Identification and Validation of Novel Potential Pathogenesis and Biomarkers to Predict the Neurological Outcome after Cardiac Arrest

Wolf Creek XVII Part 8: Neuroprotection

Introduction

Post-cardiac arrest brain injury (PCABI) is the primary determinant of clinical outcomes for patients who achieve return of spontaneous circulation after cardiac arrest (CA). There are limited neuroprotective therapies available to mitigate the acute pathophysiology of PCABI.

Methods

Neuroprotection was one of six focus topics for the Wolf Creek XVII Conference held on June 14-17, 2023 in Ann Arbor, Michigan, USA. Conference invitees included international thought leaders and scientists in the field of CA resuscitation from academia and industry. Participants submitted via online survey knowledge gaps, barriers to translation, and research priorities for each focus topic. Expert panels used the survey results and their own perspectives and insights to create and present a preliminary unranked list for each category that was debated, revised and ranked by all attendees to identify the top 5 for each category.

Results

Top 5 knowledge gaps included developing therapies for neuroprotection; improving understanding of the pathophysiology, mechanisms, and natural history of PCABI; deploying precision medicine approaches; optimizing resuscitation and CPR quality; and determining optimal timing for and duration of interventions. Top 5 barriers to translation included patient heterogeneity; nihilism & lack of knowledge about cardiac arrest; challenges with the translational pipeline; absence of mechanistic biomarkers; and inaccurate neuro-triage and neuroprognostication. Top 5 research priorities focused on translational research and trial optimization; addressing patient heterogeneity and individualized interventions; improving understanding of pathophysiology and mechanisms; developing mechanistic and outcome biomarkers across post-CA time course; and improving implementation of science and technology.

Conclusion

This overview can serve as a guide to transform the care and outcome of patients with PCABI. Addressing these topics has the potential to improve both research and clinical care in the field of neuroprotection for PCABI.

Ischemia-Reperfusion Programming of Alzheimer's Disease-Related Genes-A New Perspective on Brain Neurodegeneration after Cardiac Arrest

The article presents the latest data on pathological changes after cerebral ischemia caused by cardiac arrest. The data include amyloid accumulation, tau protein modification, neurodegenerative and cognitive changes, and gene and protein changes associated with Alzheimer's disease. We present the latest data on the dysregulation of genes related to the metabolism of the amyloid protein precursor, tau protein, autophagy, mitophagy, apoptosis, and amyloid and tau protein transport genes. We report that neuronal death after cerebral ischemia due to cardiac arrest may be dependent and independent of caspase. Moreover, neuronal death dependent on amyloid and modified tau protein has been demonstrated. Finally, the results clearly indicate that changes in the expression of the presented genes play an important role in acute and secondary brain damage and the development of post-ischemic brain neurodegeneration with the Alzheimer's disease phenotype. The data indicate that the above genes may be a potential therapeutic target for brain therapy after ischemia due to cardiac arrest. Overall, the studies show that the genes studied represent attractive targets for the development of new therapies to minimize ischemic brain injury and neurological dysfunction. Additionally, amyloid-related genes expression and tau protein gene modification after cerebral ischemia due to cardiac arrest are useful in identifying ischemic mechanisms associated with Alzheimer's disease. Cardiac arrest illustrates the progressive, time- and area-specific development of neuropathology in the brain with the expression of genes responsible for the processing of amyloid protein precursor and the occurrence of tau protein and symptoms of dementia such as those occurring in patients with Alzheimer's disease. By carefully examining the common genetic processes involved in these two diseases, these data may help unravel phenomena associated with the development of Alzheimer's disease and neurodegeneration after cerebral ischemia and may lead future research on Alzheimer's disease or cerebral ischemia in new directions.

Identification of predictors for neurological outcome after cardiac arrest in peripheral blood mononuclear cells through integrated bioinformatics analysis and machine learning

Neurological prognostication after cardiac arrest (CA) is important to avoid pursuing futile treatments for poor outcome and inappropriate withdrawal of life-sustaining treatment for good outcome. To predict neurological outcome after CA through biomarkers in peripheral blood mononuclear cells, four datasets were downloaded from the Gene Expression Omnibus database. GSE29546 and GSE74198 were used as training datasets, while GSE92696 and GSE34643 were used as verification datasets. The intersection of differentially expressed genes and hub genes from multiscale embedded gene co-expression network analysis (MEGENA) was utilized in the machine learning screening. Key genes were identified using support vector machine recursive feature elimination (SVM-RFE), least absolute shrinkage and selection operator (LASSO) logistic regression, and random forests (RF). The results were validated using receiver operating characteristic curve analysis. An mRNA-miRNA network was constructed. The distribution of immune cells was evaluated using cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT). Five biomarkers were identified as predictors for neurological outcome after CA, with an area under the curve (AUC) greater than 0.7: CASP8 and FADD-like apoptosis regulator (CFLAR), human protein kinase X (PRKX), miR-483-5p, let-7a-5p, and let-7c-5p. Interestingly, the combination of CFLAR minus PRKX showed an even higher AUC of 0.814. The mRNA-miRNA network consisted of 30 nodes and 76 edges. Statistical differences were found in immune cell distribution, including neutrophils, NK cells active, NK cells resting, T cells CD4 memory activated, T cells CD4 memory resting, T cells CD8, B cells memory, and mast cells resting between individuals with good and poor neurological outcome after CA. In conclusion, our study identified novel predictors for neurological outcome after CA. Further clinical and laboratory studies are needed to validate our findings.