Introduction Extracellular vesicles (EVs) from human Alzheimer's disease (AD) biospecimens contain amyloid beta (Aβ) peptide and tau. While AD EVs are known to affect brain disease pathobiology, their biochemical and molecular characterizations remain ill defined. Methods EVs were isolated from the cortical gray matter of 20 AD and 18 control brains. Tau and Aβ levels were measured by immunoassay. Differentially expressed EV proteins were assessed by quantitative proteomics and machine learning. Results Levels of pS396 tau and Aβ1–42 were significantly elevated in AD EVs. High levels of neuron‐ and glia‐specific factors are detected in control and AD EVs, respectively. Machine learning identified ANXA5, VGF, GPM6A, and ACTZ in AD EV compared to controls. They distinguished AD EVs from controls in the test sets with 88% accuracy. Discussion In addition to Aβ and tau, ANXA5, VGF, GPM6A, and ACTZ are new signature proteins in AD EVs.

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved ‘high-coverage’ and ‘high-accuracy’ glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics.

previous studies on parkinson's disease mechanisms have shown dysregulated extracellular transport of α-synuclein and growth factors in the extracellular space. In the human brain these consist of perineuronal nets, interstitial matrices, and basement membranes, each composed of a set of collagens, non-collagenous glycoproteins, proteoglycans, and hyaluronan. The manner by which amyloidogenic proteins spread extracellularly, become seeded, oligomerize, and are taken up by cells, depends on intricate interactions with extracellular matrix molecules. We sought to assess the alterations to structure of glycosaminoglycans and proteins that occur in pD brain relative to controls of similar age. We found that PD differs markedly from normal brain in upregulation of extracellular matrix structural components including collagens, proteoglycans and glycosaminoglycan binding molecules. We also observed that levels of hemoglobin chains, possibly related to defects in iron metabolism, were enriched in PD brains. These findings shed important new light on disease processes that occur in association with pD. The volume of the extracellular space (~ 20%) that separates brain cell surfaces and through which molecules diffuse displays regional patterns that change during development, aging and neurodegeneration 1,2. The passage of protein molecules through the extracellular space depends on the geometries and chemical compositions of extracellular and cell surface molecular complexes, the specific binding domains thereof, and the fixed negative charges of glycosaminoglycan chains 3,4. Brain extracellular matrix (ECM) is composed of perineuronal nets (PNNs), interstitial matrices, and basement membranes (blood brain barrier), each consisting of a network of glycoproteins, proteoglycans, hyaluronan and collagens 5. Despite the obvious importance of the extracellular space to neural plasticity and neurodegeneration 6,7 , there is little information available on the alterations that occur to these molecules during Parkinson's disease (PD). Inflammation and disruption of the blood brain barrier can lead to infiltration of fibroblasts and trigger a fibrotic response in an attempt to restore normal function 8. Such fibrosis demolishes the structure of the ECM, and impedes healing by secreting inhibitory molecules and serves as a barrier to axons. Infiltration of fibroblasts leads to deposition of thrombin and fibrinogen and destruction of the integrity of the ECM. These inflammatory reactions lead to local neural degeneration and activation of glial cells. In PD, the activation of glial cells and recruitment of T-cells leads to increased pro-inflammatory cytokine release and increased levels of reactive oxygen and nitrogen species. While disruption is not believed to occur, activated microglia appear to induce blood brain barrier dysfunction in PD 9. Despite this, limited information is available concerning the changes in the distribution of ECM molecules in PD, with the exception of glycosaminoglycans (GAGs) found in senile plaques and...

Supplementary data are available at Bioinformatics online.