The rehabilitation outcome and recovery, in people after stroke or with vascular severe brain injury(vSBI), are difficult to predict. Moreover, the clinical management of patients during hospitalization is problematic due to complex clinical conditions and complications, e.g. healthcare-associated infections(HAIs). Today we still lack early objective biomarkers that could predict the patient's trajectory at admission. Extracellular vesicles are nanoparticles naturally released by cells in physiological and pathological conditions. As important actors of cellular communication between different organs and body districts, EVs are currently under investigation as an informative tool able to reflect the clinical conditions of patients. Using an optimized Surface Plasmon Resonance imaging (SPRi) based biosensor, our main objective is to assess the predictive capacity of biomarkers associated to blood-derived extracellular vesicles for anticipating patients' recovery after stroke and vSBI. If successful, the project will 1) demonstrate the ability of the SPRi biosensor to reveal differences in the relative amount of specific cell-derived EV subpopulations and their molecular cargo during disease progression and rehabilitation-induced recovery, 2) verify the impact of HAI on patients' response, 3) perform a patient's stratification to personalize the rehabilitation protocol.

OBJECTIVE: The main objective of the present project is to assess the predictive capacity of biomarkers associated to extracellular vesicles (EVs) for anticipating patients' recovery after stroke and vSBI.

The characterization by SPRi of different cell-derived families of EVs (endothelium, neurons, microglia, muscle, and neutrophil) will allow to evaluate the activation status of the processes of neuroinflammation, neuronal regeneration, and angiogenesis to provide a picture of the mechanisms of response to the damage taking place in the brain of patients and enhanced by the rehabilitation treatment. The selected markers are expected to be released in the brain, but they can be monitored in the periphery taking advantage of the ability of EVs to cross the blood-brain barrier.

Due to the weight of HAIs on patients' prognosis, inflammation and infections will represent the main covariate of the analysis in the search for predictive rehabilitation biomarkers.

Specific objectives are as follows:

1. Evaluation of the SPRi biosensor's ability to detect EV-associated biomarkers correlating with stroke severity.
2. Evaluation of the ability of EV-associated biomarkers to represent a recovery biomarker by their changes according to the patient's outcome.
3. Evaluation of the ability of EV-associated biomarkers to identify infection-prone patients to help develop valuable prevention strategies for infections.

These data will be correlated with the outcome of the rehabilitation evaluated with specific functional and neurological scales that allow accurate profiling of the patient and the evaluation of functional recovery.

IMPACT: The primary impact of the present project is the clinical management of the neurorehabilitation department for stroke and vSBI patients. The identification of measurable biomarkers that could predict the response to rehabilitation of patients and group them into responders or non-responders would significantly modify the everyday activity of physiatrists. In the long term, patients will take advantage of a personalized treatment that will lead to optimal recovery. Optimal intervention and recovery imply amelioration of the quality of life of patients and their families and reduced time and costs of the intervention.

SAMPLE COLLECTION: 30 stroke patients will be recruited at IRCCS S. Maria Nascente (Milan), S. Maria ai Colli (Turin), and IRCCS Don Gnocchi (Florence), while 30 subjects with vSBI will be recruited at IRCCS S. Maria Nascente (Milan) and S. Maria ai Colli (Turin) of Fondazione Don Gnocchi. Recruited patients will undergo blood withdrawal (10 ml of blood for serum separation) at 3 time points: at admission in the rehabilitation department (T0), after completing 50% of their rehabilitation program (T1), and at discharge (T2).

EV ISOLATION: EVs isolation will be perfomed at the Laboratory of Nanomedicine and Clinical Biophotonics of IRCCS S. Maria Nascente (Milan). EVs will be isolated from serum by size exclusion chromatography. To evaluate the size distribution and the concentration of the isolated EVs, the Nanoparticle Tracking Analysis (NTA) will be carried out. Reported markers of small EVs will be evaluated by Western blot to verify the successful isolation.

SPRi BIOSENSOR: The functionalization of the SPRi chip will be optimized for marker of endothelial EVs (CD31), neuronal EVs (CD171/L1CAM), microglia Evs (IB4), muscle EVs (Irisin), and neutrophil EVs (CD15 or CD66b).

Correlation analysis will be performed between SPRi-data and clinical measures at admission (T0), T1 and T2, separately. Correlation analysis will be performed also between the biomolecular markers measured at T0 and the change scores obtained from clinical assessments to test their ability to predict the outcome measure.

Inclusion Criteria:

• Disability deriving from first ischemic or haemorrhagic stroke detected by MRI or CT scan
• Time from stroke onset or rehabilitation admission less than 1 month (for stroke) 3 months (for vSBI)
• Need of inward rehabilitation
• Signed informed consent by patient or legal representative

Exclusion Criteria:

• Subarachnoid haemorrhage
• Cerebral venous thrombosis
• Other previous neurological or psychiatric conditions
• Autoimmune diseases
• Previous severe and chronic infections conditions (e.g. tuberculosis, HIV/AIDS)
• Neoplasms or other malignant conditions
• Immunomodulatory medications (immunosuppressants).

Patients hospitalized at Fondazione Don Gnocchi (IRCCS S. Maria Nascente/Milan, S. Maria ai Colli/Turin, and IRCCS Don Gnocchi/Florence) after stroke injury or with vascular severe brain injury and undergoing an intensive rehabilitation program.

All personal data will be pseudoanonimized upon collection and reported in publications and scientific presentations only as anonymous and/or aggregated data that do not allow to trace the identity of the involved subjects.