Multiple Sclerosis (MS) Cell Models for Research
Disease Burden and Research Significance
Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system, affecting approximately 2.8 million people worldwide (WHO, 2023). The disease typically presents in young adults, with a female-to-male ratio of about 3:1. The global prevalence has increased by 30% since 2013. MS is a leading cause of non-traumatic disability in young adults, with significant economic and social impact. The clinical course varies, but most patients experience relapsing-remitting MS (RRMS), which can transition to secondary progressive MS (SPMS). Primary progressive MS (PPMS) accounts for about 10-15% of cases. The exact etiology remains unknown, but it involves an autoimmune response against myelin antigens, leading to demyelination and axonal loss. Genetic susceptibility is linked to HLA-DRB1*15:01 and other risk loci, while environmental factors such as vitamin D deficiency, smoking, and Epstein-Barr virus infection contribute to disease risk.
MS is an ideal model for studying neuroinflammation, demyelination, and remyelination. The disease involves complex interactions between immune cells (T cells, B cells, macrophages) and CNS-resident cells (microglia, astrocytes, oligodendrocytes). Research focuses on understanding the molecular mechanisms of immune cell infiltration, myelin destruction, and the failure of remyelination. Public datasets such as the International Multiple Sclerosis Genetics Consortium (IMSGC) provide extensive GWAS data, and single-cell RNA-seq studies have identified novel cell states in MS lesions. Open questions include the triggers of autoimmunity, the role of the gut microbiome, and the development of neuroprotective therapies. Gene-edited cell models enable functional validation of risk genes and drug target identification.
Core Molecular Pathogenesis
The pathogenesis of MS involves several interconnected pathways:
- • Immune cell activation and migration: Autoreactive T cells (Th1 and Th17) are activated in the periphery and migrate across the blood-brain barrier (BBB). This involves adhesion molecules (VLA-4) and chemokines (CCL2, CXCL10).
- • Demyelination: Activated microglia and macrophages release pro-inflammatory cytokines (TNF-α, IL-1β) and reactive oxygen species, damaging oligodendrocytes and myelin sheaths.
- • Axonal injury: Demyelinated axons are vulnerable to degeneration due to lack of trophic support and increased energy demand.
- • Remyelination failure: Oligodendrocyte precursor cells (OPCs) fail to differentiate into mature oligodendrocytes in chronic lesions, partly due to inhibitory signals from the glial scar (e.g., Nogo-A, LINGO-1).
- • B cell involvement: B cells contribute to disease through antibody production, antigen presentation, and cytokine secretion. Ectopic lymphoid follicles in the meninges are associated with progressive disease.
Unlike cancer, MS is not characterized by somatic mutations but by inherited risk variants. However, gene expression changes and epigenetic modifications are common. The following table summarizes key risk genes identified through GWAS (from IMSGC, 2019):
| Gene | Frequency in MS (%) | Variant Type | Functional Effect |
|---|---|---|---|
| HLA-DRB1*15:01 | 30-40% | HLA class II allele | Increased antigen presentation of myelin peptides |
| IL2RA (CD25) | 10-15% | SNP (rs2104286) | Altered T cell regulation |
| IL7RA (CD127) | 10-15% | SNP (rs6897932) | Impaired IL-7 signaling in T cells |
| TYK2 | 5-10% | SNP (rs34536443) | Reduced kinase activity, affecting cytokine signaling |
| TNFRSF1A | 5-10% | SNP (rs1800693) | Soluble TNF receptor, modulating TNF signaling |
| STAT3 | 5% | SNP (rs744166) | Altered Th17 differentiation |
These variants contribute to immune dysregulation, but their functional impact is being studied using gene-edited cell models.
Key signaling pathways involved in MS pathogenesis include:
- • JAK-STAT pathway: Cytokines (IL-6, IL-23) activate JAK-STAT, promoting Th17 differentiation. TYK2 is a key kinase.
- • NF-κB pathway: Pro-inflammatory cytokines activate NF-κB, leading to expression of adhesion molecules and inflammatory mediators.
- • MAPK pathway: ERK and p38 MAPK are involved in microglial activation and cytokine production.
- • PI3K/AKT pathway: Regulates cell survival and proliferation in immune cells and oligodendrocytes.
- • Wnt pathway: Inhibits OPC differentiation, contributing to remyelination failure.
- • Notch pathway: Also inhibits OPC differentiation.
Targeting these pathways is a major focus for drug development.
Experimental Model Systems
Commonly used cell lines in MS research include:
| Cell Line | Origin | Key Mutations/Features |
|---|---|---|
| THP-1 | Human monocytic leukemia | Used as macrophage/microglia model; can be differentiated with PMA |
| U937 | Human histiocytic lymphoma | Monocyte/macrophage model |
| HMC3 | Human microglia | SV40-immortalized microglia; used for neuroinflammation studies |
| MO3.13 | Human oligodendrocyte | Hybrid cell line; used for oligodendrocyte studies |
| iPSC-derived microglia | Human induced pluripotent stem cells | Can be differentiated into microglia; patient-specific |
| iPSC-derived oligodendrocytes | Human iPSC | Can be differentiated into OPCs and oligodendrocytes; used for myelination studies |
Organoids, such as brain organoids containing microglia and oligodendrocytes, are emerging as more physiologically relevant models to study cell-cell interactions in MS.
Animal models are essential for MS research:
- • Experimental autoimmune encephalomyelitis (EAE): The most common model, induced by immunization with myelin antigens (e.g., MOG, PLP) or adoptive transfer of encephalitogenic T cells. It mimics the inflammatory demyelination of MS.
- • Cuprizone-induced demyelination: A toxin model that causes demyelination in the corpus callosum, useful for studying remyelination.
- • Viral models: Theiler's murine encephalomyelitis virus (TMEV) infection induces a chronic progressive MS-like disease.
- • Transgenic models: Mice expressing human HLA-DR2 and TCR specific for MBP develop spontaneous EAE.
- • Zebrafish models: Used for studying myelination and drug screening.
These models have limitations, including differences in immune system and CNS architecture, but they provide valuable insights.
CRISPR-based gene editing allows the creation of isogenic cell lines with specific genetic modifications, enabling functional studies of MS risk genes. For example:
- • TREM2 knockout microglia: TREM2 is a risk gene for MS and Alzheimer's disease. Knockout lines help study its role in microglial phagocytosis and inflammation.
- • IL7RA knockout T cells: IL7RA variants affect T cell homeostasis. Knockout lines can be used to study IL-7 signaling.
- • TYK2 knockout immune cells: TYK2 is a drug target; knockout lines are used to validate the mechanism of action of TYK2 inhibitors.
- • Reporter lines: For example, a microglia line with a GFP reporter under the IBA1 promoter can be used to track microglial activation.
These gene-edited models are commercially available from various sources, ensuring sequence verification and quality. They accelerate research by providing consistent, reproducible models for drug screening and target validation.
Related Disease
| Disease name | Disease type |
|---|
Related Services
Related Products
| Product name | Cat.No. | Species | Gene ID | |
|---|---|---|---|---|
| IFNg Overexpression HEK293 Stable Cell Line | EDJ-GQ88 | Human | 3458 | Details Get a Quote |
| Pdcd1 Overexpression 4T1 Stable Cell Line | EDJ-GQ136 | Mouse | 18566 | Details Get a Quote |
| ITGB1 Knockout Hep-G2 Cell Line | EDJ-KQ37 | Human | 3688 | Details Get a Quote |
| ICAM1 Knockout HEK293 Cell Line | EDJ-KQ93 | Human | 3383 | Details Get a Quote |
| TNFRSF1A Knockout HEK293 Cell Line | EDC90705 | Human | 7132 | Details Get a Quote |
| NR1H3 Knockout HEK293T Cell Line | EDJ-KQ109 | Human | 10062 | Details Get a Quote |
| IL1B Knockout HEK293 Cell Line | EDJ-KQ140 | Human | 3553 | Details Get a Quote |
| VCAM1 Knockout HEK293 Cell Line | EDJ-KQ146 | Human | 7412 | Details Get a Quote |
| APOE Knockout HEK293 Cell Line | EDJ-KQ172 | Human | 348 | Details Get a Quote |
| STAT1 Knockout HEK293 Cell Line | EDJ-KQ188 | Human | 6772 | Details Get a Quote |
| ADAM17 Knockout HEK293 Cell Line | EDC07796 | Human | 6868 | Details Get a Quote |
| NOTCH4 Knockout HEK293 Cell Line | EDJ-KQ439 | Human | 4855 | Details Get a Quote |
| CCR2 Knockout HEK293 Cell Line | EDJ-KQ442 | Human | 729230 | Details Get a Quote |
| CNTF Knockout HEK293 Cell Line | EDJ-KQ452 | Human | 1270 | Details Get a Quote |
| GFAP Knockout HEK293 Cell Line | EDJ-KQ464 | Human | 2670 | Details Get a Quote |
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Applications of Gene-Edited Cells
Gene-edited cells are used to validate the functional impact of MS risk genes. For example:
- • Knockout of TREM2 in microglia reduces phagocytosis of myelin debris, confirming its role in clearing damaged myelin.
- • Knock-in of the IL7RA risk variant in T cells alters IL-7 signaling, affecting T cell survival and proliferation.
- • CRISPR screens can identify genes that regulate microglial activation or OPC differentiation, providing new therapeutic targets.
Isogenic cell line pairs (wild-type vs. knockout) are powerful tools for drug screening. For example:
- • TYK2 knockout cells can be used to confirm the on-target effects of TYK2 inhibitors, such as those used for MS treatment.
- • Resistance models: Chronic exposure to drugs can select for resistant cells; gene editing can create cells with specific mutations to study resistance mechanisms.
- • High-throughput screening of compound libraries on gene-edited cells can identify novel drugs that modulate disease-relevant pathways.
CRISPR-based synthetic lethality screens can identify genes that are essential in specific genetic backgrounds. In MS, this can help identify biomarkers for disease progression or response to therapy. For example:
- • Screening for genes that are synthetically lethal with TREM2 loss may reveal compensatory pathways that can be targeted.
- • Gene-edited cells can be used to identify secreted proteins that serve as biomarkers for neuroinflammation.
Public Data Resources
| Database | URL | Description |
|---|---|---|
| TCGA | https://www.cancer.gov/tcga | The Cancer Genome Atlas, though cancer-focused, provides genomic data that can be used for comparative studies. |
| cBioPortal | https://www.cbioportal.org | Visualization and analysis of cancer genomics, but also includes some MS-related datasets. |
| DepMap | https://depmap.org | The Cancer Dependency Map, providing CRISPR screens and RNAi data for cancer cell lines, useful for identifying dependencies in immune cells. |
| GEO | https://www.ncbi.nlm.nih.gov/geo/ | Gene Expression Omnibus, repository for microarray and RNA-seq data, including MS datasets. |
| IMSGC | https://www.imsgc.org/ | International Multiple Sclerosis Genetics Consortium, provides GWAS data for MS. |
| MSBase | https://www.msbase.org/ | Global MS registry with clinical data. |