Single-Nucleus RNA-seq of Normal-Appearing Brain Regions in Relapsing-Remitting vs. Secondary Progressive Multiple Sclerosis: Implications for the Efficacy of Fingolimod

A brain cell atlas integrating single-cell transcriptomes across human brain regions

While single-cell technologies have greatly advanced our comprehension of human brain cell types and functions, studies including large numbers of donors and multiple brain regions are needed to extend our understanding of brain cell heterogeneity. Integrating atlas-level single-cell data presents a chance to reveal rare cell types and cellular heterogeneity across brain regions. Here we present the Brain Cell Atlas, a comprehensive reference atlas of brain cells, by assembling single-cell data from 70 human and 103 mouse studies of the brain throughout major developmental stages across brain regions, covering over 26.3 million cells or nuclei from both healthy and diseased tissues. Using machine-learning based algorithms, the Brain Cell Atlas provides a consensus cell type annotation, and it showcases the identification of putative neural progenitor cells and a cell subpopulation of PCDH9high microglia in the human brain. We demonstrate the gene regulatory difference of PCDH9high microglia between hippocampus and prefrontal cortex and elucidate the cell-cell communication network. The Brain Cell Atlas presents an atlas-level integrative resource for comparing brain cells in different environments and conditions within the Human Cell Atlas.

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.

ZEBRA: a hierarchically integrated gene expression atlas of the murine and human brain at single-cell resolution

The molecular causes and mechanisms of neurodegenerative diseases remain poorly understood. A growing number of single-cell studies have implicated various neural, glial, and immune cell subtypes to affect the mammalian central nervous system in many age-related disorders. Integrating this body of transcriptomic evidence into a comprehensive and reproducible framework poses several computational challenges. Here, we introduce ZEBRA, a large single-cell and single-nucleus RNA-seq database. ZEBRA integrates and normalizes gene expression and metadata from 33 studies, encompassing 4.2 million human and mouse brain cells sampled from 39 brain regions. It incorporates samples from patients with neurodegenerative diseases like Alzheimer's disease, Parkinson's disease, and Multiple sclerosis, as well as samples from relevant mouse models. We employed scVI, a deep probabilistic auto-encoder model, to integrate the samples and curated both cell and sample metadata for downstream analysis. ZEBRA allows for cell-type and disease-specific markers to be explored and compared between sample conditions and brain regions, a cell composition analysis, and gene-wise feature mappings. Our comprehensive molecular database facilitates the generation of data-driven hypotheses, enhancing our understanding of mammalian brain function during aging and disease. The data sets, along with an interactive database are freely available at https://www.ccb.uni-saarland.de/zebra.

FTY720 requires vitamin B12-TCN2-CD320 signaling in astrocytes to reduce disease in an animal model of multiple sclerosis

Vitamin B12 (B12) deficiency causes neurological manifestations resembling multiple sclerosis (MS); however, a molecular explanation for the similarity is unknown. FTY720 (fingolimod) is a sphingosine 1-phosphate (S1P) receptor modulator and sphingosine analog approved for MS therapy that can functionally antagonize S1P1. Here, we report that FTY720 suppresses neuroinflammation by functionally and physically regulating the B12 pathways. Genetic and pharmacological S1P1 inhibition upregulates a transcobalamin 2 (TCN2)-B12 receptor, CD320, in immediate-early astrocytes (ieAstrocytes; a c-Fos-activated astrocyte subset that tracks with experimental autoimmune encephalomyelitis [EAE] severity). CD320 is also reduced in MS plaques. Deficiency of CD320 or dietary B12 restriction worsens EAE and eliminates FTY720's efficacy while concomitantly downregulating type I interferon signaling. TCN2 functions as a chaperone for FTY720 and sphingosine, whose complex induces astrocytic CD320 internalization, suggesting a delivery mechanism of FTY720/sphingosine via the TCN2-CD320 pathway. Taken together, the B12-TCN2-CD320 pathway is essential for the mechanism of action of FTY720.

CellGO: a novel deep learning-based framework and webserver for cell-type-specific gene function interpretation

Interpreting the function of genes and gene sets identified from omics experiments remains a challenge, as current pathway analysis tools often fail to consider the critical biological context, such as tissue or cell-type specificity. To address this limitation, we introduced CellGO. CellGO tackles this challenge by leveraging the visible neural network (VNN) and single-cell gene expressions to mimic cell-type-specific signaling propagation along the Gene Ontology tree within a cell. This design enables a novel scoring system to calculate the cell-type-specific gene-pathway paired active scores, based on which, CellGO is able to identify cell-type-specific active pathways associated with single genes. In addition, by aggregating the activities of single genes, CellGO extends its capability to identify cell-type-specific active pathways for a given gene set. To enhance biological interpretation, CellGO offers additional features, including the identification of significantly active cell types and driver genes and community analysis of pathways. To validate its performance, CellGO was assessed using a gene set comprising mixed cell-type markers, confirming its ability to discern active pathways across distinct cell types. Subsequent benchmarking analyses demonstrated CellGO's superiority in effectively identifying cell types and their corresponding cell-type-specific pathways affected by gene knockouts, using either single genes or sets of genes differentially expressed between knockout and control samples. Moreover, CellGO demonstrated its ability to infer cell-type-specific pathogenesis for disease risk genes. Accessible as a Python package, CellGO also provides a user-friendly web interface, making it a versatile and accessible tool for researchers in the field.

Atlas of the aging mouse brain reveals white matter as vulnerable foci

Aging is the key risk factor for cognitive decline, yet the molecular changes underlying brain aging remain poorly understood. Here, we conducted spatiotemporal RNA sequencing of the mouse brain, profiling 1,076 samples from 15 regions across 7 ages and 2 rejuvenation interventions. Our analysis identified a brain-wide gene signature of aging in glial cells, which exhibited spatially defined changes in magnitude. By integrating spatial and single-nucleus transcriptomics, we found that glial aging was particularly accelerated in white matter compared with cortical regions, whereas specialized neuronal populations showed region-specific expression changes. Rejuvenation interventions, including young plasma injection and dietary restriction, exhibited distinct effects on gene expression in specific brain regions. Furthermore, we discovered differential gene expression patterns associated with three human neurodegenerative diseases, highlighting the importance of regional aging as a potential modulator of disease. Our findings identify molecular foci of brain aging, providing a foundation to target age-related cognitive decline.

The Diversity of Astrocyte Activation during Multiple Sclerosis: Potential Cellular Targets for Novel Disease Modifying Therapeutics

Neuroglial cells, and especially astrocytes, constitute the most varied group of central nervous system (CNS) cells, displaying substantial diversity and plasticity during development and in disease states. The morphological changes exhibited by astrocytes during the acute and chronic stages following CNS injury can be characterized more precisely as a dynamic continuum of astrocytic reactivity. Different subpopulations of reactive astrocytes may be ascribed to stages of degenerative progression through their direct pathogenic influence upon neurons, neuroglia, the blood-brain barrier, and infiltrating immune cells. Multiple sclerosis (MS) constitutes an autoimmune demyelinating disease of the CNS. Despite the previously held notion that reactive astrocytes purely form the structured glial scar in MS plaques, their continued multifaceted participation in neuroinflammatory outcomes and oligodendrocyte and neuronal function during chronicity, suggest that they may be an integral cell type that can govern the pathophysiology of MS. From a therapeutic-oriented perspective, astrocytes could serve as key players to limit MS progression, once the integral astrocyte-MS relationship is accurately identified. This review aims toward delineating the current knowledge, which is mainly focused on immunomodulatory therapies of the relapsing-remitting form, while shedding light on uncharted approaches of astrocyte-specific therapies that could constitute novel, innovative applications once the role of specific subgroups in disease pathogenesis is clarified.

Molecular and neuroimmune pharmacology of S1P receptor modulators and other disease-modifying therapies for multiple sclerosis

Multiple sclerosis (MS) is a neurological, immune-mediated demyelinating disease that affects people in the prime of life. Environmental, infectious, and genetic factors have been implicated in its etiology, although a definitive cause has yet to be determined. Nevertheless, multiple disease-modifying therapies (DMTs: including interferons, glatiramer acetate, fumarates, cladribine, teriflunomide, fingolimod, siponimod, ozanimod, ponesimod, and monoclonal antibodies targeting ITGA4, CD20, and CD52) have been developed and approved for the treatment of MS. All the DMTs approved to date target immunomodulation as their mechanism of action (MOA); however, the direct effects of some DMTs on the central nervous system (CNS), particularly sphingosine 1-phosphate (S1P) receptor (S1PR) modulators, implicate a parallel MOA that may also reduce neurodegenerative sequelae. This review summarizes the currently approved DMTs for the treatment of MS and provides details and recent advances in the molecular pharmacology, immunopharmacology, and neuropharmacology of S1PR modulators, with a special focus on the CNS-oriented, astrocyte-centric MOA of fingolimod.

How does neurovascular unit dysfunction contribute to multiple sclerosis?

Multiple sclerosis is an inflammatory demyelinating disease of the central nervous system (CNS) and the most common non-traumatic cause of neurological disability in young adults. Multiple sclerosis clinical care has improved considerably due to the development of disease-modifying therapies that effectively modulate the peripheral immune response and reduce relapse frequency. However, current treatments do not prevent neurodegeneration and disease progression, and efforts to prevent multiple sclerosis will be hampered so long as the cause of this disease remains unknown. Risk factors for multiple sclerosis development or severity include vitamin D deficiency, cigarette smoking and youth obesity, which also impact vascular health. People with multiple sclerosis frequently experience blood-brain barrier breakdown, microbleeds, reduced cerebral blood flow and diminished neurovascular reactivity, and it is possible that these vascular pathologies are tied to multiple sclerosis development. The neurovascular unit is a cellular network that controls neuroinflammation, maintains blood-brain barrier integrity, and tightly regulates cerebral blood flow, matching energy supply to neuronal demand. The neurovascular unit is composed of vessel-associated cells such as endothelial cells, pericytes and astrocytes, however neuronal and other glial cell types also comprise the neurovascular niche. Recent single-cell transcriptomics data, indicate that neurovascular cells, particular cells of the microvasculature, are compromised within multiple sclerosis lesions. Large-scale genetic and small-scale cell biology studies also suggest that neurovascular dysfunction could be a primary pathology contributing to multiple sclerosis development. Herein we revisit multiple sclerosis risk factors and multiple sclerosis pathophysiology and highlight the known and potential roles of neurovascular unit dysfunction in multiple sclerosis development and disease progression. We also evaluate the suitability of the neurovascular unit as a potential target for future disease modifying therapies for multiple sclerosis.

A Comprehensive Exploration of the Transcriptomic Landscape in Multiple Sclerosis: A Systematic Review

Multiple Sclerosis (MS) is, to date, an incurable disease of the nervous system characterized by demyelination. Several genetic mutations are associated with the disease but they are not able to explain all the diagnosticated cases. Thus, it is suggested that altered gene expression may play a role in human pathologies. In this review, we explored the role of the transcriptomic profile in MS to investigate the main altered biological processes and pathways involved in the disease. Herein, we focused our attention on RNA-seq methods that in recent years are producing a huge amount of data rapidly replacing microarrays, both with bulk and single-cells. The studies evidenced that different MS stages have specific molecular signatures and non-coding RNAs may play a key role in the disease. Sex-dependence was observed before and after treatments used to alleviate symptomatology activating different biological processes in a drug-dependent manner. New pathways, such as neddylation, were found deregulated in MS and inflammation was linked to neuron degeneration areas through spatial transcriptomics. It is evident that the use of RNA-seq in the study of complex pathologies, such as MS, is a valid strategy to shed light on new involved mechanisms.

Single-Cell Analysis to Better Understand the Mechanisms Involved in MS

Multiple sclerosis is a chronic and inflammatory disease of the central nervous system. Although this disease is widely studied, many of the precise mechanisms involved are still not well known. Numerous studies currently focusing on multiple sclerosis highlight the involvement of many major immune cell subsets, such as CD4+ T cells, CD8+ T cells and more recently B cells. However, our vision of its pathology has remained too broad to allow the proper use of targeted therapeutics. This past decade, new technologies have emerged, enabling deeper research into the different cell subsets at the single-cell level both in the periphery and in the central nervous system. These technologies could allow us to identify new cell populations involved in the disease process and new therapeutic targets. In this review, we briefly introduce the major single-cell technologies currently used in studies before diving into the major findings from the multiple sclerosis research from the past 5 years. We focus on results that were obtained using single-cell technologies to study immune cells and cells from the central nervous system.