Introduction
Cardiac function is tightly controlled by autonomic neural circuits, yet the contribution of associated glial cells to neuro-cardiac communication remains poorly understood. Converging evidence supports the existence of peripheral tripartite synapse-like structures within cardiac autonomic circuits, where glial cells form intimate contacts with autonomic neurons and pacemaker cells. Three populations of cardiac-associated glia are consistently identified: Schwann cells, satellite glial cells and cardiac nexus glia. Genetic ablation of cardiac nexus glia abolishes autonomic heart rate modulation and increases arrhythmia vulnerability (Kikel-Coury et al., 2021), while spatial transcriptomics identifies glial populations expressing neurexins and glutamate-handling machinery adjacent to human pacemaker cells (Kanemaru et al., 2023). However, the mechanisms by which cardiac glia regulate electrophysiology, contractile function and haemodynamics in vivo remain undefined. It is also unknown whether chronic stress induces cardiac astroglial reactivity similar to CNS glia and whether this contributes to adverse post-ischaemic outcomes.
Methods
Cardiac glia will be selectively manipulated using astrocyte-specific Cre driver mice (GFAP-Cre or Aldh1l1-CreERT2) crossed with floxed effector lines. The cardiovascular phenotype will be characterised across three domains. Electrophysiology: action potential duration (APD), conduction velocity and arrhythmia susceptibility via burst pacing and programmed electrical stimulation will be studied in Langendorff-perfused hearts. Echocardiography: ejection fraction (EF), fractional shortening and diastolic function (E/A ratio, tissue Doppler) will be assessed longitudinally. Haemodynamics: pressure-volume catheterisation will quantify contractility (dP/dt max), relaxation (dP/dt min) and pressure-volume relationships.
A chronic variable stress model (4 weeks) will be implemented in parallel cohorts using a 2×2 factorial design (glial manipulation × stress). Cardiac glial inflammatory state will be assessed by GFAP immunostaining, morphological indices of astroglial activation and pro-inflammatory cytokine expression (IL-1β, TNF-α) via RT-qPCR. Recovery after myocardial ischaemia/reperfusion will be assessed by LAD coronary artery ligation, with infarct size, peri-infarct fibrosis and functional recovery (echocardiography at 1, 7, 14 and 28 days post-infarction) as outcomes.
Approach for statistical analysis
Primary outcomes: (1) APD and arrhythmia inducibility; (2) EF and dP/dt max; (3) infarct size and GFAP expression intensity. Continuous outcomes will be analysed by two-way ANOVA (genotype × stress) with Tukey’s post-hoc correction. Longitudinal echocardiographic data will use linear mixed-effects models. Arrhythmia incidence will be compared using Fisher’s exact test. Sample sizes (n=8-12 per group) are based on published effect sizes in glial ablation models to achieve 80% power at α=0.05.
Expected value of results
These studies will establish whether cardiac glia are active participants in neuro-cardiac signalling or passive bystanders. If chronic stress drives cardiac astroglial inflammation and worsens post-ischaemic outcomes, this would identify cardiac glia as a cellular link between psychosocial stress and adverse cardiac events. This could reveal peripheral glial signalling pathways as novel therapeutic targets for arrhythmias and stress-related cardiac disease.