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Joint Microbiota Activity and Dietary Assessment through Urinary Biomarkers by LC-MS/MS

Accurate dietary assessment in nutritional research is a huge challenge, but essential. Due to the subjective nature of self-reporting methods, the development of analytical methods for food intake and microbiota biomarkers determination is needed. This work presents an ultra-high performance liquid...

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Autores principales: Ramos-Garcia, Victoria, Ten-Doménech, Isabel, Moreno-Giménez, Alba, Campos-Berga, Laura, Parra-Llorca, Anna, Gormaz, María, Vento, Máximo, Karipidou, Melina, Poulimeneas, Dimitrios, Mamalaki, Eirini, Bathrellou, Eirini, Kuligowski, Julia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10146414/
https://www.ncbi.nlm.nih.gov/pubmed/37111113
http://dx.doi.org/10.3390/nu15081894
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author Ramos-Garcia, Victoria
Ten-Doménech, Isabel
Moreno-Giménez, Alba
Campos-Berga, Laura
Parra-Llorca, Anna
Gormaz, María
Vento, Máximo
Karipidou, Melina
Poulimeneas, Dimitrios
Mamalaki, Eirini
Bathrellou, Eirini
Kuligowski, Julia
author_facet Ramos-Garcia, Victoria
Ten-Doménech, Isabel
Moreno-Giménez, Alba
Campos-Berga, Laura
Parra-Llorca, Anna
Gormaz, María
Vento, Máximo
Karipidou, Melina
Poulimeneas, Dimitrios
Mamalaki, Eirini
Bathrellou, Eirini
Kuligowski, Julia
author_sort Ramos-Garcia, Victoria
collection PubMed
description Accurate dietary assessment in nutritional research is a huge challenge, but essential. Due to the subjective nature of self-reporting methods, the development of analytical methods for food intake and microbiota biomarkers determination is needed. This work presents an ultra-high performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS) method for the quantification and semi quantification of 20 and 201 food intake biomarkers (BFIs), respectively, as well as 7 microbiota biomarkers applied to 208 urine samples from lactating mothers (M) (N = 59). Dietary intake was assessed through a 24 h dietary recall (R24h). BFI analysis identified three distinct clusters among samples: samples from clusters 1 and 3 presented higher concentrations of most biomarkers than those from cluster 2, with dairy products and milk biomarkers being more concentrated in cluster 1, and seeds, garlic and onion in cluster 3. Significant correlations were observed between three BFIs (fruits, meat, and fish) and R24h data (r > 0.2, p-values < 0.01, Spearman correlation). Microbiota activity biomarkers were simultaneously evaluated and the subgroup patterns detected were compared to clusters from dietary assessment. These results evidence the feasibility, usefulness, and complementary nature of the determination of BFIs, R24h, and microbiota activity biomarkers in observational nutrition cohort studies.
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spelling pubmed-101464142023-04-29 Joint Microbiota Activity and Dietary Assessment through Urinary Biomarkers by LC-MS/MS Ramos-Garcia, Victoria Ten-Doménech, Isabel Moreno-Giménez, Alba Campos-Berga, Laura Parra-Llorca, Anna Gormaz, María Vento, Máximo Karipidou, Melina Poulimeneas, Dimitrios Mamalaki, Eirini Bathrellou, Eirini Kuligowski, Julia Nutrients Article Accurate dietary assessment in nutritional research is a huge challenge, but essential. Due to the subjective nature of self-reporting methods, the development of analytical methods for food intake and microbiota biomarkers determination is needed. This work presents an ultra-high performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS) method for the quantification and semi quantification of 20 and 201 food intake biomarkers (BFIs), respectively, as well as 7 microbiota biomarkers applied to 208 urine samples from lactating mothers (M) (N = 59). Dietary intake was assessed through a 24 h dietary recall (R24h). BFI analysis identified three distinct clusters among samples: samples from clusters 1 and 3 presented higher concentrations of most biomarkers than those from cluster 2, with dairy products and milk biomarkers being more concentrated in cluster 1, and seeds, garlic and onion in cluster 3. Significant correlations were observed between three BFIs (fruits, meat, and fish) and R24h data (r > 0.2, p-values < 0.01, Spearman correlation). Microbiota activity biomarkers were simultaneously evaluated and the subgroup patterns detected were compared to clusters from dietary assessment. These results evidence the feasibility, usefulness, and complementary nature of the determination of BFIs, R24h, and microbiota activity biomarkers in observational nutrition cohort studies. MDPI 2023-04-14 /pmc/articles/PMC10146414/ /pubmed/37111113 http://dx.doi.org/10.3390/nu15081894 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ramos-Garcia, Victoria
Ten-Doménech, Isabel
Moreno-Giménez, Alba
Campos-Berga, Laura
Parra-Llorca, Anna
Gormaz, María
Vento, Máximo
Karipidou, Melina
Poulimeneas, Dimitrios
Mamalaki, Eirini
Bathrellou, Eirini
Kuligowski, Julia
Joint Microbiota Activity and Dietary Assessment through Urinary Biomarkers by LC-MS/MS
title Joint Microbiota Activity and Dietary Assessment through Urinary Biomarkers by LC-MS/MS
title_full Joint Microbiota Activity and Dietary Assessment through Urinary Biomarkers by LC-MS/MS
title_fullStr Joint Microbiota Activity and Dietary Assessment through Urinary Biomarkers by LC-MS/MS
title_full_unstemmed Joint Microbiota Activity and Dietary Assessment through Urinary Biomarkers by LC-MS/MS
title_short Joint Microbiota Activity and Dietary Assessment through Urinary Biomarkers by LC-MS/MS
title_sort joint microbiota activity and dietary assessment through urinary biomarkers by lc-ms/ms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10146414/
https://www.ncbi.nlm.nih.gov/pubmed/37111113
http://dx.doi.org/10.3390/nu15081894
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