Tag: metabolomics

Insights into Metabolite Diagnostic Biomarkers for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a persistent and unexplained pathological state characterized by exertional and severely debilitating fatigue, with/without infectious or neuropsychiatric symptoms, and with a minimum duration of 6 consecutive months. Its pathogenesis is not fully understood. There are no firmly established diagnostic biomarkers or treatment, due to incomplete understanding of the etiology of ME/CFS and diagnostic uncertainty. Establishing a biomarker for the objective diagnosis is urgently needed to treat a lot of patients. Recently, research on ME/CFS using metabolome analysis methods has been increasing. Here, we overview recent findings concerning the metabolic features in patients with ME/CFS and the animal models which contribute to the development of diagnostic biomarkers for ME/CFS and its treatment. In addition, we discuss future perspectives of studies on ME/CFS.

Source: Yamano E, Watanabe Y, Kataoka Y. Insights into Metabolite Diagnostic Biomarkers for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. Int J Mol Sci. 2021 Mar 26;22(7):3423. doi: 10.3390/ijms22073423. PMID: 33810365. https://pubmed.ncbi.nlm.nih.gov/33810365/

A systematic review of metabolomic dysregulation in Chronic Fatigue Syndrome/Myalgic Encephalomyelitis/Systemic Exertion Intolerance Disease

Abstract:

BACKGROUND: Chronic Fatigue Syndrome/Myalgic Encephalomyelitis/Systemic Exertion Intolerance Disease (CFS/ME/SEID) is a complex illness that has an unknown aetiology. It has been proposed that metabolomics may contribute to the illness pathogenesis of CFS/ME/SEID. In metabolomics, the systematic identification of measurable changes in small molecule metabolite products have been identified in cases of both monogenic and heterogenic diseases. Therefore, the aim of this systematic review was to evaluate if there is any evidence of metabolomics contributing to the pathogenesis of CFS/ME/SEID.

METHODS: PubMed, Scopus, EBSCOHost (Medline) and EMBASE were searched using medical subject headings terms for Chronic Fatigue Syndrome, metabolomics and metabolome to source papers published from 1994 to 2020. Inclusion and exclusion criteria were used to identify studies reporting on metabolites measured in blood and urine samples from CFS/ME/SEID patients compared with healthy controls. The Joanna Briggs Institute Checklist was used to complete a quality assessment for all the studies included in this review.

RESULTS: 11 observational case control studies met the inclusion criteria for this review. The primary outcome of metabolite measurement in blood samples of CFS/ME/SEID patients was reported in ten studies. The secondary outcome of urine metabolites was measured in three of the included studies. No studies were excluded from this review based on a low-quality assessment score, however there was inconsistency in the scientific research design of the included studies. Metabolites associated with the amino acid pathway were the most commonly impaired with significant results in seven out of the 10 studies. However, no specific metabolite was consistently impaired across all of the studies. Urine metabolite results were also inconsistent.

CONCLUSION: The findings of this systematic review reports that a lack of consistency with scientific research design provides little evidence for metabolomics to be clearly defined as a contributing factor to the pathogenesis of CFS/ME/SEID. Further research using the same CFS/ME/SEID diagnostic criteria, metabolite analysis method and control of the confounding factors that influence metabolite levels are required.

Source: Huth TK, Eaton-Fitch N, Staines D, Marshall-Gradisnik S. A systematic review of metabolomic dysregulation in Chronic Fatigue Syndrome/Myalgic Encephalomyelitis/Systemic Exertion Intolerance Disease (CFS/ME/SEID). J Transl Med. 2020 May 13;18(1):198. doi: 10.1186/s12967-020-02356-2. https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-020-02356-2 (Full text)

Comprehensive Circulatory Metabolomics in ME/CFS Reveals Disrupted Metabolism of Acyl Lipids and Steroids

Abstract:

The latest worldwide prevalence rate projects that over 65 million patients suffer from myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), an illness with known effects on the functioning of the immune and nervous systems. We performed an extensive metabolomics analysis on the plasma of 52 female subjects, equally sampled between controls and ME/CFS patients, which delivered data for about 1750 blood compounds spanning 20 super-pathways, subdivided into 113 sub-pathways.

Statistical analysis combined with pathway enrichment analysis points to a few disrupted metabolic pathways containing many unexplored compounds. The most intriguing finding concerns acyl cholines, belonging to the fatty acid metabolism sub-pathway of lipids, for which all compounds are consistently reduced in two distinct ME/CFS patient cohorts. We compiled the extremely limited knowledge about these compounds and regard them as promising in the quest to explain many of the ME/CFS symptoms.

Another class of lipids with far-reaching activity on virtually all organ systems are steroids; androgenic, progestin, and corticosteroids are broadly reduced in our patient cohort. We also report on lower dipeptides and elevated sphingolipids abundance in patients compared to controls. Disturbances in the metabolism of many of these molecules can be linked to the profound organ system symptoms endured by ME/CFS patients.

Source: Germain A, Barupal DK, Levine SM, Hanson MR. Comprehensive Circulatory Metabolomics in ME/CFS Reveals Disrupted Metabolism of Acyl Lipids and Steroids. Metabolites. 2020 Jan 14;10(1). pii: E34. doi: 10.3390/metabo10010034. https://www.ncbi.nlm.nih.gov/pubmed/31947545

A laboratory approach for characterizing chronic fatigue: what does metabolomics tell us?

Abstract:

INTRODUCTION: Manifestations of fatigue range from chronic fatigue up to a severe syndrome and myalgic encephalomyelitis. Fatigue grossly affects the functional status and quality of life of affected individuals, prompting the World Health Organization to recognize it as a chronic non-communicable condition.

OBJECTIVES: Here, we explore the potential of urinary metabolite information to complement clinical criteria of fatigue, providing an avenue towards an objective measure of fatigue in patients presenting with the full spectrum of fatigue levels.

METHODS: The experimental group consisted of 578 chronic fatigue female patients. The measurement design was composed of (1) existing clinical fatigue scales, (2) a hepatic detoxification challenge test, and (3) untargeted proton nuclear magnetic resonance (1H-NMR) procedure to generate metabolomics data. Data analysed via an in-house Matlab script that combines functions from a Statistics and a PLS Toolbox.

RESULTS: Multivariate analysis of the original 459 profiled 1H-NMR bins for the low (control) and high (patient) fatigue groups indicated complete separation following the detoxification experimental challenge. Important bins identified from the 1H-NMR spectra provided quantitative metabolite information on the detoxification challenge for the fatigue groups.

CONCLUSIONS: Untargeted 1H-NMR metabolomics proved its applicability as a global profiling tool to reveal the impact of toxicological interventions in chronic fatigue patients. No clear potential biomarker emerged from this study, but the quantitative profile of the phase II biotransformation products provide a practical visible effect directing to up-regulation of crucial phase II enzyme systems in the high fatigue group in response to a high xenobiotic-load.

Source: Erasmus E, Mason S, van Reenen M, Steffens FE, Vorster BC, Reinecke CJ. A laboratory approach for characterizing chronic fatigue: what does metabolomics tell us? Metabolomics. 2019 Nov 27;15(12):158. doi: 10.1007/s11306-019-1620-4. https://www.ncbi.nlm.nih.gov/pubmed/31776682

Insights from metabolites get us closer to a test for chronic fatigue syndrome

Press Release: Columbia University’s Mailman School of Public Health, July 9, 2018. A study led by researchers at the Center for Infection and Immunity (CII) at Columbia University’s Mailman School of Public Health has identified a constellation of metabolites related to myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Combining this data with data from an earlier microbiome study, the researchers now report they can predict whether or not someone has the disorder with a confidence of 84 percent.

The research team analyzed blood samples provided by 50 patients with ME/CFS and 50 controls matched for sex and age who were recruited at four clinical sites across the United States. Using mass spectrometry, a laboratory technique used to identify molecules by measuring their mass, the scientists found 562 metabolites — microscopic byproducts of human and microbial processes such as sugar, fat, and protein molecules. They excluded molecules related to antidepressants and other drugs patients might be taking.

Their metabolomics analysis, among the most detailed and meticulous to date, uncovered altered levels of metabolites, including choline, carnitine and several complex lipids present in patients with ME/CFS. The altered metabolites suggest dysfunction of the mitochrondria, the cellular powerplant, a finding in line with those reported by other research teams. Uniquely, the CII study also reports a second distinct pattern of metabolites in patients with ME/CFS and irritable bowel syndrome (IBS), matching earlier findings from their 2017 fecal microbiome study. Half of the patients with ME/CFS also had IBS.

When the researchers combined biomarkers from both the microbiome study and the new metabolome study, they reported a .836 predictive score, indicating an 84 percent certainty as to the presence of ME/CFS — better than with either study alone.

“This is a strong predictive model that suggests we’re getting close to the point where we’ll have lab tests that will allow us to say with a high level of certainty who has this disorder,” says first author Dorottya Nagy-Szakal, MD, PhD, a researcher at CII.

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Insights into myalgic encephalomyelitis/chronic fatigue syndrome phenotypes through comprehensive metabolomics

Abstract:

The pathogenesis of ME/CFS, a disease characterized by fatigue, cognitive dysfunction, sleep disturbances, orthostatic intolerance, fever, irritable bowel syndrome (IBS), and lymphadenopathy, is poorly understood.

We report biomarker discovery and topological analysis of plasma metabolomic, fecal bacterial metagenomic, and clinical data from 50 ME/CFS patients and 50 healthy controls. We confirm reports of altered plasma levels of choline, carnitine and complex lipid metabolites and demonstrate that patients with ME/CFS and IBS have increased plasma levels of ceramide.

Integration of fecal metagenomic and plasma metabolomic data resulted in a stronger predictive model of ME/CFS (cross-validated AUC = 0.836) than either metagenomic (cross-validated AUC = 0.745) or metabolomic (cross-validated AUC = 0.820) analysis alone. Our findings may provide insights into the pathogenesis of ME/CFS and its subtypes and suggest pathways for the development of diagnostic and therapeutic strategies.

Source: Dorottya Nagy-Szakal, Dinesh K. Barupal, Bohyun Lee, Xiaoyu Che, Brent L. Williams, Ellie J. R. Kahn, Joy E. Ukaigwe, Lucinda Bateman, Nancy G. Klimas, Anthony L. Komaroff, Susan Levine, Jose G. Montoya, Daniel L. Peterson, Bruce Levin, Mady Hornig, Oliver Fiehn & W. Ian Lipkin . Insights into myalgic encephalomyelitis/chronic fatigue syndrome phenotypes through comprehensive metabolomics. Scientific Reports, volume 8, Article number: 10056 (2018) https://www.nature.com/articles/s41598-018-28477-9 (Full article)

A Glimpse into Dr. Ron Davis’ Talk in London

From Open Medicine Foundation.
June 1, 2018

Dear Friends,

I prepared this statement for Ashley Haugen to read yesterday at the Western Massachusetts  Department of Public Health screening of Unrest. This is new information from the Severely ill Patient Study (SIPS) that I also presented in London:

“We have made considerable progress in analyzing the data from the severely ill patient study. This has taken some time because we have only had one bioinformatic scientist analyzing the massive amount of data.

We have found that there are a considerable number of mutations that are more common in ME/CFS patients than in healthy controls. This would suggest that these mutations make a patient more susceptible to having ME/CFS. It could also indicate that some of the mutations are responsible for the severity of the patients we studied. We also see a large number of metabolomic changes that have been previously seen in less severe patients. These metabolomic differences between healthy controls and our severely ill patients are often much bigger than in studies with less severe patients. A more detailed analysis of this data may aid us in developing treatments.

One area we are currently studying using the genetic and metabolomic data is the possibility there may be one or more metabolic traps. This is a metabolic state that a patient can develop, possibly caused by physical stress such as infection. Once a patient is in this state they cannot easily get out by rest.

We are conducting system biology and pathway analysis that shows that a metabolic trap is possible, and that some of the observed mutations make it more likely. If this is the case we should be able to push the patients out of this state by a specific metabolic intervention. We are very hopeful that this could be a one time treatment, take only a few days, and be relatively inexpensive.”

Sending greetings from London,

Ronald W. Davis, PhD
Director, OMF ME/CFS Scientific Advisory Board
Director, Stanford Genome Technology Center

New Diagnostic Biomarkers for Chronic Fatigue Syndrome

Abstract:

Chronic fatigue syndrome (CFS) is a persistent and unexplained pathological state characterized by exertional and severely debilitating fatigue, with/without symptoms of infection or neuropsychiatric symptoms, and with a minimum duration of 6 consecutive months. The pathogenesis of CFS is not fully understood. There are no firmly established diagnostic biomarkers or treatment, due to incomplete understanding of the etiology of CFS and diagnostic uncertainty. We performed comprehensive metabolomic analyses of blood samples obtained from patients with CFS and healthy controls to establish an objective diagnosis of CFS. Here, we review previous findings concerning the immune, endocrine, and metabolic system in animal models for CFS and the patients, and present our results which may contribute to the development of a diagnostic biomarker for CFS.

Source: Yamano E, Kataoka Y. New Diagnostic Biomarkers for Chronic Fatigue Syndrome. Brain Nerve. 2018 Jan;70(1):27-34. doi: 10.11477/mf.1416200946. [Article in Japanese]  https://www.ncbi.nlm.nih.gov/pubmed/29348372

A robust, single-injection method for targeted, broad-spectrum plasma metabolomics

Abstract:

BACKGROUND: Metabolomics is a powerful emerging technology for studying the systems biology and chemistry of health and disease. Current targeted methods are often limited by the number of analytes that can be measured, and/or require multiple injections.

METHODS: We developed a single-injection, targeted broad-spectrum plasma metabolomic method on a SCIEX Qtrap 5500 LC-ESI-MS/MS platform. Analytical validation was conducted for the reproducibility, linearity, carryover and blood collection tube effects. The method was also clinically validated for its potential utility in the diagnosis of chronic fatigue syndrome (CFS) using a cohort of 22 males CFS and 18 age- and sex-matched controls.

RESULTS: Optimization of LC conditions and MS/MS parameters enabled the measurement of 610 key metabolites from 63 biochemical pathways and 95 stable isotope standards in a 45-minute HILIC method using a single injection without sacrificing sensitivity. The total imprecision (CVtotal) of peak area was 12% for both the control and CFS pools. The 8 metabolites selected in our previous study (PMID: 27573827) performed well in a clinical validation analysis even when the case and control samples were analyzed 1.5 years later on a different instrument by a different investigator, yielding a diagnostic accuracy of 95% (95% CI 85-100%) measured by the area under the ROC curve.

CONCLUSIONS: A reliable and reproducible, broad-spectrum, targeted metabolomic method was developed, capable of measuring over 600 metabolites in plasma in a single injection. The method might be a useful tool in helping the diagnosis of CFS or other complex diseases.

Source: Li K, Naviaux JC, Bright AT, Wang L, Naviaux RK. A robust, single-injection method for targeted, broad-spectrum plasma metabolomics. Metabolomics. 2017;13(10):122. doi: 10.1007/s11306-017-1264-1. Epub 2017 Sep 4. https://www.ncbi.nlm.nih.gov/pubmed/28943831

A diagnostic biomarker profile for fibromyalgia syndrome based on an NMR metabolomics study of selected patients and controls

Abstract:

BACKGROUND: Fibromyalgia syndrome (FMS) is a chronic pain syndrome. A plausible pathogenesis of the disease is uncertain and the pursuit of measurable biomarkers for objective identification of affected individuals is a continuing endeavour in FMS research. Our objective was to perform an explorative metabolomics study (1) to elucidate the global urinary metabolite profile of patients suffering from FMS, and (2) to explore the potential of this metabolite information to augment existing medical practice in diagnosing the disease.

METHODS: We selected patients with a medical history of persistent FMS (n = 18), who described their recent state of the disease through the Fibromyalgia Impact Questionnaire (FIQR) and an in-house clinical questionnaire (IHCQ). Three control groups were used: first-generation family members of the patients (n = 11), age-related individuals without any indications of FMS or related conditions (n = 10), and healthy young (18-22 years) individuals (n = 20). All subjects were female and the biofluid under investigation was urine. Correlation analysis of the FIQR showed the FMS patients represented a well-defined disease group for this metabolomics study. Spectral analyses of urine were conducted using a 500 MHz 1H nuclear magnetic resonance (NMR) spectrometer; data processing and analyses were performed using Matlab, R, SPSS and SAS software.

RESULTS AND DISCUSSION: Unsupervised and supervised multivariate analyses distinguished all three control groups and the FMS patients, and significant increases in metabolites related to the gut microbiome (hippuric, succinic and lactic acids) were observed. We have developed an algorithm for the diagnosis of FMS consisting of three metabolites – succinic acid, taurine and creatine – that have a good level of diagnostic accuracy (Receiver Operating Characteristic (ROC) analysis – area under the curve 90%) and on the pain and fatigue symptoms for the selected FMS patient group.

CONCLUSION: Our data and comparative analyses indicated an altered metabolic profile of patients with FMS, analytically detectable within their urine. Validation studies may substantiate urinary metabolites to supplement information from medical assessment, tender-point measurements and FIQR questionnaires for an improved objective diagnosis of FMS.

Source: Malatji BG, Meyer H, Mason S, Engelke UFH, Wevers RA, van Reenen M, Reinecke CJ. A diagnostic biomarker profile for fibromyalgia syndrome based on an NMR metabolomics study of selected patients and controls. BMC Neurol. 2017 May 11;17(1):88. doi: 10.1186/s12883-017-0863-9. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5426044/ (Full article)