Research: Replicated blood-based biomarkers for ME/CFS not explained by inactivity

ME Association comment

“These are some interesting results in the search for a diagnostic biomarker for ME/CFS. They come from Professor Chris Ponting's research group in Edinburgh – who have used information about people with ME/CFS and healthy controls from the UK Biobank.

“Of particular importance is the fact that they identified differences in blood molecules or cells between people with ME/CFS and healthy controls and these differences were not related to inactivity.

“Please note that these findings have been published in what is called a pre-print paper. This means that they have not yet been subjected to peer review scrutiny by other researchers. We will contact the team and ask if they can produce a lay summary of this rather complicated research.

“The MEA Ramsay Research Fund is currently funding diagnostic biomarker restart the University of Surrey and the University of Oxford.”

Dr Charles Shepherd, Trustee and Hon. Medical Adviser to the ME Association.

Preprint: Replicated blood-based biomarkers for Myalgic Encephalomyelitis not explained by inactivity

Sjoerd V Beentjes, Julia Kaczmarczyk, Amanda Cassar, Gemma Louise Samms, Nima S Hejazi, Ava Khamseh, Chris P Ponting.

Abstract

Myalgic Encephalomyelitis (ME; sometimes referred to as chronic fatigue syndrome) is a relatively common and female-biased disease of unknown pathogenesis that profoundly decreases patients’ health-related quality-of-life.

ME diagnosis is hindered by the absence of robustly-defined and specific biomarkers that are easily measured from available sources such as blood, and unaffected by ME patients’ low level of physical activity.

Previous studies of blood biomarkers have not yielded replicated results, perhaps due to low study sample sizes (n < 100). Here, we use UK Biobank (UKB)
data for up to 1,455 ME cases and 131,303 population controls to discover hundreds of molecular and cellular blood traits that differ significantly between cases and controls.

Importantly, 116 of these traits are replicated, as they are significant for both female and male cohorts. Our analysis used semi-parametric efficient estimators, an initial Super Learner fit followed by a one-step correction, three types of mediators, and natural direct and indirect estimands, to decompose the average effect of ME status on molecular and cellular traits.

Strikingly, these trait differences cannot be explained by ME cases’ restricted activity. Of 3,237 traits considered, ME status had a significant effect on only one, via the “Duration of walk” (UKB field 874) mediator. By contrast, ME status had a significant direct effect on 290 traits (9%). As expected, these effects became more significant with increased stringency of case and control definition.

Significant female and male traits were indicative of chronic inflammation, insulin resistance and liver disease. Individually, significant effects on blood traits, however, were not sufficient to cleanly distinguish cases from controls. Nevertheless, their large number, lack of sex-bias, and strong significance, despite the ‘healthy volunteer’ selection bias of UKB participants, keep alive the future ambition of a blood-based biomarker panel for accurate ME diagnosis.