Literature DB >> 31825672

Clinical insights gained through metabolomic analysis of human breast milk.

Flaminia Bardanzellu1, Chiara Peila2, Vassilios Fanos1, Alessandra Coscia2.   

Abstract

Introduction: Among the OMICS technologies, that have emerged in recent years, metabolomics has allowed relevant step forwards in clinical research. Several improvements in disease diagnosis and clinical management have been permitted, even in neonatology. Among potentially evaluable biofluids, breast milk (BM) results are highly interesting, representing a fluid of conjunction between mothers newborns, describing their interaction.Areas covered: in this review, updating a previous review article, we discuss research articles and reviews on BM metabolomics and found in MEDLINE using metabolomics, breast milk, neonatal nutrition, breastfeeding, human milk composition, and preterm neonates as keywords.Expert opinion: Our research group has a profound interest in metabolomics research. In 2012, we published the first metabolomic analysis on BM samples, reporting interesting data on its composition and relevant differences with formula milk (FM), useful to improve FM composition. As confirmed by successive studies, such technology can detect the specific BM composition and its dependence on several variables, including lactation stage, gestational age, maternal or environmental conditions. Moreover, since BM contaminants or drug levels can be detected, metabolomics also results useful to determine BM safety. These are only a few practical applications of BM analysis, which will be reviewed in this paper.

Entities:  

Keywords:  Breast milk composition; breastfeeding; prematurity

Mesh:

Year:  2019        PMID: 31825672     DOI: 10.1080/14789450.2019.1703679

Source DB:  PubMed          Journal:  Expert Rev Proteomics        ISSN: 1478-9450            Impact factor:   3.940


  4 in total

1.  Comparing human milk macronutrients measured using analyzers based on mid-infrared spectroscopy and ultrasound and the application of machine learning in data fitting.

Authors:  Huijuan Ruan; Qingya Tang; Yajie Zhang; Xuelin Zhao; Yi Xiang; Yi Feng; Wei Cai
Journal:  BMC Pregnancy Childbirth       Date:  2022-07-14       Impact factor: 3.105

2.  Metabolomic Profile of Personalized Donor Human Milk.

Authors:  Monica F Torrez Lamberti; Evon DeBose-Scarlett; Timothy Garret; Leslie Ann Parker; Josef Neu; Graciela L Lorca
Journal:  Molecules       Date:  2020-12-08       Impact factor: 4.411

Review 3.  The Human Breast Milk Metabolome in Overweight and Obese Mothers.

Authors:  Flaminia Bardanzellu; Melania Puddu; Diego Giampietro Peroni; Vassilios Fanos
Journal:  Front Immunol       Date:  2020-07-21       Impact factor: 7.561

Review 4.  How could metabolomics change pediatric health?

Authors:  Flaminia Bardanzellu; Vassilios Fanos
Journal:  Ital J Pediatr       Date:  2020-03-27       Impact factor: 2.638

  4 in total

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