Nanotechnology for Detection of Multiple Sclerosis Compared to Autoimmune and Neurological Diseases by Exhaled Samples

Overview

Multiple Sclerosis (MS) is a complex multi-factorial disease, with underlying both genetic and environmental factors. Different populations have different susceptibility to MS. The disease is characterized by 2 main phenotypes: relapsing-remitting or progressive course. Clinical disability is due to distraction of the central nervous system (CNS) myelin. Repair processes are mainly noted after the acute relapse - and recovery of function can be spontaneous. However, in severe relapses sometimes there is need for STEROID TREATMENT. For the long term prophylaxis - 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 cannot cure it. Also, they are beneficial in only \~40 % of the Relapsing -Remitting patients. Currently there are no biomarkers available for MS (other than oligoclonal Immunoglobulin G (IgG) in the cervical spine fluid (CSF) - which helps confirm diagnosis but require an invasive procedure and are not correlated with disease activity nor response to therapy) and monitoring of MS and its treatment is by magnetic resonance Imaging (MRI) - which is an expensive procedure. Dr Hossam Haick from the Technion developed an electronic nose based on nanomaterials for diagnosis of diseases (e.g., cancer, kidney failure, etc.) via breath samples.The research hypothesis is that Biomarkers of CNS inflammation and/or neurodegeneration and/or CNS repair in persons with MS can be detected by the "electronic nose".

MS is the most common chronic neurological disease affecting young adults, with onset usually at the age 20-40 years. Women are affected 3-4 times more than men. It is a complex multi-factorial disease, with underlying both genetic and environmental factors. Different populations have different susceptibility (Compston and Coles 2008). The disease is characterized by 2 main phenotypes: relapsing-remitting or progressive course. Clinical disability is due to destruction of the CNS myelin (mainly oligodendrocytes) due to 3 processes (Franklin 2002; Franklin and Ffrench-Constant 2008; Frischer, Bramow et al. 2009): 1. Inflammation- immune cells with aberrant activity invade the brain and spinal cord and cause destruction of CNS myelin (a process called demyelination and secondary neurodegeneration - axonal and neuronal loss) 2. Primary neurodegeneration (axonal and neuronal loss) - without prominent inflammation 3. Repair - the inflammatory and neurodegenerative processes are followed by an attempt of the CNS to repair - however, this partial and incomplete repair is often the basis of residual deficits and disability (Chandran, Hunt et al. 2008) . * The acute MS relapse (presented as paralysis, visual loss, etc.) - is 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 relapse - and recovery of function can be spontaneous. However, in severe relapses sometimes there is need for STEROID TREATMENT (Tischner and Reichardt 2007). Following the increased understanding of the disease, new immunotherapies were developed (COPAXON /; Interferon -beta )in the last 10-15 years for long term treatment. However these can attenuate the disease (reduce the number of relapses per year) but do not cure it. In addition, they are beneficial in only \~40 % of the Relapsing -Remitting patients. Currently there are no treatments for patients with the Progressive Disease - who have gradual increased disability (Murray 2006). Presently there are no biomarkers available for diagnosis and routine follow-up of MS. Oligoclonal IgG in the CSF - which help confirm the diagnosis, require an invasive procedure and are not correlated with disease activity nor response to therapy; and MRI, which allows monitoring of MS activity and response to treatment is too expensive to routine use (Link and Huang 2006; Murray 2006). Dr Hossam Haick from the Technion, developed an electronic nose for diagnosis of diseases via breath samples. Dr Haick's previous studies have shown that an electronic nose based on gold nanoparticles could form the basis of an inexpensive and non- invasive diagnostic tool for lung cancer (Peng, Tisch et al. 2009) and kidney diseases (Haick, Hakim et al. 2009). Research hypothesis Biomarkers of CNS inflammation and/or neurodegeneration and/or CNS repair can be detected by the "electronic nose" in breath samples of persons with MS. Aim(s) Identification of biomarkers of: 1. CNS inflammation and CNS-autoimmunity 2. Neurodegeneration 3. CNS repair * that may serve as markers for: disease (vs controls), disease activity (predicting aggressive disease course, predicting Relapse; predicting Malignant vs Benign MS); response to therapy (Steroid , immunotherapies or neuroprotective agents). Work plan outline: Evaluate few groups clinically: * MS patients at acute relapse pre - vs- after 7 ,30 and 90 days of steroids treatment - to assess indicators of the acute inflammatory process and of the effects of Steroid treatment. * Relapsing MS patients vs Progressive MS patients vs controls which include healthy individuals as well as patients suffering from neurological and autoimmune diseases other than MS - to assess inflammatory vs neurodegenerative indicators. * MS patients who are Good- vs Poor- Responders to immunotherapy or Steroids. BREATH COLLECTION: Alveolar breath of the volunteers is collected using an "offline" method that effectively separates the endogenous from the exogenous breath volatile biomarkers and excludes the nasal entrainment. Two bags of 750 ml of breath samples per volunteer are collected in inert Mylar bags (Eco Medics, Duerten, Switzerland). Vapor sampling was performed by extended breath sampling into the collection apparatus for 15-20 minutes, with several stops during this process. The first three minutes of breath sampling are discarded due to the possible contamination of the upper respiratory air. The subsequent deep air is retained for testing purposes. The samples are collected with a tube that was introduced in the volunteer's mouth and connected to the collection bag. All participants provide a signed informed consent to this study, which is performed following the approval and according to the guidelines of the Helsinki Committee of Carmel Medical Center and Technion's committee for supervision of experiments in humans. CHEMICAL ANALYSIS OF THE BREATH SAMPLES: Gas-Chromatography/Mass-Spectrometry (GCMS-QP2010; Shimadzu Corporation, Japan), combined with a thermal desorption system (TD20; Shimadzu Corporation, Japan), is used for the chemical analysis of the breath samples. A Tenax® TA adsorbent tube (Sigma Aldrich Ltd.) is employed for pre-concentrating the VOCs in the breath samples. Using a custom-made pump system, the breath samples from the Mylar bags are sucked up through the TA tube at 100 ml/min flow rate, being then transferred to a thermal desorption (TD) tube (Sigma Aldrich Ltd.) before being analyzed by GC-MS. The following oven temperature profile was set: (a) 10 min at 35°C; (b) 4°C/min ramp until 150°C; (c) 10°C/min ramp until 300°C; and (d) 15 min at 300°C. An SLB-5ms capillary column (Sigma Aldrich Ltd.) with 5% phenyl methyl siloxane (30 m length, 0.25 mm internal diameter and 0.5 μm thicknesses) is employed. The splitless injection mode is used for 2 min, at 30 cm/sec constant linear speed and 0.70 ml/min column flow. The molecular structures of the VOCs are determined via the standard modular set, using 10 ppm isobutylene (Calgaz, Cambridge, Maryland, USA) as standard calibration gas during each run. GC-MS chromatogram analysis is realized using the GCMS solutions version 2.53SU1 post-run analysis program (Shimadzu Corporation), employing the National Institute of Standards and Technology (NIST) compounds library (Gaithersburg, MD 20899-1070, USA). SENSING MEASUREMENTS: Upon interaction between the breath samples and the detector, the volatile organic compounds adsorb into the organic part of the sensing material The result of this adsorption is translated to an electrical signal (resistance) that is transmitted to the macro-world (e.g., the screen of the device) through the (semi-)conductive material found in the same film. The results are then presented on the computers screen. An automated system controlled by a custom LabView (National Instruments) program is used to perform the sensing measurements. The sensors are tested simultaneously, in the same exposure chamber, using an Agilent 34980A multifunction switch. A Stanford Research System SR830 DSP lock-in amplifier controlled by an IEEE 488 bus is used to supply the AC voltage signal (0.2 V at 1 kHz) and to measure the corresponding current (\<10μA in the studied devices). This setup allows for measuring normalized changes in conductance as small as 0.01%. Sensor resistance was continuously acquired during the experiments. Sensing experiments were continuously performed using subsequent exposure cycles (see SOI, section 2). DATA ANALYSIS: Features extraction. For VOC analysis, three parameters are extracted from each sensor response: (i) the normalized change of sensor resistance at the middle of the exposure (S1); (ii) the normalized change of sensor resistance at the end of the exposure (S2); and (iii) the area under the response curve (S3). S1 and S2 are calculated with regard to the value of sensor resistance prior to the exposure. For breath analysis, two parameters are extracted from each sensor response (either to the control VOC or to each release of breath sample): (i) the normalized change of sensors resistance soon after the exposure (S4); and (ii) the normalized change of sensors resistance at the middle of the exposure (S5). S4 and S5 are calculated with regard to the value of sensor resistance prior to the exposure. A compensation and calibration process is posteriorly applied to these parameters to retain from sensor responses only that information related to their response to the VOCs from the breath samples. The mean values of the parameters obtained over the two successive exposures to the same sample are then calculated.