Using compositional principal component analysis to describe children’s gut microbiota in relation to diet and body composition

• Published in: The American journal of clinical nutrition 2020-01, Vol.111 (1), p.70-78
• Main Authors: Leong, Claudia, Haszard, Jillian J, Heath, Anne-Louise M, Tannock, Gerald W, Lawley, Blair, Cameron, Sonya L, Szymlek-Gay, Ewa A, Gray, Andrew R, Taylor, Barry J, Galland, Barbara C, Lawrence, Julie A, Otal, Anna, Hughes, Alan, Taylor, Rachael W
• Format: Article
• Language: English
• Subjects: Bacteria - classification; Bacteria - genetics; Bacteria - isolation & purification; Body Composition; Body size; Body Weight; Breast feeding; Child, Preschool; Children; compositional analysis; Cross-Sectional Studies; Diet; Dietary Fiber - metabolism; DNA sequencing; Dual energy X-ray absorptiometry; Feces - microbiology; Female; Food composition; Gastrointestinal Microbiome; gut microbiota; Humans; Intestinal microflora; Legumes; Male; Mathematical analysis; Microbiota; Non-starch polysaccharides; Nutrition; Nutrition research; Nuts; Nuts - metabolism; Polysaccharides; Principal Component Analysis; Principal components analysis; Saccharides; Seeds; Taxa; Vegetables - metabolism
• ISSN: 0002-9165; 1938-3207
• DOI: 10.1093/ajcn/nqz270

Gut microbiota data obtained by DNA sequencing are complex and compositional because of large numbers of detectable taxa, and because microbiota characteristics are described in relative terms. Nutrition researchers use principal component analysis (PCA) to derive dietary patterns from food data. Although compositional PCA methods are not commonly used to describe patterns from complex microbiota data, this approach would be useful for identifying gut microbiota patterns associated with diet and body composition. To use compositional PCA to describe the principal components (PCs) of gut microbiota in 5-y-old children and explore associations between microbiota components, diet, and BMI z-score. A fecal sample was provided by 319 children aged 5 y. Their primary caregiver completed a validated 123-item quantitative FFQ. Body composition was determined using DXA, and a BMI z-score was calculated. Compositional PCA identified characterizing taxa and weightings for calculation of gut microbiota PC scores at the genus level, and was examined in relation to diet and body size. Three gut microbiota PCs were found. PC1 (negative loadings on uncultured Christensenellaceae and Ruminococcaceae) was related to lower BMI z-scores and longer duration of breastfeeding (per month) (β = −0.14; 95% CI: −0.26, −0.02; and β = 0.02; 95% CI: 0.003, 0.34, respectively). PC2 (positive loadings on Fusicatenibacter and Bifidobacterium; negative loadings on Bacteroides) was associated with a lower intake of nuts, seeds, and legumes (β = −0.05 per gram; 95% CI: −0.09, −0.01). When adjusted for fiber intake, PC2 was also associated with higher BMI z-scores (β = 0.12; 95% CI: 0.01, 0.24). PC3 (positive loadings on Faecalibacterium, Eubacterium, and Roseburia) was associated with higher intakes of fiber (β = 0.02 per gram; 95% CI: 0.003, 0.04) and total nonstarch polysaccharides (β = 0.02 per gram; 95% CI: 0.003, 0.04). Our results suggest that specific gut microbiota components determined using compositional PCA are associated with diet and BMI z-score. This trial was registered at clinicaltrials.gov as NCT00892983.