Relationship between gut microbiota and circulating metabolites in population-based cohorts View Full Text


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Article Info

DATE

2019-12-20

AUTHORS

Dina Vojinovic, Djawad Radjabzadeh, Alexander Kurilshikov, Najaf Amin, Cisca Wijmenga, Lude Franke, M. Arfan Ikram, Andre G. Uitterlinden, Alexandra Zhernakova, Jingyuan Fu, Robert Kraaij, Cornelia M. van Duijn

ABSTRACT

Gut microbiota has been implicated in major diseases affecting the human population and has also been linked to triglycerides and high-density lipoprotein levels in the circulation. Recent development in metabolomics allows classifying the lipoprotein particles into more details. Here, we examine the impact of gut microbiota on circulating metabolites measured by Nuclear Magnetic Resonance technology in 2309 individuals from the Rotterdam Study and the LifeLines-DEEP cohort. We assess the relationship between gut microbiota and metabolites by linear regression analysis while adjusting for age, sex, body-mass index, technical covariates, medication use, and multiple testing. We report an association of 32 microbial families and genera with very-low-density and high-density subfractions, serum lipid measures, glycolysis-related metabolites, ketone bodies, amino acids, and acute-phase reaction markers. These observations provide insights into the role of microbiota in host metabolism and support the potential of gut microbiota as a target for therapeutic and preventive interventions. More... »

PAGES

5813

References to SciGraph publications

  • 2005-08-03. Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix in HEREDITY
  • 2006-12. An obesity-associated gut microbiome with increased capacity for energy harvest in NATURE
  • 2019-10-25. Intestinal microbiome composition and its relation to joint pain and inflammation in NATURE COMMUNICATIONS
  • 2013-08-28. Richness of human gut microbiome correlates with metabolic markers in NATURE
  • 2018-09-28. Role of Gut Microbiota-Generated Short-Chain Fatty Acids in Metabolic and Cardiovascular Health in CURRENT NUTRITION REPORTS
  • 2016-06-08. Acetate mediates a microbiome–brain–β-cell axis to promote metabolic syndrome in NATURE
  • 2016-11-28. Comprehensive analysis of the fecal microbiota of healthy Japanese adults reveals a new bacterial lineage associated with a phenotype characterized by a high frequency of bowel movements and a lean body type in BMC MICROBIOLOGY
  • 1991-07. Determinants of disease and disability in the elderly: The Rotterdam elderly study in EUROPEAN JOURNAL OF EPIDEMIOLOGY
  • 2018-05-28. The fecal metabolome as a functional readout of the gut microbiome in NATURE GENETICS
  • 2018-06-08. Meta-analysis of human genome-microbiome association studies: the MiBioGen consortium initiative in MICROBIOME
  • 2017-04-13. Relationships between gut microbiota, plasma metabolites, and metabolic syndrome traits in the METSIM cohort in GENOME BIOLOGY
  • 2018-02-28. Environment dominates over host genetics in shaping human gut microbiota in NATURE
  • 2017-09. The Rotterdam Study: 2018 update on objectives, design and main results in EUROPEAN JOURNAL OF EPIDEMIOLOGY
  • 2016-10-03. The effect of host genetics on the gut microbiome in NATURE GENETICS
  • 2011-03-20. Metabolite profiles and the risk of developing diabetes in NATURE MEDICINE
  • 2017-10-10. The gut microbiome in atherosclerotic cardiovascular disease in NATURE COMMUNICATIONS
  • 2014-09-01. Plasma amino acid profiles are associated with insulin, C-peptide and adiponectin levels in type 2 diabetic patients in NUTRITION & DIABETES
  • 2014-07-25. Molecular phenotyping of a UK population: defining the human serum metabolome in METABOLOMICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41467-019-13721-1

    DOI

    http://dx.doi.org/10.1038/s41467-019-13721-1

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1123539228

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/31862950


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