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

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Item Type:Article
Title:Identification and characterization of human observational studies in nutritional epidemiology on gut microbiomics for joint data analysis
Creators Name:Pinart, M. and Nimptsch, K. and Forslund, S.K. and Schlicht, K. and Gueimonde, M. and Brigidi, P. and Turroni, S. and Ahrens, W. and Hebestreit, A. and Wolters, M. and Dötsch, A. and Nöthlings, U. and Oluwagbemigun, K. and Cuadrat, R.R.C. and Schulze, M.B. and Standl, M. and Schloter, M. and De Angelis, M. and Iozzo, P. and Guzzardi, M.A. and Vlaemynck, G. and Penders, J. and Jonkers, D.M.A.E. and Stemmer, M. and Chiesa, G. and Cavalieri, D. and De Filippo, C. and Ercolini, D. and De Filippis, F. and Ribet, D. and Achamrah, N. and Tavolacci, M.P. and Déchelotte, P. and Bouwman, J. and Laudes, M. and Pischon, T.
Abstract: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.
Keywords:Data Integration, Data Sharing, Dietary Intake, Metabolome, Metadata, Microbiome, Observational Studies
Page Range:3292
Date:September 2021
Official Publication:https://doi.org/10.3390/nu13093292
PubMed:View item in PubMed

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