POMAShiny: A user-friendly web-based workflow for metabolomics and proteomics data analysis

Metabolomics and proteomics, like other omics domains, usually face a data mining challenge in providing an understandable output to advance in biomarker discovery and precision medicine. Often, statistical analysis is one of the most difficult challenges and it is critical in the subsequent biological interpretation of the results. Because of this, combined with the computational programming skills needed for this type of analysis, several bioinformatic tools aimed at simplifying metabolomics and proteomics data analysis have emerged. However, sometimes the analysis is still limited to a few hidebound statistical methods and to data sets with limited flexibility. POMAShiny is a web-based tool that provides a structured, flexible and user-friendly workflow for the visualization, exploration and statistical analysis of metabolomics and proteomics data. This tool integrates several statistical methods, some of them widely used in other types of omics, and it is based on the POMA R/Bioconductor package, which increases the reproducibility and flexibility of analyses outside the web environment. POMAShiny and POMA are both freely available at https://github.com/nutrimetabolomics/POMAShiny and https://github.com/nutrimetabolomics/POMA, respectively

Absence of a priming effect on dissolved organic carbon degradation in lake water

The idea that small amounts of labile organic carbon might trigger the degradation of previously unreactive organic matter has attracted increasing scientific interest across multiple disciplines. Although this phenomenon, referred to as priming, has been widely reported in soils, evidence in freshwater systems is scarce and inconclusive. Here, we use a multifactorial microcosm experiment to test the conditions under which priming may be observed in freshwater ecosystems. We assessed the effect of pulse additions of three labile carbon sources (acetate, glucose, and cellobiose) on dissolved organic carbon (DOC) consumption using water from lakes with different trophic states (eutrophic to oligotrophic and clear to brownwater lakes). We further analyzed the effect of nutrient availability and the role of attachment of cells to surfaces. Despite the range of conditions tested, we found no clear evidence of a priming effect on DOC degradation, indicating that priming in freshwater systems may be of limited importance

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 1 H-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 medicin

Exhaustion of mitochondrial and autophagic reserve may contribute to the development of LRRK2 G2019S -Parkinson's disease

BACKGROUND: Mutations in leucine rich repeat kinase 2 (LRRK2) are the most common cause of familial Parkinson's disease (PD). Mitochondrial and autophagic dysfunction has been described as etiologic factors in different experimental models of PD. We aimed to study the role of mitochondria and autophagy in LRRK2 G2019S -mutation, and its relationship with the presence of PD-symptoms. METHODS: Fibroblasts from six non-manifesting LRRK2 G2019S -carriers (NM-LRRK2 G2019S ) and seven patients with LRRK2 G2019S -associated PD (PD-LRRK2 G2019S ) were compared to eight healthy controls (C). An exhaustive assessment of mitochondrial performance and autophagy was performed after 24-h exposure to standard (glucose) or mitochondrial-challenging environment (galactose), where mitochondrial and autophagy impairment may be heightened. RESULTS: A similar mitochondrial phenotype of NM-LRRK2 G2019S and controls, except for an early mitochondrial depolarization (54.14% increased, p = 0.04), was shown in glucose. In response to galactose, mitochondrial dynamics of NM-LRRK2 G2019S improved (- 17.54% circularity, p = 0.002 and + 42.53% form factor, p = 0.051), probably to maintain ATP levels over controls. A compromised bioenergetic function was suggested in PD-LRRK2 G2019S when compared to controls in glucose media. An inefficient response to galactose and worsened mitochondrial dynamics (- 37.7% mitochondrial elongation, p = 0.053) was shown, leading to increased oxidative stress. Autophagy initiation (SQTSM/P62) was upregulated in NM-LRRK2 G2019S when compared to controls (glucose + 118.4%, p = 0.014; galactose + 114.44%, p = 0.009,) and autophagosome formation increased in glucose media. Despite of elevated SQSTM1/P62 levels of PD-NM G2019S when compared to controls (glucose + 226.14%, p = 0.04; galactose + 78.5%, p = 0.02), autophagosome formation was deficient in PD-LRRK2 G2019S when compared to NM-LRRK2 G2019S (- 71.26%, p = 0.022). CONCLUSIONS: Enhanced mitochondrial performance of NM-LRRK2 G2019S in mitochondrial-challenging conditions and upregulation of autophagy suggests that an exhaustion of mitochondrial bioenergetic and autophagic reserve, may contribute to the development of PD in LRRK2 G2019S mutation carriers

Microbial metabolites are associated with a high adherence to a Mediterranean dietary pattern using a 1h-nmr-based untargeted metabolomics approach

The study of biomarkers of dietary patterns including the Mediterranean diet (MedDiet) is scarce and could improve the assessment of these patterns. Moreover, it could provide a better understanding of health benefits of dietary patterns in nutritional epidemiology. We aimed to determine a robust and accurate biomarker associated with a high adherence to a MedDiet pattern that included dietary assessment and its biological effect. In this cross-sectional study, we included 56 and 63 individuals with high (H-MDA) and low (L-MDA) MedDiet adherence categories, respectively, all from the Prevención con Dieta Mediterránea trial. A 1H-NMR-based untargeted metabolomics approach was applied to urine samples. Multivariate statistical analyses were conducted to determine the metabolite differences between groups. A stepwise logistic regression and receiver operating characteristic curves were used to build and evaluate the prediction model for H-MDA. Thirty-four metabolites were identified as discriminant between H-MDA and L-MDA. The fingerprint associated with H-MDA included higher excretion of proline betaine and phenylacetylglutamine, among others, and decreased amounts of metabolites related to glucose metabolism. Three microbial metabolites - phenylacetylglutamine, p-cresol and 4-hydroxyphenylacetate - were included in the prediction model of H-MDA (95% specificity, 95% sensitivity and 97% area under the curve). The model composed of microbial metabolites was the biomarker that defined high adherence to a Mediterranean dietary pattern. The overall metabolite profiling identified reflects the metabolic modulation produced by H-MDA. The proposed biomarker may be a better tool for assessing and aiding nutritional epidemiology in future associations between H-MDA and the prevention or amelioration of chronic diseases

Plasma metabolomic profiles of plant-based dietary indices reveal potential pathways for metabolic syndrome associations

Background and aims: Plant-based dietary patterns have been associated with improved health outcomes. This study aims to describe the metabolomic fingerprints of plant-based diet indices (PDI) and examine their association with metabolic syndrome (MetS) and its components in a Danish population. Methods: The MAX study comprised 676 participants (55% women, aged 18-67 y) from Copenhagen. Sociodemographic and dietary data were collected using questionnaires and three 24-h dietary recalls over one year (at baseline, and at 6 and 12 months). Mean dietary intakes were computed, as well as overall PDI, healthful (hPDI) and unhealthful (uPDI) scores, according to food groups for each plant-based index. Clinical variables were also collected at the same time points in a health examination that included complete blood tests. MetS was defined according to the International Diabetes Federation criteria. Plasma metabolites were measured using a targeted metabolomics approach. Metabolites associated with PDI were selected using random forest models and their relationships with PDIs and MetS were analyzed using generalized linear mixed models. Results: The mean prevalence of MetS was 10.8%. High, compared to low, hPDI and uPDI scores were associated with a lower and higher odd of MetS, respectively [odds ratio (95%CI); hPDI: 0.56 (0.43–0.74); uPDI: 1.61 (1.26–2.05)]. Out of 411 quantified plasma metabolites, machine-learning metabolomics fingerprinting revealed 13 metabolites, including food and food-related microbial metabolites, like hypaphorine, indolepropionic acid and lignan-derived enterolactones. These metabolites were associated with all PDIs and were inversely correlated with MetS components (p &lt; 0.05). Furthermore, they had an explainable contribution of 12% and 14% for the association between hPDI or uPDI, respectively, and MetS only among participants with overweight/obesity. Conclusions: Metabolites associated with PDIs were inversely associated with MetS and its components, and may partially explain the effects of plant-based diets on cardiometabolic risk factors

Microbial metabolites are associated with a high adherence to a Mediterranean dietary pattern using a 1H-NMR-based untargeted metabolomics approach [Congrés]

Podeu consultar el III Workshop anual INSA-UB complet a: http://hdl.handle.net/2445/118993Sessió 3. Comunicació oral núm.

Curso básico de R

[eng] This document is an introductory course to the R statistical language. It consists of a set of slides in PDF format. R is an environment for statistical computing and graphics. It implements most of standard statistical tools and is specially useful in statistical research and biomedicine. In addition, R is a software free project and it is very similar to the commercial statistical package S-PLUS. This course can be used for self-teaching. Just follow it step by step and you will learn R in a practical and relatively quick way.[cat] Aquest document s'utilitza per impartir un curs bàsic del llenguatge estadístic R. Es tracta d'una presentació amb diapositives en format PDF. El programari R és un entorn per al càlcul estadístic i gràfics. Implementa la majoria dels procediments estadístics estàndard i s'utilitza especialment en la recerca estadística i biomèdica. A més, R és un projecte de software lliure, molt semblant al programa estadístic comercial S-PLUS. Aquest curs es pot utilitzar per a l¿autoaprenentatge. N'hi ha prou amb seguir pas a pas els exemples i les instruccions i aprendrem R de forma pràctica i relativament ràpida.[spa] Este documento se utiliza para impartir un curso básico del lenguaje estadístico R. Se trata de una presentación con diapositivas en formato PDF. El programa R es un entorno para el cálculo estadístico y gráficos. Implementa la mayoría de los procedimientos estadísticos estándar y se utiliza especialmente en la investigación estadística y biomédica. Además, R es un proyecto de software libre, muy similar al programa estadístico comercial S-PLUS. Este curso se puede utilizar para el autoaprendizaje. Basta seguir paso a paso los ejemplos e instrucciones y aprenderemos R de forma práctica y relativamente rápida

Absence of a priming effect on dissolved organic carbon degradation in lake water

The idea that small amounts of labile organic carbon might trigger the degradation of previously unreactive organic matter has attracted increasing scientific interest across multiple disciplines. Although this phenomenon, referred to as priming, has been widely reported in soils, evidence in freshwater systems is scarce and inconclusive. Here, we use a multifactorial microcosm experiment to test the conditions under which priming may be observed in freshwater ecosystems. We assessed the effect of pulse additions of three labile carbon sources (acetate, glucose, and cellobiose) on dissolved organic carbon (DOC) consumption using water from lakes with different trophic states (eutrophic to oligotrophic and clear to brownwater lakes). We further analyzed the effect of nutrient availability and the role of attachment of cells to surfaces. Despite the range of conditions tested, we found no clear evidence of a priming effect on DOC degradation, indicating that priming in freshwater systems may be of limited importance

Microbial metabolites are associated with a high adherence to a Mediterranean dietary pattern using a 1H-NMR-based untargeted metabolomics approach

Podeu consultar el III Workshop anual INSA-UB complet a: http://hdl.handle.net/2445/118993Sessió 3. Comunicació oral núm.