Abstract
BACKGROUND: Membrane-bound vesicles called apoptotic bodies (ApoBDs) formed during apoptosis are being recognized as non-invasive biomarkers for neurological diseases like dementia and ischemic stroke. Centrifugation-based isolation of these vesicles from blood was suggested in a recent paper by Serrano-Heras et al. (2020), which asserted their use for clinical diagnosis. This initial study provides a foundational methodology for ApoBD diagnostics. Albeit, centrifugation parameters employed present technical challenges that require optimization to ensure the purity and reproducibility of ApoBD preparations for clinical utility. RESULTS: Due to the use of improper centrifugation speeds (160×g and 700×g) not consistent with accepted norms for the separation of platelets (ideally 2,000-5,000×g), running the risk of being seriously contaminated by platelets and platelet-derived EVs (P-EVs), which make up 70-90% of EVs in circulation. Such contamination can render functional studies problematic, cloud proteomic and size-distribution analysis, and lower the specificity of ApoBDs enumeration on the basis of Annexin V/PI labeling. Even more extreme centrifugation has little chance to eliminate platelets completely, according to comparative literature data. Increased centrifugal pressure, density gradient separation, size-exclusion chromatography (SEC), and confirmation with platelet-specific markers are among some procedural changes recommended to improve sample purity in attempts to solve such problems. CONCLUSIONS: Even as the Serrano-Heras et al. study pinpoints the potential of ApoBDs as biomarkers, constraints to the procedure under consideration pose the threat of bias in future studies. Proper isolation of ApoBDs requires multimodal confirmation, optimized platelet removal protocols and clinically feasible methods like SEC are essential to enhance ApoBDs isolation for neurological disease diagnostics. Rectification of such issues enhance significantly the practicality of ApoBDs in clinical practice for the detection of neurological illnesses.