Barts-MS rose-tinted-odometer: ★★★★★
Did you know that because you have MS you are likely to have different odours on your breath compared to someone who doesn’t have MS? In other words, you have a characteristic MS smell.
Multiple sclerosis is usually referred to as a complex disease, i.e. it is caused by an interaction between genetic factors and the environment and bad luck. Some people have difficulty getting their heads around this relatively simple concept.
Now I want to take it one step further. MS must be a metabolic disease, i.e. MS must have a characteristic metabolic signature that differentiates it from other diseases and from ‘normality’. The reason I say this that metabolism is the great integrator of your genome and how your genes interact with the environment (microbiome, diet, season, stress, medications, etc.). If MS is a complex disease it must manifest metabolically with a unique profile.
If the MS metabolome has a characteristic metabolic signature and some of the metabolites are likely to be volatile and released in your breath, it may be possible to train a nose, either a dog’s nose or an electronic nose to detect the presence of this metabolic signature in your breath that can then be used to diagnose MS. Science fiction or not?
This may sound like science fiction but this approach is being evaluated in neurodegenerative diseases such as Parkinson’s disease and the data looks very compelling. I even know a few Parkinson’s disease experts who say they can smell if someone has Parkinson’s disease or not.
The MS study below, although a pilot, shows promising results. Using an eNose or electronic nose the investigators first taught an AI engine to what people with MS smell like. The taught AI engine, using a new cohort of study subjects, was then able to identify who has MS from healthy controls with a sensitivity of 0.75 or 75%, which to me is very good as a starting point. Imagine how this will improve as eNose technology improves and the AI engine is given more people with MS to smell and learn from.
I see a future when we use devices such as the eNose or metabolic profiling and artificial intelligence to identify people at risk of MS or with asymptomatic MS for MS prevention studies. Smell or eNose technology will become more sophisticated with time. I see a future when it will become mainstream and be part of the new healthcare environment we work in. Patients attending their GPs or an emergency department with a diagnostic problem will be sent for an eNose evaluation as part of the diagnostic work-up. This routine screening may open a window into the early detection of MS and other diseases. Watch this space!
Ettema et al. Detecting Multiple Sclerosis via breath analysis using an eNose, a pilot study. J Breath Res. 2020 Dec 3. doi: 10.1088/1752-7163/abd080. Online ahead of print.
Objective: In the present study we investigated whether Multiple Sclerosis (MS) can be detected via exhaled breath analysis using an electronic nose. The AeonoseTM (an electronic nose, 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 AeonoseTM can make a distinction between the breath patterns of patients with MS and healthy control subjects.
Methods: In this mono-center, prospective, non-invasive study, 124 subjects with a confirmed diagnosis of MS and 129 control subjects each breathed into the AeonoseTM for 5 minutes. 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.
Results: 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].
Conclusion: The study showed that the AeonoseTM is 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 AeonoseTM is able to differentiate new MS patients from subjects who will not get the diagnosis.
Crowdfunding: Are you a supporter of Prof G’s ‘Bed-to-5km Challenge’ in support of MS research?