Intrinsic Coagulation Pathway, History of Headache, and Risk of Ischemic Stroke

Diagnostic value of coagulation index and serum inflammatory cytokines in hemorrhagic stroke patients with pulmonary infection in the sequelae stage

BACKGROUND

Stroke is the second reason for global deaths and a major reason for disabilities.

OBJECTIVE

To unravel the clinical value of the coagulation index and serum inflammatory cytokines in hemorrhagic stroke patients with pulmonary infection in the sequelae stage.

METHODS

Altogether, 130 hemorrhagic stroke patients who received treatment in Hebei General Hospital from April 2019 to December 2020 were selected. Patients were classified into the infection group (n= 65) and non-infection group (n= 65) according to whether they had a pulmonary infection in the sequelae stage of hemorrhagic stroke. Levels of coagulation index and serum inflammatory cytokines of patients in two groups were compared. Multiple linear regression analysis was used to analyze pulmonary infection-related factors of hemorrhagic stroke patients. The diagnostic value of the coagulation index and serum inflammatory cytokines in pulmonary infection was analyzed by the receiver operating characteristic (ROC) curve.

RESULTS

Prothrombin time (PT), activated partial thromboplastin time (APTT), fibrinogen (FIB), D-dimer (D-D), platelet (PLT) related to coagulation function levels and interleukin 1β (IL-1β), interleukin 17 (IL-17) related to serum inflammatory cytokines levels of patients in the infection group were higher than those in non-infection groups (p< 0.05). Multiple linear regression analysis uncovered that FIB, D-D, PLT, and IL-17 were influencing factors of pulmonary infection in the sequelae of patients with hemorrhagic stroke (p< 0.05). Area under the curve (AUC) values of pulmonary infection in the sequelae stage of patients with hemorrhagic stroke diagnosed by FIB, D-D, PLT, and IL-17 were 0.823, 0.758, 0.660, and 0.755, respectively.

CONCLUSION

FIB, D-D, PLT, and IL-17 levels could be used for pulmonary infection diagnosis in the sequelae stage of hemorrhagic stroke patients.

Association Between Prekallikrein and Stroke: A Mendelian Randomization Study

Background High plasma prekallikrein was reported to be associated with increased risks of stroke, but the causality for these associations remains unclear. We aimed to investigate the associations of genetically predicted plasma prekallikrein concentrations with all-cause stroke, ischemic stroke, 3 ischemic stroke subtypes, and intracerebral hemorrhage (ICH) using a 2-sample Mendelian randomization approach. Methods and Results Seven independent prekallikrein-related single-nucleotide polymorphisms were identified as genetic instruments for prekallikrein based on a genome-wide association study with 1000 European individuals. The summary statistics for all-cause stroke, ischemic stroke, and ischemic stroke subtypes were obtained from the Multiancestry Genome-wide Association Study of Stroke Consortium with 40 585 cases and 406 111 controls of European ancestry. The summary statistics for ICH were obtained from the ISGC (International Stroke Genetics Consortium) with 1545 ICH cases and 1481 controls of European ancestry. In the main analysis, the inverse-variance weighted method was applied to estimate the associations of plasma prekallikrein concentrations with all-cause stroke, ischemic stroke, ischemic stroke subtypes, and ICH. Genetically predicted high plasma prekallikrein levels were significantly associated with elevated risks of all-cause stroke (odds ratio [OR] per SD increase, 1.04 [95% CI, 1.02-1.06]; P=5.44×10-5), ischemic stroke (OR per SD increase, 1.05 [95% CI, 1.03-1.07]; P=1.42×10-5), cardioembolic stroke (OR per SD increase, 1.08 [95% CI, 1.03-1.12]; P=3.75×10-4), and small vessel stroke (OR per SD increase, 1.11 [95% CI, 1.06-1.17]; P=3.02×10-5). However, no significant associations were observed for genetically predicted prekallikrein concentrations with large artery stroke and ICH. Conclusions This Mendelian randomization study found that genetically predicted high plasma prekallikrein concentrations were associated with increased risks of all-cause stroke, ischemic stroke, cardioembolic stroke, and small vessel stroke, indicating that prekallikrein might have a critical role in the development of stroke.

Differential Regulation of the Immune System in Peripheral Blood Following Ischemic Stroke

Method

108 IS samples and 47 matched controls were obtained from the GEO database. Immune-related genes (IRGs) and their associated drugs were collected from the ImmPort and PharmGBK databases, respectively. Random forest (RF) regression and least absolute shrinkage and selection operator (LASSO) logistic regression were applied to identify immune-related genetic biomarkers (IRGBs) of IS, and accuracy was verified using neural network models. Finally, proportion changes of various immune cells in peripheral blood of IS patients were evaluated using CIBERSORT and xCell and correlation analyses were performed between IRGBs and differentially distributed immune cells.

Results

A total of 537 genes were differentially expressed between IS and control samples. Four immune-related differential expressed genes identified by regression analysis presented strong predictive power (AUC = 0.909) which we suggeseted them as immune-related genetic biomarkers (IRGBs). We also demonstrated six immune-related genes targeted by known drugs. In addition, post-IS immune system presented an increase in the proportion of innate immune cells and a decrease in adaptive immune cells in the peripheral circulation, and IRGBs showing significance were associated with this process.

Conclusion

The study identified CARD11, ICAM2, VIM, and CD19 as immune-related genetic biomarkers of IS. Six immune-related DEGs targeted by known drugs were found and provide new candidate drug targets for modulating the post-IS immune system. The innate immune cells and adaptive immune cells are diversified in the post-IS immune system, and IRGBs might play important role during this process.

Integrating serum proteomics and metabolomics to compare the common and distinct features between acute aggressive ischemic stroke (APIS) and acute non-aggressive ischemic stroke (ANPIS)

Understanding common and distinct pathophysiological features between acute progressive ischemic stroke (APIS) and acute non-progressive ischemic stroke (ANPIS) is a prerequisite to making clear the mechanism to determine the prognosis of acute ischemic stroke (AIS). Here, we recruited three independent sets of subjects, all of which included the APIS, ANPIS, and control groups. They were used for serum proteomic and metabolomic analyses, and validation of the critical pathophysiological processes and potential biomarkers of APIS, respectively. Results showed that there were both common and distinct metabolome and proteome between APIS and ANPIS. APIS and ANPIS shared basic processes of AIS in inflammation and oxidative stress response. Coagulation and lipid metabolism disorder, activation of the complement system, and inflammation may enhance with each other in the symptom worsening of APIS. The contents of serum amyloid A1 (SAA1) and S100 calcium-binding protein A9 (S100-A9) in the validation set confirmed the key pathophysiological processes indicated by omics data; they also jointly conferred a moderate value to distinguish APIS from ANPIS. Collectively, disturbance in coagulation and lipid metabolism, complement activation, and inflammation may be synergistically involved in symptom deterioration in APIS. SAA1 and S100-A9 serve as a potential biomarker panel to distinguish APIS from ANPIS. THE SIGNIFICANCE: In this study, we integrated serum proteomics and metabolomics to explore the similarities and differences in pathophysiological processes between APIS and ANPIS. The global metabolic networks have been constructed, and the crucial common pathophysiological processes and the key distinct pathophysiological features between APIS and ANPIS were investigated based on the differentially expressed proteins and metabolites (DEPs/DEMs). Furthermore, pivotal serum proteins (SAA1 and S100A9) were detected in a dependent set to validate the key pathophysiological characteristics, as well as to assess the possibility of them being used as a biomarker panel. Taken together, the multi-omics integration strategy used in this clinical study shows potential to comprehensively interpret and compare the pathophysiological processes of AIS in various conditions, as well as to screen a reliable new biomarker panel.

Headache as a Neurologic Manifestation of Systemic Disease

Purpose of Review

Recent Findings

Summary

Elevated microglial oxidative phosphorylation and phagocytosis stimulate post-stroke brain remodeling and cognitive function recovery in mice

New research shows that disease-associated microglia in neurodegenerative brains present features of elevated phagocytosis, lysosomal functions, and lipid metabolism, which benefit brain repair. The underlying mechanisms remain poorly understood. Intracellular pH (pH_i) is important for regulating aerobic glycolysis in microglia, where Na/H exchanger (NHE1) is a key pH regulator by extruding H⁺ in exchange of Na⁺ influx. We report here that post-stroke Cx3cr1-Cre^ER+/-;Nhe1^flox/flox (Nhe1 cKO) brains displayed stimulation of microglial transcriptomes of rate-limiting enzyme genes for glycolysis, tricarboxylic acid cycle, and oxidative phosphorylation. The other upregulated genes included genes for phagocytosis and LXR/RXR pathway activation as well as the disease-associated microglia hallmark genes (Apoe, Trem2, Spp1). The cKO microglia exhibited increased oxidative phosphorylation capacity, and higher phagocytic activity, which likely played a role in enhanced synaptic stripping and remodeling, oligodendrogenesis, and remyelination. This study reveals that genetic blockade of microglial NHE1 stimulated oxidative phosphorylation immunometabolism, and boosted phagocytosis function which is associated with tissue remodeling and post-stroke cognitive function recovery.

The Influence of Different Types of Diabetes on Vascular Complications

The final outcome of diabetes is chronic complications, of which vascular complications are the most serious, which is the main cause of death for diabetic patients and the direct cause of the increase in the cost of diabetes. Type 1 and type 2 diabetes are the main types of diabetes, and their pathogenesis is completely different. Type 1 diabetes is caused by genetics and immunity to destroy a large number of β cells, and insulin secretion is absolutely insufficient, which is more prone to microvascular complications. Type 2 diabetes is dominated by insulin resistance, leading to atherosclerosis, which is more likely to progress to macrovascular complications. This article explores the pathogenesis of two types of diabetes, analyzes the pathogenesis of different vascular complications, and tries to explain the different trends in the progression of different types of diabetes to vascular complications, in order to better prevent diabetes and its vascular complications.

Covert Brain Infarcts in Patients with Philadelphia Chromosome-Negative Myeloproliferative Disorders

Backgrounds and Purpose. Philadelphia chromosome-negative myeloproliferative disorders (Ph-negative MPD) are a rare group of hematological diseases, including three distinct pathologies: essential thrombocythemia (ET), polycythemia vera (PV), and primary myelofibrosis (PMF). They most often manifest with thrombotic complications, including cerebrovascular events. Covert brain infarcts (CBIs) are defin ed as predominantly small ischemic cerebral lesions that are detected using magnetic resonance imaging (MRI) in the absence of clinical stroke events. The relationship between MPD and CBIs remains unclear. Methods. Included in the study were 103 patients with the diagnosis of Ph-MPD (according to WHO 2016 criteria) (median age—47 (35; 54) years; 67% female). In total, 38 patients had ET, 42 had PV, and 23 had PMF. They underwent clinical examination, routine laboratory analyses (complete blood count), brain MRI, ultrasound carotid artery, flow-mediated dilatation (as a measure of endothelial dysfunction—FMD). Results. Overall, 23 patients experienced an ischemic stroke (as per MRI and/or clinical history), of which 16 (15.5%) could be classified as CBIs. The rate of CBIs per MPD subtype was statistically non-significant between groups (p = 0.35): ET–13.2%, PV–21.4%, and PMF–8.7%. The major vascular risk factors, including arterial hypertension, carotid atherosclerosis, and prior venous thrombosis, were not associated with CBIs (p > 0.05). Age was significantly higher in patients with CBIs compared to patients without MRI ischemic lesions: 50 (43; 57) years vs. 36 (29; 48) (p = 0.002). The frequency of headaches was comparable between the two groups. CBIs were associated with endothelial dysfunction (OR - 0.71 (95% CI: 0.49–0.90; p = 0.02)) and higher hemoglobin levels (OR—1.21 (95% CI: 1.06–1.55); p =0.03). Conclusions. CBIs are common in patients with Ph-negative MPD. Arterial hypertension and carotid atherosclerosis were not associated with CBIs in this group of patients. The most significant factors in the development of CBIs were endothelial dysfunction (as measured by FMD) and high hemoglobin levels. Patients with Ph-negative MPD and CBIs were older and had more prevalent endothelial dysfunction.

Associations of coagulation factor X and XI with incident acute coronary syndrome and stroke: A nested case-control study

BACKGROUND

Coagulation cascade contributes to thrombotic and hemorrhagic diseases, but it remains unclear whether coagulation factors X (FX) and XI (FXI) levels are associated with cardiovascular diseases.

OBJECTIVE

To evaluate prospective associations of FX and FXI levels with incident acute coronary syndrome (ACS), stroke, and their subtypes (acute myocardial infarction, unstable angina, ischemic stroke, and hemorrhagic stroke).

METHODS

We performed a nested case-control study (n = 1846) within the Dongfeng-Tongji cohort from 2013 to 2016 matched on age (within 1 year), sex, and sampling date (within 1 month) by incidence density sampling, and measured plasma FX and FXI levels by enzyme-linked immunosorbent assay. FX and FXI levels were categorized into three groups (low, <25th; middle, 25th to <75th; and high ≥75th percentiles) according to distributions, and conditional logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

After adjustment for traditional cardiovascular risk factors, compared with middle groups, the OR (95% CI) in high levels of FX and FXI were 1.11 (0.79-1.56) and 0.96 (0.68-1.36) for incident ACS, and 1.01 (0.63-1.62) and 1.72 (1.14-2.60) for incident stroke, respectively. As for subtypes of ACS and stroke, only high FXI levels were significantly associated with incident ischemic stroke (OR 1.66, 95% CI 1.05-2.65). Moreover, all associations remained steady after additional adjustment for platelet and leukocyte.

CONCLUSION

FXI levels were associated with a greater risk of incident ischemic stroke but not hemorrhagic stroke or ACS. FX levels were not associated with incident ACS or stroke.