Are All Breast‐fed Infants Equal? Clustering Metabolomics Data to Identify Predictive Risk Clusters for Childhood Obesity

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 ¼ 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 ¼ 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.

The Triad Mother-Breast Milk-Infant as Predictor of Future Health: A Narrative Review

“…De Luca et al aimed to compare breast-milk composition of obese versus normal-weight mothers. In their cross-sectional observational study, they found a higher amount of leptin in breast milk of obese mothers, whereas breast milk was not different in terms of protein, lipid, and carbohydrate composition and volume [ 137 , 138 ]. Leptin content has also been positively correlated with higher weight gain in infants and increased adiposity as far as 12 months of lactation.…”

Detailed knowledge of maternal and infant factors and human milk composition could inform recommendations for optimal composition

“…Kirchberg et al grouped plasma metabolomic profiles of breastfed infants using Bayesian agglomerative clustering 27 . Clustering was predominantly determined by the levels of phosphatidylcholines and sphingomyelins, which suggests that lipoprotein metabolism was an important determinant 27 . Differences in human milk fatty acid composition may also have contributed to the differentiation between clusters.…”

Metabolomics in Radiation Biodosimetry: Current Approaches and Advances

“…Predictive metabolomics-At one extreme of the predictive use of metabolomics is research that looks at metabolomic profiles in children (e.g.,-children who were breast-fed versus those that were not) [108], to determine if there is a signature present at a young age that could be used to predict some later aspect of health and development. The reports of prospective use of these kinds are markers are varied in scope, but a small sampling of the literature finds studies that indicate that there are also signatures that contain predictive markers of the progression of amyotrophic lateral sclerosis [109], bone mass in menopausal women [110] and a proclivity towards the development of major depression [87].…”