Assessment of brain-derived extracellular vesicle enrichment for blood biomarker analysis in age-related neurodegenerative diseases: An international overview.

INTRODUCTION: Brain-derived extracellular vesicles (BEVs) in blood allows for minimally-invasive investigations of central nervous system (CNS) -specific markers of age-related neurodegenerative diseases (NDDs). Polymer-based EV- and immunoprecipitation (IP)-based BEV-enrichment protocols from blood have gained popularity. We systematically investigated protocol consistency across studies, and determined CNS-specificity of proteins associated with these protocols. METHODS: NDD articles investigating BEVs in blood using polymer-based and/or IP-based BEV enrichment protocols were systematically identified, and protocols compared. Proteins used for BEV-enrichment and/or post-enrichment were assessed for CNS- and brain-cell-type-specificity, extracellular domains (ECD+), and presence in EV-databases. RESULTS: A total of 82.1% of studies used polymer-based (ExoQuick) EV-enrichment, and 92.3% used L1CAM for IP-based BEV-enrichment. Centrifugation times differed across studies. A total of 26.8% of 82 proteins systematically identified were CNS-specific: 50% ECD+, 77.3% were listed in EV-databases. CONCLUSIONS: We identified protocol steps requiring standardization, and recommend additional CNS-specific proteins that can be used for BEV-enrichment or as BEV-biomarkers. HIGHLIGHTS: Across NDDs, we identified protocols commonly used for EV/BEV enrichment from blood. We identified protocol steps showing variability that require harmonization. We assessed CNS-specificity of proteins used for BEV-enrichment or found in BEV cargo. CNS-specific EV proteins with ECD+ or without were identified. We recommend evaluation of blood-BEV enrichment using these additional ECD+ proteins.

Extracellular vesicles in disorders of hemostasis following traumatic brain injury.

Traumatic brain injury (TBI) is a global health priority. In addition to being the leading cause of trauma related death, TBI can result in long-term disability and loss of health. Disorders of haemostasis are common despite the absence of some of the traditional risk factors for coagulopathy following trauma. Similar to trauma induced coagulopathy, this manifests with a biphasic response consisting of an early hypocoagulable phase and delayed hypercoagulable state. This coagulopathy is clinically significant and associated with increased rates of haemorrhagic expansion, disability and death. The pathophysiology of TBI-induced coagulopathy is complex but there is biologic plausibility and emerging evidence to suggest that extracellular vesicles (EVs) have a role to play. TBI and damage to the blood brain barrier result in release of brain-derived EVs that contain tissue factor and phosphatidylserine on their surface. This provides a platform on which coagulation can occur. Preclinical animal models have shown that an early rapid release of EVs results in overwhelming activation of coagulation resulting in a consumptive coagulopathy. This phenomenon can be attenuated with administration of substances to promote EV clearance and block their effects. Small clinical studies have demonstrated elevated levels of procoagulant EVs in patients with TBI correlating with clinical outcome. EVs represent a promising opportunity for use as minimally invasive biomarkers and potential therapeutic targets for TBI patients. However, additional research is necessary to bridge the gap between their potential and practical application in clinical settings.

Smart Nanoscale Extracellular Vesicles in the Brain: Unveiling their Biology, Diagnostic Potential, and Therapeutic Applications.

Information exchange is essential for the brain, where it communicates the physiological and pathological signals to the periphery and vice versa. Extracellular vesicles (EVs) are a heterogeneous group of membrane-bound cellular informants actively transferring informative calls to and from the brain via lipids, proteins, and nucleic acid cargos. In recent years, EVs have also been widely used to understand brain function, given their "cell-like" properties. On the one hand, the presence of neuron and astrocyte-derived EVs in biological fluids have been exploited as biomarkers to understand the mechanisms and progression of multiple neurological disorders; on the other, EVs have been used in designing targeted therapies due to their potential to cross the blood-brain-barrier (BBB). Despite the expanding literature on EVs in the context of central nervous system (CNS) physiology and related disorders, a comprehensive compilation of the existing knowledge still needs to be made available. In the current review, we provide a detailed insight into the multifaceted role of brain-derived extracellular vesicles (BDEVs) in the intricate regulation of brain physiology. Our focus extends to the significance of these EVs in a spectrum of disorders, including brain tumors, neurodegenerative conditions, neuropsychiatric diseases, autoimmune disorders, and others. Throughout the review, parallels are drawn for using EVs as biomarkers for various disorders, evaluating their utility in early detection and monitoring. Additionally, we discuss the promising prospects of utilizing EVs in targeted therapy while acknowledging the existing limitations and challenges associated with their applications in clinical scenarios. A foundational comprehension of the current state-of-the-art in EV research is essential for informing the design of future studies.

Early Diagnosis of Brain Diseases Using Artificial Intelligence and EV Molecular Data: A Proposed Noninvasive Repeated Diagnosis Approach.

Brain-derived extracellular vesicles (BDEVs) are released from the central nervous system. Brain-related research and diagnostic techniques involving BDEVs have rapidly emerged as a means of diagnosing brain disorders because they are minimally invasive and enable repeatable measurements based on body fluids. However, EVs from various cells and organs are mixed in the blood, acting as potential obstacles for brain diagnostic systems using BDEVs. Therefore, it is important to screen appropriate brain EV markers to isolate BDEVs in blood. Here, we established a strategy for screening potential BDEV biomarkers. To collect various molecular data from the BDEVs, we propose that the sensitivity and specificity of the diagnostic system could be enhanced using machine learning and AI analysis. This BDEV-based diagnostic strategy could be used to diagnose various brain diseases and will help prevent disease through early diagnosis and early treatment.