High throughput amino acid and acylcarnitine profiling in infant serum by means of LC-MS/MSMRM for the elucidation of early-life obesity risk

Date
March 20, 2022

Obesity has become a global pandemic in recent years. Alongside the increasing number of obese adults, also the rate of overweight and obese children has reached alarming levels. These developments pose a significant financial burden on health systems due to the rising incidence of associated non-communicable diseases, such as diabetes and cardiovascular diseases. Therefore, it is essential to understand the metabolic alterations towards overweight development already at an early stage of life. Associations between early-life risk factors such as high pre-conceptional maternal BMI and long-term offspring health outcomes have been identified successfully. However, the metabolic processes underlying these factors have not been clarified to date, mainly due to the low metabolite concentrations and the resulting analytical challenges.
To gain more comprehensive knowledge on obesity and nutrition related pathways, a sensitive and reliable multi-analyte hydrophilic interaction liquid chromatography (HILIC)-MS/MS method was developed for infant serum. A fast and derivatization-free sample preparation was established using minimum amounts of serum from 3 to 4-month-old infants of the prospective mother-child cohort PEACHES (Programming of Enhanced Adiposity Risk in CHildhood–Early Screening) and facilitating high throughput analysis. By means of the multiple reaction monitoring (MRM) mode and isotopically labelled standards, ∑ 62 serum metabolites, in particular 40 amino acids and derivatives as well as 22 acylcarnitines, could be quantified precisely within a single 20 minutes run. 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. This profiling method enabled the derivation of different infant metabotypes in combination with the characterization of nutrition related metabolites and thus provides a basis for investigating metabolic risk for overweight development already early in life.

Presenter

Speakers

Speaker Image for Andreas Dunkel
Leibniz-Institut fur Lebensmittel-Systembiologie an der Technischen Universitat Munchen

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