Showing papers by "John W. Newman published in 2010"

Plasma Metabolomic Profiles Reflective of Glucose Homeostasis in Non-Diabetic and Type 2 Diabetic Obese African-American Women

Abstract: Insulin resistance progressing to type 2 diabetes mellitus (T2DM) is marked by a broad perturbation of macronutrient intermediary metabolism. Understanding the biochemical networks that underlie metabolic homeostasis and how they associate with insulin action will help unravel diabetes etiology and should foster discovery of new biomarkers of disease risk and severity. We examined differences in plasma concentrations of >350 metabolites in fasted obese T2DM vs. obese non-diabetic African-American women, and utilized principal components analysis to identify 158 metabolite components that strongly correlated with fasting HbA1c over a broad range of the latter (r = −0.631; p<0.0001). In addition to many unidentified small molecules, specific metabolites that were increased significantly in T2DM subjects included certain amino acids and their derivatives (i.e., leucine, 2-ketoisocaproate, valine, cystine, histidine), 2-hydroxybutanoate, long-chain fatty acids, and carbohydrate derivatives. Leucine and valine concentrations rose with increasing HbA1c, and significantly correlated with plasma acetylcarnitine concentrations. It is hypothesized that this reflects a close link between abnormalities in glucose homeostasis, amino acid catabolism, and efficiency of fuel combustion in the tricarboxylic acid (TCA) cycle. It is speculated that a mechanism for potential TCA cycle inefficiency concurrent with insulin resistance is “anaplerotic stress” emanating from reduced amino acid-derived carbon flux to TCA cycle intermediates, which if coupled to perturbation in cataplerosis would lead to net reduction in TCA cycle capacity relative to fuel delivery.

Insight in modulation of inflammation in response to diclofenac intervention: a human intervention study.

Abstract: Background. Chronic systemic low-grade inflammation in obese subjects is associated with health complications including cardiovascular diseases, insulin resistance and diabetes. Reducing inflammatory responses may reduce these risks. However, available markers of inflammatory status inadequately describe the complexity of metabolic responses to mild anti-inflammatory therapy. Methods. To address this limitation, we used an integrative omics approach to characterize modulation of inflammation in overweight men during an intervention with the non-steroidal anti-inflammatory drug diclofenac. Measured parameters included 80 plasma proteins, >300 plasma metabolites (lipids, free fatty acids, oxylipids and polar compounds) and an array of peripheral blood mononuclear cells (PBMC) gene expression products. These measures were submitted to multivariate and correlation analysis and were used for construction of biological response networks. Results. A panel of genes, proteins and metabolites, including PGE2 and TNF-alpha, were identified that describe a diclofenac-response network (68 genes in PBMC, 1 plasma protein and 4 plasma metabolites). Novel candidate markers of inflammatory modulation included PBMC expression of annexin A1 and caspase 8, and the arachidonic acid metabolite 5,6-DHET. Conclusion. In this study the integrated analysis of a wide range of parameters allowed the development of a network of markers responding to inflammatory modulation, thereby providing insight into the complex process of inflammation and ways to assess changes in inflammatory status associated with obesity. Trial registration. The study is registered as NCT00221052 in clinicaltrials.gov database. © 2010 van Erk et al; licensee BioMed Central Ltd.

Web-Enabled and Improved Software Tools and Data Are Needed to Measure Nutrient Intakes and Physical Activity for Personalized

Abstract: Food intake, physical activity (PA), and genetic makeup each affect health and each factor influences the impact of theother 2 factors. Nutrigenomics describes interactions between genes and environment. Knowledge about the interplaybetween environment and genetics would be improved if experimental designs included measures of nutrient intake andPA. Lack of familiarity about how to analyze environmental variables and ease of access to tools and measurementinstruments are 2 deterrents to these combined studies. This article describes the state of the art for measuring foodintake and PA to encourage researchers to make their tools better known and more available to workers in other fields.InformationpresentedwasdiscussedduringaworkshoponthistopicsponsoredbytheUSDA,NIH,andFDAinthespringof 2009. J. Nutr. doi: 10.3945/jn.110.128371. Introduction Omics technologies open new avenues to produce discipline-specific research knowledge that is transforming biomedicalresearch. Omics are generally defined as any high-informationcontentanalysesof a large numberof analytical targets belongingtoorganizationalsubclassessuchasgenes,metabolites,proteins,and transcripts. Combining results from several omic technolo-gies in 1 study to more fully characterize and quantify physiolo-gical processesandgeneticmakeupisfundamentaltothepromiseof creating science-based, personalized nutrition, medicine, andhealthcare.The breadth of a population’s response to normal andstressful environmental exposures is defined by the extent ofindividual responses within that population, with geneticvariation being a major contributor to this variance. Thus, theintegration of datasets from deep phenotyping (1) and geno-typing is necessary, but likely insufficient, to develop theknowledge base for personalized healthcare. Metabolic phe-notypes, whether healthy or diseased, result from complexinteractions between an individual’s genetic makeup and hisor her environment. Because food is required for survival,nutrients and other bioactive compounds are among the mostimportant environmental factors to alter the expression ofgenetic information [reviewed in (2,3)]. However, manygenomic and omic studies fail to account for not only theenergy intake but also the types and amounts of nutrientsconsumed (4). Moreover, the fate of consumed energy isdetermined by combining the energy expenditure and meta-bolic efficiency in fuel use of an individual, which also isaffected by genetic makeup. Thus, the quality and quantity ofthe diet, in conjunction with energetic demand and fitness ofthe individual, are critical variables affecting health mainte-nance. The dramatic rise in obesity and nutrition-relatedchronic diseases in the past;25 y confirms the importance ofenergy balance in maintaining health (5).The “silo” nature of biomedical research (most advancesdevelop vertically within the discipline rather than horizontallybetween and among multiple fields) is often blamed for the

Web-Enabled and Improved Software Tools and Data Are Needed to Measure Nutrient Intakes and Physical Activity for Personalized Health Research

Abstract: Food intake, physical activity (PA), and genetic makeup each affect health and each factor influences the impact of the other 2 factors. Nutrigenomics describes interactions between genes and environment. Knowledge about the interplay between environment and genetics would be improved if experimental designs included measures of nutrient intake and PA. Lack of familiarity about how to analyze environmental variables and ease of access to tools and measurement instruments are 2 deterrents to these combined studies. This article describes the state of the art for measuring food intake and PA to encourage researchers to make their tools better known and more available to workers in other fields. Information presented was discussed during a workshop on this topic sponsored by the USDA, NIH, and FDA in the spring of 2009.