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Preterm human milk at lactation weeks 1 and 4 categorized by maternal pre-pregnancy body mass index: Metabolomics and lipidomics datasets.

Authors :
Robinson DT
Balmert L
Josefson J
Van Horn L
Source :
Data in brief [Data Brief] 2020 Nov 06; Vol. 33, pp. 106507. Date of Electronic Publication: 2020 Nov 06 (Print Publication: 2020).
Publication Year :
2020

Abstract

Human milk samples were prospectively obtained from women who delivered prior to the 32nd week of gestation [1]. The 36 preterm human milk samples analysed in this dataset were collected at week 1 and week 4 of lactation. Samples were categorized as being from women with normal pre-pregnancy body mass index (BMI 18-24.9 kg/m <superscript>2</superscript> ) versus overweight/obese (BMI ≥25). Whole milk samples were frozen at -80 Celsius without prior processing and shipped for analysis on dry ice. Untargeted metabolomic and lipidomic platforms using UPLC-MS/MS and infusion-MS analysis for select lipids were performed by Metabolon. Lipidomic analysis included detection of complex lipids found in the milk fat globule membrane. Data were categorized by maternal BMI, week of lactation as well as gestational age at delivery. Data sheets are separated based on whether they report metabolomics versus lipidomics, as well as whether they report output from samples collected at week 1 versus week 4 of lactation. These data allow calculating relationships between clinical variables and human milk components. As an illustrative example, correlations between pre-pregnancy BMI and total milk fatty acids were calculated for this report using the Spearman correlation. These data will inform scientists of variability in milk composition attributable to maternal pre-pregnancy BMI as well as changes in milk composition as milk matures during lactation from week 1 to week 4. These data may best be used for generating hypotheses and justification of future work investigating whether maternal pre-pregnancy body mass index impacts preterm human milk composition.<br />Competing Interests: None.<br /> (© 2020 The Authors.)

Details

Language :
English
ISSN :
2352-3409
Volume :
33
Database :
MEDLINE
Journal :
Data in brief
Publication Type :
Academic Journal
Accession number :
33251308
Full Text :
https://doi.org/10.1016/j.dib.2020.106507