Hash Brown Taha, Shomik S. Ati

Evaluation of α‐synuclein in CNS‐originating extracellular vesicles for Parkinsonian disorders: A systematic review and meta‐analysis

  • Pharmacology (medical)
  • Physiology (medical)
  • Psychiatry and Mental health
  • Pharmacology
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AbstractBackground & AimsParkinsonian disorders, such as Parkinson's disease (PD), multiple system atrophy (MSA), dementia with Lewy bodies (DLB), progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS), share early motor symptoms but have distinct pathophysiology. As a result, accurate premortem diagnosis is challenging for neurologists, hindering efforts for disease‐modifying therapeutic discovery. Extracellular vesicles (EVs) contain cell‐state‐specific biomolecules and can cross the blood‐brain barrier to the peripheral circulation, providing a unique central nervous system (CNS) insight. This meta‐analysis evaluated blood‐isolated neuronal and oligodendroglial EVs (nEVs and oEVs) α‐synuclein levels in Parkinsonian disorders.MethodsFollowing PRISMA guidelines, the meta‐analysis included 13 studies. An inverse‐variance random‐effects model quantified effect size (SMD), QUADAS‐2 assessed risk of bias and publication bias was evaluated. Demographic and clinical variables were collected for meta‐regression.ResultsThe meta‐analysis included 1,565 patients with PD, 206 with MSA, 21 with DLB, 172 with PSP, 152 with CBS and 967 healthy controls (HCs). Findings suggest that combined concentrations of nEVs and oEVs α‐syn is higher in patients with PD compared to HCs (SMD = 0.21, p = 0.021), while nEVs α‐syn is lower in patients with PSP and CBS compared to patients with PD (SMD = ‐1.04, p = 0.0017) or HCs (SMD = ‐0.41, p < 0.001). Additionally, α‐syn in nEVs and/or oEVs did not significantly differ in patients with PD vs. MSA, contradicting the literature. Meta‐regressions show that demographic and clinical factors were not significant predictors of nEVs or oEVs α‐syn concentrations.ConclusionThe results highlight the need for standardized procedures and independent validations in biomarker studies and the development of improved biomarkers for distinguishing Parkinsonian disorders.

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