Background: Fibromyalgia is a complex, relatively unknown disease characterised by chronic, widespread musculoskeletal pain. The gut-brain axis connects the gut microbiome with the brain through the enteric nervous system (ENS); its disruption has been associated with psychiatric and gastrointestinal disorders. To gain an insight into the pathogenesis of fibromyalgia and identify diagnostic biomarkers, we combined different omics techniques to analyse microbiome and serum composition. Methods: We collected faeces and blood samples to study the microbiome, the serum metabolome and circulating cytokines and miRNAs from a cohort of 105 fibromyalgia patients and 54 age-and environment-matched healthy individuals. We sequenced the V3 and V4 regions of the 16S rDNA gene from faeces samples. UPLC-MS metabolomics and custom multiplex cytokine and miRNA analysis (FirePlex™ technology) were used to examine sera samples. Finally, we combined the different data types to search for potential biomarkers. Results: We found that the diversity of bacteria is reduced in fibromyalgia patients. The abundance of the Bifidobacterium and Eubacterium genera (bacteria participating in the metabolism of neurotransmitters in the host) in these patients was significantly reduced. The serum metabolome analysis revealed altered levels of glutamate and serine, suggesting changes in neurotransmitter metabolism. The combined serum metabolomics and gut microbiome datasets showed a certain degree of correlation, reflecting the effect of the microbiome on metabolic activity. We also examined the microbiome and serum metabolites, cytokines and miRNAs as potential sources of molecular biomarkers of fibromyalgia.

Urine contains extracellular vesicles (EVs) that concentrate molecules and protect them from degradation. Thus, isolation and characterisation of urinary EVs could increase the efficiency of biomarker discovery. We have previously identified proteins and RNAs with differential abundance in urinary EVs from prostate cancer (PCa) patients compared to benign prostate hyperplasia (BPH). Here, we focused on the analysis of the metabolites contained in urinary EVs collected from patients with PCa and BPH. Targeted metabolomics analysis of EVs was performed by ultra-high-performance liquid chromatography–mass spectrometry. The correlation between metabolites and clinical parameters was studied, and metabolites with differential abundance in PCa urinary EVs were detected and mapped into cellular pathways. We detected 248 metabolites belonging to different chemical families including amino acids and various lipid species. Among these metabolites, 76 exhibited significant differential abundance between PCa and BPH. Interestingly, urine EVs recapitulated many of the metabolic alterations reported in PCa, including phosphathidylcholines, acyl carnitines, citrate and kynurenine. Importantly, we found elevated levels of the steroid hormone, 3beta-hydroxyandros-5-en-17-one-3-sulphate (dehydroepiandrosterone sulphate) in PCa urinary EVs, in line with the potential elevation of androgen synthesis in this type of cancer. This work supports urinary EVs as a non-invasive source to infer metabolic changes in PCa.

Although colorectal cancer (CRC) is the second leading cause of death in developed countries, current diagnostic tests for early disease stages are suboptimal. We have performed a combination of UHPLC-MS metabolomics and 16S microbiome analyses on 224 feces samples in order to identify early biomarkers for both advanced adenomas (AD) and CRC. We report differences in fecal levels of cholesteryl esters and sphingolipids in CRC. We identified Fusobacterium, Parvimonas and Staphylococcus to be increased in CRC patients and Lachnospiraceae family to be reduced. We finally described Adlercreutzia to be more abundant in AD patients’ feces. Integration of metabolomics and microbiome data revealed tight interactions between bacteria and host and performed better than FOB test for CRC diagnosis. This study identifies potential early biomarkers that outperform current diagnostic tools and frame them into the stablished gut microbiota role in CRC pathogenesis.