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Infant microbiota in colic: predictive associations with problem crying and subsequent child behavior

Published online by Cambridge University Press:  13 April 2020

Amy Loughman*
Affiliation:
Deakin University, IMPACT (the Institute for Mental and Physical Health and Clinical Translation), Food & Mood Centre, Level 3, 299 Ryrie Street, Geelong, Victoria3220, Australia
Thomas Quinn
Affiliation:
Applied Artificial Intelligence Institute, Deakin University, Geelong, Victoria3220, Australia
Monica L. Nation
Affiliation:
Murdoch Children’s Research Institute, Parkville, Victoria3052, Australia
Amy Reichelt
Affiliation:
Robarts Research Institute, Western University, London, Ontario, Canada Florey Institute of Neuroscience and Mental Health, Parkville, Victoria3052, Australia
Robert J. Moore
Affiliation:
School of Science, RMIT University, Bundoora, Victoria3083, Australia
Thi Thu Hao Van
Affiliation:
School of Science, RMIT University, Bundoora, Victoria3083, Australia
Valerie Sung
Affiliation:
Murdoch Children’s Research Institute, Parkville, Victoria3052, Australia Department of Paediatrics, University of Melbourne, Parkville, Victoria3052, Australia Royal Children’s Hospital, Parkville, Victoria3052, Australia
Mimi L. K. Tang
Affiliation:
Murdoch Children’s Research Institute, Parkville, Victoria3052, Australia Department of Paediatrics, University of Melbourne, Parkville, Victoria3052, Australia Royal Children’s Hospital, Parkville, Victoria3052, Australia
*
Address for correspondence: Amy Loughman, Deakin University, IMPACT (the Institute for Mental and Physical Health and Clinical Translation), Food & Mood Centre, Level 3, 299 Ryrie Street, Geelong, Victoria3220, Australia. Email: amy.loughman@deakin.edu.au

Abstract

Infant colic is a condition of unknown cause which can result in carer distress and attachment difficulties. Recent studies have implicated the gut microbiota in infant colic, and certain probiotics have demonstrated possible efficacy. We aim to investigate whether the intestinal microbiota composition in infants with colic is associated with cry/fuss time at baseline, persistence of cry/fuss at 4-week follow-up, or child behavior at 2 years of age. Fecal samples from infants with colic (n = 118, 53% male) were analyzed using 16S rRNA sequencing. After examining the alpha and beta diversity of the clinical samples, we performed a differential abundance analysis of the 16S data to look for taxa that associate with baseline and future behavior, while adjusting for potential confounding variables. In addition, we used random forest classifiers to evaluate how well baseline gut microbiota can predict future crying time. Alpha diversity of the fecal microbiota was strongly influenced by birth mode, feed type, and child gender, but did not significantly associate with crying or behavioral outcomes. Several taxa within the microbiota (including Bifidobacterium, Clostridium, Lactobacillus, and Klebsiella) associate with colic severity, and the baseline microbiota composition can predict further crying at 4 weeks with up to 65% accuracy. The combination of machine learning findings with associative relationships demonstrates the potential prognostic utility of the infant fecal microbiota in predicting subsequent infant crying problems.

Type
Original Article
Copyright
© Cambridge University Press and the International Society for Developmental Origins of Health and Disease 2020

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Footnotes

Joint first authors

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