@inproceedings{01HZP7Y5BNP7J9A38KP7FNEP6M,
  abstract     = {{Introduction: The rising incidence of pediatric overweight and obesity, accompanied by detrimental effects on psychosocial and metabolic development, is a significant public health concern. This condition not only impairs the current health and functionality of children but also predisposes them to numerous health issues in adulthood. Understanding the mechanisms underlying overweight and obesity is crucial for developing effective therapeutic and preventive strategies. Salivary metabolomics has emerged in recent years because of its noninvasive and painless collection procedures as well as its simple storage and handling requirements.

Approach: In this study, we aimed to investigate the impact of anthropometrics and diet on the salivary metabolome. To this end, we analyzed 442 saliva samples collected from children aged 11-17 years (FAME cohort). The analysis was conducted using our fully validated ultra-high performance liquid chromatography coupled to high-resolution Orbitrap mass spectrometry methodology (Wijnant et al., 2020). To obtain detailed information on the participants' long-term dietary habits, each participant was provided with a food frequency questionnaire comprising 52 diverse food items. Additionally, multiple anthropometric measurements were taken to assess the participants' physical characteristics. These data were then correlated (Spearman’s max. absolute rho values reported below) with the salivary metabolic features (n = 8913) to identify those features that exhibited significant interactions with specific anthropometric measures (|rho|>0.30) or food items (|rho|>0.35).

Results: Of the anthropometric measures, fat percentage and waist displayed the highest correlations of respectively 0.32 and 0.33. Interestingly, fat-rich foods exhibited strong correlations, including pizza (0.47), savory snacks (0.43), fast food meat (0.42), spreadable and melted cheese (0.42), fried or baked potatoes (0.38), eggs prepared with fat (0.36), fish prepared with fat (0.42), and snacks in general (0.36). Additionally, sugar-rich foods showed significant correlations, such as dried fruits (0.45), store-bought fruit juice with 100% fruit (0.42), fresh fruits with added sugars (0.36), non-carbonated drinks sweetened with sugar (0.45), sweetened milk (0.43), sweetened yogurt (0.37), and jam/honey (0.38). Higher correlations were also noted for legumes (0.42), meat replacement products (0.36), fish (0.44), and eggs prepared without fat (0.42). Metabolic features with the highest correlations within the overweight/obesity or normal weight groups will be annotated in the next months and presented during the meeting.

Discussion: Understanding the metabolic background of these correlations, will allow us to determine to which extent different food items contribute to children’s weight status, and facilitate the development of personalized targeted dietary interventions and preventive strategies to combat pediatric overweight and obesity.}},
  author       = {{Callemeyn, Emile and De Paepe, Ellen and Vangeenderhuysen, Pablo and Michels, Nathalie and De Henauw, Stefaan and Geerts, Anja and Vanhaecke, Lynn}},
  booktitle    = {{Benelux Metabolomics Days 2024, Abstracts}},
  keywords     = {{Metabolomics,childhood obesity}},
  language     = {{eng}},
  location     = {{Ghent, Belgium}},
  title        = {{Determining the drivers of pediatric overweight and obesity : how does the salivary metabolome reflect children’s anthropometrics and dietary intake?}},
  year         = {{2024}},
}