Trial Information

Applications of Nanotechnology and Chemical Sensors for the Detection and Identification of Multiple Sclerosis by Respiratory Samples

Multiple Sclerosis (MS) is a complex multi-factorial disease, with underlying both genetic
and environmental factors. Different populations have different susceptibility. The disease
is characterized by 2 main phenotypes: relapsing-remitting or progressive course. Clinical
disability is due to distraction of the CNS myelin (mainly oligodendrocytes) due to 3
processes:

1. Inflammation- immune cells with aberrant activity invade the brain and spinal cord and
cause distraction of CNS myelin.

2. Primary neurodegeneration - without prominent inflammation

3. Repair - the inflammatory and neurodegenerative processes are followed by an attempt of
the CNS to repair - however, this is partial and incomplete repair is often the basis
of residual deficits and disability.

- The acute MS attack- are considered to be due to an aberrant acute immune
activation and inflammatory process in the CNS

- The chronic accumulating disability - is considered to be due to the
Neuro-degenerative process.

Repair processes are mainly noted after the acute attack - and recovery of function can be
spontaneous. However, in severe attacks sometimes there is need for adding STEROID TREATMENT
(6 days IV) for the acute attack.

For the long term prophylactics - following the increased understanding of the disease, in
the last 10-15 years there are new immunotherapies available (COPAXON / TEVA; Interferon
-beta). However these can attenuate the disease (reduce the number of relapses per year) but
are not cure. Also, they are beneficial in only ~40 % of the Relapsing -Remitting patients.

Currently there are no biomarkers available for MS (other than oligoclonal IgG in the CSF -
which help confirm diagnosis but require invasive procedure and are not correlated with
disease activity nor response to therapy) and - monitoring of MS and its treatment is by MRI
- which is expensive.

Dr Hossam Haick from the Technion developed an electronic nose based nanomaterials for
diagnosis of diseases (e.g., cancer, kidney failure, etc.) via breath samples. Research
hypothesis Biomarkers of CNS inflammation and/or neurodegeneration and/or CNS repair can be
detected by "electronic nose".

Aim(s)

Identification of biomarkers of:

1. CNS inflammation and CNS-autoimmunity

2. Neurodegeneration

3. CNS repair o that may serve as markers for disease (vs controls), of disease activity
(predicting aggressive disease course (predicting Relapse; predicting Malignant vs
Benign MS); predicting response to therapy (Steroid , immunotherapies or
neuroprotective agents).

Work plan outline:

Evaluate few groups clinically:

- MS patients at acute relapse pre - vs- after 7 and 30 days of steroids treatment.

- Relapsing MS patients vs Progressive MS patients vs Healthy controls.

- MS patients who are Good- vs Poor- Responders to immunotherapy When available, MRI will
be used as a surrogate marker, together with the clinical assessment.

Evaluation of the Electronic Nose for Diagnosis of MS We will apply a four-phase approach in
order to achieve the objectives of this research. In the first phase we will collect
suitable breath samples from each patient and compare the patient data to age-adjusted
healthy controls. In the second phase we will analyze the collected breath samples with the
electronic nose setup. In the third phase we will carry out auxiliary chemical analysis,
using gas-chromatography linked with mass spectrometry (GC-MS), of the breath samples under
different aspects. The fourth phase will aim at the improvement of our electronic nose setup
and will be conducted in parallel to the first three phases.

We will collect breath samples of a representative group of MS patients of all types and of
age-matched controls. Our GC-MS chemical analysis will address: (1) the dependence of the MS
breath biomarker levels on the type/stage of the MS disease; and (2) the effect of
environmental factors such as age, diet, lifestyle (especially smoking and drinking habits)
on the chemical composition of the breath. Based on the results of the GC-MS chemical
analysis, we will improve and optimize our array of nanosensors setup so as to achieve: (1)
maximum sensitivity to the MS biomarkers and their stage dependent concentration profiles;
(2) minimum sensitivity to non-MS related changes of the chemical composition of the breath,
and (3) minimum sensitivity to the major ingredients of the breath, such as water vapor. We
will attempt to define MS sub-categories, supported by the information from the
clinical/imaging reports, which might be relevant for clinical management, by more
sophisticated statistical treatment of the collected data. Towards the end of this
proof-of-concept study we will compare the performance of our electronic nose setup to the
conventional MS diagnostic tools. The comparison will be done in terms of true positive,
true negative, false positive, false negative, sensitivity and specificity.