No abstract

ScopeMicronutrients are in small amounts in foods, act in concert, and require variable amounts of time to see changes in health and risk for disease. These first principles are incorporated into an intervention study designed to develop new experimental strategies for setting target recommendations for food bioactives for populations and individuals.Methods and resultsA 6‐week multivitamin/mineral intervention is conducted in 9–13 year olds. Participants (136) are (i) their own control (n‐of‐1); (ii) monitored for compliance; (iii) measured for 36 circulating vitamin forms, 30 clinical, anthropometric, and food intake parameters at baseline, post intervention, and following a 6‐week washout; and (iv) had their ancestry accounted for as modifier of vitamin baseline or response. The same intervention is repeated the following year (135 participants). Most vitamins respond positively and many clinical parameters change in directions consistent with improved metabolic health to the intervention. Baseline levels of any metabolite predict its own response to the intervention. Elastic net penalized regression models are identified, and significantly predict response to intervention on the basis of multiple vitamin/clinical baseline measures.ConclusionsThe study design, computational methods, and results are a step toward developing recommendations for optimizing vitamin levels and health parameters for individuals.

No 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 6-14 year old in 2 years. Genetic makeup, blood metabolite and protein levels, and dietary differences were measured in each individual. Twenty-four-hour dietary intakes, eight 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.

Nutrition research, like most biomedical disciplines, adopted and often uses experimental approaches based on Beadle and Tatum's one gene-one polypeptide hypothesis, thereby reducing biological processes to single reactions or pathways. Systems thinking is needed to understand the complexity of health and disease processes requiring measurements of physiological processes, as well as environmental and social factors, which may alter the expression of genetic information. Analysis of physiological processes with omics technologies to assess systems' responses has only become available over the past decade and remains costly. Studies of environmental and social conditions known to alter health are often not connected to biomedical research. While these facts are widely accepted, developing and conducting comprehensive research programs for health are often beyond financial and human resources of single research groups. We propose a new research program on essential nutrients for optimal underpinning of growth and health (ENOUGH) that will use systems approaches with more comprehensive measurements and biostatistical analysis of the many biological and environmental factors that influence undernutrition. Creating a knowledge base for nutrition and health is a necessary first step toward developing solutions targeted to different populations in diverse social and physical environments for the two billion undernourished people in developed and developing economies.

Bioelectrical impedance vector analysis (BIVA) is a new method that is used for the routine monitoring of the variation in body fluids and nutritional status with assumptions regarding body composition values. The aim of the present study was to determine bivariate tolerance intervals of the whole-body impedance vector and to describe phase angle (PA) values for healthy term newborns aged 7-28 d. This descriptive cross-sectional study was conducted on healthy term neonates born at a low-risk public maternity. General and anthropometric neonatal data and bioelectrical impedance data (800 mA-50 kHz) were obtained. Bivariate vector analysis was conducted with the resistance -reactance (RXc) graph method. The BIVA software was used to construct the graphs. The study was conducted on 109 neonates (52·3 % females) who were born at term, adequate for gestational age, exclusively breast-fed and aged 13 (SD 3·6) d. We constructed one standard, reference, RXc-score graph and RXc-tolerance ellipses (50, 75 and 95 %) that can be used with any analyser. Mean PA was 3·14 (SD 0·43)8 (3·12 (SD 0·39)8 for males and 3·17 (SD 0·48)8 for females). Considering the overlapping of ellipses of males and females with the general distribution, a graph for newborns aged 7 -28 d with the same reference tolerance ellipse was defined for boys and girls. The results differ from those reported in the literature probably, in part, due to the ethnic differences in body composition. BIVA and PA permit an assessment without the need to know body weight and the prediction error of conventional impedance formulas.

OBJECTIVE:To describe nutritional status, body composition and lipid profile in children and adolescents receiving protease inhibitors.METHODS:Fifty-nine patients, 23 treated with protease inhibitors (group 1) and 36 not using protease inhibitors (group 2). Their dietary intake, anthropometry, bioimpedance analysis and lipid profile variables were measured.RESULTS:There was no difference in nutritional status or body composition between groups at the beginning of the study. After 6 months of follow-up, there was an increase in weight and height in both groups, as well as in waist circumference and subscapular skinfold thickness. In group 2, body mass index and triceps skinfold thickness adequacy were significantly higher after 6 months of follow-up. The groups had similar energy and macronutrient intake at any time point. After 6 months, group 1 had a higher cholesterol intake and group 2 had a higher fiber intake. Triglyceride serum levels were significantly different between the groups, with higher values in G1, at any time point [G1: 153 mg/dl (30–344); 138 (58–378) versus G2: 76 mg/dl (29–378); 76 (29–378)]. After 6 months of follow-up, G1 had higher LDL-cholesterol than G2 [104 mg/dl (40–142) versus 82 (42–145)].CONCLUSION:The use of protease inhibitors, per se, does not seem to significantly interfere with anthropometric measures, body composition and food intake of HIV-infected children and adolescents. However, this antiretroviral therapy was associated with a significant increase in triglyceride and LDL-cholesterol in our subjects.

Studies on children with cancer have suggested that energy expenditure may indeed be greater than predicted for healthy children. Nutritional assessment is important for intervention and for the prevention of complications associated with malnutrition. The present study aimed to describe the nutritional status, energy expenditure, and substrate utilization of children and adolescents with cancer compared to healthy children matched for age, sex, and body mass index. Subjects were evaluated by anthropometry, food intake pattern, and body composition analysis. Energy expenditure and substrate oxidation were measured by indirect calorimetry. Indirect calorimetry data, energy, and macronutrient intake, anthropometry, and body composition parameters showed no significant differences between groups. There was no evidence of increased energy expenditure or of a change in substrate utilization in children with cancer compared to the healthy group. The data regarding usual food consumption showed no significant differences between groups.