QComics: Recommendations and Guidelines for Robust, Easily Implementable and Reportable Quality Control of Metabolomics Data.

The implementation of quality control strategies is crucial to ensure the reproducibility, accuracy, and meaningfulness of metabolomics data. However, this pivotal step is often overlooked within the metabolomics workflow and frequently relies on the use of nonstandardized and poorly reported protocols. To address current limitations in this respect, we have developed QComics, a robust, easily implementable and reportable method for monitoring and controlling data quality. The protocol operates in various sequential steps aimed to (i) correct for background noise and carryover, (ii) detect signal drifts and "out-of-control" observations, (iii) deal with missing data, (iv) remove outliers, (v) monitor quality markers to identify samples affected by improper collection, preprocessing, or storage, and (vi) assess overall data quality in terms of precision and accuracy. Notably, this tool considers important issues often neglected along quality control, such as the need of separately handling missing values and truly absent data to avoid losing relevant biological information, as well as the large impact that preanalytical factors may elicit on metabolomics results. Altogether, the guidelines compiled in QComics might contribute to establishing gold standard recommendations and best practices for quality control within the metabolomics community.

Association of dietary and nutritional factors with cognitive decline, dementia, and depressive symptomatology in older individuals according to a neurogenesis-centred biological susceptibility to brain ageing.

Hippocampal neurogenesis (HN) occurs throughout the life course and is important for memory and mood. Declining with age, HN plays a pivotal role in cognitive decline (CD), dementia, and late-life depression, such that altered HN could represent a neurobiological susceptibility to these conditions. Pertinently, dietary patterns (e.g., Mediterranean diet) and/or individual nutrients (e.g., vitamin D, omega 3) can modify HN, but also modify risk for CD, dementia, and depression. Therefore, the interaction between diet/nutrition and HN may alter risk trajectories for these ageing-related brain conditions. Using a subsample (n = 371) of the Three-City cohort-where older adults provided information on diet and blood biobanking at baseline and were assessed for CD, dementia, and depressive symptomatology across 12 years-we tested for interactions between food consumption, nutrient intake, and nutritional biomarker concentrations and neurogenesis-centred susceptibility status (defined by baseline readouts of hippocampal progenitor cell integrity, cell death, and differentiation) on CD, Alzheimer's disease (AD), vascular and other dementias (VoD), and depressive symptomatology, using multivariable-adjusted logistic regression models. Increased plasma lycopene concentrations (OR [95% CI] = 1.07 [1.01, 1.14]), higher red meat (OR [95% CI] = 1.10 [1.03, 1.19]), and lower poultry consumption (OR [95% CI] = 0.93 [0.87, 0.99]) were associated with an increased risk for AD in individuals with a neurogenesis-centred susceptibility. Increased vitamin D consumption (OR [95% CI] = 1.05 [1.01, 1.11]) and plasma γ-tocopherol concentrations (OR [95% CI] = 1.08 [1.01, 1.18]) were associated with increased risk for VoD and depressive symptomatology, respectively, but only in susceptible individuals. This research highlights an important role for diet/nutrition in modifying dementia and depression risk in individuals with a neurogenesis-centred susceptibility.

Childhood obesity, metabolic syndrome, and oxidative stress: microRNAs go on stage.

The incidence of childhood obesity and metabolic syndrome has grown notably in the last years, becoming major public health burdens in developed countries. Nowadays, oxidative stress is well-recognized to be closely associated with the onset and progression of several obesity-related complications within the framework of a complex crosstalk involving other intertwined pathogenic events, such as inflammation, insulin disturbances, and dyslipidemia. Thus, understanding the molecular basis behind these oxidative dysregulations could provide new approaches for the diagnosis, prevention, and treatment of childhood obesity and associated disorders. In this respect, the transcriptomic characterization of miRNAs bares great potential because of their involvement in post-transcriptional modulation of genetic expression. Herein, we provide a comprehensive literature revision gathering state-of-the-art research into the association between childhood obesity, metabolic syndrome, and miRNAs. We put special emphasis on the potential role of miRNAs in modulating obesity-related pathogenic events, with particular focus on oxidative stress.

Impaired hippocampal neurogenesis in vitro is modulated by dietary-related endogenous factors and associated with depression in a longitudinal ageing cohort study.

Environmental factors like diet have been linked to depression and/or relapse risk in later life. This could be partially driven by the food metabolome, which communicates with the brain via the circulatory system and interacts with hippocampal neurogenesis (HN), a form of brain plasticity implicated in depression aetiology. Despite the associations between HN, diet and depression, human data further substantiating this hypothesis are largely missing. Here, we used an in vitro model of HN to test the effects of serum samples from a longitudinal ageing cohort of 373 participants, with or without depressive symptomology. 1% participant serum was applied to human fetal hippocampal progenitor cells, and changes in HN markers were related to the occurrence of depressive symptoms across a 12-year period. Key nutritional, metabolomic and lipidomic biomarkers (extracted from participant plasma and serum) were subsequently tested for their ability to modulate HN. In our assay, we found that reduced cell death and increased neuronal differentiation were associated with later life depressive symptomatology. Additionally, we found impairments in neuronal cell morphology in cells treated with serum from participants experiencing recurrent depressive symptoms across the 12-year period. Interestingly, we found that increased neuronal differentiation was modulated by increased serum levels of metabolite butyrylcarnitine and decreased glycerophospholipid, PC35:1(16:0/19:1), levels - both of which are closely linked to diet - all in the context of depressive symptomology. These findings potentially suggest that diet and altered HN could subsequently shape the trajectory of late-life depressive symptomology.

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.

The serum metabolome mediates the concert of diet, exercise, and neurogenesis, determining the risk for cognitive decline and dementia.

INTRODUCTION: Diet and exercise influence the risk of cognitive decline (CD) and dementia through the food metabolome and exercise-triggered endogenous factors, which use the blood as a vehicle to communicate with the brain. These factors might act in concert with hippocampal neurogenesis (HN) to shape CD and dementia. METHODS: Using an in vitro neurogenesis assay, we examined the effects of serum samples from a longitudinal cohort (n = 418) on proxy HN readouts and their association with future CD and dementia across a 12-year period. RESULTS: Altered apoptosis and reduced hippocampal progenitor cell integrity were associated with exercise and diet and predicted subsequent CD and dementia. The effects of exercise and diet on CD specifically were mediated by apoptosis. DISCUSSION: Diet and exercise might influence neurogenesis long before the onset of CD and dementia. Alterations in HN could signify the start of the pathological process and potentially represent biomarkers for CD and dementia.

Evolution of Physicochemical Parameters during the Thermal-Based Production of Água-mel, a Traditional Portuguese Honey-Related Food Product.

The purpose of this work was to investigate the physicochemical changes occurring during the thermal-based production of água-mel, a traditional Portuguese honey-related food product. The refractive index, color parameters (hue angle, H°; chroma, C*), and the content of total reducing sugars, glucose, fructose, total brown pigments, and 5-hydroxymethylfurfural were monitored along the entire production process, and their evolution was kinetically modelled. Thermal processing caused a gradual decrease in sugars, which was accompanied by the formation of brown pigments and 5-hydroxymethylfurfural, increased concentration of soluble solids as evaluated through refractive index measurements, as well as the appearance of darker colors. In particular, a zero-order kinetic model could explain the changes in H° and reducing sugars, while the evolution of refractive index, brown pigments, 5-hydroxymethylfurfural, C*, fructose, and glucose were best fitted using a first-order kinetics model.

Characterization of the Human Exposome by a Comprehensive and Quantitative Large-Scale Multianalyte Metabolomics Platform.

The exposome, defined as the cumulative measure of external exposures and associated biological responses throughout the lifespan, has emerged in recent years as a cornerstone in biomedical sciences. Metabolomics stands out here as one of the most powerful tools for investigating the interplay between the genetic background, exogenous, and endogenous factors within human health. However, to address the complexity of the exposome, novel methods are needed to characterize the human metabolome. In this work, we have optimized and validated a multianalyte metabolomics platform for large-scale quantitative exposome research in plasma and urine samples, based on the use of simple extraction methods and high-throughput metabolomic fingerprinting. The methodology enables, for the first time, the simultaneous characterization of the endogenous metabolome, food-related metabolites, pharmaceuticals, household chemicals, environmental pollutants, and microbiota derivatives, comprising more than 1000 metabolites in total. This comprehensive and quantitative investigation of the exposome is achieved in short run times, through simple extraction methods requiring small-sample volumes, and using integrated quality control procedures for ensuring data quality. This metabolomics approach was satisfactorily validated in terms of linearity, recovery, matrix effects, specificity, limits of quantification, intraday and interday precision, and carryover. Furthermore, the clinical potential of the methodology was demonstrated in a dietary intervention trial as a case study. In summary, this study describes the optimization, validation, and application of a multimetabolite platform for comprehensive and quantitative metabolomics-based exposome research with great utility in large-scale epidemiological studies.

Quantifying the human diet in the crosstalk between nutrition and health by multi-targeted metabolomics of food and microbiota-derived metabolites.

BACKGROUND: Metabolomics is a powerful tool for investigating the association between nutrition and health status. Although urine is commonly employed for studying the metabolism and transformation of food components, the use of blood samples could be preferable to gain new insights into the bioavailability of diet-derived compounds and their involvement in health. However, the chemical complexity of blood samples hinders the analysis of this biological fluid considerably, which makes the development of novel and comprehensive analytical methods mandatory. METHODS: In this work, we optimized a multi-targeted metabolomics platform for the quantitative and simultaneous analysis of 450 food-derived metabolites by ultra-high performance liquid chromatography coupled to tandem mass spectrometry. To handle the chemical complexity of blood samples, three complementary extraction methods were assayed and compared in terms of recovery, sensitivity, precision and matrix effects with the aim of maximizing metabolomics coverage: protein precipitation, reversed solid-phase extraction, and hybrid protein precipitation with solid-phase extraction-mediated phospholipid removal. RESULTS: After careful optimization of the extraction conditions, protein precipitation enabled the most efficient and high-throughput extraction of the food metabolome in plasma, although solid-phase extraction-based protocols provided complementary performance for the analysis of specific polyphenol classes. The developed method yielded accurate recovery rates with negligible matrix effects, and good linearity, as well as high sensitivity and precision for most of the analyzed metabolites. CONCLUSIONS: The multi-targeted metabolomics platform optimized in this work enables the simultaneous detection and quantitation of 450 dietary metabolites in short-run times using small volumes of biological sample, which facilitates its application to epidemiological studies.

Effect of a polyphenol-rich dietary pattern on intestinal permeability and gut and blood microbiomics in older subjects: study protocol of the MaPLE randomised controlled trial.

BACKGROUND: During aging, alterations of the intestinal microbial ecosystem can occur contributing to immunosenescence, inflamm-aging and impairment of intestinal barrier function (increased intestinal permeability; IP). In the context of a diet-microbiota-IP axis in older subjects, food bioactives such as polyphenols may play a beneficial modulatory role. METHODS: MaPLE is a project centered on a randomized, controlled cross-over dietary intervention trial [polyphenol-rich diet (PR-diet) versus control diet (C-diet)] targeted to older people (≥ 60 y) living in a well-controlled setting (i.e. nursing home). The 8-week interventions are separated by an 8-week wash-out period. Three small portions per day of selected polyphenol-rich foods are consumed during intervention in substitution of other comparable products within the C-diet. Biological samples are collected before and after each treatment period to evaluate markers related to IP, inflammation, vascular function, oxidative stress, gut and blood microbiomics, metabolomics. A sample size of 50 subjects was defined based on IP as primary outcome. DISCUSSION: Evidence that increasing the consumption of polyphenol-rich food products can positively affect intestinal microbial ecosystem resulting in reduced IP and decreased translocation of inflammogenic bacterial factors into the bloodstream will be provided. The integration of data from gut and blood microbiomics, metabolomics and other IP-related markers will improve the understanding of the beneficial effect of the intervention in the context of polyphenols-microbiota-IP interactions. Finally, findings obtained will provide a proof of concept of the reliability of the dietary intervention, also contributing to future implementations of dietary guidelines directed to IP management in the older and other at risk subjects. TRIAL REGISTRATION: The trial is registered at (ISRCTN10214981); April 28, 2017.

Iron Metabolism in Obesity and Metabolic Syndrome.

Obesity is an excessive adipose tissue accumulation that may have detrimental effects on health. Particularly, childhood obesity has become one of the main public health problems in the 21st century, since its prevalence has widely increased in recent years. Childhood obesity is intimately related to the development of several comorbidities such as nonalcoholic fatty liver disease, dyslipidemia, type 2 diabetes mellitus, non-congenital cardiovascular disease, chronic inflammation and anemia, among others. Within this tangled interplay between these comorbidities and associated pathological conditions, obesity has been closely linked to important perturbations in iron metabolism. Iron is the second most abundant metal on Earth, but its bioavailability is hampered by its ability to form highly insoluble oxides, with iron deficiency being the most common nutritional disorder. Although every living organism requires iron, it may also cause toxic oxygen damage by generating oxygen free radicals through the Fenton reaction. Thus, iron homeostasis and metabolism must be tightly regulated in humans at every level (i.e., absorption, storage, transport, recycling). Dysregulation of any step involved in iron metabolism may lead to iron deficiencies and, eventually, to the anemic state related to obesity. In this review article, we summarize the existent evidence on the role of the most recently described components of iron metabolism and their alterations in obesity.

Characterization of Metabolomic Profile Associated with Metabolic Improvement after Bariatric Surgery in Subjects with Morbid Obesity.

The exact impact of bariatric surgery in metabolically "healthy" (MH) or "unhealthy" (MU) phenotypes for the study of the metabolic improvement is still unknown. We applied an untargeted LC-ESI-TripleTOF-MS-driven metabolomics approach in serum samples from 39 patients with morbid obesity (MH and MU) 1, 3, and 6 months after bariatric surgery. Multiple factor analysis, along with correlation and enrichment analyses, was carried out to distinguish those metabolites associated with metabolic improvement. Hydroxypropionic acids, medium-/long-chain hydroxy fatty acids, and bile acid glucuronides were the most discriminative biomarkers of response between MH and MU phenotypes. Hydroxypropionic (hydroxyphenyllactic-related) acids, amino acids, and glycerolipids were the most significant clusters of metabolites altered after bariatric surgery in MU ( p < 0.001). After surgery, MU and MH changed toward a common metabolic state 3 months after surgery. We observed a negative correlation with changes in waist circumference and cholesterol levels with metabolites of lipid metabolism. Glycemic variables were correlated with hexoses, which, in turn, correlated with gluconic acid and amino acid metabolism. Finally, we noted that hydroxyphenyllactic acid was associated with amino acid and lipid metabolism. Microbial metabolism of amino acid and BA glucuronidation pathways may be the key points of metabolic rearrangement after surgery.

Untargeted Profiling of Concordant/Discordant Phenotypes of High Insulin Resistance and Obesity To Predict the Risk of Developing Diabetes.

This study explores the metabolic profiles of concordant/discordant phenotypes of high insulin resistance (IR) and obesity. Through untargeted metabolomics (LC-ESI-QTOF-MS), we analyzed the fasting serum of subjects with high IR and/or obesity ( n = 64). An partial least-squares discriminant analysis with orthogonal signal correction followed by univariate statistics and enrichment analysis allowed exploration of these metabolic profiles. A multivariate regression method (LASSO) was used for variable selection and a predictive biomarker model to identify subjects with high IR regardless of obesity was built. Adrenic acid and a dyglyceride (DG) were shared by high IR and obesity. Uric and margaric acids, 14 DGs, ketocholesterol, and hydroxycorticosterone were unique to high IR, while arachidonic, hydroxyeicosatetraenoic (HETE), palmitoleic, triHETE, and glycocholic acids, HETE lactone, leukotriene B4, and two glutamyl-peptides to obesity. DGs and adrenic acid differed in concordant/discordant phenotypes, thereby revealing protective mechanisms against high IR also in obesity. A biomarker model formed by DGs, uric and adrenic acids presented a high predictive power to identify subjects with high IR [AUC 80.1% (68.9-91.4)]. These findings could become relevant for diabetes risk detection and unveil new potential targets in therapeutic treatments of IR, diabetes, and obesity. An independent validated cohort is needed to confirm these results.

Synergic effects of sugar and caffeine on insulin-mediated metabolomic alterations after an acute consumption of soft drinks.

High sugar consumption elicits numerous deleterious effects on health by inducing insulin resistance, which is closely associated with the development of metabolic disorders such as obesity or type-2 diabetes. Furthermore, there is also growing evidence that caffeine may play an important role in the regulation of insulin release and the appearance of related metabolic impairments. Thus, the aim of this work was to investigate the impact of acute sugar and caffeine intake on the metabolic health status by using a metabolomic multi-platform based on the combination of flow injection mass spectrometry and ultra-high performance liquid chromatography mass spectrometry. To this end, we performed a randomized, crossover and double-blind intervention study with different soft drinks from the same brand. Numerous metabolomic changes were detected in serum samples over time after the intake of sugar-sweetened beverages, including energy-related metabolites, amino acids and lipids, thus demonstrating the intense effects provoked by acute sugar consumption on the organism during 3 h of follow-up. However, the most significant findings were observed after the co-ingestion of caffeine, which could be indicative of a synergic effect of this psychostimulant on insulin-mediated perturbations.

Region-specific metabolic alterations in the brain of the APP/PS1 transgenic mice of Alzheimer's disease.

Alzheimer's disease (AD) is the most common neurodegenerative disorder worldwide, but its etiology is still not completely understood. The identification of underlying pathological mechanisms is becoming increasingly important for the discovery of biomarkers and therapies, for which metabolomics presents a great potential. In this work, we studied metabolic alterations in different brain regions of the APP/PS1 mice by using a high-throughput metabolomic approach based on the combination of gas chromatography-mass spectrometry and ultra-high performance liquid chromatography-mass spectrometry. Multivariate statistics showed that metabolomic perturbations are widespread, affecting mainly the hippocampus and the cortex, but are also present in regions not primarily associated with AD such as the striatum, cerebellum and olfactory bulbs. Multiple metabolic pathways could be linked to the development of AD-type disorders in this mouse model, including abnormal purine metabolism, bioenergetic failures, dyshomeostasis of amino acids and disturbances in membrane lipids, among others. Interestingly, region-specific alterations were observed for some of the potential markers identified, associated with abnormal fatty acid composition of phospholipids and sphingomyelins, or differential regulation of neurotransmitter amino acids (e.g. glutamate, glycine, serine, N-acetyl-aspartate), not previously described to our knowledge. Therefore, these findings could provide a new insight into brain pathology in Alzheimer's disease.

Metabolomics reveals significant impairments in the immune system of the APP/PS1 transgenic mice of Alzheimer's disease.

Inflammatory processes and other failures related to the immune system are common features associated with Alzheimer's disease (AD), in both brain and the peripheral system. Thus, the study of the main organs of the immune system may have a great potential for the elucidation of pathological mechanisms underlying these abnormalities. This is the first metabolomic investigation performed in spleen and thymus from transgenic mice of AD. Tissues were fingerprinted using a metabolomic platform comprising GC-MS and ultra-HPLC-MS. Multivariate statistics demonstrated significant differences in numerous metabolites between the APP/PS1 mice and wild-type controls, and it was proven that multiple biochemical pathways are disturbed in these organs including abnormal metabolism of phospholipids, energy deficiencies, altered homeostasis of amino acids, oxidative stress, and others. Therefore, these findings highlight the importance of the proper metabolic functioning of peripheral immune system in the development of neurodegenerative disorders such as AD.

High throughput multiorgan metabolomics in the APP/PS1 mouse model of Alzheimer's disease.

Metabolomics has demonstrated a great potential for the study of pathological mechanisms occurring in brain from Alzheimer's disease patients and transgenic models. However, its application to peripheral samples is not so common, although it can provide interesting information about systemic abnormalities underlying to disease. This work represents the first metabolomic investigation of multiple peripheral organs (liver, kidney, spleen, and thymus) from the APP/PS1 mice by using a high-throughput approach based on direct infusion MS. Our findings demonstrated that these organs suffer significant metabolic impairments related to energy metabolism (e.g. glycolysis, Krebs cycle, ß-oxidation), lipid homeostasis (e.g. cellular membrane breakdown and fatty acid metabolism), degradation of nucleotides, oxidative stress, hyperammonemia, and metabolism of amino acids. It is noteworthy that many of these alterations have been previously described in brain, confirming the systemic character of this neurodegenerative disorder and the utility of peripheral samples to understand its pathogenesis.

Metabolomic profiling of serum in the progression of Alzheimer's disease by capillary electrophoresis-mass spectrometry.

There is high interest in the discovery of early diagnostic biomarkers of Alzheimer's disease, for which metabolomics exhibits a great potential. In this work, a metabolomic approach based on ultrafiltration and analysis by CE-MS has been used to obtain representative fingerprints of polar metabolites from serum samples in order to distinguish between patients with Alzheimer's disease, mild cognitive impairment, and healthy controls. By the use of partial least squares discriminant analysis it was possible to classify patients according to the disease stage and then identify potential markers. Significant increase was observed with progression of disease in levels of choline, creatinine, asymmetric dimethyl-arginine, homocysteine-cysteine disulfide, phenylalanyl-phenylalanine, and different medium chain acylcarnitines. On the other hand, asparagine, methionine, histidine, carnitine, acetyl-spermidine, and C5-carnitine were reduced in these serum samples. In this way, multiple essential pathways were found implicated in the underlying pathology, such as oxidative stress or defects in energy metabolism. However, the most interesting results are related to the association of several vascular risk factors with Alzheimer's disease.

Development of a metabolomic approach based on urine samples and direct infusion mass spectrometry.

The analysis of urine by direct infusion mass spectrometry suffers from ion suppression due to its high salt content and inter-sample variability caused by the differences in urine volume between persons. Thus, urine metabolomics requires a careful selection of the sample preparation procedure and a normalization strategy to deal with these problems. Several approaches were tested for metabolomic analysis of urine samples by direct infusion electrospray mass spectrometry (DI-ESI-MS), including solid phase extraction, liquid-liquid extraction, and sample dilution. In addition, normalization of results based on conductivity values and statistical treatment was performed to minimize sample variability. Both urine dilution and solid phase extraction with mixed mode sorbent considerably reduced the salt content in urine, providing comprehensive metabolomic fingerprints. Moreover, statistical data normalization enabled the correction of inter-sample physiological variability, improving the quality of results obtained. Therefore, high-throughput DI-ESI-MS fingerprinting of urine samples can be achieved with simple pretreatment procedures allowing the use of this noninvasive sampling in metabolomics. Finally, the optimized approach was tested in a pilot metabolomic investigation of urine samples from transgenic mice models of Alzheimer's disease (APP/PS1) in order to illustrate the potential of the methodology.

Homeostasis of metals in the progression of Alzheimer's disease.

In order to study the involvement of metals in the progression of Alzheimer's disease, serum samples from patients with Alzheimer and mild cognitive impairment were investigated. For this purpose, metal content was analyzed after size-fractionation of species and then, inter-element and inter-fraction ratios were computed. In this way, the analysis allowed discovering changes that could be used as markers of disease, but also provided a new insight into the interactions in the homeostasis of elements in neurodegeneration and its progression. Aluminum and labile forms of iron and copper were increased in demented patients, while manganese, zinc and selenium were reduced. Interestingly, levels of different elements, principally iron, aluminum and manganese, were closely inter-related, which could evidence a complex interdependency between the homeostasis of the different metals in this disorder. On the other hand, imbalances in metabolism of copper, zinc and selenium could be associated to abnormal redox status. Therefore, this study may contribute to our understanding of the pathological mechanisms related to metals in Alzheimer's disease.