Fluid phase biomarkers in multiple sclerosis

Investigating the Potential of Extracellular Vesicles as Delivery Systems for Chemotherapeutics

BACKGROUND/OBJECTIVES

Standard chemotherapy is generally considered the best approach to treat many solid cancers, even accounting for severe side effects. Therefore, the development of a drug delivery system for chemotherapeutic administration could significantly improve standard chemotherapy by maintaining the cytotoxic effects of the drugs while decreasing the inherent side effects of the treatment. The aim of our study is the optimization of a loading strategy that conjugates the use of extracellular vesicles (EVs) as drug delivery carriers, by preserving their integrity, with the loading efficiency and activity maintenance of chemotherapeutics.

METHODS

We compared the EV loading of the chemotherapeutics epirubicin, mitomycin, methotrexate and mitoxantrone by co-incubation. Once loaded, the activity of drug-carrying EVs was tested on cancer cells and compared to that of free chemotherapeutics.

RESULTS

We defined a linear correlation between chemotherapeutics' concentration and their absorbance at the drug-specific wavelength, which allowed the definition of a highly sensitive absorbance-based spectrophotometric quantification system, enabling the assessment of drug loading efficiency. Co-incubation of EVs and chemotherapeutics was sufficient to obtain quantifiable drug loading, and the efficacy of EV loading was drug-dependent. Epirubicin-loaded vesicles showed increased toxicity to bladder cancer cells with respect to the free chemotherapeutic. The cytotoxicity was maintained even upon 6-month storage at -80 °C of loaded EVs.

CONCLUSION

We established an absorbance-based spectrophotometric quantification system that enables a straightforward measure of drug loading efficiency into EVs, and we demonstrated that chemotherapeutic-carrying EVs can be obtained by co-incubation, preserving and increasing drug cytotoxicity.

Tetraspanins, GLAST and L1CAM Quantification in Single Extracellular Vesicles from Cerebrospinal Fluid and Serum of People with Multiple Sclerosis

Objective: This study aimed to unravel the single tetraspanin pattern of extracellular vesicles (EVs), L1CAM+ and GLAST+ EV levels as diagnostic biomarkers to stratify people with multiple sclerosis (pwMS), specifically relapsing-remitting (RRMS) and primary progressive (PPMS). Methods: The ExoView platform was used to directly track single EVs using a clinically feasible volume of cerebrospinal fluid (CSF) and serum samples. This technology allowed us to examine the patterns of classical tetraspanin and quantify the levels of L1CAM and GLAST proteins, commonly used to immunoisolate putative neuron- and astrocyte-derived EVs. Results: The tetraspanin EV pattern does not allow us to differentiate RRMS, PPMS and non-MS donors neither in CSF nor serum, but this was associated with the type of biofluid. L1CAM+ and GLAST+ EVs showed a very low presence of tetraspanin proteins. Additionally, a significant decrease in the particle count of L1CAM+ EVs was detected in L1CAM-captured spots, and L1CAM+ and GLAST+ EVs decreased in GLAST-captured spots in the CSF from PPMS subjects compared to RRMS. Interestingly, only GLAST+ EVs exhibited a lower quantity in the CSF from PPMS compared to both MS and non-MS samples. Finally, GLAST+ EVs demonstrated a medium negative and significative correlation with GFAP levels-a biomarker of MS progression, astrocyte damage and neurodegenerative processes. Conclusions: ExoView technology could track neural EV biomarkers and be potentially useful in the diagnostic evaluation and follow-up of pwMS. GLAST+ EVs might provide insights into the etiology of PPMS and could offer small windows to elucidate the molecular mechanisms behind its clinical presentation.

The interaction between exercise and neurofilament light chain in multiple sclerosis: a systematic review and meta-analysis

BACKGROUND

Exercise in patients with multiple sclerosis (pwMS) found to improve symptom management and regain function. Whether exercise lowers neurofilament light chain (NfL), neuroaxonal injury biomarker, in MS remains unknown with conflicting findings. In this study, we aimed to assess the interaction between exercise and NfL levels in pwMS.

METHODS

Systematic search of Medline, CENTRAL, Embase, and Web of Science was conducted until March 2024 to identify relevant reports. We included studies that investigated the mean change in NfL levels pre- and post-training programs and compared them to different exercise programs or no exercise activity control groups. A standardized mean difference (SMD) with a 95 % confidence interval were applied using a random-effects model.

RESULTS

Of 222 articles, 7 studies met the inclusion criteria. Patients who underwent structured exercise programs had a significant decrease in blood NfL levels post-training (SMD -0.55; 95 % CI -1.00, -0.09). Specifically, outdoor Pilates and home-based trainings were significantly associated with blood NfL reduction (SMD -2.08; 95 % CI -2.99, -1.17) and (SMD -1.46; 95 % CI -2.28, -0.64), respectively. Patients in the control group did not show significant differences in blood NfL levels between the baseline and at the end of the study (SMD 0.04; 95 % CI -0.17, 0.24). Subgroup analysis based on duration revealed that 8 weeks of exercise significantly reduced blood NfL levels (SMD -0.73; 95 % CI -1.35, -0.11).

CONCLUSION

Our study provides preliminary evidence for the potential role of training in reducing blood NfL levels in pwMS. However, more rigorous, and well-designed studies are warranted to confirm these findings.

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.

Modeling and simulation for prediction of multiple sclerosis progression

In light of extensive work that has created a wide range of techniques for predicting the course of multiple sclerosis (MS) disease, this paper attempts to provide an overview of these approaches and put forth an alternative way to predict the disease progression. For this purpose, the existing methods for estimating and predicting the course of the disease have been categorized into clinical, radiological, biological, and computational or artificial intelligence-based markers. Weighing the weaknesses and strengths of these prognostic groups is a profound method that is yet in need and works directly at the level of diseased connectivity. Therefore, we propose using the computational models in combination with established connectomes as a predictive tool for MS disease trajectories. The fundamental conduction-based Hodgkin-Huxley model emerged as promising from examining these studies. The advantage of the Hodgkin-Huxley model is that certain properties of connectomes, such as neuronal connection weights, spatial distances, and adjustments of signal transmission rates, can be taken into account. It is precisely these properties that are particularly altered in MS and that have strong implications for processing, transmission, and interactions of neuronal signaling patterns. The Hodgkin-Huxley (HH) equations as a point-neuron model are used for signal propagation inside a small network. The objective is to change the conduction parameter of the neuron model, replicate the changes in myelin properties in MS and observe the dynamics of the signal propagation across the network. The model is initially validated for different lengths, conduction values, and connection weights through three nodal connections. Later, these individual factors are incorporated into a small network and simulated to mimic the condition of MS. The signal propagation pattern is observed after inducing changes in conduction parameters at certain nodes in the network and compared against a control model pattern obtained before the changes are applied to the network. The signal propagation pattern varies as expected by adapting to the input conditions. Similarly, when the model is applied to a connectome, the pattern changes could give an insight into disease progression. This approach has opened up a new path to explore the progression of the disease in MS. The work is in its preliminary state, but with a future vision to apply this method in a connectome, providing a better clinical tool.

Immunosensors for Autoimmune-Disease-Related Biomarkers: A Literature Review

Immunosensors are a special class of biosensors that employ specific antibodies for biorecognition of the target analyte. Immunosensors that target disease biomarkers may be exploited as tools for disease diagnosis and/or follow-up, offering several advantages over conventional analytical techniques, such as rapid and easy analysis of patients' samples at the point-of-care. Autoimmune diseases have been increasingly prevalent worldwide in recent years, while the COVID-19 pandemic has also been associated with autoimmunity. Consequently, demand for tools enabling the early and reliable diagnosis of autoimmune diseases is expected to increase in the near future. To this end, interest in immunosensors targeting autoimmune disease biomarkers, mainly, various autoantibodies and specific pro-inflammatory proteins (e.g., specific cytokines), has been rekindled. This review article presents most of the immunosensors proposed to date as potential tools for the diagnosis of various autoimmune diseases, such as type 1 diabetes, rheumatoid arthritis, and multiple sclerosis. The signal transduction and the immunoassay principles of each immunosensor have been suitably classified and are briefly presented along with certain sensor elements, e.g., special nano-sized materials used in the construction of the immunosensing surface. The main concluding remarks are presented and future perspectives of the field are also briefly discussed.

Novel CSF Biomarkers Tracking Autoimmune Inflammatory and Neurodegenerative Aspects of CNS Diseases

The accurate diagnosis of neuroinflammatory (NIDs) and neurodegenerative (NDDs) diseases and the stratification of patients into disease subgroups with distinct disease-related characteristics that reflect the underlying pathology represents an unmet clinical need that is of particular interest in the era of emerging disease-modifying therapies (DMT). Proper patient selection for clinical trials and identifying those in the prodromal stages of the diseases or those at high risk will pave the way for precision medicine approaches and halt neuroinflammation and/or neurodegeneration in early stages where this is possible. Towards this direction, novel cerebrospinal fluid (CSF) biomarker candidates were developed to reflect the diseased organ's pathology better. Μisfolded protein accumulation, microglial activation, synaptic dysfunction, and finally, neuronal death are some of the pathophysiological aspects captured by these biomarkers to support proper diagnosis and screening. We also describe advances in the field of molecular biomarkers, including miRNAs and extracellular nucleic acids known as cell-free DNA and mitochondrial DNA molecules. Here we review the most important of these novel CSF biomarkers of NIDs and NDDs, focusing on their involvement in disease development and emphasizing their ability to define homogeneous disease phenotypes and track potential treatment outcomes that can be mirrored in the CSF compartment.