Regulation of appetite and food intake is partly regulated by
-acylethanolamine lipids oleoylethanolamide (OEA), stearoylethanolamide (SEA), and palmitoylethanolamide (PEA), which induce satiety ...through endogenous formation in the small intestine upon feeding, but also when orally or systemic administered. OEA, SEA, and PEA are present in human milk, and we hypothesized that the content of OEA, SEA, and PEA in mother's milk differed for infants being heavy (high weight-for-age Z-score (WAZ)) or light (low WAZ) at time of milk sample collection. Ultra-high performance liquid chromatography-mass spectrometry was used to determine the concentration of OEA, SEA, and PEA in milk samples collected four months postpartum from mothers to high (
= 50) or low (
= 50) WAZ infants. Associations between OEA, SEA, and PEA concentration and infant anthropometry at four months of age as well as growth from birth were investigated using linear and logistic regression analyses, adjusted for birth weight, early infant formula supplementation, and maternal pre-pregnancy body mass index. Mean OEA, SEA, and PEA concentrations were lower in the high compared to the low WAZ group (all
< 0.02), and a higher concentration of SEA was associated with lower anthropometric measures, e.g., triceps skinfold thickness (mm) (β = -2.235, 95% CI = -4.04, -0.43,
= 0.016), and weight gain per day since birth (g) (β = -8.169, 95% CI = -15.26, -1.08,
= 0.024). This raises the possibility, that the content of satiety factors OEA, SEA, and PEA in human milk may affect infant growth.
Blood pressure (BP) and blood lipid profile (BLP) have been shown to track from childhood into adulthood, and n-3 long-chain polyunsaturated fatty acids (LC-PUFAs) in breast milk have been suggested ...as mediators of the beneficial long-term effect of breastfeeding on BP and BLP. We aimed to investigate associations between n-3 LC-PUFA content in breast milk at 4 months postpartum and offspring BP and BLP in early life. BP and BLP were measured at 4, 18, and 36 months. Statistical analyses were sex-stratified and adjusted for gestational age, maternal pre-pregnancy body mass index (BMI), and maternal educational level. Based on 336 mother-child dyads, high n-3 LC-PUFA in breast milk was inversely associated with systolic and diastolic BP in boys at 4 months (β = -20.0 (95% CI = -33.4, -6.7),
= 0.004 and β = -10.2 (95% CI = -19.8, -0.5),
= 0.039, respectively); inversely associated with HDL cholesterol, and directly associated with triglyceride in girls at 4 months (β = -0.7 (95% CI = -1.1, -0.3),
= 0.001 and β = 3.1 (95% CI = 1.0, 5.2),
= 0.005, respectively). Associations observed at the later time points were non-significant. Furthermore, we observed sex-specific changes over time in both size and direction of the associations. Our results indicate that early intake of n-3 LC-PUFA can affect early development in cardiometabolic factors such as BP and BLP in a sex-specific manner. Follow-up and further investigation in later childhood is planned.
Despite scientific advances it remains difficult to predict the risk and benefit balance of immune interventions. Since a few years, network models have been built based on comprehensive datasets at ...multiple molecular/cellular levels (genes, gene products, metabolic intermediates, macromolecules, cells) to illuminate functional and structural relationships. Here we used a systems biology approach to identify key immune pathways involved in immune health endpoints and rank crucial candidate biomarkers to predict adverse and beneficial effects of nutritional immune interventions. First, a literature search was performed to select the molecular and cellular dynamics involved in hypersensitivity, autoimmunity and resistance to infection and cancer. Thereafter, molecular interaction between molecules and immune health endpoints was defined by connecting their relations by using database information. MeSH terms related to the immune health endpoints were selected resulting in the following selection: hypersensitivity (D006967: 184 genes), autoimmunity (D001327: 564 genes), infection (parasitic, bacterial, fungal and viral: 357 genes), and cancer (D009369: 3173 genes). In addition, a sequence of key processes was determined using Gene Ontology which drives the development of immune health disturbances resulting in the following selection: hypersensitivity (164 processes), autoimmunity (203 processes), infection (187 processes), and cancer (309 processes). Finally, an evaluation of the genes for each of the immune health endpoints was performed, which indicated that many genes played a role in multiple immune health endpoints, but also unique genes were observed for each immune health endpoint. This approach helps to build a screening/prediction tool which indicates the interaction of chemicals or food substances with immune health endpoint-related genes and suggests candidate biomarkers to evaluate risks and benefits. Several anti-cancer drugs and omega 3 fatty acids were evaluated as
test cases. To conclude, here we provide a systems biology approach to identify genes/molecules and their interaction with immune related disorders. Our examples illustrate that the prediction with our systems biology approach is promising and can be used to find both negatively and positively correlated interactions. This enables identification of candidate biomarkers to monitor safety and efficacy of therapeutic immune interventions.
A healthy immune status is strongly conditioned during early life stages. Insights into the molecular drivers of early life immune development and function are prerequisite to identify strategies to ...enhance immune health. Even though several starting points for targeted immune modulation have been identified and are being developed into prophylactic or therapeutic approaches, there is no regulatory guidance on how to assess the risk and benefit balance of such interventions. Six early life immune causal networks, each compromising a different time period in early life (the 1st, 2nd, 3rd trimester of gestations, birth, newborn, and infant period), were generated. Thereto information was extracted and structured from early life literature using the automated text mining and machine learning tool: Integrated Network and Dynamical Reasoning Assembler (INDRA). The tool identified relevant entities (e.g., genes/proteins/metabolites/processes/diseases), extracted causal relationships among these entities, and assembled them into early life-immune causal networks. These causal early life immune networks were denoised using GeneMania, enriched with data from the gene-disease association database DisGeNET and Gene Ontology resource tools (GO/GO-SLIM), inferred missing relationships and added expert knowledge to generate information-dense early life immune networks. Analysis of the six early life immune networks by PageRank, not only confirmed the central role of the "commonly used immune markers" (e.g., chemokines, interleukins,
, and other immune activation regulators (e.g.,
), but also identified less obvious candidates (e.g.,
). Comparison of the different early life periods resulted in the prediction of 11 key early life genes overlapping all early life periods (
, and
, and also genes that were only described in certain early life period(s). Concluding, here we describe a network-based approach that provides a science-based and systematical method to explore the functional development of the early life immune system through time. This systems approach aids the generation of a testing strategy for the safety and efficacy of early life immune modulation by predicting the key candidate markers during different phases of early life immune development.
High protein intake during infancy results in accelerated early weight gain and potentially later obesity. The aim of this follow-up study at 12 months was to evaluate if modified low-protein ...formulas fed during early infancy have long-term effects on growth and metabolism. In a double-blinded RCT, the ALFoNS study, 245 healthy-term infants received low-protein formulas with either alpha-lactalbumin-enriched whey (α-lac-EW; 1.75 g protein/100 kcal), casein glycomacropeptide-reduced whey (CGMP-RW; 1.76 g protein/100 kcal), or standard infant formula (SF; 2.2 g protein/100 kcal) between 2 and 6 months of age. Breastfed (BF) infants served as a reference. At 12 months, anthropometrics and dietary intake were assessed, and serum was analyzed for insulin, C-peptide, and insulin-like growth factor 1 (IGF-1). Weight gain between 6 and 12 months and BMI at 12 months were higher in the SF than in the BF infants (
= 0.019;
< 0.001, respectively), but were not significantly different between the low-protein formula groups and the BF group. S-insulin and C-peptide were higher in the SF than in the BF group (
< 0.001;
= 0.003, respectively), but more alike in the low-protein formula groups and the BF group. Serum IGF-1 at 12 months was similar in all study groups. Conclusion: Feeding modified low-protein formula during early infancy seems to reduce insulin resistance, resulting in more similar growth, serum insulin, and C-peptide concentrations to BF infants at 6-months post intervention. Feeding modified low-protein formula during early infancy results in more similar growth, serum insulin, and C-peptide concentrations to BF infants 6-months post intervention, probably due to reduced insulin resistance in the low-protein groups.
Protein intake is higher in formula-fed than in breast-fed infants during infancy, which may lead to an increased risk of being overweight. Applying alpha-lactalbumin (α-lac)-enriched whey or casein ...glycomacropeptide (CGMP)-reduced whey to infant formula may enable further reduction of formula protein by improving the amino acid profile. Growth, nutrient intake, and protein metabolites were evaluated in a randomized, prospective, double-blinded intervention trial where term infants received standard formula (SF:2.2 g protein/100 kcal;
= 83) or low-protein formulas with α-lac-enriched whey (α-lac-EW;1.75 g protein/100 kcal;
= 82) or CGMP-reduced whey (CGMP-RW;1.76 g protein/100 kcal;
= 80) from 2 to 6 months. Breast-fed infants (BF;
= 83) served as reference. Except between 4 and 6 months, when weight gain did not differ between α-lac-EW and BF (
= 0.16), weight gain was higher in all formula groups compared to BF. Blood urea nitrogen did not differ between low-protein formula groups and BF during intervention, but was lower than in SF. Essential amino acids were similar or higher in α-lac-EW and CGMP-RW compared to BF. Conclusion: Low-protein formulas enriched with α-lac-enriched or CGMP-reduced whey supports adequate growth, with more similar weight gain in α-lac-enriched formula group and BF, and with metabolic profiles closer to that of BF infants.
It remains largely unknown how physicochemical properties of hydrolysed infant formulas influence their allergy preventive capacity, and results from clinical and animal studies comparing the ...preventive capacity of hydrolysed infant formula with conventional infant formula are inconclusive. Thus, the use of hydrolysed infant formula for allergy prevention in atopy-prone infants is highly debated. Furthermore, knowledge on how gut microbiota influences allergy prevention remains scarce.
To gain knowledge on (1) how physicochemical properties of hydrolysed whey products influence the allergy preventive capacity, (2) whether host microbiota disturbance influences allergy prevention, and (3) to what extent hydrolysed whey products influence gut microbiota composition.
The preventive capacity of four different
administered whey products was investigated in Brown Norway rats with either a conventional or an amoxicillin-disturbed gut microbiota. The preventive capacity of products was evaluated as the capacity to reduce whey-specific sensitisation and allergic reactions to intact whey after intraperitoneal post-immunisations with intact whey. Additionally, the direct effect of the whey products on the growth of gut bacteria derived from healthy human infant donors was evaluated by
incubation.
Two partially hydrolysed whey products with different physicochemical characteristics were found to be superior in preventing whey-specific sensitisation compared to intact and extensively hydrolysed whey products. Daily oral amoxicillin administration, initiated one week prior to intervention with whey products, disturbed the gut microbiota but did not impair the prevention of whey-specific sensitisation. The
incubation of infant faecal samples with whey products indicated that partially hydrolysed whey products might confer a selective advantage to enterococci.
Our results support the use of partially hydrolysed whey products for prevention of cow's milk allergy in atopy-predisposed infants regardless of their microbiota status. However, possible direct effects of partially hydrolysed whey products on gut microbiota composition warrants further investigation.
ABSTRACT
Objectives:
Osteopontin (OPN) is a multifunctional protein expressed in many cell types, tissues and body fluids with the highest concentrations found in milk; significantly higher in human ...than in bovine milk. Intervention studies have indicated beneficial effects of supplementing infant formula with bovine OPN. In this multicenter study, we determined the OPN content in human milk samples from 629 Chinese, Danish, Japanese and Korean mothers.
Methods:
At each study site, milk samples were collected and analyzed for OPN and protein concentration using ELISA and infrared spectroscopy, respectively.
Results:
A total of 829 milk samples from 629 women were included. When delivering the first sample, mean maternal age was 31.4 years (SD 4.0), and median infant age was 13.4 weeks (interquartile range 4.6–17.9). The median OPN concentration varied across sites; from 99.7 mg/L in Danish, 185.0 mg/L in Japanese, 216.2 mg/L in Korean to 266.2 mg/L in Chinese mothers (P < 0.001), corresponding to 1.3%, 2.4%, 1.8% and 2.7% of the total protein content (OPN/protein%) (P < 0.05), respectively. Based on 75 Chinese and 33 Japanese mothers delivering more than 1 sample, multilevel (mixed model) linear regression analysis showed a decrease in OPN concentration with infant age (β = (−11.3), 95% confidence interval (CI) = (−13.9) to (−8.8) and β = (−2.1), 95% CI = (−3.2) to (−0.9), respectively).
Conclusions:
In this large multicenter study, we observed statistically significant differences in the OPN concentration and the OPN/protein% in human milk samples between countries. Based on mothers delivering more than 1 sample, a significant decrease within the lactation period was observed.
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•Degree of hydrolysis is a poor predictor of milk protein hydrolysate sensitizing capacity.•Whey- and casein-based hydrolysates exhibit distinct immunological properties.•Surface ...hydrophobicity may affect hydrolysate immunogenicity and allergenicity.
The use of infant formulas (IFs) based on hydrolyzed cow’s milk proteins to prevent cow’s milk allergy (CMA) is highly debated. The risk of sensitization to milk proteins induced by IFs may be affected by the degree of hydrolysis (DH) as well as other physicochemical properties of the cow’s milk-based protein hydrolysates within the IFs. The immunogenicity (specific IgG1 induction) and sensitizing capacity (specific IgE induction) of 30 whey- or casein-based hydrolysates with different physicochemical characteristics were compared using an intraperitoneal model of CMA in Brown Norway rats. In general, the whey-based hydrolysates demonstrated higher immunogenicity than casein-based hydrolysates, inducing higher levels of hydrolysate-specific and intact-specific IgG1. The immunogenicity of the hydrolysates was influenced by DH, peptide size distribution profile, peptide aggregation, nano-sized particle formation, and surface hydrophobicity. Yet, only the surface hydrophobicity was found to affect the sensitizing capacity of hydrolysates, as high hydrophobicity was associated with higher levels of specific IgE. The whey- and casein-based hydrolysates exhibited distinct immunological properties with highly diverse molecular composition and physicochemical properties which are not accounted for by measuring DH, which was a poor predictor of sensitizing capacity. Thus, future studies should consider and account for physicochemical characteristics when assessing the sensitizing capacity of cow’s milk-based protein hydrolysates.
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