Prof. Julia Newton, Clinical Professor of Ageing and Medicine
Institute for Ageing and Health, The Medical School, Newcastle University, Newcastle upon Tyne, UK
Background and aim
The studies involving Prof. Julia Newton and Prof. David Jones of the Faculty of Medical Sciences, Newcastle University, represent one of the very few research programmes anywhere in the world on ME/CFS – and a rare example of a consistent, directed, problem-solving approach to tackling the illness.
Since 2006, the group has received separate grants from ME Research UK to look at the autonomic nervous system (2006) and muscle bioenergetics (2009), plus another other large grant (2007) from ME Research UK, the John Richardson Research Group, and the Irish ME Trust to investigate muscle, liver and heart function in a large patient cohort. In a series of novel scientific papers emanating from these awards, they have reported that, compared with healthy people, many ME/CFS patients have:
- Dysfunction of the autonomic nervous system (three-quarters of patients)
- Fatigue that is directly related to the burden of autonomic nervous system symptoms
- An abnormal heart rate response to standing
- Lower blood pressure, and abnormal blood pressure regulation
- Substantially slower recovery from standarised exercise of the skeletal muscles
The very large amount of data emanating from these and similar projects, including the data available from every patient attending the Newcastle ME/CFS Clinical Service, represents a very valuable longitudinal resource of clinical and biological information on people with the illness. And while the scientific papers published to date have reported key headline findings, Prof. Newton and colleagues recognise that mining this rich dataset has the potential to reveal even more about the illness, including the relationships between demographic, clinical and biological parameters.
The power of modern computing and, in particular, a scientific approach called ‘systems biology’ allows the development of multi-dimensional models of how a large number of measured parameters link with each other. Such models might allow the identification of processes causing disease, and crucially allow estimations to be made of how changes in one or more symptoms might be expected to impact on the overall burden of disease. Of course, these models can never replace studies involving patients, but they can allow prediction of which patient studies are most important and indicate the direction of future research and treatment.
An example of such a systems approach to a complex clinical problem is the work on the cell biology of ageing by Prof. Kirkwood and colleagues of Newcastle University (published in Nat Rev Mol Cell Biol, 2003). Their modelling of the interactions between multiple molecular mechanisms believed to contribute to cellular senescence led to a novel prediction of the interaction between mitochondrial dysfunction, oxidative stress and telomere erosion in human fibroblasts, something that was subsequently confirmed experimentally.
The aim of this study, headed by Prof. Newton but involving other colleagues in a cross-discipline collaboration, is to apply similar computational and mathematical tools to the rich dataset on ME/CFS patients which now exists at Newcastle University. The work may yield novel insights and hypotheses that can be tested subsequently in clinical or biomarker studies.