Location: Houston, Texas2012 Annual Report
1a. Objectives (from AD-416):
Obj. 1: No longer applies. Obj. 2: Investigate the pathways and nutritional modulation of methyl group production in under- and normal weight pregnant women. Sub-Obj 2A. Determine whole body protein kinetics, methionine kinetics and transmethylation, an index of methyl production and utilization, serine and glycine fluxes, indices of production rates of methyl group precursors, and conversion of serine to glycine, and glycine to CO2, indices of methyl group supply from these precursors to the transmethylation pathway, in under- and normal-weight pregnant women. Sub-Obj 2B. Determine the effect of dietary supplementation with sulfur amino acid-rich whey protein vs. legume/cereal protein on methionine production and transmethylation rate and on serine and glycine fluxes in underweight pregnant women. Sub-Obj 2C. Determine methionine kinetics and transmethylation rates during the first trimester in groups of underweight pregnant women with either normal or low plasma vitamin B12 concentration, after dietary supplementation with Vitamin B12. Sub-Obj 2D. Determine methionine kinetics and transmethylation rates in underweight pregnant women with either normal or low plasma folate concentration after dietary supplementation with folate.Obj. 3: Investigate differences in bowel flora, antioxidant capacity, and mitochondrial integrity between severely malnourished and well-nourished children. Sub-Obj 3A. Measure the populations of bacterial divisions and species in bowel flora populations in children as well as bowel flora diversity with edematous as well as non-edematous SCU and in well-nourished children. Sub-Obj 3B. Measure antioxidant capacity and mitochondrial integrity, as well as characterize the immune system in children with edematous vs. non-edematous SCU. Obj. 4: Initiate a pilot study of genetic susceptibility to ESCM. Obj. 5: Conduct exploratory analyses of the relationship between risk of ESCM and individual genetic variation. Obj. 6: Evaluate population-specific genetic variation. Obj. 7: Characterize the developmental profile of the GI microbiome and transcriptome in healthy, term infants. Obj. 8: Compare the effect of breast versus bottle-feeding on the development of GI microbiome and lactose digestion/absorption. Obj. 9: Profile changes in the GI microbiome in response to the introduction of weaning foods such as dietary starch in the form of cereal. Obj. 10: detect gene-gene/environment interactions.
1b. Approach (from AD-416):
Whole body protein kinetics, methionine production and transmethylation, serine and glycine fluxes, and conversion of serine to glycine and glycine to carbon dioxide will be measured in groups of Indian women with low (=18.5) and normal (>18.5 = 25) BMI between 10 and 12 weeks of pregnancy and again at 26-28 weeks. These measurements plus maternal gestational weight gain, neonate gestational age, birth weight, length, and head circumference will be repeated in groups with BMIs =18.5 after dietary supplement with more energy and protein and in those women with low blood vitamin B12 and folate, after 16 weeks of supplementation with vitamin B12 and folate. Additional studies will evaluate 6- to 24-month twins who are at high risk for malnutrition. Stool samples will be collected in a disposable diaper for multiplex pyrosequencing of bacterial 16S rRNA genes present in gut microbial communities and pyrosequencing of total community DNA (the gut microbiome). A second study will be performed in 50 severely undernourished, 6- to 12-month-old children who are receiving therapeutic food to promote rapid catch-up growth. Antioxidant capacity will be assessed by whole blood glutathione, erythrocyte superoxide dismutase, erythrocyte glutathione peroxidase, and serum oxidized proteins. Mitochondrial integrity will be assessed by lactate and the copy numbers of mitochondrial DNA/RNA in peripheral monocytes, measured by real time duplex nucleic acid sequence-based amplification. To assess how immune response varies with nutritional state, a panel of 27 cytokines will be assessed. Collect data on genetic susceptibility to ESCM and other phenotypes that result from malnutrition using cutting-edge genomics tools and methods in human genetics. Cutting edge technology will be utilized to address this significant global health/nutritional concern. Utilize models to identify genotype associations.
3. Progress Report:
We completed sub-objective 2C to determine methionine kinetics and transmethylation rates during the first trimester in underweight pregnant women with either normal or low plasma vitamin B(12) concentration and during the third trimester in the deficient group, after dietary supplementation with vitamin B(12). Studies were conducted to determine the effect of dietary supplementation with sulfur amino acid-rich whey protein versus legume/cereal protein on methionine production and transmethylation rate and on serine and glycine fluxes in underweight pregnant women. The data were analyzed and two manuscripts are being written. Studies to achieve sub-objective 2A, to determine whole body protein kinetics, methionine kinetics and transmethylation, an index of methyl production and utilization, serine and glycine fluxes, indices of production rates of methyl group precursors, and conversion of serine to glycine and glycine to carbon dioxide, indices of methyl group supply from these precursors to the transmethylation pathway, in underweight and normal weight pregnant women in the first and third trimesters have been started and will be continued. We have now completed measurements in 29 women. For objective 3A, a total of 321 pairs of twins and 3 sets of triplets have been enrolled at 5 different rural health centers in 4 different districts in southern Malawi, as part of a longitudinal study to explore the relationship between the intestinal microbiome and childhood growth and nutritional status. As of July all children have completed the follow-up. A total of 45 pairs of twins and 2 sets of triplets have had at least one child die during the course of the study. Through the course of the study, a total of 16,722 patient visits have been recorded and a total of 8,563 stool specimens have been collected from the children in the study during these visits. (An additional 519 specimens have been collected from their mothers and 250 specimens from sibling controls.) A total of 382 episodes of moderate acute malnutrition (defined as weight-for-height Z score between -2 and -3, without nutritional edema) have been diagnosed. In terms of severe acute malnutrition, a total of 88 episodes of kwashiorkor (nutritional edema regardless of weight) and 78 episodes of marasmus (weight-for-height Z score less than -3, without nutritional edema) have been diagnosed. Sample analyses are complete, a major publication in Nature has been released, and further data interpretation is pending. For objective 3B, we are continuing enrollment. 35 children have been enrolled and their samples are being analyzed. For objective 4-6 we continued using genomic approaches to understand differences in outcome among children with severe under-nutrition in the Afro-Caribbean population of Jamaica. We completed genome-wide genotyping of approximately 1 million DNA variants in 104 additional samples and looked for significant differences at the DNA sequence level between kwashiorkor and marasmus through a preliminary genomic association study. We performed additional analyses to determine genetic pathways that might be important to whether children develop Kwashiorkor or Marasmus. To provide another view of DNA-related differences between the two groups, we carried out a pilot study of genomic methylation patterns in individuals with kwashiorkor and marasmus by analyzing levels of DNA methylation at approximately 450,000 sites across the genome in 48 samples. In so doing we were able to fulfill one of our milestones from the previous year. General observations regarding differences in methylation between the two groups and analyses of the associated genetic pathways are ongoing and encouraging. The study promises some unique insights into Kwashiorkor, and is, to our knowledge, one of the first studies of its kind to be undertaken on this scale. We have also begun to integrate the genotyping results with methylation studies in order to fully understand and interpret the results obtained from both analyses. This is a new and particularly complex analysis that will require us to develop new statistical methodologies and paradigms. These analyses, however, have the potential to shed light upon why some children get the edematous form and not the non-edematous form of severe under-nutrition. We plan to engage our collaborators in Malawi, as well as potential collaborators in other parts of Africa (Ethiopia, Uganda), to bolster this effort, particularly with regard to replication and validation of results. In objectives 7-9, we had carried out a preliminary comparison of the gut microbial (bacterial) population in healthy children versus healthy adults. The total number of bacteria did not differ between children and adults. Because bacteria are classified by their degree of relatedness, we compared the children with the adults along a scale (phylogenetics) that provided information as to whether the bacteria were broadly related (phylum) down to closely related (genus). At the phylum level, a greater proportion of bacteria were Firmicutes in children compared with adults. In contrast, children had a smaller proportion of Bacteroidetes and Proteobacteria. At the genus level, the most striking difference was a greater abundance in children of Subdoligranulum, Dialister, and Alistipes. The genus Dialister was present in strikingly greater proportions (approximately ten-fold greater in terms of proportion) in children versus adults. In contrast, the children had a reduced proportion of Parabacteroides and Megamonas compared with adults. In order to develop more insight into what makes the composition of the gut microbial (bacterial) population unique in healthy children versus adults, we have begun to employ an analysis technique that has been used in the environmental sciences. This methodology, called network analysis, can demonstrate patterns of association between bacteria – how the presence of one organism is related to the presence of another, or alternatively, how they are independent of each other. This analysis will help us understand better how one group of bacteria enhance or inhibit the presence of another. Thus, we can begin to understand how "good" bacteria work together to protect us from "bad" bacteria. By comparing what people eat to the gut bacterial population, we can begin to learn how diet can affect the relationships between bacteria in the gut. Thus, we will understand better how, through its effect on bacteria, our diet can protect or predispose us to illness. As an outgrowth of network analysis, over the next year we will begin not only to identify specific bacteria in the gut, but will seek to define the genes they contain. Preliminary steps in this direction were started this past year. Knowing the genes the bacteria contain will allow us to make predictions about what chemicals the bacteria can produce. Among many other important pieces of information, it will begin to shed light on how good bacteria utilize dietary nutrients, how they communicate with each other, and how they promote the growth of other good bacteria, and influence our immune system and mental functioning. These results likely will have great implications for understanding and treating disorders of the immune system as well as mood disorders that now appear to be influenced, in part, by gut bacteria (and their products). For objective 10, we developed an efficient algorithm to directly work with diploid genotype data, so that the computation for local ancestry inference can be applied to three-way admixed individuals such as Latinos even without haploid reference genotypes. We also developed a statistical model and a preliminary computational method to sample directed acyclic graph, a way to specify a joint distribution for many variables. We developed a new computational method for Bayesian variable selection. It is much faster and can be used for risk assessment using genome-wide polymorphic data.