Plasma metabolomics and proteomics profiling after a postprandial challenge reveal subtle diet effects on human metabolic status

Characterizing human postprandial metabolic response using multiway data analysis

INTRODUCTION

Analysis of time-resolved postprandial metabolomics data can improve our understanding of the human metabolism by revealing similarities and differences in postprandial responses of individuals. Traditional data analysis methods often rely on data summaries or univariate approaches focusing on one metabolite at a time.

OBJECTIVES

Our goal is to provide a comprehensive picture in terms of the changes in the human metabolism in response to a meal challenge test, by revealing static and dynamic markers of phenotypes, i.e., subject stratifications, related clusters of metabolites, and their temporal profiles.

METHODS

We analyze Nuclear Magnetic Resonance (NMR) spectroscopy measurements of plasma samples collected during a meal challenge test from 299 individuals from the COPSAC2000 cohort using a Nightingale NMR panel at the fasting and postprandial states (15, 30, 60, 90, 120, 150, 240 min). We investigate the postprandial dynamics of the metabolism as reflected in the dynamic behaviour of the measured metabolites. The data is arranged as a three-way array: subjects by metabolites by time. We analyze the fasting state data to reveal static patterns of subject group differences using principal component analysis (PCA), and fasting state-corrected postprandial data using the CANDECOMP/PARAFAC (CP) tensor factorization to reveal dynamic markers of group differences.

RESULTS

Our analysis reveals dynamic markers consisting of certain metabolite groups and their temporal profiles showing differences among males according to their body mass index (BMI) in response to the meal challenge. We also show that certain lipoproteins relate to the group difference differently in the fasting vs. dynamic state. Furthermore, while similar dynamic patterns are observed in males and females, the BMI-related group difference is observed only in males in the dynamic state.

CONCLUSION

The CP model is an effective approach to analyze time-resolved postprandial metabolomics data, and provides a compact but a comprehensive summary of the postprandial data revealing replicable and interpretable dynamic markers crucial to advance our understanding of changes in the metabolism in response to a meal challenge.

Phosphoproteomics analysis of serum from dogs affected with pulmonary hypertension secondary to degenerative mitral valve disease

Pulmonary hypertension (PH), a common complication in dogs affected by degenerative mitral valve disease (DMVD), is a progressive disorder characterized by increased pulmonary arterial pressure (PAP) and pulmonary vascular remodeling. Phosphorylation of proteins, impacting vascular function and cell proliferation, might play a role in the development and progression of PH. Unlike gene or protein studies, phosphoproteomic focuses on active proteins that function as end-target proteins within signaling cascades. Studying phosphorylated proteins can reveal active contributors to PH development. Early diagnosis of PH is crucial for effective management and improved clinical outcomes. This study aimed to identify potential serum biomarkers for diagnosing PH in dogs affected with DMVD using a phosphoproteomic approach. Serum samples were collected from healthy control dogs (n = 28), dogs with DMVD (n = 24), and dogs with DMVD and PH (n = 29). Phosphoproteins were enriched from the serum samples and analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Data analysis was performed to identify uniquely expressed phosphoproteins in each group and differentially expressed phosphoproteins among groups. Phosphoproteomic analysis revealed nine uniquely expressed phosphoproteins in the serum of dogs in the DMVD+PH group and 15 differentially upregulated phosphoproteins in the DMVD+PH group compared to the DMVD group. The phosphoproteins previously implicated in PH and associated with pulmonary arterial remodeling, including small nuclear ribonucleoprotein G (SNRPG), alpha-2-macroglobulin (A2M), zinc finger and BTB domain containing 42 (ZBTB42), hemopexin (HPX), serotransferrin (TRF) and complement C3 (C3), were focused on. Their unique expression and differential upregulation in the serum of DMVD dogs with PH suggest their potential as biomarkers for PH diagnosis. In conclusion, this phosphoproteomic study identified uniquely expressed and differentially upregulated phosphoproteins in the serum of DMVD dogs with PH. Further studies are warranted to validate the diagnostic utility of these phosphoproteins.

Proteomic analysis of the serum in dogs with pulmonary hypertension secondary to myxomatous mitral valve disease: the preliminary study

Background

Pulmonary hypertension (PH) is a common complication in dogs with myxomatous mitral valve disease (MMVD), characterized by elevated blood pressure in pulmonary artery. Echocardiography is a reliable technique for PH diagnosis in veterinary medicine. However, it is limited to use as an early detection method. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has found extensive application in the discovery of serum protein biomarkers for various diseases. The objective of this study was to identify serum proteins in healthy control dogs and MMVD dogs both with and without PH using LC-MS/MS.

Materials and methods

In this research, a total of 81 small-breed dogs participated, and they were categorized into three groups: the control (n = 28), MMVD (n = 24) and MMVD+PH (n = 29) groups. Serum samples were collected and analyzed by LC-MS/MS.

Results

Differentially expressed proteins were identified, and the upregulated and downregulated proteins in MMVD+PH group including Myomesin 1 (MYOM1) and Histone deacetylase 7 (HDAC7), Pleckstrin homology domain containing M3 (PLEKHM3), Diacylglycerol lipase alpha (DAGLA) and Tubulin tyrosine ligase like 6 (TTLL6) were selected as proteins of interest in MMVD dogs with PH.

Conclusion

Different types of proteins have been identified in healthy dogs and MMVD dogs with and without PH. Additional studies are needed to investigate the potential of these proteins as biomarkers for PH in dogs with MMVD.

Analyzing postprandial metabolomics data using multiway models: a simulation study

BACKGROUND

Analysis of time-resolved postprandial metabolomics data can improve the understanding of metabolic mechanisms, potentially revealing biomarkers for early diagnosis of metabolic diseases and advancing precision nutrition and medicine. Postprandial metabolomics measurements at several time points from multiple subjects can be arranged as a subjects by metabolites by time points array. Traditional analysis methods are limited in terms of revealing subject groups, related metabolites, and temporal patterns simultaneously from such three-way data.

RESULTS

We introduce an unsupervised multiway analysis approach based on the CANDECOMP/PARAFAC (CP) model for improved analysis of postprandial metabolomics data guided by a simulation study. Because of the lack of ground truth in real data, we generate simulated data using a comprehensive human metabolic model. This allows us to assess the performance of CP models in terms of revealing subject groups and underlying metabolic processes. We study three analysis approaches: analysis of fasting-state data using principal component analysis, T0-corrected data (i.e., data corrected by subtracting fasting-state data) using a CP model and full-dynamic (i.e., full postprandial) data using CP. Through extensive simulations, we demonstrate that CP models capture meaningful and stable patterns from simulated meal challenge data, revealing underlying mechanisms and differences between diseased versus healthy groups.

CONCLUSIONS

Our experiments show that it is crucial to analyze both fasting-state and T0-corrected data for understanding metabolic differences among subject groups. Depending on the nature of the subject group structure, the best group separation may be achieved by CP models of T0-corrected or full-dynamic data. This study introduces an improved analysis approach for postprandial metabolomics data while also shedding light on the debate about correcting baseline values in longitudinal data analysis.

Proteomic and Metabolomic Signatures of Diet Quality in Young Adults

The assessment of "omics" signatures may contribute to personalized medicine and precision nutrition. However, the existing literature is still limited in the homogeneity of participants' characteristics and in limited assessments of integrated omics layers. Our objective was to use post-prandial metabolomics and fasting proteomics to identify biological pathways and functions associated with diet quality in a population of primarily Hispanic young adults. We conducted protein and metabolite-wide association studies and functional pathway analyses to assess the relationships between a priori diet indices, Healthy Eating Index-2015 (HEI) and Dietary Approaches to Stop Hypertension (DASH) diets, and proteins (n = 346) and untargeted metabolites (n = 23,173), using data from the MetaAIR study (n = 154, 61% Hispanic). Analyses were performed for each diet quality index separately, adjusting for demographics and BMI. Five proteins (ACY1, ADH4, AGXT, GSTA1, F7) and six metabolites (undecylenic acid, betaine, hyodeoxycholic acid, stearidonic acid, iprovalicarb, pyracarbolid) were associated with both diets (p < 0.05), though none were significant after adjustment for multiple comparisons. Overlapping proteins are involved in lipid and amino acid metabolism and in hemostasis, while overlapping metabolites include amino acid derivatives, bile acids, fatty acids, and pesticides. Enriched biological pathways were involved in macronutrient metabolism, immune function, and oxidative stress. These findings in young Hispanic adults contribute to efforts to develop precision nutrition and medicine for diverse populations.

Phenotypic flexibility in nutrition research to quantify human variability: building the bridge to personalised nutrition

Phenotypic flexibility is a methodology that accurately assesses health in terms of mechanistic understanding of the interrelationship of multiple metabolic and physiological processes. This starts from the perspective that a healthy person is better able to cope with changes in environmental stressors that affect homeostasis compared to people with a compromised health state. The term 'phenotypic flexibility' expresses the cumulative ability of overarching physiological processes to return to homeostatic levels after short-term perturbations. The concept of phenotypic flexibility to define biomarkers for nutrition-related health was introduced in 2009 in the area of health optimisation and prevention and delay of non-communicable disease. The core approach consists of the combination of imposing a challenge test to the body followed by time-resolved analysis of multiple biomarkers. This new approach may better facilitate nutritional health research in intervention studies since it may show effects on early derailed physiological markers and the biomarker response can be extended by perturbing the system, thereby making them more sensitive in detecting health effects from food and nutrition. At the same time, interindividual variation can also be extended and compressed by challenge tests, facilitating the bridge to personalised nutrition. This review will overview where the science is in this research arena and what the phenotypic flexibility potential is for the nutrition field.

The effects of fatty acid-based dietary interventions on circulating bioactive lipid levels as intermediate biomarkers of health, cardiovascular disease, and cardiovascular disease risk factors: a systematic review and meta-analysis of randomized clinical trials

CONTEXT

Dietary fatty acids (FAs), primarily n-3 polyunsaturated FAs, have been associated with enrichment of the circulating bioactive lipidome and changes in the enzymatic precursor lipoprotein-associated phospholipase A2 (Lp-PLA2) mass; however, the magnitude of this effect remains unclear.

OBJECTIVE

The aim of this systematic review and meta-analysis was to evaluate the effect of different dietary FAs on the bioactive lipid profile of healthy participants and those with cardiovascular disease (CVD) and CVD risk factors.

DATA SOURCES

PubMed, SCOPUS and the Cochrane Library databases were searched for relevant articles published between October 2010 and May 2022.

DATA EXTRACTION

Data were screened for relevance and then retrieved in full and evaluated for eligibility by 2 reviewers independently.

DATA ANALYSIS

The net difference in the bioactive lipid mean values between the endpoint and the baseline, and the corresponding SDs or SEs, were used for the qualitative synthesis. For the meta-analysis, a fixed-effects model was used.

RESULTS

Twenty-seven randomized clinical trials (representing >2560 participants) were included. Over 78% of the enrolled participants had ≥1 associated CVD risk factor, whereas <22% were healthy. In the meta-analysis, marine n-3 supplements (dose range, 0.37-1.9 g/d) significantly increased pro-inflammatory lysophosphatidylcholines (lyso-PCs; for lyso-PC(16:0): mean, +0.52 [95% confidence interval (CI), 0.02-1.01] µM; for lyso-PC(18:0): mean, +0.58 [95%CI, 0.09-1.08] µM) in obese participants. Additionally, n-3 supplementation (1-5.56 g/d) decreased plasma Lp-PLA2 mass, a well-known inflammation marker, in healthy (-0.35 [95%CI, -0.59 to -0.10] ng/mL), dyslipidemic (-0.36 [95%CI, -0.47 to -0.25] ng/mL), and stable coronary artery disease participants (-0.52 [95%CI, -0.91 to -0.12] ng/mL).

CONCLUSIONS

Daily n-3 provided as EPA+DHA supplements and consumed from 1 to 6 months reduced plasma Lp-PLA2 mass in healthy participants and those with CVD and CVD risk factors, suggesting an anti-inflammatory effect. However, the saturated lyso-PC response to n-3 was impaired in obese participants.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration no. CRD42021218335.

Extensive Summary of the Important Roles of Indole Propionic Acid, a Gut Microbial Metabolite in Host Health and Disease

Increasing evidence suggests that metabolites produced by the gut microbiota play a crucial role in host-microbe interactions. Dietary tryptophan ingested by the host enters the gut, where indole-like metabolites such as indole propionic acid (IPA) are produced under deamination by commensal bacteria. Here, we summarize the IPA-producing bacteria, dietary patterns on IPA content, and functional roles of IPA in various diseases. IPA can not only stimulate the expression of tight junction (TJ) proteins to enhance gut barrier function and inhibit the penetration of toxic factors, but also modulate the immune system to exert anti-inflammatory and antioxidant effects to synergistically regulate body physiology. Moreover, IPA can act on target organs through blood circulation to form the gut-organ axis, which helps maintain systemic homeostasis. IPA shows great potential for the diagnosis and treatment of various clinical diseases, such as NAFLD, Alzheimer's disease, and breast cancer. However, the therapeutic effect of IPA depends on dose, target organ, or time. In future studies, further work should be performed to explore the effects and mechanisms of IPA on host health and disease to further improve the existing treatment program.

UPLC‐MS‐based plasma metabolomics for identifying energy metabolism biomarkers of maintenance in growing pigs

The purpose of this study is to explore the potential plasma metabolism biomarkers reflecting the maintenance status of growing pigs. The repeated measurement design was used in this experiment, and six barrows (28.6 ± 0.5 kg BW) were selected and kept in metabolism crates. The feeding level in growing pigs close to ad libitum was 2400 kJ ME/kg BW^0.6 ·day^-1 during Day 1 to Day 7, while a feeding level of 782 kJ ME/kg BW^0.6 ·day^-1 was provided as energy requirement for maintenance during Day 8 to Day 14. Plasma samples of each pig were collected from the anterior vena cava on the morning of Day 8 and Day 15. The metabolites of plasma were determined by high-resolution mass spectrometry using a metabolomics approach. Results showed that metabolomics analysis between ad libitum-fed state and maintained status revealed differences in 16 compounds. Identified compounds were enriched in metabolic pathways related to linoleic acid metabolism, tryptophan metabolism, and alanine, aspartate and glutamate metabolism. In conclusion, linoleic acid metabolism, tryptophan metabolism, alanine, aspartate and glutamic acid metabolism pathways played a major regulatory role in the maintenance status of growing pigs. The potential metabolism biomarkers of maintenance in growing pigs were linoleic acid, glutamine and tyrosine.

Serum and Urine Metabolites in Healthy Men after Consumption of Acidified Milk and Yogurt

The identification of molecular biomarkers that can be used to quantitatively link dietary intake to phenotypic traits in humans is a key theme in modern nutritional research. Although dairy products (with and without fermentation) represent a major food group, the identification of markers of their intake lags behind that of other food groups. Here, we report the results from an analysis of the metabolites in postprandial serum and urine samples from a randomized crossover study with 14 healthy men who ingested acidified milk, yogurt, and a non-dairy meal. Our study confirms the potential of lactose and its metabolites as markers of lactose-containing dairy foods and the dependence of their combined profiles on the fermentation status of the consumed products. Furthermore, indole-3-lactic acid and 3-phenyllactic acid are two products of fermentation whose postprandial behaviour strongly discriminates yogurt from milk intake. Our study also provides evidence of the ability of milk fermentation to increase the acute delivery of free amino acids to humans. Notably, 3,5-dimethyloctan-2-one also proves to be a specific marker for milk and yogurt consumption, as well as for cheese consumption (previously published data). These molecules deserve future characterisation in human interventional and observational studies.

Indolepropionic Acid, a Gut Bacteria-Produced Tryptophan Metabolite and the Risk of Type 2 Diabetes and Non-Alcoholic Fatty Liver Disease

An intricate relationship between gut microbiota, diet, and the human body has recently been extensively investigated. Gut microbiota and gut-derived metabolites, especially, tryptophan derivatives, modulate metabolic and immune functions in health and disease. One of the tryptophan derivatives, indolepropionic acid (IPA), is increasingly being studied as a marker for the onset and development of metabolic disorders, including type 2 diabetes (T2D) and non-alcoholic fatty liver disease (NAFLD). The IPA levels heavily depend on the diet, particularly dietary fiber, and show huge variations among individuals. We suggest that these variations could partially be explained using genetic variants known to be associated with specific diseases such as T2D. In this narrative review, we elaborate on the beneficial effects of IPA in the mitigation of T2D and NAFLD, and further study the putative interactions between IPA and well-known genetic variants (TCF7L2, FTO, and PPARG), known to be associated with the risk of T2D. We have investigated the long-term preventive value of IPA in the development of T2D in the Finnish prediabetic population and the correlation of IPA with phytosterols in obese individuals from an ongoing Kuopio obesity surgery study. The diversity in IPA-linked mechanisms affecting glucose metabolism and liver fibrosis makes it a unique small metabolite and a promising candidate for the reversal or management of metabolic disorders, mainly T2D and NAFLD.

Combining Feature-Based Molecular Networking and Contextual Mass Spectral Libraries to Decipher Nutrimetabolomics Profiles

Untargeted metabolomics approaches deal with complex data hindering structural information for the comprehensive analysis of unknown metabolite features. We investigated the metabolite discovery capacity and the possible extension of the annotation coverage of the Feature-Based Molecular Networking (FBMN) approach by adding two novel nutritionally-relevant (contextual) mass spectral libraries to the existing public ones, as compared to widely-used open-source annotation protocols. Two contextual mass spectral libraries in positive and negative ionization mode of ~300 reference molecules relevant for plant-based nutrikinetic studies were created and made publicly available through the GNPS platform. The postprandial urinary metabolome analysis within the intervention of Vaccinium supplements was selected as a case study. Following the FBMN approach in combination with the added contextual mass spectral libraries, 67 berry-related and human endogenous metabolites were annotated, achieving a structural annotation coverage comparable to or higher than existing non-commercial annotation workflows. To further exploit the quantitative data obtained within the FBMN environment, the postprandial behavior of the annotated metabolites was analyzed with Pearson product-moment correlation. This simple chemometric tool linked several molecular families with phase II and phase I metabolism. The proposed approach is a powerful strategy to employ in longitudinal studies since it reduces the unknown chemical space by boosting the annotation power to characterize biochemically relevant metabolites in human biofluids.

Holistic Integration of Omics Tools for Precision Nutrition in Health and Disease

The combination of multiple omics approaches has emerged as an innovative holistic scope to provide a more comprehensive view of the molecular and physiological events underlying human diseases (including obesity, dyslipidemias, fatty liver, insulin resistance, and inflammation), as well as for elucidating unique and specific metabolic phenotypes. These omics technologies include genomics (polymorphisms and other structural genetic variants), epigenomics (DNA methylation, histone modifications, long non-coding RNA, telomere length), metagenomics (gut microbiota composition, enterotypes), transcriptomics (RNA expression patterns), proteomics (protein quantities), and metabolomics (metabolite profiles), as well as interactions with dietary/nutritional factors. Although more evidence is still necessary, it is expected that the incorporation of integrative omics could be useful not only for risk prediction and early diagnosis but also for guiding tailored dietary treatments and prognosis schemes. Some challenges include ethical and regulatory issues, the lack of robust and reproducible results due to methodological aspects, the high cost of omics methodologies, and high-dimensional data analyses and interpretation. In this review, we provide examples of system biology studies using multi-omics methodologies to unravel novel insights into the mechanisms and pathways connecting the genotype to clinically relevant traits and therapy outcomes for precision nutrition applications in health and disease.

Dynamic patterns of postprandial metabolic responses to three dietary challenges

Food intake triggers extensive changes in the blood metabolome. The kinetics of these changes depend on meal composition and on intrinsic, health-related characteristics of each individual, making the assessment of changes in the postprandial metabolome an opportunity to assess someone's metabolic status. To enable the usage of dietary challenges as diagnostic tools, profound knowledge about changes that occur in the postprandial period in healthy individuals is needed. In this study, we characterize the time-resolved changes in plasma levels of 634 metabolites in response to an oral glucose tolerance test (OGTT), an oral lipid tolerance test (OLTT), and a mixed meal (SLD) in healthy young males (n = 15). Metabolite levels for samples taken at different time points (20 per individual) during the challenges were available from targeted (132 metabolites) and non-targeted (502 metabolites) metabolomics. Almost half of the profiled metabolites (n = 308) showed a significant change in at least one challenge, thereof 111 metabolites responded exclusively to one particular challenge. Examples include azelate, which is linked to ω-oxidation and increased only in OLTT, and a fibrinogen cleavage peptide that has been linked to a higher risk of cardiovascular events in diabetes patients and increased only in OGTT, making its postprandial dynamics a potential target for risk management. A pool of 89 metabolites changed their plasma levels during all three challenges and represents the core postprandial response to food intake regardless of macronutrient composition. We used fuzzy c-means clustering to group these metabolites into eight clusters based on commonalities of their dynamic response patterns, with each cluster following one of four primary response patterns: (i) “decrease-increase” (valley-like) with fatty acids and acylcarnitines indicating the suppression of lipolysis, (ii) “increase-decrease” (mountain-like) including a cluster of conjugated bile acids and the glucose/insulin cluster, (iii) “steady decrease” with metabolites reflecting a carryover from meals prior to the study, and (iv) “mixed” decreasing after the glucose challenge and increasing otherwise. Despite the small number of subjects, the diversity of the challenges and the wealth of metabolomic data make this study an important step toward the characterization of postprandial responses and the identification of markers of metabolic processes regulated by food intake.

Breath response following a nutritional challenge monitored by secondary electrospray ionization high-resolution mass spectrometry

On-line breath analysis using secondary electrospray ionization coupled to high-resolution mass spectrometry (SESI-HRMS) is a sensitive method for biomarker discovery. The strengths of this technology have already been demonstrated in the clinical environment. For the first time, this study demonstrates the application of SESI-HRMS in the field of nutritional science using a standardized nutritional intervention, consisting of a high-energy shake (950 kcal, 8% protein, 35% sugar and 57% fat). Eleven subjects underwent the intervention on three separate days and their exhaled breath was monitored up to six hours postprandially. In addition, sampling was performed during equivalent fasting conditions for selected subjects. To estimate the impact of inter- and intra-individual variability, analysis of variance simultaneous component analysis (ASCA) was conducted, revealing that the inter-individual variability accounted for 30 % of the data variation. To distinguish the effect of the intervention from fasting conditions, partial least squares discriminant analysis was performed. Candidate compound annotation was performed with pathway analysis and collision-induced dissociation (CID) experiments. Pathway analysis highlighted, among others, features associated with the metabolism of linoleate, butanoate and amino sugars. Tentative compounds annotated through CID measurements include fatty acids, amino acids, and amino acid derivatives, some of them likely derived from nutrients by the gut microbiome (e.g. propanoate, indoles), as well as organic acids from the Krebs cycle. Time-series clustering showed an overlap of observed kinetic trends with those reported previously in blood plasma.

Assessing Insulin Sensitivity and Postprandial Triglyceridemic Response Phenotypes With a Mixed Macronutrient Tolerance Test

The use of meal challenge tests to assess postprandial responses in carbohydrate and fat metabolism is well established in clinical nutrition research. However, challenge meal compositions and protocols remain a variable. Here, we validated a mixed macronutrient tolerance test (MMTT), containing 56-g palm oil, 59-g sucrose, and 26-g egg white protein for the parallel determination of insulin sensitivity and postprandial triglyceridemia in clinically healthy subjects. The MMTT was administered in two study populations. In one, women with overweight/obese BMIs (n = 43) involved in an 8-week dietary intervention were administered oral glucose tolerance tests (OGTTs) and MMTTs within 2 days of each other after 0, 2, and 8 weeks of the dietary intervention. In the other, 340 men and women between 18 and 64 years of age, with BMI from 18–40 kg/m2, completed the MMTT as part of a broad nutritional phenotyping effort. Postprandial blood collected at 0, 0.5, 3, and 6 h was used to measure glucose, insulin, and clinical lipid panels. The MMTT postprandial insulin-dependent glucose disposal was evaluated by using the Matsuda Index algorithm and the 0- and 3 h blood insulin and glucose measures. The resulting MMTT insulin sensitivity index (ISIMMTT) was strongly correlated (r = 0.77, p &lt; 0.001) with the OGTT-dependent 2 h composite Matsuda index (ISIComposite), being related by the following equation: Log (ISIComposite) = [0.8751 x Log(ISIMMTT)] –0.2115. An area under the triglyceride excursion curve &gt;11.15 mg/mL h–1 calculated from the 0, 3, and 6 h blood draws established mild-to-moderate triglyceridemia in agreement with ∼20% greater prevalence of hypertriglyceridemia than fasting indications. We also demonstrated that the product of the 0 to 3 h and 3 to 6 h triglyceride rate of change as a function of the triglyceride incremental area under the curve optimally stratified subjects by postprandial response patterns. Notably, ∼2% of the population showed minimal triglyceride appearance by 6 h, while ∼25% had increasing triglycerides through 6 h. Ultimately, using three blood draws, the MMTT allowed for the simultaneous determination of insulin sensitivity and postprandial triglyceridemia in individuals without clinically diagnosed disease.

Clinical Trial Registration

[https://clinicaltrials.gov/], identifier [NCT02298725; NCT02367287].

Investigating the Postprandial Metabolome after Challenge Tests to Assess Metabolic Flexibility and Dysregulations Associated with Cardiometabolic Diseases

This review focuses on the added value provided by a research strategy applying metabolomics analyses to assess phenotypic flexibility in response to different nutritional challenge tests in the framework of metabolic clinical studies. We discuss findings related to the Oral Glucose Tolerance Test (OGTT) and to mixed meals with varying fat contents and food matrix complexities. Overall, the use of challenge tests combined with metabolomics revealed subtle metabolic dysregulations exacerbated during the postprandial period when comparing healthy and at cardiometabolic risk subjects. In healthy subjects, consistent postprandial metabolic shifts driven by insulin action were reported (e.g., a switch from lipid to glucose oxidation for energy fueling) with similarities between OGTT and mixed meals, especially during the first hours following meal ingestion while differences appeared in a wider timeframe. In populations with expected reduced phenotypic flexibility, often associated with increased cardiometabolic risk, a blunted response on most key postprandial pathways was reported. We also discuss the most suitable statistical tools to analyze the dynamic alterations of the postprandial metabolome while accounting for complexity in study designs and data structure. Overall, the in-depth characterization of the postprandial metabolism and associated phenotypic flexibility appears highly promising for a better understanding of the onset of cardiometabolic diseases.

Exploring dynamic metabolomics data with multiway data analysis: a simulation study

BACKGROUND

Analysis of dynamic metabolomics data holds the promise to improve our understanding of underlying mechanisms in metabolism. For example, it may detect changes in metabolism due to the onset of a disease. Dynamic or time-resolved metabolomics data can be arranged as a three-way array with entries organized according to a subjects mode, a metabolites mode and a time mode. While such time-evolving multiway data sets are increasingly collected, revealing the underlying mechanisms and their dynamics from such data remains challenging. For such data, one of the complexities is the presence of a superposition of several sources of variation: induced variation (due to experimental conditions or inborn errors), individual variation, and measurement error. Multiway data analysis (also known as tensor factorizations) has been successfully used in data mining to find the underlying patterns in multiway data. To explore the performance of multiway data analysis methods in terms of revealing the underlying mechanisms in dynamic metabolomics data, simulated data with known ground truth can be studied.

RESULTS

We focus on simulated data arising from different dynamic models of increasing complexity, i.e., a simple linear system, a yeast glycolysis model, and a human cholesterol model. We generate data with induced variation as well as individual variation. Systematic experiments are performed to demonstrate the advantages and limitations of multiway data analysis in analyzing such dynamic metabolomics data and their capacity to disentangle the different sources of variations. We choose to use simulations since we want to understand the capability of multiway data analysis methods which is facilitated by knowing the ground truth.

CONCLUSION

Our numerical experiments demonstrate that despite the increasing complexity of the studied dynamic metabolic models, tensor factorization methods CANDECOMP/PARAFAC(CP) and Parallel Profiles with Linear Dependences (Paralind) can disentangle the sources of variations and thereby reveal the underlying mechanisms and their dynamics.

The relationship between hair metabolites, air pollution exposure and gestational diabetes mellitus: A longitudinal study from pre-conception to third trimester

BACKGROUND

Gestational diabetes mellitus (GDM) is a metabolic condition defined as glucose intolerance with first presentation during pregnancy. Many studies suggest that environmental exposures, including air pollution, contribute to the pathogenesis of GDM. Although hair metabolite profiles have been shown to reflect pollution exposure, few studies have examined the link between environmental exposures, the maternal hair metabolome and GDM. The aim of this study was to investigate the longitudinal relationship (from pre-conception through to the third trimester) between air pollution exposure, the hair metabolome and GDM in a Chinese cohort.

METHODS

A total of 1020 women enrolled in the Complex Lipids in Mothers and Babies (CLIMB) birth cohort were included in our study. Metabolites from maternal hair segments collected pre-conception, and in the first, second, and third trimesters were analysed using gas chromatography-mass spectrometry (GC-MS). Maternal exposure to air pollution was estimated by two methods, namely proximal and land use regression (LUR) models, using air quality data from the air quality monitoring station nearest to the participant's home. Logistic regression and mixed models were applied to investigate associations between the air pollution exposure data and the GDM associated metabolites.

RESULTS

Of the 276 hair metabolites identified, the concentrations of fourteen were significantly different between GDM cases and non-GDM controls, including some amino acids and their derivatives, fatty acids, organic acids, and exogenous compounds. Three of the metabolites found in significantly lower concentrations in the hair of women with GDM (2-hydroxybutyric acid, citramalic acid, and myristic acid) were also negatively associated with daily average concentrations of PM_2.5, PM₁₀, SO₂, NO₂, CO and the exposure estimates of PM_2.5 and NO_2, and positively associated with O₃.

CONCLUSIONS

This study demonstrated that the maternal hair metabolome reflects the longitudinal metabolic changes that occur in response to environmental exposures and the development of GDM.

Biological and Clinical Factors Contributing to the Metabolic Heterogeneity of Hospitalized Patients with and without COVID-19

The Corona Virus Disease 2019 (COVID-19) pandemic represents an ongoing worldwide challenge. The present large study sought to understand independent and overlapping metabolic features of samples from acutely ill patients (n = 831) that tested positive (n = 543) or negative (n = 288) for COVID-19. High-throughput metabolomics analyses were complemented with antigen and enzymatic activity assays on plasma from acutely ill patients collected while in the emergency department, at admission, or during hospitalization. Lipidomics analyses were also performed on COVID-19-positive or -negative subjects with the lowest and highest body mass index (n = 60/group). Significant changes in amino acid and fatty acid/acylcarnitine metabolism emerged as highly relevant markers of disease severity, progression, and prognosis as a function of biological and clinical variables in these patients. Further, machine learning models were trained by entering all metabolomics and clinical data from half of the COVID-19 patient cohort and then tested on the other half, yielding ~78% prediction accuracy. Finally, the extensive amount of information accumulated in this large, prospective, observational study provides a foundation for mechanistic follow-up studies and data sharing opportunities, which will advance our understanding of the characteristics of the plasma metabolism in COVID-19 and other acute critical illnesses.

Tutorial: best practices and considerations for mass-spectrometry-based protein biomarker discovery and validation

Mass-spectrometry-based proteomic analysis is a powerful approach for discovering new disease biomarkers. However, certain critical steps of study design such as cohort selection, evaluation of statistical power, sample blinding and randomization, and sample/data quality control are often neglected or underappreciated during experimental design and execution. This tutorial discusses important steps for designing and implementing a liquid-chromatography-mass-spectrometry-based biomarker discovery study. We describe the rationale, considerations and possible failures in each step of such studies, including experimental design, sample collection and processing, and data collection. We also provide guidance for major steps of data processing and final statistical analysis for meaningful biological interpretations along with highlights of several successful biomarker studies. The provided guidelines from study design to implementation to data interpretation serve as a reference for improving rigor and reproducibility of biomarker development studies.

Advantages of Studying the Metabolome in Response to Mixed-Macronutrient Challenges and Suggestions for Future Research Designs

Evaluating the postprandial response to a dietary challenge containing all macronutrients-carbohydrates, lipids, and protein-may provide stronger insights of metabolic health than a fasted measurement. Metabolomic profiling deepens the understanding of the homeostatic and adaptive response to a dietary challenge by classifying multiple metabolic pathways and biomarkers. A total of 26 articles were identified that measure the human blood metabolome or lipidome response to a mixed-macronutrient challenge. Most studies were cross-sectional, exploring the baseline and postprandial response to the dietary challenge. Large variations in study designs were reported, including the macronutrient and caloric composition of the challenge and the delivery of the challenge as a liquid shake or a solid meal. Most studies utilized a targeted metabolomics platform, assessing only a particular metabolic pathway, however, several studies utilized global metabolomics and lipidomics assays demonstrating the expansive postprandial response of the metabolome. The postprandial response of individual amino acids was largely dependent on the amino acid composition of the test meal, with the exception of alanine and proline, 2 nonessential amino acids. Long-chain fatty acids and unsaturated long-chain acylcarnitines rapidly decreased in response to the dietary challenges, representing the switch from fat to carbohydrate oxidation. Studies were reviewed that assessed the metabolome response in the context of obesity and metabolic diseases, providing insight on how weight status and disease influence the ability to cope with a nutrient load and return to homeostasis. Results demonstrate that the flexibility to respond to a substrate load is influenced by obesity and metabolic disease and flexibility alterations will be evident in downstream metabolites of fat, carbohydrate, and protein metabolism. In response, we propose suggestions for standardization between studies with the potential of creating a study exploring the postprandial response to a multitude of challenges with a variety of macronutrients.

Serum Metabolites Responding in a Dose-Dependent Manner to the Intake of a High-Fat Meal in Normal Weight Healthy Men Are Associated with Obesity

Although the composition of the human blood metabolome is influenced both by the health status of the organism and its dietary behavior, the interaction between these two factors has been poorly characterized. This study makes use of a previously published randomized controlled crossover acute intervention to investigate whether the blood metabolome of 15 healthy normal weight (NW) and 17 obese (OB) men having ingested three doses (500, 1000, 1500 kcal) of a high-fat (HF) meal can be used to identify metabolites differentiating these two groups. Among the 1024 features showing a postprandial response, measured between 0 h and 6 h, in the NW group, 135 were dose-dependent. Among these 135 features, 52 had fasting values that were significantly different between NW and OB men, and, strikingly, they were all significantly higher in OB men. A subset of the 52 features was identified as amino acids (e.g., branched-chain amino acids) and amino acid derivatives. As the fasting concentration of most of these metabolites has already been associated with metabolic dysfunction, we propose that challenging normal weight healthy subjects with increasing caloric doses of test meals might allow for the identification of new fasting markers associated with obesity.

Nutrigenomics: lessons learned and future perspectives

The omics technologies of metabolomics, transcriptomics, proteomics, and metagenomics are playing an increasingly important role in nutrition science. With the emergence of the concept of precision nutrition and the need to understand individual responses to dietary interventions, it is an opportune time to examine the impact of these tools to date in human nutrition studies. Advances in our mechanistic understanding of dietary interventions were realized through incorporation of metabolomics, proteomics, and, more recently, metagenomics. A common observation across the studies was the low intra-individual variability of the omics measurements and the high inter-individual variation. Harnessing this data for use in the development of precision nutrition will be important. Metabolomics in particular has played a key role in the development of biomarkers of food intake in an effort to enhance the accuracy of dietary assessments. Further work is needed to realize the full potential of such biomarkers and to demonstrate integration with current strategies, with the goal of overcoming the well-established limitations of self-reported approaches. Although many of the nutrigenomic studies performed to date were labelled as proof-of-concept or pilot studies, there is ample evidence to support the use of these technologies in nutrition science. Incorporating omic technologies from the start of study designs will ensure that studies are sufficiently powered for such data. Furthermore, multi-disciplinary collaborations are likely to become even more important to aid analyses and interpretation of the data.

Deciphering the Plasma Proteome of Type 2 Diabetes

With an estimated prevalence of 463 million affected, type 2 diabetes represents a major challenge to health care systems worldwide. Analyzing the plasma proteomes of individuals with type 2 diabetes may illuminate hitherto unknown functional mechanisms underlying disease pathology. We assessed the associations between type 2 diabetes and >1,000 plasma proteins in the Cooperative Health Research in the Region of Augsburg (KORA) F4 cohort (n = 993, 110 cases), with subsequent replication in the third wave of the Nord-Trøndelag Health Study (HUNT3) cohort (n = 940, 149 cases). We computed logistic regression models adjusted for age, sex, BMI, smoking status, and hypertension. Additionally, we investigated associations with incident type 2 diabetes and performed two-sample bidirectional Mendelian randomization (MR) analysis to prioritize our results. Association analysis of prevalent type 2 diabetes revealed 24 replicated proteins, of which 8 are novel. Proteins showing association with incident type 2 diabetes were aminoacylase-1, growth hormone receptor, and insulin-like growth factor-binding protein 2. Aminoacylase-1 was associated with both prevalent and incident type 2 diabetes. MR analysis yielded nominally significant causal effects of type 2 diabetes on cathepsin Z and rennin, both known to have roles in the pathophysiological pathways of cardiovascular disease, and of sex hormone-binding globulin on type 2 diabetes. In conclusion, our high-throughput proteomics study replicated previously reported type 2 diabetes-protein associations and identified new candidate proteins possibly involved in the pathogenesis of type 2 diabetes.

Next Generation Health Claims Based on Resilience: The Example of Whole-Grain Wheat

Health claims on foods are a way of informing consumers about the health benefits of a food product. Traditionally, these claims are based on scientific evaluation of markers originating from a pharmacological view on health. About a decade ago, the definition of health has been rephrased to 'the ability to adapt' that opened up the possibility for a next generation of health claims based on a new way of quantifying health by evaluating resilience. Here, we would like to introduce an opportunity for future scientific substantiation of health claims on food products by using whole-grain wheat as an example. Characterization of the individual whole wheat grain food product or whole wheat flour would probably be considered as sufficiently characterized by the European Food Safety Authority, while the food category whole grain is not specific enough. Meta-analysis provides the scientific evidence that long-term whole-grain wheat consumption is beneficial for health, although results from single 'gold standard' efficacy studies are not always straight forward based on classic measurement methods. Future studies may want to underpin the scientific argumentation that long-term whole grain wheat consumption improves resilience, by evaluating the disruption and rate of a selected panel of blood markers in response to a standardized oral protein glucose lipid tolerance test and aggregated into biomarkers with substantiated physiological benefits, to make a next-generation health claim for whole-grain wheat achievable in the near future.

Time-restricted feeding alters lipid and amino acid metabolite rhythmicity without perturbing clock gene expression

Time-restricted feeding (TRF) improves metabolism independent of dietary macronutrient composition or energy restriction. To elucidate mechanisms underpinning the effects of short-term TRF, we investigated skeletal muscle and serum metabolic and transcriptomic profiles from 11 men with overweight/obesity after TRF (8 h day^-1) and extended feeding (EXF, 15 h day^-1) in a randomised cross-over design (trial registration: ACTRN12617000165381). Here we show that muscle core clock gene expression was similar after both interventions. TRF increases the amplitude of oscillating muscle transcripts, but not muscle or serum metabolites. In muscle, TRF induces rhythmicity of several amino acid transporter genes and metabolites. In serum, lipids are the largest class of periodic metabolites, while the majority of phase-shifted metabolites are amino acid related. In conclusion, short-term TRF in overweight men affects the rhythmicity of serum and muscle metabolites and regulates the rhythmicity of genes controlling amino acid transport, without perturbing core clock gene expression.

From lifespan to healthspan: the role of nutrition in healthy ageing

Across the globe, there has been a marked increase in longevity, but significant inequalities remain. These are exacerbated by inadequate access to proper nutrition and health care services and to reliable information to make the decisions related to nutrition and health care. Many in economically developing as well as developed societies are plagued with the double-burden of energy excess and undernutrition. This has resulted in mental and physical deterioration, increased non-communicable disease rates, lost productivity, increased medical costs and reduced quality of life. While adequate nutrition is fundamental to good health at all stages of the life course, the impact of diet on prolonging good quality of life during ageing remains unclear. For progress to continue, there is need for new and/or innovative approaches to promoting health as individuals age, as well as qualitative and quantitative biomarkers and other accepted tools that can measure improvements in physiological integrity throughout life. A framework for progress has been proposed by the World Health Organization in their Global Strategy and Action Plan on Ageing and Health. Here, we focused on the impact of nutrition within this framework, which takes a broad, person-centred emphasis on healthy ageing, stressing the need to better understand each individual's intrinsic capacity, their functional abilities at various life stages, and the impact of their mental, and physical health, as well as the environments they inhabit.

Postprandial NMR-Based Metabolic Exchanges Reflect Impaired Phenotypic Flexibility across Splanchnic Organs in the Obese Yucatan Mini-Pig

The postprandial period represents one of the most challenging phenomena in whole-body metabolism, and it can be used as a unique window to evaluate the phenotypic flexibility of an individual in response to a given meal, which can be done by measuring the resilience of the metabolome. However, this exploration of the metabolism has never been applied to the arteriovenous (AV) exploration of organs metabolism. Here, we applied an AV metabolomics strategy to evaluate the postprandial flexibility across the liver and the intestine of mini-pigs subjected to a high fat–high sucrose (HFHS) diet for 2 months. We identified for the first time a postprandial signature associated to the insulin resistance and obesity outcomes, and we showed that the splanchnic postprandial metabolome was considerably affected by the meal and the obesity condition. Most of the changes induced by obesity were observed in the exchanges across the liver, where the metabolism was reorganized to maintain whole body glucose homeostasis by routing glucose formed de novo from a large variety of substrates into glycogen. Furthermore, metabolites related to lipid handling and energy metabolism showed a blunted postprandial response in the obese animals across organs. Finally, some of our results reflect a loss of flexibility in response to the HFHS meal challenge in unsuspected metabolic pathways that must be further explored as potential new events involved in early obesity and the onset of insulin resistance.

Metabolic signatures associated with Western and Prudent dietary patterns in women

BACKGROUND

The Western dietary pattern (WD) is positively associated with risk of coronary artery disease (CAD) and cancer, whereas the Prudent dietary pattern (PD) may be protective. Foods may influence metabolite concentrations as well as oxidative stress and lipid dysregulation, biological mechanisms associated with CAD and cancer.

OBJECTIVE

The aim was to assess the association of 2 derived dietary pattern scores with serum metabolites and identify metabolic pathways associated with the metabolites.

METHODS

We evaluated the cross-sectional association between each dietary pattern (WD, PD) and metabolites in 2199 Women's Health Initiative (WHI) participants. With FFQ and factor analysis, we determined 2 dietary patterns consistent with WD and PD. Metabolites were measured with LC-tandem MS. Metabolite discovery among 904 WHI Observational Study (WHI-OS) participants was replicated among 1295 WHI Hormone Therapy Trial (WHI-HT) participants. We analyzed each of 495 metabolites with each dietary score (WD, PD) in linear regression models.

RESULTS

The PD included higher vegetables and fruit intake compared with the WD with higher saturated fat and meat intake. Independent of energy intake, BMI, physical activity, and other confounding variables, 45 overlapping metabolites were identified (WHI-OS) and replicated (WHI-HT) with an opposite direction of associations for the WD compared with the PD [false discovery rate (FDR) P < 0.05]. In metabolite set enrichment analyses, phosphatidylethanolamine (PE) plasmalogens were positively enriched for association with WD [normalized enrichment score (NES) = 2.01, P = 0.001, FDR P = 0.005], and cholesteryl esters (NES = -1.77, P = 0.005, FDR P = 0.02), and phosphatidylcholines (NES = -1.72, P = 0.01, P = 0.03) were negatively enriched for WD. PE plasmalogens were positively correlated with saturated fat and red meat. Phosphatidylcholines and cholesteryl esters were positively correlated with fatty fish.

CONCLUSIONS

Distinct metabolite signatures associated with Western and Prudent dietary patterns highlight the positive association of mitochondrial oxidative stress and lipid dysregulation with a WD and the inverse association with a PD.

Developing preliminary blood metabolomics-based biomarkers of insufficient sleep in humans

STUDY OBJECTIVE

Identify small molecule biomarkers of insufficient sleep using untargeted plasma metabolomics in humans undergoing experimental insufficient sleep.

METHODS

We conducted a crossover laboratory study where 16 normal-weight participants (eight men; age 22 ± 5 years; body mass index < 25 kg/m2) completed three baseline days (9 hours sleep opportunity per night) followed by 5-day insufficient (5 hours sleep opportunity per night) and adequate (9 hours sleep opportunity per night) sleep conditions. Energy balanced diets were provided during baseline, with ad libitum energy intake provided during the insufficient and adequate sleep conditions. Untargeted plasma metabolomics analyses were performed using blood samples collected every 4 hours across the final 24 hours of each condition. Biomarker models were developed using logistic regression and linear support vector machine (SVM) algorithms.

RESULTS

The top-performing biomarker model was developed by linear SVM modeling, consisted of 65 compounds, and discriminated insufficient versus adequate sleep with 74% overall accuracy and a Matthew's Correlation Coefficient of 0.39. The compounds in the top-performing biomarker model were associated with ATP Binding Cassette Transporters in Lipid Homeostasis, Phospholipid Metabolic Process, Plasma Lipoprotein Remodeling, and sphingolipid metabolism.

CONCLUSION

We identified potential metabolomics-based biomarkers of insufficient sleep in humans. Although our current biomarkers require further development and validation using independent cohorts, they have potential to advance our understanding of the negative consequences of insufficient sleep, improve diagnosis of poor sleep health, and could eventually help identify targets for countermeasures designed to mitigate the negative health consequences of insufficient sleep.

Potential Markers of Dietary Glycemic Exposures for Sustained Dietary Interventions in Populations without Diabetes

There is considerable interest in dietary and other approaches to maintaining blood glucose concentrations within the normal range and minimizing exposure to postprandial hyperglycemic excursions. The accepted marker to evaluate the sustained maintenance of normal blood glucose concentrations is glycated hemoglobin A1c (HbA1c). However, although this is used in clinical practice to monitor glycemic control in patients with diabetes, it has a number of drawbacks as a marker of efficacy of dietary interventions that might beneficially affect glycemic control in people without diabetes. Other markers that reflect shorter-term glycemic exposures have been studied and proposed, but consensus on the use and relevance of these markers is lacking. We have carried out a systematic search for studies that have tested the responsiveness of 6 possible alternatives to HbA1c as markers of sustained variation in glycemic exposures and thus their potential applicability for use in dietary intervention trials in subjects without diabetes: 1,5-anhydroglucitol (1,5-AG), dicarbonyl stress, fructosamine, glycated albumin (GA), advanced glycated end products (AGEs), and metabolomic profiles. The results suggest that GA may be the most promising for this purpose, but values may be confounded by effects of fat mass. 1,5-AG and fructosamine are probably not sensitive enough to the range of variation in glycemic exposures observed in healthy individuals. Use of measures based on dicarbonyls, AGEs, or metabolomic profiles would require further research into possible specific molecular species of interest. At present, none of the markers considered here is sufficiently validated and sensitive for routine use in substantiating the effects of sustained variation in dietary glycemic exposures in people without diabetes.

Characterization of Postprandial Effects on CSF Metabolomics: A Pilot Study with Parallel Comparison to Plasma

Cerebrospinal fluid (CSF) metabolites reflect biochemical diffusion/export from the brain and possibly serve as biomarkers related to brain disease severity, pathophysiology, and therapeutic efficacy/toxicity. Metabolomic studies using blood matrices have demonstrated interindividual and preanalytical variation of blood metabolites, whereas those of CSF metabolites remain unclear. In this study, we aimed to delineate the postprandial effects on CSF metabolites because fasting of patients with brain-related disorders is challenging. We collected pre- and postprandial (1.5, 3, and 6 h) plasma and CSF from nine healthy subjects. Using a mass-spectrometry-based global metabolomics approach, 150 and 130 hydrophilic metabolites and 263 and 340 lipids were detected in CSF and plasma, respectively. Principal component analysis of CSF hydrophilic metabolites and lipids primarily classified individual subjects at any time point, suggesting that the postprandial effects had a lower impact than interindividual variations on CSF metabolites. Individually, less than 10% of the CSF metabolites were putatively altered by postprandial effects (with either significant differences or over 2-fold changes, but not both) at any time point. Thus, global CSF metabolite levels are not directly associated with food intake, and except for several putatively altered CSF metabolites, postprandial effects are not a major concern when applying CSF metabolomics to screen biomarkers.

Metabo groups in response to micronutrient intervention: Pilot study

Micronutrients and their metabolites are cofactors in proteins involved in lipid metabolism. The present study was a subproject of the Harmonized Micronutrient Project (ClinTrials.gov # NCT01823744). Twenty participants were randomly selected from 136 children and adolescents that consumed a daily dose of 12 vitamins and 5 minerals supplementation for 6 weeks. The 20 individuals were divided into two pools of 10 individuals, according to their lipid profile at baseline (Pool 1 with lower triglycerides, LDL, and VLDL). The individuals were analyzed at baseline, after 6 weeks of daily supplementation, and after 6 weeks of a washout period in relation to anthropometric, body composition, food intake, lipid profile, micronutrient levels, and iTRAQ proteomic data. Genetic ancestry and its association with vitamin serum levels were also determined. After supplementation, LDL levels decreased while alpha-tocopherol and pantothenic acid levels increased in pool 2; lipid profiles in pool 1 did not change but had higher plasma levels of pantothenic acid, pyridoxal, and pyridoxic acid. In pool 2, expression of some proteins increased, and expression of other ones decreased after intervention, while in pool 1, the same proteins responded inversely or did not change their levels. Plasma alpha-tocopherol and Native American genetic ancestry explained a significant fraction of LDL plasma levels at baseline and in response to the intervention. After intervention, changes in expression of alpha-1 antitrypsin, haptoglobin, Ig alpha-1 chain C region, plasma protease C1 inhibitor, alpha-1-acid glycoprotein 1, fibrinogen alpha, beta, and gamma-chain in individuals in pool 2 may be associated with levels of LDL and vitamin E. Vitamin E and Native American genetic ancestry may also be implicated in changes of vitamin E and LDL levels. The results of this pilot study must be validated in future studies with larger sample size or in in vitro studies.

Ingestion of lean meat elevates muscle inositol hexakisphosphate kinase 1 protein content independent of a distinct post-prandial circulating proteome in young adults with obesity

BACKGROUND

We have recently shown that a novel signalling kinase, inositol hexakisphosphate kinase 1 (IP6K1), is implicated in whole-body insulin resistance via its inhibitory action on Akt. Insulin and insulin like growth factor 1 (IGF-1) share many intracellular processes with both known to play a key role in glucose and protein metabolism in skeletal muscle.

AIMS

We aimed to compare IGF/IP6K1/Akt signalling and the plasma proteomic signature in individuals with a range of BMIs after ingestion of lean meat.

METHODS

Ten lean [Body mass index (BMI) (in kg/m²): 22.7 ± 0.4; Homeostatic model assessment of insulin resistance (HOMA_IR): 1.36 ± 0.17], 10 overweight (BMI: 27.1 ± 0.5; HOMA_IR: 1.25 ± 0.11), and 10 obese (BMI: 35.9 ± 1.3; HOMA_IR: 5.82 ± 0.81) adults received primed continuous L-[ring-¹³C₆]phenylalanine infusions. Blood and muscle biopsy samples were collected at 0 min (post-absorptive), 120 min and 300 min relative to the ingestion of 170 g pork loin (36 g protein and 5 g fat) to examine skeletal muscle protein signalling, plasma proteomic signatures, and whole-body phenylalanine disappearance rates (R_d).

RESULTS

Phenylalanine R_d was not different in obese compared to lean individuals at all time points and was not responsive to a pork ingestion (basal, P = 0.056; 120 & 300 min, P > 0.05). IP6K1 was elevated in obese individuals at 120 min post-prandial vs basal (P < 0.05). There were no acute differences plasma proteomic profiles between groups in the post-prandial state (P > 0.05).

CONCLUSIONS

These data demonstrate, for the first time that muscle IP6K1 protein content is elevated after lean meat ingestion in obese adults, suggesting that IP6K1 may be contributing to the dysregulation of nutrient uptake in skeletal muscle. In addition, proteomic analysis showed no differences in proteomic signatures between obese, overweight or lean individuals.

Whole Grain Wheat Consumption Affects Postprandial Inflammatory Response in a Randomized Controlled Trial in Overweight and Obese Adults with Mild Hypercholesterolemia in the Graandioos Study

BACKGROUND

Whole grain wheat (WGW) consumption is associated with health benefits in observational studies. However, WGW randomized controlled trial (RCT) studies show mixed effects.

OBJECTIVES

The health impact of WGW consumption was investigated by quantification of the body's resilience, which was defined as the "ability to adapt to a standardized challenge."

METHODS

A double-blind RCT was performed with overweight and obese (BMI: 25-35 kg/m2) men (n = 19) and postmenopausal women (n = 31) aged 45-70 y, with mildly elevated plasma total cholesterol (>5 mmol/L), who were randomly assigned to either 12-wk WGW (98 g/d) or refined wheat (RW). Before and after the intervention a standardized mixed-meal challenge was performed. Plasma samples were taken after overnight fasting and postprandially (30, 60, 120, and 240 min). Thirty-one biomarkers were quantified focusing on metabolism, liver, cardiovascular health, and inflammation. Linear mixed-models evaluated fasting compared with postprandial intervention effects. Health space models were used to evaluate intervention effects as composite markers representing resilience of inflammation, liver, and metabolism.

RESULTS

Postprandial biomarker changes related to liver showed decreased alanine aminotransferase by WGW (P = 0.03) and increased β-hydroxybutyrate (P = 0.001) response in RW. Postprandial changes related to inflammation showed increased C-reactive protein (P = 0.001), IL-6 (P = 0.02), IL-8 (P = 0.007), and decreased IL-1B (P = 0.0002) in RW and decreased C-reactive protein (P < 0.0001), serum amyloid A (P < 0.0001), IL-8 (P = 0.02), and IL-10 (P < 0.0001) in WGW. Health space visualization demonstrated diminished inflammatory (P < 0.01) and liver resilience (P < 0.01) by RW, whereas liver resilience was rejuvenated by WGW (P < 0.05).

CONCLUSIONS

Twelve-week 98 g/d WGW consumption can promote liver and inflammatory resilience in overweight and obese subjects with mildly elevated plasma cholesterol. The health space approach appeared appropriate to evaluate intervention effects as composite markers. This trial was registered at www.clinicaltrials.gov as NCT02385149.

Current and Future Nutritional Strategies to Modulate Inflammatory Dynamics in Metabolic Disorders

Obesity, type 2 diabetes, and other metabolic disorders have a large impact on global health, especially in Western countries. An important hallmark of metabolic disorders is chronic low-grade inflammation. A key player in chronic low-grade inflammation is dysmetabolism, which is defined as the inability to keep homeostasis resulting in loss of lipid control, oxidative stress, inflammation, and insulin resistance. Although often not yet detectable in the circulation, chronic low-grade inflammation can be present in one or multiple organs. The response to a metabolic challenge containing lipids may magnify dysfunctionalities at the tissue level, causing an overflow of inflammatory markers into the circulation and hence allow detection of early low-grade inflammation. Here, we summarize the evidence of successful application of metabolic challenge tests in type 2 diabetes, metabolic syndrome, obesity, and unhealthy aging. We also review how metabolic challenge tests have been successfully applied to evaluate nutritional intervention effects, including an "anti-inflammatory" mixture, dark chocolate, whole grain wheat and overfeeding. Additionally, we elaborate on future strategies to (re)gain inflammatory flexibility. Through epigenetic and metabolic regulation, the inflammatory response may be trained by regular mild and metabolic triggers, which can be understood from the perspective of trained immunity, hormesis and pro-resolution. New strategies to optimize dynamics of inflammation may become available.

Dynamic changes of postprandial plasma metabolites after intake of corn-soybean meal or casein-starch diets in growing pigs

Background

Postprandial nutrients utilization and metabolism of a certain diet is a complicated process. The metabolic feature of pigs after intake of corn-soybean meal or casein-starch diets are largely unknown. Therefore, this study was conducted to investigate the dynamic postprandial changes of plasma metabolic profile using growing pigs using metabolomics.

Methods

Twenty-four growing pigs with average initial body weight (BW) about 30 kg were placed in metabolic cages and then fitted with precaval vein catheters. Pigs were fed daily 4% of initial body weight. Two experimental diets were included: (i) a starch-casein based purified diet (PD) and (ii) a common corn-soybean meal diet (CD). Plasma was collected before feeding and 0.5 h, 1 h, 2 h, 4 h, 8 h after feeding.

Results

In both diets, compared to prior to feeding, the concentrations of glucose, most amino acids, metabolites such as 5-aminopentanoic acid, pipecolic acid, ornithine and 5-hydroxy-L-tryptophan were significantly increased in plasma during the first hour, whereas the concentrations of plasma triglycerides, glutamate, glycine, palmitelaidic acid, 13-HODE and oleic acid were decreased in the first hour. Compared with PD group, concentration of plasma leucine and isoleucine declined at 30 min in CD group. Plasma linoleic acid, sphingosine and many dipeptides were significantly higher in pigs fed CD.

Conclusion

Most significant metabolic changes occurred during the first hour after feeding and then became relatively stable after 2 h in both diets. These results show a broad scope picture of postprandial changes in plasma metabolites after intake of PD and CD and could be a reference for further nutrition intervention as well as the design of nutritional studies.

Electronic supplementary material

The online version of this article (10.1186/s40104-019-0351-8) contains supplementary material, which is available to authorized users.

Biotransformation profiles from a cohort of chronic fatigue women in response to a hepatic detoxification challenge

Chronic fatigue, in its various manifestations, frequently co-occur with pain, sleep disturbances and depression and is a non-communicable condition which is rapidly becoming endemic worldwide. However, it is handicapped by a lack of objective definitions and diagnostic measures. This has prompted the World Health Organization to develop an international instrument whose intended purpose is to improve quality of life (QOL), with energy and fatigue as one domain of focus. To complement this objective, the interface between detoxification, the exposome, and xenobiotic-sensing by nuclear receptors that mediate induction of biotransformation-linked genes, is stimulating renewed attention to a rational development of strategies to identify the metabolic profiles in complex multifactorial conditions like fatigue. Here we present results from a seven-year study of a cohort of 576 female patients suffering from low to high levels of chronic fatigue, in which phase I and phase II biotransformation was assessed. The biotransformation profiles used were based on hepatic detoxification challenge tests through oral caffeine, acetaminophen and acetylsalicylic acid ingestion coupled with oxidative stress analyses. The interventions indicated normal phase I but increased phase II glucuronidation and glycination conjugation. Complementarity was indicated between a fatigue scale, medical symptoms and associated energy-related parameters by application of Chi-square Automatic Interaction Detector (CHAID) analysis. The presented study provides a cluster of data from which we propose that multidisciplinary inputs from the combination of a fatigue scale, medical symptoms and biotransformation profiles provide the rationale for the development of a comprehensive laboratory instrument for improved diagnostics and personalized interventions in patients with chronic fatigue with a view to improving their QOL.

Postprandial Metabolic Effects of Fiber Mixes Revealed by in vivo Stable Isotope Labeling in Humans

Food supplementation with a fiber mix of guar gum and chickpea flour represents a promising approach to reduce the risk of type 2 diabetes mellitus (T2DM) by attenuating postprandial glycemia. To investigate the effects on postprandial metabolic fluxes of glucose-derived metabolites in response to this fiber mix, a randomized, cross-over study was designed. Twelve healthy, male subjects consumed three different flatbreads either supplemented with 2% guar gum or 4% guar gum and 15% chickpea flour or without supplementation (control). The flatbreads were enriched with ~2% of ¹³C-labeled wheat flour. Blood was collected at 16 intervals over a period of 360 min after bread intake and plasma samples were analyzed by GC-MS based metabolite profiling combined with stable isotope-assisted metabolomics. Although metabolite levels of the downstream metabolites of glucose, specifically lactate and alanine, were not altered in response to the fiber mix, supplementation of 4% guar gum was shown to significantly delay and reduce the exogenous formation of these metabolites. Metabolic modeling and computation of appearance rates revealed that the effects induced by the fiber mix were strongest for glucose and attenuated downstream of glucose. Further investigations to explore the potential of fiber mix supplementation to counteract the development of metabolic diseases are warranted.

Metabolomic profiling to identify effects of dietary calcium reveal the influence of the individual and postprandial dynamics on the canine plasma metabolome

Short-term feeding studies have highlighted a phenomenon in Ca regulation that raises concerns around Ca absorption in dogs that may make an impact on commercial diets near to the maximum recommended level. A recent study to determine responses in dogs fed one of two diets differing in dietary Ca over 40 weeks found no evidence to suggest a concern across a range of biological parameters hypothesised to be affected by Ca. Unforeseen consequences of dietary Ca could have occurred and metabolic profiling was deemed a suitable data-driven approach to identify effects of dietary Ca. The objectives were to compare the fasted plasma metabolome (sampled at 8-week intervals over 40 weeks) of dogs fed one of two diets, near to the minimum and maximum recommended levels of dietary Ca. Comparisons with the control diet were also investigated across the postprandial time course (1-4 h) following acute (1 d) and long-term (24 weeks) feeding of the test diet. Comparing fasted plasma samples at each time point, no significant effect (adjusted P < 0·05) of diet on metabolites was observed. In the postprandial state, only phosphate was consistently different between diets and was explained by additional dietary P to maintain Ca:P. Metabolic profiling analysis supports the view that the dietary Ca upper limit is safe. Additionally, the canine plasma metabolome was characterised, providing insights into the stability of individual profiles across 40 weeks, the response to consumption of a nutritionally complete meal over a 4 h postprandial time course and different kinetic categories of postprandial absorption.

Plasma metabolomics reveals lower carnitine concentrations in overweight Labrador Retriever dogs

Background

The prevalence of overweight is increasing in dogs, but the metabolic events related to this condition are still poorly understood. The purpose of the study was to investigate the postprandial response of plasma metabolites using a meal-challenge test and to identify metabolic variations related to spontaneous overweightness in privately owned dogs.

Results

Twenty-eight healthy male intact Labrador Retriever dogs were included, 12 of which were classified as lean (body condition score (BCS) 4–5 on a 9-point scale) and 16 as overweight (BCS 6–8). After an overnight fast (14–17 h), blood samples were collected and dogs were thereafter fed a high-fat meal. Postprandial blood samples were collected hourly four times. Plasma metabolites were identified by nuclear magnetic resonance. Postprandial metabolomes differed from the fasting metabolome in multivariate discriminant analysis (PLS-DA: Q²Y = 0.31–0.63, cross-validated ANOVA: P ≤ 0.00014) Eleven metabolites, all amino acids, contributed to the separations. Carnitine was identified as a metabolite related to overweight (stepwise logistic regression analysis P ≤ 0.03) and overweight dogs had overall lower carnitine response (mixed model repeated measures analysis P = 0.005) than lean dogs. Notably, mean fasting carnitine concentration in overweight dogs (9.4 ± 4.2 µM) was close to a proposed reference limit for carnitine insufficiency.

Conclusions

A postprandial amino acid response was detected but no time-dependent variations with regards to body condition groups were found. Lower carnitine concentrations were found in overweight compared to lean dogs. The latter finding could indicate a carnitine insufficiency related to spontaneous adiposity and altered lipid metabolism in overweight dogs in this cohort of otherwise healthy Labrador Retrievers.

Electronic supplementary material

The online version of this article (10.1186/s13028-019-0446-4) contains supplementary material, which is available to authorized users.

Effect of different time intervals after feeding on plasma metabolites in growing pigs: an UPLC-MS-based metabolomics study

A diet consumed by pigs provides the nutrients for the production of a large number of metabolites that, after first-pass metabolism in the liver, circulate systemically where they may exert diverse physiologic influences on pigs. So far, little is known of how feeding elicits changes in metabolic profiles for growing pigs. This study investigated differences in plasma metabolites in growing pigs at several intervals after feeding using the technique of metabolomics. Ten barrows (22.5 ± 0.5 kg BW) were fed a corn-soybean meal basal diet and were kept in metabolism crates for a period of 11 days. An indwelling catheter was inserted into the jugular vein of each pig before the experimental period. Plasmas before and 1, 4, and 8 hr after feeding were collected at day 11 and differential metabolites were determined using a metabolomics approach. Direct comparison at several intervals after feeding revealed differences in 14 compounds. Identified signatures were enriched in metabolic pathways related to linoleic acid metabolism, arginine and proline metabolism, lysine degradation, glycine, serine and threonine metabolism, and lysine biosynthesis. These results suggest that plasma metabolites of growing pigs after feeding were modulated through changes in linoleic acid metabolism and amino acid metabolism.

Postprandial metabolomics: GC-MS analysis reveals differences in organic acid profiles of impaired fasting glucose individuals in response to highland barley loads

The HB load producing low postprandial glucose and insulin responses brings about several alterations in organic acids.

Global testing of shifts in metabolic phenotype

INTRODUCTION

Current metabolomics approaches to unravel impact of diet- or lifestyle induced phenotype variation and shifts predominantly deploy univariate or multivariate approaches, with a posteriori interpretation at pathway level. This however often provides only a fragmented view on the involved metabolic pathways.

OBJECTIVES

To demonstrate the feasibility of using Goeman's global test (GGT) for assessment of variation and shifts in metabolic phenotype at the level of a priori defined pathways.

METHODS

Two intervention studies with identified phenotype variations and shifts were examined. In a weight loss (WL) intervention study obese subjects received a mixed meal challenge before and after WL. In a polyphenol (PP) intervention study obese subjects received a high fat mixed meal challenge (61E% fat) before and after a PP intervention. Plasma samples were obtained at fasting and during the postprandial response. Besides WL- and PP-induced phenotype shifts, also correlation of plasma metabolome with phenotype descriptors was assessed at pathway level. The plasma metabolome covered organic acids, amino acids, biogenic amines, acylcarnitines and oxylipins.

RESULTS

For the population of the WL study, GGT revealed that HOMA correlated with the fasting levels of the TCA cycle, BCAA catabolism, the lactate, arginine-proline and phenylalanine-tyrosine pathways. For the population of the PP study, HOMA correlated with fasting metabolite levels of TCA cycle, fatty acid oxidation and phenylalanine-tyrosine pathways. These correlations were more pronounced for metabolic pathways in the fasting state, than during the postprandial response. The effect of the WL and PP intervention on a priori defined metabolic pathways, and correlation of pathways with insulin sensitivity as described by HOMA was in line with previous studies.

CONCLUSION

GGT confirmed earlier biological findings in a hypothesis led approach. A main advantage of GGT is that it provides a direct view on involvement of a priori defined pathways in phenotype shifts.

Nutritional Metabolomics: Postprandial Response of Meals Relating to Vegan, Lacto-Ovo Vegetarian, and Omnivore Diets

Metabolomics provide an unbiased tool for exploring the modulation of the human metabolome in response to food intake. This study applied metabolomics to capture the postprandial metabolic response to breakfast meals corresponding to vegan (VE), lacto ovo-vegetarian (LOV), and omnivore (OM) diets. In a cross over design 32 healthy volunteers (16 men and 16 females) consumed breakfast meals in a randomized order during three consecutive days. Fasting and 3 h postprandial serum samples were collected and then subjected to metabolite profiling using ¹H-nuclear magnetic resonance (NMR) spectroscopy. Changes in concentration of identified and discriminating metabolites, between fasting and postprandial state, were compared across meals. Betaine, choline, and creatine displayed higher concentration in the OM breakfast, while 3-hydroxyisobutyrate, carnitine, proline, and tyrosine showed an increase for the LOV and unidentified free fatty acids displayed a higher concentration after the VE breakfast. Using ¹H NMR metabolomics it was possible to detect and distinguish the metabolic response of three different breakfast meals corresponding to vegan, lacto-ovo vegetarian, and omnivore diets in serum.

Metabolic Footprinting of Fermented Milk Consumption in Serum of Healthy Men

Background

Fermentation is a widely used method of natural food preservation that has consequences on the nutritional value of the transformed food. Fermented dairy products are increasingly investigated in view of their ability to exert health benefits beyond their nutritional qualities.

Objective

To explore the mechanisms underpinning the health benefits of fermented dairy intake, the present study followed the effects of milk fermentation, from changes in the product metabolome to consequences on the human serum metabolome after its ingestion.

Methods

A randomized crossover study design was conducted in 14 healthy men [mean age: 24.6 y; mean body mass index (in kg/m2): 21.8]. At the beginning of each test phase, serum samples were taken 6 h postprandially after the ingestion of 800 g of a nonfermented milk or a probiotic yogurt. During the 2-wk test phases, subjects consumed 400 g of the assigned test product daily (200 g, 2 times/d). Serum samples were taken from fasting participants at the end of each test phase. The serum metabolome was assessed through the use of LC-MS-based untargeted metabolomics.

Results

Postprandial serum metabolomes after milk or yogurt intake could be differentiated [orthogonal projections to latent structures discriminant analysis (OPLS-DA) Q2 = 0.74]. Yogurt intake was characterized by higher concentrations of 7 free amino acids (including proline, P = 0.03), reduced concentrations of 5 bile acids (including glycocholic acid, P = 0.04), and modulation of 4 indole derivative compounds (including indole lactic acid, P = 0.01). Fasting serum samples after 2 wk of daily intake of milk or yogurt could also be differentiated based on their metabolic profiles (OPLS-DA Q2 = 0.56) and were discussed in light of the postprandial results.

Conclusion

Metabolic pathways related to amino acids, indole derivatives, and bile acids were modulated in healthy men by the intake of yogurt. Further investigation to explore novel health effects of fermented dairy products is warranted.This trial was registered at clinicaltrials.gov as NCT02230345.

Metabolomics Reveals that the Type of Protein in a High-Fat Meal Modulates Postprandial Mitochondrial Overload and Incomplete Substrate Oxidation in Healthy Overweight Men

Background

A meal rich in saturated fatty acids induces a postprandial metabolic challenge. The type of dietary protein may modulate postprandial metabolism.

Objective

We studied the effect of dietary protein type on postprandial changes in the metabolome after a high-fat meal.

Methods

In a 3-period, crossover, postprandial study, 10 healthy overweight men with an elevated waist circumference (>94 cm) ingested high-fat meals made up of cream fat (70% of energy), sucrose (15% energy), and protein (15% energy) from either casein (CAS), whey protein (WHE), or α-lactalbumin-enriched whey protein (LAC). Urine collected immediately before and 2, 4, and 6 h after the meal was analyzed for metabolomics, a secondary outcome of the clinical study. We used mixed-effect models, partial least-square regression, and pathway enrichment analysis.

Results

At 4 and 6 h after the meal, the postprandial metabolome was found to be fully discriminated according to protein type. We identified 17 metabolites that significantly explained the effect of protein type on postprandial metabolomic changes (protein-time interaction). Among this signature, acylcarnitines and other acylated metabolites related to fatty acid or amino acid oxidation were the main discriminant features. The difference in metabolic profiles was mainly explained by urinary acylcarnitines and some other acylated products (protein type, Ps < 0.0001), with a dramatically greater increase (100- to 1000-fold) after WHE, and to a lesser extent after LAC, as compared with CAS. Pathway enrichment analysis confirmed that the type of protein had modified fatty acid oxidation (P < 0.05).

Conclusion

Taken together, our results indicate that, in healthy overweight men, the type of protein in a high-fat meal interplays with fatty acid oxidation with a differential accumulation of incomplete oxidation products. A high-fat meal containing WHE, but not CAS, resulted in this outpacing of the tricarboxylic acid cycle. This study was registered at clinicaltrials.gov as NCT00931151.

The Effect of Lean-Seafood and Non-Seafood Diets on Fasting and Postprandial Serum Metabolites and Lipid Species: Results from a Randomized Crossover Intervention Study in Healthy Adults

The metabolic effects associated with intake of different dietary protein sources are not well characterized. We aimed to elucidate how two diets that varied in main protein sources affected the fasting and postprandial serum metabolites and lipid species. In a randomized controlled trial with crossover design, healthy adults (n = 20) underwent a 4-week intervention with two balanced diets that varied mainly in protein source (lean-seafood versus non-seafood proteins). Nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry analyses were applied to examine the effects of the two diets on serum metabolites. In the fasting state, the lean-seafood diet period, as opposed to the non-seafood diet period, significantly decreased the serum levels of isoleucine and valine, and during the postprandial state, a decreased level of lactate and increased levels of citrate and trimethylamine N-oxide were observed. The non-seafood diet significantly increased the fasting level of 26 lipid species including ceramides 18:1/14:0 and 18:1/23:0 and lysophosphatidylcholines 20:4 and 22:5, as compared to the lean-seafood diet. Thus, the lean-seafood diet decreased circulating isoleucine and valine levels, whereas the non-seafood diet elevated the levels of certain ceramides, metabolites that are associated with insulin-resistance.

Plasma metabolome analysis identifies distinct human metabotypes in the postprandial state with different susceptibility to weight loss-mediated metabolic improvements

Health has been defined as the capability of the organism to adapt to challenges. In this study, we tested to what extent comprehensively phenotyped individuals reveal differences in metabolic responses to a standardized mixed meal tolerance test (MMTT) and how these responses change when individuals experience moderate weight loss. Metabolome analysis was used in 70 healthy individuals. with profiling of ∼300 plasma metabolites during an MMTT over 8 h. Multivariate analysis of plasma markers of fatty acid catabolism identified 2 distinct metabotype clusters (A and B). Individuals from metabotype B showed slower glucose clearance, had increased intra-abdominal adipose tissue mass and higher hepatic lipid levels when compared with individuals from metabotype A. An NMR-based urine analysis revealed that these individuals also to have a less healthy dietary pattern. After a weight loss of ∼5.6 kg over 12 wk, only the subjects from metabotype B showed positive changes in the glycemic response during the MMTT and in markers of metabolic diseases. Our study in healthy individuals demonstrates that more comprehensive phenotyping can reveal discrete metabotypes with different outcomes in a dietary intervention and that markers of lipid catabolism in plasma could allow early detection of the metabolic syndrome.-Fiamoncini, J., Rundle, M., Gibbons, H., Thomas, E. L., Geillinger-Kästle, K., Bunzel, D., Trezzi, J.-P., Kiselova-Kaneva, Y., Wopereis, S., Wahrheit, J., Kulling, S. E., Hiller, K., Sonntag, D., Ivanova, D., van Ommen, B., Frost, G., Brennan, L., Bell, J. Daniel, H. Plasma metabolome analysis identifies distinct human metabotypes in the postprandial state with different susceptibility to weight loss-mediated metabolic improvements.