Methylation potential associated with diet, genotype, protein, and metabolite levels in the Delta Obesity Vitamin Study

Authors: MONTEIRO, JACQUELINE - Sao Paulo State University (UNESP); WISE, CAROLYN - Food And Drug Administration(FDA); MORINE, MELISSA - Sao Paulo State University (UNESP); TEITEL, CANDEE - Food And Drug Administration(FDA); PENCE, LISA - Food And Drug Administration(FDA); WILLIAMS, ANNA - Food And Drug Administration(FDA); MCCABE-SELLERS, BEVERLY - Delta Nutrition Intervention Research Iniative (NIRI); CHAMPAGNE, CATHERINE - Pennington Biomedical Research Center; TURNER, JEROME - Delta Nutrition Intervention Research Iniative (NIRI); SHELBY, BEATRICE - Delta Nutrition Intervention Research Iniative (NIRI); BAITANG, NING - Food And Drug Administration(FDA); OGUNTIMEIN, JOAN - Drexel University; TAYLOR, LAUREN - Emory University; TOENNESSEN, TERRI - Food And Drug Administration(FDA); PRIAMI, CORRADO - University Of Trento, Italy; BEGER, RICHARD - Food And Drug Administration(FDA); BOGLE, MARGARET - Delta Nutrition Intervention Research Iniative (NIRI); KAPUT, JIM - Nestle

Submitted to: Genes and Nutrition
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/6/2014
Publication Date: 4/24/2014
Citation: Monteiro, J.P., Wise, C., Morine, M.J., Teitel, C., Pence, L., Williams, A., McCabe-Sellers, B., Champagne, C., Turner, J., Shelby, B., Baitang, N., Oguntimein, J., Taylor, L., Toennessen, T., Priami, C., Beger, R.D., Bogle, M., Kaput, J. 2014. Methylation potential associated with diet, genotype, protein, and metabolite levels in the Delta Obesity Vitamin Study. Genes and Nutrition. 9:403.

Interpretive Summary: An optimal level of micronutrients is essential to maintain health and prevent the onset of chronic diseases. A team of researchers conducted an observational study that analyzed blood micronutrient levels in children who attended the Boys, Girls, Adults Development Center's summer day camp in Marvel, AR. In this paper we described differences in blood levels of vitamins and other metabolites between girls and boys or between children of different ages. Through our research activities we found that that there was an association between the ratio of two red blood cell metabolites and specific patterns of nutrient and energy intake among the children. This research provides the foundation for similar studies being conducted in populations throughout the world and aids in developing strategies for nutritional interventions in target groups of individuals.

Technical Abstract: Micronutrient research typically focuses on analyzing the effects of single or a few nutrients on health by analyzing a limited number of biomarkers. The observational study described here analyzed micronutrients, plasma proteins, dietary intakes, and genotype using a systems approach. Participants attended a community-based summer day program for 6– to 14-year-old children in 2 years. Genetic makeup, blood metabolite and protein levels, and dietary differences were measured in each individual. Twenty-four-hour dietary intakes, 8 micronutrients (vitamins A, D, E, thiamin, folic acid, riboflavin, pyridoxal, and pyridoxine) and 3 one-carbon metabolites [homocysteine (Hcy), S-adenosylmethionine (SAM), and S-adenosylhomocysteine (SAH)], and 1,129 plasma proteins were analyzed as a function of diet at metabolite level, plasma protein level, age, and sex. Cluster analysis identified two groups differing in SAM/SAH and differing in dietary intake patterns, indicating that SAM/SAH was a potential marker of nutritional status. The approach used to analyze genetic association with the SAM/SAH metabolites is called middle-out: SNPs in 275 genes involved in the one-carbon pathway (folate, pyridoxal/pyridoxine, thiamin) or were correlated with SAM/SAH (vitamin A, E, Hcy) were analyzed instead of the entire 1M SNP data set. This procedure identified 46 SNPs in 25 genes associated with SAM/SAH demonstrating a genetic contribution to the methylation potential. Individual plasma metabolites correlated with 99 plasma proteins. Fourteen proteins correlated with body mass index, 49 with group age, and 30 with sex. The analytical strategy described here identified subgroups for targeted nutritional interventions.