The ME Association End of Week Research Round-up

August 7, 2020

Charlotte Stephens, Research Correspondent, ME Association.

We show below brief summaries of the research studies about ME/CFS that have been published in the last week, followed by the abstracts from those studies.

All research relating to ME/CFS can be located in the ME Association: Index of ME/CFS Published Research.

This extensive library of research is updated at the end of every month, and is correct to the end of July 2020. It is a free resource available to anyone.

The Index provides an A-Z of published research studies and selected key documents and articles, listed by subject matter, on myalgic encephalomyelitis, myalgic encephalopathy, and/or chronic fatigue syndrome (ME/CFS).

You can use it to easily locate and read any research in a particular area that you might be interested in, e.g. epidemiology, infection, neurology, post-exertional malaise etc.

You can also find the Research Index in the Research section of the website together with a list of Research Summaries that provide lay explanations of the more important and interesting work that has been published to date.

ME/CFS Research Published 01 August – 06 August 2020

This week, 3 new research studies have been published:

1. Researchers from the University of Edinburgh have published a review of existing evidence for genetic risk factors in ME/CFS.

They concluded that there is currently no consistent evidence of significant associations in gene variants with ME/CFS and much larger studies are needed.

The DecodeME study, which will analyse 20,000 DNA samples from people with M.E., should add more knowledge to this area.

2. A research group from the USA have successfully used machine learning models to differentiate CFS from Golf War Illness (GWI) with high before and after exercise with high accuracy using differences in functional magnetic resonance imaging (fMRI).

3. Researchers from Berlin carried out a pilot trial in which they treated five ME/CFS patients with immunoadsorption (a procedure that removes specific antibodies from the blood), based on the hypothesis that ME/CFS has an autoimmune component involving ß2-adrenoreceptor antibodies.

The treatment was well tolerated and generated a 80–90% decline of ß2-adrenoreceptor antibodies. Four patients showed a rapid improvement in several clinical symptoms during IA therapy, lasting for six to 12 months. One patient had no improvement. They concluded that the results from their trial warrant further studies in this area.

ME/CFS Research references and abstracts

1. Dibble J et al. (2020)
Genetic Risk Factors of ME/CFS: A Critical Review.
Human Molecular Genetics [Epub ahead of print]

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex multisystem illness that lacks effective therapy and a biomedical understanding of its causes.

Despite a prevalence of approximately 0.2-0.4% and its high public health burden, and evidence that it has a heritable component, ME/CFS has not yet benefited from the advances in technology and analytical tools that have improved our understanding of many other complex diseases.

Here we critically review existing evidence that genetic factors alter ME/CFS risk before concluding that most ME/CFS candidate gene associations are not replicated by the larger CFS cohort within UK Biobank.

Multiple genome-wide association studies of this cohort also have not yielded consistently significant associations.

Ahead of upcoming larger genome-wide association studies we discuss how these could generate new lines of enquiry into the DNA variants, genes and cell-types that are causally involved in ME/CFS disease.

2. Provenzano D et al. (2020)
Machine Learning Detects Pattern of Differences in Functional Magnetic Resonance Imaging (fMRI) Data between Chronic Fatigue Syndrome (CFS) and Gulf War Illness (GWI).
Brain Sciences 10 (7).

Background: Gulf War Illness (GWI) and Chronic Fatigue Syndrome (CFS) are two debilitating disorders that share similar symptoms of chronic pain, fatigue, and exertional exhaustion after exercise.

Many physicians continue to believe that both are psychosomatic disorders and to date no underlying etiology has been discovered. As such, uncovering objective biomarkers is important to lend credibility to criteria for diagnosis and to help differentiate the two disorders.

Methods: We assessed cognitive differences in 80 subjects with GWI and 38 with CFS by comparing corresponding fMRI scans during 2-back working memory tasks before and after exercise to model brain activation during normal activity and after exertional exhaustion, respectively.

Voxels were grouped by the count of total activity into the Automated Anatomical Labeling (AAL) atlas and used in an “ensemble” series of machine learning algorithms to assess if a multi-regional pattern of differences in the fMRI scans could be detected.

Results: A K-Nearest Neighbor (70%/81%), Linear Support Vector Machine (SVM) (70%/77%), Decision Tree (82%/82%), Random Forest (77%/78%), AdaBoost (69%/81%), Naïve Bayes (74%/78%), Quadratic Discriminant Analysis (QDA) (73%/75%), Logistic Regression model (82%/82%), and Neural Net (76%/77%) were able to differentiate CFS from GWI before and after exercise with an average of 75% accuracy in predictions across all models before exercise and 79% after exercise.

An iterative feature selection and removal process based on Recursive Feature Elimination (RFE) and Random Forest importance selected 30 regions before exercise and 33 regions after exercise that differentiated CFS from GWI across all models, and produced the ultimate best accuracies of 82% before exercise and 82% after exercise by Logistic Regression or Decision Tree by a single model, and 100% before and after exercise when selected by any six or more models.

Differential activation on both days included the right anterior insula, left putamen, and bilateral orbital frontal, ventrolateral prefrontal cortex, superior, inferior, and precuneus (medial) parietal, and lateral temporal regions. Day 2 had the cerebellum, left supplementary motor area and bilateral pre- and post-central gyri. Changes between days included the right Rolandic operculum switching to the left on Day 2, and the bilateral midcingulum switching to the left anterior cingulum.

Conclusion: We concluded that CFS and GWI are significantly differentiable using a pattern of fMRI activity based on an ensemble machine learning model.

3. Tolle M et al. (2020)
Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Efficacy of Repeat Immunoadsorption.
Journal of Clinical Medicine 9 (8).

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex neuroimmunological disease. There is evidence for an autoimmune mechanism for ME/CFS with an infection-triggered onset and dysfunction of ß2-adrenoreceptor antibodies (ß2AR-AB).

In a first proof-of-concept study, we could show that IA was effective to reduce ß2AR-AB and led to improvement of various symptoms. Five of the ME/CFS patients who had clinical improvement following treatment with a five-day IA were retreated in the current study about two years later with a modified IA protocol. The severity of symptoms was assessed by disease specific scores during a follow-up period of 12 months. The antibodies were determined by ELISA.

The modified IA treatment protocol resulted in a remarkable similar clinical response. The treatment was well tolerated and 80–90% decline of total IgG and ß2AR-AB was achieved. Four patients showed a rapid improvement in several clinical symptoms during IA therapy, lasting for six to 12 months. One patient had no improvement.

We could provide further evidence that IA has clinical efficacy in patients with ME/CFS. Data from our pilot trial warrant further controlled studies in ME/CFS.

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