ESPE2019 Poster Category 1 Fat, Metabolism and Obesity (25 abstracts)
Put Your Money Where Your Mouth is: Preliminary Evidence that Oral Microbiota Diversity may Shape Later Cardiometabolic Health in Children
Mélanie Henderson 1,2 , Belinda Nicolau 3 , Andraea Van Hulst 3 , Gabrielle Simoneau 1,3 , Tracie A. Barnett 1,4 , Vicky Drapeau 5 , Angelo Tremblay 5 , Marie-Ève Mathieu 2 , Gilles Paradis 3 , Michael Zappitelli 6 , Thibaut Varin 7,5 & André Marette 7,5
1CHU Sainte-Justine, Montréal, Canada. 2Université de Montréal, Montréal, Canada. 3McGill University, Montréal, Canada. 4Centre INRS - Institut Armand-Frappier, Laval, Canada. 5Université Laval, Québec, Canada. 6University of Toronto, Toronto, Canada. 7IUCPQ, Québec, Canada
Background: Emerging evidence suggests a link between the intestinal microbiota and cardiometabolic outcomes in both children and adults. The oral microbiota is less studied, and the association between the oral microbiota and cardiometabolic health in childhood remains largely unknown.
Objective: To explore the associations between oral microbiota diversity measured at 8-10 yr and cardiometabolic health in childhood and adolescence.
Methods: Data stem from the QUALITY cohort, a prospective cohort study of 630 children aged 8-10 years at recruitment, with a parental history of obesity. 16S-rRNA based microbial profiling of oral plaque samples obtained at baseline from 80 participants (40 normal weight, 40 overweight/obese) were performed to determine diversity of the oral microbiota. Measures of diversity include Observed OTUs, Chao1, Shannon and Simpson reciprocal indices. Measures of cardiometabolic health were assessed at 8-10 yrs, 10-12 yrs and 15-17 yrs, and include: fasting blood glucose, glucose 2hr post oral glucose load, homeostasis model of assessment (HOMA-IR), lipid profile (LDL cholesterol, HDL cholesterol and triglycerides), as well as age-, sex-, height-adjusted systolic (zSBP) and diastolic (zDBP) blood pressure z-scores. Pearson's correlations were used to estimate associations between diversity indices and cardiometabolic outcomes.
Results: LDL cholesterol at 8-10 yr was positively correlated with all indices of microbiota diversity (Obs OTUs r=0.23, P=0.046; Chao1 r=0.22, P=0.055; Shannon r=0.24, P=0.035; Simpson reciprocal r=0.22, P=0.049). While correlations remained positive for LDL measured at 10-12 yr and 15-17 yr, they did not reach statistical significance. Similarly, microbiota diversity was positively correlated with zSBP at 8-10 yrs (r=0.22–0.25) and 10-12 yrs (r=0.22–0.25), not reaching statistical significance at 15-17 yrs. Indices of diversity at 8-10 yr were negatively correlated with fasting glucose (r=–0.27 to –0.31) and glucose 2hr post load (r=–0.27 to –0.29) 7 years later (at 15-17 yrs). Microbiota diversity was not correlated with HOMA-IR.
Conclusions: These preliminary data in a small sample of children followed over 7 years suggest that oral microbiota diversity in early childhood may influence cardiometabolic health in later adolescence.
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