The Role of Blood-Based Molecular Clock Biomarkers in Predicting the Onset Time of Acute Ischemic Stroke: A Prospective Observational Study
The Role of Blood-Based Molecular Clock Biomarkers in Predicting the Onset Time of Acute Ischemic Stroke: A Prospective Observational Study
Acute ischemic stroke (AIS) is a major cause of mortality and long-term neurological disability worldwide. The effectiveness of reperfusion therapies such as intravenous thrombolysis and mechanical thrombectomy is highly dependent on the time elapsed since symptom onset. However, in approximately 15-25% of patients, the exact onset time cannot be determined because symptoms begin during sleep (wake-up stroke) or the onset is otherwise unclear. This uncertainty often prevents patients from receiving time-dependent reperfusion treatments.
Currently, imaging-based approaches such as diffusion-weighted imaging-fluid attenuated inversion recovery (DWI-FLAIR) mismatch are used to estimate the biological stage of ischemia in patients with unknown onset time. However, advanced imaging techniques may not be available in all centers and interpretation may vary.
This study aims to evaluate the diagnostic performance of a multi-biomarker panel representing different biological components of ischemic brain injury, including glial, neuronal, axonal, cellular stress, and vascular responses. Blood samples obtained at admission will be analyzed for glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase L1 (UCH-L1), serum neurofilament light chain (sNfL), phosphatidylethanolamine-binding protein 1 (PEBP1), and matrix metalloproteinase-9 (MMP-9).
The primary objective is to determine whether this biomarker panel can distinguish patients presenting within ≤4.5 hours from those presenting after >4.5 hours of symptom onset. Biomarker findings will be compared with imaging-based reference methods to explore the feasibility of a blood-based "molecular clock" approach for estimating stroke timing in patients with uncertain onset.
Acute ischemic stroke (AIS) is one of the leading causes of mortality and long-term neurological disability worldwide. The effectiveness of reperfusion therapies, including intravenous thrombolysis and mechanical thrombectomy, is highly dependent on the time elapsed since symptom onset. Determination of the symptom onset time is therefore a critical component of treatment eligibility. However, a substantial proportion of patients present with stroke symptoms of unknown onset, most commonly because the symptoms develop during sleep (wake-up stroke) or because the exact onset time cannot be reliably established. This uncertainty may prevent eligible patients from receiving time-dependent reperfusion therapies.
Current clinical decision-making in patients with uncertain onset time relies largely on imaging-based approaches that attempt to estimate the biological stage of ischemia. The diffusion-weighted imaging-fluid attenuated inversion recovery (DWI-FLAIR) mismatch concept is the most widely used method and is based on the hypothesis that tissue signal evolution reflects the duration of ischemia. Advanced perfusion imaging techniques have also been incorporated into clinical practice. However, these imaging methods require specialized equipment and expertise, may not be available in all centers, and their interpretation may vary between institutions. Consequently, there is increasing interest in identifying circulating biomarkers that can reflect the biological timing of ischemic injury.
Ischemic brain injury initiates a complex cascade of pathophysiological processes involving astroglial activation, neuronal membrane disruption, axonal injury, inflammatory signaling, cellular stress responses, and vascular dysfunction. These processes evolve dynamically over time and lead to the release of measurable molecular components into the systemic circulation. Biomarkers reflecting different cellular compartments of the neurovascular unit may therefore provide complementary information regarding the temporal evolution of ischemic injury.
Several candidate biomarkers have been identified that represent different biological aspects of this process. Glial fibrillary acidic protein (GFAP) is an astrocyte-specific structural protein that reflects astroglial injury and early glial activation following acute brain damage. Ubiquitin C-terminal hydrolase L1 (UCH-L1) is a neuron-specific cytoplasmic enzyme released after neuronal membrane disruption and has been proposed as an indicator of acute neuronal injury. Serum neurofilament light chain (sNfL) is a structural component of the axonal cytoskeleton and is considered a marker of axonal degeneration and structural neuronal damage. Phosphatidylethanolamine-binding protein 1 (PEBP1), also known as Raf kinase inhibitory protein, is involved in the regulation of cellular signaling pathways and stress responses and may reflect cellular adaptation to ischemic stress. Matrix metalloproteinase-9 (MMP-9) is associated with inflammatory activation, extracellular matrix degradation, and blood-brain barrier dysfunction during the evolution of ischemic brain injury.
The combined evaluation of biomarkers representing multiple biological layers of the neurovascular unit may provide a more comprehensive representation of the temporal dynamics of ischemic injury than single-marker approaches. A multi-biomarker strategy has the potential to capture different phases of the ischemic cascade, including glial activation, neuronal damage, axonal injury, cellular stress response, and vascular dysfunction.
The present study aims to investigate whether a multi-compartment biomarker panel can contribute to the estimation of the biological timing of acute ischemic stroke. By evaluating circulating biomarkers representing different components of the neurovascular unit, the study seeks to explore the feasibility of a blood-based molecular signature that reflects the temporal evolution of ischemic injury.
The findings of this study may contribute to the development of a biologically informed approach for estimating stroke timing and may support clinical decision-making in patients presenting with uncertain symptom onset, particularly in settings where advanced imaging techniques are not readily available.
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