Gut microbiome and serum metabolome analyses identify molecular biomarkers and altered glutamate metabolism in fibromyalgia

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....

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Veröffentlicht in:EBioMedicine 2019-08, Vol.46, p.499-511
Hauptverfasser: Clos-Garcia, Marc, Andrés-Marin, Naiara, Fernández-Eulate, Gorka, Abecia, Leticia, Lavín, José L., van Liempd, Sebastiaan, Cabrera, Diana, Royo, Félix, Valero, Alejandro, Errazquin, Nerea, Vega, María Cristina Gómez, Govillard, Leila, Tackett, Michael R., Tejada, Genesis, Gónzalez, Esperanza, Anguita, Juan, Bujanda, Luis, Orcasitas, Ana María Callejo, Aransay, Ana M., Maíz, Olga, López de Munain, Adolfo, Falcón-Pérez, Juan Manuel
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container_start_page 499
container_title EBioMedicine
container_volume 46
creator Clos-Garcia, Marc
Andrés-Marin, Naiara
Fernández-Eulate, Gorka
Abecia, Leticia
Lavín, José L.
van Liempd, Sebastiaan
Cabrera, Diana
Royo, Félix
Valero, Alejandro
Errazquin, Nerea
Vega, María Cristina Gómez
Govillard, Leila
Tackett, Michael R.
Tejada, Genesis
Gónzalez, Esperanza
Anguita, Juan
Bujanda, Luis
Orcasitas, Ana María Callejo
Aransay, Ana M.
Maíz, Olga
López de Munain, Adolfo
Falcón-Pérez, Juan Manuel
description 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. 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. 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. Our results show that the microbiome analysis provides more significant biomarkers than the other techniques employed in the work. Gut microbiome analysis combined with serum metabolomics can shed new light onto the pathogenesis of fibromyalgia. We provide a list of bacteria whose abundance changes in this disease and propose several molecules as potential biomarkers that can be used to evaluate the current diagnostic criteria.
doi_str_mv 10.1016/j.ebiom.2019.07.031
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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. 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. We found that the diversity of bacteria is reduced in fibromyalgia patients. 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Andrés-Marin, Naiara ; Fernández-Eulate, Gorka ; Abecia, Leticia ; Lavín, José L. ; van Liempd, Sebastiaan ; Cabrera, Diana ; Royo, Félix ; Valero, Alejandro ; Errazquin, Nerea ; Vega, María Cristina Gómez ; Govillard, Leila ; Tackett, Michael R. ; Tejada, Genesis ; Gónzalez, Esperanza ; Anguita, Juan ; Bujanda, Luis ; Orcasitas, Ana María Callejo ; Aransay, Ana M. ; Maíz, Olga ; López de Munain, Adolfo ; Falcón-Pérez, Juan Manuel</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c459t-91c3251d42945428c8b460961556c265498dd2bbb51b1a2c4283eb5388f450883</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Biomarkers</topic><topic>Chromatography, High Pressure Liquid</topic><topic>Computational Biology - methods</topic><topic>Cytokines</topic><topic>Cytokines - metabolism</topic><topic>Female</topic><topic>Fibromyalgia</topic><topic>Fibromyalgia - etiology</topic><topic>Fibromyalgia - metabolism</topic><topic>Gastrointestinal Microbiome</topic><topic>Glutamates - metabolism</topic><topic>Gut microbiota</topic><topic>Humans</topic><topic>Male</topic><topic>Metabolome</topic><topic>Metabolomics</topic><topic>Metabolomics - methods</topic><topic>Metagenome</topic><topic>Metagenomics - methods</topic><topic>Middle Aged</topic><topic>miRNAs</topic><topic>Omics integration</topic><topic>Pain</topic><topic>Research paper</topic><topic>RNA, Ribosomal, 16S - genetics</topic><topic>ROC Curve</topic><topic>Tandem Mass Spectrometry</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Clos-Garcia, Marc</creatorcontrib><creatorcontrib>Andrés-Marin, Naiara</creatorcontrib><creatorcontrib>Fernández-Eulate, Gorka</creatorcontrib><creatorcontrib>Abecia, Leticia</creatorcontrib><creatorcontrib>Lavín, José L.</creatorcontrib><creatorcontrib>van Liempd, Sebastiaan</creatorcontrib><creatorcontrib>Cabrera, Diana</creatorcontrib><creatorcontrib>Royo, Félix</creatorcontrib><creatorcontrib>Valero, Alejandro</creatorcontrib><creatorcontrib>Errazquin, Nerea</creatorcontrib><creatorcontrib>Vega, María Cristina Gómez</creatorcontrib><creatorcontrib>Govillard, Leila</creatorcontrib><creatorcontrib>Tackett, Michael R.</creatorcontrib><creatorcontrib>Tejada, Genesis</creatorcontrib><creatorcontrib>Gónzalez, Esperanza</creatorcontrib><creatorcontrib>Anguita, Juan</creatorcontrib><creatorcontrib>Bujanda, Luis</creatorcontrib><creatorcontrib>Orcasitas, Ana María Callejo</creatorcontrib><creatorcontrib>Aransay, Ana M.</creatorcontrib><creatorcontrib>Maíz, Olga</creatorcontrib><creatorcontrib>López de Munain, Adolfo</creatorcontrib><creatorcontrib>Falcón-Pérez, Juan Manuel</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>EBioMedicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Clos-Garcia, Marc</au><au>Andrés-Marin, Naiara</au><au>Fernández-Eulate, Gorka</au><au>Abecia, Leticia</au><au>Lavín, José L.</au><au>van Liempd, Sebastiaan</au><au>Cabrera, Diana</au><au>Royo, Félix</au><au>Valero, Alejandro</au><au>Errazquin, Nerea</au><au>Vega, María Cristina Gómez</au><au>Govillard, Leila</au><au>Tackett, Michael R.</au><au>Tejada, Genesis</au><au>Gónzalez, Esperanza</au><au>Anguita, Juan</au><au>Bujanda, Luis</au><au>Orcasitas, Ana María Callejo</au><au>Aransay, Ana M.</au><au>Maíz, Olga</au><au>López de Munain, Adolfo</au><au>Falcón-Pérez, Juan Manuel</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Gut microbiome and serum metabolome analyses identify molecular biomarkers and altered glutamate metabolism in fibromyalgia</atitle><jtitle>EBioMedicine</jtitle><addtitle>EBioMedicine</addtitle><date>2019-08-01</date><risdate>2019</risdate><volume>46</volume><spage>499</spage><epage>511</epage><pages>499-511</pages><issn>2352-3964</issn><eissn>2352-3964</eissn><abstract>Fibromyalgia is a complex, relatively unknown disease characterised by chronic, widespread musculoskeletal pain. 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subjects Adult
Aged
Biomarkers
Chromatography, High Pressure Liquid
Computational Biology - methods
Cytokines
Cytokines - metabolism
Female
Fibromyalgia
Fibromyalgia - etiology
Fibromyalgia - metabolism
Gastrointestinal Microbiome
Glutamates - metabolism
Gut microbiota
Humans
Male
Metabolome
Metabolomics
Metabolomics - methods
Metagenome
Metagenomics - methods
Middle Aged
miRNAs
Omics integration
Pain
Research paper
RNA, Ribosomal, 16S - genetics
ROC Curve
Tandem Mass Spectrometry
title Gut microbiome and serum metabolome analyses identify molecular biomarkers and altered glutamate metabolism in fibromyalgia
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