Tag: phenylalanine

Urine Metabolite Analysis to Identify Pathomechanisms of Long COVID: A Pilot Study

Abstract:

Background: Around 10% of people who had COVID-9 infection suffer from persistent symptoms such as fatigue, dyspnoea, chest pain, arthralgia/myalgia, sleep disturbances, cognitive dysfunction and impairment of mental health. Different underlying pathomechanisms appear to be involved, in particular inflammation, alterations in amino acid metabolism, autonomic dysfunction and gut dysbiosis.

Aim: As routine tests are often inconspicuous in patients with Long COVID (LC), similarly to patients suffering from myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), accessible biomarkers indicating dysregulation of specific pathways are urgently needed to identify underlying pathomechanisms and enable personalized medicine treatment. Within this pilot study we aimed to proof traceability of altered metabolism by urine analysis.

Patients and methods: Urine metabolome analyses were performed to investigate the metabolic signature of patients with LC (n = 25; 20 women, 5 men) in comparison to healthy controls (Ctrl, n = 8; 7 women, 1 man) and individuals with ME/CFS (n = 8; 2 women, 6 men). Concentrations of neurotransmitter precursors tryptophan, phenylalanine and their downstream metabolites, as well as their association with symptoms (fatigue, anxiety and depression) in the patients were examined.

Results and conclusion: Phenylalanine levels were significantly lower in both the LC and ME/CFS patient groups when compared to the Ctrl group. In many LC patients, the concentrations of downstream metabolites of tryptophan and tyrosine, such as serotonin, dopamine and catecholamines, deviated from the reference ranges. Several symptoms (sleep disturbance, pain or autonomic dysfunction) were associated with certain metabolites. Patients experiencing fatigue had lower levels of kynurenine, phenylalanine and a reduced kynurenine to tryptophan ratio (Kyn/Trp). Lower concentrations of gamma-aminobutyric acid (GABA) and higher activity of kynurenine 3-monooxygenase (KMO) were observed in patients with anxiety.

Conclusively, our results suggest that amino acid metabolism and neurotransmitter synthesis is disturbed in patients with LC and ME/CFS. The identified metabolites and their associated dysregulations could serve as potential biomarkers for elucidating underlying pathomechanisms thus enabling personalized treatment strategies for these patient populations.

Source: Taenzer M, Löffler-Ragg J, Schroll A, Monfort-Lanzas P, Engl S, Weiss G, Brigo N, Kurz K. Urine Metabolite Analysis to Identify Pathomechanisms of Long COVID: A Pilot Study. Int J Tryptophan Res. 2023 Dec 22;16:11786469231220781. doi: 10.1177/11786469231220781. PMID: 38144169; PMCID: PMC10748708. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10748708/ (Full text)

Developing a blood cell-based diagnostic test for myalgic encephalomyelitis/chronic fatigue syndrome using peripheral blood mononuclear cells

Abstract:

A blood-based diagnostic test for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and multiple sclerosis (MS) would be of great value in both conditions, facilitating more accurate and earlier diagnosis, helping with current treatment delivery, and supporting the development of new therapeutics.

Here we use Raman micro-spectroscopy to examine differences between the spectral profiles of blood cells of ME/CFS, MS and healthy controls.

We were able to discriminate the three groups using ensemble classification models with high levels of accuracy (91%) with the additional ability to distinguish mild, moderate, and severe ME/CFS patients from each other (84%).

To our knowledge, this is the first research using Raman micro-spectroscopy to discriminate specific subgroups of ME/CFS patients on the basis of their symptom severity. Specific Raman peaks linked with the different disease types with the potential in further investigations to provide insights into biological changes associated with the different conditions.

Source: Jiabao Xu, Tiffany Lodge,  Caroline Claire Kingdon, James W L Strong, John Maclennan, Eliana Lacerda, Slawomir Kujawski, Pawel Zalewski, Wei Huang, Karl J. Morten. Developing a blood cell-based diagnostic test for myalgic encephalomyelitis/chronic fatigue syndrome using peripheral blood mononuclear cells. medRxiv [Preprint] medRxiv 2023.03.18.23286575; doi: https://doi.org/10.1101/2023.03.18.23286575 https://www.medrxiv.org/content/10.1101/2023.03.18.23286575v1.full-text (Full text)

A new approach to find biomarkers in chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) by single-cell Raman micro-spectroscopy

Abstract:

Chronic fatigue syndrome (CFS), also called myalgic encephalomyelitis (ME), is a debilitating disorder characterized by physical and mental exhaustion. Mitochondrial and energetic dysfunction has been investigated in CFS patients due to a hallmark relationship with fatigue, however, no consistent conclusion has yet been achieved.

Single-cell Raman spectra (SCRS) are label-free biochemical profiles, indicating phenotypic fingerprints of single cells. In this study, we applied a new approach using single-cell Raman microspectroscopy (SCRM) to examine 0 cells that lack mitochondrial DNA (mtDNA), and peripheral blood mononuclear cells (PBMCs) from CFS patients and healthy controls.

The experimental results show that Raman bands associated with phenylalanine in 0 cells and CFS patient PBMCs were significantly higher than wild type model and healthy controls. Remarkably, an increase in intensities of Raman phenylalanine bands were also observed in CFS patients. As similar changes were observed in the 0 cell model with a known deficiency in the mitochondrial respiratory chain as well as in CFS patients, our results suggest that the increase in cellular phenylalanine may relate to mitochondrial/energetic dysfunction in both systems.

Interestingly, phenylalanine can be used as a potential biomarker for diagnosis of CFS by SCRM. A machine learning classification model achieved an accuracy rate of 98% correctly assigning Raman spectra to either the CFS group or the control group. SCRM combined with machine learning algorithm therefore has the potential to become a diagnostic tool for CFS.

Source: Jiabao Xu, Michelle Potter, Cara Tomas, Jo Elson, Karl Morten, Joanna Poulton, Ning Wang, Hanqing Jin, Zhaoxu Hou and Wei Huang. A new approach to find biomarkers in chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) by single-cell Raman micro-spectroscopy. Analyst, 22 Aug 2018.  http://pubs.rsc.org/en/Content/ArticleLanding/2018/AN/C8AN01437J#!divAbstract