Gestational Diabetes Mellitus Is Associated with Differences in Human Milk Hormone and Cytokine Concentrations in a Fully Breastfeeding United States Cohort

Yuni Choi, Emily M Nagel, Harmeet K Kharoud, Kelsey E Johnson, Tipper T Gallagher, Katy Duncan, Elyse O. Kharbanda, David A. Fields, Cheryl A Gale, Katherine M Jacobs, David Jacobs, Ellen W. Demerath

Research output: Contribution to journalArticlepeer-review

Abstract

It is unclear whether gestational diabetes mellitus (GDM) alters breast milk composition. We prospectively examined associations of GDM status with concentrations of six potentially bioactive elements (glucose, insulin, C-reactive protein (CRP), interleukin-6 (IL-6), leptin, and adiponectin) in human milk. These were measured at both 1 and 3 months postpartum in 189 fully breastfeeding women. Mixed-effects linear regression assessed GDM status-related differences in these milk bioactives, adjusting for demographics, maternal factors, and diet. At 1 and 3 months postpartum, milk CRP was higher (1.46 ± 0.31 ng/mL; p < 0.001 and 1.69 ± 0.31 ng/mL; p < 0.001) in women with GDM than in women without GDM, whereas milk glucose (-5.23 ± 2.22 mg/dL; p = 0.02 and -5.70 ± 2.22; p = 0.01) and milk insulin (-0.38 ± 0.17 μIU/mL; p = 0.03 and -0.53 ± 0.17; p = 0.003) were lower in women with GDM. These significant associations remained similar after additional adjustment for maternal weight status and its changes. No difference was found for milk IL-6, leptin, and adiponectin. There was no evidence of association between these milk bioactive compounds and 1 h non-fasting oral glucose challenge serum glucose in the women without GDM. This prospective study provides evidence that potentially bioactive elements of human milk composition are altered in women with GDM.

Original languageEnglish (US)
Article number667
JournalNutrients
Volume14
Issue number3
DOIs
StatePublished - Feb 1 2022

Bibliographical note

Funding Information:
Funding: The MILk study is supported by an NIH/NICHD grant (R01HD080444) to Demerath, Fields, Kharbanda, and Jacobs. The 4M Study is supported by a University of Minnesota Office of Academic and Clinical Affairs Faculty Development Grant to Demerath, Gale, and KO Jacobs. E.M.N. was supported by NIH/NIDDK fellowship grant (T32DK083250). K.E.J. was supported by MinnCResT postdoctoral training grant T32 DE007288 and NIH NICHD NRSA postdoctoral fellow‐ ship F32 HD105364.

Funding Information:
Acknowledgments: The authors would like to acknowledge and thank all the women and health care providers who contributed to the MILk study. We also acknowledge the valuable assistance of Lauren Asfaw and Dr. Stephanie Mackenthun in the University of Minnesota Division of Maternal‐ Fetal Medicine, Neely Miller and Kristin Sandness and the resources of the Center for Neurobehav‐ ioral Development, Rebecca Hollister from the Center for Pediatric Obesity at the University of Min‐ nesota, the Clinical and Translational Research Services support team at the Clinical and Transla‐ tional Science Institute at the University of Minnesota (supported by grant number UL1TR002494 from the National Institutes of Health’s National Center for Advancing Translational Sciences), la‐ boratory resources from the University of Oklahoma Health Sciences Center, and Elisabeth Seburg, and the data collection and information technology team at the HealthPartners Institute. The au‐ thors also acknowledge use of the following resources: Diet*Calc Analysis Program, Version 1.5.0. National Cancer Institute, Epidemiology and Genomics Research Program. October 2012. Diet His‐ tory Questionnaire, Version 2.0. National Institutes of Health, Epidemiology and Genomics Re‐ search Program, National Cancer Institute. 2010. DHQ Nutrient Database. dhq2.data‐ base.092914.csv. National Cancer Institute, Epidemiology and Genomics Research Program. Study data were collected and managed using REDCap electronic data capture tools hosted at the Univer‐ sity of Minnesota. REDCap (Research Electronic Data Capture) is a secure, web‐based software plat‐ form designed to support data capture for research studies (Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)‐A metadata‐driven method‐ ology and workflow process for providing translational research informatics support. J Biomed In‐ form. 2009;42:377–381. ; Harris PA, Taylor R, Minor BL, et al. The REDCap consortium: Building an international community of software platform partners. J Biomed Inform. 2019;95).

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • Breast Feeding
  • Breastmilk
  • Cytokines
  • Cytokines/metabolism
  • Diabetes, Gestational
  • Female
  • Gestational diabetes mellitus
  • Glucose Tolerance Test
  • Hormones
  • Human milk
  • Humans
  • Milk, Human/metabolism
  • Pregnancy
  • Prospective Studies
  • Prospective cohort
  • United States
  • Cytokines/chemistry
  • Milk, Human/chemistry
  • Hormones/chemistry

PubMed: MeSH publication types

  • Journal Article

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