Influence of technical and maternal-infant factors on the measurement and expression of extracellular miRNA in human milk

Abstract

Breast milk contains thousands of bioactive compounds including extracellular vesicle microRNAs (EV-miRNAs), which may regulate pathways such as infant immune system development and metabolism. We examined the associations between the expression of EV-miRNAs and laboratory variables (i.e., batch effects, sample characteristics), sequencing quality indicators, and maternal-infant characteristics. The study included 109 Latino mother-infant dyads from the Southern California Mother’s Milk Study. Mothers were age 28.0 ± 5.6 and 23-46 days postpartum. We used principal components analysis to evaluate whether EV-miRNA expression was associated with factors of interest. Then, we used linear models to estimate relationships between these factors and specific EV-miRNA counts and analyzed functional pathways associated with those EV-miRNAs. Finally, we explored which maternal-infant characteristics predicted sequencing quality indicators. Sequencing quality indicators, predominant breastfeeding, and breastfeedings/day were associated with EV-miRNA principal components. Maternal body mass index and breast milk collection timing predicted proportion of unmapped reads. Expression of 2 EV-miRNAs were associated with days postpartum, 23 EV-miRNAs were associated with breast milk collection time, 23 EV-miRNAs were associated with predominant breastfeeding, and 38 EV-miRNAs were associated with breastfeedings/day. These EV-miRNAs were associated with pathways including Hippo signaling pathway and ECM-receptor interaction, among others. This study identifies several important factors that may contribute to breast milk EV-miRNA expression. Future studies should consider these findings in the design and analysis of breast milk miRNA research.