Obesity has become a global pandemic, significantly burdening healthcare systems due to the rising incidence of associated non-communicable diseases. To prevent this development it is essential to understand the early onset of obesity already at an early stage of life. Early-life risk factors such as high maternal preconception body mass index (BMI) and limited breastfeeding have been identified to affect long-term health outcomes in offspring, including metabolic disorders and obesity. However, the underlying metabolic mechanisms remain poorly understood, notably due to analytical challenges arising from low metabolite levels.
To investigate the metabolic processes linked to obesity and nutrition, we developed a sensitive multi-analyte hydrophilic interaction liquid chromatography (HILIC)-MS/MS method for infant serum analysis. Using micro volumes of serum (25 µL), we developed a derivatization-free sample preparation technique suitable for high-throughput analysis. A total of 62 serum metabolites, comprising 40 amino acids and their derivatives, as well as 22 acylcarnitines, were accurately quantified within a 20-minute run using isotopically labeled standards and multiple reaction monitoring. Comprehensive method validation utilizing reference control serum and covering parameters such as matrix effects, precision and accuracy, highlighted the applicability of this multi-analyte method.
Our profiling method was applied to serum samples from 1,246 three-month-old infants enrolled in the PEACHES cohort study. We identified distinct patterns of amino acids and acylcarnitines related to maternal BMI and breastfeeding. Specific metabolites, such as valine, 2-aminobutyric acid, and 2-aminoadipic acid, were predictive of a higher BMI development at preschool-age. Notably, valine was identified as a key mediator between breastfeeding and BMI. Integrating metabolic, clinical, and demographic data from early infancy enabled individual risk prediction of BMI development during preschool-age.