KEMREP: A New Qualitative Method for the Assessment of an Analyst’s Ability to Generate a Metabolomics Data Matrix by Gas Chromatography– Mass Spectrometry

The GC-MS metabolomics signature in patients with fibromyalgia syndrome directs to dysbiosis as an aspect contributing factor of FMS pathophysiology

INTRODUCTION

Fibromyalgia syndrome (FMS) is a chronic pain syndrome. Previous analyses of untargeted metabolomics data indicated altered metabolic profile in FMS patients.

OBJECTIVES

We report a semi-targeted explorative metabolomics study on the urinary metabolite profile of FMS patients; exploring the potential of urinary metabolite information to augment existing medical diagnosis.

METHODS

All cases were females. Patients had a medical history of persistent FMS (n = 18). Control groups were first-generation family members of the patients (n = 11), age-related individuals without indications of FMS (n = 10), and healthy, young (18-22 years) individuals (n = 41). The biofluid investigated was early morning urine samples. Data generation was done through gas chromatography-mass spectrometry (GC-MS) analysis and data processing and analyses were performed using Matlab, R, SPSS and SAS software.

RESULTS

Quantitative analysis revealed the presence of 196 metabolites. Unsupervised and supervised multivariate analyses distinguished all three control groups and the FMS patients, which could be related to 14 significantly increased metabolites. These metabolites are associated with energy metabolism, digestion and metabolism of carbohydrates and other host and gut metabolites.

CONCLUSIONS

Overall, urinary metabolite profiles in the FMS patients suggest: (1) energy utilization is a central aspect of this pain disorder, (2) dysbiosis seems to prevail in FMS patients, indicated by disrupted microbiota metabolites, supporting the model that microbiota may alter brain function through the gut-brain axis, with the gut being a gateway to generalized pain, and (3) screening of urine from FMS is an avenue to explore for adding non-invasive clinical information for diagnosis and treatment of FMS.

Tuberculous meningitis in infants and children: Insights from nuclear magnetic resonance metabolomics

Abstract Tuberculous meningitis (TBM) is a prevalent form of central nervous system tuberculosis (CNS-TB) and the most severe common form of bacterial meningitis in infants and children below the age of 13 years, especially in the Western Cape Province of South Africa. Research to identify markers for timely and accurate diagnosis and treatment outcomes remains high on the agenda for TBM, in respect of which the field of metabolomics is as yet largely unexploited. However, the national Department of Science and Technology (DST) recently established several biotechnology platforms at South African institutions, including one for metabolomics hosted at North-West University. We introduce this national platform for nuclear magnetic resonance (NMR) metabolomics by providing an overview of work on TBM. We focus on selected collaborative multidisciplinary approaches to this disease and conclude with the outcomes of an untargeted NMR metabolomics study of cerebrospinal fluid from TBM patients. This study enabled the formulation of a conceptual shuttle representing the unique metabolic plasticity of CNS metabolism towards the energy requirements for the microglia-driven neuroinflammatory responses, of which TBM is one example. From insights generated by this explorative NMR metabolomics investigation, we propose directions for future in-depth research strategies to address this devastating disease. In our view, the timely initiative of the DST, the operational expertise in metabolomics now available and the potential for involving national and international networks in this field of research offers remarkable opportunities for the future of metabolomics in South Africa and for an ever greater understanding of disease mechanisms.