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Pinart, M.* ; Nimptsch, K.* ; Schlicht, K.* ; Gueimonde, M.* ; Brigidi, P.* ; Turroni, S.* ; Ahrens, W.* ; Hebestreit, A.* ; Wolters, M.* ; Dötsch, A.* ; Nöthlings, U.* ; Oluwagbemigun, K.* ; Cuadrat, R.R.C.* ; Schulze, M.B.* ; Standl, M. ; Schloter, M. ; de Angelis, M.* ; Iozzo, P.* ; Guzzardi, M.A.* ; Vlaemynck, G.* ; Penders, J.* ; Jonkers, D.M.A.E.* ; Stemmer, M.* ; Chiesa, G.* ; Cavalieri, D.* ; De Filippo, C.* ; Ercolini, D.* ; De Filippis, F.* ; Ribet, D.* ; Achamrah, N.* ; Tavolacci, M.P.* ; Déchelotte, P.* ; Bouwman, J.* ; Laudes, M.*

Identification and characterization of human observational studies in nutritional epidemiology on gut microbiomics for joint data analysis.

Nutrients 13:3292 (2021)
Postprint Forschungsdaten DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
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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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Data Integration ; Data Sharing ; Dietary Intake ; Metabolome ; Metadata ; Microbiome ; Observational Studies; Age
ISSN (print) / ISBN 2072-6643
e-ISSN 2072-6643
Zeitschrift Nutrients
Quellenangaben Band: 13, Heft: 9, Seiten: , Artikelnummer: 3292 Supplement: ,
Verlag MDPI
Verlagsort Basel
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Epidemiology (EPI)
Research Unit Comparative Microbiome Analysis (COMI)
Förderungen Joint Programming Initiative A healthy diet for a healthy life