Association between PAI-1 Polymorphisms and Ischemic Stroke in a South Korean Case-Control Cohort.

Stroke is the second leading cause of death in the world. Approximately 80% of strokes are ischemic in origin. Many risk factors have been linked to stroke, including an increased level of plasminogen activator inhibitor-1 (PAI-1). PAI-1 levels increase and remain elevated in blood during the acute phase of ischemic stroke, which can impair fibrinolytic activity, leading to coronary artery disease and arterial thrombotic disorders. Here, we present a case-control study of 574 stroke patients and 425 controls seen for routine health examination or treatment for nonspecific dizziness, nonorganic headache, or anxiety for positive family history of stroke at the Bundang Medical Center in South Korea. Polymorphisms in PAI-1 were identified by polymerase chain reaction/restriction fragment length polymorphism analysis using genomic DNA. Specifically, three variations (-675 4G>5G, 10692T>C, and 12068G>A) were linked to a higher overall prevalence of stroke as well as a higher prevalence of certain stroke subtypes. Haplotype analyses also revealed combinations of these variations (-844G>A, -675 4G>5G, 43G>A, 9785A>G, 10692T>C, 11053T>G, and 12068G>A) that were significantly associated with a higher prevalence of ischemic stroke. To the best of our knowledge, this is the first strong evidence that polymorphic sites in PAI-1 promoter and 3'-UTR regions are associated with higher ischemic stroke risk. Furthermore, the PAI-1 genotypes and haplotypes identified here have potential as clinical biomarkers of ischemic stroke and could improve the prognosis and future management of stroke patients.

Angiography-Based Machine Learning for Predicting Fractional Flow Reserve in Intermediate Coronary Artery Lesions.

Background An angiography-based supervised machine learning ( ML ) algorithm was developed to classify lesions as having fractional flow reserve ≤0.80 versus >0.80. Methods and Results With a 4:1 ratio, 1501 patients with 1501 intermediate lesions were randomized into training versus test sets. Between the ostium and 10 mm distal to the target lesion, a series of angiographic lumen diameter measurements along the centerline was plotted. The 24 computed angiographic features based on the diameter plot and 4 clinical features (age, sex, body surface area, and involve segment) were used for ML by XGBoost. The model was independently trained and tested by 2000 bootstrap iterations. External validation with 79 patients was conducted. Including all 28 features, the ML model with 5-fold cross-validation in the 1204 training samples predicted fractional flow reserve ≤0.80 with overall diagnostic accuracy of 78±4% (averaged area under the curve: 0.84±0.03). The 12 high-ranking features selected by scatter search were involved segment; body surface area; distal lumen diameter; minimal lumen diameter; length of a lumen diameter <2.0 mm, <1.5 mm, and <1.25 mm; mean lumen diameter within the worst segment; sex; diameter stenosis; distal 5-mm reference lumen diameter; and length of diameter stenosis >70%. Using those 12 features, the ML predicted fractional flow reserve ≤0.80 in the test set with sensitivity of 84%, specificity of 80%, and overall accuracy of 82% (area under the curve: 0.87). The averaged diagnostic accuracy in bootstrap replicates was 81±1% (averaged area under the curve: 0.87±0.01). External validation showed accuracy of 85% (area under the curve: 0.87). Conclusions Angiography-based ML showed good diagnostic performance in identifying ischemia-producing lesions and reduced the need for pressure wires.

Association of the Single Nucleotide Polymorphisms in microRNAs 130b, 200b, and 495 with Ischemic Stroke Susceptibility and Post-Stroke Mortality.

The microRNA (miRNA) is a small non-coding RNA molecule that modulates gene expression at the posttranscriptional level. Platelets have a crucial role in both hemostasis and thrombosis, a condition that can occlude a cerebral artery and cause ischemic stroke. miR-130b, miR-200b, and miR-495 are potential genetic modulators involving platelet production and activation. We hypothesized that single nucleotide polymorphisms (SNPs) in these miRNAs might potentially contribute to the susceptibility to ischemic stroke and post-stroke mortality. This study included 523 ischemic stroke patients and 400 control subjects. We investigated the association of three miRNA SNPs (miR-130bT>C, miR-200bT>C, and miR-495A>C) with ischemic stroke prevalence and post-stroke mortality. In the multivariate logistic regression, there was no statistically significant difference in the distribution of miR-130bT>C, miR-200bT>C, or miR-495A>C between the ischemic stroke and control groups. In the subgroup analysis based on ischemic stroke subtype, the miR-200b CC genotype was less frequently found in the large-artery atherosclerosis stroke subtype compared with controls (TT+CT vs CC; adjusted odds ratio for CC, 0.506; 95% confidence interval, 0.265-0.965). During a mean follow-up period of 4.80 ± 2.11 years after stroke onset, there were 106 all-cause deaths among the 523 stroke patients. Multivariate Cox regression analysis did not find a significant association between post-stroke mortality and three miRNA SNPs. Our findings suggest that the functional SNP of miR-200b might be responsible for the susceptibility to large-artery atherosclerotic stroke.

Association of miR-34a, miR-130a, miR-150 and miR-155 polymorphisms with the risk of ischemic stroke.

MicroRNAs (miRNAs or miRs) are small (19-23 nt) non-coding RNA molecules that are endogenous regulators of gene expression. Previous studies have found that some miRNAs are related to the progression of ischemia in the cerebral artery. Furthermore, a recent study found a significant association between miRNA single nucleotide polymorphisms (SNPs) and the risk of ischemic stroke. Therefore, it may be valuable to investigate associations between megakaryocyte formation-related miRNA polymorphisms and the prevalence of ischemic stroke. We thus conducted a case-control study of 1,000 individuals who were screened for 4 miRNA polymorphisms (miR­34a rs6577555C>A, miR-130a rs731384C>T, miR-150 rs73056059G>A and miR­155 rs767649T>A) by PCR-RFLP analysis. The study population comprised 596 patients with ischemic stroke and 404 control subjects without any history of neurological disorders. We observed associations between miRNA polymorphisms and individual stroke subtypes. The miR­150 polymorphisms were significantly associated with ischemic stroke subgroups, such as left anterior descending artery (LAD) disease [GG vs. AA: adjusted odds ratio (AOR), 1.922; 95% confidence interval (CI), 1.003-3.681] and cardioembolism (GG vs. AA: AOR, 2.996; 95% CI, 1.293-6.939). Additionally, Cox proportional analysis indicated that the miR­150GA genotype was associated with survival in patients with ischemic stroke [adjusted hazard ratio (HR), 2.063; 95% CI, 1.142-3.727; P=0.017] and with the LAD subgroup [adjusted HR, 3.021; 95% CI, 1.345-6.785; P=0.008]. Our findings suggest that miR­150 polymorphisms may contribute to the development of ischemic stroke and may potentially act as biomarkers to predict the risk of ischemic stroke. To the best of our knowledge, this is the first study to evaluate the association between miRNA polymorphisms (miR-34aC>A, miR-130aC>T, miR-150G>A and miR-155T>A) and ischemic stroke.