Journal
EUROPEAN JOURNAL OF NUTRITION
Volume 56, Issue 7, Pages 2379-2391Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s00394-016-1278-x
Keywords
Nutrition; Metabolomics; Twins; Biomarkers; Milk
Categories
Funding
- Wellcome Trust
- European Community's Seventh Framework Programme (FP7)
- National Institute for Health Research (NIHR) Clinical Research Facility at Guy's & St Thomas' NHS Foundation Trust
- NIHR Biomedical Research Centre at Guy's and St Thomas' NHS Foundation Trust and King's College London
- Pfizer
- Helmholtz Zentrum Munchen-German Research Center for Environmental Health - German Federal Ministry of Education and Research
- State of Bavaria
- Munich Center of Health Sciences (MC Health), Ludwig-Maximilians-Universitat, as part of LMUinnovativ
- European Union's Seventh Framework Programme (FP7-Health-F5) [305280]
- University of Tartu (Grant Center of Translational Genomics)
- Estonian Government [TP1GV14060I, ETF9353]
- European Commission through the European Regional Development Fund
- EFSD New Horizons grant
- Estonian Research Infrastructure's Roadmap
- FP7 Grant [313010]
- Medical Research Council [MR/M004422/1] Funding Source: researchfish
- National Institute for Health Research [NF-SI-0514-10027] Funding Source: researchfish
- MRC [MR/M004422/1] Funding Source: UKRI
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Purpose Milk provides a significant source of calcium, protein, vitamins and other minerals to Western populations throughout life. Due to its widespread use, the metabolic and health impact of milk consumption warrants further investigation and biomarkers would aid epidemiological studies. Methods Milk intake assessed by a validated food frequency questionnaire was analyzed against fasting blood metabolomic profiles from two metabolomic platforms in females from the TwinsUK cohort (n = 3559). The top metabolites were then replicated in two independent populations (EGCUT, n = 1109 and KORA, n = 1593), and the results from all cohorts were meta-analyzed. Results Four metabolites were significantly associated with milk intake in the TwinsUK cohort after adjustment for multiple testing (P < 8.08 x 10(-5)) and covariates (BMI, age, batch effects, family relatedness and dietary covariates) and replicated in the independent cohorts. Among the metabolites identified, the carnitine metabolite trimethyl-N-aminovalerate (beta = 0.012, SE = 0.002, P = 2.98 x 10(-12)) and the nucleotide uridine (beta = 0.004, SE = 0.001, P = 9.86 x 10(-6)) were the strongest novel predictive biomarkers from the non-targeted platform. Notably, the association between trimethyl-N-aminovalerate and milk intake was significant in a group of MZ twins discordant for milk intake (beta = 0.050, SE = 0.015, P = 7.53 x 10(-4)) and validated in the urine of 236 UK twins (beta = 0.091, SE = 0.032, P = 0.004). Two metabolites from the targeted platform, hydroxysphingomyelin C14:1 (beta = 0.034, SE = 0.005, P = 9.75 x 10(-14)) and diacylphosphatidylcholine C28:1 (beta = 0.034, SE = 0.004, P = 4.53 x 10(-16)), were also replicated. Conclusions We identified and replicated in independent populations four novel biomarkers of milk intake: trimethyl-N-aminovalerate, uridine, hydroxysphingomyelin C14:1 and diacylphosphatidylcholine C28:1. Together, these metabolites have potential to objectively examine and refine milk-disease associations.
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