ESPE2018 Poster Presentations Fat, Metabolism and Obesity P1 (42 abstracts)
aCentre de Recherche du CHU Sainte Justine, Montréal, Canada; bDivision of Endocrinology, Department of Pediatrics, CHU Sainte-Justine and Université de Montréal, Montréal, Canada; cIngram School of Nursing, McGill University, Montréal, Canada; dDepartment of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Canada; eEpidemiology and Biostatistics Unit, Centre INRS - Institut Armand-Frappier, Laval, Canada; fDepartment of Physical Education, Université Laval, Québec, Canada; gDepartment of Kinesiology, Université de Montréal, Montréal, Canada; hDepartment of Dentistry, McGill University, Montréal, Canada; iDepartment of Medicine, IUCPQ and INAF, Université Laval, Québec, Canada
Background: Dietary intake has been shown to influence the composition and diversity of the gut microbiota in adults, however its impact in childhood and adolescence remains uncertain. Moreover, the impact of other lifestyle behaviors such as physical activity, sedentary behaviors, sleep and fitness on the gut microbiota has rarely been investigated.
Objective: To explore the correlations between intestinal microbiota composition and measures of diversity among 1517 year-old adolescents with a family history of obesity and 1. lifestyle habits at 1517 years; 2. lifestyle habits in earlier childhood.
Methods: Data stem from the QUALITY cohort, a prospective cohort study of 630 children with a parental history of obesity. Lifestyle habits were assessed at 810 years, 1012 years and 1517 years, including: physical activity by 7-day accelerometry, self-reported screen time, dietary intake (at 810 and 1517 years only) by 3 non-consecutive 24h dietary recalls, and self-reported sleep duration. Fitness was measured by VO2peak. 16S-rRNA based microbial profiling of stool samples obtained from 22 participants at 1517 years (14 normal weight, 6 overweight and 2 obese) were performed to determine composition and diversity of the gut microbiota. Measures of diversity include Shannon, Simpson, Chao1 and Observed OTU indices. Pearsons correlations assessed associations between diversity indices and lifestyle habits.
Results: Fitness at 1517 years was positively correlated with measures of diversity (r=0.330.41 across all indices). More importantly, statistically significant positive correlations were noted between fitness at 1012 years and greater microbiotal diversity 5 years later (Shannon r=0.70, P=0.001; Simpson r=0.51, P=0.03; Obs OTU r=0.50, P=0.036). Physical activity and screen time were not associated with microbiota diversity. Both total dietary fat intake and saturated fat intake at 1517 years were negatively correlated with the Simpson index (r=−0.50, P=0.019 and r=−0.43, P=0.046, respectively). Similar, not quite statistically significant, negative correlations between total and saturated fat consumption at 810 years and measures of diversity at 1517 years were also noted. At both 810 years and 1517 years, percent carbohydrate intake was positively correlated with the Simpson index (r=0.43, P=0.049 and r=0.49, P=0.021, respectively). Finally, sleep duration at 1012 years tended to positively correlate with indices of diversity at 1517 years, the strongest correlation being with the Shannon index (r=0.39, P=0.08).
Conclusions: These preliminary findings from a small sample of children followed over 8 years suggest that microbiome diversity in late adolescence may be modulated by lifestyle habits, even in earlier childhood.