Hostname: page-component-8448b6f56d-qsmjn Total loading time: 0 Render date: 2024-04-18T06:27:31.879Z Has data issue: false hasContentIssue false
  • English
  • Français

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

Published online by Cambridge University Press:  13 April 2020

Amy Loughman Open the ORCID record for Amy Loughman [Opens in a new window] ,
Thomas Quinn ,
Monica L. Nation ,
Amy Reichelt ,
Robert J. Moore ,
Thi Thu Hao Van ,
Valerie Sung  and
Mimi L. K. Tang
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
Get access Rights & Permissions [Opens in a new window]

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.

Keywords

Infantcryinggut–brain axismicrobiotaneurodevelopment
Type
Original Article
Information
Journal of Developmental Origins of Health and Disease , Volume 12 , Issue 2 , April 2021 , pp. 260 - 270
Check for updates
Copyright
© Cambridge University Press and the International Society for Developmental Origins of Health and Disease 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

†

Joint first authors

References

Pronovost, GN, Hsiao, EY. Perinatal interactions between the microbiome, immunity, and neurodevelopment. Immunity. 2019; 50(1), 18–36.CrossRefGoogle ScholarPubMed
Aatsinki, A-K, Lahti, L, Uusitupa, H-M, et al. Gut microbiota composition is associated with temperament traits in infants. Brain Behav Immun. 2019, 80, 849–858.CrossRefGoogle ScholarPubMed
Christian, LM, Galley, JD, Hade, EM, Schoppe-Sullivan, S, Kamp Dush, C, Bailey, MT. Gut microbiome composition is associated with temperament during early childhood. Brain Behav Immun. 2015; 45, 118–127.CrossRefGoogle ScholarPubMed
Carlson, AL, Xia, K, Azcarate-Peril, MA, et al. Infant gut microbiome associated with cognitive development. Biol Psychiatry. 2018; 83, 148–159.CrossRefGoogle ScholarPubMed
Sordillo, JE, Korrick, S, Laranjo, N, et al. Association of the infant gut microbiome with early childhood neurodevelopmental outcomes: an ancillary study to the VDAART randomized clinical trial. JAMA Netw Open. 2019; 2(3), e190905–e190905.CrossRefGoogle ScholarPubMed
Valles-Colomer, M, Falony, G, Darzi, Y, et al. The neuroactive potential of the human gut microbiota in quality of life and depression. Nat Microbiol. 2019; doi: 10.1038/s41564-018-0337-x.CrossRefGoogle ScholarPubMed
Hemmi, MH, Wolke, D, Schneider, S. Associations between problems with crying, sleeping and/or feeding in infancy and long-term behavioural outcomes in childhood: a meta-analysis. Arch Dis. Child. 2011; 96, 622–629.CrossRefGoogle ScholarPubMed
Sung, V, D’Amico, F, Cabana, MD, et al. Lactobacillus reuteri to treat infant colic: a meta-analysis. Pediatrics. 2018; 141(1), e20171811.CrossRefGoogle ScholarPubMed
Pärtty, A, Kalliomäki, M. Infant colic is still a mysterious disorder of the microbiota–gut–brain axis. Acta Paediatr. 2017; 106(4), 528–529.CrossRefGoogle Scholar
Savino, F, Quartieri, A, De Marco, A, et al. Comparison of formula-fed infants with and without colic revealed significant differences in total bacteria, Enterobacteriaceae and faecal ammonia. Acta Paediatr. 2017; 106(4), 573–578.CrossRefGoogle ScholarPubMed
Bell, G, Hiscock, H, Tobin, S, Cook, F, Sung, V. Behavioral outcomes of infant colic in toddlerhood: a longitudinal study. J Pediatr. 2018; 201, 154–159.CrossRefGoogle ScholarPubMed
Savino, F, Castagno, E, Bretto, R, Brondello, C, Palumeri, E, Oggero, R. A prospective 10-year study on children who had severe infantile colic. Acta Paediatr Suppl. 2005; 94(449), 129–132.CrossRefGoogle Scholar
Rautava, P, Lehtonen, L, Helenius, H, Sillanpaa, M. Infantile colic: child and family three years later. Pediatrics. 1995; 96(1 Pt 1), 43–47.Google ScholarPubMed
Canivet, C, Jakobsson, I, Hagander, B. Infantile colic. Follow-up at four years of age: still more “emotional”. Acta Paediatr. 2000; 89(1), 13–17.CrossRefGoogle ScholarPubMed
Sung, V, Hiscock, H, Tang, M, et al. Probiotics to improve outcomes of colic in the community: protocol for the Baby Biotics randomised controlled trial. BMC Pediatr. 2012; 12, 1.CrossRefGoogle ScholarPubMed
Sung, V, Hiscock, H, Tang, ML, et al. Treating infant colic with the probiotic Lactobacillus reuteri: double blind, placebo controlled randomised trial. Bmj. 2014; 348, g2107.CrossRefGoogle ScholarPubMed
Nation, ML, Dunne, EM, Joseph, SJ, et al. Impact of Lactobacillus reuteri colonization on gut microbiota, inflammation, and crying time in infant colic. Sci Rep. 2017; 7, 15047.CrossRefGoogle ScholarPubMed
Oksanen, J, Blanchet, FG, Kindt, R, et al. Vegan: community ecology package. R package version 1.17-4. http://cran.r-project.org Acessoem.2010; 23, 2010.Google Scholar
Wessel, MA. Paroxysmal fussing in infants, sometimes called colic. Pediatrics. 1954; 14, 421–434.Google ScholarPubMed
Barr, R, Kramer, M, Boisjoly, C, McVey-White, L, Pless, I. Parental diary of infant cry and fuss behaviour. Arch Dis Childhood. 1988; 63(4), 380–387.CrossRefGoogle ScholarPubMed
Achenbach, TM. The child behavior checklist and related instruments. In The Use of Psychological Testing for Treatment Planning and Outcomes Assessment (ed. Maruish, ME), 1999; pp. 429–466. Lawrence Erlbaum Associates Publishers, NJ, USA.Google Scholar
Petty, CR, Rosenbaum, JF, Hirshfeld-Becker, DR, et al. The child behavior checklist broad-band scales predict subsequent psychopathology: A 5-year follow-up. J Anxiety Disord. 2008; 22, 532–539.CrossRefGoogle ScholarPubMed
Prochaska, JJ, Sung, H-Y, Max, W, Shi, Y, Ong, M. Validity study of the K6 scale as a measure of moderate mental distress based on mental health treatment need and utilization. Int J Methods Psychiatr Res. 2012; 21(2), 88–97.CrossRefGoogle ScholarPubMed
Anders, S, Huber, W. Differential expression analysis for sequence count data. Genome Biol. 2010; 11(10), R106.CrossRefGoogle ScholarPubMed
Gloor, GB, Macklaim, JM, Pawlowsky-Glahn, V, Egozcue, JJ. Microbiome datasets are compositional: and this is not optional. Front Microbiol. . 2017; 8, 1–6.CrossRefGoogle Scholar
Magurran, AE. Measuring Biological Diversity, 2013. John Wiley & Sons.Google Scholar
Quinn, T, Tylee, D, Glatt, S. exprso: an R-package for the rapid implementation of machine learning algorithms. F1000Res. 2016; 5, 2588.CrossRefGoogle ScholarPubMed
Palarea-Albaladejo, J, Martin-Fernandez, JA. zCompositions—R package for multivariate imputation of left-censored data under a compositional approach. Chemom Intell Lab Syst. 2015; 143, 85–96.CrossRefGoogle Scholar
Fernandes, AD, Reid, JNS, Macklaim, JM, McMurrough, TA, Edgell, DR, Gloor, GB. Unifying the analysis of high-throughput sequencing datasets: characterizing RNA-seq, 16S rRNA gene sequencing and selective growth experiments by compositional data analysis. Microbiome. 2014; 2(1), 15.CrossRefGoogle ScholarPubMed
Quinn, TP, Erb, I, Gloor, G, Notredame, C, Richardson, MF, Crowley, TM. A field guide for the compositional analysis of any-omics data. GigaScience. 2019; 8(9).CrossRefGoogle ScholarPubMed
Liaw, A, Wiener, M. Classification and regression by randomForest. R news. 2002; 2(3), 18–22.Google Scholar
Sing, T, Sander, O, Beerenwinkel, N, Lengauer, T. ROCR: visualizing classifier performance in R. Bioinformatics. 2005; 21(20), 3940–3941.CrossRefGoogle ScholarPubMed
Lehtonen, L, Korvenranta, H, Eerola, E. Intestinal microflora in colicky and noncolicky infants: bacterial cultures and gas-liquid chromatography. J Pediatr Gastroenterol Nutr. 1994; 19(3), 310–314.CrossRefGoogle ScholarPubMed
Pärtty, A, Kalliomäki, M, Salminen, S, Isolauri, E. Infantile colic is associated with low-grade systemic inflammation. J Pediatr Gastroenterol Nutr. 2017; 64(5), 691–695.CrossRefGoogle ScholarPubMed
Zeevenhooven, J, Browne, PD, L’Hoir, MP, de Weerth, C, Benninga, MA. Infant colic: mechanisms and management. Nat Rev Gastroenterol Hepatol. 2018; 15, 479–496.CrossRefGoogle ScholarPubMed
Chichlowski, M, Guillaume De Lartigue, J, Raybould, HE, Mills, DA. Bifidobacteria isolated from infants and cultured on human milk oligosaccharides affect intestinal epithelial function. J Pediatr Gastroenterol Nutr. 2012; 55(3), 321.CrossRefGoogle ScholarPubMed
Salli, K, Anglenius, H, Hirvonen, J, et al. The effect of 2′-fucosyllactose on simulated infant gut microbiome and metabolites; a pilot study in comparison to GOS and lactose. Sci Rep. 2019; 9(1), 13232.CrossRefGoogle ScholarPubMed
Pham, VT, Lacroix, C, Braegger, CP, Chassard, C. Lactate-utilizing community is associated with gut microbiota dysbiosis in colicky infants. Sci Rep. 2017; 7(1), 1–13.CrossRefGoogle ScholarPubMed
Duvallet, C, Gibbons, SM, Gurry, T, Irizarry, RA, Alm, EJ. Meta-analysis of gut microbiome studies identifies disease-specific and shared responses. Nat Commun. 2017; 8.Google ScholarPubMed
Gardner, F, Shaw, DS. Behavioral problems of infancy and preschool children (0–5). Rutter’s Child Adolesc Psychiat. 2008; 5, 662–893.Google Scholar
de Weerth, C, Fuentes, S, de Vos, WM. Crying in infants: on the possible role of intestinal microbiota in the development of colic. Gut Microbes. 2013; 4(5), 416–421.CrossRefGoogle ScholarPubMed
Roos, S, Dicksved, J, Tarasco, V, et al. 454 pyrosequencing analysis on faecal samples from a randomized DBPC trial of colicky infants treated with Lactobacillus reuteri DSM 17938. PLoS One. 2013; 8(2), e56710.CrossRefGoogle ScholarPubMed
Pärtty, A, Kalliomäki, M, Endo, A, Salminen, S, Isolauri, E. Compositional development of Bifidobacterium and Lactobacillus microbiota is linked with crying and fussing in early infancy. PLoS One. 2012; 7(3), e32495.CrossRefGoogle ScholarPubMed
Pärtty, A, Kalliomäki, M, Wacklin, P, Salminen, S, Isolauri, E. A possible link between early probiotic intervention and the risk of neuropsychiatric disorders later in childhood: a randomized trial. Pediatr Res. 2015; 77, 823–828.CrossRefGoogle ScholarPubMed
de Weerth, C, Fuentes, S, Puylaert, P, de Vos, WM. Intestinal microbiota of infants with colic: dDevelopment and specific signatures. Pediatrics. 2013; 131, e550–e558.CrossRefGoogle Scholar
Savino, F, Cordisco, L, Tarasco, V, et al. Antagonistic effect of Lactobacillus strains against gas-producing coliforms isolated from colicky infants. BMC Microbiol. 2011; 11, 157.CrossRefGoogle ScholarPubMed
Mentula, S, Tuure, T, Koskenala, R, Korpela, R, Könönen, E. Microbial composition and fecal fermentation end products from colicky infants – a probiotic supplementation pilot. Microbial Ecol Health Dis. 2008; 20(1), 37–47.CrossRefGoogle Scholar
Rhoads, JM, Fatheree, NY, Norori, J, et al. Altered fecal microflora and increased fecal calprotectin in infants with colic. J Pediatr. 2009; 155(6), 823–828. e821.CrossRefGoogle ScholarPubMed
Savino, F, Bailo, E, Oggero, R, et al. Bacterial counts of intestinal Lactobacillus species in infants with colic. Pediatr Allergy Immunol. 2005; 16(1), 72–75.CrossRefGoogle ScholarPubMed
Savino, F, Cresi, F, Pautasso, S, et al. Intestinal microflora in breastfed colicky and non-colicky infants. Acta Paediatr. 2004; 93(6), 825–829.CrossRefGoogle ScholarPubMed
Supplementary material: File

Loughman et al. supplementary material

Loughman et al. supplementary material

Download Loughman et al. supplementary material(File)
File 1.3 MB