L1CAM immunocapture generates a unique extracellular vesicle population with a reproducible miRNA fingerprint

CNS cell-derived exosome signatures as blood-based biomarkers of neurodegenerative diseases

Molecular biomarkers require the reproducible capture of disease-associated changes and are ideally sensitive, specific and accessible with minimal invasiveness to patients. Exosomes are a subtype of extracellular vesicles that have gained attention as potential biomarkers. They are released by all cell types and carry molecular cargo that reflects the functional state of the cells of origin. These characteristics make them an attractive means of measuring disease-related processes within the central nervous system (CNS), as they cross the blood-brain barrier (BBB) and can be captured in peripheral blood. In this review, we discuss recent progress made toward identifying blood-based protein and RNA biomarkers of several neurodegenerative diseases from circulating, CNS cell-derived exosomes. Given the lack of standardized methodology for exosome isolation and characterization, we discuss the challenges of capturing and quantifying the molecular content of exosome populations from blood for translation to clinical use.

Immune capture and protein profiling of small extracellular vesicles from human plasma

Extracellular vesicles (EVs), the key players in inter-cellular communication, are produced by all cell types and are present in all body fluids. Analysis of the proteome content is an important approach in structural and functional studies of these vesicles. EVs circulating in human plasma are heterogeneous in size, cellular origin, and functions. This heterogeneity and the potential presence of contamination with plasma components such as lipoprotein particles and soluble plasma proteins represent a challenge in profiling the proteome of EV subsets by mass spectrometry. An immunocapture strategy prior to mass spectrometry may be used to isolate a homogeneous subpopulation of small EVs (sEV) with a specific endocytic origin from plasma or other biofluids. Immunocapture selectively separates EV subpopulations in biofluids based on the presence of a unique protein carried on the vesicle surface. The advantages and disadvantages of EV immune capture as a preparative step for mass spectrometry are discussed.

A Machine Learning Approach for Highlighting microRNAs as Biomarkers Linked to Amyotrophic Lateral Sclerosis Diagnosis and Progression

Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease characterized by the progressive loss of motor neurons in the brain and spinal cord. The early diagnosis of ALS can be challenging, as it usually depends on clinical examination and the exclusion of other possible causes. In this regard, the analysis of miRNA expression profiles in biofluids makes miRNAs promising non-invasive clinical biomarkers. Due to the increasing amount of scientific literature that often provides controversial results, this work aims to deepen the understanding of the current state of the art on this topic using a machine-learning-based approach. A systematic literature search was conducted to analyze a set of 308 scientific articles using the MySLR digital platform and the Latent Dirichlet Allocation (LDA) algorithm. Two relevant topics were identified, and the articles clustered in each of them were analyzed and discussed in terms of biomolecular mechanisms, as well as in translational and clinical settings. Several miRNAs detected in the tissues and biofluids of ALS patients, including blood and cerebrospinal fluid (CSF), have been linked to ALS diagnosis and progression. Some of them may represent promising non-invasive clinical biomarkers. In this context, future scientific priorities and goals have been proposed.

Prevalence of amyotrophic lateral sclerosis in the United States, 2018

OBJECTIVE

To estimate prevalent ALS cases in the United States for calendar year 2018.

METHODS

The National ALS Registry (Registry) compiled data from national administrative databases (from the Centers for Medicare and Medicaid Services, the Veterans Health Administration, and the Veterans Benefits Administration) and enrollment data voluntarily submitted through a web portal (www.cdc.gov/als). We used log-linear capture-recapture (CRC) model-based methodology to estimate the number of cases not ascertained by the Registry.

RESULTS

The Registry identified 21,655 cases of ALS in 2018, with an age-adjusted prevalence of 6.6 per 100,000 U.S. population. When CRC methods were used, an estimated 29,824 cases were identified, for an adjusted prevalence of 9.1 per 100,000 U.S. population. The demographics of cases of ALS did not change from previous year's reports. ALS continues to impact Whites, males, and persons over 50 years of age more so than other comparison groups. The results from the present report suggest case ascertainment for the Registry has improved, with the estimate of missing prevalent cases decreasing from 44% in 2017 to 27% in in 2018.

DISCUSSION

Consistent with previous estimates that used CRC, ALS prevalence in the United States is about 29,824 cases per year.

Challenges associated with using extracellular vesicles as biomarkers in neurodegenerative disease

INTRODUCTION

The hunt for new biomarkers - for the diagnosis of subcategories of disease, or for the monitoring of the efficacy of novel therapeutics - is an increasingly relevant challenge in the current era of precision medicine. In neurodegenerative research, the aim is to look for simple tools which can predict cognitive or motor decline early, and to determine whether these can also be used to test the efficacy of new interventions. Extracellular vesicles (EVs) are thought to play an important role in intercellular communication and have been shown to play a vital role in a number of diseases.

AREAS COVERED

The aim of this review is to examine what we know about EVs in neurodegeneration and to discuss their potential to be diagnostic and prognostic biomarkers in the future. It will cover the techniques used to isolate and study EVs and what is currently known about their presence in neurodegenerative diseases. In particular, we will discuss what is required for standardization in biomarker research, and the challenges associated with using EVs within this framework.

EXPERT OPINION

The technical challenges associated with isolating EVs consistently, combined with the complex techniques required for their efficient analysis, might preclude 'pure' EV populations from being used as effective biomarkers. Whilst biomarker discovery is important for more effective diagnosis, monitoring, prediction and prognosis in neurodegenerative disease, reproducibility and ease-of-use should be the priorities.