Multiple biological systems show abnormalities in ME/CFS patients

New Australian research has identified simultaneous abnormalities across multiple biological systems in people with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS).

Key findings of a multimodal study published today in the journal Cell Reports Medicine include changes in markers of cellular energy metabolism, in the proportions and maturity of circulating immune cells, and in plasma proteins associated with blood vessel dysfunction in people with ME/CFS.

Led by researchers from Macquarie University, the study compared whole blood samples from 61 people meeting clinical diagnostic criteria for ME/CSF with samples from healthy age- and sex-matched volunteers.

White blood cells from ME/CFS patients showed evidence of 'energy stress' in the form of higher levels of adenosine monophosphate (AMP) and adenosine diphosphate (ADP), indicating reduced generation of adenosine triphosphate (ATP), the key energy source within cells.

Profiling of immune cell populations revealed a trend toward less mature subsets of T-lymphocyte subsets, dendritic cells and natural killer cells in people with ME/CSF.

Comprehensive analysis of plasma proteins highlighted disruptions of vascular and immune homeostasis in patients with ME/CFS. Levels of proteins associated with activation of the endothelium – the innermost lining of blood vessels – and remodelling of vessel walls were higher, while levels of circulating immunoglobulin-related proteins were lower.

Although cellular energy dysfunction and altered immune profiles have been noted before in patients with ME/CFS, previous studies have often focused on a single analytical platform without looking at concurrence and interactions.

"ME/CFS is a complex disorder with undefined mechanisms, limited diagnostic tools and treatments," said senior author of the study Dr Richard Schloeffel OAM, Clinical Senior Lecturer in the Macquarie Medical School and an experienced general practitioner. "Our findings provide further insights into the clinical and biological complexity of ME/CFS."

Lead author Dr Benjamin Heng, Research Fellow in the Macquarie Medical School, said: "We know ME/CFS is a heterogeneous disease with abnormalities in several different biological systems, but these dysfunctions have rarely been studied simultaneously within the same patients."

"Potential interactions between these dysregulated systems may contribute to how the disease presents clinically," said Dr Heng.

Using classification and regression tree (CART) modelling – a predictive algorithm approach used in machine learning – the researchers were able to identify a combination of seven biological variables that are strongly associated with ME/CFS, highlighting potential interactions between areas of dysfunction that contribute to the clinical manifestations of ME/CSF.

"A model like this – if clinically validated – has the potential to reduce diagnostic delays and improve patient quality of life, alleviating the prolonged suffering and economic burden faced by patients with ME/CFS," said Dr Schloeffel.