Human milk extracellular vesicle miRNA expression and associations with maternal characteristics in a population-based cohort from the Faroe Islands

Sci Rep. 2021 Mar 12;11(1):5840. doi: 10.1038/s41598-021-84809-2.

Abstract

Human milk plays a critical role in infant development and health, particularly in cognitive, immune, and cardiometabolic functions. Milk contains extracellular vesicles (EVs) that can transport biologically relevant cargo from mother to infant, including microRNAs (miRNAs). We aimed to characterize milk EV-miRNA profiles in a human population cohort, assess potential pathways and ontology, and investigate associations with maternal characteristics. We conducted the first study to describe the EV miRNA profile of human milk in 364 mothers from a population-based mother-infant cohort in the Faroe Islands using small RNA sequencing. We detected 1523 miRNAs with ≥ one read in 70% of samples. Using hierarchical clustering, we determined five EV-miRNA clusters, the top three consisting of 15, 27 and 67 miRNAs. Correlation coefficients indicated that the expression of many miRNAs within the top three clusters was highly correlated. Top-cluster human milk EV-miRNAs were involved in pathways enriched for the endocrine system, cellular community, neurodevelopment, and cancers. miRNA expression was associated with time to milk collection post-delivery, maternal body mass index, and maternal smoking, but not maternal parity. Future studies investigating determinants of human EV-miRNAs and associated health outcomes are needed to elucidate the role of human milk EV-miRNAs in health and disease.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Adult
  • Cluster Analysis
  • Cohort Studies
  • Denmark
  • Extracellular Vesicles / genetics*
  • Female
  • Gene Expression Regulation*
  • Gene Ontology
  • Humans
  • MicroRNAs / genetics*
  • MicroRNAs / metabolism
  • Milk, Human / metabolism*
  • Pregnancy
  • Signal Transduction / genetics
  • Statistics as Topic

Substances

  • MicroRNAs