PLasmatic Extracellular Vesicles AS Biomarkers of nEural Tissue Damage

Neurodegenerative disorders are among the main challenges of future health care. The current lack of effective treatments and the discouraging signals of disappointing feedback from the pharma industry, are possibly due to the lack of accessible and inexpensive tools to perform early diagnosis, monitor disease progression, and evaluate possible response to treatments. The search of biomarkers for neurological disorders has lately received high attention with the availability of new technologies that allow detection, in the blood, of extracellular vesicles (EVs) released by cells of the central nervous system, and CNS-derived molecules through highly sensitive immunoassays. We propose here to take advantage of these technologies to detect EVs in the blood with the most sensitive techniques to identify proteins, and nucleic acids, with the aim to uncovering the most promising blood biomarkers to detect disease and monitor progression in patients affected by multiple sclerosis, and stroke. The reason to choose these diseases is very simple: stroke allows to have a very defined initial event, causing a large tissue damage, supposed to create an identifiable wave of released biomarkers in peripheral blood. Multiple sclerosis, on the other hands, represents a prototypical chronic disease of the CNS, needing prolonged monitoring. We hypothesize that if we identify a novel tissue biomarker, being it an EVs subtype, or one of its contents, it will be more easily identified in stroke, but relevant also in MS. In both cases imaging, and in particular MRI, cannot be replaced. Nevertheless, both disease have unsatisfying biomarkers available right now to monitor the neurodegenerative phases of their evolution. Our current proposal relies on techniques and knowledge that are already available in the consortium. The identification of new reliable biomarkers for neurodegenerative processes underlying pathologies like MS and stroke has a potential tremendous effect on patients but also on drug development and, therefore, on pharmaceutical industry, allowing to test in a more economical and timely way numerous compounds and considerably increasing the chances to find an effective treatment on empirical basis.

Specific Aim 1 Set-up of neural EVs detection tehcniques. We have used brain assembloids, containing neurons, astrocytes, oligodendrocytes, and microglia, to analyze the supernatant for the presence of released EVs and to set up the best techniques for their detection. We screened several antibodies for surface antigens and we found that we could detect PLP (oligodendrocytes), CD171 (neurons), GLAST (astrocytes), and TREM-2 (microglia/myeloid cells) positive EVs using ExoView. When we moved to flow cytometry, however, not all markers were equally working, but we could detect in plasma from stroke patients during the acute phase PLP, CD171, and TREM-2 positive Evs. We will complete the set-up to have also an astrocytic marker to be included in our panel of antibodies working in flow cytometry. The final goal will be to move our detection techniques onto spectral flow cytometry platforms (i.e. Cytek Aurora), suited for routine analysis of clinical samples. Both Unit 1 and Unit 2 have large experience in flow cytometry of EVs. Both units, however, have also large experience with the SIMOA (Quanterix) platform. This platform has been used for high sensitivity detection of EVs in biological fluids. We will therefore test identified antibodies on the SIMOA platform, to assess if we can increase sensitivity over spectral flow cytometry. Finally, we will need to harmonize protocols between Unit 1 and Unit 2 before moving to assess clinical samples. Our Specific AIM 1 is therefore subdivided in three work packages: WP1. Set-up of spectral flow cytometry for the detection of neuronal, astrocytic, oligodendroglial, microglial/myeloid EVs in plasma.

WP2. Set-up of SIMOA home-brew assays for the detection of neuronal, astrocytic, oligodendroglial, microglial/myeloid EVs in plasma, and comparison to spectral flow cytometry in terms of sensitivity.

WP3. Harmonisation of protocols among the two units achieved by exchange of blinded samples.

Specific Aim 2 Neural EVs measurement in plasma of multiple sclerosis and stroke patients. MS is sustained by multifaceted pathogenic mechanisms. Current treatments address successfully acute inflammation, but fail to target neurodegenerative processes that are ongoing since the early phases of the disease. Similarly, current stroke treatments can efficiently target risk factors and ameliorate the acute phase by thrombolysis and/or thrombectomy, but cannot halt the following neurodegenerative processes that considerably enlarge the originally damaged area. New biomarkers, able to monitor the different ongoing pathogenic mechanisms, and especially neurodegeneration, are needed to allow tailoring of treatments in the case of MS, and to for more reliable prognosis for stroke. In both cases, physical and cognitive rehabilitation is offered to patients, and the measurement of ongoing tissue damage in real time would allow to evaluate the impact of drugs and rehabilitative activities on the CNS. To this aim we plan to enroll 20 persons during the diagnostic work up for MS, usually close to an acute phase, and 20 stroke patients. Patients will be selected and sampled by both Units. For persons with MS (18-55yrs, balanced for sex, excluding other inflammatory or neurological comorbidities) sampling will occur on the first day and then at three months intervals for the first year. For stroke patients (20-65yrs balanced for sex, excluding other inflammatory or neurological comorbidities) sampling will occur at baseline, day one, day three, day seven and day fourteen. Twenty healthy donors, matched for sex and age, will used for reference values. Plasma EVs will be measured and/or isolated on fresh samples, since freezing alters EVs features and composition. We will collect also clinical and paraclinical, including standard routine imaging, data. We also will measure plasma levels of NfL, GFAP, TAU, and UCHL-1, to allow comparison with currently investigated tissue damage biomarkers. Our Specific AIM 2 is therefore subdivided in three work packages: WP1. Selection and enrollment of persons with MS at diagnosis and of stroke patients according to indicated inclusion/exclusion criteria. Selection of the healthy donors control group. Clinical follow up of patients.

WP2. Measurements of neural plasma EVs and plasma tissue damage biomarkers. WP3. Isolation and storage of plasma EVs. The number of neural plasma EVs is so limited that it will not possible to isolate them for further analysis. We will therefore collect whole plasma EVs using size exclusion columns.

Specific Aim 3

Analysis of EVs isolated from the plasma of MS and stroke patients. Surface markers that we have selected to identify neural EVs may not be the most informative markers. In particular, the composition of EVs may possibly provide additional information bearing clinical usefulness. To investigate this possibility, at the time of sampling, we will process plasma samples of persons with MS at diagnosis and of stroke patients at baseline to immediately isolate total EVs. Downstream analyses will comprise proteomic and next generation sequencing (NGS) analyses to identify by bioinformatic and biostatistical tools candidate signaling pathways potentially referring to CNS releasing cells, and suggesting new biomarkers. As already stated, tissue damage biomarkers have been already described but bear substantial defects. Neurofilament light chain, the most investigated CNS tissue damage marker, ready for clinical translation, does not differentiate between central and peripheral nervous system, and is not ideal to capture neurodegeneration, rather acute damage. We have described EVs over ten years ago as potential biomarkers of tissue damage in neurological diseases but despite technological improvements, their detection remains a challenge, limited to highly sensitive technologies that are difficult to adapt to routine workout. Therefore, along with the set-up of relatively more handy technologies like spectral flow cytometry and SIMOA, we will also explore EVs as a potential casket of new biomarkers more easy to be exploited in a clinical setting. Our Specific AIM 3 is therefore subdivided in three work packages, performed by Unit 1:

WP1. Proteomic analysis of isolated EVs will be performed by modifed single-pot, solidphase-enhanced (SP3) sample preparation protocol. LC-MS/MS experiments will use an Easy-nLC 1000 coupled to an Orbitrap Fusion mass spectrometer (Termo Fisher Scientifc) Raw data files will be processed using Proteome Discoverer 2.1 (Termo Scientific).

WP2. NGS of isolated EVs content will be performed as follows: total RNA will be isolated with QIAGEN miRNeasy Kit for miRNA Purification. To generate the libraries, we will exploit the TruSeq stranded mRNA protocol. Libraries will be barcoded, pooled and sequenced on an Illumina Nova-Seq 6000 sequencing system. Differential gene expression will be assessed in R/BioConductor using the DESeq2 package, which represents the state-of-the art in analysis of quantitative data using negative binomial models.

WP3. Identification of potentially biomarkers delivered by EVs through bioinformatic analysis. Combining the information gained by proteomic and transcriptomic analysis of plasma EVs, we aim at identifying signals with a potential as biomarkers. We will perform differential expression analysis on the count data will be performed using the R package DESeq2. Functional enrichment analysis (ontologies, pathways, etc.) will be performed using Enrichr as database library to identify pathways deregulated in the various subsets.