The role of different subsets of T cells (white blood cells) in driving different forms of asthma.

What is it about?

By combining fibre optic camera technology with the mathematics of ‘Big Data’ from Silicon Valley, my team at the University of Southampton have been with gaining new insights into the nature of the world’s commonest long-term lung disease: asthma. Up to 300 million people are affected worldwide of which 1 in 20 suffer severe disease which responds poorly to current treatments. There remains no cure, and a major barrier to research has been a poor understanding of the different forms of asthma, and of the specific problems with the immune system which underlie each form.

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Why is it important?

To tackle afresh the problem of working out what different sorts of asthma exist our research team joined up with a company from Palo Alto (Ayasdi Inc) to pioneer the novel approach of ‘Topological Data Analysis’. Instead of asking a string of questions of a dataset, this new approach uses machine learning algorithms to plot the data as a three dimensional ‘network’, analysing potentially thousands of measurements simultaneously and allows features within the data to emerge, letting the data speak for itself. In this case six different forms of asthma became apparent. Some were previously well recognised but others had not been defined previously and showed two different forms of severe asthma. ‘Mast cells’ play a role in both of these, but type-2 cytokines – whose importance in asthma is well recognised – were only increased in one of these two groups. This approach paves the way for larger studies, now ongoing, to define the precise nature of distinct forms of asthma.

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