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Extracellular Vesicle Surface Markers In Acute Cerebrovascular Syndromes. (ElViS-ACS)

O

Ospedale Civico, Lugano

Status

Enrolling

Conditions

Stroke, TIA, Stroke-mimics, Stroke Biomarkers

Treatments

Diagnostic Test: Extracellular vescicles (EV) analysis

Study type

Observational

Funder types

Other

Identifiers

NCT06319742
NSISTRCR_2201

Details and patient eligibility

About

Clinical implication of eventual blood biomarkers for stroke diagnosis and prognosis would be limited, mainly because clinical evaluation and scales (providing stroke severity) or neuroimaging (providing accurate size of the lesion) are more reliable predictors for clinical outcome prediction. In clinical practice, it would be more useful to find a biomarker, which can help to orientate the physician in conditions in which the clinical picture and imaging provide a limited support.

Transient Ischemic Attacks (TIAs) represent a classical example for which a biomarker would be of interest to confirm and distinguish a brain ischemic process from a stroke mimic. Diagnostic biomarkers of TIA have been investigated, but none of the potential candidates reached enough accuracy for TIA diagnosis. Our group has found that Extracellular Vesicles (EVs) could be useful as biomarkers for detecting brain ischemia in patients with TIA because the EV-surface antigen profile appears to be different in patients with transient symptoms, adjudicated to be very likely caused by brain ischemia, compared to patients whose symptoms were less likely to due to brain ischemia. Our study has raised interest in the scientific community recognizing the promising role of of blood-derived EVs analysis in expanding the possibilities to correctly diagnose and classify TIA and stroke events, discriminate them from TIA or stroke mimics, with important future implications in management and therapy of the patients with acute ischemic cerebrovascular syndrome. the validity of our approach needs to be tested in a larger, prospective, multicenter study.

Full description

Characterization of extracellular vesicles Extracellular vesicles (EVs) will be characterized in pre-cleared serum samples (see transfer and managements of blood samples). EVs will be characterized by nanoparticle tracking analysis, western blot, bead-based flow cytometry (direct and inverse approach), and ELISA.

We will evaluate diameter and concentration of serum nanoparticles (NPs) by nanoparticle tracking analysis (NTA) using NanoSight LM10 (Malvern Instruments, United Kingdom) equipped with a 405 nm laser and Nanoparticle Tracking Analysis NTA 2.3 analytic software. A camera will record Brownian movement of EVs and size and number of EVs per mL will be calculated by Stokes-Einstein equation. Three videos of 60 s will be recorded for each analysis.

Western Blot analysis will be performed on protein lysate after EV immuno-capture (using beads covered with antibodies against EV specific tetraspanins, CD9, CD63 and CD81). Blots of representative samples will be incubated with primary antibodies against specific markers expressed on the surface or within EVs (TSG101, Syntenin-1, CD81, Alix) and potential contaminants (GRP94, Apolipoprotein A1, Apolipoprotein B48).

EV profiling will be performed using a standardized multiplex bead-based flow cytometric assay, using MACSPlex Human Exosome Kit (Miltenyi Biotec; Bergisch Gladbach, Germany), as previously described. 22 The detection of 37 different surface antigens commonly expressed on EV membrane (including markers from activated platelets, endothelium, and inflammatory cells) will be simultaneously performed. Background will be subtracted from the MFI value of each marker, and then normalized using by the mean fluorescence intensity levels (MFI) of CD9, CD63, and CD81. Levels of expression will be reported as normalized MFI (nMFI; %) for each EV-surface antigen (median value and interquartile range).

After an initial screening by multiplexed assay, single candidate EV biomarkers will be confirmed by either reverse flow cytometry and ELISA techniques.

The reverse flow cytometric assay will be performed by isolating EVs by capture beads coated with antibodies against CD9-CD63-CD81 (EpCam; JSR Micro) and then incubated with fluorochrome-conjugated antibodies against single EV surface antigens, associated to patient diagnosis during the initial screening by MACSPlex assay. Beads incubated with isotype-matched antibodies, and beads incubated in absence of vesicles will serve as controls. Candidate EV biomarkers will be confirmed also by ELISA technique, using specific antibodies as per manufacturer's instructions.

Enrollment

200 estimated patients

Sex

All

Ages

18+ years old

Volunteers

No Healthy Volunteers

Inclusion criteria

Affected by:

I. Suspect ischemic minor stroke (acute loss of focal cerebral function of presumed vascular etiology and NIHSS ≤327, 28) within 48 hours of symptoms onset or II. TIA (defined as the acute onset of focal neurological symptoms lasting <24 h and presumed to be caused by brain ischemia at the time of referral)19 III. Symptoms mimicking I. or II. with but with high suspition of a non-ischemic condition being the cause of the event;

  1. age ≥18 years; 3) if cerebral magnetic resonance imaging will be performed within 48-72 hours from admission; 4) if baseline CT/MRI is without hemorrhage; 5) if informed consent obtained.

Exclusion criteria

  1. ocular TIA (amaurosis fugax);
  2. contraindications for MRI;
  3. pregnancy;
  4. concomitant acute/chronic inflammatory disease (e.g., infections, autoimmune disease);
  5. concomitant hematological diseases;
  6. Central Nervous System infection within 30 days;
  7. serious head trauma within 30 days;
  8. major surgery within 90 days.

Trial design

200 participants in 3 patient groups

Stroke
Treatment:
Diagnostic Test: Extracellular vescicles (EV) analysis
TIA
Treatment:
Diagnostic Test: Extracellular vescicles (EV) analysis
Stroke Mimic
Treatment:
Diagnostic Test: Extracellular vescicles (EV) analysis

Trial contacts and locations

1

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Central trial contact

Carlo Walter Cereda, PI; Giovanni Bianco

Data sourced from clinicaltrials.gov

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