Coffee polyphenols ameliorate early-life stress-induced cognitive deficits in male mice.

Stress exposure during the sensitive period of early development has been shown to program the brain and increases the risk to develop cognitive deficits later in life. We have shown earlier that early-life stress (ES) leads to cognitive decline at an adult age, associated with changes in adult hippocampal neurogenesis and neuroinflammation. In particular, ES has been shown to affect neurogenesis rate and the survival of newborn cells later in life as well as microglia, modulating their response to immune or metabolic challenges later in life. Both of these processes possibly contribute to the ES-induced cognitive deficits. Emerging evidence by us and others indicates that early nutritional interventions can protect against these ES-induced effects through nutritional programming. Based on human metabolomics studies, we identified various coffee-related metabolites to be part of a protective molecular signature against cognitive decline in humans. Caffeic and chlorogenic acids are coffee-polyphenols and have been described to have potent anti-oxidant and anti-inflammatory actions. Therefore, we here aimed to test whether supplementing caffeic and chlorogenic acids to the early diet could also protect against ES-induced cognitive deficits. We induced ES via the limited nesting and bedding paradigm in mice from postnatal(P) day 2-9. On P2, mice received a diet to which 0.02% chlorogenic acid (5-O-caffeoylquinic acid) + 0.02% caffeic acid (3',4'-dihydroxycinnamic acid) were added, or a control diet up until P42. At 4 months of age, all mice were subjected to a behavioral test battery and their brains were stained for markers for microglia and neurogenesis. We found that coffee polyphenols supplemented early in life protected against ES-induced cognitive deficits, potentially this is mediated by the survival of neurons or microglia, but possibly other mechanisms not studied here are mediating the effects. This study provides additional support for the potential of early nutritional interventions and highlights polyphenols as nutrients that can protect against cognitive decline, in particular for vulnerable populations exposed to ES.

Non-targeted metabolomic biomarkers and metabotypes of type 2 diabetes: A cross-sectional study of PREDIMED trial participants.

AIM: To characterize the urinary metabolomic fingerprint and multi-metabolite signature associated with type 2 diabetes (T2D), and to classify the population into metabotypes related to T2D. METHODS: A metabolomics analysis using the 1H-NMR-based, non-targeted metabolomic approach was conducted to determine the urinary metabolomic fingerprint of T2D compared with non-T2D participants in the PREDIMED trial. The discriminant metabolite fingerprint was subjected to logistic regression analysis and ROC analyses to establish and to assess the multi-metabolite signature of T2D prevalence, respectively. Metabotypes associated with T2D were identified using the k-means algorithm. RESULTS: A total of 33 metabolites were significantly different (P<0.05) between T2D and non-T2D participants. The multi-metabolite signature of T2D comprised high levels of methylsuccinate, alanine, dimethylglycine and guanidoacetate, and reduced levels of glutamine, methylguanidine, 3-hydroxymandelate and hippurate, and had a 96.4% AUC, which was higher than the metabolites on their own and glucose. Amino-acid and carbohydrate metabolism were the main metabolic alterations in T2D, and various metabotypes were identified in the studied population. Among T2D participants, those with a metabotype of higher levels of phenylalanine, phenylacetylglutamine, p-cresol and acetoacetate had significantly higher levels of plasma glucose. CONCLUSION: The multi-metabolite signature of T2D highlights the altered metabolic fingerprint associated mainly with amino-acid, carbohydrate and microbiota metabolism. Metabotypes identified in this patient population could be related to higher risk of long-term cardiovascular events and therefore require further studies. Metabolomics is a useful tool for elucidating the metabolic complexity and interindividual variation in T2D towards the development of stratified precision nutrition and medicine. Trial registration at www.controlled-trials.com: ISRCTN35739639.

Evolution of occupational asthma: does cessation of exposure really improve prognosis?

AIM: To assess the evolution of occupational asthma (OA) depending on whether the patient avoids or continues with exposure to the offending agent. METHODS: Study in patients diagnosed with OA using a specific inhalation challenge. Patients underwent the following examinations on the same day: clinical interview, physical examination, forced spirometry, methacholine test and determination of total IgE. Clinical improvement, deterioration or no change were defined according to the changes seen on the GINA severity scale at the time of diagnosis. RESULTS: Of the 73 patients finally included, 55 had totally ended exposure and 18 continued to be exposed at work. Clinical improvement was observed in 47% of those who had terminated exposure and in 22% of those who remained exposed; clinical deterioration was observed in 14% and 17% respectively (p = 0.805). Logistical regression analysis, including the type of agent and the persistence or avoidance of exposure among the variables, did not show any predictive factors of clinical evolution. Similarly, the changes in FEV1 and in bronchial hyperresponsiveness were not associated with the avoidance or continuation of exposure to the causative agent. CONCLUSIONS: Avoiding exposure to the causative agent in patients with OA does not seem to improve prognosis in this disease. Despite these findings, there is insufficient evidence to recommend a change in current management guidelines.

SerbGO: searching for the best GO tool.

In recent years, the scientific community has provided many tools to assist with pathway analysis. Some of these programs can be used to manage functional annotation of gene products, others are oriented to exploring and analyzing data sets and many allow both possibilities. Potential users of these tools are faced with the necessity to decide which of the existing programs are the most appropriate for their needs. SerbGO is a user-friendly web tool created to facilitate this task. It can be used (i) to search for specific functionalities and determine which applications provide them and (ii) to compare several applications on the basis of different types of functionalities. Iterating and combining both functionalities can easily lead to selecting an appropriate tool. Data required by SerbGO is either the desired capabilities within a defined Standard Functionalities Set or the list of the tools to be compared. The analysis performed carries out a cross-classification that produces an easily readable output with the list of tools that implement the capabilities demanded or a table with the categorization of the GO tools that one wishes to compare. SerbGO is freely available and does not require a login. It can be accessed either directly at our server (http://estbioinfo.stat.ub.es/apli/serbgo) or at the GO Consortium website (http://www.geneontology.org/GO.tools.microarray.shtml#serbgo).