This international research symposium was organised in Geelong by Emerge Australia, the peak body For ME/CFS advocacy. It was a pleasure to chair the first session, Research Innovation, Big Data and Bioinformatics, at this conference on Thursday 14 March.
Dr Ronald Davis, Director of the Stanford Genome Technology Center spoke first, on Establishing new mechanistic and diagnostic paradigms for ME/CFS. His interest in ME/CFS is personal, as he described his experience caring for an adult son with a severe form of the condition. I firmly believe that a personal passion can be very helpful when the research going gets tough, however a more dispassionate passion is also valuable in terms of evaluating the evidence and reacting with caution in the face of uncertainty.
Ron has been using the Stanford supercomputer to compare masses of gene sequences to masses of other gene sequences in his search for signals of ME/CFS. He’s been looking at viruses too, and parasites (think trypanosomiasis or sleeping sickness, and Leishmaniasis). Even metallomics is a thing now.
Dr Wenzhong Xiao of Harvard Medical Center spoke next, on The Severely Ill Patient Study of ME/CFS. I like his use of heat maps to visualise everything from correlation matrices to the usual gene expression data, but I look forward to measure of variability being included in these plots such as is now packaged up in R by my colleague Petra Kuhnert. I was also keen to know more about the 60-odd metabolites out of 600 that were found to be significant. Would these be hypothesis-testing, needing adjustment for multiple testing, or more in the way of hypothesis-generating, ready for further research.
Dr Robert Phair of Integrative Bioinformatics Inc, completed the session with a presentation on Metabolic Traps in ME/CFS. He firmly placed ME/CFS at the intersection of three concepts – bistability, biochemistry and genetics. Bistability refers to the multiple stable points of metabolite curves. Robert’s main research focus is common gene variants, wondering if ME/CFS is actually a common condition with common variants, rather than the more widely studies rare conditions with rare variants.
The second session was on Metabolomics and Transcriptomics. Dr Chris Armstrong of the Open Medicine Foundation spoke on Longitudinal ME/CFS MMR Metabolomics. He briefly introduced results from studies of B cells then moved on to the part that interested me much more, a longitudinal study involving 25 blood samples in 25 days from ten patients. The analysis of this data is work-in-progress and I see it as a huge opportunity to apply techniques such as functional data analysis to a problem that so clearly involves autocorrelated data.
Ruud Raijmakers of Radboud University Medical Centre in the Netherlands came at things from a completely different direction, to speak on Transcriptome analysis of QFS and CFS in the Netherlands. His jumping off point was an “outbreak” over several years in the early 2010s of Q fever in the south of the Netherlands, traced to infected goats on farms in the region. A proportion of people who contract Q fever go on to experience CFS-lime symptoms and Ruud was interested in seeing if the experience in treating Q fever fatigue syndrome had any parallels in the chronic fatigue space.