Urinary metabolic signatures of human adiposity

2-Furoylglycine as a Candidate Biomarker of Coffee Consumption

Specific and sensitive food biomarkers are necessary to support dietary intake assessment and link nutritional habits to potential impact on human health. A multistep nutritional intervention study was conducted to suggest novel biomarkers for coffee consumption. (1)H NMR metabolic profiling combined with multivariate data analysis resolved 2-furoylglycine (2-FG) as a novel putative biomarker for coffee consumption. We relatively quantified 2-FG in the urine of coffee drinkers and investigated its origin, metabolism, and excretion kinetics. When searching for its potential precursors, we found different furan derivatives in coffee products, which are known to get metabolized to 2-FG. Maximal urinary excretion of 2-FG occurred 2 h after consumption (p = 0.0002) and returned to baseline after 24 h (p = 0.74). The biomarker was not excreted after consumption of coffee substitutes such as tea and chicory coffee and might therefore be a promising acute biomarker for the detection of coffee consumption in human urine.

First Trimester Urine and Serum Metabolomics for Prediction of Preeclampsia and Gestational Hypertension: A Prospective Screening Study

Hypertensive disorders of pregnancy, including preeclampsia, are major contributors to maternal morbidity. The goal of this study was to evaluate the potential of metabolomics to predict preeclampsia and gestational hypertension from urine and serum samples in early pregnancy, and elucidate the metabolic changes related to the diseases. Metabolic profiles were obtained by nuclear magnetic resonance spectroscopy of serum and urine samples from 599 women at medium to high risk of preeclampsia (nulliparous or previous preeclampsia/gestational hypertension). Preeclampsia developed in 26 (4.3%) and gestational hypertension in 21 (3.5%) women. Multivariate analyses of the metabolic profiles were performed to establish prediction models for the hypertensive disorders individually and combined. Urinary metabolomic profiles predicted preeclampsia and gestational hypertension at 51.3% and 40% sensitivity, respectively, at 10% false positive rate, with hippurate as the most important metabolite for the prediction. Serum metabolomic profiles predicted preeclampsia and gestational hypertension at 15% and 33% sensitivity, respectively, with increased lipid levels and an atherogenic lipid profile as most important for the prediction. Combining maternal characteristics with the urinary hippurate/creatinine level improved the prediction rates of preeclampsia in a logistic regression model. The study indicates a potential future role of clinical importance for metabolomic analysis of urine in prediction of preeclampsia.

The promise of metabolic phenotyping in gastroenterology and hepatology

Disease risk and treatment response are determined, at the individual level, by a complex history of genetic and environmental interactions, including those with our endogenous microbiomes. Personalized health care requires a deep understanding of patient biology that can now be measured using a range of '-omics' technologies. Patient stratification involves the identification of genetic and/or phenotypic disease subclasses that require different therapeutic strategies. Stratified medicine approaches to disease diagnosis, prognosis and therapeutic response monitoring herald a new dimension in patient care. Here, we explore the potential value of metabolic profiling as applied to unmet clinical needs in gastroenterology and hepatology. We describe potential applications in a number of diseases, with emphasis on large-scale population studies as well as metabolic profiling on the individual level, using spectrometric and imaging technologies that will leverage the discovery of mechanistic information and deliver novel health care solutions to improve clinical pathway management.