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EAE Model Overview

Experimental Autoimmune Encephalomyelitis (EAE) is a gold-standard mouse model for assessing therapeutic agents targeting autoimmune-mediated central nervous system (CNS) disease. EAE induction is most commonly performed by immunizing mice against myelin-derived antigens, such as:

  • Myelin Oligodendrocyte Glycoprotein (MOG35-55 or MOG1-125)
  • Myelin Basic Protein (MBP)
  • Proteolipid Protein (PLP)

The EAE mice model several key aspects of human MS, including the following key pathologic features:

  • Neuroinflammation
  • Peripheral inflammatory infiltrates
  • Demyelination in white matter
  • Axonal damage

The EAE model of multiple sclerosis demonstrates motor symptoms, such as paralysis, which recapitulates clinical symptoms seen in MS patients. The EAE animal model is characterized by a progressive paralysis followed by full or partial recovery, which may then be relapsing-remitting or chronic depending on the specific antigen used.

EAE Mouse Model Generation

  • We most frequently use the MOG35-55 model in C57BL/6 mice, which is a well-established, chronic model of multiple sclerosis that is advantageous for therapeutic studies
  • Injection of MOG35-55 peptide with Complete Freund's Adjuvant (CFA) and pertussis toxin (PTx) on a defined schedule to produce a T cell-mediated autoimmune disease

Our Validated EAE Mouse Model Measures

  • Body weight
  • EAE scoring
  • Grip strength test & wire hang test
  • Neurofilament Light measures in plasma & CSF
  • Immunohistochemistry & multiplex immunofluorescence of the spinal cord
MS - EAE Scores Graph

Learn more about our characterization of this model, our validated measures, and our Preclinical Neuroscience CRO services.

Discover more of our Multiple Sclerosis Models


What is the "EAE Score"?

The EAE Score is a standardized. clinical scoring system that assesses the disease progression in this rodent model. It typically uses a 5 point scale. An example is:

MS - EAE Score Scale

There are several variations on the EAE score, and we would be happy to discuss what may be most suitable for your study.

What is the typical dosing paradigm?

The dosing paradigm can be:
(1) Prophylactic (starting before or at the time of immunization)
(2) Therapeutic/interventional
      (a) Starting when the first mice show symptoms
      (b) Starting from the first signs of symptoms in each mouse
      (c) Starting a fixed time after immunization or symptom onset in each mouse

Our team can discuss the best dosing paradigm for your study.

Can a "positive control" be included in the study?

Yes. The existence of well-established positive controls is an advantage of the EAE animal models.

What is the difference between using MOG35-55 and MOG1-125?

The MOG1-125 induced model is thought to have some dependence on B cells, which may be useful for evaluating B cell-targeted therapies.

What is the difference between active and passive EAE models?

In active EAE, the disease is induced in mice via immunization with myelin-derived antigens, such as MOG, PLP, or MBP. MOG35-55-induced EAE is commonly used to induce EAE in C57BL/6 mice, making is a well-established and widely employed rodent model for studying autoimmune demyelinating diseases.

In passive EAE (also known as adoptive transfer), the disease is induced by first generating encephalitogenic CD4+ T cells that are specific for myelin-derived antigens in immunized (donor) mice, then activated these cells in culture, and finally injecting them into recipient mice. This approach is useful when therapies target specific T cell populations.

Can Biospective perform "adoptive transfer" (passive) EAE model studies?

Yes. We can generate these animal models and our EAE model scientists would be happy to discuss further with you.

Is neurofilament light a useful measure in EAE?

Definitely. Plasma and/or CSF neurofilament light levels are excellent measures of axonal damage in this mouse model of multiple sclerosis.

More Information

Let us know what you’re interested in. Our team will be happy to discuss with you!

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