Monocyte NOTCH2 expression predicts IFN-β immunogenicity in multiple sclerosis patients

Current Knowledge about Nonclassical Monocytes in Patients with Multiple Sclerosis, a Systematic Review

Monocytes play a critical role in the initiation and progression of multiple sclerosis (MS). Recent research indicates the importance of considering the roles of monocytes in the management of MS and the development of effective interventions. This systematic review examined published research on the roles of nonclassical monocytes in MS and how they influence disease management. Reputable databases, such as PubMed, EMBASE, Cochrane, and Google Scholar, were searched for relevant studies on the influence of monocytes on MS. The search focused on studies on humans and patients with experimental autoimmune encephalomyelitis (EAE) published between 2014 and 2024 to provide insights into the study topic. Fourteen articles that examined the role of monocytes in MS were identified; the findings reported in these articles revealed that nonclassical monocytes could act as MS biomarkers, aid in the development of therapeutic interventions, reveal disease pathology, and improve approaches for monitoring disease progression. This review provides support for the consideration of monocytes when researching effective diagnostics, therapeutic interventions, and procedures for managing MS pathophysiology. These findings may guide future research aimed at gaining further insights into the role of monocytes in MS.

Immunopathogenesis of multiple sclerosis: molecular and cellular mechanisms and new immunotherapeutic approaches

BACKGROUND

Multiple sclerosis (MS) is a central nervous system (CNS) demyelinating autoimmune disease with increasing global prevalence. It predominantly affects females, especially those of European descent. The interplay between environmental factors and genetic predisposition plays a crucial role in MS etiopathogenesis.

METHODS

We searched recent relevant literature on reputable databases, which include, PubMed, Embase, Web of Science, Scopus, and ScienceDirect using the following keywords: multiple sclerosis, pathogenesis, autoimmunity, demyelination, therapy, and immunotherapy.

RESULTS

Various animal models have been employed to investigate the MS etiopathogenesis and therapeutics. Autoreactive T cells within the CNS recruit myeloid cells through chemokine expression, leading to the secretion of inflammatory cytokines driving the MS pathogenesis, resulting in demyelination, gliosis, and axonal loss. Key players include T cell lymphocytes (CD4+ and CD8+), B cells, and neutrophils. Signaling dysregulation in inflammatory pathways and the immunogenetic basis of MS are essential considerations for any successful therapy to MS. Data indicates that B cells and neutrophils also have significant roles in MS, despite the common belief that T cells are essential. High neutrophil-to-lymphocyte ratios correlate with MS severity, indicating their contribution to disease progression. Dysregulated signaling pathways further exacerbate MS progression.

CONCLUSION

MS remains incurable, but disease-modifying therapies, monoclonal antibodies, and immunomodulatory drugs offer hope for patients. Research on the immunogenetics and immunoregulatory functions of gut microbiota is continuing to provide light on possible treatment avenues. Understanding the complex interplay between genetic predisposition, environmental factors, and immune dysregulation is critical for developing effective treatments for MS.

Blood metabolomic and transcriptomic signatures stratify patient subgroups in multiple sclerosis according to disease severity

There are no blood-based biomarkers distinguishing patients with relapsing-remitting (RRMS) from secondary progressive multiple sclerosis (SPMS) although evidence supports metabolomic changes according to MS disease severity. Here machine learning analysis of serum metabolomic data stratified patients with RRMS from SPMS with high accuracy and a putative score was developed that stratified MS patient subsets. The top differentially expressed metabolites between SPMS versus patients with RRMS included lipids and fatty acids, metabolites enriched in pathways related to cellular respiration, notably, elevated lactate and glutamine (gluconeogenesis-related) and acetoacetate and bOHbutyrate (ketone bodies), and reduced alanine and pyruvate (glycolysis-related). Serum metabolomic changes were recapitulated in the whole blood transcriptome, whereby differentially expressed genes were also enriched in cellular respiration pathways in patients with SPMS. The final gene-metabolite interaction network demonstrated a potential metabolic shift from glycolysis toward increased gluconeogenesis and ketogenesis in SPMS, indicating metabolic stress which may trigger stress response pathways and subsequent neurodegeneration.

Single-Cell Sequencing Combined with Transcriptome Sequencing Constructs a Predictive Model of Key Genes in Multiple Sclerosis and Explores Molecular Mechanisms Related to Cellular Communication

Background

Multiple sclerosis (MS) causes chronic inflammation and demyelination of the central nervous system and comprises a class of neurodegenerative diseases in which interactions between multiple immune cell types mediate the involvement of MS development. However, the early diagnosis and treatment of MS remain challenging.

Methods

Gene expression profiles of MS patients were obtained from the Gene Expression Omnibus (GEO) database. Single-cell and intercellular communication analyses were performed to identify candidate gene sets. Predictive models were constructed using LASSO regression. Relationships between genes and immune cells were analyzed by single sample gene set enrichment analysis (ssGSEA). The molecular mechanisms of key genes were explored using gene enrichment analysis. An miRNA network was constructed to search for target miRNAs related to key genes, and related transcription factors were searched by transcriptional regulation analysis. We utilized the GeneCard database to detect the correlations between disease-regulated genes and key genes. We verified the mRNA expression of 4 key genes by reverse transcription-quantitative PCR (RT‒qPCR).

Results

Monocyte marker genes were selected as candidate gene sets. CD3D, IL2RG, MS4A6A, and NCF2 were found to be the key genes by LASSO regression. We constructed a prediction model with AUC values of 0.7569 and 0.719. The key genes were closely related to immune factors and immune cells. We explored the signaling pathways and molecular mechanisms involving the key genes by gene enrichment analysis. We obtained and visualized the miRNAs associated with the key genes using the miRcode database. We also predicted the transcription factors involved. We used validated key genes in MS patients, several of which were confirmed by RT‒qPCR.

Conclusion

The prediction model constructed with the CD3D, IL2RG, MS4A6A, and NCF2 genes has good diagnostic efficacy and provides new ideas for the diagnosis and treatment of MS.

Longitudinal analysis of anti-drug antibody development in multiple sclerosis patients treated with interferon beta-1a (Rebif™) using B cell receptor repertoire analysis

A significant proportion of multiple sclerosis (MS) patients treated with interferon beta-1a (Rebif™) develop anti-drug antibodies (ADA) with a negative impact on treatment efficacy. We hypothesized that high-throughput B-cell receptor (BCR) repertoire analysis could be used to predict and monitor ADA development. To study this we analyzed 228 peripheral blood samples from 68 longitudinally followed patients starting on interferon beta-1a. Our results show that whole blood BCR analysis does not reflect, and does not predict ADA development in MS patients treated with interferon beta-1a. We propose that BCR analysis of phenotypically selected cell subsets or tissues might be more informative.

Implementing a Clinical Immunogenicity Strategy using Preclinical Risk Assessment Outputs

Immunogenicity to biologics is often observed following dosing in human subjects during clinical trials. Both product and host specific factors may be implicated in contributing to a potential immune response. However, even if such risk factors are identified and eliminated as part of the rational quality by design approaches, the outcome in clinic can be uncertain and challenging to predict. Several tools have been employed to identify these risk factors and consequent mitigation approaches implemented prior to dosing in humans. However, the complexity of the immune system with an interplay of network of immune cells involved in driving a long- term immune response as well as patient characteristics, can make it challenging to predict the outcome in clinic. This perspective will provide an insight into recent advances in the risk assessment approaches that are utilized during preclinical stage of development of a biologic. The outputs from such tools can help to rank order and select the most optimal candidate with the least likelihood of an immune response and can further drive the development of a clinical bioanalytical and immunogenicity monitoring strategy. Such a strategy can be proactively shared with the regulators along with the proposal to streamline clinical immunogenicity and personalizing the outcome based on pharmacogenomics and other patient-related factors. This paper provides a roadmap on performing risk assessments through a systematic identification of risks and their mitigations wherever possible. Recommendations on incorporating the key components of such risk assessments as part of the new regulatory submissions are also provided. Shorter abstract Immunogenicity to biologics is common during clinical trials. Both product and host specific factors have been implicated. Several risk assessment tools can be used to identify and mitigate the risk factors responsible for immunogenicity. An insight into recent advances in the risk assessment approaches will be presented. The outputs can define a risk score and guide the clinical bioanalytical and immunogenicity monitoring strategy. A roadmap on performing risk assessments through a systematic identification of risks and their mitigations wherever possible is provided. Best practices for a risk assessment strategy and recommendations on the content for IND and the Integrated summary of Immunogenicity are also provided.

Human Monocytes Plasticity in Neurodegeneration

Monocytes play a crucial role in immunity and tissue homeostasis. They constitute the first line of defense during the inflammatory process, playing a role in the pathogenesis and progression of diseases, making them an attractive therapeutic target. They are heterogeneous in morphology and surface marker expression, which suggest different molecular and physiological properties. Recent evidences have demonstrated their ability to enter the brain, and, as a consequence, their hypothetical role in different neurodegenerative diseases. In this review, we will discuss the current knowledge about the correlation between monocyte dysregulation in the brain and/or in the periphery and neurological diseases in humans. Here we will focus on the most common neurodegenerative disorders, such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis and multiple sclerosis.

Targeting the Notch Signaling Pathway in Chronic Inflammatory Diseases

The Notch signaling pathway regulates developmental cell-fate decisions and has recently also been linked to inflammatory diseases. Although therapies targeting Notch signaling in inflammation in theory are attractive, their design and implementation have proven difficult, at least partly due to the broad involvement of Notch signaling in regenerative and homeostatic processes. In this review, we summarize the supporting role of Notch signaling in various inflammation-driven diseases, and highlight efforts to intervene with this pathway by targeting Notch ligands and/or receptors with distinct therapeutic strategies, including antibody designs. We discuss this in light of lessons learned from Notch targeting in cancer treatment. Finally, we elaborate on the impact of individual Notch members in inflammation, which may lay the foundation for development of therapeutic strategies in chronic inflammatory diseases.

Type I Interferon (IFN)-Regulated Activation of Canonical and Non-Canonical Signaling Pathways

For several decades there has been accumulating evidence implicating type I interferons (IFNs) as key elements of the immune response. Therapeutic approaches incorporating different recombinant type I IFN proteins have been successfully employed to treat a diverse group of diseases with significant and positive outcomes. The biological activities of type I IFNs are consequences of signaling events occurring in the cytoplasm and nucleus of cells. Biochemical events involving JAK/STAT proteins that control transcriptional activation of IFN-stimulated genes (ISGs) were the first to be identified and are referred to as "canonical" signaling. Subsequent identification of JAK/STAT-independent signaling pathways, critical for ISG transcription and/or mRNA translation, are denoted as "non-canonical" or "non-classical" pathways. In this review, we summarize these signaling cascades and discuss recent developments in the field, specifically as they relate to the biological and clinical implications of engagement of both canonical and non-canonical pathways.

Immunogenicity of biologic therapies in psoriasis: Myths, facts and a suggested approach

With biologic drugs dominating the therapeutic space for severe immune-mediated inflammatory disease, it is critical for clinicians to be familiar with the concept of drug immunogenicity, with the potential for our patients to develop antidrug antibodies (ADA) of clinical relevance. Whilst there are clear differences between different therapeutic biologics in terms of reported ADA rates, there is no accepted dermatology guideline or grouping of drugs by risk of clinically relevant ADA, nor a consensus on approach to ADA management. This is partly because making valid comparisons of immunogenicity across drugs is fundamentally flawed: the differing types of ADA assay, trial design and included patient population - as well as the molecular structure of the biologic molecules themselves - are all highly influential on reported ADA prevalence and impact on clinical response. Therefore, the first part of this article aims to give an overview of ADA that also clarifies common misconceptions on the subject, whilst the second part of this article outlines Phase III immunogenicity data on commonly used biologics for psoriasis, the most common dermatological indication. Based on this, and acknowledging current limitations in available evidence, we propose a working categorization of biologics together with a broad approach to management: Group 1 - biologics with higher risk of clinically relevant ADA; Group 2 - biologics with lower risk of clinically relevant ADA; and Group 3 - biologics with no established risk of clinically relevant ADA. However, these groupings represent a working concept only; more research is required, using comparable ADA assays and consistent reporting of related outcomes. Finally, there is an urgent need for better characterization of individuals at particular risk of developing ADA to inform future clinical decision-making.

Using Serum Metabolomics to Predict Development of Anti-drug Antibodies in Multiple Sclerosis Patients Treated With IFNβ

Background: Neutralizing anti-drug antibodies (ADA) can greatly reduce the efficacy of biopharmaceuticals used to treat patients with multiple sclerosis (MS). However, the biological factors pre-disposing an individual to develop ADA are poorly characterized. Thus, there is an unmet clinical need for biomarkers to predict the development of immunogenicity, and subsequent treatment failure. Up to 35% of MS patients treated with beta interferons (IFNβ) develop ADA. Here we use machine learning to predict immunogenicity against IFNβ utilizing serum metabolomics data. Methods: Serum samples were collected from 89 MS patients as part of the ABIRISK consortium-a multi-center prospective study of ADA development. Metabolites and ADA were quantified prior to and after IFNβ treatment. Thirty patients became ADA positive during the first year of treatment (ADA+). We tested the efficacy of six binary classification models using 10-fold cross validation; k-nearest neighbors, decision tree, random forest, support vector machine and lasso (Least Absolute Shrinkage and Selection Operator) logistic regression with and without interactions. Results: We were able to predict future immunogenicity from baseline metabolomics data. Lasso logistic regression with/without interactions and support vector machines were the most successful at identifying ADA+ or ADA- cases, respectively. Furthermore, patients who become ADA+ had a distinct metabolic response to IFNβ in the first 3 months, with 29 differentially regulated metabolites. Machine learning algorithms could also predict ADA status based on metabolite concentrations at 3 months. Lasso logistic regressions had the greatest proportion of correct classifications [F1 score (accuracy measure) = 0.808, specificity = 0.913]. Finally, we hypothesized that serum lipids could contribute to ADA development by altering immune-cell lipid rafts. This was supported by experimental evidence demonstrating that, prior to IFNβ exposure, lipid raft-associated lipids were differentially expressed between MS patients who became ADA+ or remained ADA-. Conclusion: Serum metabolites are a promising biomarker for prediction of ADA development in MS patients treated with IFNβ, and could provide novel insight into mechanisms of immunogenicity.

Post-Developmental Roles of Notch Signaling in the Nervous System

Since its discovery in Drosophila, the Notch signaling pathway has been studied in numerous developmental contexts in diverse multicellular organisms. The role of Notch signaling in nervous system development has been extensively investigated by numerous scientists, partially because many of the core Notch signaling components were initially identified through their dramatic ‘neurogenic’ phenotype of developing fruit fly embryos. Components of the Notch signaling pathway continue to be expressed in mature neurons and glia cells, which is suggestive of a role in the post-developmental nervous system. The Notch pathway has been, so far, implicated in learning and memory, social behavior, addiction, and other complex behaviors using genetic model organisms including Drosophila and mice. Additionally, Notch signaling has been shown to play a modulatory role in several neurodegenerative disease model animals and in mediating neural toxicity of several environmental factors. In this paper, we summarize the knowledge pertaining to the post-developmental roles of Notch signaling in the nervous system with a focus on discoveries made using the fruit fly as a model system as well as relevant studies in C elegans, mouse, rat, and cellular models. Since components of this pathway have been implicated in the pathogenesis of numerous psychiatric and neurodegenerative disorders in human, understanding the role of Notch signaling in the mature brain using model organisms will likely provide novel insights into the mechanisms underlying these diseases.

T-Cell Dependent Immunogenicity of Protein Therapeutics Pre-clinical Assessment and Mitigation-Updated Consensus and Review 2020

Immune responses to protein and peptide drugs can alter or reduce their efficacy and may be associated with adverse effects. While anti-drug antibodies (ADA) are a standard clinical measure of protein therapeutic immunogenicity, T cell epitopes in the primary sequences of these drugs are the key drivers or modulators of ADA response, depending on the type of T cell response that is stimulated (e.g., T helper or Regulatory T cells, respectively). In a previous publication on T cell-dependent immunogenicity of biotherapeutics, we addressed mitigation efforts such as identifying and reducing the presence of T cell epitopes or T cell response to protein therapeutics prior to further development of the protein therapeutic for clinical use. Over the past 5 years, greater insight into the role of regulatory T cell epitopes and the conservation of T cell epitopes with self (beyond germline) has improved the preclinical assessment of immunogenic potential. In addition, impurities contained in therapeutic drug formulations such as host cell proteins have also attracted attention and become the focus of novel risk assessment methods. Target effects have come into focus, given the emergence of protein and peptide drugs that target immune receptors in immuno-oncology applications. Lastly, new modalities are entering the clinic, leading to the need to revise certain aspects of the preclinical immunogenicity assessment pathway. In addition to drugs that have multiple antibody-derived domains or non-antibody scaffolds, therapeutic drugs may now be introduced via viral vectors, cell-based constructs, or nucleic acid based therapeutics that may, in addition to delivering drug, also prime the immune system, driving immune response to the delivery vehicle as well as the encoded therapeutic, adding to the complexity of assessing immunogenicity risk. While it is challenging to keep pace with emerging methods for the preclinical assessment of protein therapeutics and new biologic therapeutic modalities, this collective compendium provides a guide to current best practices and new concepts in the field.

Expansion of Neutrophils and Classical and Nonclassical Monocytes as a Hallmark in Relapsing-Remitting Multiple Sclerosis

Neutrophils and monocytes encompassing the classical, intermediate, and nonclassical population constitute the majority of circulating myeloid cells in humans and represent the first line of innate immune defense. As such, changes in their relative and absolute amounts serve as sensitive markers of diverse inflammatory conditions. Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system, causing demyelination and axonal loss, affecting various neuron functions and often causing irreversible neurological disability. MS disease course is individually highly heterogeneous but can be classified as progressive (PMS) or relapsing-remitting (RRMS). Each MS course type may be further characterized as active or inactive, depending on the recent disability progression and/or current relapses. Data on specific alterations of the myeloid compartment in association with MS disease course are scarce and conflicting. In the current study, we systematically immunophenotyped blood myeloid leukocytes by flow cytometry in 15 healthy and 65 MS subjects. We found a highly significant expansion of granulocytes, CD15⁺ neutrophils, and classical and nonclassical monocytes in inactive RRMS (RRMSi) with concomitant shrinkage of the lymphocyte compartment, which did not correlate with biochemical readouts of systemic inflammation. Each of these leukocyte populations and the combined myeloid signature accurately differentiated RRMSi from other MS forms. Additionally, nonclassical monocyte proportions were particularly elevated in RRMSi individuals receiving disease-modifying therapy (DMT), such as natalizumab. Our results suggest that flow cytometry-based myeloid cell immunophenotyping in MS may help to identify RRMSi earlier and facilitate monitoring of DMT response.

Integrating the Ribonucleic Acid Sequencing Data From Various Studies for Exploring the Multiple Sclerosis-Related Long Noncoding Ribonucleic Acids and Their Functions

Multiple sclerosis (MS) is a chronic fatal central nervous system (CNS) disease involving in complex immunity dysfunction. Recently, long noncoding RNAs (lncRNAs) were discovered as the important regulatory factors for the pathogenesis of MS. However, these findings often cannot be repeated and confirmed by the subsequent studies. We considered that the small-scale samples or the heterogeneity among various tissues may result in the divergence of the results. Currently, RNA-seq has become a powerful approach to quantify the abundances of lncRNA transcripts. Therefore, we comprehensively collected the MS-related RNA-seq data from a variety of previous studies, and integrated these data using an expression-based meta-analysis to identify the differentially expressed lncRNA between MS patients and controls in whole samples and subgroups. Then, we performed the Jensen-Shannon (JS) divergence and cluster analysis to explore the heterogeneity and expression specificity among various tissues. Finally, we investigated the potential function of identified lncRNAs for MS using weighted gene co-expression network analysis (WGCNA) and gene set enrichment analysis (GSEA), and 5,420 MS-related lncRNAs specifically expressed in the brain tissue were identified. The subgroup analysis found a small heterogeneity of the lncRNA expression profiles between brain and blood tissues. The results of WGCNA and GSEA showed that a potential important function of lncRNAs in MS may be involved in the regulation of ribonucleoproteins and tumor necrosis factor cytokines receptors. In summary, this study provided a strategy to explore disease-related lncRNAs on genome-wide scale, and our findings will be benefit to improve the understanding of MS pathogenesis.

Low Percentage of Signal Regulatory Protein α/β+ Memory B Cells in Blood Predicts Development of Anti-drug Antibodies (ADA) in Adalimumab-Treated Rheumatoid Arthritis Patients

An important goal for personalized treatment is predicting response to a particular therapeutic. A drawback of biological treatment is immunogenicity and the development of antibodies directed against the drug [anti-drug antibodies (ADA)], which are associated with a poorer clinical outcome. Here we set out to identify a predictive biomarker that discriminates rheumatoid arthritis (RA) patients who are more likely to develop ADA in response to adalimumab, a human monoclonal antibody against tumor necrosis factor (TNF)α. By taking advantage of an immune-phenotyping platform, LEGENDScreen™, we measured the expression of 332 cell surface markers on B and T cells in a cross-sectional adalimumab-treated RA patient cohort with a defined ADA response. The analysis revealed seven differentially expressed markers (DEMs) between the ADA⁺ and ADA⁻ patients. Validation of the DEMs in an independent prospective European cohort of adalimumab treated RA patients, revealed a significant and consistent reduced frequency of signal regulatory protein (SIRP)α/β-expressing memory B cells in ADA⁺ vs. ADA⁻ RA patients. We also assessed the predictive value of SIRPα/β expression in a longitudinal RA cohort prior to the initiation of adalimumab treatment. We show that a frequency of < 9.4% of SIRPα/β-expressing memory B cells predicts patients that will develop ADA, and consequentially fail to respond to treatment, with a receiver operating characteristic (ROC) area under the curve (AUC) score of 0.92. Thus, measuring the frequency of SIRPα/β-expressing memory B cells in patients prior to adalimumab treatment may be clinically useful to identify a subgroup of active RA subjects who are going to develop an ADA response and not gain substantial clinical benefit from this treatment.