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Lipid Profiles of Human Milk and Infant Formulas: A Comparative Lipidomics Study.

Danjie Wu | Le Zhang | Yan Zhang | Jiachen Shi | Chin Ping Tan | Zhaojun Zheng | Yuanfa Liu
Foods (Basel, Switzerland) | 2023

Infant formulas (IFs) are prevalent alternatives for human milk (HM), although their comparative lipid profiles have not been fully investigated. We adopted lipidomics to analyze and compare in-depth the lipid patterns of HM and IFs. The results indicated that the distribution of fatty acids (FAs) and the structure of triacylglycerols varied substantially in the analyzed samples. A total number of 425 species were identified during the analysis. HM was abundant in triacylglycerols that contained unsaturated and long-chain FAs (>C13), while triacylglycerols in IFs were mainly comprised of saturated and medium-chain FAs (C8-C13). Higher levels of sphingomyelin were observed in HM. Furthermore, HM and IF1 contained 67 significantly differential lipids (SDLs), and 73 were identified between HM and IF2. These SDLs were closely associated with nine metabolic pathways, of which the most significant was the glycerophospholipid metabolism. The results shed light on the differences between the lipid profiles of human and infant formula milks, and provide support for designing Chinese infant formula.

Pubmed ID: 36766129

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Associated grants

  • Agency: Chinese Institute of Food Science and Technology & Abbott Research Program,
    Id: 2020-02
  • Agency: National Key Research and Development Program of China,
    Id: 2021YFD210030400
  • Agency: National Key Research and Development Program of Shandong Provence,
    Id: 2021CXGC010808
  • Agency: Top medical expert team of Wuxi Taihu Talent Program,
    Id: DJTD202106
  • Agency: Medical Key Discipline Program of Wuxi Health Commission,
    Id: ZDXK2021007
  • Agency: National Natural Science Foundation of China,
    Id: 81901517

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MetaboAnalyst (tool)

RRID:SCR_015539

Web server for statistical, functional and integrative analysis of metabolomics data. Web based tool suite used for metabolomic data processing, normalization, multivariate statistical analysis, and data annotation, biomarker discovery and classification.

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