Fasting plasma metabolites reflecting meat consumption and their associations with incident type 2 diabetes in two Swedish cohorts.

BACKGROUND: Consumption of processed red meat has been associated with increased risk of developing type 2 diabetes (T2D), but challenges in dietary assessment call for objective intake biomarkers. OBJECTIVES: This study aimed to investigate metabolite biomarkers of meat intake and their associations with T2D risk. METHODS: Fasting plasma samples were collected from a case-control study nested within Västerbotten Intervention Program (VIP) (214 females and 189 males) who developed T2D after a median follow-up of 7 years. Panels of biomarker candidates reflecting the consumption of total, processed, and unprocessed red meat and poultry were selected from the untargeted metabolomics data collected on the controls. Observed associations were then replicated in Swedish Mammography clinical subcohort in Uppsala (SMCC) (n = 4457 females). Replicated metabolites were assessed for potential association with T2D risk using multivariable conditional logistic regression in the discovery and Cox regression in the replication cohorts. RESULTS: In total, 15 metabolites were associated with ≥1 meat group in both cohorts. Acylcarnitines 8:1, 8:2, 10:3, reflecting higher processed meat intake [r > 0.22, false discovery rate (FDR) < 0.001 for VIP and r > 0.05; FDR < 0.001 for SMCC) were consistently associated with higher T2D risk in both data sets. Conversely, lysophosphatidylcholine 17:1 and phosphatidylcholine (PC) 15:0/18:2 were associated with lower processed meat intake (r < -0.12; FDR < 0.023, for VIP and r < -0.05; FDR < 0.001, for SMCC) and with lower T2D risk in both data sets, except for PC 15:0/18:2, which was significant only in the VIP cohort. All associations were attenuated after adjustment for BMI (kg/m2). CONCLUSIONS: Consistent associations of biomarker candidates involved in lipid metabolism between higher processed red meat intake with higher T2D risk and between those reflecting lower intake with the lower risk may suggest a relationship between processed meat intake and higher T2D risk. However, attenuated associations after adjusting for BMI indicates that such a relationship may at least partly be mediated or confounded by BMI.

Exploration of differential responses to FODMAPs and gluten in people with irritable bowel syndrome- a double-blind randomized cross-over challenge study.

INTRODUCTION: There is large variation in response to diet in irritable bowel syndrome (IBS) and determinants for differential response are poorly understood. OBJECTIVES: Our aim was to investigate differential clinical and molecular responses to provocation with fermentable oligo-, di-, monosaccharides, and polyols (FODMAPs) and gluten in individuals with IBS. METHODS: Data were used from a crossover study with week-long interventions with either FODMAPs, gluten or placebo. The study also included a rapid provocation test. Molecular data consisted of fecal microbiota, short chain fatty acids, and untargeted plasma metabolomics. IBS symptoms were evaluated with the IBS severity scoring system. IBS symptoms were modelled against molecular and baseline questionnaire data, using Random Forest (RF; regression and clustering), Parallel Factor Analysis (PARAFAC), and univariate methods. RESULTS: Regression and classification RF models were in general of low predictive power (Q2 ≤ 0.22, classification rate < 0.73). Out of 864 clustering models, only 2 had significant associations to clusters (0.69 < CR < 0.73, p < 0.05), but with no associations to baseline clinical measures. Similarly, PARAFAC revealed no clear association between metabolome data and IBS symptoms. CONCLUSION: Differential IBS responses to FODMAPs or gluten exposures could not be explained from clinical and molecular data despite extensive exploration with different data analytical approaches. The trial is registered at www. CLINICALTRIALS: gov as NCT03653689 31/08/2018.

Quantitation of circulating short-chain fatty acids in small volume blood samples from animals and humans.

BACKGROUND: The role of gut microbiota in human health has been intensively studied and more recently shifted from emphasis on composition towards function. Function is partly mediated through formed metabolites. Short-chain fatty acids (SCFAs) such as acetate, propionate, and butyrate as well as their branched analogues represent major products from gut fermentation of dietary fibre and proteins, respectively. Robust and high-throughput analysis of SCFAs in small volume blood samples have proven difficult. Major obstacles come from the ubiquitous presence of SCFAs that leads to contaminations and unstable analytical results because of the high volatility of these small molecules. Comprehensive and comparable data on the variation of SCFAs in blood samples from different blood matrices and mammal species including humans is lacking. Therefore, our aim was to develop and evaluate a stable and robust method for quantitation of 8 SCFAs and related fermentation products in small volume blood plasma samples and to investigate their variation in humans and different animal species. RESULTS: Derivatization was a successful approach for measurement of SCFAs in biological samples but quenching of the derivatization reaction was crucial to obtain long-term stability of the derivatized analytes. In total 9 compounds (including succinic acid) were separated in 5 min. The method was linear over the range 0.6-3200 nM formic (FA), acetic (AA), 0.3-1600 nM propionic (PA), and 0.16-800 nM for butyric (BA)-, isobutyric (IBA)-, valeric (VA)-, isovaleric (IVA)-, succinic (SA) and caproic acid (CA). The precision ranged ≤12 % within days and ≤28 % between days (except for CA and VA) in three different plasma quality control (QC) samples (29 batches analyzed over 3 months). The extraction recovery was on average 94 % for the different SCFAs. Typical interquartile range (IQR) concentrations (µM) of SCFAs in human plasma samples were 168 µM (FA), 64 µM (AA), 2.2 µM (PA), 0.54 µM (BA), 0.66 µM (IBA), 0.18 µM (VA), 0.40 µM (IVA), and 0.34 µM (CA). In total, 55 samples per batch/day were successfully analyzed and in total 5380 human plasma samples measured over a 3-year timespan. SIGNIFICANCE: The developed UHPLC-MS based method was suitable for measuring SCFAs in small blood volume samples and enabled robust quantitative data.

Temporal gut microbiota variability and association with dietary patterns: From the one-year observational Diet, Cancer, and Health - Next Generations MAX study.

BACKGROUND: Knowledge about the variability of gut microbiota within an individual over time is important to allow meaningful investigations of the gut microbiota in relation to diet and health outcomes in observational studies. Plant-based dietary patterns have been associated with a lower risk of morbidity and mortality and may alter gut microbiota in a favorable direction. OBJECTIVES: To assess the gut microbiota variability during one year and investigate the association between adherence to diet indexes and the gut microbiota in a Danish population. METHODS: Four hundred forty-four participants were included in the Diet, Cancer, and Health - Next Generations MAX study (DCH-NG MAX). Stool samples collected up to three times during a year were analyzed by 16S ribosomal ribonucleic acid gene sequencing. Diet was obtained by 24-hour dietary recalls. Intraclass correlation coefficient (ICC) was calculated to assess temporal microbial variability based on 214 individuals. Diet indexes (Nordic, Mediterranean, and plant-based diets) and food groups thereof were associated with gut microbiota using linear regression analyses. RESULTS: We found that 91 out of 234 genera had an ICC >0.5. We identified three subgroups dominated by Bacteroides, Prevotella 9, and Ruminococcaceae and adherence to diet indexes differed between subgroups. Higher adherence to diet indexes was associated with the relative abundance of 22 genera. Across diet indexes, higher intakes of fruit, vegetables, whole grains/cereals, and nuts were most frequently associated with these genera. CONCLUSIONS: In the DCH-NG MAX study, 39% of the genera had an ICC >0.5 over one year, suggesting that these genera could be studied with health outcomes in prospective analyses with acceptable precision. Adherence to the Nordic, Mediterranean, and plant-based diets differed between bacterial subgroups and was associated with a higher abundance of genera with fiber-degrading properties. Fruits, vegetables, whole grains/cereals, and nuts were frequently associated with these genera.

Effects on cardiovascular risk factors of a low- vs high-glycemic index Mediterranean diet in high cardiometabolic risk individuals: the MEDGI-Carb study.

BACKGROUND: The role of dietary Glycemic Index (GI), independently of fiber intake, in modulating cardiovascular disease (CVD) risk among non-diabetic individuals has not been fully elucidated. OBJECTIVE: To evaluate the effects of a low- versus a high-GI diet, based on a Mediterranean dietary pattern, on cardiometabolic risk factors in individuals at high CVD risk, participating in the MEDGI-Carb intervention study. SUBJECTS AND METHODS: 160 individuals, aged 30-69 years, BMI 25-37 kg/m2, with a waist circumference >102 cm (males) or >88 cm (females) and one feature of the metabolic syndrome, participated in a multi-national (Italy, Sweden, USA) randomized controlled parallel group trial. Participants were assigned to a low GI (< 55) or high-GI MedDiet ( > 70) for 12 weeks. The diets were isoenergetic and similar for available carbohydrate (270 g/d) and fiber (35 g/d) content. Fasting metabolic parameters were evaluated in the whole cohort, while an 8-h triglyceride profile (after standard breakfast and lunch) was evaluated only in the Italian cohort. RESULTS: Blood pressure and most fasting metabolic parameters improved at the end of the dietary intervention (time effect, p < 0.05 for all); however, no differences were observed between the low- and the high-GI MedDiet groups (time x group effect; p > 0.05 for all). Conversely, the low-GI diet, compared with high-GI diet, significantly reduced the 8-h triglyceride profile (p < 0.017, time*group effect) that was measured only in the Italian cohort. However, it induced a reduction of plasma triglycerides after lunch (tAUC) that was of only borderline statistically significance (p = 0.065). CONCLUSIONS: Consuming a low-GI in comparison with a high-GI MedDiet does not differentially affect the major cardiometabolic risk factors at fasting in individuals at increased cardiometabolic risk. Conversely, it could reduce postprandial plasma triglycerides. CLINICAL TRIAL REGISTRY NUMBER: NCT03410719, ( https://clinicaltrials.gov ).

OMICs Signatures Linking Persistent Organic Pollutants to Cardiovascular Disease in the Swedish Mammography Cohort.

Cardiovascular disease (CVD) development may be linked to persistent organic pollutants (POPs), including organochlorine compounds (OCs) and perfluoroalkyl and polyfluoroalkyl substances (PFAS). To explore underlying mechanisms, we investigated metabolites, proteins, and genes linking POPs with CVD risk. We used data from a nested case-control study on myocardial infarction (MI) and stroke from the Swedish Mammography Cohort - Clinical (n = 657 subjects). OCs, PFAS, and multiomics (9511 liquid chromatography-mass spectrometry (LC-MS) metabolite features; 248 proteins; 8110 gene variants) were measured in baseline plasma. POP-related omics features were selected using random forest followed by Spearman correlation adjusted for confounders. From these, CVD-related omics features were selected using conditional logistic regression. Finally, 29 (for OCs) and 12 (for PFAS) unique features associated with POPs and CVD. One omics subpattern, driven by lipids and inflammatory proteins, associated with MI (OR = 2.03; 95% CI = 1.47; 2.79), OCs, age, and BMI, and correlated negatively with PFAS. Another subpattern, driven by carnitines, associated with stroke (OR = 1.55; 95% CI = 1.16; 2.09), OCs, and age, but not with PFAS. This may imply that OCs and PFAS associate with different omics patterns with opposite effects on CVD risk, but more research is needed to disentangle potential modifications by other factors.

Metabolome biomarkers linking dietary fibre intake with cardiometabolic effects: results from the Danish Diet, Cancer and Health-Next Generations MAX study.

Biomarkers associated with dietary fibre intake, as complements to traditional dietary assessment tools, may improve the understanding of its role in human health. Our aim was to discover metabolite biomarkers related to dietary fibre intake and investigate their association with cardiometabolic risk factors. We used data and samples from the Danish Diet Cancer and Health Next Generation (DCH-NG) MAX-study, a one-year observational study with evaluations at baseline, six and 12 months (n = 624, 55% female, mean age: 43 years, 1353 observations). Direct associations between fibre intake and plasma concentrations of 2,6-dihydroxybenzoic acid (2,6-DHBA) and indolepropionic acid were observed at the three time-points. Both metabolites showed an intraclass-correlation coefficient (ICC) > 0.50 and were associated with the self-reported intake of wholegrain cereals, and of fruits and vegetables, respectively. Other metabolites associated with dietary fibre intake were linolenoyl carnitine, 2-aminophenol, 3,4-DHBA, and proline betaine. Based on the metabolites associated with dietary fibre intake we calculated predicted values of fibre intake using a multivariate, machine-learning algorithm. Metabolomics-based predicted fibre, but not self-reported fibre values, showed negative associations with cardiometabolic risk factors (i.e. high sensitivity C-reactive protein, systolic and diastolic blood pressure, all FDR-adjusted p-values <0.05). Furthermore, different correlations with gut microbiota composition were observed. In conclusion, 2,6-DHBA and indolepropionic acid in plasma may better link dietary fibre intake with its metabolic effects than self-reported values. These metabolites may represent a novel class of biomarkers reflecting both dietary exposure and host and/or gut microbiota characteristics providing a read-out that is differentially related to cardiometabolic risk.

Association between gut health and gut microbiota in a polluted environment.

Animals host complex bacterial communities in their gastrointestinal tracts, with which they share a mutualistic interaction. The numerous effects these interactions grant to the host include regulation of the immune system, defense against pathogen invasion, digestion of otherwise undigestible foodstuffs, and impacts on host behaviour. Exposure to stressors, such as environmental pollution, parasites, and/or predators, can alter the composition of the gut microbiome, potentially affecting host-microbiome interactions that can be manifest in the host as, for example, metabolic dysfunction or inflammation. However, whether a change in gut microbiota in wild animals associates with a change in host condition is seldom examined. Thus, we quantified whether wild bank voles inhabiting a polluted environment, areas where there are environmental radionuclides, exhibited a change in gut microbiota (using 16S amplicon sequencing) and concomitant change in host health using a combined approach of transcriptomics, histological staining analyses of colon tissue, and quantification of short-chain fatty acids in faeces and blood. Concomitant with a change in gut microbiota in animals inhabiting contaminated areas, we found evidence of poor gut health in the host, such as hypotrophy of goblet cells and likely weakened mucus layer and related changes in Clca1 and Agr2 gene expression, but no visible inflammation in colon tissue. Through this case study we show that inhabiting a polluted environment can have wide reaching effects on the gut health of affected animals, and that gut health and other host health parameters should be examined together with gut microbiota in ecotoxicological studies.

Dietary patterns, untargeted metabolite profiles and their association with colorectal cancer risk.

We investigated data-driven and hypothesis-driven dietary patterns and their association to plasma metabolite profiles and subsequent colorectal cancer (CRC) risk in 680 CRC cases and individually matched controls. Dietary patterns were identified from combined exploratory/confirmatory factor analysis. We assessed association to LC-MS metabolic profiles by random forest regression and to CRC risk by multivariable conditional logistic regression. Principal component analysis was used on metabolite features selected to reflect dietary exposures. Component scores were associated to CRC risk and dietary exposures using partial Spearman correlation. We identified 12 data-driven dietary patterns, of which a breakfast food pattern showed an inverse association with CRC risk (OR per standard deviation increase 0.89, 95% CI 0.80-1.00, p = 0.04). This pattern was also inversely associated with risk of distal colon cancer (0.75, 0.61-0.96, p = 0.01) and was more pronounced in women (0.69, 0.49-0.96, p = 0.03). Associations between meat, fast-food, fruit soup/rice patterns and CRC risk were modified by tumor location in women. Alcohol as well as fruit and vegetables associated with metabolite profiles (Q2 0.22 and 0.26, respectively). One metabolite reflecting alcohol intake associated with increased CRC risk, whereas three metabolites reflecting fiber, wholegrain, and fruit and vegetables associated with decreased CRC risk.

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.

A Systematic Review and Comprehensive Evaluation of Human Intervention Studies to Unravel the Bioavailability of Hydroxycinnamic Acids.

Significance: Hydroxycinnamic acids (HCAs) are the main phenolic acids in the western diet. Harmonizing the available information on the absorption, distribution, metabolism, and excretion (ADME) of HCAs is fundamental to unraveling the compounds responsible for their health effects. This work systematically assessed pharmacokinetics, including urinary recovery, and bioavailability of HCAs and their metabolites, based on literature reports. Recent Advances: Forty-seven intervention studies with coffee, berries, herbs, cereals, tomato, orange, grape products, and pure compounds, as well as other sources yielding HCA metabolites, were included. Up to 105 HCA metabolites were collected, mainly acyl-quinic and C6-C3 cinnamic acids. C6-C3 cinnamic acids, such as caffeic and ferulic acid, reached the highest blood concentrations (maximum plasma concentration [Cmax] = 423 nM), with time to reach Cmax (Tmax) values ranging from 2.7 to 4.2 h. These compounds were excreted in urine in higher amounts than their phenylpropanoic acid derivatives (4% and 1% of intake, respectively), but both in a lower percentage than hydroxybenzene catabolites (11%). Data accounted for 16 and 18 main urinary and blood HCA metabolites, which were moderately bioavailable in humans (collectively 25%). Critical Issues: A relevant variability emerged. It was not possible to unequivocally assess the bioavailability of HCAs from each ingested source, and data from some plant based-foods were absent or inconsistent. Future Directions: A comprehensive study investigating the ADME of HCAs derived from their most important dietary sources is urgently required. Eight key metabolites were identified and reached interesting plasma Cmax concentrations and urinary recoveries, opening up new perspectives to evaluate their bioactivity at physiological concentrations. Antioxid. Redox Signal. 40, 510-541.

Effects of Wholegrain Compared to Refined Grain Intake on Cardiometabolic Risk Markers, Gut Microbiota, and Gastrointestinal Symptoms in Children: A Randomized Crossover Trial.

BACKGROUND: Wholegrain intake is associated with lower risk of cardiometabolic diseases in adults, potentially via changes in the gut microbiota. Although cardiometabolic prevention should start early, we lack evidence on the effects in children. OBJECTIVES: This study investigated the effects of wholegrain oats and rye intake on serum low-density lipoprotein (LDL) cholesterol and plasma insulin (coprimary outcomes), other cardiometabolic markers, body composition, gut microbiota composition and metabolites, and gastrointestinal symptoms in children with high body mass index (BMI). METHODS: In a randomized crossover trial, 55 healthy Danish 8- to 13-y-olds received wholegrain oats and rye ("WG") or refined grain ("RG") products ad libitum for 8 wk in random order. At 0, 8, and 16 wk, we measured anthropometry, body composition by dual-energy absorptiometry, and blood pressure. Fasting blood and fecal samples were collected for analysis of blood lipids, glucose homeostasis markers, gut microbiota, and short-chain fatty acids. Gut symptoms and stool characteristics were determined by questionnaires. Diet was assessed by 4-d dietary records and compliance by plasma alkylresorcinols (ARs). RESULTS: Fifty-two children (95%) with a BMI z-score of 1.5 ± 0.6 (mean ± standard deviation) completed the study. They consumed 108 ± 38 and 3 ± 2 g/d wholegrain in the WG and RG period, which was verified by a profound difference in ARs (P < 0.001). Compared with RG, WG reduced LDL cholesterol by 0.14 (95% confidence interval: -0.24, -0.04) mmol/L (P = 0.009) and reduced total:high-density lipoprotein cholesterol (P < 0.001) and triacylglycerol (P = 0.048) without altering body composition or other cardiometabolic markers. WG also modulated the abundance of specific bacterial taxa, increased plasma acetate, propionate, and butyrate and fecal butyrate and reduced fatigue with no other effects on gut symptoms. CONCLUSION: High intake of wholegrain oats and rye reduced LDL cholesterol and triacylglycerol, modulated bacterial taxa, and increased beneficial metabolites in children. This supports recommendations of exchanging refined grain with wholegrain oats and rye among children. This trial was registered at clinicaltrials.gov as NCT04430465.

Dietary Intake of Fructooligosaccharides Protects against Metabolic Derangements Evoked by Chronic Exposure to Fructose or Galactose in Rats.

SCOPE: Diets rich in fat and sugars evoke chronic low-grade inflammation, leading to metabolic derangements. This study investigates the impact of fructose and galactose, two commonly consumed simple sugars, on exacerbation of the harmful effects caused by high fat intake. Additionally, the potential efficacy of fructooligosaccharides (FOS), a fermentable dietary fiber, in counteracting these effects is examined. METHODS AND RESULTS: Male Sprague-Dawley rats (six/group) are fed 8 weeks as follows: control 5% fat diet (CNT), 20% fat diet (FAT), FAT+10% FOS diet (FAT+FOS), FAT+25% galactose diet (FAT+GAL), FAT+GAL+10% FOS diet (FAT+GAL+FOS), FAT+25% fructose diet (FAT+FRU), FAT+FRU+10% FOS diet (FAT+FRU+FOS). The dietary manipulations tested do not affect body weight gain, blood glucose, or markers of systemic inflammation whereas significant increases in plasma concentrations of triacylglycerols, cholesterol, aspartate aminotransferase, and alanine aminotrasferase are detected in both FAT+FRU and FAT+GAL compared to CNT. In the liver and skeletal muscle, both sugars induce significant accumulation of lipids and advanced glycation end-products (AGEs). FOS supplementation prevents these impairments. CONCLUSION: This study extends the understanding of the deleterious effects of a chronic intake of simple sugars and demonstrates the beneficial role of the prebiotic FOS in dampening the sugar-induced metabolic impairments by prevention of lipid and AGEs accumulation.

Dietary biomarkers-an update on their validity and applicability in epidemiological studies.

The aim of this literature review was to identify and provide a summary update on the validity and applicability of the most promising dietary biomarkers reflecting the intake of important foods in the Western diet for application in epidemiological studies. Many dietary biomarker candidates, reflecting intake of common foods and their specific constituents, have been discovered from intervention and observational studies in humans, but few have been validated. The literature search was targeted for biomarker candidates previously reported to reflect intakes of specific food groups or components that are of major importance in health and disease. Their validity was evaluated according to 8 predefined validation criteria and adapted to epidemiological studies; we summarized the findings and listed the most promising food intake biomarkers based on the evaluation. Biomarker candidates for alcohol, cereals, coffee, dairy, fats and oils, fruits, legumes, meat, seafood, sugar, tea, and vegetables were identified. Top candidates for all categories are specific to certain foods, have defined parent compounds, and their concentrations are unaffected by nonfood determinants. The correlations of candidate dietary biomarkers with habitual food intake were moderate to strong and their reproducibility over time ranged from low to high. For many biomarker candidates, critical information regarding dose response, correlation with habitual food intake, and reproducibility over time is yet unknown. The nutritional epidemiology field will benefit from the development of novel methods to combine single biomarkers to generate biomarker panels in combination with self-reported data. The most promising dietary biomarker candidates that reflect commonly consumed foods and food components for application in epidemiological studies were identified, and research required for their full validation was summarized.

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

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

Nutritional metabolomics: Recent developments and future needs.

Metabolomics has rapidly been adopted as one of the key methods in nutrition research. This review focuses on the recent developments and updates in the field, including the analytical methodologies that encompass improved instrument sensitivity, sampling techniques and data integration (multiomics). Metabolomics has advanced the discovery and validation of dietary biomarkers and their implementation in health research. Metabolomics has come to play an important role in the understanding of the role of small molecules resulting from the diet-microbiota interactions when gut microbiota research has shifted towards improving the understanding of the activity and functionality of gut microbiota rather than composition alone. Currently, metabolomics plays an emerging role in precision nutrition and the recent developments therein are discussed.

Differential Responders to a Mixed Meal Tolerance Test Associated with Type 2 Diabetes Risk Factors and Gut Microbiota-Data from the MEDGI-Carb Randomized Controlled Trial.

The global prevalence of type 2 diabetes mellitus (T2DM) has surged in recent decades, and the identification of differential glycemic responders can aid tailored treatment for the prevention of prediabetes and T2DM. A mixed meal tolerance test (MMTT) based on regular foods offers the potential to uncover differential responders in dynamical postprandial events. We aimed to fit a simple mathematical model on dynamic postprandial glucose data from repeated MMTTs among participants with elevated T2DM risk to identify response clusters and investigate their association with T2DM risk factors and gut microbiota. Data were used from a 12-week multi-center dietary intervention trial involving high-risk T2DM adults, comparing high- versus low-glycemic index foods within a Mediterranean diet context (MEDGICarb). Model-based analysis of MMTTs from 155 participants (81 females and 74 males) revealed two distinct plasma glucose response clusters that were associated with baseline gut microbiota. Cluster A, inversely associated with HbA1c and waist circumference and directly with insulin sensitivity, exhibited a contrasting profile to cluster B. Findings imply that a standardized breakfast MMTT using regular foods could effectively distinguish non-diabetic individuals at varying risk levels for T2DM using a simple mechanistic model.

Characterization of the Bacterial Composition of 47 Fermented Foods in Sweden.

Fermentation has long been utilized to preserve and enhance the flavor and nutritional value of foods. Recently, fermented foods have gained popularity, reaching new consumer groups due to perceived health benefits. However, the microbial composition of many fermented foods re-mains unknown. Here, we characterized the bacterial composition, diversity, and richness of 47 fermented foods available in Sweden, including kombucha, water kefir, milk kefir, yogurt, plant-based yogurt alternatives, kimchi, sauerkraut, and fermented vegetables. Via 16S rRNA gene sequencing, we identified 2497 bacteria (amplicon sequence variants). The bacterial composition was strongly associated with the type of fermented food, and lactic acid bacteria and/or acetic acid bacteria dominated most samples. However, each fermented food had a unique composition, with kombucha and water kefir having the highest diversity across and within samples. Few bacteria were abundant in multiple foods and food groups. These were Streptococcus thermophilus in yogurts and plant-based yoghurts; Lactococcus lactis in milk kefirs and one water kefir; and Lactiplantibacillus plantarum in kimchi, sauerkraut, and fermented cucumber. The broad range of fermented foods included in this study and their diverse bacterial communities warrant further investigation into the implications of microbial compositions for product traits and potential impact on human health.