Stroke-induced hexokinase 2 in circulating monocytes exacerbates vascular inflammation and atheroprogression

Exploring Genetic Associations of 3 Types of Risk Factors With Ischemic Stroke: An Integrated Bioinformatics Study

BACKGROUND

Ischemic stroke (IS) is a major cause of disability and mortality worldwide. Increasing evidence suggests a strong association between blood pressure, blood glucose, circulating lipids, and IS. Nonetheless, the genetic association of these 3 risk factors with IS remains elusive.

METHODS

We screened genetic instruments related to blood pressure, blood glucose, and circulating lipids and paired them with IS genome-wide association study data to conduct Mendelian randomization analysis. Positive Mendelian randomization findings were then subjected to colocalization analysis. Subsequently, we utilized the Gene Expression Omnibus data set to perform differential expression analysis, aiming to identify differentially expressed associated genes. We determined the importance scores of these differentially expressed associated genes through 4 machine learning models and constructed a nomogram based on these findings.

RESULTS

The combined results of the Mendelian randomization analysis indicate that blood pressure (systolic blood pressure: odds ratio [OR], 1.02 [95% CI, 1.01-1.02]; diastolic blood pressure: OR, 1.03 [95% CI, 1.03-1.04]) and some circulating lipids (low-density lipoprotein cholesterol: OR, 1.06 [95% CI, 1.01-1.12]; apoA1: OR, 0.95 [95% CI, 0.92-0.98]; apoB: OR, 1.05 [95% CI, 1.01-1.09]; eicosapentaenoic acid: OR, 2.36 [95% CI, 1.41-3.96]) have causal relationships with the risk of IS onset. We identified 73 genes that are linked to blood pressure and circulating lipids in the context of IS, and 16 are differentially expressed associated genes. FURIN, MAN2A2, HDDC3, ALDH2, and TOMM40 were identified as feature genes for constructing the nomogram that provides a quantitative prediction of the risk of IS onset.

CONCLUSIONS

This study indicates that there are causal links between blood pressure, certain circulating lipids, and the development of IS. The potential mechanisms underlying these causal relationships involve the regulation of lipid metabolism, blood pressure, DNA repair and methylation, cell apoptosis and autophagy, immune inflammation, and neuronal protection, among others.

HMGB1: A New Target for Ischemic Stroke and Hemorrhagic Transformation

Stroke in China is distinguished by its high rates of morbidity, recurrence, disability, and mortality. The ultra-early administration of rtPA is essential for restoring perfusion in acute ischemic stroke, though it concurrently elevates the risk of hemorrhagic transformation. High-mobility group box 1 (HMGB1) emerges as a pivotal player in neuroinflammation after brain ischemia and ischemia-reperfusion. Released passively by necrotic cells and actively secreted, including direct secretion of HMGB1 into the extracellular space and packaging of HMGB1 into intracellular vesicles by immune cells, glial cells, platelets, and endothelial cells, HMGB1 represents a prototypical damage-associated molecular pattern (DAMP). It is intricately involved in the pathogenesis of atherosclerosis, thromboembolism, and detrimental inflammation during the early phases of ischemic stroke. Moreover, HMGB1 significantly contributes to neurovascular remodeling and functional recovery in later stages. Significantly, HMGB1 mediates hemorrhagic transformation by facilitating neuroinflammation, directly compromising the integrity of the blood-brain barrier, and enhancing MMP9 secretion through its interaction with rtPA. As a systemic inflammatory factor, HMGB1 is also implicated in post-stroke depression and an elevated risk of stroke-associated pneumonia. The role of HMGB1 extends to influencing the pathogenesis of ischemia by polarizing various subtypes of immune and glial cells. This includes mediating excitotoxicity due to excitatory amino acids, autophagy, MMP9 release, NET formation, and autocrine trophic pathways. Given its multifaceted role, HMGB1 is recognized as a crucial therapeutic target and prognostic marker for ischemic stroke and hemorrhagic transformation. In this review, we summarize the structure and redox properties, secretion and pathways, regulation of immune cell activity, the role of pathophysiological mechanisms in stroke, and hemorrhage transformation for HMGB1, which will pave the way for developing new neuroprotective drugs, reduction of post-stroke neuroinflammation, and expansion of thrombolysis time window.

High serum lactate dehydrogenase to albumin ratio is associated with increased risk of poor prognosis after ischemic stroke

BACKGROUND

Lactate dehydrogenase to albumin ratio (LAR) is a comprehensive biomarker for anaerobiosis, inflammation, and nutritional status, but its prognostic value for ischemic stroke has rarely been reported. We aimed to prospectively investigate whether serum LAR is associated with the prognosis of ischemic stroke patients in a large-scale cohort study.

MATERIALS AND METHODS

Serum LAR levels were measured among 6634 patients with ischemic stroke admitted at Minhang hospital from January 2018 to December 2022. The primary outcome was the composite of major disability and death (modified Rankin Scale score [mRS] ≥ 3) at 3-month follow up. Secondary outcomes included death and the ordered 7-level category score of mRS. Multivariate logistic regression and restricted cubic splines were adopted to evaluate the associations between serum LAR levels and adverse clinical outcomes of ischemic stroke.

RESULTS

During 3 months of follow-up period, a total of 2125 patients experienced primary outcome. After multivariate adjustment, the highest quartile of serum LAR was associated with an increased risk of primary outcome (odds ratio [OR], 1.52; 95% confidence interval [CI], 1.27-1.83; P for trend < 0.001). Each standard deviation higher log-transformed serum LAR resulted in a 20% (95% CI, 12%-28%) increased risk of primary outcome. Furthermore, multivariable-adjusted restricted cubic spline analyses showed a linear association between the serum LAR level with primary outcome (P for linearity < 0.001). Finally, the addition of serum LAR to conventional risk factors significantly improved risk predictive abilities for the primary outcome (net reclassification improvement [NRI]: 18.35%, P < 0.001; integrated discrimination improvement [IDI]: 0.35%, P < 0.001) at 3-month follow up in patients with ischemic stroke.

CONCLUSION

High serum LAR level was independently associated with an increased risk of adverse clinical outcomes among patients with ischemic stroke, indicating that serum LAR may be a valuable prognostic biomarker for ischemic stroke.

A Nomogram for Predicting the Recurrence of Acute Non-Cardioembolic Ischemic Stroke: A Retrospective Hospital-Based Cohort Analysis

Non-cardioembolic ischemic stroke (IS) is the predominant subtype of IS. This study aimed to construct a nomogram for recurrence risks in patients with non-cardioembolic IS in order to maximize clinical benefits. From April 2015 to December 2019, data from consecutive patients who were diagnosed with non-cardioembolic IS were collected from Lanzhou University Second Hospital. The least absolute shrinkage and selection operator (LASSO) regression analysis was used to optimize variable selection. Multivariable Cox regression analyses were used to identify the independent risk factors. A nomogram model was constructed using the "rms" package in R software via multifactor Cox regression. The accuracy of the model was evaluated using the receiver operating characteristic (ROC), calibration curve, and decision curve analyses (DCA). A total of 729 non-cardioembolic IS patients were enrolled, including 498 (68.3%) male patients and 231 (31.7%) female patients. Among them, there were 137 patients (18.8%) with recurrence. The patients were randomly divided into training and testing sets. The Kaplan-Meier survival analysis of the training and testing sets consistently revealed that the recurrence rates in the high-risk group were significantly higher than those in the low-risk group (p < 0.01). Moreover, the receiver operating characteristic curve analysis of the risk score demonstrated that the area under the curve was 0.778 and 0.760 in the training and testing sets, respectively. The nomogram comprised independent risk factors, including age, diabetes, platelet-lymphocyte ratio, leukoencephalopathy, neutrophil, monocytes, total protein, platelet, albumin, indirect bilirubin, and high-density lipoprotein. The C-index of the nomogram was 0.752 (95% CI: 0.705~0.799) in the training set and 0.749 (95% CI: 0.663~0.835) in the testing set. The nomogram model can be used as an effective tool for carrying out individualized recurrence predictions for non-cardioembolic IS.