Biomarker Test for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

By Jennifer Abbasi

Myalgic encephalomyelitis/chronic fatigue syndrome affects at least 2 million people in the United States. Despite its prevalence, there’s no laboratory test for the disease, and its diagnosis is based on symptoms like exhaustion, unrefreshing sleep, and light sensitivity. For patients with this debilitating condition, getting a diagnosis is often a long and expensive process. Now, a long-awaited biomarker-based test for the mysterious disease could be on the horizon.

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JAMA. 2019;322(2):107. doi:10.1001/jama.2019.8890

A nanoelectronics-blood-based diagnostic biomarker for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS)

Abstract:

There is not currently a well-established, if any, biological test to diagnose myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). The molecular aberrations observed in numerous studies of ME/CFS blood cells offer the opportunity to develop a diagnostic assay from blood samples. Here we developed a nanoelectronics assay designed as an ultrasensitive assay capable of directly measuring biomolecular interactions in real time, at low cost, and in a multiplex format.

To pursue the goal of developing a reliable biomarker for ME/CFS and to demonstrate the utility of our platform for point-of-care diagnostics, we validated the array by testing patients with moderate to severe ME/CFS patients and healthy controls. The ME/CFS samples’ response to the hyperosmotic stressor observed as a unique characteristic of the impedance pattern and dramatically different from the response observed among the control samples. We believe the observed robust impedance modulation difference of the samples in response to hyperosmotic stress can potentially provide us with a unique indicator of ME/CFS. Moreover, using supervised machine learning algorithms, we developed a classifier for ME/CFS patients capable of identifying new patients, required for a robust diagnostic tool.

Source: R. Esfandyarpour, A. Kashi, M. Nemat-Gorgani, J. Wilhelmy, and R. W. Davis. A nanoelectronics-blood-based diagnostic biomarker for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). PNAS first published April 29, 2019 https://doi.org/10.1073/pnas.1901274116

Biomarker for chronic fatigue syndrome identified by Stanford researchers

People suffering from a debilitating and often discounted disease known as chronic fatigue syndrome may soon have something they’ve been seeking for decades: scientific proof of their ailment.

Researchers at the Stanford University School of Medicine have created a blood test that can flag the disease, which currently lacks a standard, reliable diagnostic test.

“Too often, this disease is categorized as imaginary,” said Ron Davis, PhD, professor of biochemistry and of genetics. When individuals with chronic fatigue syndrome seek help from a doctor, they may undergo a series of tests that check liver, kidney and heart function, as well as blood and immune cell counts, Davis said. “All these different tests would normally guide the doctor toward one illness or another, but for chronic fatigue syndrome patients, the results all come back normal,” he said.

The problem, he said, is that they’re not looking deep enough. Now, Davis; Rahim Esfandyarpour, PhD, a former Stanford research associate; and their colleagues have devised a blood-based test that successfully identified participants in a study with chronic fatigue syndrome. The test, which is still in a pilot phase, is based on how a person’s immune cells respond to stress. With blood samples from 40 people — 20 with chronic fatigue syndrome and 20 without — the test yielded precise results, accurately flagging all chronic fatigue syndrome patients and none of the healthy individuals.

The diagnostic platform could even help identify possible drugs to treat chronic fatigue syndrome. By exposing the participants’ blood samples to drug candidates and rerunning the diagnostic test, the scientists could potentially see whether the drug improved the immune cells’ response. Already, the team is using the platform to screen for potential drugs they hope can help people with chronic fatigue syndrome down the line.

A paper describing the research findings will be published online April 29 in the Proceedings of the National Academy of Sciences. Davis is the senior author. Esfandyarpour, who is now on the faculty of the University of California-Irvine, is the lead author.

Providing the proof

The diagnosis of chronic fatigue syndrome, when it actually is diagnosed, is based on symptoms — exhaustion, sensitivity to light and unexplained pain, among other things — and it comes only after other disease possibilities have been eliminated. It’s estimated that 2 million people in the United States have chronic fatigue syndrome, but that’s a rough guess, Davis said, and it’s likely much higher.

For Davis, the quest to find scientific evidence of the malady is personal. It comes from a desire to help his son, who has suffered from chronic fatigue syndrome for about a decade. In fact, it was a biological clue that Davis first spotted in his son that led him and Esfandyarpour to develop the new diagnostic tool.

The approach, of which Esfandyarpour led the development, employs a “nanoelectronic assay,” which is a test that measures changes in miniscule amounts of energy as a proxy for the health of immune cells and blood plasma. The diagnostic technology contains thousands of electrodes that create an electrical current, as well as chambers to hold simplified blood samples composed of immune cells and plasma. Inside the chambers, the immune cells and plasma interfere with the current, changing its flow from one end to another. The change in electrical activity is directly correlated with the health of the sample.

The idea is to stress the samples from both healthy and ill patients using salt, and then compare how each sample affects the flow of the electrical current. Changes in the current indicate changes in the cell: the bigger the change in current, the bigger the change on a cellular level. A big change is not a good thing; it’s a sign that the cells and plasma are flailing under stress and incapable of processing it properly. All of the blood samples from chronic fatigue syndrome patients created a clear spike in the test, whereas those from healthy controls returned data that was on a relatively even keel.

“We don’t know exactly why the cells and plasma are acting this way, or even what they’re doing,” Davis said. “But there is scientific evidence that this disease is not a fabrication of a patient’s mind. We clearly see a difference in the way healthy and chronic fatigue syndrome immune cells process stress.” Now, Esfandyarpour and Davis are expanding their work to confirm the findings in a larger cohort of participants.

Doubling up

In addition to diagnosing chronic fatigue syndrome, the researchers are also harnessing the platform to screen for drug-based treatments, since currently the options are slim. “Using the nanoelectronics assay, we can add controlled doses of many different potentially therapeutic drugs to the patient’s blood samples and run the diagnostic test again,” Esfandyarpour said.

If the blood samples taken from those with chronic fatigue syndrome still respond poorly to stress and generate a spike in electrical current, then the drug likely didn’t work. If, however, a drug seems to mitigate the jump in electrical activity, that could mean it is helping the immune cells and plasma better process stress. So far, the team has already found a candidate drug that seems to restore healthy function to immune cells and plasma when tested in the assay. The drug, while successful in the assay, is not currently being used in people with chronic fatigue syndrome, but Davis and Esfandyarpour are hopeful that they can test their finding in a clinical trial in the future.

All of the drugs being tested are either already approved by the Food and Drug Administration or will soon be broadly accessible to the public, which is key to fast access and dissemination should any of these compounds pan out.

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Other Stanford authors of the study are research scientists Neda Nemat-Gorgani and Julie Wilhelmy and research assistant, Alex Kashi.

The study was funded by the Open Medicine Foundation. Davis is the director of the foundation’s scientific advisory board.

Stanford’s departments of Genetics and of Biochemistry also supported the work

The Stanford University School of Medicine consistently ranks among the nation’s top medical schools, integrating research, medical education, patient care and community service. For more news about the school, please visit http://med.stanford.edu/school.html. The medical school is part of Stanford Medicine, which includes Stanford Health Care and Stanford Children’s Health. For information about all three, please visit http://med.stanford.edu.

Evidence of Clinical Pathology Abnormalities in People with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) from an Analytic Cross-Sectional Study

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disease presenting with extreme fatigue, post-exertional malaise, and other symptoms. In the absence of a diagnostic biomarker, ME/CFS is diagnosed clinically, although laboratory tests are routinely used to exclude alternative diagnoses. In this analytical cross-sectional study, we aimed to explore potential haematological and biochemical markers for ME/CFS, and disease severity.

We reviewed laboratory test results from 272 people with ME/CFS and 136 healthy controls participating in the UK ME/CFS Biobank (UKMEB). After corrections for multiple comparisons, most results were within the normal range, but people with severe ME/CFS presented with lower median values (p < 0.001) of serum creatine kinase (CK; median = 54 U/L), compared to healthy controls (HCs; median = 101.5 U/L) and non-severe ME/CFS (median = 84 U/L).

The differences in CK concentrations persisted after adjusting for sex, age, body mass index, muscle mass, disease duration, and activity levels (odds ratio (OR) for being a severe case = 0.05 (95% confidence interval (CI) = 0.02–0.15) compared to controls, and OR = 0.16 (95% CI = 0.07–0.40), compared to mild cases). This is the first report that serum CK concentrations are markedly reduced in severe ME/CFS, and these results suggest that serum CK merits further investigation as a biomarker for severe ME/CFS.

Source: Nacul, L.; de Barros, B.; Kingdon, C.C.; Cliff, J.M.; Clark, T.G.; Mudie, K.; Dockrell, H.M.; Lacerda, E.M. Evidence of Clinical Pathology Abnormalities in People with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) from an Analytic Cross-Sectional Study. Diagnostics 2019, 9, 41. https://www.mdpi.com/2075-4418/9/2/41 (Full article available as PDF file)

Artificial intelligence based discovery of the association between depression and chronic fatigue syndrome

Abstract:

BACKGROUND: Both of the modern medicine and the traditional Chinese medicine classify depressive disorder (DD) and chronic fatigue syndrome (CFS) to one type of disease. Unveiling the association between depressive and the fatigue diseases provides a great opportunity to bridge the modern medicine with the traditional Chinese medicine.

METHODS: In this work, 295 general participants were recruited to complete Zung Self-Rating Depression Scales and Chalder Fatigue Scales, and meanwhile, to donate plasma and urine samples for 1H NMR-metabolic profiling. Artificial intelligence methods was used to analysis the underlying association between DD and CFS. Principal components analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to analyze the metabolic profiles with respect to gender and age. Variable importance in projection and t-test were employed in conjunction with the PLS-DA models to identify the metabolite biomarkers. Considering the asymmetry and complexity of the data, convolutional neural networks (CNN) model, an artificial intelligence method, was built to analyze the data characteristics between each groups.

RESULTS: The results showed the gender- and age-related differences for the candidate biomarkers of the DD and the CFS diseases, and indicated the same and different biomarkers of the two diseases. PCA analysis for the data characteristics reflected that DD and CFS was separated completely in plasma metabolite. However, DD and CFS was merged into one group.

LIMITATION: Lack of transcriptomic analysis limits the understanding of the association of the DD and the CFS diseases on gene level.

CONCLUSION: The unmasked candidate biomarkers provide reliable evidence to explore the commonality and differences of the depressive and the fatigue diseases, and thereby, bridge over the traditional Chinese medicine with the modern medicine.

Copyright © 2019 Elsevier B.V. All rights reserved.

Source: Zhang F, Wu C, Jia C, Gao K, Wang J, Zhao H, Wang W, Chen J. Artificial intelligence based discovery of the association between depression and chronic fatigue syndrome. J Affect Disord. 2019 Mar 8;250:380-390. doi: 10.1016/j.jad.2019.03.011. [Epub ahead of print]

Diagnostic sensitivity of 2-day cardiopulmonary exercise testing in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Abstract:

BACKGROUND: There are no known objective biomarkers to assist with the diagnosis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). A small number of studies have shown that ME/CFS patients exhibit an earlier onset of ventilatory threshold (VT) on the second of two cardiopulmonary exercise tests (CPET) performed on consecutive days. However, cut-off values which could be used to differentiate between ME/CFS patients have not been established.

METHODS: 16 ME/CFS patients and 10 healthy controls underwent CPET on a cycle-ergometer on 2-consecutive days. Heart rate (HR), ventilation, ratings of perceived exertion (RPE) and work rate (WR) were assessed on both days.

RESULTS: WR at VT decreased from day 1 to day 2 and by a greater magnitude in ME/CFS patients (p < 0.01 group × time interaction). No interaction effects were found for any other parameters. ROC curve analysis of the percentage change in WR at VT revealed decreases of - 6.3% to - 9.8% provided optimal sensitivity and specificity respectively for distinguishing between patients with ME/CFS and controls.

CONCLUSION: The decrease in WR at VT of 6.3-9.8% on the 2nd day of consecutive-day CPET may represent an objective biomarker that can be used to assist with the diagnosis of ME/CFS.

Source: Nelson MJ, Buckley JD, Thomson RL, Clark D, Kwiatek R, Davison K. Diagnostic sensitivity of 2-day cardiopulmonary exercise testing in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. J Transl Med. 2019 Mar 14;17(1):80. doi: 10.1186/s12967-019-1836-0. (Full study)

Multidimensional Comparison of Cancer-Related Fatigue and Chronic Fatigue Syndrome: The Role of Psychophysiological Markers

Abstract:

OBJECTIVE: The present study compared cancer-related fatigue (CRF) and chronic fatigue syndrome (CFS) using multidimensional measurements with the aim of better understanding characteristics and exploring markers of two similar fatigue syndromes.

METHODS: Twenty-five patients with CRF and twenty patients with CFS completed questionnaires, including the Fatigue Severity Scale (FSS), Hospital Anxiety Depression Scale (HADS), Perceived Stress Scale (PSS), and Pittsburgh Sleep Quality Index (PSQI). Additionally, levels of high sensitivity C-reactive protein (hs-CRP), heart rate variability (HRV), and electroencephalography (EEG) were obtained. Neurocognitive functioning was also evaluated.

RESULTS: Both groups showed comparable levels of psychological variables, including fatigue. Compared to CFS subjects, CRF patients had significantly higher hs-CRP levels and a reduced HRV-index. The within-group analyses revealed that the FSS score of the CRF group was significantly related to scores on the HADS-anxiety, HADS-depression, and PSQI scales. In the CFS group, FSS scores were significantly associated with scores on the PSS and the absolute delta, theta, and alpha powers in frontal EEG.

CONCLUSION: Findings indicate that different pathophysiological mechanisms underlie CFS and CRF. Inflammatory marker and HRV may be potential biomarkers for distinguishing two fatigue syndromes and frontal EEG parameters may be quantitative biomarkers for CFS.

Source: Park HY, Jeon HJ, Bang YR, Yoon IY. Multidimensional Comparison of Cancer-Related Fatigue and Chronic Fatigue Syndrome: The Role of Psychophysiological Markers. Psychiatry Investig. 2019 Jan 7. doi: 10.30773/pi.2018.10.26. [Epub ahead of print] https://www.ncbi.nlm.nih.gov/pubmed/30605994

Prospective Biomarkers from Plasma Metabolomics of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Implicate Redox Imbalance in Disease Symptomatology

Abstract:

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a disease of enigmatic origin with no established cure. Its constellation of symptoms has silently ruined the lives of millions of people around the world. A plethora of hypotheses have been vainly investigated over the past few decades, so that the biological basis of this debilitating condition remains a mystery.

In this study, we investigate whether there is a disturbance in homeostasis of metabolic networks in the plasma of a female 32-patient cohort compared to 19 healthy female controls. Extensive analysis of the 832-metabolite dataset generated by Metabolon®, covering eight biological classes, generated important insight into metabolic disruptions that occur in ME/CFS.

We report on 14 metabolites with differences in abundance, allowing us to develop a theory of broad redox imbalance in ME/CFS patients, which is consistent with findings of prior work in the ME/CFS field. Moreover, exploration of enrichment analysis using www.MetaboAnalyst.ca provides information concerning similarities between metabolite disruptions in ME/CFS and those that occur in other diseases, while its biomarker analysis unit yielded prospective plasma biomarkers for ME/CFS. This work contributes key elements to the development of ME/CFS diagnostics, a crucial step required for discovering a therapy for any disease of unknown origin.

Source:  Arnaud Germain, David Ruppert , Susan M. Levine  and Maureen R. Hanson. Prospective Biomarkers from Plasma Metabolomics of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Implicate Redox Imbalance in Disease Symptomatology.  Metabolites 20188(4), 90; doi:10.3390/metabo8040090 https://www.mdpi.com/2218-1989/8/4/90/htm (Full article)

Evaluation of four clinical laboratory parameters for the diagnosis of myalgic encephalomyelitis

Abstract:

Background: Myalgic encephalomyelitis (ME) is a complex and debilitating disease that often initially presents with flu-like symptoms, accompanied by incapacitating fatigue. Currently, there are no objective biomarkers or laboratory tests that can be used to unequivocally diagnosis ME; therefore, a diagnosis is made when a patient meets series of a costly and subjective inclusion and exclusion criteria. The purpose of the present study was to evaluate the utility of four clinical parameters in diagnosing ME.

Methods: In the present study, we utilized logistic regression and classification and regression tree analysis to conduct a retrospective investigation of four clinical laboratory in 140 ME cases and 140 healthy controls.

Results: Correlations between the covariates ranged between [− 0.26, 0.61]. The best model included the serum levels of the soluble form of CD14 (sCD14), serum levels of prostaglandin E2 (PGE2), and serum levels of interleukin 8, with coefficients 0.002, 0.249, and 0.005, respectively, and p-values of 3 × 10−7, 1 × 10−5, and 3 × 10−3, respectively.

Conclusions: Our findings show that these parameters may help physicians in their diagnosis of ME and may additionally shed light on the pathophysiology of this disease.

© The Author(s) 2018

Source: Kenny L. De Meirleir, Tatjana Mijatovic, Krishnamurthy Subramanian, Karen A. Schlauch and Vincent C. Lombardi. Evaluation of four clinical laboratory parameters for the diagnosis of myalgic encephalomyelitis. Journal of Translational Medicine201816:322
https://doi.org/10.1186/s12967-018-1696-z Received: 1 September 2018, Accepted: 14 November 2018, Published: 21 November 2018 https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-018-1696-z (Full article)

Erythrocyte Deformability As a Potential Biomarker for Chronic Fatigue Syndrome

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is arguably the last major disease we know almost nothing about. It is a multi-systemic illness of unknown etiology affecting millions of individuals worldwide, with the capacity to persist for several years. ME/CFS is characterized by disabling fatigue of at least 6 months, accompanied serious fatigue and musculoskeletal pain, in addition to impaired short-term memory or concentration, and unrefreshing sleep or extended post-exertional. While the etiology of the disease is still debated, evidence suggest oxidative damage to immune and hematological systems as one of the pathophysiological mechanisms of the disease. Erythrocytes are potent scavengers of oxidative stress, and their shape changes appreciably in response to oxidative stress and certain inflammatory conditions including obesity and diabetes. The shape of erythrocytes change from biconcave discoid to an ellipsoid due shear flow in microcapillaries that provides a larger specific surface area-to-volume ratio for optimal microvascular perfusion and tissue oxygenation establishing the importance not only of total hematocrit but also of the capacity for large deformations in physiology. Clinically, ME/CFS patients show normal arterial oxygen saturation but nothing much is known about microvascular perfusion. In this work, we tested the hypothesis that the erythrocyte deformability in ME/CFS is adversely affected, using a combination of biophysical and biochemical techniques.

We tested the deformability of RBCs using a high-throughput microfluidic device which mimics blood flow through microcapillaries. We perfused RBCs (suspension in plasma) from ME/CFS patients and from age and sex matched healthy controls (n=9 pairs of donors) through a high-throughput microfluidic platform of 5µm width and 3-5 µm height. We recorded the movement of the cells at high speed (4000 fps), followed by image analysis to assess the following parameters: entry time (time required by the cells to completely enter the test channels), average transit velocity (velocity of the cells inside the test channels) and elongation index (ratio of the major diameter before and after deformation in the test channel). We observed that RBCs from ME/CFS patients had higher entry time (~12%, p<0.0001), lower average transit velocity (~17%, p<0.0001) and lower elongation index (~14%, p<0.0001) as compared to RBCs from healthy controls. Taken together, this data shows that RBCs from ME/CFS patients have reduced deformability. To corroborate our findings, we also measured the erythrocyte sedimentation rate (ESR) for these donors which show that the RBCs from ME/CFS patients had lower (~40%, p<0.01) sedimentation rates.

To understand the basis for differences in deformability, we investigated the changes in the fluidity of the membrane using a lateral diffusion assay using pyrenedecanoic acid (PDA), and observed that RBCs from ME/CFS patients have lower membrane fluidity (~30%, p<0.01). Apart from the fluidity, Zeta potential measurements showed that ME/CFS patients had lower net negative surface charge on the RBC plasma membrane (~18%, p<0.0001). Higher levels of reactive oxygen species (ROS) in RBCs from ME/CFS patients (~30%, p<0.008) were also observed, as compared to healthy controls. Using scanning electron microscopy (SEM), we also observed changes in RBC morphology between ME/CFS patients and healthy controls (presence of different morphological subclasses like biconcave disc, leptocyte, acanthocyte and burr cells; area and aspect ratio; levels of RBC aggregation). Despite these changes in RBC physiology, the hemoglobin levels remained comparable between healthy donors and ME/CFS patients. Finally, preliminary studies show that RBCs from recovering ME/CFS patients do not show such differences in cellular physiology, suggesting a connection between RBC deformability and disease severity.

Taken together, our data demonstrates that the significant decrease in deformability of RBCs from ME/CFS patients may have origins in oxidative stress, and suggests that altered microvascular perfusion can be a possible cause for ME/CFS symptoms. Our data also suggests that RBC deformability may serve as a potential biomarker for ME/CFS, albeit further studies are necessary for non-specific classification of the disease.

SourceSaha, A. K., Schmidt, B. R., Wilhelmy, J., Nguyen, V., Do, J., Suja, V. C., Nemat-Gorgani, M., Ramasubramanian, A. K., & Davis, R. W. (2018).Erythrocyte Deformability As a Potential Biomarker for Chronic Fatigue SyndromeBlood, 132(Suppl 1)4874Accessed November 28, 2018. https://doi.org/10.1182/blood-2018-99-117260.