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Published on: January 9, 2014
Are All Breast-fed Infants Equal? Clustering Metabolomics Data to Identify Predictive Risk Clusters for Childhood
Franca Fabiana Kirchberg1, Veit Grote1, Dariusz Gruszfeld2
1Ludwig-Maximilians-Universität München, Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Munich, Germany.
Insights
Infants show distinct metabolic profiles (metabotypes) at 6 months, influenced by factors like phosphatidylcholines. These metabotypes may predict later obesity risk, enabling personalized early health strategies.
Area of Science:
- Metabolomics and Developmental Biology
- Pediatric Health and Nutrition
- Personalized Medicine
Background:
- Early life metabolic programming is influenced by environmental and nutritional factors.
- Understanding metabolic heterogeneity in infants is crucial for predicting long-term health outcomes.
- Metabolic pathways undergo significant modification during fetal and early development.
Purpose of the Study:
- To explore metabolic clustering (metabotypes) in 6-month-old breast-fed infants.
- To investigate if identified metabotypes can predict later obesity risk up to 6 years of age.
- To identify underlying factors associated with infant metabotypes.
Main Methods:
- Analysis of plasma samples from 183 breast-fed infants (6 months old).
- Measurement of amino acids and polar lipids (e.g., phosphatidylcholines).
- Application of Bayesian agglomerative clustering to determine metabotypes and assess associations with clinical data up to age 6.
Main Results:
- Identification of 20 distinct metabolite clusters (metabotypes).
- Phosphatidylcholines were key drivers of infant clustering.
- Significant differences in birth length, weight, and length at 6 months were observed between clusters, with trends for differing BMI z-scores at 6 years.
Conclusions:
- Breast-fed infants exhibit metabolic heterogeneity, not a homogeneous metabolic profile.
- Infant metabotypes offer insights into later developmental trajectories and health.
- Metabotypes hold potential for developing personalized early preventive strategies against diseases like obesity.
Objectives:
Fetal and early life represent a period of developmental plasticity during which metabolic pathways are modified by environmental and nutritional cues. Little is known on the pathways underlying this multifactorial complex. We explored whether 6 months old breast-fed infants could be clustered into metabolically similar groups and that those metabotypes could be used to predict later obesity risk.
Methods:
Plasma samples were obtained from 183 breast-fed infants aged 6 months participating in the European multicenter Childhood Obesity Project study. We measured amino acids along with polar lipid concentrations (acylcarnitines, lysophosphatidylcholines, phosphatidylcholines, sphingomyelins). We determined the metabotypes using a Bayesian agglomerative clustering method and investigated the properties of these clusters with respect to clinical, programming, and metabolic factors up to 6 years of age.
Results:
We identified 20 metabolite clusters comprising 1 to 39 children. Phosphatidylcholines predominantly influenced the clustering process. In the largest clusters (n ≥ 14), large differences existed for birth length (unadjusted P < 0.0001) and length and weight at 6 months (unadjusted P < 0.0001 and P = 0.012, respectively). Infants tended to cluster together by country (unadjusted P < 0.001). The body mass index (BMI) z score at 6 years of age tended to differ (unadjusted P = 0.07).
Conclusions:
Our exploratory study provided evidence that breast-fed infants are not metabolically homogeneous and that variation in metabolic profiles among infants may provide insight into later development and health. This work highlights the potential of metabotypes for identifying inter-individual differences that may form the basis for developing personalized early preventive strategies.
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