Nutrition for the ageing brain: towards evidence for an optimal diet

As people age they become increasingly susceptible to chronic and extremely debilitating brain diseases. The precise cause of the neuronal degeneration underlying these disorders, and indeed normal brain ageing remains however elusive. Considering the limits of existing preventive methods, there is a desire to develop effective and safe strategies. Growing preclinical and clinical research in healthy individuals or at the early stage of cognitive decline has demonstrated the beneficial impact of nutrition on cognitive functions. The present review is the most recent in a series produced by the Nutrition and Mental Performance Task Force under the auspice of the International Life Sciences Institute Europe (ILSI Europe). The latest scientific advances specific to how dietary nutrients and non-nutrient may affect cognitive ageing are presented. Furthermore, several key points related to mechanisms contributing to brain ageing, pathological conditions affecting brain function, and brain biomarkers are also discussed. Overall, findings are inconsistent and fragmented and more research is warranted to determine the underlying mechanisms and to establish dose-response relationships for optimal brain maintenance in different population subgroups. Such approaches are likely to provide the necessary evidence to develop research portfolios that will inform about new dietary recommendations on how to prevent cognitive decline

Untargeted Metabolomics as a Screening Tool for Estimating Compliance to a Dietary Pattern

There is a growing interest in studying the nutritional effects of complex diets. For such studies, measurement of dietary compliance is a challenge because the currently available compliance markers cover only limited aspects of a diet. In the present study, an untargeted metabolomics approach was used to develop a compliance measure in urine to distinguish between two dietary patterns. A parallel intervention study was carried out in which 181 participants were randomized to follow either a New Nordic Diet (NND) or an Average Danish Diet (ADD) for 6 months. Dietary intakes were closely monitored over the whole study period, and 24 h urine samples as well as weighed dietary records were collected several times during the study. The urine samples were analyzed by UPLC-qTOF-MS, and a partial least-squares discriminant analysis with feature selection was applied to develop a compliance model based on data from 214 urine samples. The optimized model included 52 metabolites and had a misclassification rate of 19% in a validation set containing 139 samples. The metabolites identified in the model were markers of individual foods such as citrus, cocoa-containing products, and fish as well as more general dietary traits such as high fruit and vegetable intake or high intake of heat-treated foods. It was easier to classify the ADD diet than the NND diet probably due to seasonal variation in the food composition of NND and indications of lower compliance among the NND subjects. In conclusion, untargeted metabolomics is a promising approach to develop compliance measures that cover the most important discriminant metabolites of complex diets

Metabolomic profiling of spot urines from SU.VI.MAX2 subjects.

<p>Subjects reported either low or high consumption of coffee, represented by squares and circles respectively. A) One-dimensional OSC-PLS-DA score plot of urinary metabolomes of low and high consumers. B) Loading plot of the OSC-PLS-DA. Circled outlying ions contribute most strongly to the discrimination. C) Model validation assessed by permutation test (<i>n</i> = 100).</p

ROC curve AUCs for single and combination biomarkers.

<p>Error bars represent 95% confidence intervals. cIP, cyclo(isoleucyl-prolyl); MX, 1-methylxanthine; Tr, trigonelline; Atr, atractyligenin glucuronides; Caf, caffeine.</p

Chemical structures of some identified discriminants.

<p>Chemical structures of some identified discriminants.</p

Mass Spectrometry-based Metabolomics for the Discovery of Biomarkers of Fruit and Vegetable Intake: Citrus Fruit as a Case Study

Elucidation of the relationships between genotype, diet, and health requires accurate dietary assessment. In intervention and epidemiological studies, dietary assessment usually relies on questionnaires, which are susceptible to recall bias. An alternative approach is to quantify biomarkers of intake in biofluids, but few such markers have been validated so far. Here we describe the use of metabolomics for the discovery of nutritional biomarkers, using citrus fruits as a case study. Three study designs were compared. Urinary metabolomes were profiled for volunteers that had (a) consumed an acute dose of orange or grapefruit juice, (b) consumed orange juice regularly for one month, and (c) reported high or low consumption of citrus products for a large cohort study. Some signals were found to reflect citrus consumption in all three studies. Proline betaine and flavanone glucuronides were identified as known biomarkers, but various other biomarkers were revealed. Further, many signals that increased after citrus intake in the acute study were not sensitive enough to discriminate high and low citrus consumers in the cohort study. We propose that urine profiling of cohort subjects stratified by consumption is an effective strategy for discovery of sensitive biomarkers of consumption for a wide range of foods