Mapping the complexity of ME/CFS: Evidence for abnormal energy metabolism, altered immune profile, and vascular dysfunction

Abstract

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex disorder with undefined mechanisms, no diagnostic tools and treatments. To investigate concurrent system dysfunctions, we recruited age- and sex-matched ME/CFS patients and healthy controls for a multimodal analysis of energy metabolism, immune profiles, and plasma proteomics. Immune cells from ME/CFS patients show elevated adenosine monophosphate (AMP) and adenosine diphosphate (ADP) with a reduced ATP/ADP ratio, indicating decreased ATP generation and cellular energy stress. Immune profiling reveals skewing toward less mature effector subsets of CD4⁺, CD8⁺, and γδ T cells, with reduced CD1c⁺CD141^- conventional DC type 2 and CD56^lowCD16⁺ terminal natural killer cells. Elevated levels of plasma proteins associated with thrombus formation and vascular reactivity may contribute to the endothelial dysfunction observed in ME/CFS patients. Classification and regression tree modeling identifies variables with strong predictive potential for ME/CFS. Together, this study provides insights into the somatic symptoms and underlying biology of ME/CFS.

Keywords: energy metabolism; immune dysfunction; metabolomics; myalgic encephalomyelitis/chronic fatigue syndrome; proteomics.

Graphical abstract

Figure 1

Overall recruitment and experimental workflow Sixty-three potential ME/CFS patients were recruited and underwent detailed case reviews. Among them, two did not meet the Canadian Consensus Criteria or satisfy the case definition classification according to the DePaul Symptoms Questionnaire-Short Form (DSQ-SF) and were therefore excluded. Sixty-one healthy controls were recruited separately to age- and sex-match the patient cohort. All participants were further assessed for their health status and quality of life using the SF-36 and Karnofsky Performance Scale. Blood was collected and processed for plasma, and peripheral blood mononuclear cells (PBMCs) were isolated for downstream targeted metabolite analysis, immune profiling, and plasma proteome analysis.

Figure 2

Analysis of energy metabolism of peripheral and immune cell population (A) Simplified schematic of the kynurenine pathway (KP), illustrating its role in producing NAD⁺. (B) Shows plasma levels of metabolites in the KP. 3HK was significantly higher, whereas KYNA, PIC, and QUIN were significantly lower in patients compared to healthy controls. (C) ME/CFS patients had a higher level of AMP and lower ATP/ADP ratio in their plasma, indicating reduced ATP production. (D) In ME/CFS patient PBMCs, levels of NAD⁺, AMP, ADP, and the NADP/NADPH ratio were elevated, whereas the ATP/ADP ratio was reduced. Collectively, these findings suggest abnormal energy production in patients with ME/CFS, potentially contributing to their chronic fatigue. Each scatterplot represents individual participants (dots), and data are presented as the median and 95% confidence intervals. p value was calculated using Mann-Whitney U test. Plasma samples were collected from 61 ME/CFS patients and 61 healthy controls. However, matched PBMC samples were available for only 60 patients and 60 healthy controls due to insufficient immune cell yield from one healthy control sample and no quantification signals from one ME/CFS patient sample, as described under sample collection. For the calculation of the NADP/NADPH ratio, only 47 of 60 healthy controls were included, as 13 controls recorded zero value for NADP⁺.

Figure 3

Immunophenotyping of peripheral blood mononuclear cells We observed a significantly lower proportion of (A) CD1c⁺CD141⁻ conventional dendritic cells 2 (cDC2) and a higher proportion of CD11c⁻CD123⁺ plasmacytoid dendritic cells (pDC) in ME/CFS patients. There was a significantly lower proportion of effector memory cell subsets of (B) CD4⁺ and (C) CD8⁺ T cells, primarily attributable to the reduction in CD27⁻CD28⁻ terminal subset of the effector memory population. Additionally, ME/CFS patients also had decreased proportions of (D) the CD45RA⁺CCR7⁻ TEMRA γδ T cell subset and (E) CD56^lowCD16⁺ terminal NK cells. Collectively, the reduction in pathogen-responding immune cell subsets suggests an altered immune system in ME/CFS patients and an increased vulnerability to viral infection. Each scatterplot represents individual participants (dots), and data are presented as the median and 95% confidence intervals. p value was calculated using Mann-Whitney U test or Welsh’s t test. PBMCs were collected from 61 ME/CFS patients and 60 age- and sex-matched healthy controls.

Figure 4

Proteomic analysis of plasma protein in ME/CFS patients and healthy controls (A) Volcano plot illustrating the distribution of plasma proteins that were shown to be differentially expressed in ME/CFS patients compared to healthy controls. Twenty proteins were elevated in ME/CFS patients: namely (B) LYVE1, DNAJC2, THBS1, VASN, IGHV3-74, IGKV6-21, PIGR, CFHR5, EFEMP1, SHBG, PRG4, PROC, FN1, B2M, PCYOX1, VWF, CFHR2, MASP1, IGHV5-51, and FETUB. (C) Eight plasma proteins were significantly lower in ME/CFS patients: IGHG3, IGHG2, IGKV1-17, IGHA1, IGKC, PIEZO1, CDH5, and IGLL1. Many of these proteins are associated with immune activity or vascular integrity. Each scatterplot represents individual participants (dots), and data are presented as the median and 95% confidence intervals. A relative abundance comparison was made by t test in R. Proteins with p value <0.05 and fold change >1.2 were determined to be differentially expressed between healthy controls and patients with ME/CFS. Plasma was collected from age- and sex-matched 61 ME/CFS patients and 61 healthy controls. (D) Top 10 upregulated and downregulated pathways in MECFS patient compared to controls, ranked by the highest and lowest Z score based on differentially expressed proteins. The bars are color-coded to indicate the regulatory status of the genes within each pathway.

Figure 5

Identification of strong predictive potential for ME/CFS using classification and regression tree modeling Among the 114 biological parameters, CART modeling identified seven significant contributors to discriminate between ME/CFS patients and controls with 85.2% sensitivity, 96.7% specificity, and 91% accuracy. These were FN1, cDC1, VWF, LYVE1, AMP (plasma), IGHG2, and THBS1 to predicting ME/CFS patients. CART modeling was used to develop a classification model using IBM SPSS Statistics v.29 and JMP v.17.2.