Acta Diabetologica

, Volume 56, Issue 5, pp 569–579 | Cite as

Glutamate interactions with obesity, insulin resistance, cognition and gut microbiota composition

  • María Encarnación Palomo-Buitrago
  • Mònica Sabater-Masdeu
  • Jose Maria Moreno-Navarrete
  • Estefanía Caballano-Infantes
  • María Arnoriaga-Rodríguez
  • Clàudia Coll
  • Lluís Ramió
  • Martina Palomino-Schätzlein
  • Patricia Gutiérrez-Carcedo
  • Vicente Pérez-Brocal
  • Rafael Simó
  • Andrés Moya
  • Wifredo Ricart
  • José Raúl HeranceEmail author
  • José Manuel Fernández-RealEmail author
Original Article
Part of the following topical collections:
  1. Gut Microbiome and Metabolic Disorders



To investigate the interactions among fecal and plasma glutamate levels, insulin resistance cognition and gut microbiota composition in obese and non-obese subjects.


Gut microbiota composition (shotgun) and plasma and fecal glutamate, glutamine and acetate (NMR) were analyzed in a pilot study of obese and non-obese subjects (n = 35). Neuropsychological tests [Trail making test A (TMT-A) and Trail making test B (TMT-B)] scores measured cognitive information about processing speed, mental flexibility and executive function.


Trail-making test score was significantly altered in obese compared with non-obese subjects. Fecal glutamate and glutamate/glutamine ratio tended to be lower among obese subjects while fecal glutamate/acetate ratio was negatively associated with BMI and TMT-A scores. Plasma glutamate/acetate ratio was negatively associated with TMT-B. The relative abundance (RA) of some bacterial families influenced glutamate levels, given the positive association of fecal glutamate/glutamine ratio with Corynebacteriaceae, Coriobacteriaceae and Burkholderiaceae RA. In contrast, Streptococaceae RA, that was significantly higher in obese subjects, negatively correlated with fecal glutamate/glutamine ratio. To close the circle, Coriobacteriaceae/Streptococaceae ratio and Corynebacteriaceae/Streptococaceae ratio were associated both with TMT-A scores and fecal glutamate/glutamine ratio.


Gut microbiota composition is associated with processing speed and mental flexibility in part through changes in fecal and plasma glutamate metabolism.


Microbiota Metabolomics Glutamate Trail making test Cognition 



The authors acknowledge the technical assistance of Emilio Loshuertos (Girona Biomedical Research Institute, IdIBGi) and Oscar Rovira.

Author contributions

MEPB, MSM and MAR researched the data, performed the statistical analysis and wrote and edited the manuscript. CC and LR researched the data and performed neuropsychological assessment TMT-A and TMT-B MP-S, PG-C and JRH researched the data, performed the 1H-NMR for plasma and feces metabolomic analysis and contributed to the writing and editing of the manuscript. VP-B, AM performed the gut microbiota composition analysis and contributed to the writing of the manuscript. JMM-N, EC-I, RS, JRH, WR contributed to the discussion and reviewed the manuscript. JMF-R Carried out the conception and coordination of the study, contributed to statistical analysis and writing the manuscript and directly participated in the execution of the study. JMF-R is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.


This work was supported by FIS Grant (PI15/01934), FIS Grant (PI16/02064) from the National Institute of Health Carlos III and by ERDF (European Regional Development Fund).

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest.

Ethical standards

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

592_2019_1313_MOESM1_ESM.pdf (273 kb)
Supplementary material 1 (PDF 272 KB)
592_2019_1313_MOESM2_ESM.pdf (46 kb)
Supplementary material 2 (PDF 45 KB)


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Copyright information

© Springer-Verlag Italia S.r.l., part of Springer Nature 2019

Authors and Affiliations

  • María Encarnación Palomo-Buitrago
    • 1
  • Mònica Sabater-Masdeu
    • 1
    • 2
  • Jose Maria Moreno-Navarrete
    • 1
    • 2
  • Estefanía Caballano-Infantes
    • 1
    • 2
  • María Arnoriaga-Rodríguez
    • 1
    • 2
  • Clàudia Coll
    • 3
  • Lluís Ramió
    • 3
  • Martina Palomino-Schätzlein
    • 9
  • Patricia Gutiérrez-Carcedo
    • 4
  • Vicente Pérez-Brocal
    • 5
    • 6
  • Rafael Simó
    • 7
    • 8
  • Andrés Moya
    • 5
    • 6
  • Wifredo Ricart
    • 1
    • 2
  • José Raúl Herance
    • 4
    Email author
  • José Manuel Fernández-Real
    • 1
    • 2
    Email author
  1. 1.Department of Diabetes, Endocrinology and Nutrition, Hospital of Girona “Dr Josep Trueta”Institut d’Investigació Biomèdica de Girona (IDIBGI)GironaSpain
  2. 2.CIBER de la Fisiopatología de la Obesidad y Nutrición (CIBERobn, CB06/03/010) and Instituto de Salud Carlos III (ISCIII)GironaSpain
  3. 3.Department of NeurologyInstitut d’Investigació Biomèdica de Girona (IDIBGI), Hospital of Girona “Dr Josep Trueta”GironaSpain
  4. 4.Medical Molecular Imaging Research Group, Vall d’Hebron Research InstituteInstituto de Salud Carlos III (ISCIII), CIBBIM-Nanomedicine, CIBER-bbnBarcelonaSpain
  5. 5.Genomics and Health AreaFoundation for the Promotion of Sanitary and Biomedical Research (FISABIO)ValènciaSpain
  6. 6.CIBER de Epidemiology y Salud Pública (CIBERESP), Instituto de Salud Carlos IIIMadridSpain
  7. 7.Diabetes and Metabolism Research UnitVall d’Hebron Research InstituteBarcelonaSpain
  8. 8.Department of Endocrinology, Vall d’Hebron Research InstituteInstituto de Salud Carlos III (ISCIII), CIBERDEMBarcelonaSpain
  9. 9.NMR FacilityCentro de Investigación Principe FelipeValenciaSpain

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