The impact of human breast milk components on the infant metabolism

Background & aims Breastfeeding is beneficial for mothers and infants. Underlying mechanisms and biochemical mediators thus need to be investigated to develop and support improved infant nutrition practices promoting the child health. We analysed the relation between maternal breast milk composition and infant metabolism. Methods 196 pairs of mothers and infants from a European research project (PreventCD) were studied. Maternal milk samples collected at month 1 and month 4 after birth were analysed for macronutrient classes, hormone, and fatty acid (FA) content. Phospholipids, acylcarnitines, and amino acids were measured in serum samples of 4-month old infants. Associations between milk components and infant metabolites were analysed with spearman correlation and linear mixed effect models (LME). P-values were corrected for multiple testing (P-LME). Results Month 1 milk protein content was strongly associated with infant serum lyso-phosphatidylcholine (LPC) 14: 0 (P-LME = 0.009). Month 1 milk insulin was associated to infant acetylcarnitine (P-LME = 0.01). There were no associations between milk protein content and serum amino acids and milk total fat content and serum polar lipids. Middle- and odd-chain FA% in breast milk at both ages were significantly related to serum LPC and sphingomyelins (SM) species in infant serum (all P-LME < 0.05), while FA% 20: 5n(-3) and 22: 6n(-3) percentages were significantly associated to serum LPC 22:6 (P-LME = 1.91x10(-4)/7.93x10(-5)) in milk only at month 4. Other polyunsaturated fatty acids and hormones in milk showed only weak associations with infant serum metabolites. Conclusions Infant serum LPC are influenced by breast milk FA composition and, intriguingly, milk protein content in early but not late lactation. LPC 14:0, previously found positively associated with obesity risk, was the serum metabolite which was the most strongly associated to milk protein content. Thus, LPC 14:0 might be a key metabolite not only reflecting milk protein intake in infants, but also relating high protein content in milk or infant formula to childhood obesity risk

Assessment of dietary compliance in celiac children using a standardized dietary interview

Development and application of statistical models for medical scientific researc

Associations between breast milk macronutrient classes and hormones to infant serum metabolites at 4 months of age.

<p>Breast milk components were measured at month 1 (a) or month 4 (b). Negative log-transformed P-values are plotted for each metabolite arranged by metabolite group and species. Higher values represented in the outer circles present a higher association between metabolite and predictor. P-values were calculated by linear regression models with the milk compound as independent variable, adjusted for infant sex, breastfeeding status at 4-month blood withdrawal (exclusively BF yes/no), and the infant’s age at blood withdrawal. Random intercepts were modelled for batch number and study centre. P-values were corrected (PLME) for multiple testing using Bonferroni’s methods, this is by dividing the p-value with number of metabolites (n = 184).</p

CONSORT flow diagram.

<p>Of 944 children in the PreventCD-cohort, 196 complete mother/infant pairs with complete sample sets were analysed. 136 pairs were studied for the associations between <i>month 1</i> breast milk composition and infant serum metabolites at age of 4 months and 137 were studied for the associations between <i>month 4</i> breast milk composition and infant serum metabolites at age of 4 months. 87 were studied at both time points.</p

Characteristics of the infant/mother pairs studied with breast milk samples available at month 1 and month 4.

<p>Characteristics of the infant/mother pairs studied with breast milk samples available at month 1 and month 4.</p

Correlations between breast milk fatty acids percentages to infant serum metabolites at 4 months of age.

<p>Breast milk components were measured at month 1 (a) or month 4 (b). Spearman correlation coefficients are plotted for each metabolite arranged by metabolite group. AA, amino acids; Carn, acylcarnitines; LPC, lysophosphatidylcholines; PC aa, diacyl-phosphatidylcholines; PC ae, acyl-alkyl-phosphatidylcholines SM, sphingomyelins.</p

Impact on parents of HLA-DQ2/DQ8 genotyping in healthy children from coeliac families

Due to the association of coeliac disease and HLA-specificities DQ2 and DQ8, HLA-typing can be used for risk determination of the disease. This study was designed to evaluate the knowledge of parents from coeliac families regarding HLA-typing and the impact of HLA-typing on the perception of the health of their children. A structured questionnaire was sent to the Dutch, Spanish and German parents participating with their child in the European PreventCD study on disease prevention in high-risk families, addressing parents' understanding of and attitude towards HLA-typing, distress related to HLA-typing and perceived health and health-related quality of life of their children. Sixty-eight percent of parents of 515 children returned the questionnaires, with 85% of children being DQ2/DQ8 positive. The majority of all parents answered the questions on knowledge correctly. Forty-eight percent of parents of DQ2/DQ8-negative children thought their child could develop coeliac disease. More distress was reported by parents of DQ2/DQ8-positive children (