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.

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.

Descriptive analysis of dietary (poly)phenol intake in the subcohort MAX from DCH-NG: "Diet, Cancer and Health-Next Generations cohort".

PURPOSE: (Poly)phenols are bioactive compounds widely distributed in plant-based foods. Currently, limited data exist on the intake distribution of (poly)phenols across meals. This study aimed to estimate dietary intakes of all individual (poly)phenols and total intake per class and subclass by meal event, and to identify their main food sources in the subcohort MAX from the Diet, Cancer and Health-Next Generations cohort (DCH-NG). METHODS: Dietary data were collected using three web-based 24-h dietary recalls over 1 year. In total, 676 participants completed at least one recall. The dietary data were linked to Phenol-Explorer database using standardized procedures and an in-house software. We categorized foods/drinks into five options of meal events selected by the participant: 'Breakfast', 'Lunch', 'Evening', 'Snack', and 'Drink'. RESULTS: Adjusted total (poly)phenols mean intake by meal was the highest in the drink event (563 mg/day in men and 423 mg/day in women) and the lowest in the evening event (146 mg/day in men and 137 mg/day in women). The main overall (poly)phenol class contributor was phenolic acids (55.7-79.0%), except for evening and snack events where it was flavonoids (45.5-60%). The most consumed (poly)phenol subclasses were hydroxycinnamic acids and proanthocyanidins. Nonalcoholic beverages (coffee accounted for 66.4%), cocoa products, and cereals were the main food sources of total (poly)phenols. CONCLUSION: This study provides data on the variability in the intake of classes and subclasses of (poly)phenols and their main food sources by meal event according to lifestyle data, age, and gender in a Danish population.

Apolipoprotein E gene variants shape the association between dietary fibre intake and cognitive decline risk in community-dwelling older adults.

BACKGROUND: healthy dietary patterns have been associated with lower risk for age-related cognitive decline. However, little is known about the specific role of dietary fibre on cognitive decline in older adults. OBJECTIVE: this study aimed to examine the association between dietary fibre and cognitive decline in older adults and to assess the influence of genetic, lifestyle and clinical characteristics in this association. DESIGN AND PARTICIPANTS: the Invecchiare in Chianti, aging in the Chianti area study is a cohort study of community-dwelling older adults from Italy. Cognitive function, dietary and clinical data were collected at baseline and years 3, 6, 9 and 15. Our study comprised 848 participants aged ≥ 65 years (56% female) with 2,038 observations. MAIN OUTCOME AND MEASURES: cognitive decline was defined as a decrease ≥3 units in the Mini-Mental State Examination score during consecutive visits. Hazard ratios for cognitive decline were estimated using time-dependent Cox regression models. RESULTS: energy-adjusted fibre intake was not associated with cognitive decline during the 15-years follow-up (P > 0.05). However, fibre intake showed a significant interaction with Apolipoprotein E (APOE) haplotype for cognitive decline (P = 0.02). In participants with APOE-ɛ4 haplotype, an increase in 5 g/d of fibre intake was significantly associated with a 30% lower risk for cognitive decline. No association was observed in participants with APOE-ɛ2 and APOE-ɛ3 haplotypes. CONCLUSIONS AND RELEVANCE: dietary fibre intake was not associated with cognitive decline amongst older adults for 15 years of follow-up. Nonetheless, older subjects with APOE-ɛ4 haplotype may benefit from higher fibre intakes based on the reduced risk for cognitive decline in this high-risk group.

Dietary polyphenols, metabolic syndrome and cardiometabolic risk factors: An observational study based on the DCH-NG subcohort.

BACKGROUND AND AIMS: Polyphenol-rich foods have beneficial properties that may lower cardiometabolic risk. We aimed to prospectively investigate the relationship between intakes of dietary polyphenols, and metabolic syndrome (MetS) and its components, in 676 Danish residents from the MAX study, a subcohort of the Danish Diet, Cancer and Health-Next Generations (DCH-NG) cohort. METHODS AND RESULTS: Dietary data were collected using web-based 24-h dietary recalls over one year (at baseline, and at 6 and 12 months). The Phenol-Explorer database was used to estimate dietary polyphenol intake. Clinical variables were also collected at the same time point. Generalized linear mixed models were used to investigate relationships between polyphenol intake and MetS. Participants had a mean age of 43.9y, a mean total polyphenol intake of 1368 mg/day, and 75 (11.6%) had MetS at baseline. Compared to individuals with MetS in Q1 and after adjusting for age, sex, lifestyle and dietary confounders, those in Q4 - for total polyphenols, flavonoids and phenolic acids-had a 50% [OR (95% CI): 0.50 (0.27, 0.91)], 51% [0.49 (0.26, 0.91)] and 45% [0.55 (0.30, 1.00)] lower odds of MetS, respectively. Higher total polyphenols, flavonoids and phenolic acids intakes as continuous variable were associated with lower risk for elevated systolic blood pressure (SBP) and low high-density lipoprotein cholesterol (HDL-c) (p < 0.05). CONCLUSIONS: Total polyphenol, flavonoid and phenolic acid intakes were associated with lower odds of MetS. These intakes were also consistently and significantly associated with a lower risk for higher SBP and lower HDL-c concentrations.

The fobitools framework: the first steps towards food enrichment analysis.

MOTIVATION: The FOBI ontology can be of great help in nutrimetabolomic studies due to its wide variety of applications, including the possibility of performing different enrichment analyses. However, the programming skills required to query and explore it may limit its use by the scientific community. RESULTS: Here, we present the fobitools framework, comprised of an R/Bioconductor package and its complementary web interface. These two tools allow researchers to interact and explore the FOBI ontology in a highly user-friendly way. The fobitools framework is focused on the novel concept of food enrichment analysis in nutrimetabolomic studies. However, other useful features, such as the network interactive visualization of FOBI and the automatic annotation of dietary free-text data are also presented. AVAILABILITY AND IMPLEMENTATION: Both the fobitools R/Bioconductor package and the fobitoolsGUI web-based application, together with their installation instructions and examples, are freely available at https://github.com/nutrimetabolomics/fobitools and https://github.com/nutrimetabolomics/fobitoolsGUI, respectively. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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.

Higher bacterial DNAemia can affect the impact of a polyphenol-rich dietary pattern on biomarkers of intestinal permeability and cardiovascular risk in older subjects.

PURPOSE: Aging can be characterized by increased systemic low-grade inflammation, altered gut microbiota composition, and increased intestinal permeability (IP). The intake of polyphenol-rich foods is proposed as a promising strategy to positively affect the gut microbiota-immune system-intestinal barrier (IB) axis. In this context, we tested the hypothesis that a PR-dietary intervention would affect the presence of bacterial factors in the bloodstream of older adults. METHODS: We collected blood samples within a randomized, controlled, crossover intervention trial in which older volunteers (n = 51) received a polyphenol-enriched and a control diet. We quantified the presence of bacterial DNA in blood by qPCR targeting the 16S rRNA gene (16S; bacterial DNAemia). Blood DNA was taxonomically profiled via 16S sequencing. RESULTS: Higher blood 16S levels were associated with higher BMI and markers of IP, inflammation, and dyslipidemia. PR-intervention did not significantly change bacterial DNAemia in the older population (P = 0.103). Nonetheless, the beneficial changes caused by the polyphenol-enriched diet were greatest in participants with higher bacterial DNAemia, specifically in markers related to IP, inflammation and dyslipidemia, and in fecal bacterial taxa. Finally, we found that the bacterial DNA detected in blood mostly belonged to γ-Proteobacteria, whose abundance significantly decreased after the polyphenol-rich diet in subjects with higher bacterial DNAemia at baseline. CONCLUSIONS: This study shows that older subjects with higher bacterial DNAemia experienced a beneficial effect from a polyphenol-rich diet. Bacterial DNAemia may be a further relevant marker for the identification of target populations that could benefit more from a protective dietary treatment. REGISTRATION: This trial was retrospectively registered at www.isrctn.org (ISRCTN10214981) on April 28, 2017.

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.

Visceral Adipose Tissue Phospholipid Signature of Insulin Sensitivity and Obesity.

Alterations in visceral adipose tissue (VAT) are closely linked to cardiometabolic abnormalities. The aim of this work is to define a metabolic signature in VAT of insulin resistance (IR) dependent on, and independent of, obesity. An untargeted UPLC-Q-Exactive metabolomic approach was carried out on the VAT of obese insulin-sensitive (IS) and insulin-resistant subjects (N = 11 and N = 25, respectively) and nonobese IS and IR subjects (N = 25 and N = 10, respectively). The VAT metabolome in obesity was defined among other things by changes in the metabolism of lipids, nucleotides, carbohydrates, and amino acids, whereas when combined with high IR, it affected the metabolism of 18 carbon fatty acyl-containing phospholipid species. A multimetabolite model created by glycerophosphatidylinositol (18:0); glycerophosphatidylethanolamine (18:2); glycerophosphatidylserine (18:0); and glycerophosphatidylcholine (18:0/18:1), (18:2/18:2), and (18:2/18:3) exhibited a highly predictive performance to identify the metabotype of "insulin-sensitive obesity" among obese individuals [area under the curve (AUC) 96.7% (91.9-100)] and within the entire study population [AUC 87.6% (79.0-96.2)]. We demonstrated that IR has a unique and shared metabolic signature dependent on, and independent of, obesity. For it to be used in clinical practice, these findings need to be validated in a more accessible sample, such as blood.

Adherence to the Mediterranean diet assessed by a novel dietary biomarker score and mortality in older adults: the InCHIANTI cohort study.

BACKGROUND: Dietary biomarkers may complement dietary intake assessment made by dietary questionnaires. We developed an a-posteriori dietary biomarkers score based on Mediterranean diet food groups and evaluated its association with mortality. METHODS: 642 participants (56% female), aged ≥65 years, with complete data on dietary biomarkers were followed during 20 years in the InCHIANTI cohort study (Tuscany, Italy). The main outcomes were all-cause, cardiovascular, and cancer mortality. Dietary biomarkers were selected from literature and from correlation analyses with dietary intakes of Mediterranean diet food groups in the study. The baseline levels of the following dietary biomarkers were chosen: urinary total polyphenols and resveratrol metabolites, and plasma carotenoids, selenium, vitamin B12, linolenic, eicosapentaenoic and docosahexaenoic acids, and the mono-unsaturated/saturated fatty acid ratio. Associations of the Mediterranean diet score using dietary biomarkers and a validated food frequency questionnaire (FFQ) (as tertiles) with mortality were assessed through Cox regression. RESULTS: During the 20-year follow-up [median (Q1-Q3), 14 (8-18) years], and 435 deaths occurred (139 from cardiovascular diseases and 89 from cancer-related causes). In the fully adjusted models, the dietary biomarker-Mediterranean diet score was inversely associated with all-cause (HRT3vs.T1 0.72; 95%CI 0.56-0.91) and cardiovascular (HRT3vs.T1 0.60; 95%CI 0.38-0.93), but not with cancer mortality. Associations between the FFQ-Mediterranean diet score and mortality were not statistically significant. CONCLUSIONS: A greater adherence at baseline to a Mediterranean diet assessed by a dietary biomarker score was associated with a lower risk of mortality in older adults during a 20-year follow-up. The measurement of dietary biomarkers may contribute to guide individualized dietary counseling to older people. TRIAL REGISTRATION: NCT01331512.

A healthy eating score is inversely associated with depression in older adults: results from the Chilean National Health Survey 2016-2017.

OBJECTIVE: To investigate the relationship of a healthy eating score with depression in Chilean older adults. DESIGN: Cross-sectional study. SETTING: Older adults from the Chilean National Health Survey 2016-2017. Associations were analysed using complex samples multivariable logistic regressions adjusted for age, sex, socio-demographic, lifestyles (physical activity, smoking, alcohol consumption and sleep duration), BMI and clinical conditions (hypertension, diabetes, hypercholesterolaemia and cardiovascular diseases). PARTICIPANTS: The number of participants was 2031 (≥ 60 years). The Composite International Diagnostic Interview-Short Form was applied to establish the diagnosis of major depressive episode. Six healthy eating habits were considered to produce the healthy eating score (range: 0-12): consumption of seafood, whole grain, dairy, fruits, vegetables and legumes. Participants were categorised according to their final scores as healthy (≥ 9), average (5-8) and unhealthy (≤ 4). RESULTS: Participants with a healthy score had a higher educational level, physical activity and regular sleep hours than participants with an average and unhealthiest healthy eating score. Participants classified in the healthiest healthy eating score had an inverse association with depression (OR: 0·28, (95 % CI 0·10, 0·74)). Food items that contributed the most to this association were legumes (15·2 %) and seafood (12·7 %). CONCLUSION: Older adults classified in the healthiest healthy eating score, characterised by a high consumption of legumes and seafood, showed a lower risk for depression in a representative sample of Chilean population.

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.

Different alterations of glomerular filtration rate and their association with uric acid in children and adolescents with type 1 diabetes or with overweight/obesity.

BACKGROUND: Hyperfiltration (HF) occurs early in diabetes or obesity (OB)-associated renal disease. Alterations of glomerular filtration rate (GFR) in childhood OB remain unclear. OBJECTIVES: To compare the prevalence of GFR alterations and its association with uric acid in children and adolescents with type 1 diabetes (T1D) vs overweight (OW)/OB. METHODS: Cross-sectional study of 29 youths (aged: 13 ± 2 years) with T1D (disease duration: 7 ± 3 years) and 165 with OW/OB (aged: 11 ± 3 years). Patients with an albumin-creatinine ratio >3.39 mg/mmol were excluded. GFR was estimated with creatinine-cystatin C Zappitelli equation. HF and low GFR were defined by a GFR > 135 and <90 mL/min.1.73 m2 , respectively. RESULTS: HF was higher in children with T1D vs OW/OB (28% vs 10%, P < .005). Children with OW/OB also showed a 10% of low GFR. In patients with T1D, HbA1c (ß = .8, P < .001), and systolic blood pressure (ß = 11.4, P < .005) were independent predictors of GFR (R2 = .65). In OW/OB, HF cases were almost limited to prepubertal children and low GFR to pubertal ones. GFR in OW/OB was associated with age (ß = -2.2, P < .001), male sex (ß = -11.6, P < .001), and uric acid (ß = -.05, P < .001) in adjusted models (R2 = .33). CONCLUSIONS: GFR alterations were different between youths with T1D and with OW/OB. Higher uric acid, older age, and puberty were related to lower GFR values in OW/OB children. Longitudinal studies will determine if low GFR is consequence of a rapid GFR decline in pediatric patients with OW/OB.

Association of glomerular hyperfiltration with serum chemokine levels and metabolic features in prepubertal children with overweight/obesity.

BACKGROUND AND AIMS: Glomerular hyperfiltration (GH) is proposed as one of the earliest events in obesity (OB)-associated renal disease. Children with GH and type-1 diabetes showed increased chemokine levels. Chemokine associations with glomerular filtration rate (GFR) and metabolic features in prepubertal children with overweight (OW)/OB are unknown. METHODS AND RESULTS: Cross-sectional study. 75 prepubertal children (aged: 9.0 ± 1.7 years) with OW/OB were studied. Clinical and metabolic characteristics (including non-esterified fatty acids, NEFA) and GFR (combined Zappitelli equation) were assessed. GH was defined as GFR >135 ml/min.1.73 m2. Serum levels of regulated on activation, normal T cell expressed and secreted (RANTES)/CCL5, interleukin-8 (IL-8)/CXCL8 and monokine-induced by interferon-γ (MIG)/CXCL9 were measured by ELISA. Age- and sex-adjusted correlations and differences were tested. 48% of the cohort was female and 13% were OW, 54% OB and 33% severe OB. Prepubertal children with GH showed lower z-BMI (-12%), NEFA (-26%) and uric acid (-22%) than those without GH (all p < 0.05). Similarly to high sensitivity C-reactive protein (hsCRP), there were no differences in serum chemokines between children with GH or not (all p > 0.05). Adjusted correlations were significant for RANTES and z-BMI (r = 0.26; p < 0.05) and for MIG with z-BMI (r = -0.26; p < 0.05) and with NEFA (r = 0.27; p < 0.05). CONCLUSION: GH was not associated with higher chemokine levels in prepubertal children with OW/OB. Decreased rather than elevated GFR values were correlated with obesity and worse metabolic profiles. Chemokines levels in children with severe OB suggest a regulation of the immune response. Follow-up studies are needed to address the clinical implications of these findings.

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.

Evaluation and comparison of bioinformatic tools for the enrichment analysis of metabolomics data.

BACKGROUND: Bioinformatic tools for the enrichment of 'omics' datasets facilitate interpretation and understanding of data. To date few are suitable for metabolomics datasets. The main objective of this work is to give a critical overview, for the first time, of the performance of these tools. To that aim, datasets from metabolomic repositories were selected and enriched data were created. Both types of data were analysed with these tools and outputs were thoroughly examined. RESULTS: An exploratory multivariate analysis of the most used tools for the enrichment of metabolite sets, based on a non-metric multidimensional scaling (NMDS) of Jaccard's distances, was performed and mirrored their diversity. Codes (identifiers) of the metabolites of the datasets were searched in different metabolite databases (HMDB, KEGG, PubChem, ChEBI, BioCyc/HumanCyc, LipidMAPS, ChemSpider, METLIN and Recon2). The databases that presented more identifiers of the metabolites of the dataset were PubChem, followed by METLIN and ChEBI. However, these databases had duplicated entries and might present false positives. The performance of over-representation analysis (ORA) tools, including BioCyc/HumanCyc, ConsensusPathDB, IMPaLA, MBRole, MetaboAnalyst, Metabox, MetExplore, MPEA, PathVisio and Reactome and the mapping tool KEGGREST, was examined. Results were mostly consistent among tools and between real and enriched data despite the variability of the tools. Nevertheless, a few controversial results such as differences in the total number of metabolites were also found. Disease-based enrichment analyses were also assessed, but they were not found to be accurate probably due to the fact that metabolite disease sets are not up-to-date and the difficulty of predicting diseases from a list of metabolites. CONCLUSIONS: We have extensively reviewed the state-of-the-art of the available range of tools for metabolomic datasets, the completeness of metabolite databases, the performance of ORA methods and disease-based analyses. Despite the variability of the tools, they provided consistent results independent of their analytic approach. However, more work on the completeness of metabolite and pathway databases is required, which strongly affects the accuracy of enrichment analyses. Improvements will be translated into more accurate and global insights of the metabolome.

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.