ECE2021 Audio Eposter Presentations Diabetes, Obesity, Metabolism and Nutrition (223 abstracts)
The ecology of the microbiome in children with obesity is associated to insulin resistance anddiet composition
Roberta Ricotti 1 , Francesca Archero 1 , Valentina Landoni 1 , Valentina Mancioppi 1 , Marina Caputo 2 , Simonetta Bellone 1 , Arianna Solito 1 , Valentina Antoniotti 1 , Elisa Gamalero 3 , Nadia Massa 3 , Flavio Mignone 3 , 4 , 5 , Maria Cavaletto 3 , Emanuela Agosti 6 , Elisa Bona 3 , 5 & Flavia Prodam 2 & 6
1Università del Piemonte Orientale, SCDU Pediatrics, Department of Health Sciences, Novara, Italy; 2Università del Piemonte Orientale, Endocrinology Unit, Department of Translational Medicine, Novara, Italy; 3Università del Piemonte Orientale, Department of Sciences and Technological Innovation, Vercelli, Italy; 4SmartSeq S.R.L., spin-off of the Università del Piemonte Orientale, Novara, Italy; 5UPO-CAAD- Center of Translational Research on Autoimmune and Allergic Disease, Novara, Italy; 6Università del Piemonte Orientale, Department of Health Sciences, Novara, Italy
Introduction
In the pediatric population, the progression of obesity-related diseases can be delayed or prevented through lifestyle changes, including the promotion of a Mediterranean-like dietary (MD) pattern.
Objective
We aimed to evaluate the gut microbiome ecology in relation to dietary and clinical parameters in the pediatric subjects with obesity recruited at baseline in a protocol on an educational training to MD.
Methods
A total of 55 subjects (6 and 18 years) with obesity, diet naïve or with failure to a previous weight loss program were recruited. We collected auxological, metabolic, nutritional parameters (KIDMED score; IDEFICS food frequency questionnaire), and stool samples. DNA was extracted directly from 0.25 g of stool using the Power SoilKit. DNA was amplified with primers for the V3 and V6 regions of 16S rDNA tagged with Multiplex Identifier sequences using Microbiota Solution B Kit optimized for Illumina Miseq sequencing. Raw FastQ sequences were analyzed using MicrobAT Software. Statistical analyses were performed using R software.
Results
All the 55 subjects showed a Bacteroides enterotype: 38% Bacteroidetes, 34% Firmicutes, 22% Unclassified Bacteria, 4% Actinobacteria, 1% Proteobacteria. At baseline, clinical and metabolic characteristics were homogeneous among children while microbial communities associated with the different subjects showed statistically significant differences according to age, Tanner stage considering sex, fasting insulin levels, fasting insulin resistance (HOMA-IR 95° percentile), percentage of carbohydrates, and fiber intake with the diet. In particular, considering HOMA-IR, Bifidobacterium pseudocatenulatum, unclassified Faecalibacterium, Bifidobacterium sp., Unclassified Sutterella, and unclassified Blautia were correlated with higher insulin resistance while Dialister invisus and Barnesiella sp. were associated with lower insulin resistance. Moreover, we observed Bacteroides dorei, Bacteroides vulgatus, Unclassified Ruminococcaceae, and unclassified Faecalibaterium associated with a higher carbohydrate intake. Finally, with a greater daily intake of fibers (> 8.5 g/1000 Kcal) we observed a decrease in Unclassified Faecalibacterium and an increase in Ruminococcus bromii, Gemmiger fomicilis, and Prevotella sp.
Discussion
These preliminary results highlight as diet, insulin sensitivity, and microbiome are strictly related also in children with obesity. We identified several bacterial groups not previously described in obesity. These findings are of importance for clustering patients and studying tailored dietary programs.
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Endocrine Abstracts
ISSN 1470-3947 (print) | ISSN 1479-6848 (online)
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