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Identification and Characterization of Human Observational Studies in Nutritional Epidemiology on Gut Microbiomics for Joint Data Analysis

In any research field, data access and data integration are major challenges that even large, well-established consortia face. Although data sharing initiatives are increasing, joint data analyses on nutrition and microbiomics in health and disease are still scarce. We aimed to identify observationa...

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Autores principales: Pinart, Mariona, Nimptsch, Katharina, Forslund, Sofia K., Schlicht, Kristina, Gueimonde, Miguel, Brigidi, Patrizia, Turroni, Silvia, Ahrens, Wolfgang, Hebestreit, Antje, Wolters, Maike, Dötsch, Andreas, Nöthlings, Ute, Oluwagbemigun, Kolade, Cuadrat, Rafael R. C., Schulze, Matthias B., Standl, Marie, Schloter, Michael, De Angelis, Maria, Iozzo, Patricia, Guzzardi, Maria Angela, Vlaemynck, Geertrui, Penders, John, Jonkers, Daisy M. A. E., Stemmer, Maya, Chiesa, Giulia, Cavalieri, Duccio, De Filippo, Carlotta, Ercolini, Danilo, De Filippis, Francesca, Ribet, David, Achamrah, Najate, Tavolacci, Marie-Pierre, Déchelotte, Pierre, Bouwman, Jildau, Laudes, Matthias, Pischon, Tobias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8466729/
https://www.ncbi.nlm.nih.gov/pubmed/34579168
http://dx.doi.org/10.3390/nu13093292
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author Pinart, Mariona
Nimptsch, Katharina
Forslund, Sofia K.
Schlicht, Kristina
Gueimonde, Miguel
Brigidi, Patrizia
Turroni, Silvia
Ahrens, Wolfgang
Hebestreit, Antje
Wolters, Maike
Dötsch, Andreas
Nöthlings, Ute
Oluwagbemigun, Kolade
Cuadrat, Rafael R. C.
Schulze, Matthias B.
Standl, Marie
Schloter, Michael
De Angelis, Maria
Iozzo, Patricia
Guzzardi, Maria Angela
Vlaemynck, Geertrui
Penders, John
Jonkers, Daisy M. A. E.
Stemmer, Maya
Chiesa, Giulia
Cavalieri, Duccio
De Filippo, Carlotta
Ercolini, Danilo
De Filippis, Francesca
Ribet, David
Achamrah, Najate
Tavolacci, Marie-Pierre
Déchelotte, Pierre
Bouwman, Jildau
Laudes, Matthias
Pischon, Tobias
author_facet Pinart, Mariona
Nimptsch, Katharina
Forslund, Sofia K.
Schlicht, Kristina
Gueimonde, Miguel
Brigidi, Patrizia
Turroni, Silvia
Ahrens, Wolfgang
Hebestreit, Antje
Wolters, Maike
Dötsch, Andreas
Nöthlings, Ute
Oluwagbemigun, Kolade
Cuadrat, Rafael R. C.
Schulze, Matthias B.
Standl, Marie
Schloter, Michael
De Angelis, Maria
Iozzo, Patricia
Guzzardi, Maria Angela
Vlaemynck, Geertrui
Penders, John
Jonkers, Daisy M. A. E.
Stemmer, Maya
Chiesa, Giulia
Cavalieri, Duccio
De Filippo, Carlotta
Ercolini, Danilo
De Filippis, Francesca
Ribet, David
Achamrah, Najate
Tavolacci, Marie-Pierre
Déchelotte, Pierre
Bouwman, Jildau
Laudes, Matthias
Pischon, Tobias
author_sort Pinart, Mariona
collection PubMed
description In any research field, data access and data integration are major challenges that even large, well-established consortia face. Although data sharing initiatives are increasing, joint data analyses on nutrition and microbiomics in health and disease are still scarce. We aimed to identify observational studies with data on nutrition and gut microbiome composition from the Intestinal Microbiomics (INTIMIC) Knowledge Platform following the findable, accessible, interoperable, and reusable (FAIR) principles. An adapted template from the European Nutritional Phenotype Assessment and Data Sharing Initiative (ENPADASI) consortium was used to collect microbiome-specific information and other related factors. In total, 23 studies (17 longitudinal and 6 cross-sectional) were identified from Italy (7), Germany (6), Netherlands (3), Spain (2), Belgium (1), and France (1) or multiple countries (3). Of these, 21 studies collected information on both dietary intake (24 h dietary recall, food frequency questionnaire (FFQ), or Food Records) and gut microbiome. All studies collected stool samples. The most often used sequencing platform was Illumina MiSeq, and the preferred hypervariable regions of the 16S rRNA gene were V3–V4 or V4. The combination of datasets will allow for sufficiently powered investigations to increase the knowledge and understanding of the relationship between food and gut microbiome in health and disease.
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spelling pubmed-84667292021-09-27 Identification and Characterization of Human Observational Studies in Nutritional Epidemiology on Gut Microbiomics for Joint Data Analysis Pinart, Mariona Nimptsch, Katharina Forslund, Sofia K. Schlicht, Kristina Gueimonde, Miguel Brigidi, Patrizia Turroni, Silvia Ahrens, Wolfgang Hebestreit, Antje Wolters, Maike Dötsch, Andreas Nöthlings, Ute Oluwagbemigun, Kolade Cuadrat, Rafael R. C. Schulze, Matthias B. Standl, Marie Schloter, Michael De Angelis, Maria Iozzo, Patricia Guzzardi, Maria Angela Vlaemynck, Geertrui Penders, John Jonkers, Daisy M. A. E. Stemmer, Maya Chiesa, Giulia Cavalieri, Duccio De Filippo, Carlotta Ercolini, Danilo De Filippis, Francesca Ribet, David Achamrah, Najate Tavolacci, Marie-Pierre Déchelotte, Pierre Bouwman, Jildau Laudes, Matthias Pischon, Tobias Nutrients Article In any research field, data access and data integration are major challenges that even large, well-established consortia face. Although data sharing initiatives are increasing, joint data analyses on nutrition and microbiomics in health and disease are still scarce. We aimed to identify observational studies with data on nutrition and gut microbiome composition from the Intestinal Microbiomics (INTIMIC) Knowledge Platform following the findable, accessible, interoperable, and reusable (FAIR) principles. An adapted template from the European Nutritional Phenotype Assessment and Data Sharing Initiative (ENPADASI) consortium was used to collect microbiome-specific information and other related factors. In total, 23 studies (17 longitudinal and 6 cross-sectional) were identified from Italy (7), Germany (6), Netherlands (3), Spain (2), Belgium (1), and France (1) or multiple countries (3). Of these, 21 studies collected information on both dietary intake (24 h dietary recall, food frequency questionnaire (FFQ), or Food Records) and gut microbiome. All studies collected stool samples. The most often used sequencing platform was Illumina MiSeq, and the preferred hypervariable regions of the 16S rRNA gene were V3–V4 or V4. The combination of datasets will allow for sufficiently powered investigations to increase the knowledge and understanding of the relationship between food and gut microbiome in health and disease. MDPI 2021-09-21 /pmc/articles/PMC8466729/ /pubmed/34579168 http://dx.doi.org/10.3390/nu13093292 Text en © 2021 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
Pinart, Mariona
Nimptsch, Katharina
Forslund, Sofia K.
Schlicht, Kristina
Gueimonde, Miguel
Brigidi, Patrizia
Turroni, Silvia
Ahrens, Wolfgang
Hebestreit, Antje
Wolters, Maike
Dötsch, Andreas
Nöthlings, Ute
Oluwagbemigun, Kolade
Cuadrat, Rafael R. C.
Schulze, Matthias B.
Standl, Marie
Schloter, Michael
De Angelis, Maria
Iozzo, Patricia
Guzzardi, Maria Angela
Vlaemynck, Geertrui
Penders, John
Jonkers, Daisy M. A. E.
Stemmer, Maya
Chiesa, Giulia
Cavalieri, Duccio
De Filippo, Carlotta
Ercolini, Danilo
De Filippis, Francesca
Ribet, David
Achamrah, Najate
Tavolacci, Marie-Pierre
Déchelotte, Pierre
Bouwman, Jildau
Laudes, Matthias
Pischon, Tobias
Identification and Characterization of Human Observational Studies in Nutritional Epidemiology on Gut Microbiomics for Joint Data Analysis
title Identification and Characterization of Human Observational Studies in Nutritional Epidemiology on Gut Microbiomics for Joint Data Analysis
title_full Identification and Characterization of Human Observational Studies in Nutritional Epidemiology on Gut Microbiomics for Joint Data Analysis
title_fullStr Identification and Characterization of Human Observational Studies in Nutritional Epidemiology on Gut Microbiomics for Joint Data Analysis
title_full_unstemmed Identification and Characterization of Human Observational Studies in Nutritional Epidemiology on Gut Microbiomics for Joint Data Analysis
title_short Identification and Characterization of Human Observational Studies in Nutritional Epidemiology on Gut Microbiomics for Joint Data Analysis
title_sort identification and characterization of human observational studies in nutritional epidemiology on gut microbiomics for joint data analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8466729/
https://www.ncbi.nlm.nih.gov/pubmed/34579168
http://dx.doi.org/10.3390/nu13093292
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