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