (because the half-life of ALB is 21 days). All in all, lowered ALB levels may predispose patients towards interrelated aberrations in both the immune and hemostasis subnetworks, thereby, increasing risk of death due to IS.
In the enlarged giant network, VEGFA is another switch between the immune and hemostasis communalities. This gene is a member of the VEGF family and the protein acts as a mitogen, thereby activating endothelial cells and regulating neuronal cells [134]. VEGFA is implicated in the pathophysiology of atherosclerosis, and in stroke, VEGFA is elevated in the ischemic penumbra and mediates vessel and neuron repair and remote plasticity in ischemic brain regions [134]. Treatment with VEGFA coupled with stem cells may show therapeutic effects in animal stroke models. Moreover, there is an association between IS and different genetic variants of VEGF genes (e.g., -2578C>A and 936C>T variants) [135].
There are many more pathways and functions which link inflammation and coagulation, including TLRs (impact coagulation, platelet activity and aggregation, and thrombosis) [136], NOD2 signaling (enhances platelet activation and thrombosis) [137], TNF-α signaling (activates coagulation, fibrinolysis, neutrophil degranulation, and the release of secretory phospholipase A2, predominantly mediated by the p55 TNFR) [138], platelets (platelet degranulation causes increased cIMT and thus increased inflammatory atherosclerotic processes) [46][139], protease-activated receptors and thrombin, complement, neutrophil extracellular traps, and microparticles [140].
Moreover, our TTRUST enrichment analysis shows that not only NF-κB and RELA (discussed in the previous sections), but also SP1 is a major regulator of both the immune and hemostasis subnetworks. NF-κB is not only critically involved in modulating inflammatory processes but also in thrombotic responses [46]. Thus, NF-κB activation increases the thrombogenic potential, activates platelets, and promotes coagulation, microthrombi formation, immunothrombosis and thromboinflammatory disease [46]. In addition, F8, PAI1, uPA and F3 are target genes of NF-κB. SP1 or transcription factor SP1 (or specificity protein 1) regulates the expression of housekeeping genes which are involved in immune responses, apoptosis, chromatine remodelling, cell differentiation and cell growth [141]. This transcription factor regulates different subnetworks including the immune response (including TNF-α), MAPK and JAK-STAT pathways, platelet activation, ECM, and blood vessels [141].
Our REACTOME pathway and PANTHER process enrichment analyses performed on all markers including miRNA levels revealed the strong impact of translation, RNA, metabolism of mRNA, RNA splicing, and nonsense-mediated decay on the interactome of death due to IS, indicating that dysfunctions in postischemic translation regulation are involved. During ischemia and brain cell injury, translation may arrest due to lack of ATP, and changes in translational regulation at the mRNA level and the ribosomic network may develop, which may cause a multitude of aberrations in the downstream PPI and metabolic network modules [142][143]. The nonsense-mediated decay pathway degrades transcripts with a premature stop codon, thereby reducing errors in gene expression. Failures in this surveillance system may be accompanied by increased synthesis of abnormal, including toxic, proteins [144].
It is interesting to note that both miRNAs, which are altered in death due to IS, regulate immune functions, with hsa-mir-10a regulating IL-8, IL-6, TNF-α, GATA6 apoptotic pathways, and hsa-mir-34b regulating innate immunity (target mining in (accessed on 19 September 2021)). Our study also showed that the expression of the most important miRNA, which is over-represented in death due to IS (hsa-mir-16-5p), was found to be increased in IS and to regulate NF-κB transcription [145][146]. Moreover, also the second-most important miRNA (hsa-mir-26b-5p) is part of a long noncoding RNA (LncRNA)-miRNA-mRNA network of IS and inhibits NF-κB expression [147][148]. Some miRNAs are associated with IS risk factors including hypertension (miR-155), atherosclerosis (miR-21, miR-126, miR-143), atrial fibrillation (miR-26), diabetes mellitus (miR-124a, miR-126), and dyslipidemia (miR-33, miR-122), while some miRNA antagonists have the potential to act as neuroprotective molecules [149]. Elevated expression of miR-15a, miR-16, and miR-17-5p in the serum is strongly associated with IS [150].


  1. Benjamin, E.J.; Virani, S.S.; Callaway, C.W.; Chamberlain, A.M.; Chang, A.; Cheng, S.; Chiuve, S.E.; Cushman, M.; Delling, F.N.; Deo, R.; et al. Heart Disease and Stroke Statistics—2018 Update: A Report from the American Heart Association. Circulation 2018, 137, e67–e492.
  2. Kuriakose, D.; Xiao, Z. Pathophysiology and Treatment of Stroke: Present Status and Future Perspectives. Int. J. Mol. Sci. 2020, 21, 7609.
  3. Sacco, R.L. Risk factors, outcomes, and stroke subtypes for ischemic stroke. Neurology 1997, 49, S39–S44.
  4. Chen, X.; Zhou, L.; Zhang, Y.; Yi, D.; Liu, L.; Rao, W.; Wu, Y.; Ma, D.; Liu, X.; Zhou, X.-H.A.; et al. Risk Factors of Stroke in Western and Asian Countries: A Systematic Review and Meta-analysis of Prospective Cohort Studies. BMC Public Health 2014, 14, 776.
  5. Kleindorfer, D.O.; Towfighi, A.; Chaturvedi, S.; Cockroft, K.M.; Gutierrez, J.; Lombardi-Hill, D.; Kamel, H.; Kernan, W.N.; Kittner, S.J.; Leira, E.C.; et al. 2021 Guideline for the Prevention of Stroke in Patients With Stroke and Transient Ischemic Attack: A Guideline From the American Heart Association/American Stroke Association. Stroke 2021, 52, e364–e467, Erratum in 2021, 52, e483–e484.
  6. Zhou, X.; Yu, F.; Feng, X.; Wang, J.; Li, Z.; Zhan, Q.; Xia, J. Immunity and inflammation predictors for short-term outcome of stroke in young adults. Int. J. Neurosci. 2018, 128, 634–639.
  7. Wiseman, S.; Marlborough, F.J.; Doubal, F.N.; Webb, D.J.; Wardlaw, J.M. Blood Markers of Coagulation, Fibrinolysis, Endothelial Dysfunction and Inflammation in Lacunar Stroke versus Non-Lacunar Stroke and Non-Stroke: Systematic Review and Meta-Analysis. Cerebrovasc. Dis. 2014, 37, 64–75.
  8. Lehmann, A.L.C.F.; Alfieri, D.F.; de Araújo, M.C.M.; Trevisani, E.R.; Nagao, M.R.; Pesente, F.S.; Gelinski, J.R.; de Freitas, L.B.; Flauzino, T.; Lehmann, M.F.; et al. Immune-inflammatory, coagulation, adhesion, and imaging biomarkers combined in machine learning models improve the prediction of death 1 year after ischemic stroke. Clin. Exp. Med. 2021, 12.
  9. Tzoulaki, I.; Murray, G.D.; Lee, A.J.; Rumley, A.; Lowe, G.D.; Fowkes, F.G.R. Relative Value of Inflammatory, Hemostatic, and Rheological Factors for Incident Myocardial Infarction and Stroke. Circulation 2007, 115, 2119–2127.
  10. Alakbarzade, V.; Taylor, A.; Scully, M.; Simister, R.; Chandratheva, A. Utility of current thrombophilia screening in young patients with stroke and TIA. Stroke Vasc. Neurol. 2018, 3, 231–236.
  11. Hashem, S.S.; Helmy, S.M.; El-Fayomy, N.M.; Oraby, M.I.; Menshawy, M.; Dawood, N.A.; Hashem, H.S. Predictors of stroke outcome: The role of hemorheology, natural anticoagulants, and serum albumin. Egypt. J. Neurol. Psychiatry Neurosurg. 2018, 54, 1–7.
  12. Donkel, S.J.; Benaddi, B.; Dippel, D.W.; Cate, H.T.; De Maat, M.P. Prognostic Hemostasis Biomarkers in Acute Ischemic Stroke. Arter. Thromb. Vasc. Biol. 2019, 39, 360–372.
  13. Lehmann, A.L.C.F.; Alfieri, D.F.; de Araújo, M.C.M.; Trevisani, E.R.; Nagao, M.R.; Pesente, F.S.; Gelinski, J.R.; de Freitas, L.B.; Flauzino, T.; Lehmann, M.F.; et al. Carotid intima media thickness measurements coupled with stroke severity strongly predict short-term outcome in patients with acute ischemic stroke: A machine learning study. Metab. Brain Dis. 2021, 36, 1747–1761.
  14. Brott, T.; AdamsJr, H.P.; Olinger, C.P.; Marler, J.R.; Barsan, W.G.; Biller, J.; Spilker, J.; Holleran, R.; Eberle, R.; Hertzberg, V. Measurements of acute cerebral infarction: A clinical examination scale. Stroke 1989, 20, 864–870.
  15. Bonita, R.; Beaglehole, R. Recovery of motor function after stroke. Stroke 1988, 19, 1497–1500.
  16. Adams, H.P.; Davis, P.H.; Leira, E.C.; Chang, K.-C.; Bendixen, B.H.; Clarke, W.R.; Woolson, R.F.; Hansen, M.D. Baseline NIH Stroke Scale score strongly predicts outcome after stroke: A report of the Trial of Org 10172 in Acute Stroke Treatment (TOAST). Neurology 1999, 53, 126.
  17. Johnston, K.C.; Wagner, D.P.; Haley, J.E.C.; Connors, A.F. Combined Clinical and Imaging Information as an Early Stroke Outcome Measure. Stroke 2002, 33, 466–472.
  18. Weimar, C.; König, I.; Kraywinkel, K.; Ziegler, A.; Diener, H. Age and National Institutes of Health Stroke Scale Score Within 6 Hours After Onset Are Accurate Predictors of Outcome After Cerebral Ischemia. Stroke 2004, 35, 158–162.
  19. Bustamante, A.; Simats, A.; Vilar-Bergua, A.; García-Berrocoso, T.; Montaner, J. Blood/Brain Biomarkers of Inflammation After Stroke and Their Association with Outcome: From C-Reactive Protein to Damage-Associated Molecular Patterns. Neurotherapeutics 2016, 13, 671–684.
  20. Johnson, C.O.; Nguyen, M.; A Roth, G.; Nichols, E.; Alam, T.; Abate, D.; Abd-Allah, F.; Abdelalim, A.; Abraha, H.N.; Abu-Rmeileh, N.M.; et al. Global, regional, and national burden of stroke, 1990–2016: A systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019, 18, 439–458.
  21. Donkor, E.S. Stroke in the21stCentury: A Snapshot of the Burden, Epidemiology, and Quality of Life. Stroke Res. Treat. 2018, 27, 1–10.
  22. Heller, R.F.; Langhorne, P.; James, E. Improving stroke outcome: The benefits of increasing availability of technology. Bull. World Health Organ. 2000, 78, 1337–1343.
  23. Brønnum-Hansen, H.; Davidsen, M.; Thorvaldsen, P. Long-Term Survival and Causes of Death After Stroke. Stroke 2001, 32, 2131–2136.
  24. Medicover Hospitals. What is the Life Expectancy after a Brain Stroke? 2021. Available online: (accessed on 26 August 2021).
  25. Petty, G.W.; Brown, R.D.; Whisnant, J.P.; Sicks, J.D.; O’Fallon, W.M.; Wiebers, D.O. Survival and recurrence after first cerebral infarction. Neurology 1998, 50, 208–216.
  26. Vernino, S.; Brown, R.D., Jr.; Sejvar, J.J.; Sicks, J.D.; Petty, G.W.; O’Fallon, W.M. Cause specific mortality after first cerebral infarction: A population-based study. Stroke 2003, 34, 1828–1832.
  27. Koton, S.; Tanne, D.; Green, M.S.; Bornstein, N.M. Mortality and predictors of death 1 month and 3 years after first-ever ischemic stroke: Data from the first national acute stroke Israeli survey (NASIS 2004). Neuroepidemiology 2010, 34, 90–96.
  28. Jia, Q.; Liu, G.; Zheng, H.; Zhao, X.; Wang, C.; Wang, Y.; Wang, Y. Impaired Glucose Regulation Predicted 1-Year Mortality of Chinese Patients with Ischemic Stroke: Data from Abnormal Glucose Regulation in Patients with Acute Stroke across China. Stroke 2014, 45, 1498–1500.
  29. Tziomalos, K.; Spanou, M.; Bouziana, S.D.; Papadopoulou, M.; Giampatzis, V.; Kostaki, S.; Dourliou, V.; Tsopozidi, M.; Savopoulos, C.; Hatzitolios, A.I. Type 2 diabetes is associated with a worse functional outcome of ischemic stroke. World J. Diabetes 2014, 5, 939–944.
  30. Carter, A.M.; Catto, A.J.; Bamford, J.M.; Grant, P.J. Platelet GP IIIa Pl A and GP Ib Variable Number Tandem Repeat Polymorphisms and Markers of Platelet Activation in Acute Stroke. Arter. Thromb. Vasc. Biol. 1998, 18, 1124–1131.
  31. Hoekstra, T.; Geleijnse, J.M.; Kluft, C.; Giltay, E.J.; Kok, F.J.; Schouten, E.G. 4G/4G Genotype of PAI-1 Gene Is Associated with Reduced Risk of Stroke in Elderly. Stroke 2003, 34, 2822–2828.
  32. Reiner, A.P.; Carty, C.L.; Jenny, N.S.; Nievergelt, C.; Cushman, M.; Stearns-Kurosawa, D.J.; Kurosawa, S.; Kuller, L.H.; Lange, L.A. PROC, PROCR and PROS1 polymorphisms, plasma anticoagulant phenotypes, and risk of cardiovascular disease and mortality in older adults: The Cardiovascular Health Study. J. Thromb. Haemost. 2008, 6, 1625–1632.
  33. Trompet, S.; Pons, D.; Kanse, S.M.; de Craen, A.J.M.; Ikram, M.A.; Verschuren, J.J.W.; Zwinderman, A.H.; Doevendans, P.A.F.M.; Tio, R.A.; de Winter, R.J.; et al. Factor VII Activating Protease Polymorphism (G534E) Is Associated with Increased Risk for Stroke and Mortality. Stroke Res. Treat. 2011, 2011, 1–6.
  34. Lv, W.; Lin, Y.; Song, W.; Sun, K.; Yu, H.; Zhang, Y.; Zhang, C.; Li, L.; Suo, M.; Hui, R.; et al. Variants of COL3A1 Are Associated with the Risk of Stroke Recurrence and Prognosis in the Chinese Population: A Prospective Study. J. Mol. Neurosci. 2014, 53, 196–203.
  35. Martiskainen, M.; Oksala, N.; Pohjasvaara, T.; Kaste, M.; Oksala, A.; Karhunen, P.J.; Erkinjuntti, T. Βeta-fibrinogen gene promoter A −455 allele associated with poor longterm survival among 55–71 years old Caucasian women in Finnish stroke cohort. BMC Neurol. 2014, 14, 137.
  36. Shemirani, A.-H.; Antalfi, B.; Pongrácz, E.; Mezei, Z.A.; Bereczky, Z.; Csiki, Z. Factor XIII-A subunit Val34Leu polymorphism in fatal atherothrombotic ischemic stroke. Blood Coagul. Fibrinolysis 2014, 25, 364–368.
  37. Bouziana, S.D.; Tziomalos, K.; Goulas, A.; Vyzantiadis, T.-A.; Panderi, A.; Hatzitolios, A. Major Adipokines and the −420C>G Resistin Gene Polymorphism as Predictors of Acute Ischemic Stroke Severity and In-Hospital Outcome. J. Stroke Cerebrovasc. Dis. 2018, 27, 963–970.
  38. Feng, C.; Yang, Y.; Yang, S.; Tu, X.; Wang, Y.; Song, Y.; Hui, R.; Zhang, W. Effect of gene–gene and gene–environment interaction on the risk of first-ever stroke and poststroke death. Mol. Genet. Genom. Med. 2019, 7, e846.
  39. Mola-Caminal, M.; Carrera, C.; Soriano-Tárraga, C.; Giralt-Steinhauer, E.; Díaz-Navarro, R.M.; Tur, S.; Jiménez, C.; Medina-Dols, A.; Cullell, N.; Torres-Aguila, N.P.; et al. PATJ Low Frequency Variants Are Associated with Worse Ischemic Stroke Functional Outcome. Circ. Res. 2019, 124, 114–120.
  40. Ryu, C.S.; Bae, J.; Kim, I.J.; Kim, J.; Oh, S.H.; Kim, O.J.; Kim, N.K. MPG and NPRL3 Polymorphisms are Associated with Ischemic Stroke Susceptibility and Post-Stroke Mortality. Diagnostics 2020, 10, 947.
  41. Ryu, C.S.; Oh, S.H.; Lee, K.O.; Park, H.S.; An, H.J.; Lee, J.Y.; Ko, E.J.; Park, H.W.; Kim, O.J.; Kim, N.K. MiR-10a, 27a, 34b/c, and 300 Polymorphisms are Associated with Ischemic Stroke Susceptibility and Post-Stroke Mortality. Life 2020, 10, 309.
  42. Song, L.; Li, H.; Suo, M.; Sun, Y.; Su, M.; Song, Y.; Xiao, N.; Hui, R.; Qin, C.; Chen, J. A functional variant of the long noncoding RNA AL110200 is associated with the risk of ischaemic stroke recurrence. Eur. J. Neurol. 2021, 28, 2708–2715.
  43. Banerjee, C.; Chimowitz, M.I. Stroke Caused by Atherosclerosis of the Major Intracranial Arteries. Circ. Res. 2017, 120, 502–513.
  44. Jüttler, E.; Unterberg, A.; Woitzik, J.; Bösel, J.; Amiri, H.; Sakowitz, O.W.; Gondan, M.; Hill, M.; Limprecht, R.; Luntz, S.; et al. Hemicraniectomy in Older Patients with Extensive Middle-Cerebral-Artery Stroke. N. Engl. J. Med. 2014, 370, 1091–1100.
  45. Norrving, B.; Barrick, J.; Davalos, A.; Dichgans, M.; Cordonnier, C.; Guekht, A.; Kutluk, K.; Mikulik, R.; Wardlaw, J.; Richard, E.; et al. Action Plan for Stroke in Europe 2018–2030. Eur. Stroke J. 2018, 3, 309–336.
  46. Mussbacher, M.; Salzmann, M.; Brostjan, C.; Hoesel, B.; Schoergenhofer, C.; Datler, H.; Hohensinner, P.; Basílio, J.; Petzelbauer, P.; Assinger, A.; et al. Cell Type-Specific Roles of NF-κB Linking Inflammation and Thrombosis. Front. Immunol. 2019, 10, 85.
  47. Harari, O.A.; Liao, J.K. NF-κB and innate immunity in ischemic stroke. Ann. N. Y. Acad. Sci. 2010, 1207, 32–40.
  48. Steffen, B.J.; Breier, G.; Butcher, E.C.; Schulz, M.; Engelhardt, B. ICAM-1, VCAM-1, and MAdCAM-1 are expressed on choroid plexus epithelium but not endothelium and mediate binding of lymphocytes in vitro. Am. J. Pathol. 1996, 148, 1819–1838.
  49. Tang, S.-C.; Arumugam, T.; Xu, X.; Cheng, A.; Mughal, M.R.; Jo, D.-G.; Lathia, J.D.; Siler, D.A.; Chigurupati, S.; Ouyang, X.; et al. Pivotal role for neuronal Toll-like receptors in ischemic brain injury and functional deficits. Proc. Natl. Acad. Sci. USA 2007, 104, 13798–13803.
  50. Nurmi, A.; Lindsberg, P.; Koistinaho, M.; Zhang, W.; Juettler, E.; Karjalainen-Lindsberg, M.-L.; Weih, F.; Frank, N.; Schwaninger, M.; Koistinaho, J. Nuclear Factor-κB Contributes to Infarction After Permanent Focal Ischemia. Stroke 2004, 35, 987–991.
  51. Ali, A.; Shah, F.A.; Zeb, A.; Malik, I.; Alvi, A.M.; AlKury, L.T.; Rashid, S.; Hussain, I.; Ullah, N.; Khan, A.U.; et al. NF-κB Inhibitors Attenuate MCAO Induced Neurodegeneration and Oxidative Stress—A Reprofiling Approach. Front. Mol. Neurosci. 2020, 13, 33.
  52. Kim, S.K.; Jang, H.M.; Kim, D.-Y. The promoter polymorphism of NFKB1 gene contributes to susceptibility of ischemic stroke in Korean population. J. Exerc. Rehabilitation 2018, 14, 1096–1100.
  53. Lanzillotta, A.; Sarnico, I.; Ingrassia, R.; Boroni, F.; Branca, C.; Benarese, M.; Faraco, G.; Blasi, F.; Chiarugi, A.; Spano, P.; et al. The acetylation of RelA in Lys310 dictates the NF-κB-dependent response in post-ischemic injury. Cell Death Dis. 2010, 1, e96, Erratum in 2010, 1, e107.
  54. Inta, I.; Paxian, S.; Maegele, I.; Zhang, W.; Pizzi, M.; Spano, P.; Sarnico, I.; Muhammad, S.; Herrmann, O.; Inta, D.; et al. Bim and Noxa Are Candidates to Mediate the Deleterious Effect of the NF- B Subunit RelA in Cerebral Ischemia. J. Neurosci. 2006, 26, 12896–12903.
  55. Tajalli-Nezhad, S.; Karimian, M.; Beyer, C.; Atlasi, M.A.; Tameh, A.A. The regulatory role of Toll-like receptors after ischemic stroke: Neurosteroids as TLR modulators with the focus on TLR2/4. Experientia 2019, 76, 523–537.
  56. Brea, D.; Blanco, M.; Ramos-Cabrer, P.; Moldes, O.; Arias, S.; Pérez-Mato, M.; Leira, R.; Sobrino, T.; Castillo, J. Toll-like receptors 2 and 4 in ischemic stroke: Outcome and therapeutic values. J. Cereb. Blood Flow Metab. 2011, 31, 1424–1431.
  57. Cao, C.-X.; Yang, Q.-W.; Lv, F.-L.; Cui, J.; Fu, H.-B.; Wang, J.-Z. Reduced cerebral ischemia-reperfusion injury in Toll-like receptor 4 deficient mice. Biochem. Biophys. Res. Commun. 2007, 353, 509–514.
  58. Caso, J.R.; Pradillo, J.M.; Hurtado, O.; Leza, J.C.; Moro, M.A.; Lizasoain, I. Toll-Like Receptor 4 Is Involved in Subacute Stress–Induced Neuroinflammation and in the Worsening of Experimental Stroke. Stroke 2008, 39, 1314–1320.
  59. Kawai, T.; Akira, S. Signaling to NF-κB by Toll-like receptors. Trends Mol. Med. 2007, 13, 460–469.
  60. Lin, Y.-C.; Chang, Y.-M.; Yu, J.-M.; Yen, J.-H.; Chang, J.-G.; Hu, C.-J. Toll-like receptor 4 gene C119A but not Asp299Gly polymorphism is associated with ischemic stroke among ethnic Chinese in Taiwan. Atherosclerosis 2005, 180, 305–309.
  61. Zaremba, J.; Losy, J. Early TNF-α levels correlate with ischaemic stroke severity. Acta Neurol. Scand. 2001, 104, 288–295.
  62. Doll, D.N.; Rellick, S.L.; Barr, T.L.; Ren, X.; Simpkins, J.W. Rapid mitochondrial dysfunction mediates TNF-alpha-induced neurotoxicity. J. Neurochem. 2015, 132, 443–451.
  63. Wu, J.-C.; Zhang, X.; Wang, J.-H.; Liu, Q.-W.; Wang, X.-Q.; Wu, Z.-Q.; Wang, J.; Zhang, C.; Qun, S. Gene polymorphisms and circulating levels of the TNF-alpha are associated with ischemic stroke: A meta-analysis based on 19,873 individuals. Int. Immunopharmacol. 2019, 75, 105827.
  64. Tian, J.; Bai, Y.; You, A.; Shen, R.; Yan, J.; Deng, W.; Wen, L.; Li, M.; Teng, J. Interleukin-17 receptor C gene polymorphism reduces treatment effect and promotes poor prognosis of ischemic stroke. Biosci. Rep. 2019, 39, BSR20190435, Erratum in 2020, 40.
  65. Zhang, Q.; Liao, Y.; Liu, Z.; Dai, Y.; Li, Y.; Li, Y.; Tang, Y. Interleukin-17 and ischaemic stroke. Immunology 2021, 162, 179–193.
  66. Planas, A.M.; Soriano, M.A.; Berruezo, M.; Justicia, C.; Estrada, A.; Pitarch, S.; Ferrer, I. Induction of Stat3, a Signal Transducer and Transcription Factor, in Reactive Microglia following Transient Focal Cerebral Ischaemia. Eur. J. Neurosci. 1996, 8, 2612–2618.
  67. Suzuki, S.; Tanaka, K.; Nogawa, S.; Dembo, T.; Kosakai, A.; Fukuuchi, Y. Phosphorylation of Signal Transducer and Activator of Transcription-3 (Stat3) after Focal Cerebral Ischemia in Rats. Exp. Neurol. 2001, 170, 63–71.
  68. Choi, J.-S.; Kim, S.Y.; Cha, J.-H.; Choi, Y.-S.; Sung, K.-W.; Oh, S.T.; Kim, O.N.; Chung, J.-W.; Chun, M.-H.; Lee, S.B.; et al. Upregulation of gp130 and STAT3 activation in the rat hippocampus following transient forebrain ischemia. Glia 2003, 41, 237–246.
  69. Satriotomo, I.; Bowen, K.K.; Vemuganti, R. JAK2 and STAT3 activation contributes to neuronal damage following transient focal cerebral ischemia. J. Neurochem. 2006, 98, 1353–1368.
  70. Wu, Y.; Xu, J.; Xu, J.; Zheng, W.; Chen, Q.; Jiao, D. Study on the mechanism of JAK2/STAT3 signaling pathway-mediated inflammatory reaction after cerebral ischemia. Mol. Med. Rep. 2018, 17, 5007–5012.
  71. Wang, X.-L.; Qiao, C.-M.; Liu, J.-O.; Li, C.-Y. Inhibition of the SOCS1-JAK2-STAT3 Signaling Pathway Confers Neuroprotection in Rats with Ischemic Stroke. Cell. Physiol. Biochem. 2017, 44, 85–98.
  72. Morris, R.; Kershaw, N.J.; Babon, J.J. The molecular details of cytokine signaling via the JAK/STAT pathway. Protein Sci. 2018, 27, 1984–2009.
  73. Geddes, K.; Magalhães, J.G.; Girardin, S.E. Unleashing the therapeutic potential of NOD-like receptors. Nat. Rev. Drug Discov. 2009, 8, 465–479.
  74. Liu, H.; Wei, X.; Kong, L.; Liu, X.; Cheng, L.; Yan, S.; Zhang, X.; Chen, L. NOD2 is Involved in the Inflammatory Response after Cerebral Ischemia-Reperfusion Injury and Triggers NADPH Oxidase 2-Derived Reactive Oxygen Species. Int. J. Biol. Sci. 2015, 11, 525–535.
  75. Vila, N.; Castillo, J.; Dávalos, A.; Chamorro, A. Proinflammatory Cytokines and Early Neurological Worsening in Ischemic Stroke. Stroke 2000, 31, 2325–2329.
  76. Lv, K.; Yang, Y. Relationship between interleukin-10 polymorphisms and susceptibility to ischemic stroke: A Meta-analysis. Scand. J. Clin. Lab. Investig. 2020, 80, 20–24.
  77. Zhao, X.; Wang, H.; Sun, G.; Zhang, J.; Edwards, N.J.; Aronowski, J. Neuronal Interleukin-4 as a Modulator of Microglial Pathways and Ischemic Brain Damage. J. Neurosci. 2015, 35, 11281–11291.
  78. Xiong, X.; Barreto, G.E.; Xu, L.; Ouyang, Y.B.; Xie, X.S.; Giffard, R.G. Increased Brain Injury and Worsened Neurological Outcome in Interleukin-4 Knockout Mice After Transient Focal Cerebral Ischemia. Stroke 2011, 42, 2026–2032.
  79. Taj, S.H.; Le Blon, D.; Hoornaert, C.; Daans, J.; Quarta, A.; Praet, J.; Van Der Linden, A.; Ponsaerts, P.; Hoehn, M. Targeted intracerebral delivery of the anti-inflammatory cytokine IL13 promotes alternative activation of both microglia and macrophages after stroke. J. Neuroinflam. 2018, 15, 1–17.
  80. Couper, K.; Blount, D.G.; Riley, E.M. IL-10: The Master Regulator of Immunity to Infection. J. Immunol. 2008, 180, 5771–5777.
  81. Pera, J.; Zawadzka, M.; Kaminska, B.; Szczudlik, A. Influence of chemical and ischemic preconditioning on cytokine expression after focal brain ischemia. J. Neurosci. Res. 2004, 78, 132–140.
  82. Bonni, S.; Bonni, A. SnoN signaling in proliferating cells and postmitotic neurons. FEBS Lett. 2012, 586, 1977–1983.
  83. Caraci, F.; Battaglia, G.; Sortino, M.A.; Spampinato, S.F.; Molinaro, G.; Copani, A.; Nicoletti, F.; Bruno, V.M.G. Metabotropic glutamate receptors in neurodegeneration/neuroprotection: Still a hot topic? Neurochem. Int. 2012, 61, 559–565.
  84. Prasad, K.; Kumar, P.; Misra, S.; Kumar, A.; Faruq, M.; Shakya, S.; Vardhan, G.; Vivekanandhan, S.; Srivastava, A.K. Transforming growth factor-β1 (C509T, G800A, and T869C) gene polymorphisms and risk of ischemic stroke in North Indian population: A hospital-based case-control study. Ann. Indian Acad. Neurol. 2017, 20, 5–12.
  85. Konkel, J.E.; Chen, W. Balancing acts: The role of TGF-β in the mucosal immune system. Trends Mol. Med. 2011, 17, 668–676.
  86. Kovacic, P.; Somanathan, R. Cell signaling and receptors in toxicity of advanced glycation end products (AGEs): α-dicarbonyls, radicals, oxidative stress, and antioxidants. J. Recept. Signal Transduct. 2011, 31, 332–339.
  87. Song, L.; Liu, F.-F.; Liu, C.-Y.; Li, X.-P.; Zheng, S.-Z.; Li, Q.-Q.; Liu, Q. Neuroprotective effects of SMADs in a rat model of cerebral ischemia/reperfusion. Neural Regen. Res. 2015, 10, 438–444.
  88. Zhu, H.; Gui, Q.; Hui, X.; Wang, X.; Jiang, J.; Ding, L.; Sun, X.; Wang, Y.; Chen, H. TGF-β1/Smad3 Signaling Pathway Suppresses Cell Apoptosis in Cerebral Ischemic Stroke Rats. Med. Sci. Monit. 2017, 23, 366–376.
  89. Supanc, V.; Biloglav, Z.; Kes, V.B.; Demarin, V. Role of cell adhesion molecules in acute ischemic stroke. Ann. Saudi Med. 2011, 31, 365–370.
  90. Kong, D.-H.; Kim, Y.K.; Kim, M.R.; Jang, J.H.; Lee, S. Emerging Roles of Vascular Cell Adhesion Molecule-1 (VCAM-1) in Immunological Disorders and Cancer. Int. J. Mol. Sci. 2018, 19, 1057.
  91. Kivisäkk, P.; Mahad, D.J.; Callahan, M.K.; Trebst, C.; Tucky, B.; Wei, T.; Wu, L.; Baekkevold, E.S.; Lassmann, H.; Staugaitis, S.M.; et al. Human cerebrospinal fluid central memory CD4+T cells: Evidence for trafficking through choroid plexus and meninges via P-selectin. Proc. Natl. Acad. Sci. USA 2003, 100, 8389–8394.
  92. Maglinger, B.; Sands, M.; Frank, J.A.; McLouth, C.J.; Trout, A.L.; Roberts, J.M.; Grupke, S.; Turchan-Cholewo, J.; Stowe, A.M.; Fraser, J.F.; et al. Intracranial VCAM1 at time of mechanical thrombectomy predicts ischemic stroke severity. J. Neuroinflam. 2021, 18, 1–13.
  93. Frijns, C.; Kappelle, L. Inflammatory Cell Adhesion Molecules in Ischemic Cerebrovascular Disease. Stroke 2002, 33, 2115–2122.
  94. Castillo, J.; Álvarez-Sabín, J.; Martínez-Vila, E.; Montaner, J.; Sobrino, T.; Vivancos, J. Inflammation markers and prediction of post-stroke vascular disease recurrence: The MITICO study. J. Neurol. 2009, 256, 217–224.
  95. Levine, S.R.; Brey, R.L.; Tilley, B.C.; Thompson, J.L.P.; Sacco, R.L.; Sciacca, R.R.; Murphy, A.; Lu, Y.; Costigan, T.M.; Rhine, C.; et al. Antiphospholipid Antibodies and Subsequent Thrombo-occlusive Events in Patients with Ischemic Stroke. JAMA 2004, 291, 576–584.
  96. Bushnell, C.; Siddiqi, Z.; Morgenlander, J.C.; Goldstein, L.B. Use of specialized coagulation testing in the evaluation of patients with acute ischemic stroke. Neurology 2001, 56, 624–627.
  97. Bushnell, C.D.; Siddiqi, Z.; Goldstein, L.B. Improving patient selection for coagulopathy testing in the setting of acute ischemic stroke. Neurology 2001, 57, 1333–1335.
  98. Patel, M.L.; Sachan, R.; Seth, G. Combined deficiency of proteins C and S: Ischaemic stroke in young individuals. BMJ Case Rep. 2013, 2013, bcr2012008016.
  99. Luo, G.-P.; Ni, B.; Yang, X.; Wu, Y.-Z. von Willebrand Factor: More Than a Regulator of Hemostasis and Thrombosis. Acta Haematol. 2012, 128, 158–169.
  100. Gragnano, F.; Sperlongano, S.; Golia, E.; Natale, F.; Bianchi, R.; Crisci, M.; Fimiani, F.; Pariggiano, I.; Diana, V.; Carbone, A.; et al. The Role of von Willebrand Factor in Vascular Inflammation: From Pathogenesis to Targeted Therapy. Mediat. Inflamm. 2017, 2017, 1–13.
  101. Sidelmann, J.J.; Gram, J.B.; Jespersen, J.; Kluft, C. Fibrin Clot Formation and Lysis: Basic Mechanisms. Semin. Thromb. Hemost. 2000, 26, 605–618.
  102. Kozuka, K.; Kohriyama, T.; Nomura, E.; Ikeda, J.; Kajikawa, H.; Nakamura, S. Endothelial markers and adhesion molecules in acute ischemic stroke—sequential change and differences in stroke subtype. Atherosclerosis 2002, 161, 161–168.
  103. Hanson, E.; Jood, K.; Karlsson, S.; Nilsson, S.; Blomstrand, C.; Jern, C. Plasma levels of von Willebrand factor in the etiologic subtypes of ischemic stroke. J. Thromb. Haemost. 2011, 9, 275–281.
  104. Ancedy, Y.; Berthelot, E.; Lang, S.; Ederhy, S.; Boyer-Chatenet, L.; Di Angelantonio, E.; Dufour, L.S.; Etienney, A.; Adavane-Scheublé, S.; Boccara, F.; et al. Is von Willebrand factor associated with stroke and death at mid-term in patients with non-valvular atrial fibrillation? Arch. Cardiovasc. Dis. 2018, 111, 357–369.
  105. Tóth, N.K.; Székely, E.G.; Czuriga-Kovács, K.R.; Sarkady, F.; Nagy, O.; Lánczi, L.I.; Berényi, E.; Fekete, K.; Fekete, I.; Csiba, L.; et al. Elevated Factor VIII and von Willebrand Factor Levels Predict Unfavorable Outcome in Stroke Patients Treated with Intravenous Thrombolysis. Front. Neurol. 2018, 8, 721.
  106. Dirks, M.; Grosse, G.M.; Böckmann, M.; Goetz, F.; Pasedag, T.; Bode-Böger, S.M.; Martens-Lobenhoffer, J.; Budde, U.; Lanfermann, H.; Lichtinghagen, R.; et al. ADAMTS-13 Activity Predicts Outcome in Acute Ischaemic Stroke Patients Undergoing Endovascular Treatment. Thromb. Haemost. 2018, 47, 758–767.
  107. Dai, K.; Gao, W.; Ruan, C. The Sma I Polymorphism in the von Willebrand Factor Gene Associated with Acute Ischemic Stroke. Thromb. Res. 2001, 104, 389–395.
  108. De Meyer, S.F.; Stoll, G.; Wagner, D.D.; Kleinschnitz, C. von Willebrand Factor. Stroke 2012, 43, 599–606.
  109. Drouet, L. Fibrinogen: A Treatable Risk Factor? Cerebrovasc. Dis. 1996, 6, 2–6.
  110. Pieters, M.; Wolberg, A.S. Fibrinogen and fibrin: An illustrated review. Res. Pr. Thromb. Haemost. 2019, 3, 161–172.
  111. Rallidis, L.S.; Vikelis, M.; Panagiotakos, D.B.; Liakos, G.K.; Krania, E.; Kremastinos, D.T. Usefulness of inflammatory and haemostatic markers to predict short-term risk for death in middle-aged ischaemic stroke patients. Acta Neurol. Scand. 2008, 117, 415–420.
  112. Swarowska, M.; Polczak, A.; Pera, J.; Klimkowicz-Mrowiec, A.; Slowik, A.; Dziedzic, T. Hyperfibrinogenemia predicts long-term risk of death after ischemic stroke. J. Thromb. Thrombolysis 2014, 38, 517–521.
  113. Di Napoli, M.; Papa, F. Inflammation, Hemostatic Markers, and Antithrombotic Agents in Relation to Long-Term Risk of New Cardiovascular Events in First-Ever Ischemic Stroke Patients. Stroke 2002, 33, 1763–1771.
  114. Pikija, S.; Trkulja, V.; Mutzenbach, J.S.; McCoy, M.R.; Ganger, P.; Sellner, J. Fibrinogen consumption is related to intracranial clot burden in acute ischemic stroke: A retrospective hyperdense artery study. J. Transl. Med. 2016, 14, 250.
  115. Beamer, N.B.; Coull, B.M.; Clark, W.M.; Hazel, J.S.; Silberger, J.R. Interleukin-6 and interleukin-1 receptor antagonist in acute stroke. Ann. Neurol. 1995, 37, 800–805.
  116. Di Napoli, M.; Papa, F.; Bocola, V. Prognostic Influence of Increased C-Reactive Protein and Fibrinogen Levels in Ischemic Stroke. Stroke 2001, 32, 133–138.
  117. Di Napoli, M.; Singh, P. Is Plasma Fibrinogen Useful in Evaluating Ischemic Stroke Patients? Stroke 2009, 40, 1549–1552.
  118. Feinberg, W.M.; Erickson, L.P.; Bruck, D.; Kittelson, J. Hemostatic Markers in Acute Ischemic Stroke. Stroke 1996, 27, 1296–1300.
  119. Barber, M.; Langhorne, P.; Rumley, A.; Lowe, G.D.; Stott, D.J. D-dimer predicts early clinical progression. Stroke 2004, 35, 1421–1425.
  120. Carter, A.M.; Catto, A.J.; Mansfield, M.; Bamford, J.M.; Grant, P.J. Predictive Variables for Mortality After Acute Ischemic Stroke. Stroke 2007, 38, 1873–1880.
  121. Montaner, J.; Molina, C.A.; Arenillas, J.F.; Santamarina, E.; Alvarez-Sabín, J.; Ribo, M. Admission fibrinolytic profile predicts clot lysis resistance in stroke patients treated with tissue plasminogen activator. Thromb. Haemost. 2004, 91, 1146–1151.
  122. Merino, P.; Díaz, A.; Yepes, M. Urokinase-type Plasminogen Activator (uPA) and its Receptor (uPAR) Promote Neurorepair in the Ischemic Brain. Recept. Clin. Investig. 2017, 4, e1552.
  123. Diaz, A.; Merino, P.; Manrique, L.G.; Cheng, L.; Yepes, M. Urokinase-type plasminogen activator (uPA) protects the tripartite synapse in the ischemic brain via ezrin-mediated formation of peripheral astrocytic processes. Br. J. Pharmacol. 2019, 39, 2157–2171.
  124. Menshikov, M.; Plekhanova, O.; Cai, H.; Chalupsky, K.; Parfyonova, Y.; Bashtrikov, P.; Tkachuk, V.; Berk, B.C. Urokinase Plasminogen Activator Stimulates Vascular Smooth Muscle Cell Proliferation Via Redox-Dependent Pathways. Arter. Thromb. Vasc. Biol. 2006, 26, 801–807.
  125. Kim, S.-H.; Turnbull, J.; Guimond, S. Extracellular matrix and cell signalling: The dynamic cooperation of integrin, proteoglycan, and growth factor receptor. J. Endocrinol. 2011, 209, 139–151.
  126. Guell, K.; Bix, G.J. Brain endothelial cell specific integrins and ischemic stroke. Expert Rev. Neurother. 2014, 14, 1287–1292.
  127. Edwards, D.N.; Bix, G.J. Roles of blood-brain barrier integrins and extracellular matrix in stroke. Am. J. Physiol. Physiol. 2019, 316, C252–C263.
  128. Edwards, D.N.; Bix, G.J. The Inflammatory Response After Ischemic Stroke: Targeting β2 and β1 Integrins. Front. Neurosci. 2019, 13, 540.
  129. Baeten, K.M.; Akassoglou, K. Extracellular matrix and matrix receptors in blood-brain barrier formation and stroke. Dev. Neurobiol. 2011, 71, 1018–1039.
  130. Yang, C.; Hawkins, K.E.; Doré, S.; Candelario-Jalil, E. Neuroinflammatory mechanisms of blood-brain barrier damage in ischemic stroke. Am. J. Physiol. Physiol. 2019, 316, C135–C153.
  131. Kusindarta, D.; Wihadmadyatami, H. The Role of Extracellular Matrix in Tissue Regeneration. IntechOpen Book Series. Open access peer-reviewed paper. 2018. Available online: (accessed on 19 September 2021).
  132. Paar, M.; Rossmann, C.; Nusshold, C.; Wagner, T.; Schlagenhauf, A.; Leschnik, B.; Oettl, K.; Koestenberger, M.; Cvirn, G.; Hallström, S. Anticoagulant action of low, physiologic, and high albumin levels in whole blood. PLoS ONE 2017, 12, e0182997.
  133. Rogers, K. Serum Albumin. In Encyclopaedia Britannica; Encyclopaedia Britannica, Inc.: London, UK, 2018; Available online: www.britannica.cpm/science/serum-albumin (accessed on 30 August 2021).
  134. Greenberg, D.A.; Jin, K. Vascular endothelial growth factors (VEGFs) and stroke. Cell. Mol. Life Sci. 2013, 70, 1753–1761.
  135. Kim, O.J.; Hong, S.H.; Oh, S.H.; Kim, T.G.; Min, K.T.; Oh, D.; Kim, N.K. Association Between VEGF Polymorphisms and Homocysteine Levels in Patients with Ischemic Stroke and Silent Brain Infarction. Stroke 2011, 42, 2393–2402.
  136. Vallance, T.M.; Zeuner, M.-T.; Williams, H.F.; Widera, D.; Vaiyapuri, S. Toll-Like Receptor 4 Signalling and Its Impact on Platelet Function, Thrombosis, and Haemostasis. Mediat. Inflamm. 2017, 2017, 1–13.
  137. Zhang, S.; Zhang, S.; Hu, L.; Zhai, L.; Xue, R.; Ye, J.; Chen, L.; Cheng, G.; Mruk, J.; Kunapuli, S.P.; et al. Nucleotide-Binding Oligomerization Domain 2 Receptor Is Expressed in Platelets and Enhances Platelet Activation and Thrombosis. Circulation 2015, 131, 1160–1170.
  138. Van der Poll, T.; Jansen, P.M.; Van Zee, K.J.; Welborn, M.B., 3rd; de Jong, I.; Hack, C.E.; Loetscher, H.; Lesslauer, W.; Lowry, S.F.; Moldawer, L.L. Tumor necrosis factor-alpha induces activation of coagulation and fibrinolysis in baboons through an exclusive effect on the p55 receptor. Blood 1996, 88, 922–927.
  139. Fateh-Moghadam, S.; Li, Z.; Ersel, S.; Reuter, T.; Htun, P.; Plöckinger, U.; Bocksch, W.; Dietz, R.; Gawaz, M. Platelet Degranulation Is Associated with Progression of Intima-Media Thickness of the Common Carotid Artery in Patients with Diabetes Mellitus Type 2. Arter. Thromb. Vasc. Biol. 2005, 25, 1299–1303.
  140. Foley, J.; Conway, E.M. Cross Talk Pathways Between Coagulation and Inflammation. Circ. Res. 2016, 118, 1392–1408.
  141. Ma, S.; Snyder, M.; Dinesh-Kumar, S.P. Discovery of Novel Human Gene Regulatory Modules from Gene Co-expression, and Promoter Motif Analysis. Sci. Rep. 2017, 7, 1–16.
  142. DeGracia, D.J. Regulation of mRNA following brain ischemia and reperfusion. Wiley Interdiscip. Rev. RNA 2017, 8, e1415.
  143. DeGracia, N.J. Disease of mRNA Regulation: Relevance for Ischemic Brain Injury. Transl. Stroke Res. 2018, 9, 251–257.
  144. Khajavi, M.; Inoue, K.; Lupski, J.R. Nonsense-mediated mRNA decay modulates clinical outcome of genetic disease. Eur. J. Hum. Genet. 2006, 14, 1074–1081.
  145. Gu, Z.; Li, Z.; Xu, R.; Zhu, X.; Hu, R.; Xue, Y.; Xu, W. miR-16-5p Suppresses Progression and Invasion of Osteosarcoma via Targeting at Smad3. Front. Pharmacol. 2020, 26, 11.
  146. Zhou, R.; Li, X.; Hu, G.; Gong, A.-Y.; Drescher, K.M.; Chen, X.-M. miR-16 Targets Transcriptional Corepressor SMRT and Modulates NF-kappaB-Regulated Transactivation of Interleukin-8 Gene. PLoS ONE 2012, 7, e30772.
  147. Xu, H.; Zhang, J.; Ma, Y.; Gu, J.; Jing, X.; Lu, S.; Chen, X.; Yang, W.; Bian, Y.; Fu, S. The Identification and Verification of Key Long Noncoding RNAs in Ischemic Stroke. BioMed Res. Int. 2020, 2020, 1–10.
  148. Su, Z.-F.; Sun, Z.-W.; Zhang, Y.; Wang, S.; Yu, Q.-G.; Wu, Z.-B. Regulatory effects of miR-146a/b on the function of endothelial progenitor cells in acute ischemic stroke in mice. Kaohsiung J. Med. Sci. 2017, 33, 369–378.
  149. Koutsis, G.; Siasos, G.; Spengos, K. The emerging role of microRNA in stroke. Curr. Top. Med. Chem. 2013, 13, 1573–1588.
  150. Wu, J.; Du, K.; Lu, X. Elevated expressions of serum miR-15a, miR-16, and miR-17-5p are associated with acute ischemic stroke. Int. J. Clin. Exp. Med. 2015, 8, 21071–21079.
Contributor MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to :
View Times: 381
Entry Collection: Neurodegeneration
Revisions: 3 times (View History)
Update Date: 17 Nov 2021
Video Production Service