| Project Detail |
Current diagnosis of individuals suffering from disorders on the autism spectrum is based on behavioural and developmental observations, usually in their early life. Even so, there is a significant amount of people having to live with these life-long disorders that remain undetected and no treatment is provided to them. However, it is already established that such disorders are associated with metabolic changes. There is now a growing amount of evidence suggesting that such metabolic
alterations can be detected in samples such as blood or urine taken from children early in their life. These routines however can cause significant discomfort to the child.
The primary aim of the proposal will involve the use of less invasive sampling techniques such as exhaled breath and exhaled breath condensate for the early diagnosis of metabolic hallmarks of autism spectrum disorders. These samples will be analysed using already established chemical analysis techniques for the detection of small metabolic changes in the obtained samples. Tandem mass spectrometry techniques will be used for the unambiguous identification of these metabolites. Data analysis tools such as principal component analysis (PCA) and hierarchical clustering will be used, to associate these metabolic changes with existing medical records obtained from the patients, to establish a potential diagnostic tool.
The potential for the rapid detection of these metabolites will be examined through the integration of novel ambient mass spectrometric ionisation methods such as plasma ionisation. The ability to selectively ionise specific metabolites associated with autism will be investigated with the aim of generating an early prototype of a rapid screening method for routine use. Data generated during the initial stage of the work will be used to create a database that will be used for near real-time
characterisation of the exhaled breath through the analysis of metabolites and volatile organic compounds (VOCs). |
