Published 2013

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Publication details

Journal : PLoS Computational Biology , vol. 9 , 2013

International Standard Numbers :
Printed : 1553-734X
Electronic : 1553-7358

Publication type : Academic article

Contributors : White, Richard; Bjørnholt, Jørgen; Baird, Donna D.; Midtvedt, Tore; Harris, Jennifer; Pagano, Marcello; Hide, Winston; Rudi, Knut; Moen, Birgitte; Iszatt, Nina; Peddada, Shyamal D.; Eggesbø, Merete Åse

Issue : 5

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Kjetil Aune
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It is acknowledged that some obesity trajectories are set early in life, and that rapid weight gain in infancy is a risk factor for later development of obesity. Identifying modifiable factors associated with early rapid weight gain is a prerequisite for curtailing the growing worldwide obesity epidemic. Recently, much attention has been given to findings indicating that gut microbiota may play a role in obesity development. We aim at identifying how the development of early gut microbiota is associated with expected infant growth. We developed a novel procedure that allows for the identification of longitudinal gut microbiota patterns (corresponding to the gut ecosystem developing), which are associated with an outcome of interest, while appropriately controlling for the false discovery rate. Our method identified developmental pathways of Staphylococcus species and Escherichia coli that were associated with expected growth, and traditional methods indicated that the detection of Bacteroides species at day 30 was associated with growth. Our method should have wide future applicability for studying gut microbiota, and is particularly important for translational considerations, as it is critical to understand the timing of microbiome transitions prior to attempting to manipulate gut microbiota in early life.