Urinary electrophoretic profiles from chronic fatigue syndrome and chronic fatigue syndrome/fibromyalgia patients: a pilot study for achieving their normalization

A systematic review and meta-analysis of urinary biomarkers in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS)

BACKGROUND

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a multifactorial illness that affects many body systems including the immune, nervous, endocrine, cardiovascular, and urinary systems. There is currently no universal diagnostic marker or targeted treatment for ME/CFS. Urine is a non-invasive sample that provides biomarkers that may have the potential to be used in a diagnostic capacity for ME/CFS. While there are several studies investigating urine-based biomarkers for ME/CFS, there are no published systematic reviews to summarise existing evidence of these markers. The aim of this systematic review was to compile and appraise literature on urinary-based biomarkers in ME/CFS patients compared with healthy controls.

METHODS

Three databases: Embase, PubMed, and Scopus were searched for articles pertaining to urinary biomarkers for ME/CFS compared with healthy controls published between December 1994 to December 2022. The final articles included in this review were determined through application of specific inclusion and exclusion criteria. Quality and bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Case Control Studies. A meta-analysis according to Cochrane guidelines was conducted on select studies, in particular, those that investigate urinary free cortisol levels in ME/CFS patients compared to healthy controls using the program STATA 17.

RESULTS

Twenty-one studies were included in this review. All of the studies investigated urinary-based markers in ME/CFS patients compared with healthy controls. The reported changes in urinary outputs include urinary free cortisol (38.10%), carnitine (28.6%), iodine (4.76%), and the metabolome (42.86%). In most cases, there was minimal overlap in the main outcomes measured across the studies, however, differences in urinary free cortisol between ME/CFS patients and healthy controls were commonly reported. Seven studies investigating urinary free cortisol were included in the meta-analysis. While there were significant differences found in urinary free cortisol levels in ME/CFS patients, there was also substantial heterogeneity across the included studies that makes drawing conclusions difficult.

CONCLUSIONS

There is limited evidence suggesting a consistent and specific potential urinary-based biomarker for ME/CFS. Further investigations using more standardised methodologies and more stringent case criteria may be able to identify pathophysiological differences with diagnostic potential in ME/CFS patients compared with healthy controls.

Scopes of Bioanalytical Chromatography–Mass Spectrometry

The areas of application of modern bioanalytical chromatography–mass spectrometry are so extensive that any attempt to systematize them becomes subjective. It would be more correct to say that there is no such area of biology and medicine where chromatography–mass spectrometry would not find application. This article focuses on the areas of application of this technique that are either relatively new or insufficiently covered in recent reviews. State-of-the-art bioanalytical techniques have become multitargeted in terms of analytes and standardized in terms of matrices. The ability to detect trace concentrations of analytes in the presence of a huge number of biomatrix macrocomponents using chromatography–mass spectrometry is especially important for bioanalytical chemistry. In the target-oriented determination of persistent organic pollutants by chromatography–mass spectrometry, the main problem is the expansion of the list of analytes, including isomers. In the detection of exposures to unstable toxicants, the fragmented adducts of xenobiotics with biomolecules become target biomarkers along with hydrolytic metabolites. The exposome reflects the general exposure of a human being to total xenobiotics and the metabolic status reflects the physiological state of the body. Chromatography–mass spectrometry is a key technique in metabolomics. Metabolomics is currently used to solve the problems of clinical diagnostics and anti-doping control. Biological sample preparation procedures for instrumental analysis are being simplified and developed toward increasing versatility. Proteomic technologies with the use of various versions of mass spectrometry have found application in the development of new methods for diagnosing coronavirus infections.

Is chronic fatigue syndrome the same illness as fibromyalgia: evaluating the 'single syndrome' hypothesis

Chronic fatigue syndrome (CFS) and fibromyalgia (FM) are medically unexplained syndromes that can and often do co-occur. For this reason, some have posited that the two are part of the same somatic syndrome--examples of symptom amplification. This hypothesis would suggest that few differences exist between the two syndromes. To evaluate this interpretation, we have searched the literature for articles comparing CFS to FM, reviewing only those articles which report differences between the two. This review presents data showing differences across a number of parameters--implying that the underlying pathophysiology in CFS may differ from that of FM. We hope that our review encourages other groups to look for additional differences between CFS and FM. By continuing to preserve the unique illness definitions of the two syndromes, clinicians will be able to better identify, understand and provide treatment for these individuals.

Capillary electrophoresis as a metabolomics tool for non-targeted fingerprinting of biological samples

Metabolomics, understood as a data driven strategy trying to find markers of a situation under study without a priori hypothesis, has rapidly caught the attention and evolved from the simple pattern recognition strategy, which was a great innovation at its origins, to the interest for the final identification of markers responsible for class separation, i.e., from data to knowledge. Due to differences in physico-chemical properties and concentrations of the metabolites, but also due to differences in matrix properties, cross-platform approaches are proving to increase the capability of information. Once more techniques do not compete. This is the scene where capillary electrophoresis (CE) has its niche to provide information mainly on polar or ionic compounds in biological fluids. General advantages and disadvantages of CE for sample fingerprinting will be discussed and methods will be classified depending on the detection system (UV or MS) as this strongly affects all the conditions. Recent developments will be presented in different biological fluids, although urine is without a doubt the preferred sample for CE analysis.

Metabonomics study of urine and plasma in depression and excess fatigue rats by ultra fast liquid chromatography coupled with ion trap-time of flight mass spectrometry

A novel metabonomic method based on fast liquid chromatography coupled with ion trap-time of flight mass spectrometry (UFLC/MS-IT-TOF) was applied to study the metabolic changes of plasma and urine in depression and excess fatigue rats. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were applied for classifying the depression, excess fatigue and the control rats. Metabolites which were important for the classification in the three groups of rats were selected as potential biomarkers and identified by MS(n) information achieved from UFLC/MS-IT-TOF analysis. Spermine, propionylcarnitine, butyrylcarnitine, phenylalanine, lysophosphatidylcholine (LPC) C14:0 and LPC C18:2 were down-regulated, methyl-hippuric acid and chenodeoxycholic acid (CDCA) were up-regulated significantly in plasma of the excess fatigue rats. Spermine, leucine, propionylcarnitine, and butyrylcarnitine decreased, hippuric acid, methyl-hippuric acid, cholic acid, CDCA and LPC C16:0 increased markedly in plasma of the depression rats. Ethyl N2-acetyl-L-argininate and N-methyl-2-pyridone-5-carboxamide (2-PY) (or N-methyl-4-pyridone-3-carboxamide (4-PY)) were down-regulated, leucylproline and pantothenic acid were up-regulated remarkably both in urine of depression and excess fatigue rats. The concentration of kynurenic acid and N2-succinyl-L-ornithine was low in urine of depression rats compared with control rats. Based on the data, correlation networks for depression and excess fatigue rats revealed the abnormality of nicotinate and nicotinamide metabolism, arginine metabolism, cholesterol metabolism, tryptophan metabolism and kynurenine metabolism in depression rats, and in excess fatigue rat alterations of energy metabolism, nicotinate and nicotinamide metabolism and lecithin metabolism. Our results provide novel insights in the complex metabolic mechanisms occurring in depression and excess fatigue rats.

Evaluation of different warping methods for the analysis of CE profiles of urinary nucleosides

Nowadays, numerous metabolite concentrations can readily be determined in a given biological sample by high-throughput analytical methods. However, such raw analytical data comprise noninformative components due to many disturbances normally occurring in the analyses of biological material. To eliminate those unwanted original analytical data components, advanced chemometric data preprocessing methods might be of help. Here, such methods are applied to electrophoretic nucleoside profiles in urine samples of cancer patients and healthy volunteers. In this study, three warping methods: dynamic time warping (DTW), correlation optimized warping (COW), and parametric time warping (PTW) were examined on two sets of electrophoretic data by means of quality of peaks alignment, time of preprocessing, and way of customization. The application of warping methods helped to limit shifting of peaks and enabled differentiation between whole electropherograms of healthy and cancer patients objectively by a principal component analysis (PCA). The evaluation of preprocessed data and raw data by PC analysis confirms differences between the applied warping tools and proves their suitability in metabonomic data interpretation.

Application of metabonomics in drug development

Metabolic profiling (metabonomics/metabolomics) is the untargeted analysis of metabolic composition in a biological sample, and is principally aimed at biomarker discovery. The frequent use of noninvasive biofluid analysis in metabonomics is suited to the clinic and facilitates dynamic monitoring. Analytical protocols for metabolic biomarkers are potentially robust because a metabolite is the same chemical entity irrespective of its origin, facilitating ‘bench-to-bedside’ translational research. Metabonomics can make an impact at several points in the drug-development process: target identification; lead discovery and optimization; preclinical efficacy and safety assessment; mode-of-action and mechanistic toxicology; patient stratification; and clinical pharmacological monitoring. This review describes and exemplifies the latest developments in each of these areas, including the impact of new data and chemical analytical techniques. The future goals for metabonomics are the validation of existing biomarkers, in terms of mechanism and translation to man, together with a focus on characterizing the individual (‘personalized healthcare’).

Increasing conclusiveness of metabonomic studies by chem-informatic preprocessing of capillary electrophoretic data on urinary nucleoside profiles

Nowadays, bioinformatics offers advanced tools and procedures of data mining aimed at finding consistent patterns or systematic relationships between variables. Numerous metabolites concentrations can readily be determined in a given biological system by high-throughput analytical methods. However, such row analytical data comprise noninformative components due to many disturbances normally occurring in analysis of biological samples. To eliminate those unwanted original analytical data components advanced chemometric data preprocessing methods might be of help. Here, such methods are applied to electrophoretic nucleoside profiles in urine samples of cancer patients and healthy volunteers. The electrophoretic nucleoside profiles were obtained under following conditions: 100 mM borate, 72.5 mM phosphate, 160 mM SDS, pH 6.7; 25 kV voltage, 30 degrees C temperature; untreated fused silica capillary 70 cm effective length, 50 microm I.D. Different most advanced preprocessing tools were applied for baseline correction, denoising and alignment of electrophoretic data. That approach was compared to standard procedure of electrophoretic peak integration. The best results of preprocessing were obtained after application of the so-called correlation optimized warping (COW) to align the data. The principal component analysis (PCA) of preprocessed data provides a clearly better consistency of the nucleoside electrophoretic profiles with health status of subjects than PCA of peak areas of original data (without preprocessing).

Micellar electrokinetic chromatographic and capillary zone electrophoretic methods for screening urinary biomarkers of human disorders: a critical review of the state-of-the-art

Human urine plays a central role in clinical diagnostic being one of the most-frequently used body fluid for detection of biological markers. Samples from patients with different diseases display patterns of biomarkers that differ significantly from those obtained from healthy subjects. The availability of fast, reproducible, and easy-to-apply analytical techniques that would allow identification of a large number of these analytes is thus highly desiderable since they may provide detailed information about the progression of a pathological process. From among the variety of methods so far applied for the determination of urinary metabolites, capillary electrophoresis, both in the capillary zone electrophoresis (CZE) and micellar electrokinetic chromatography (MEKC) modes, represents a robust and reliable analytical tool widely used in this area. The aim of the present article is to focus the interest of the reader on recent applications of MEKC and CZE in the field of urinary biomarkers and to discuss advantages and/or limitations of each mode.