A recent publication by Hoel et al. who carried out a comprehensive study of the biochemical composition of the blood, suggests that ME/CFS may be a condition associated with cellular energy strain. Concluding that ME/CFS symptoms may be caused by metabolic dysfunction.
“We suggest that elevated energy strain may result from exertion-triggered tissue hypoxia and lead to systemic metabolic adaptation and compensation. Through various mechanisms, such metabolic dysfunction represents a likely mediator of key symptoms in ME/CFS and possibly a target for supportive intervention.”
This is a fairly exciting study within ME/CFS research, as it is comparatively large with 83 patients with ME/CFS and 35 healthy controls (although much larger studies would still be needed to confirm results).
What is the background?
The etiology (the cause) of ME/CFS is still unknown, however, it is often triggered by a viral infection and the resulting immune system response, with possible roles of autoimmunity, immune dysregulation and inflammation involved in the disease.
ME/CFS is often reported to cause other changes in the body, such as neuroinflammation, neuroendocrine abnormalities, autonomic nervous system abnormalities, disturbed energy metabolism, and immunological changes. These changes are connected at the molecular, cellular and systemic levels.
Previous research by this research group has found evidence suggesting reduced function of a central enzyme in the cell's energy metabolism called pyruvate dehydrogenase (PDH) (Fluge et al., 2016). Furthermore, other studies by other researchers in vitro (experimental work performed outside of a living organism, such as in a test tube) have shown stressed cell metabolism (Esfadyarpour et al., 2019; Schreiner et al., 2020). Despite these findings routine blood tests don’t usually show anything outside the normal ranges (Nacul et al., 2019).
Metabolism (which describes all the chemical processes that go on continuously inside your body) plays a key role in the body’s defences against deficiencies and threats, such as starvation, hypoxia and infection. Energy metabolism is linked to mechanisms that contribute to fatigue, such as the depletion of nutrients and oxygen. These effects affect mitochondrial function, which has previously been proposed to be a factor in ME/CFS (Blomstand, 2001; Fitts, 1994). Despite these findings and the evidence of stressed cell metabolism, there is currently no complete overview of the changes in systemic (relating to a particular part in the bodies system) energy metabolism in ME/CFS.
What do the authors hypothesis and what is the aim of this study?
“We hypothesize that impaired metabolism and strain on cellular energetics may play a central role.”
“The aim of the present study was to map metabolic phenotypes of ME/CFS and thereby gain insights into disease-related mechanisms. We performed comprehensive serum metabolite measurements and exploratory data analyses (EDA), and we found both common and variable alterations in the ME/CFS patient group. The abnormalities covered recognizable patterns of energy strain, as well as context-dependent signatures of deregulated metabolism. The possible clinical impact should be further investigated, as some aspects may contribute to worsening of the disease.”
What do some of the key terms mean in this paper?
- Metabolism describes all the chemical processes that go on continuously inside your body.
- Phenotype refers to the observable physical properties of an organism; these include the organism's appearance, development, and behaviour. Such as eye colour and height.
- Systemic relates to a particular part in the bodies system.
What was investigated?
Similar studies to this have been performed before, but not to this scope and size. This study used 83 ME/CFS patients and 35 healthy controls and blood samples were collected. The composition of the blood samples were analysed to determine the metabolites, lipids and metabolic hormones present. Exploratory data analysis was then used to compare between ME/CFS patients and healthy controls.
“ A strength of the study was that statistical analyses were strongly and independently supported by multiple layers of biochemical findings and rationale.”
What are the main findings of this study?
This study revealed a map of the common and variable metabolic phenotypes in ME/CFS, 3 subsets of ME/CFS patients were identified with two of these groups expressing characteristics contexts of deregulated energy metabolism.
Initial findings:
- In blood serum, 880 compounds were detected.
- After exclusion of compounds with a high level of missing data, 610 different compounds could be used in the analysis.
- Statistical analysis showed of the 610 compounds, 159 were significantly different in ME/CFS patients.
- Of the 159 compounds which were different in ME/CFS, 87 were elevated and 72 were lower compared to health controls.
- Of the 159 compounds, 75 were lipid related compounds and 49 amino acid.
Three different metabolic phenotypes were identified following further analysis:
- Further statistical analysis of the 159 compounds divided ME/CFS patients into three groups.
- The three ME/CFS groups were labelled as M1, M2, M3.
- Results showed relatively little overlap between the health controls (HC), ME-M1, and ME-M2 clusters, whereas the ME-M3 subset was positioned as a merger phenotype between the 3 others.
- ME/CFS subsets were found to be separated by lipid and amino acid metabolites.
- Further assessment ranked the apparent functioning levels in the orders M2 < M2 < M3, with the M3 having the vast majority of patients being diagnosed with mild/moderate severity.
How do the three subsets of ME/CFS differ?
The ME-M1 and ME-M2 subsets displayed distinct metabolic patterns.
ME-M1 showed typical signs of increased fatty acid mobilisation and oxidation, with higher levels of free fatty acids and ketone bodies in the blood. This group also had lower levels of several energy-linked amino acids. The pattern appeared to resemble metabolic effects of fasting or endurance training. Therefore, these effects may indicate a context of reduced utilisation of carbohydrates as energy fuel.
ME-M2 was characterised by increased levels of triglycerides and lower levels of free fatty acids compared to the healthy controls. This may indicate impaired control of lipid metabolism due to disturbed energy homeostasis. This subgroup also had significantly increased FGF-21 level in blood compared to the controls, which supports elevated metabolic strain. Of not, the ME-M2 subgroup scored worse on physical function compared to the others.
However, ME-M3, this subgroup largely overlapped with the healthy control group, yet with some similarities with the two other subgroups.
What are the implications of this research?
“The observed metabolic changes mainly fit into the paradigm of direct and indirect effects of energy strain. The physiological relevance was supported by associations with endocrine and clinical characteristics. Through the following discussion, we suggest that energy strain may result from exertion-sensitive tissue hypoxia and leads to the systemic patterns of metabolic adaptation and compensation.”
“These findings pointing to vascular dysfunction support that exertion-triggered tissue oxygenation may be impaired, and clearly this would contribute to lowered activity tolerance and involve mitochondrial energy metabolism. One may also speculate that symptom-generating mitochondrial effects are pathologically reinforced by exertion, as observed after excessive exercise”.
What are the next steps from the findings in this research?
“ Further investigations should be performed to pursue this theory and to identify possible support strategies for improved clinical care.”
These findings should be replicated in additional cohorts. Further investigations into the causes of these metabolic changes should be done. One current working hypothesis is that exertion-triggered tissue hypoxia may play a role, possibly maintained by an autoimmune mechanism, further reading on this hypothesis can be found here.
What are the limitations of the findings in this research?
“Possible limitations of the study included metabolite stability and the limited accuracy of global untargeted metabolomics. The limitations of univariate feature selection for the purpose of clustering and identifying patient subtypes in high dimensional data sets are well known issues in the statistical community.”
There are always many factors to consider when analysing big datasets of this complexity. Extensive statistical analyses were performed to test if the conclusions were valid. Although factors such as sex, age, BMI, diet and medication are known do influence metabolism, they did not explain the overall picture in the ME/CFS subsets. Furthermore, key findings were supported by independent quantitative methods.
What do the authors say about their findings?
Karl Tronstad from the study says:
“The study identified common and variable metabolic features in ME/CFS patients, which provides a framework for understanding the role of metabolic alterations in this disease. The findings may be useful in future investigations to find biomarkers and supportive treatments.”
What are the authors connections to ME/CFS?
The authors are clinical and biomedical researchers associated with ME/CFS research at Haukeland University Hospital and University of Bergen, Bergen, Norway. The biobank samples were collected in the context of the RituxMe and CycloME clinical trials.
Further reading on the findings from this paper
- Hypothesis: An autoimmune mechanism blocks the oxygen supply to the cells during exertion.
- Researchers unravel pathomechanisms involved in Chronic Fatigue Syndrome.
References
Blomstrand E. (2001) Amino acids and central fatigue. Amino Acids 20 (1): 25-34. Link: https://pubmed.ncbi.nlm.nih.gov/11310928/
Esfandyarpour R, Kashi A, Nemat-Gorgani M, Wilhelmy J, Davis RW. (2019) A nanoelectronics-blood-based diagnostic biomarker for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Proceedings of the National Academy of Science of the Unites States of America 116 (21): 10250-10257. Link: https://pubmed.ncbi.nlm.nih.gov/31036648/
Fitts RH. (1994) Cellular mechanisms of muscle fatigue. Physiological Reviews 74 (1): 49-94. Link: https://pubmed.ncbi.nlm.nih.gov/8295935/
Fluge Ø, Mella O, Bruland O, Risa K, Dyrstad SE, Alme K, Rekeland IG, Sapkota D, Røsland GV, Fosså A, Ktoridou-Valen I, Lunde S, Sørland K, Lien K, Herder I, Thürmer H, Gotaas ME, Baranowska KA, Bohnen LM, Schäfer C, McCann A, Sommerfelt K, Helgeland L, Ueland PM, Dahl O, Tronstad KJ. (2016) Metabolic profiling indicates impaired pyruvate dehydrogenase function in myalgic encephalopathy/chronic fatigue syndrome. JCI Insight 1 (21): e89376. Link: https://pubmed.ncbi.nlm.nih.gov/28018972/
Nacul L, de Barros B, Kingdon CC, Cliff JM, Clark TG, Mudie K, Dockrell HM, Lacerda EM. (2019) Evidence of Clinical Pathology Abnormalities in People with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) from an Analytic Cross-Sectional Study. Diagnostics (Basel, Switzerland) 9 (2): 41. Link: https://pubmed.ncbi.nlm.nih.gov/30974900/
Schreiner P, Harrer T, Scheibenbogen C, Lamer S, Schlosser A, Naviaux RK, Prusty BK. (2020) Human Herpesvirus-6 Reactivation, Mitochondrial Fragmentation, and the Coordination of Antiviral and Metabolic Phenotypes in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. ImmunoHorizons 4 (4): 201-215. Link: https://pubmed.ncbi.nlm.nih.gov/32327453/