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

Abstract

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.

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Data availability

The clinical details on the patients, as well as the full complement of NMR metabolomics data, are available in the Supplementary Information of (Malatji et al. 2017).

Abbreviations

2-D-3,5-DHPL:

2-Deoxy-3,5-dihydroxypentanoic lactone

2,3,4-Trihydroxy-butyl-L:

2,3,4-Trihydroxybutyl-lactone

4-HBA:

4-Hydroxybutyric acid

ACR:

American College of Rheumatology

ADP:

Adenosine-diphosphate

ATP:

Adenosine-triphosphate

B–F:

Bonferroni–Holm test

BSTFA:

N,O-bis-(trimethylsilyl)trifluoraceteamine

CF:

Group of first-degree relatives of the patients

CN:

Group of healthy young subjects

CO:

Group of age-matched subjects but unrelated to the patients

CNS:

Central nervous system

EI and HP:

A general and a histidine-containing cytoplasmic phosphor-carrier bacterial protein system

EII-AT, EII-BT and EII-CT:

Tagatose-specific B. licheniformis multi-domain membrane proteins

EC:

Enzyme Commission number

ES:

Effect size

FC:

Fold change

FIQR:

Fibromyalgia impact questionnaire

FM:

Fibromyalgia

FMS:

Fibromyalgia syndrome

FPS:

Functional pain syndromes

G:

Galactonic acid-lactone

GC–MS:

Gas chromatographic–mass spectrometric

H:

2-Hydroxy-glutaric acid

HMDB:

Human metabolome database

IBS:

Irritable bowel syndrome

IHCQ:

In-house clinical questionnaire

M:

Malic acid

MW:

Mann–Whitney test

NIST:

National Institute of Standards and Technology

1H-NMR:

Proton nuclear magnetic resonance

NTeMBI:

Nuclear Technologies in Medicine and Biosciences Initiative

NWU:

North-West University

~P:

High-energy phosphate

PC:

Principal component

PCA:

Principal components analysis

PLS-DA:

Partial least squares discriminant analysis

PTS:

Phosphoenolpyruvate:carbohydrate phosphotransferase system

Q2:

Predictive ability parameter

R2:

Goodness-of-fit parameter

SIBO:

Small intestinal bacterial over-growth

Tag-1P:

Tagatose-1-phosphate

Tag-6P:

Tagatose-6-phosphate

TagK:

Tagatose-1-phosphate kinase

TMCS:

Trimethylchlorosilane

TPs:

Tender-points

VIP:

Variable important in projection

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Acknowledgements

Research funding for this project was provided by the Technological Innovation Agency (TIA) of the South African Department of Science and Technology (DST) and from the Nuclear Technologies in Medicine and the Biosciences Initiative (NTeMBI) of the Nuclear Energy Corporation of South Africa (NECSA). BM received a postgraduate bursary from the National Research Foundation (NRF) of South Africa.

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Authors

Contributions

This investigation required a multidisciplinary approach and the inputs of all authors were essential to produce the concept and final manuscript. CR and HM defined the aim of the study. The urine samples from the FMS patients and age-matched and family-related controls were provided by HM, who also performed all relevant clinical aspects, and acted as assistant promoter to BM. CR developed the experimental design, acted as the promoter for BM and arranged with HM for ethical approval for the study and for the collection of samples from the young controls. BM conducted all experimental analyses and compiled the clinical information provided by HM. LJM gave guidance and assessment on GC–MS data generation and analyses. RW was responsible for critical evaluation of the analytical aspects of the clinical chemistry data and for their interpretation. MvR performed all the statistical analyses. SM was responsible for coordination and integration of inputs from the authors who contributed to the manuscript as presented here.

Corresponding author

Correspondence to Shayne Mason.

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The authors declare that there are no competing interests regarding the publication of this paper.

Ethical approval

Ethical approval for the study was obtained via a consortium under the Nuclear Technologies in Medicine and Biosciences Initiative (NTeMBI) of South Africa and ethical approval by Pharma Ethics Pty, Ltd (Reference number 11064365). Pharma Ethics confirmed the following: “The study has been accepted as complying to the Ethics Standards for Clinical Research with a new drug in participants based on FDA, ICH GCP and the Declaration of Helsinki guidelines. The Ethics Committee (IRB) granting this APPROVAL is in compliance with the Guidelines for Good Practice in the Conduct of Clinical Trials in Human Participants in South Africa (2006), ICH Harmonised Tripartite Guidelines E6: Note: for the Guidance in Good Clinical Practice (CPMP/ICH/135/95) and FDA Code of Federal Regulation Part 50, 56 and 312.” Informed consent was obtained from all the participants in this study by means of a voluntarily completed consent form, included in the SI.

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Malatji, B.G., Mason, S., Mienie, L.J. et al. The GC–MS metabolomics signature in patients with fibromyalgia syndrome directs to dysbiosis as an aspect contributing factor of FMS pathophysiology. Metabolomics 15, 54 (2019). https://doi.org/10.1007/s11306-019-1513-6

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Keywords

  • Fibromyalgia syndrome (FMS)
  • Gas chromatography–mass spectrometry (GC–MS)
  • Dysbiosis
  • Carbohydrate
  • Pain
  • Biomarkers