Innate immune memory after brain injury drives inflammatory cardiac dysfunction.

The medical burden of stroke extends beyond the brain injury itself and is largely determined by chronic comorbidities that develop secondarily. We hypothesized that these comorbidities might share a common immunological cause, yet chronic effects post-stroke on systemic immunity are underexplored. Here, we identify myeloid innate immune memory as a cause of remote organ dysfunction after stroke. Single-cell sequencing revealed persistent pro-inflammatory changes in monocytes/macrophages in multiple organs up to 3 months after brain injury, notably in the heart, leading to cardiac fibrosis and dysfunction in both mice and stroke patients. IL-1ß was identified as a key driver of epigenetic changes in innate immune memory. These changes could be transplanted to naive mice, inducing cardiac dysfunction. By neutralizing post-stroke IL-1ß or blocking pro-inflammatory monocyte trafficking with a CCR2/5 inhibitor, we prevented post-stroke cardiac dysfunction. Such immune-targeted therapies could potentially prevent various IL-1ß-mediated comorbidities, offering a framework for secondary prevention immunotherapy.

Biomarker Periodic Repolarization Dynamics Indicates Enhanced Risk for Arrhythmias and Sudden Cardiac Death in Myocardial Infarction in Pigs.

BACKGROUND: Periodic repolarization dynamics (PRD) is an electrocardiographic biomarker that captures repolarization instability in the low frequency spectrum and is believed to estimate the sympathetic effect on the ventricular myocardium. High PRD indicates an increased risk for postischemic sudden cardiac death (SCD). However, a direct link between PRD and proarrhythmogenic autonomic remodeling has not yet been shown. METHODS AND RESULTS: We investigated autonomic remodeling in pigs with myocardial infarction (MI)-related ischemic heart failure induced by balloon occlusion of the left anterior descending artery (n=17) compared with pigs without MI (n=11). Thirty days after MI, pigs demonstrated enhanced sympathetic innervation in the infarct area, border zone, and remote left ventricle paralleled by altered expression of autonomic marker genes/proteins. PRD was enhanced 30 days after MI compared with baseline (pre-MI versus post-MI: 1.75±0.30 deg2 versus 3.29±0.79 deg2, P<0.05) reflecting pronounced autonomic alterations on the level of the ventricular myocardium. Pigs with MI-related ventricular fibrillation and SCD had significantly higher pre-MI PRD than pigs without tachyarrhythmias, suggesting a potential role for PRD as a predictive biomarker for ischemia-related arrhythmias (no ventricular fibrillation versus ventricular fibrillation: 1.50±0.39 deg2 versus 3.18±0.53 deg2 [P<0.05]; no SCD versus SCD: 1.67±0.32 deg2 versus 3.91±0.63 deg2 [P<0.01]). CONCLUSIONS: We demonstrate that ischemic heart failure leads to significant proarrhythmogenic autonomic remodeling. The concomitant elevation of PRD levels in pigs with ischemic heart failure and pigs with MI-related ventricular fibrillation/SCD suggests PRD as a biomarker for autonomic remodeling and as a potential predictive biomarker for ventricular arrhythmias/survival in the context of MI.

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice.

Arrhythmias are common, affecting millions of patients worldwide. Current treatment strategies are associated with significant side effects and remain ineffective in many patients. To improve patient care, novel and innovative therapeutic concepts causally targeting arrhythmia mechanisms are needed. To study the complex pathophysiology of arrhythmias, suitable animal models are necessary, and mice have been proven to be ideal model species to evaluate the genetic impact on arrhythmias, to investigate fundamental molecular and cellular mechanisms, and to identify potential therapeutic targets. Implantable telemetry devices are among the most powerful tools available to study electrophysiology in mice, allowing continuous ECG recording over a period of several months in freely moving, awake mice. However, due to the huge number of data points (>1 million QRS complexes per day), analysis of telemetry data remains challenging. This article describes a step-by-step approach to analyze ECGs and to detect arrhythmias in long-term telemetry recordings using the software, Ponemah, with its analysis modules, ECG Pro and Data Insights, developed by Data Sciences International (DSI). To analyze basic ECG parameters, such as heart rate, P wave duration, PR interval, QRS interval, or QT duration, an automated attribute analysis was performed using Ponemah to identify P, Q, and T waves within individually adjusted windows around detected R waves. Results were then manually reviewed, allowing adjustment of individual annotations. The output from the attribute-based analysis and the pattern recognition analysis was then used by the Data Insights module to detect arrhythmias. This module allows an automatic screening for individually defined arrhythmias within the recording, followed by a manual review of suspected arrhythmia episodes. The article briefly discusses challenges in recording and detecting ECG signals, suggests strategies to improve data quality, and provides representative recordings of arrhythmias detected in mice using the approach described above.