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BACKGROUND: The associations of sweetened beverages (SBs) and added sugar (AS) intake with adiposity are still debated. Metabolomics could provide insights into the mechanisms linking their intake to adiposity. OBJECTIVES: We aimed to identify metabolomics biomarkers of intake of low- and no-calorie sweetened beverages (LNCSBs), sugar-sweetened beverages (SSBs), and ASs and to investigate their associations with body mass index, body fat percentage, and waist circumference. METHODS: We analyzed 3 data sets from the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) cohort study, of children who provided 2 urine samples (n = 297), adolescents who provided a single urine sample (n = 339), and young adults who provided a single plasma sample (n = 195). Urine and plasma were analyzed using untargeted metabolomics. Dietary intakes were assessed using 3-d weighed dietary records. The random forest, partial least squares, and least absolute shrinkage and selection operator were jointly used for metabolite selection. We examined associations of intakes with metabolites and anthropometric measures using linear and mixed-effects regression. RESULTS: In adolescents, LNCSB were positively associated with acesulfame (ß: 0.0012; 95% confidence interval [CI]: 0.0006, 0.0019) and saccharin (ß: 0.0009; 95% CI: 0.0002, 0.0015). In children, the association was observed with saccharin (ß: 0.0016; 95% CI: 0.0005, 0.0027). In urine and plasma, SSBs were positively associated with 1-methylxanthine (ß: 0.0005; 95% CI: 0.0003, 0.0008; and ß: 0.0010, 95% CI 0.0004, 0.0015, respectively) and 5-acetylamino-6-amino-3-methyluracil (ß: 0.0005; 95% CI: 0.0002, 0.0008; and ß: 0.0009; 95% CI: 0.0003, 0.0014, respectively). AS was associated with urinary sucrose (ß: 0.0095; 95% CI: 0.0069, 0.0121) in adolescents. Some of the food-related metabolomics profiles were also associated with adiposity measures. CONCLUSIONS: We identified SBs- and AS-related metabolites, which may be important for understanding the interplay between these intakes and adiposity in young individuals.
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BACKGROUND: Identifying diets beneficial for both human and planetary health has become increasingly important. However, to date, there is limited research on sustainable diets for children and adolescents, a vulnerable population group with specific nutritional needs. OBJECTIVES: We aimed to identify 1) the main determinants; 2) age and time trends of greenhouse gas emissions (GHGE), land use (LU), and water use (WU) of diets of children and adolescents; and 3) analyze the associations of dietary GHGE, LU, and WU with nutrient adequacy. METHODS: A total of 5510 3-d-weighted dietary records (n = 856; 6-17 y; 48% â) of the DONALD (DOrtmund Nutritional and Anthropometric Longitudinally Designed) study between 2000 and 2021 were analyzed. Values of GHGE (kgCO2eq), LU (m2 × year), and WU (L) determined by life cycle assessment were assigned to all recorded foods. For nutrient adequacy, the mean adequacy ratio (MAR = ∑(nutrient intake / recommended intake) / number of nutrients) was used. Data were analyzed using polynomial mixed-effects regression models. RESULTS: The main contributors to GHGE and LU were meat products (GHGE: 25.6%; LU: 32.8%), dairy products (22.2%; 17.7%), and sweets and pastries (14.0%; 14.3%); to WU, nonalcoholic beverages (24.3%), meat products (18.9%), and vegetables and fruits (17.7%). GHGE, LU, and WU per 1000 kcal increased with age (P < 0.01). GHGE and LU per 1000 kcal increased between 2000 and 2010 and decreased after that in females (P < 0.01) and males (GHGE only: P = 0.02). No significant time trend was found for WU (P > 0.05). A higher MAR was directly associated with GHGE/1000 kcal (MAR: ß: 0.011, 95% CI: 0.008, 0.013, P < 0.0001), LU/1000 kcal (MAR: ß: 0.009, 95%CI: 0.005, 0.013, P < 0.0001), and WU/1000 kcal (MAR: ß: 0.429, 95% CI: 0.325, 0.533, P < 0.0001). CONCLUSIONS: Our findings underscore the further need and the capacity for change toward more environmentally sustainable diets. Yet, the tradeoff between environmental sustainability and nutrient adequacy in the diets of children and adolescents requires specific attention to dietary composition.
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Dieta , Humanos , Niño , Adolescente , Femenino , Masculino , Alemania , Estudios de Cohortes , Gases de Efecto Invernadero/análisis , Conservación de los Recursos Naturales , Estudios Longitudinales , Estado Nutricional , Valor NutritivoRESUMEN
The gut microbiome may be involved in the occurrence of dementia primarily through the molecular mechanisms of producing bioactive molecules and promoting inflammation. Epidemiological evidence linking gut microbiome molecules and inflammatory markers to dementia risk has been mixed, and the intricate interplay between these groups of biomarkers suggests that their joint investigation in the context of dementia is warranted. We aimed to simultaneously investigate the association of circulating levels of selected gut microbiome molecules and inflammatory markers with dementia risk. This case-cohort epidemiological study included 805 individuals (83 years, 66% women) free of dementia at baseline. Plasma levels of 19 selected gut microbiome molecules comprising lipopolysaccharide, short-chain fatty acids, and indole-containing tryptophan metabolites as well as four inflammatory markers measured at baseline were linked to incident all-cause (ACD) and Alzheimer's disease dementia (AD) in binary outcomes and time-to-dementia analyses. Independent of several covariates, seven gut microbiome molecules, 5-hydroxyindole-3-acetic acid, indole-3-butyric acid, indole-3-acryloylglycine, indole-3-lactic acid, indole-3-acetic acid methyl ester, isobutyric acid, and 2-methylbutyric acid, but no inflammatory markers discriminated incident dementia cases from non-cases. Furthermore, 5-hydroxyindole-3-acetic acid (hazard ratio: 0.58; 0.36-0.94, P = 0.025) was associated with time-to-ACD. These molecules underpin gut microbiome-host interactions in the development of dementia and they may be crucial in its prevention and intervention strategies. Future larger epidemiological studies are needed to confirm our findings, specifically in exploring the repeatedly measured circulating levels of these molecules and investigating their causal relationship with dementia risk.
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BACKGROUND: Regular physical activity elicits many health benefits. However, the underlying molecular mechanisms through which physical activity influences overall health are less understood. Untargeted metabolomics enables system-wide mapping of molecular perturbations which may lend insights into physiological responses to regular physical activity. In this study, we investigated the associations of habitual physical activity with plasma and urine metabolome in adolescents and young adults. METHODS: This cross-sectional study included participants from the DONALD (DOrtmund Nutritional and Anthropometric Longitudinally Designed) study with plasma samples n = 365 (median age: 18.4 (18.1, 25.0) years, 58% females) and 24 h urine samples n = 215 (median age: 18.1 (17.1, 18.2) years, 51% females). Habitual physical activity was assessed using a validated Adolescent Physical Activity Recall Questionnaire. Plasma and urine metabolite concentrations were determined using ultra-high-performance liquid chromatography-tandem mass spectroscopy (UPLC-MS/MS) methods. In a sex-stratified analysis, we conducted principal component analysis (PCA) to reduce the dimensionality of metabolite data and to create metabolite patterns. Multivariable linear regression models were then applied to assess the associations between self-reported physical activity (metabolic equivalent of task (MET)-hours per week) with single metabolites and metabolite patterns, adjusted for potential confounders and controlling the false discovery rate (FDR) at 5% for each set of regressions. RESULTS: Habitual physical activity was positively associated with the "lipid, amino acids and xenometabolite" pattern in the plasma samples of male participants only (ß = 1.02; 95% CI: 1.01, 1.04, p = 0.001, adjusted p = 0.042). In both sexes, no association of physical activity with single metabolites in plasma and urine and metabolite patterns in urine was found (all adjusted p > 0.05). CONCLUSIONS: Our explorative study suggests that habitual physical activity is associated with alterations of a group of metabolites reflected in the plasma metabolite pattern in males. These perturbations may lend insights into some of underlying mechanisms that modulate effects of physical activity.
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Metabolomics-derived metabolites (henceforth metabolites) may mediate the relationship between modifiable risk factors and clinical biomarkers of metabolic health (henceforth clinical biomarkers). We set out to study the associations of metabolites with clinical biomarkers and a potential mediation effect in a population of young adults. First, we conducted a systematic literature review searching for metabolites associated with 11 clinical biomarkers (inflammation markers, glucose, blood pressure or blood lipids). Second, we replicated the identified associations in a study population of n = 218 (88 males and 130 females, average age of 18 years) participants of the DONALD Study. Sex-stratified linear regression models adjusted for age and BMI and corrected for multiple testing were calculated. Third, we investigated our previously reported metabolites associated with anthropometric and dietary factors mediators in sex-stratified causal mediation analysis. For all steps, both urine and blood metabolites were considered. We found 41 metabolites in the literature associated with clinical biomarkers meeting our inclusion criteria. We were able to replicate an inverse association of betaine with CRP in women, between body mass index and C-reactive protein (CRP) and between body fat and leptin. There was no evidence of mediation by lifestyle-related metabolites after correction for multiple testing. We were only able to partially replicate previous findings in our age group and did not find evidence of mediation. The complex interactions between lifestyle factors, the metabolome, and clinical biomarkers warrant further investigation.
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Metaboloma , Metabolómica , Masculino , Adulto Joven , Humanos , Femenino , Adolescente , Estudios de Cohortes , Biomarcadores , Factores de RiesgoRESUMEN
SCOPE: Habitual diet may be reflected in metabolite profiles that can improve accurate assessment of dietary exposure and further enhance our understanding of their link to health conditions. The study aims to explore the relationship of habitual food intake with blood and urine metabolites in adolescents and young adults. METHODS: The study population comprises 228 participants (94 males and 134 females) of the DONALD study. Dietary intake is assessed by yearly repeated 3d-food records. Habitual diet is estimated as the average consumption of 23 food groups in adolescence. Using an untargeted metabolomics approach, the study quantifies 2638 metabolites in plasma and 1407 metabolites in urine. In each sex, unique diet-metabolite associations using orthogonal projection to latent structures (oPLS) and random forests (RF) is determined. RESULTS: Six metabolites in agreement between oPLS and RF in urine, one in female (vanillylmandelate to processed/other meat) and five in males (indole-3-acetamide, and N6-methyladenosine to eggs; hippurate, citraconate/glutaconate, and X - 12111 to vegetables) are observed. No association in blood in agreement is observed. CONCLUSION: A limited reflection of habitual food group intake by single metabolites in urine and not in blood is observed. The explored biomarkers should be confirmed in additional studies.
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Metaboloma , Metabolómica , Adolescente , Biomarcadores , Estudios de Cohortes , Dieta , Ingestión de Alimentos , Femenino , Hipuratos , Humanos , Masculino , Verduras , Adulto JovenRESUMEN
BACKGROUND: Validation of the EAT-Lancet reference diet (ELR-diet), recently proposed by the EAT-Lancet Commission, within the context of real-life studies is necessary to elucidate its feasibility, nutritional value, sustainability, and health effects. OBJECTIVES: We aimed to develop a dietary index (DI) score to measure adherence to the ELR-diet. We further aimed to study the association between the DI score and 1) nutritional characteristics, 2) indicators of ecological sustainability, and 3) anthropometric markers and biomarkers for cardiometabolic health. METHODS: A DI score was constructed by comparing the categories defined by the ELR-diet with the dietary data of 2-5 sets of 3-d weighed dietary records from DONALD (Dortmund Nutritional and Anthropometric Longitudinal Designed) study participants (n = 298; ≥15 y of age). Prospective associations between the DI score and risk markers (anthropometric and cardiometabolic) in young adulthood (≥18 y old) were investigated using multivariate linear regression. RESULTS: Adherence to the DI score components was considerable (majority > 50%), but varied within the population (2%-100%). The highest tertile of the DI score was inversely associated with the intake of protein (tertile 3 compared with tertile 1: 13.5 compared with 14.5 energy %), added sugars (10.5 compared with 12.4 energy %), and cholesterol (100 compared with 116 mg/1000 kcal), but positively associated with fiber intake (10.0 compared with 8.82 g/1000 kcal) (all P < 0.05). The DI score was inversely associated with greenhouse-gas emissions (tertile 1 compared with tertile 3: 6.48 compared with 5.85 kg of carbon dioxide equivalents/2500 kcal; P < 0.001) and land use (8.24 compared with 7.16 m2 × y/2500 kcal; P < 0.001). Inverse associations between the DI score and anthropometric markers during young adulthood were observed (e.g., BMI: tertile 1 compared with tertile 3: 22.9 compared with 21.9 kg/m2; P = 0.03) (all P < 0.05). No associations between the DI score and cardiometabolic risk markers were found (all P ≥ 0.05). CONCLUSIONS: Adherence to the ELR-diet was associated with favorable nutritional characteristics and reduced environmental impact. Adherence to the DI score in adolescence was also beneficial with respect to anthropometric markers in early adulthood, although not for further cardiometabolic risk markers.
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Enfermedades Cardiovasculares , Dieta , Adolescente , Adulto , Antropometría , Enfermedades Cardiovasculares/epidemiología , Estudios de Cohortes , Registros de Dieta , Humanos , Adulto JovenRESUMEN
BACKGROUND: There is emerging evidence that the gut microbiome composition is associated with several human health outcomes, which include cognitive performance. However, only a few prospective epidemiological studies exist and none among young adults. Here we address the gap in the literature by investigating whether the gut microbiome composition is prospectively linked to fluid intelligence among healthy young adults. METHODS: Forty individuals (65% females, 26 years) from the DOrtmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study provided a fecal sample for gut microbiome composition and subsequently (average of 166 days) completed a cognitive functioning test using the Cattell's Culture Fair Intelligence Test, revised German version (CFT 20-R). The assessment of the gut microbiome at the genera level was by 16S rRNA V3-V4 Illumina sequencing. The relative abundance of 158 genera was summarized into bacterial communities using a novel data-driven dimension reduction, amalgamation. The fluid intelligence score was regressed on the relative abundance of the bacterial communities and adjusted for selected covariates. RESULTS: The 158 genera were amalgamated into 12 amalgams (bacterial communities), which were composed of 18, 6, 10, 14, 8, 10, 16, 13, 12, 12, 3, and 11 genera. Only the 14-genera bacterial community, named the "Ruminococcaceae- and Coriobacteriaceae-dominant community" was positively associated with fluid intelligence score (ß = 7.8; 95% CI: 0.62, 15.65, P = 0.04). CONCLUSION: Among healthy young adults, the abundance of a gut bacterial community was associated with fluid intelligence score. This study suggests that cognitive performance may potentially benefit from gut microbiome-based intervention.
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Tryptophan and its bioactive metabolites are associated with health conditions such as systemic inflammation, cardiometabolic diseases, and neurodegenerative disorders. There are dynamic interactions among metabolites of tryptophan. The interactions between metabolites, particularly those that are strong and temporally reproducible could be of pathophysiological relevance. Using a targeted metabolomics approach, the concentration levels of tryptophan and 18 of its metabolites across multiple pathways was quantified in 24-hours urine samples at 2 time-points, age 17 years (baseline) and 18 years (follow-up) from 132 (52% female) apparently healthy adolescent participants of the DOrtmund Nutritional and Anthropometric Longitudinally Designed (DONALD) Study. In sex-specific analyses, we applied 2 network approaches, the Gaussian graphical model and Bayesian network to (1) explore the network structure for both time-points, (2) retrieve strongly related metabolites, and (3) determine whether the strongly related metabolites were temporally reproducible. Independent of selected covariates, the 2 network approaches revealed 5 associations that were strong and temporally reproducible. These were novel relationships, between kynurenic acid and indole-3-acetic acid in females and between kynurenic acid and xanthurenic acid in males, as well as known relationships between kynurenine and 3-hydroxykynurenine, and between 3-hydroxykynurenine and 3-hydroxyanthranilic acid in females and between tryptophan and kynurenine in males. Overall, this epidemiological study using network-based approaches shed new light into tryptophan metabolism, particularly the interaction of host and microbial metabolites. The 5 observed relationships suggested the existence of a temporally stable pattern of tryptophan and 6 metabolites in healthy adolescent, which could be further investigated in search of fingerprints of specific physiological states. The metabolites in these relationships may represent a multi-biomarker panel that could be informative for health outcomes.
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In any research field, data access and data integration are major challenges that even large, well-established consortia face. Although data sharing initiatives are increasing, joint data analyses on nutrition and microbiomics in health and disease are still scarce. We aimed to identify observational studies with data on nutrition and gut microbiome composition from the Intestinal Microbiomics (INTIMIC) Knowledge Platform following the findable, accessible, interoperable, and reusable (FAIR) principles. An adapted template from the European Nutritional Phenotype Assessment and Data Sharing Initiative (ENPADASI) consortium was used to collect microbiome-specific information and other related factors. In total, 23 studies (17 longitudinal and 6 cross-sectional) were identified from Italy (7), Germany (6), Netherlands (3), Spain (2), Belgium (1), and France (1) or multiple countries (3). Of these, 21 studies collected information on both dietary intake (24 h dietary recall, food frequency questionnaire (FFQ), or Food Records) and gut microbiome. All studies collected stool samples. The most often used sequencing platform was Illumina MiSeq, and the preferred hypervariable regions of the 16S rRNA gene were V3-V4 or V4. The combination of datasets will allow for sufficiently powered investigations to increase the knowledge and understanding of the relationship between food and gut microbiome in health and disease.
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Microbioma Gastrointestinal , Encuestas Nutricionales , Ciencias de la Nutrición , Estudios Observacionales como Asunto , Encuestas sobre Dietas/métodos , Ingestión de Alimentos , Europa (Continente) , Humanos , Difusión de la Información , Metadatos , Encuestas Nutricionales/métodos , Ciencias de la Nutrición/métodosRESUMEN
Intake of added sugars (AS) is challenging to assess compared with total dietary sugar because of the lack of reliable assessment methods. The reliance on self-reported dietary data in observational studies is often cited as biased, with evidence of AS intake in relation to health outcomes rated as low to moderate quality. Sugar-sweetened beverages (SSBs) are a major source of AS. A regular and high intake of SSBs is associated with an overall poor diet, weight gain, and cardiometabolic risks. An elevated intake of low-calorie sweetened beverages (LCSBs), often regarded as healthier alternatives to SSBs, is also increasingly associated with increased risk for metabolic dysfunction. In this review, we systematically collate evidence and provide perspectives on the use of metabolomics for the discovery of candidate biomarkers associated with the intake of SSBs and LCSBs. We searched the Medline, Embase, Scopus, and Web of Science databases until the end of December 2020. Seventeen articles fulfilled our inclusion criteria. We evaluated specificity and validity of the identified biomarkers following Guidelines for Biomarker of Food Intake Reviews (BFIRev). We report that the 13C:12C carbon isotope ratio (δ13C), particularly, the δ13C of alanine is the most robust, sensitive, and specific biomarker of SSBs intake. Acesulfame-K, saccharin, sucralose, cyclamate, and steviol glucuronide showed moderate validity for predicting the short-term intake of LCSBs. More evidence is required to evaluate the validity of other panels of metabolites associated with the intake of SSBs.
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BACKGROUND AND PURPOSE: It used to be a common practice in the field of nutritional epidemiology to analyze separate nutrients, foods, or food groups. However, in reality, nutrients and foods are consumed in combination. The introduction of dietary patterns (DP) and their analysis has revolutionized this field, making it possible to take into account the synergistic effects of foods and to account for the complex interaction among nutrients and foods. Three approaches of DP analysis exist: (1) the hypothesis-based approach (based on prior knowledge regarding the current understanding of dietary components and their health relation), (2) the exploratory approach (solely relying on dietary intake data), and (3) the hybrid approach (a combination of both approaches). During the recent past, complementary approaches for DP analysis have emerged both conceptually and methodologically. METHOD: We have summarized the recent developments that include incorporating the Treelet transformation method as a complementary exploratory approach in a narrative review. RESULTS: Uses, peculiarities, strengths, limitations, and scope of recent developments in DP analysis are outlined. Next, the narrative review gives an overview of the literature that takes into account potential relevant dietary-related factors, specifically the metabolome and the gut microbiome in DP analysis. Then the review deals with the aspect of data processing that is needed prior to DP analysis, particularly when dietary data arise from assessment methods other than the long-established food frequency questionnaire. Lastly, potential opportunities for upcoming DP analysis are summarized in the outlook. CONCLUSION: Biological factors like the metabolome and the microbiome are crucial to understand diet-disease relationships. Therefore, the inclusion of these factors in DP analysis might provide deeper insights.
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Conducta Alimentaria , Microbioma Gastrointestinal , Dieta , Encuestas sobre Dietas , AlimentosRESUMEN
BACKGROUND: Gut microbiota composition as influenced by long-term diet may be associated with the risk of adult chronic diseases. Thus, establishing the relation of long-term diet, particularly starting from early life, with adult microbiota composition would be an important research advance. OBJECTIVE: We aimed to investigate the association of long-term intake of energy, carbohydrate, fiber, protein, and fat from infancy to late adolescence with microbiota composition in adulthood. METHODS: Within the prospective DOrtmund Nutritional and Anthropometric Longitudinally Designed (DONALD) Study, we sampled stool 1 or 2 times within 1 y from 128 adults (median age: 29 y). Microbiota composition was profiled by 16S ribosomal RNA sequencing. Annual dietary records from age 1 to 18 y were retrieved. We estimated trajectories of energy, energy-adjusted carbohydrate, fiber, protein, and fat intake with multilevel models, producing predicted intake at age 1 y and rates of change in intake. A multivariate, zero-inflated, logistic-normal model was used to model the association between intake trajectories and the composition of 158 genera in single-sampled individuals. Associations found in this model were confirmed in double-sampled individuals using a zero-inflated Beta regression model. RESULTS: Adjusting for covariates and temporal differences in microbiota composition, long-term carbohydrate intake was associated with 3 genera. Specifically, carbohydrate intake at age 1 y was negatively associated with Phascolarctobacterium [coefficient = -4.31; false discovery rate (FDR)-adjusted P = 0.006] and positively associated with Dialister (coefficient = 3.06; FDR-adjusted P = 0.003), and the rate of change in carbohydrate intake was positively associated with Desulfovibrio (coefficient = 13.16; FDR-adjusted P = 0.00039). Energy and other macronutrients were not associated with any genus. CONCLUSIONS: This work links long-term carbohydrate intake to microbiota composition. Considering the associations of high carbohydrate intake and microbiota composition with some diseases, these findings could inform the development of gut microbiota-targeted dietary recommendations for disease prevention.
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Envejecimiento , Bacterias/clasificación , Fenómenos Fisiológicos Nutricionales Infantiles , Carbohidratos de la Dieta/administración & dosificación , Microbioma Gastrointestinal , Adolescente , Adulto , Bacterias/genética , Niño , Preescolar , ADN Bacteriano/genética , Heces/microbiología , Humanos , Lactante , ARN Bacteriano , ARN Ribosómico 16S/genéticaRESUMEN
Metabolomics can be a tool to identify dietary biomarkers. However, reported food-metabolite associations have been inconsistent, and there is a need to explore further associations. Our aims were to confirm previously reported food-metabolite associations and to identify novel food-metabolite associations. We conducted a cross-sectional analysis of data from 849 participants (57% men) of the PopGen cohort. Dietary intake was obtained using FFQ and serum metabolites were profiled by an untargeted metabolomics approach. We conducted a systematic literature search to identify previously reported food-metabolite associations and analyzed these associations using linear regression. To identify potential novel food-metabolite associations, datasets were split into training and test datasets and linear regression models were fitted to the training datasets. Significant food-metabolite associations were evaluated in the test datasets. Models were adjusted for covariates. In the literature, we identified 82 food-metabolite associations. Of these, 44 associations were testable in our data and confirmed associations of coffee with 12 metabolites, of fish with five, of chocolate with two, of alcohol with four, and of butter, poultry and wine with one metabolite each. We did not identify novel food-metabolite associations; however, some associations were sex-specific. Potential use of some metabolites as biomarkers should consider sex differences in metabolism.
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Epidemiologic studies examining the relationship between body composition and the urine metabolome may improve our understanding of the role of metabolic dysregulation in body composition-related health conditions. Previous studies, mostly in adult populations, have focused on a single measure of body composition, body mass index (BMI), and sex-specific associations are rarely explored. We investigate sex-specific associations of two measures of body composition-BMI and body fat (BF)-with the urine metabolome in adolescents. In 369 participants (age 16-18, 49% female) of the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study, we examined sex-specific associations of these two measures of body composition, BMI and BF, and 1407 (467 unknown) 24 h urine metabolites analyzed by untargeted metabolomics cross-sectionally. Missing metabolites were imputed. We related metabolites (dependent variable) to BMI and BF (independent variable) separately using linear regression. The models were additionally adjusted for covariates. We found 10 metabolites associated with both BMI and BF. We additionally found 11 metabolites associated with only BF, and nine with only BMI. None of these associations was in females. We observed a strong sexual dimorphism in the relationship between body composition and the urine metabolome.
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Amino acid metabolites in biofluids are associated with high body mass index (BMI) and cardiometabolic abnormalities. However, prospective investigations regarding these associations are few, particularly among young individuals. Moreover, little is presently known about the impact of long-term high BMI. Using data from the DOrtmund Nutritional and Anthropometric Longitudinally Designed study (111 males and 107 females), we prospectively investigated relations between repeatedly measured urinary levels of 33 metabolites and (1) previously identified long-term BMI trajectory groups from childhood into late adolescence and (2) cardiometabolic risk markers in late adolescence-young adulthood, in sex-specific linear mixed regression models. Males with long-term overweight had lower indole-3-acetic acid when compared to others. Further, methionine, isoleucine, tryptophan, xanthurenic acid, and indole-3-carboxaldehyde were negatively associated with C-reactive protein (CRP), but 5-hydroxyindole-3-acetic acid was positively associated with CRP. No associations were observed in females. Long-term overweight from childhood into late adolescence is associated with decreased urinary levels of gut bacteria-derived indole-3-acetic acid, and several urinary amino acids, including gut bacteria-derived indole-3-carboxaldehyde are associated with elevated CRP later on in life. Taken together, our data suggest that indole metabolites, and their gut bacteria producers play potentially important roles in overweight-related inflammation.
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Aminoácidos/metabolismo , Índice de Masa Corporal , Enfermedades Cardiovasculares/metabolismo , Indoles/metabolismo , Enfermedades Metabólicas/metabolismo , Metaboloma , Adolescente , Biomarcadores/metabolismo , Niño , Femenino , Humanos , Quinurenina/metabolismo , Modelos Lineales , Masculino , Análisis Multivariante , Factores de RiesgoRESUMEN
BACKGROUND: Although dietary intakes and dietary intake patterns (DPs) have been associated with single metabolites, it is unclear whether DPs are also reflected in specific metabolite patterns (MPs). Moreover, the influence of groups of gut bacteria on the relationship between DPs and MPs is underexplored. OBJECTIVES: We aimed to investigate the association of DPs and serum MPs and also the modifying effect of the gut bacteria compositional patterns (BCPs). METHODS: This is a cross-sectional investigation among 225 individuals (median age: 63 y; 53% women) from the European Prospective Investigation into Cancer and Nutrition study. Dietary intakes were assessed by three 24-h dietary recalls, gut bacteria composition was quantified by 16S rRNA gene sequencing, and the serum metabolome was profiled by an untargeted approach. We identified DPs and BCPs by the treelet transform analysis. We modeled associations between DPs and 8 previously published MPs and the modifying effect of BCPs by fitting generalized linear models using DataSHIELD R. RESULTS: We identified 5 DPs and 7 BCPs. The "bread, margarine, and processed meat" and "fruiting vegetables and vegetable oils" DPs were positively associated with the "amino acids" (ß = 0.35; 95% CI: 0.02, 0.69; P = 0.03) and "fatty acids" MPs (ß = 0.45; 95% CI: 0.16, 0.74; P = 0.01), respectively. The "tea and miscellaneous" was inversely associated with the "amino acids" (ß = -0.28; 95% CI: -0.52, -0.05; P = 0.02) and "amino acid derivatives" MPs (ß = -0.21; 95% CI: -0.39, -0.02; P = 0.03). One BCP negatively modified the association between the "bread, margarine, and processed meat" DP and the "amino acids" MP (P-interaction = 0.01). CONCLUSIONS: In older German adults, DPs are reflected in MPs, and the gut bacteria attenuate 1 DP-MP association. These MPs should be explored as biomarkers of these jointly consumed foods while taking into account a potentially modifying role of the gut bacteria.
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Dieta , Conducta Alimentaria , Alimentos/clasificación , Microbioma Gastrointestinal , Adulto , Anciano , Biomarcadores/sangre , Estudios Transversales , Femenino , Humanos , Masculino , Persona de Mediana EdadRESUMEN
PURPOSE: The aim of the present study was to derive overall and sex-specific dietary patterns associated with inflammatory biomarkers in a general population sample from Northern Germany. METHODS: The present analysis included 1158 participants (477 men, 681 women, mean age: 53.1 years; mean body mass index: 26.2 kg/m2) of the Food Chain Plus (FoCus) cohort in Kiel, Germany. Participants completed a semi-quantitative food frequency questionnaire and provided blood samples. Reduced rank regression with C-reactive protein (CRP) and Interleukin 6 (IL-6) as response variables was used to derive dietary patterns. After a mean follow-up of 1.7 years, a second blood sample was obtained in a subsample of 112 individuals. Multiple regression models were used to examine the association between dietary patterns at baseline and inflammatory biomarkers at follow-up. RESULTS: The overall pattern characterised by high intakes of soft drinks, meat, potatoes and sauce, and low intakes of other cereals (except pasta/rice), wine, nuts, seeds, vegetarian dishes, vegetable oil, and fish was positively associated with CRP (OR 2.20; 95% CI 1.12, 4.35) and IL-6 (OR 3.14; 95% CI 1.26, 7.87) at follow-up. In men, the dietary pattern was higher in soft drinks, processed meat and low in cereals and plant-based fats. In women, the pattern was characterised by soft drinks, meat, vegetables and low in other cereals, wine, nuts, and seeds. The association between sex-specific patterns with inflammatory biomarkers was weaker for CRP. CONCLUSION: We identified dietary patterns positively associated with established biomarkers of chronic low-grade inflammation.
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Dieta/métodos , Inflamación/sangre , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Biomarcadores/sangre , Estudios de Cohortes , Femenino , Estudios de Seguimiento , Alemania , Encuestas Epidemiológicas/métodos , Encuestas Epidemiológicas/estadística & datos numéricos , Humanos , Masculino , Persona de Mediana Edad , Factores Sexuales , Adulto JovenRESUMEN
Tryptophan and tyrosine metabolism has a major effect on human health, and disorders have been associated with the development of several pathologies. Recently, gut microbial metabolism was found to be important for maintaining correct physiology. Here, we describe the development and validation of a UHPLC-ESI-MS/MS method for targeted quantification of 39 metabolites related to tryptophan and tyrosine metabolism, branched chain amino acids and gut-derived metabolites in human plasma and urine. Extraction from plasma was optimised using 96-well plates, shown to be effective in removing phospholipids. Urine was filtered and diluted ten-fold. Metabolites were separated with reverse phase chromatography and detected using triple quadrupole MS. Linear ranges (from ppb to ppm) and correlation coefficients (r2 > 0.990) were established for both matrices independently and the method was shown to be linear for all tested metabolites. At medium spiked concentration, recovery was over 80% in both matrices, while analytical precision was excellent (CV < 15%). Matrix effects were minimal and retention time stability was excellent. The applicability of the methods was tested on biological samples, and metabolite concentrations were found to be in agreement with available data. The method allows the analysis of up to 96 samples per day and was demonstrated to be stable for up to three weeks from acquisition.
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BACKGROUND: Porphyromonas gingivalis (P.g) is unique among pathogens due to its ability to generate citrullinated proteins in an inflammatory milieu, potentially mediating the loss of immune tolerance, the production of anticitrullinated protein antibodies (ACPAs), and subsequently the development of rheumatoid arthritis (RA). Based on this hypothesis, we set out to investigate whether P.g is linked to ACPAs in a well-characterized German population. PARTICIPANTS AND METHODS: A total of 600 participants (292 women and 308 men with a mean age of 67 years) of the European Prospective Investigation into Cancer and Nutrition-Potsdam study were selected in 2013, and paired saliva and serum samples were collected. Salivary P.g DNA and serum anticyclic citrullinated peptide (anti-CCP2) levels were quantified by real-time polymerase chain reaction and anti-CCP2 enzyme-linked immunosorbent assay, respectively. In selected participants, additional ACPA fine-specificities were also analysed on a custom-made multiplex peptide array. RESULTS: Among participants with C-reactive protein greater than 3.0 mg/l, a one-unit increase in P.g DNA was associated with an almost twofold increase in anti-CCP2 levels. Moreover, participants with high P.g DNA had on average approximately 2.8-times higher anti-CCP2 levels when compared with participants with low P.g DNA, (Holm-adjusted p value = 0.01). Furthermore, citrullinated epitopes on α-enolase and vimentin were common ACPA reactivities among participants who also had high P.g DNA and elevated C-reactive protein. CONCLUSIONS: Our study suggests that in specific subgroups of individuals with systemic inflammation, higher salivary P.g DNA is associated with elevated serum ACPA. These data support a role for P.g in the development of anticitrulline immunity.