New ideas and drugs to treat multiple sclerosis





MRI of a mouse spinal cord taken as part of a study investigation methods for detecting demyelination using MRI. Image taken at 9.4T in the Experimental Imaging Centre c/o Nabeela Nathoo.



Multiple sclerosis is a very complex disease—scientists have found out a lot about it but  there is no cure and the underlying cause remains a mystery. The wealth of information is apparent by doing a search on the term “multiple sclerosis” which shows that, at time of writing, 60401 scientific papers have been written about this disease.

It would be wonderful if we could come up with the trigger and create treatments that prevent MS from occurring. A breakthrough in this area could literally come anytime. However in the mean time we need treatments. Clinical colleagues of mine agree that there are a lot more treatment options now then there were 10 years ago and more are in the pipeline.

Research in these areas requires funding. I’m excited to report that Dr. Wee Yong at the University of Calgary just received funding from Alberta Innovates Health Solutions to study new treatment options. This is in collaboration with our clinical lead, Dr. Luanne Metz and a list of other scientists including myself.

So how does one come up with a new drug? Just do a thought experiment for a moment. You need to understand the processes that are ongoing through the disease. Much of what has been done to date has been in this area. We know about inflammation and demyelination and we know a lot about how to detect the disease through clinical exams and imaging—especially MRI. Many of these findings were the result of studies in patients, but more were from studies in animal models.

Much of what we take for granted in terms of our understanding of brain structure and development has come from studies of animal models. This is because we need tissue samples and people aren’t too keen to volunteer to have their brain biopsied. Even MRI, which can be done repeatedly on patients, requires a fundamental understanding of the link between the MR signal and the structural changes in brain.

To validate imaging methods, we use the animal model to triggering some aspect of multiple sclerosis, inflammation related demyelination for instance. Then we undertake MR imaging and follow up with a good histological study of the brain. You will often see reference to the EAE model. This model is induced by stimulating the immune system at the same time as injecting small proteins common to white matter. The immune system activates against the white matter and you get demyelination. Another model, called the lysolecithin model, is one where you inject this particular chemical into the white matter and get rapid demyelination. The myelin then returns. By imaging and then quantifying the pathological changes, we are able link the changes seen in MR with a specific pathology.

When you get your next MRI you will hear sounds banging away. Each pattern is related to a specific type of MR image. Every few minutes the pattern will change, indicating that a new image type is being collected. Every one of these imaging methods has been validated with animal models by comparing the results of the image to the histological results.

Do get back to the drug studies, you need the same type of paradigm. Some aspect of the biology of MS needs to be understood and, if blocked or stimulated, expected to improve the condition of the patient. Once the target is identified, one can look at the existing pantheon of drugs to see if there is a candidate or you can begin to design a drug. Animal models were needed to identify these landmarks, or processes, which will be targeted. Once the process and drug are identified, animal models are used to test the specific hypothesis that the treatment will do what you expect.

Granted, many drugs which work in animal models don’t work well in patients, but drugs do not make it to patient care without some validation in animal models.

As a researcher in MR imaging, I’m very much aware of the need for good animal model studies in the path to drug development.  My PhD student Nabeela Nathoo and I became aware that there was no such succinct argument in the literature pointing out how best to use animal models in combination with imaging to study pathology and treatment options in Multiple Sclerosis.

To fill this gap, we wrote a review on how you would combine animal model studies with MRI in the drug development path. My lab, and my collaborators have a lot of exciting new ideas about what drugs might improve remyelination or reduce progression and we now are embarking on testing some of these ideas. We worked with the Multiple Sclerosis Journal to get this published. Thanks to editors Jack Antel and Duddy Martin as well as everyone at the MS journal for working with us on this publication.

The citation and abstract are below.
If you would like a copy of the paper, drop me a note at dunnj@ucalgary.ca.


Nathoo N, Yong VW, and Dunn JF. 2014. Using magnetic resonance imaging in animal models to guide drug development in multiple sclerosis. Mult Scler 20: 3-11.
http://msj.sagepub.com/content/20/1/3

Major advances are taking place in the development of therapeutics for multiple sclerosis (MS), with a move past traditional immunomodulatory/immunosuppressive therapies toward medications aimed at promoting remyelination or neuroprotection. With an increase in diversity of MS therapies comes the need to assess the effectiveness of such therapies. Magnetic resonance imaging (MRI) is one of the main tools used to evaluate the effectiveness of MS therapeutics in clinical trials. As all new therapeutics for MS are tested in animal models first, it is logical that MRI be incorporated into preclinical studies assessing therapeutics. Here, we review key papers showing how MR imaging has been combined with a range of animal models to evaluate potential therapeutics for MS. We also advise on how to maximize the potential for incorporating MRI into preclinical studies evaluating possible therapeutics for MS, which should improve the likelihood of discovering new medications for the condition.
 

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