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.
Are All Breast-fed Infants Equal? Clustering Metabolomics Data to Identify Predictive Risk Clusters for Childhood Obesity / F. Kirchberg, V. Grote, D. Gruszfeld, P. Socha, R. Closa-Monasterolo, J. Escribano, E. Verduci, B. Mariani, J. Langhendries, P. Poncelet, B. Koletzko, C. Hellmuth. - In: JOURNAL OF PEDIATRIC GASTROENTEROLOGY AND NUTRITION. - ISSN 0277-2116. - 68:3(2019 Mar), pp. 408-415.
Are All Breast-fed Infants Equal? Clustering Metabolomics Data to Identify Predictive Risk Clusters for Childhood Obesity
E. Verduci;B. Mariani;
2019
Abstract
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.File | Dimensione | Formato | |
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