In silico-derived inflammatory and HIBI-related microRNAs showed time-dependent expression patterns that may distinguish neurological outcomes within 72 hours after out-of-hospital cardiac arrest.
Key Findings
Results
Eleven candidate microRNAs were identified through in silico network analysis showing differential time-dependent expression within 72 hours after OHCA.
A total of 100 consecutive OHCA patients admitted to the Acute Cardiac Care Unit with available cryopreserved blood samples were analyzed.
Patient mean age was 59.7 ± 12.5 years, 19% were women.
53% of patients had unfavourable neurological outcomes (CPC 3-5).
Blood samples were collected at 0, 24, and 72 hours after hospital admission.
An in silico-derived network of inflammation-HIBI-related microRNAs was generated and validated across all three time-points.
Results
miR-1-3p and miR-124-3p were the earliest and most predictive microRNAs for unfavourable neurological outcome at hospital admission (0 hours).
miR-1-3p achieved an AUC of 0.637 at 0 hours.
miR-124-3p achieved an AUC of 0.606 at 0 hours.
These were identified as the earlier and most predictive microRNAs for unfavourable neurological outcome at the earliest time-point.
Neurological outcome was classified as favourable (CPC 1-2) or unfavourable (CPC 3-5) using the Cerebral Performance Category scale.
Results
miR-21-5p and miR-499a-5p were the most predictive microRNAs for unfavourable neurological outcome at 24 hours after admission.
miR-21-5p achieved an AUC of 0.614 at 24 hours.
miR-499a-5p achieved an AUC of 0.645 at 24 hours.
miR-499a-5p maintained the best AUC across all time-points among the individual microRNAs tested.
These findings suggest miR-499a-5p has sustained discriminatory value throughout the 72-hour observation window.
Results
A multiparametric model combining microRNA and inflammatory biomarker data achieved an AUC of 0.690 for predicting unfavourable neurological outcome.
The multiparametric model AUC of 0.690 exceeded the performance of any individual microRNA tested.
The model incorporated microRNA signatures alongside inflammatory biomarkers.
This represents an improvement over single-biomarker approaches for neuroprognostication after OHCA.
Results
Neuroinflammatory microRNAs miR-let-7a-5p, miR-23a-3p, and miR-146a-5p were significantly overexpressed in patients with unfavourable neurological outcomes and positively correlated with C-Reactive Protein.
These three microRNAs were classified as neuroinflammatory in the in silico-derived network.
Their overexpression in the unfavourable group and positive correlation with CRP suggests they reflect a pro-inflammatory environment associated with poor neurological outcome.
C-Reactive Protein (CRP) and neutrophil-to-lymphocyte ratio characterized a pro-inflammatory environment with distinct temporal expression patterns regarding neurological outcome.
Results
A pro-inflammatory environment characterized by CRP and neutrophil-to-lymphocyte ratio showed distinct temporal expression patterns with respect to neurological outcome after OHCA.
CRP and neutrophil-to-lymphocyte ratio were the inflammatory biomarkers evaluated alongside microRNAs.
These markers showed differential temporal patterns between the favourable and unfavourable neurological outcome groups.
The temporal dimension of inflammatory marker expression was highlighted as relevant to outcome discrimination.
What This Means
When someone suffers a cardiac arrest outside of a hospital and is resuscitated, one of the most critical and difficult questions doctors face is predicting whether the patient's brain has been severely damaged. This research investigated whether small molecules in the blood called microRNAs — which help regulate how genes are expressed — could serve as early warning signals of poor brain recovery after out-of-hospital cardiac arrest. The researchers used computer modeling to identify microRNAs likely to be involved in brain injury and inflammation, then measured them in blood samples from 100 cardiac arrest patients at three time points: upon hospital admission, 24 hours later, and 72 hours later.
The study found that specific microRNAs showed different levels depending on whether patients ultimately had good or poor neurological recovery. Some microRNAs, like miR-1-3p and miR-124-3p, were informative as early as hospital admission, while others like miR-499a-5p remained consistently predictive across all three time points. Additionally, three microRNAs associated with brain inflammation (miR-let-7a-5p, miR-23a-3p, and miR-146a-5p) were elevated in patients with worse outcomes and tracked alongside C-Reactive Protein, a standard blood marker of inflammation. When multiple microRNAs and inflammatory markers were combined into a single model, prediction accuracy improved beyond any single marker alone.
This research suggests that measuring specific microRNAs in the blood — particularly within the first 24 to 72 hours after cardiac arrest — could help clinicians more accurately identify which patients are at risk for severe neurological damage. While individual microRNA markers showed only modest predictive ability on their own, combining them with standard inflammatory markers improved performance. This approach could eventually complement existing brain injury assessment methods, though further validation in larger studies would be needed before clinical application.
Jiménez-Trinidad F, Moreno-Monterde E, Roca-Guerrero C, de Diego O, López-Sobrino T, Izquierdo-Ribas M, et al.. (2026). MicroRNA and Inflammatory Biomarker Signatures Associated With Neurological Outcome After Out-Of-Hospital Cardiac Arrest: The MiRacle Study.. European journal of clinical investigation. https://doi.org/10.1111/eci.70251