Location: Obesity and Metabolism Research
Project Number: 2032-10700-004-000-D
Project Type: In-House Appropriated
Start Date: Apr 28, 2025
End Date: Apr 27, 2029
Objective:
There is no comprehensive study of factors affecting micronutrient (MN) concentrations in human milk or the relationship between maternal and infant MN status, milk nutrients, milk volume and other factors. Lacking adequate and reliable data, it is not possible to set Estimated Average Requirements for most MNs for infants, estimate prevalence of inadequate infant and maternal nutrient intakes during lactation, or understand the need for, and effects of, maternal and infant interventions such as supplementation. This project will take advantage of a unique data set from our Mothers, Infants and Lactation Quality (MILQ) study, which was designed to construct global Reference Values for nutrients in milk supported through a grant ending in July 2024. Data were collected from 1000 well-nourished lactating women and their infants across 8.5 months of lactation, in Denmark, Brazil, Bangladesh and The Gambia. The general approach will be to focus on key public-health related questions about relationships among maternal intake, status, milk content and infant status for micronutrients (MN), using existing data, analysis of additional biomarkers, and analysis of dietary intake and genomics.
Objective 1: Develop a model of predictors of the nutrient composition of human milk, including biomarkers of maternal nutritional status, the nutrient composition of maternal diets, milk volume, parity, and maternal body composition and genotype.
Objective 2: Develop a model predicting biomarkers of infant micronutrient status, including milk composition, milk volume, nutrient intake from complementary foods, maternal status biomarkers and diet, and markers of inflammation in the infant and the mother.
Approach:
Objective 1: Hypothesis 1. Maternal micronutrient status is a stronger predictor of milk micronutrient concentrations than is current maternal dietary intake.
Rationale: It is not understood whether the concentrations of MN in human milk predominantly reflect maternal MN status or her recent or longer-term MN intake, and whether they are affected by maternal factors including milk volume, parity, body composition or genotype.
Approach: Maternal micronutrient status will be assessed based on existing and additional plasma and red blood nutrient status biomarkers. Correlations between milk MN concentrations, maternal MN status and dietary intake will be estimated. The eight days of food intake data collected for each mother will be used to create a combined nutrient data base for each study site, and indicators of Dietary Quality will also be calculated.
Objective 1: Hypothesis 2. Milk volume and composition are associated with maternal genotype.
Rationale: There are large inter-individual differences in human milk composition which are unlikely to be entirely due to differences in maternal diet and nutritional status but may be due to variation in transporters of specific nutrients.
Approach: DNA has been extracted from buffy coats obtained from maternal blood. The Infinium Multi-Ethnic Global Array has been used for genotyping, which will catalog common sources of variation in Single Nucleotide Polymorphisms (SNPs). Genotypes will be imputed for 1000 mothers. Genome-Wide Association Study (GWAS) and individual SNP analyses for milk nutrient concentrations and volume will be carried out by linear regression analysis.
Objective 2: Hypothesis. Infant MN status is more strongly predicted by maternal status biomarkers and other maternal factors including genomics, than by the total amount of each MN the infant consumes in milk.
Rationale: It is not understood how strongly milk composition and volume, and other maternal factors, influence infant MN status.
Approach: Infant intake of each nutrient will be primarily modeled as total intake using the milk volume times concentration data, and infant status will be based on biomarkers of nutritional status in plasma. Plasma indicators of maternal nutrient status, maternal genotype and diet, and other relevant maternal factors identified in the previous models will be included in this model.
