This application addresses broad Challenge Area (03) Biomarker Discovery and Validation and specific challenge topic, 03-ES-101 Validation of new exposure assessment methodologies Suboptimal dietary macronutrient choices are arguably the major environmental stressor in individuals living in Western societies. Unraveling the specifics of this inter-relationship has been complicated by the well known difficulty in accurately assessing intake in a large human population. Our work within the Biological Response Indicators component of the Exposure Biology Program of the NIEHS/NIH Genes and Environment Initiative has focused on the development of a metabolomic signature of class-specific fats (eg, saturated, trans, polyunsaturated) and carbohydrates (differing glycemic index), including testing the biomarkers within the Nurses'Health Study I (NHS), a large, well-characterized human population. A distinct, but related component of dietary macronutrient choice is the distribution of the major nutrient between fat, carbohydrate, and protein. One study, OMNIHEART, uniquely offers the ability to generate and validate biomarkers for these macronutrients. OMNIHEART was a large (164 people), completely controlled feeding study in which each individual was rotated through 3 diets (6 weeks each). Our current specific design takes advantage of existing large electronic datasets (plasma metabolomics/proteomics on 3500/2000 people) that we have generated/are generating from the NHS samples under other NIH support. The reciprocal design proposed is complex but was chosen because it optimally leverages both these two resources (NHS, OMNIHEART). The goal of this study is to generate validated profiles for primary macronutrient balance.
The Aims are:
Aim 1 To determine the effects of primary macronutrient composition on the plasma metabolome and proteome by retrospectively mining existing datasets generated within NHS Aim 2: To validate the effects of primary macronutrient composition on the plasma metabolome and proteome determined in Aim 1 using the samples from OMNIHEART Aim 3: To determine the effects of primary macronutrient composition on the plasma metabolome and proteome in OMNIHEART Aim 4: To validate the profiles of primary macronutrient composition on the plasma metabolome and proteome determined developed in Aim 3 with existing data from NHS Aim 5: To determine the extent to which adherence to profiles reflecting primary macronutrients predict type II diabetes (part A) and breast cancer (part B) in previously profiled case control studies nested within the Nurses'Health Study The proposed studies are directly responsive to the RFA (RC1, 03-ES-101, Validation of new exposure assessment methodologies) and further general NIH goals of focusing on health and early interventions rather than late stage disease. The proposed study is well within the capacity of the lab to complete within 2 years.
Suboptimal dietary macronutrient choices are arguably the major environmental stressor in individuals living in Western societies. We have been studying the effect of overall caloric intake on chronic disease. We now propose to identify biomarkers that can be used in epidemiological studies to best understand the role of differential intake of protein, fat, and carbohydrate in chronic disease.
| Bird, Susan S; Marur, Vasant R; Sniatynski, Matthew J et al. (2011) Serum lipidomics profiling using LC-MS and high-energy collisional dissociation fragmentation: focus on triglyceride detection and characterization. Anal Chem 83:6648-57 |
| Chen, Yen-Fu; Hsu, Kai-Cheng; Lin, Po-Tsun et al. (2011) LigSeeSVM: ligand-based virtual screening using support vector machines and data fusion. Int J Comput Biol Drug Des 4:274-89 |
| Bird, Susan S; Marur, Vasant R; Sniatynski, Matthew J et al. (2011) Lipidomics profiling by high-resolution LC-MS and high-energy collisional dissociation fragmentation: focus on characterization of mitochondrial cardiolipins and monolysocardiolipins. Anal Chem 83:940-9 |
