Our research Research by location and type Plymouth University - Dr Xinzhong Li, Dr Stephen Pearson & Prof Emmanuel Ifeachor Breath tests to detect Alzheimer’s disease Scientific title: Breath-based non-invasive diagnosis of Alzheimer’s disease: a pilot study Type of project: Pilot study What do we already know? Drugs targeting amyloid-β plaques and tau protein tangles, two hallmarks accumulated in the brain of Alzheimer’s disease sufferers, have been unsuccessful in clinical trials. It is now thought that soluble precursors of these deposits in the brain occur 15-20 years before symptoms develop, and if we can target these smaller molecules – instead of the larger protein aggregates – then we stand a much better chance of combating the disease. Existing diagnostic tools can assist AD diagnosis, but these can be invasive (e.g. cerebrospinal fluid analysis of proteins) or expensive (MRI/PET scanning). Volatile organic compounds (VOCs) are the end products of metabolic processes in the body that can be modulated by a variety of diseases, therefore breath testing (which links specific VOCs in exhaled breath to medical conditions), may offer a diagnostic opportunity for a variety of diseases. Indeed, trials around the UK are currently underway looking at diagnosing oesophageal, gastric and lung cancers, as well as Parkinson’s disease. Regarding dementia, one study recently found that VOC signals in AD differ from healthy participants. What is this group trying to find out? This project aims to determine whether VOCs in exhaled breath can act as biomarkers for non-invasive early diagnosis of Alzheimer’s disease. How do they do this? Alzheimer’s disease and control participants will breathe into a breath analyser (a state-of-the-art Field Asymmetric Ion Mobility Spectrometry (FAIMS) technology) which detects VOCs in real-time. The VOC profiles of Alzheimer’s disease and control participants will then be compared to see if there are any differences. In addition, the group will compile participants’ gender, age, education level, MMSE, and other medical variables together with the VOC profiles to create a comprehensive database. Why is it important? By combining the aforementioned database with machine learning technology, the team aims to discover novel biomarkers of Alzheimer’s disease, and use this to develop a cloud-based, non-invasive and cost-effective platform for early diagnosis and monitoring using breath testing. This would be a huge leap forward in dementia research and such early detection may enable more effective treatment. Further information Please click here for more information about the work of Dr Xinzhong Li. Please click here for more information about the work of Dr Stephen Pearson. Please click here for more information about the work of Prof Emmanuel Ifeachor.