title: Linear growth faltering in infants is associated with Acidaminococcus sp. and community-level changes in the gut microbiota.
abstract: BACKGROUND
  Chronic malnutrition, termed stunting, is defined as suboptimal linear growth, affects one third of children in developing countries, and leads to increased mortality and poor developmental outcomes. The causes of childhood stunting are unknown, and strategies to improve growth and related outcomes in children have only had modest impacts. Recent studies have shown that the ecosystem of microbes in the human gut, termed the microbiota, can induce changes in weight. However, the specific changes in the gut microbiota that contribute to growth remain unknown, and no studies have investigated the gut microbiota as a determinant of chronic malnutrition.
  
  
  RESULTS
  We performed secondary analyses of data from two well-characterized twin cohorts of children from Malawi and Bangladesh to identify bacterial genera associated with linear growth. In a case-control analysis, we used the graphical lasso to estimate covariance network models of gut microbial interactions from relative genus abundances and used network analysis methods to select genera associated with stunting severity. In longitudinal analyses, we determined associations between these selected microbes and linear growth using between-within twin regression models to adjust for confounding and introduce temporality. Reduced microbiota diversity and increased covariance network density were associated with stunting severity, while increased relative abundance of Acidaminococcus sp. was associated with future linear growth deficits.
  
  
  CONCLUSIONS
  We show that length growth in children is associated with community-wide changes in the gut microbiota and with the abundance of the bacterial genus, Acidaminococcus. Larger cohorts are needed to confirm these findings and to clarify the mechanisms involved.
authors.affiliation: Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, H3A 1A2, QC Canada.
authors.forename: Ethan K
authors.initials: EK
authors.lastname: Gough
authors.affiliation: Department of Mathematics and Statistics, McGill University, Montreal, H3A 2K6, QC Canada.
authors.forename: David A
authors.initials: DA
authors.lastname: Stephens
authors.affiliation: Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, H3A 1A2, QC Canada.
authors.forename: Erica E M
authors.initials: EE
authors.lastname: Moodie
authors.affiliation: Centre for Paediatrics, Blizard Institute, Queen Mary University of London, London, E1 2AT UK ; Zvitambo Institute for Maternal Child Health Research, Harare, Zimbabwe.
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Prendergast
authors.affiliation: Program in International Nutrition, Division of Nutritional Sciences, Cornell University, Ithaca, NY 14853 USA.
authors.forename: Rebecca J
authors.initials: RJ
authors.lastname: Stoltzfus
authors.affiliation: Zvitambo Institute for Maternal Child Health Research, Harare, Zimbabwe ; Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 USA.
authors.forename: Jean H
authors.initials: JH
authors.lastname: Humphrey
authors.affiliation: Faculty of Medicine, School of Population and Public Health, University of British Columbia, 137-2206 East Mall, Vancouver, V6T 1Z3, BC Canada.
authors.forename: Amee R
authors.initials: AR
authors.lastname: Manges
keywords: Growth; Intestinal; Microbiome; Microbiota; Networks; Statistical learning; Stunting