Detecting multiple sclerosis via breath analysis using an eNose, a pilot study

In the present study we investigated whether multiple sclerosis (MS) can be detected via exhaled breath analysis using an electronic nose (eNose). The Aeonose^TM(an eNose, The eNose Company, Zutphen, the Netherlands) is a diagnostic test device to detect patterns of volatile organic compounds in exhaled breath. We evaluated whether the Aeonose^TMcan make a distinction between the breath patterns of patients with MS and healthy control subjects. In this mono-center, prospective, non-invasive study, 124 subjects with a confirmed diagnosis of MS and 129 control subjects each breathed into the Aeonose^TMfor 5 min. Exhaled breath data was used to train an artificial neural network (ANN) predictive model. To investigate the influence of medication intake we created a second predictive model with a subgroup of MS patients without medication prescribed for MS. The ANN model based on the entire dataset was able to distinguish MS patients from healthy controls with a sensitivity of 0.75 (95% CI: 0.66-0.82) and specificity of 0.60 (0.51-0.69). The model created with the subgroup of MS patients not using medication and the healthy control subjects had a sensitivity of 0.93 (0.82-0.98) and a specificity of 0.74 (0.65-0.81). The study showed that the Aeonose^TMis able to make a distinction between MS patients and healthy control subjects, and could potentially provide a quick screening test to assist in diagnosing MS. Further research is needed to determine whether the Aeonose^TMis able to differentiate new MS patients from subjects who will not get the diagnosis.