Bioinformatics Seminar
Time: 11AM
Venue: Davis Auditorium and Online
1 April 2025
NAExploring the sex differences in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) in biobank data
Sara BallouzUniversity of New South Wales
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) can be debilitating for the people suffering from it, with ~25% housebound. The disease mechanisms behind it are difficult to study in part due to the nature of fatigue: it is co-morbid with many other illnesses and thus hard to define and diagnose. Furthermore, several sets of disease definitions and diagnostic criteria are in use, obscuring the estimation of ME/CFS prevalence and diagnosis. However, one aspect universally agreed upon is the stark sex differences – with 75-85% of women among those afflicted. As ME/CFS and autoimmune diseases are both sex-biased, there is evidence that the immune system, along with pathogenic infections, may be involved in the cause and progression of the disease. With data from Australian and US ME/CFS biobanks, we aimed to characterize ME/CFS and explore common features of the disease. We first report on the demographics of the individuals within the biobanks and replicate known characteristics of ME/CFS. We also observe that viral infections were the most common triggers for ME/CFS. We then applied a supervised simple linear regression classifier to test whether we could use phenotypic and survey features to classify individuals. We find that even broad quality of life scores are highly good predictors of disease status. Future work will improve on this classifier through an unsupervised approach to select better discriminatory features.