Disease Activity Markers

1
Disease Activity Markers

• Nicola R. Donelan, Ph.D.
• Research Associate

The Multiple Sclerosis Research Center of New York
2
Disease activity markers (biomarkers) in MS
Biomarkers are defined as biological molecules
that act as indicators of physiologic state and
also of change during a disease process

• Diagnosis of MS and identification of disease
  stages and subcategories
• Prediction of onset and disease course
• May help in elucidating disease mechanisms
• Treatment selection and improved prognosis of
  treatment success
• The evaluation of novel therapeutics

3
Panel of activity markers currently measured in
the lab

• Fetuin-A
• Nitric oxide
• Osteopontin
• Matrix metalloproteinase-9 (MMP-9) and Tissue
  inhibitors of metalloproteinase1 and 2 (TIMP-1,
  -2)

4
Active vs Inactive

• Absence of the 3 criteria for active diagnosis

• More than 1 relapse in the past year
• Increased disability - change in EDSS score
• Increase in MRI lesion load and/or presence of
  gadolinium enhancing lesions

5
Fetuin-A (Alpha2 HS-glycoprotein)

• 95 liver-derived protein
• Modulator of the immune response
• TGFB antagonist
• Regulation of matrix metalloproteinases
• Regulator of insulin activity
• Involved in osteogenesis and bone resorption

6
Fetuin-A is a marker of disease activity in MS

• Levels of Fetuin-A are significantly elevated in
  the CSF of patients with active disease
• Increased levels of Fetuin-A are found in areas
  of demyelination in autopsy MS brain tissue
• Increased levels of Fetuin-A are found in areas
  of demyelination in the animal model of MS

7
Fetuin-A levels are Elevated in the CSF of
Active vs Inactive MS
800 ng/ml
SP-MS
PP-MS
RR-MS
8
Fetuin-A is Elevated in Areas of Demyelination
9
Fetuin-A is also Elevated in Areas of
Demyelination in the animal model of MS
10
Measuring Treatment Efficacy

• Clinical examination
• Magnetic Resonance Imaging (MRI)
• Analysis of a panel of disease activity markers
  in CSF

11
Concentration of Fetuin-A in the CSF before and
after 6 months of Tysabri treatment
Concentration of Fetuin-A (ng/ml)
Patients 1-4
12
Nitric Oxide (NO)

• Nitric oxide is produced by macrophages and
  neutrophils as part of the immune response
• Important mediator/messenger in neuroprotection,
  neurotransmission, memory, and synaptic
  plasticity under physiological conditions
• Implicated as a potential mediator of
  microglia-dependent demyelination
• High levels of NO in CSF may lead to toxic damage
  of myelin and oligodendrocytes
• Recent evidence suggests that nitric oxide is
  also immunoregulatory and may suppresses the
  function of activated proinflammatory macrophages
  and T lymphocytes
• High levels of NO in CSF have been associated
  with activity and progression
  of MS

13
Concentration of NO in the CSF before and after
6 months of Tysabri treatment
Concentration of Nitric Oxide (ng/ml)
Patients 1-4
14
Osteopontin (Opn)

• Early T cell-activation gene 1, enhances the
  survival of activated T cells
• Produced by immune and non-immune cells
  including T cells, macrophages, NK cells,
  endothelial cells, epithelial cells, astrocytes
  and neurons
• Inflammation (activates dendritic cells driving
  pro-inflammatory response)
• Bone remodeling
• Opn deficient mice are resistant to EAE
• Increased levels of Opn have been found in MS
  patients with active disease

15
Concentration of Osteopontin in the CSF before
and after 6 months of Tysabri treatment
Concentration of Osteopontin (ng/ml)
Patients 1-4
16
Immune Cells found in
Cerebrospinal Fluid (CSF)
B cells
T cells
Typical Cellular Composition 60-80
lymphocytes Up to 30 monocytes/macrophages 2
Other cells (e.g.. Dendritic cells, NK cells)
17
Number of cells in the CSF before and after 6
months of Tysabri treatment
Number of cells in the CSF (cells/ml)
Patients 1-4
18
Summary

• The cellular content of the CSF crudely reflects
  disease activity
• Measuring protein levels of Fetuin-A, nitric
  oxide and osteopontin in the CSF provide a
  reliable indicator of disease activity in MS
• Measuring this panel of disease activity markers
  allows for improved treatment selection and
  better prediction of treatment success

19
Acknowledgements

• Jacqueline Dinzey, B.A.
• Christina Poopatana, B.A.
• Mustapha Rammal, B.A.
• Qi Jian Yan, M.D., Ph.D.
• Soheli Chowdhury, Ph.D
• Saud Sadiq, M.D.
• Special thanks to the MSRCNY Board of Directors