Comparative analysis of the gut microbiomein children with obesity and normal weight

ORIGINAL STUDIES

Keywords:
intestinal microbiota childhood obesity artificial intelligence machine learning Random Forest biomarkers кишечная микробиота детское ожирение искусственный интеллект машинное обучение Случайный лес биомаркеры

Abstract

Background.Current research indicates a significant influence of gut microbiota on the development and maintenance of obesity in children. Analyzing the relationships between gut microbial composition and obesity requires the application of high-precision modern methods of data processing, including artificial intelligence technologies.

Aim.To characterize the taxonomic structure of the gut microbiota in children aged 6–9 years with obesity compared to peers with normal body weight and to assess the associations of key taxa with SDS body mass index (BMI).

Materials and methods.203 children, including 154 with obesity and 49 with normal body weight, were included in the study. The microbial composition of the large intestine was investigated by real-time polymerase chain reaction (PCR) (ENTEROFLOR Children kit). Biostatistical analysis included calculation of alpha- and beta-diversity indices (Shannon, Simpson, Bray–Curtis), ANOSIM (Analysis of Similarities), PCA (Principal Coordinate Analysis) and the Random Forest algorithm. Associations between taxa and body mass index (SDS BMI) were tested using correlation analysis (Spearman and Pearson).

Results.Alpha diversity of microbiota in obese children and controls had no statistically significant differences (p=0.288 for Shannon index; p=0.411 for Simpson index). However, beta diversity analysis using the Bray–Curtis metric and ANOSIM method established significant differences in the taxonomic structure of microbial communities between the groups (R coefficient = 0.138, p=0.002).

Using the “Random Forest” algorithm, nine significant microbiome biomarkers associated with the disease were identified:Prevotellaspp., Enterobacterales, and theDialister group, Allisonella, Megasphaera,andVeillonellawere positively correlated with obesity, whileAkkermansia muciniphilaandCandidaspp. showed negative associations. The sensitivity of the model was 100%, specificity — 81,25%.

Conclusions.In children aged 6–9 years with obesity, the gut microbiota is characterized by structural alterations while maintaining alpha diversity. The key microbiome markers of obesity arePrevotellaspp.,Enterobacterales, and the groupDialister + Allisonella + Megasphaera + Veillonella, whereasAkkermansia muciniphilaandCandidaspp. show protective associations. The use of machine learning methods confirmed the informativeness of these taxa and their significance for early diagnosis and prognosis of childhood obesity.

Author Biographies

Olga P. Kovtun, Ural State Medical University

MD, Ph D, Dr Med Sci, President

Margarita A. Ustiuzhanina, Ural State Medical University

MD, Ph D, Associate Professor, Department of Outpatient Pediatrics

Svyatoslav I. Solodushkin, Ural Federal University named after the first President of Russia B.N. Yeltsin

Ph D, Associate Professor,
Department of Computational Mathematics and Computer
Science

Ekaterina S. Voroshilina, Ural State Medical University

MD, Ph D, Dr Med Sci, Professor, Head, Department of Medical Microbiology and Clinical Laboratory Diagnostics

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