Identification of Predictive Biomarkers of Mastitis in Lactating Mothers Using a Metabolomic Approach

Breastfeeding is the optimal feeding for infants. WHO currently promotes breastfeeding and recommends it to be exclusive until the baby is 6 months old. Breastfeeding has a positive impact on both the mother's and the infant's health and is directly associated with the decrease in diseases such as cancer, diabetes, cardiovascular disease, and inflammatory and infectious diseases. Currently, in Spain, only 39% of infants at 6 months are breastfed. The factors that influence the abandonment of breastfeeding are returning to work, the sensation of hypogalactia, problems to breastfeed, and breast complications, like mastitis, being the pain its main cause. Recent studies have associated pain while breastfeeding with mammary gland inflammation (mastitis) caused by dysbiosis.

In order to increase breastfeeding rates, it is necessary to find factors related to the progression of mastitis in breastfeeding women. In this context, the discovery of predictive biomarkers based on metabolic markers is key to act before or at the beginning of the progression of mastitis and thus reduce the rates of abandonment of breastfeeding due to pain.

The present project aims to identify and validate metabolic biomarkers capable of predicting mastitis. For this purpose, a prospective observational case-control hypothesis-free study will be carried out in order to identify and validate biomarkers of mastitis in breastfeeding women. The study will be performed in two phases: the discovery of the possible biomarkers and the validation of the biomarkers.

Breast milk will be collected at the beginning of the study and when women present symptoms compatible with mastitis. The presence or not of mastitis will be confirmed with a milk culture. Milk samples will be analyzed using non-targeted metabolomics approach. Using multivariate statistical models, the potential metabolites capable of discriminating the presence of mastitis in maternal milk will be identified. Later, these potential markers will be validated in independent samples.