Proteomics Profiling of Neuron-Derived Small Extracellular Vesicles from Human Plasma: Enabling Single-Subject Analysis.

Small extracellular vesicles have been intensively studied as a source of biomarkers in neurodegenerative disorders. The possibility to isolate neuron-derived small extracellular vesicles (NDsEV) from blood represents a potential window into brain pathological processes. To date, the absence of sensitive NDsEV isolation and full proteome characterization methods has meant their protein content has been underexplored, particularly for individual patients. Here, we report a rapid method based on an immunoplate covalently coated with mouse monoclonal anti-L1CAM antibody for the isolation and the proteome characterization of plasma-NDsEV from individual Parkinson's disease (PD) patients. We isolated round-shaped vesicles with morphological characteristics consistent with exosomes. On average, 349 ± 38 protein groups were identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis, 20 of which are annotated in the Human Protein Atlas as being highly expressed in the brain, and 213 were shared with a reference NDsEV dataset obtained from cultured human neurons. Moreover, this approach enabled the identification of 23 proteins belonging to the Parkinson disease KEGG pathway, as well as proteins previously reported as PD circulating biomarkers.

Longitudinal Bottom-Up Proteomics of Serum, Serum Extracellular Vesicles, and Cerebrospinal Fluid Reveals Candidate Biomarkers for Early Detection of Glioblastoma in a Murine Model.

Glioblastoma Multiforme (GBM) is a brain tumor with a poor prognosis and low survival rates. GBM is diagnosed at an advanced stage, so little information is available on the early stage of the disease and few improvements have been made for earlier diagnosis. Longitudinal murine models are a promising platform for biomarker discovery as they allow access to the early stages of the disease. Nevertheless, their use in proteomics has been limited owing to the low sample amount that can be collected at each longitudinal time point. Here we used optimized microproteomics workflows to investigate longitudinal changes in the protein profile of serum, serum small extracellular vesicles (sEVs), and cerebrospinal fluid (CSF) in a GBM murine model. Baseline, pre-symptomatic, and symptomatic tumor stages were determined using non-invasive motor tests. Forty-four proteins displayed significant differences in signal intensities during GBM progression. Dysregulated proteins are involved in cell motility, cell growth, and angiogenesis. Most of the dysregulated proteins already exhibited a difference from baseline at the pre-symptomatic stage of the disease, suggesting that early effects of GBM might be detectable before symptom onset.

The mediating role of neuroimaging-derived biological brain age in the association between risk factors for dementia and cognitive decline in middle-aged and older individuals without cognitive impairment: a cohort study.

BACKGROUND: Neuroimaging-based brain-age delta has been shown to be a mediator linking cardiovascular risk factors to cognitive function. We aimed to assess the mediating role of brain-age delta in the association between modifiable risk factors of dementia and longitudinal cognitive decline in middle-aged and older individuals who are asymptomatic, stratified by Alzheimer's disease pathology. We also explored whether the mediation effect is specific to cognitive domain. METHODS: In this cohort study, we included participants from the ALFA+ cohort aged between 45 years and 65 years who were cognitively unimpaired and who had available structural MRI, cerebrospinal fluid ß-amyloid (Aß)42 and Aß40 measurements obtained within 1 year of each other, modifiable risk factors assessment, and cognitive evaluation over 3 years. Participants were recruited from the Barcelonaßeta Brain Research Center (Barcelona, Spain). Included individuals underwent a first assessment between Oct 25, 2016, and Jan 28, 2020, and a follow-up cognitive assessment 3·28 (SD 0·27) years later. We computed brain-age delta and composites of different cognitive function domains (preclinical Alzheimer's cognitive composite [PACC], attention, executive function, episodic memory, visual processing, and language). We used partial least squares path modelling to explore mediation effects in the associations between modifiable risk factors (including cardiovascular, mental health, mood, metabolic or endocrine history, and alcohol use) and changes in cognitive composites. To assess the role of Alzheimer's disease pathology, we computed separate models for Aß-negative and Aß-positive individuals. FINDINGS: Of the 419 participants enrolled in ALFA+, 302 met our inclusion criteria, of which 108 participants were classified as Aß-positive and 194 as Aß-negative. In Aß-positive individuals, brain-age delta partially mediated (percent mediation proportion 15·73% [95% CI 14·22-16·66]) the association between modifiable risk factors and decline in overall cognition (across cognitive domains). Brain-age delta fully mediated (mediation proportion 28·03% [26·25-29·21]) the effect of modifiable risk factors on the PACC, wherein increased values for risk factors correlated with an older brain-age delta, and, consequently, an older brain-age delta was linked to greater PACC decline. This effect appears to be primarily driven by memory decline. Mediation was not significant in Aß-negative individuals (3·52% [0·072-4·17]) on PACC, although path coefficients were not significantly different from those in the Aß-positive group. INTERPRETATION: Our findings suggest that brain-age delta captures the association between modifiable risk factors and longitudinal cognitive decline in middle-aged and older people. In asymptomatic middle-aged and older individuals who are Aß-positive, the pathology might be the strongest driver of cognitive decline, whereas the effect of risk factors is smaller. Our results highlight the potential of brain-age delta as an objective outcome measure for preventive lifestyle interventions targeting cognitive decline. FUNDING: La Caixa Foundation, the TriBEKa Imaging Platform, and the Universities and Research Secretariat of the Catalan Government. TRANSLATION: For the Spanish translation of the abstract see Supplementary Materials section.

Proteomics analysis of circulating small extracellular vesicles: Focus on the contribution of EVs to tumor metabolism.

The term small extracellular vesicle (sEV) is a comprehensive term that includes any type of cell-derived, membrane-delimited particle that has a diameter < 200 nm, and which includes exosomes and smaller microvesicles. sEVs transfer bioactive molecules between cells and are crucial for cellular homeostasis and particularly during tumor development, where sEVs provide important contributions to the formation of the premetastic niche and to their altered metabolism. sEVs are thus legitimate targets for intervention and have also gained increasing interest as an easily accessible source of biomarkers because they can be rapidly isolated from serum/plasma and their molecular cargo provides information on their cell-of origin. To target sEVs that are specific for a given cell/disease it is essential to identify EV surface proteins that are characteristic of that cell/disease. Mass-spectrometry based proteomics is widely used for the identification and quantification of sEV proteins. The methods used for isolating the sEVs, preparing the sEV sample for proteomics analysis, and mass spectrometry analysis, can have a strong influence on the results and requires careful consideration. This review provides an overview of the approaches used for sEV proteomics and discusses the inherent compromises regarding EV purity versus depth of coverage. Additionally, it discusses the practical applications of the methods to unravel the involvement of sEVs in regulating the metabolism of pancreatic ductal adenocarcinoma (PDAC). The metabolic reprogramming in PDAC includes enhanced glycolysis, elevated glutamine metabolism, alterations in lipid metabolism, mitochondrial dysfunction and hypoxia, all of which are crucial in promoting tumor cell growth. A thorough understanding of these metabolic adaptations is imperative for the development of targeted therapies to exploit PDAC's vulnerabilities.

Isolation and Proteomic Analysis of Mouse Serum Small Extracellular Vesicles for Individual Subject Analysis.

Proteomics characterization of blood and circulating material has been extensively explored for the study of pathological states. In particular, circulating small extracellular vesicles (sEV, diameter: 30-150 nm) are known to play an important role in intercellular communication processes, and proteomics profiling has been explored to develop minimally invasive assays for disease monitoring and diagnosis. Due to the genetic and physiological similarities between the two species, and also on account of their shorter life span and rapid disease progression, rodent models are the most commonly used animal model for many human diseases. Such models have provided invaluable insight into the molecular mechanisms of disease progression, candidate drug efficacy, therapy monitoring, and biomarkers research.Longitudinal investigations, in which individuals are monitored over periods of time, are more able to resolve molecular changes during disease progression because they circumvent the inter-individual variation. Longitudinal investigations of rodent models are challenging because of the limited amount of blood that can be withdrawn at each time; the American Association of Veterinary Science stipulates that fortnightly sampling should be limited to a maximum of 10% of the total blood volume. For adult mice this corresponds to approximately 75 µL of serum. We developed an approach for the isolation and characterization of serum sEV proteins from just 50 µL of serum, for longitudinal studies of disease mouse models. This chapter describes in detail the steps and considerations involved in the sEV isolation, morphological characterization, and proteome profiling by mass spectrometry.

Proteomics analysis of serum small extracellular vesicles for the longitudinal study of a glioblastoma multiforme mouse model.

Longitudinal analysis of disease models enables the molecular changes due to disease progression or therapeutic intervention to be better resolved. Approximately 75 µl of serum can be drawn from a mouse every 14 days. To date no methods have been reported that are able to analyze the proteome of small extracellular vesicles (sEV's) from such low serum volumes. Here we report a method for the proteomics analysis of sEV's from 50 µl of serum. Two sEV isolation procedures were first compared; precipitation based purification (PPT) and size exclusion chromatography (SEC). The methodological comparison confirmed that SEC led to purer sEV's both in terms of size and identified proteins. The procedure was then scaled down and the proteolytic digestion further optimized. The method was then applied to a longitudinal study of serum-sEV proteome changes in a glioblastoma multiforme (GBM) mouse model. Serum was collected at multiple time points, sEV's isolated and their proteins analyzed. The protocol enabled 274 protein groups to be identified and quantified. The longitudinal analysis revealed 25 deregulated proteins in GBM serum sEV's including proteins previously shown to be associated with GBM progression and metastasis (Myh9, Tln-1, Angpt1, Thbs1).