Maternal diet and genetics shape the human milk metabolome

Authors

Johnson, K. E., Duan, Y., Youssef, A., Aristizabal-Henao, J. J., Johnson, A., Kiebish, M. A., Nagel, E. M., Palmsten, K., Pierce, S., Wernimont, S., Bode, L., Lock, E. F., Isganaitis, E. M., Fields, D. A., Albert, F. W., Blekhman, R., Demerath, E. W.

Abstract

Human milk contains a diverse array of metabolites that contribute to infant nutrition, immune development, and microbial colonization. The maternal factors shaping the milk metabolome, and the relative contribution of genetics or diet vs. other factors, remain poorly understood. Here, we profiled 458 milk metabolites in 349 one-month postpartum human milk samples and integrated metabolomic data with maternal diet, clinical, transcriptomic, and genomic measurements. Maternal diet was broadly associated with milk metabolite composition, with significant correlations identified between dietary features and 323 metabolites. Coffee consumption strongly predicted milk quinic acid and 1,3-dimethyluric acid abundance, while high-fiber dietary patterns were associated with metabolites including proline-betaine and N-acetylornithine. Integration of milk transcriptomic and metabolomic data via machine learning identified biologically plausible gene-metabolite pairs, including associations between QPRT expression and quinolinic acid, and DPEP1 and cysteine-glycine dipeptide. Genome-wide association analyses identified nine study-wide significant metabolite quantitative trait loci, including novel milk-specific associations near PDE6A affecting purine metabolites and near GNE affecting free sialic acid. Comparison with plasma metabolite studies demonstrated both shared and milk-specific genetic regulation of metabolites. Finally, we found that of all tested maternal features, diet explained the largest proportion of variation in the milk metabolome. Together, these findings demonstrate that the human milk metabolome reflects both maternal exposures and mammary gland-specific biology. This work establishes a framework for understanding how genetic and environmental factors shape milk composition.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 16 Aug 2026.

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