Assessing individual metabolic responsiveness to a lipid challenge using a targeted metabolomic approach

Revealing static and dynamic biomarkers from postprandial metabolomics data through coupled matrix and tensor factorizations

INTRODUCTION

Longitudinal metabolomics data from a meal challenge test contains both fasting and dynamic signals, that may be related to metabolic health and diseases. Recent work has explored the multiway structure of time-resolved metabolomics data by arranging it as a three-way array with modes: subjects, metabolites, and time. The analysis of such dynamic data (where the fasting data is subtracted from postprandial states) reveals dynamic markers of various phenotypes, and differences between fasting and dynamic states. However, there is still limited success in terms of extracting static and dynamic biomarkers for the same subject stratifications.

OBJECTIVES

Through joint analysis of fasting and dynamic metabolomics data, our goal is to capture static and dynamic biomarkers of a phenotype for the same subject stratifications providing a complete picture, that will be more effective for precision health.

METHODS

We jointly analyze fasting and dynamic metabolomics data collected during a meal challenge test from the COPSAC2000 cohort using coupled matrix and tensor factorizations (CMTF), where the dynamic data (subjects by metabolites by time) is coupled with the fasting data (subjects by metabolites) in the subjects mode.

RESULTS

The proposed data fusion approach extracts shared subject stratifications in terms of BMI (body mass index) from fasting and dynamic signals as well as the static and dynamic metabolic biomarker patterns corresponding to those stratifications. Specifically, we observe a subject stratification showing the positive association with all fasting VLDLs and higher BMI. For the same subject stratification, a subset of dynamic VLDLs (mainly the smaller sizes) correlates negatively with higher BMI. Higher correlations of the subject quantifications with the phenotype of interest are observed using such a data fusion approach compared to individual analyses of the fasting and postprandial state.

CONCLUSION

The CMTF-based approach provides a complete picture of static and dynamic biomarkers for the same subject stratifications-when markers are present in both fasting and dynamic states.

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.

Precision Nutrition and Cardiovascular Disease Risk Reduction: the Promise of High-Density Lipoproteins

PURPOSE OF REVIEW

Emerging evidence supports the promise of precision nutritional approaches for cardiovascular disease (CVD) prevention. Here, we discuss current findings from precision nutrition trials and studies reporting substantial inter-individual variability in responses to diets and dietary components relevant to CVD outcomes. We highlight examples where early precision nutrition research already points to actionable intervention targets tailored to an individual's biology and lifestyle. Finally, we make the case for high-density lipoproteins (HDL) as a compelling next generation target for precision nutrition aimed at CVD prevention. HDL possesses complex structural features including diverse protein components, lipids, size distribution, extensive glycosylation, and interacts with the gut microbiome, all of which influence HDL's anti-inflammatory, antioxidant, and cholesterol efflux properties. Elucidating the nuances of HDL structure and function at an individual level may unlock personalized dietary and lifestyle strategies to optimize HDL-mediated atheroprotection and reduce CVD risk.

RECENT FINDINGS

Recent human studies have demonstrated that HDL particles are key players in the reduction of CVD risk. Our review highlights the role of HDL and the importance of personalized therapeutic approaches to improve their potential for reducing CVD risk. Factors such as diet, genetics, glycosylation, and gut microbiome interactions can modulate HDL structure and function at the individual level. We emphasize that fractionating HDL into size-based subclasses and measuring particle concentration are necessary to understand HDL biology and for developing the next generation of diagnostics and biomarkers. These discoveries underscore the need to move beyond a one-size-fits-all approach to HDL management. Precision nutrition strategies that account for personalized metabolic, genetic, and lifestyle data hold promise for optimizing HDL therapies and function to mitigate CVD risk more potently. While human studies show HDL play a key role in reducing CVD risk, recent findings indicate that factors such as diet, genetics, glycosylation, and gut microbes modulate HDL function at the individual level, underscoring the need for precision nutrition strategies that account for personalized variability to optimize HDL's potential for mitigating CVD risk.

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.

Non-targeted lipidomics and transcriptomics analysis reveal the molecular underpinnings of mandibular gland development in Apis mellifera ligustica

The mandibular gland is an important exocrine gland of worker bees, which mainly secretes fatty acids and pheromones. Lipids have important roles in energy storage, membrane structure stabilization, and signaling. However, molecular underpinnings of mandibular gland development and lipid remodeling at the different physiological stages of worker bees is still lacking. In this study, we used scanning and transmission electron microscopy to reveal the morphological changes in secretory cells, and liquid chromatography-mass spectrometry and RNA-seq to investigate the lipidome and gene transcripts during development. The morphology of secretory cells was flat in newly emerged workers, becoming vacuolated and turgid when they were activated in nurse bees and foragers. Transport vesicles became denser from newly emerged bees to 21-day worker bees. Concentrations of 10-HDA reached a maximum within 15d workers and changes in genes expression were consistent with 10-HDA content. Non-targeted lipidomics analysis of newly emerged, 6d, and 15d worker bees revealed that PC and TAG were the main lipids in mandibular gland, and lipids dramatically altered across developmental stages. TAG 54:4 was increased most strongly at 6d and 15d worker bees, meanwhile, the abundances of TAG 54:1 and TAG 54:2 were decreased sharply. Further, transcriptomics analysis showed that differentially expressed genes were significantly enriched in key nutrient metabolic pathways, particularly lipid metabolism, in 6d and 15d bees. This multi-omic perspective provides a unique resource and deeper insight into bee mandibular gland development and baseline data for further study of the mandibular gland in worker bees.

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.

Wearable Technology to Quantify the Nutritional Intake of Adults: Validation Study

Background

Wearable and mobile sensor technologies can be useful tools in precision nutrition research and practice, but few are reliable for obtaining accurate and precise measurements of diet and nutrition.

Objective

This study aimed to assess the ability of wearable technology to monitor the nutritional intake of adult participants. This paper describes the development of a reference method to validate the wristband’s estimation of daily nutritional intake of 25 free-living study participants and to evaluate the accuracy (kcal/day) and practical utility of the technology.

Methods

Participants were asked to use a nutrition tracking wristband and an accompanying mobile app consistently for two 14-day test periods. A reference method was developed to validate the estimation of daily nutritional intake of participants by the wristband. The research team collaborated with a university dining facility to prepare and serve calibrated study meals and record the energy and macronutrient intake of each participant. A continuous glucose monitoring system was used to measure adherence with dietary reporting protocols, but these findings are not reported. Bland-Altman tests were used to compare the reference and test method outputs (kcal/day).

Results

A total of 304 input cases were collected of daily dietary intake of participants (kcal/day) measured by both reference and test methods. The Bland-Altman analysis had a mean bias of −105 kcal/day (SD 660), with 95% limits of agreement between −1400 and 1189. The regression equation of the plot was Y=−0.3401X+1963, which was significant (P<.001), indicating a tendency for the wristband to overestimate for lower calorie intake and underestimate for higher intake. Researchers observed transient signal loss from the sensor technology of the wristband to be a major source of error in computing dietary intake among participants.

Conclusions

This study documents high variability in the accuracy and utility of a wristband sensor to track nutritional intake, highlighting the need for reliable, effective measurement tools to facilitate accurate, precision-based technologies for personal dietary guidance and intervention.

Lipidomics perturbations in the brain of adult zebrafish (Danio rerio) after exposure to chiral ibuprofen

The stereoselective effects of chiral ibuprofen (IBU) were studied using lipidomics by exposing adult zebrafish (Danio rerio) to an environmental concentration of 5 μg/L for 28 days. After treatment with rac-/R-(-)-/S-(+)-IBU, the brain tissue of the zebrafish was harvested to analyze for lipid metabolites by using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. Results showed that the six classes of lipids, namely, glycerophospholipids, sterol lipids, prenol lipids, fatty acyls, glycerolipids, and sphingolipids, including 46 biomarkers, were affected after exposure. The different influences on metabolites were observed in the rac-/R-(-)-/S-(+)-IBU-treated samples. The rac-IBU treatment remarkably affected nine lipids. The R-(-)-IBU and S-(+)-IBU treatments had remarkably effects on six and four lipids, respectively. According to the HMDB database and KEGG pathways, nine important lipids were successfully matched to the involved biochemical pathways, such as glycerophospholipid metabolism, arachidonic acid metabolism, and linoleic acid metabolism. Therefore, IBU can cause disorders in the metabolism of the brain lipids of adult zebrafish and affect the composition of biological membranes, inflammatory responses, and cardiovascular and cerebrovascular diseases. The significant difference in the effects of R-(-)-IBU and S-(+)-IBU on lipidomics indicated that chiral IBU has stereoselective toxicity to aquatic organisms. Our study provided new insights into the environmental toxicology and highlighted the hazard of pharmaceutical and personal care product pollution in aquatic environments.

Impact of nutrient overload on metabolic homeostasis

Nutrient overload occurs worldwide as a consequence of the modern diet pattern and the physical inactivity that sometimes accompanies it. Cells initiate multiple protective mechanisms to adapt to elevated intracellular metabolites and restore metabolic homeostasis, but irreversible injury to the cells can occur in the event of prolonged nutrient overload. Many studies have advanced the understanding of the different detrimental effects of nutrient overload; however, few reports have made connections and given the full picture of the impact of nutrient overload on cellular metabolism. In this review, detailed changes in metabolic and energy homeostasis caused by chronic nutrient overload, as well as their associations with the development of metabolic disorders, are discussed. Overnutrition-induced changes in key organelles and sensors rewire cellular bioenergetic pathways and facilitate the shift of the metabolic state toward biosynthesis, thereby leading to the onset of various metabolic disorders, which are essentially the downstream manifestations of a misbalanced metabolic equilibrium. Based on these mechanisms, potential therapeutic targets for metabolic disorders and new research directions are proposed.

The Effect of Anticoagulants, Temperature, and Time on the Human Plasma Metabolome and Lipidome from Healthy Donors as Determined by Liquid Chromatography-Mass Spectrometry

Liquid-chromatography mass spectrometry is commonly used to identify and quantify metabolites from biological samples to gain insight into human physiology and pathology. Metabolites and their abundance in biological samples are labile and sensitive to variations in collection conditions, handling and processing. Variations in sample handling could influence metabolite levels in ways not related to biology, ultimately leading to the misinterpretation of results. For example, anticoagulants and preservatives modulate enzyme activity and metabolite oxidization. Temperature may alter both enzymatic and non-enzymatic chemistry. The potential for variation induced by collection conditions is particularly important when samples are collected in remote locations without immediate access to specimen processing. Data are needed regarding the variation introduced by clinical sample collection processes to avoid introducing artifact biases. In this study, we used metabolomics and lipidomics approaches paired with univariate and multivariate statistical analyses to assess the effects of anticoagulant, temperature, and time on healthy human plasma samples collected to provide guidelines on sample collection, handling, and processing for vaccinology. Principal component analyses demonstrated clustering by sample collection procedure and that anticoagulant type had the greatest effect on sample metabolite variation. Lipids such as glycerophospholipids, acylcarnitines, sphingolipids, diacylglycerols, triacylglycerols, and cholesteryl esters are significantly affected by anticoagulant type as are amino acids such as aspartate, histidine, and glutamine. Most plasma metabolites and lipids were unaffected by storage time and temperature. Based on this study, we recommend samples be collected using a single anticoagulant (preferably EDTA) with sample processing at <24 h at 4 °C.

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.

APOE and the Association of Fatty Acids With the Risk of Stroke, Coronary Heart Disease, and Mortality

Background and Purpose- The role of dietary fat on cardiovascular health and mortality remains under debate. Because the APOE is central to the transport and metabolism of lipids, we examined associations between plasma fatty acids and the risk of stroke, coronary heart disease, and mortality by APOE-ε4 genotype. Methods- We included 943 FHS (Framingham Heart Study) and 1406 3C (Three-City) Bordeaux Study participants. Plasma docosahexaenoic, linoleic, arachidonic, and palmitic fatty acids were measured at baseline by gas chromatography. All-cause stroke, ischemic stroke, coronary heart disease, and all-cause mortality events were identified prospectively using standardized protocols. Each cohort used Cox models to separately relate fatty acid levels to the risk of developing each event during ≤10 years of follow-up adjusting for potential confounders and stratifying by APOE genotype (ε4 carriers versus noncarriers). We then meta-analyzed summary statistics using random-effects models. Results- On average, participants had a mean age of 74 years, 61% were women, and 21% (n=483) were APOE-ε4 carriers. Meta-analysis results showed that, only among APOE-ε4 carriers, every SD unit increase in linoleic acid was associated with a reduced risk of all-cause stroke (hazard ratio [HR], 0.54 [95% CI, 0.38-0.78]), ischemic stroke (HR, 0.48 [95% CI, 0.33-0.71]), and all-cause mortality (HR, 0.70 [95% CI, 0.57-0.85]). In contrast, every SD unit increase in palmitic acid was related to an increased risk of all-cause stroke (HR, 1.58 [95% CI, 1.16-2.17]), ischemic stroke (HR, 1.76 [95% CI, 1.26-2.45]), and coronary heart disease (HR, 1.48 [95% CI, 1.09-2.01]), also in APOE-ε4 carriers only. Results for docosahexaenoic acid and arachidonic acid were heterogeneous between cohorts. Conclusions- These exploratory results suggest that APOE-ε4 carriers may be more susceptible to the beneficial or adverse impact of fatty acids on cardiovascular disease and mortality. In this subgroup, higher linoleic acid was protective for stroke and mortality, whereas palmitic acid was a risk factor for stroke and coronary heart disease. The mechanisms underlying these novel findings warrant further investigation.

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.

Metabolomic profiles of plasma, exhaled breath condensate, and saliva are correlated with potential for air toxics detection

INTRODUCTION

Advances in the development of high-resolution metabolomics (HRM) have provided new opportunities for their use in characterizing exposures to environmental air pollutants and air pollution-related disease etiologies. Exposure assessment studies have considered blood, breath, and saliva as biological matrices suitable for measuring responses to air pollution exposures. The current study examines comparability among these three matrices using HRM and explores their potential for measuring mobile-source air toxics.

METHODS

Four participants provided saliva, exhaled breath concentrate (EBC), and plasma before and after a 2 h road traffic exposure. Samples were analyzed on a Thermo Scientific QExactive MS system in positive electrospray ionization mode and resolution of 70 000 full-width at half-maximum with C18 chromatography. Data were processed using an apLCMS and xMSanalyzer on the R statistical platform.

RESULTS

The analysis yielded 7110, 6019, and 7747 reproducible features in plasma, EBC, and saliva, respectively. Correlations were moderate-to-strong (R = 0.41-0.80) across all pairwise comparisons of feature intensity within profiles, with the strongest between EBC and saliva. The associations of mean intensities between matrix pairs were positive and significant, controlling for subject and sampling time effects. Six out of 20 features shared in all three matrices putatively matched a list of known mobile-source air toxics.

CONCLUSIONS

Plasma, saliva, and EBC have largely comparable metabolic profiles measurable through HRM. These matrices have the potential to be used in identification and measurement of exposures to mobile-source air toxics, though further, targeted study is needed.

Effects of stimulation technique, anatomical region, and time on human sweat lipid mediator profiles

Few studies compare sampling protocol effect on sweat composition. Here we evaluate the impact of sweat stimulation mode and site of collection on lipid mediator composition. Sweat from healthy males (n=7) was collected weekly for three weeks from the volar forearm following either pilocarpine iontophoresis or exercise, and from the forearm, back and thigh following pilocarpine iontophoresis only. Sweat content of over 150 lipid mediators were measured by liquid chromatography-tandem mass spectrometry. Seventy lipid mediators were routinely detected, including prostanoids, alcohols, diols, epoxides, ketones, nitrolipids, N-acylethanolamides, monoacylglycerols, and ceramides. Detected lipid mediators appeared unaffected by sampling site, though the forearm was the most consistent source of sweat. Pilocarpine-induced sweat showed increased concentrations of most detected compounds. Moreover, lipid mediator concentrations and profiles were temporally stable over the study duration. Sweat therefore appears to be a consistent and anatomically-stable source of lipid mediators, but care must be taken in comparing results obtained from different stimulation techniques.

21st century toolkit for optimizing population health through precision nutrition

Scientific, technological, and economic progress over the last 100 years all but eradicated problems of widespread food shortage and nutrient deficiency in developed nations. But now society is faced with a new set of nutrition problems related to energy imbalance and metabolic disease, which require new kinds of solutions. Recent developments in the area of new analytical tools enable us to systematically study large quantities of detailed and multidimensional metabolic and health data, providing the opportunity to address current nutrition problems through an approach called Precision Nutrition. This approach integrates different kinds of "big data" to expand our understanding of the complexity and diversity of human metabolism in response to diet. With these tools, we can more fully elucidate each individual's unique phenotype, or the current state of health, as determined by the interactions among biology, environment, and behavior. The tools of precision nutrition include genomics, metabolomics, microbiomics, phenotyping, high-throughput analytical chemistry techniques, longitudinal tracking with body sensors, informatics, data science, and sophisticated educational and behavioral interventions. These tools are enabling the development of more personalized and predictive dietary guidance and interventions that have the potential to transform how the public makes food choices and greatly improve population health.

Plant sterol ester diet supplementation increases serum plant sterols and markers of cholesterol synthesis, but has no effect on total cholesterol levels

This double-blind, randomized, placebo-controlled, cross-over intervention-study was conducted in healthy volunteers to evaluate the effects of plant sterol ester supplemented margarine on cholesterol, non-cholesterol sterols and oxidative stress in serum and monocytes. Sixteen volunteers, average age 34 years, with no or mild hypercholesterolemia were subjected to a 4 week period of daily intake of 3g plant sterols per day supplied via a supplemented margarine on top of regular eating habits. After a wash-out period of one week, volunteers switched groups. Compared to placebo, a diet supplementation with plant sterols increased serum levels of plant sterols such as campesterol (+0.16±0.19mg/dL, p=0.005) and sitosterol (+0.27±0.18mg/dL, p<0.001) and increased markers of cholesterol synthesis such as desmosterol (+0.05±0.07mg/dL, p=0.006) as well as lathosterol (+0.11±0.16mg/dL, p=0.012). Cholesterol serum levels, however, were not changed significantly (+18.68±32.6mg/dL, p=0.052). These findings could not be verified in isolated circulating monocytes. Moreover, there was no effect on monocyte activation and no differences with regard to redox state after plant sterol supplemented diet. Therefore, in a population of healthy volunteers with no or mild hypercholesterolemia, consumption of plant sterol ester supplemented margarine results in increased concentrations of plant sterols and cholesterol synthesis markers without affecting total cholesterol in the serum, activation of circulating monocytes or redox state.

Lipidomics, Biomarkers, and Schizophrenia: A Current Perspective

Lipidomics is a lipid-targeted metabolomics approach aiming at comprehensive analysis of lipids in biological systems. Recent technological progresses in mass spectrometry, nuclear magnetic resonance spectroscopy, and chromatography have significantly enhanced the developments and applications of metabolic profiling of lipids in more complex biological samples. As many diseases reveal a notable change in lipid profiles compared with that of healthy people, lipidomics have also been broadly introduced to scientific research on diseases. Exploration of lipid biochemistry by lipidomics approach will not only provide insights into specific roles of lipid molecular species in health and disease, but it will also support the identification of potential biomarkers for establishing preventive or therapeutic approaches for human health. This chapter aims to illustrate how lipidomics can contribute for understanding the biological mechanisms inherent to schizophrenia and why lipids are relevant biomarkers of schizophrenia. The application of lipidomics in clinical studies has the potential to provide new insights into lipid profiling and pathophysiological mechanisms underlying schizophrenia. The future perspectives of lipidomics in mental disorders are also discussed herein.

Bioanalytical techniques in nontargeted clinical lipidomics

Lipidomic analysis aims at comprehensive characterization of molecular lipids in biological systems. Due to the central role of lipid metabolism in many devastating diseases, lipidomics is being increasingly applied in biomedical research. Over the past years, advances in analytical techniques and bioinformatics enabled increasingly comprehensive and accurate coverage of lipids both in tissues and biofluids, yet many challenges remain. This review highlights recent progress in the domain of analytical lipidomics, with main emphasis on non-targeted methodologies for large scale clinical applications, as well as discusses some of the key challenges and opportunities in this field.

Postprandial metabolomics: A pilot mass spectrometry and NMR study of the human plasma metabolome in response to a challenge meal

The study of postprandial metabolism is relevant for understanding metabolic diseases and characterizing personal responses to diet. We combined three analytical platforms - gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) - to validate a multi-platform approach for characterizing individual variation in the postprandial state. We analyzed the postprandial plasma metabolome by introducing, at three occasions, meal challenges on a usual diet, and 1.5 years later, on a modified background diet. The postprandial response was stable over time and largely independent of the background diet as revealed by all three analytical platforms. Coverage of the metabolome between NMR and GC-MS included more polar metabolites detectable only by NMR and more hydrophobic compounds detected by GC-MS. The variability across three separate testing occasions among the identified metabolites was in the range of 1.1-86% for GC-MS and 0.9-42% for NMR in the fasting state at baseline. For the LC-MS analysis, the coefficients of variation of the detected compounds in the fasting state at baseline were in the range of 2-97% for the positive and 4-69% for the negative mode. Multivariate analysis (MVA) of metabolites detected with GC-MS revealed that for both background diets, levels of postprandial amino acids and sugars increased whereas those of fatty acids decreased at 0.5 h after the meal was consumed, reflecting the expected response to the challenge meal. MVA of NMR data revealed increasing postprandial levels of amino acids and other organic acids together with decreasing levels of acetoacetate and 3-hydroxybutanoic acid, also independent of the background diet. Together these data show that the postprandial response to the same challenge meal was stable even though it was tested 1.5 years apart, and that it was largely independent of background diet. This work demonstrates the efficacy of a multi-platform metabolomics approach followed by multivariate and univariate data analysis for a broad-scale screen of the individual metabolome, particularly for studies using repeated measures to determine dietary response phenotype.

Profiling the Oxylipin and Endocannabinoid Metabolome by UPLC-ESI-MS/MS in Human Plasma to Monitor Postprandial Inflammation

Bioactive lipids, including oxylipins, endocannabinoids, and related compounds may function as specific biochemical markers of certain aspects of inflammation. However, the postprandial responsiveness of these compounds is largely unknown; therefore, changes in the circulating oxylipin and endocannabinoid metabolome in response to a challenge meal were investigated at six occasions in a subject who freely modified her usual diet. The dietary change, and especially the challenge meal itself, represented a modification of precursor fatty acid status, with expectedly subtle effects on bioactive lipid levels. To detect even the slightest alteration, highly sensitive ultra-performance liquid chromatography (UPLC) coupled to electrospray ionization (ESI) tandem mass spectrometry (MS/MS) methods for bioactive lipid profiling was employed. A previously validated UPLC-ESI-MS/MS method for profiling the endocannabinoid metabolome was used, while validation of an UPLC-ESI-MS/MS method for oxylipin analysis was performed with acceptable outcomes for a majority of the parameters according to the US Food and Drug Administration guidelines for linearity (0.9938 < R2 < 0.9996), limit of detection (0.0005-2.1 pg on column), limit of quantification (0.0005-4.2 pg on column), inter- and intraday accuracy (85-115%) and precision (< 5%), recovery (40-109%) and stability (40-105%). Forty-seven of fifty-two bioactive lipids were detected in plasma samples at fasting and in the postprandial state (0.5, 1, and 3 hours after the meal). Multivariate analysis showed a significant shift of bioactive lipid profiles in the postprandial state due to inclusion of dairy products in the diet, which was in line with univariate analysis revealing seven compounds (NAGly, 9-HODE, 13-oxo-ODE, 9(10)-EpOME, 12(13)-EpOME, 20-HETE, and 11,12-DHET) that were significantly different between background diets in the postprandial state (but not at fasting). The only change in baseline levels at fasting was displayed by TXB2. Furthermore, postprandial responsiveness was detected for seven compounds (POEA, SEA, 9(10)-DiHOME, 12(13)-DiHOME, 13-oxo-ODE, 9-HODE, and 13-HODE). Hence, the data confirm that the UPLC-ESI-MS/MS method performance was sufficient to detect i) a shift, in the current case most notably in the postprandial bioactive lipid metabolome, caused by changes in diet and ii) responsiveness to a challenge meal for a subset of the oxylipin and endocannabinoid metabolome. To summarize, we have shown proof-of-concept of our UPLC-ESI-MS/MS bioactive lipid protocols for the purpose of monitoring subtle shifts, and thereby useful to address lipid-mediated postprandial inflammation.

Metabolome and fecal microbiota in monozygotic twin pairs discordant for weight: a Big Mac challenge

Postprandial responses to food are complex, involving both genetic and environmental factors. We studied postprandial responses to a Big Mac meal challenge in monozygotic co-twins highly discordant for body weight. This unique design allows assessment of the contribution of obesity, independent of genetic liability. Comprehensive metabolic profiling using 3 analytical platforms was applied to fasting and postprandial serum samples from 16 healthy monozygotic twin pairs discordant for weight (body mass index difference >3 kg/m(2)). Nine concordant monozygotic pairs were examined as control pairs. Fecal samples were analyzed to assess diversity of the major bacterial groups by using 5 different validated bacterial group specific denaturing gradient gel electrophoresis methods. No differences in fecal bacterial diversity were detected when comparing co-twins discordant for weight (ANOVA, P<0.05). We found that within-pair similarity is a dominant factor in the metabolic postprandial response, independent of acquired obesity. Branched chain amino acids were increased in heavier as compared with leaner co-twins in the fasting state, but their levels converged postprandially (paired t tests, FDR q<0.05). We also found that specific bacterial groups were associated with postprandial changes of specific metabolites. Our findings underline important roles of genetic and early life factors in the regulation of postprandial metabolite levels.

The future of yogurt: scientific and regulatory needs

Lactation biology, microbial selection, and human diversity are central themes that could guide investment in scientific research, industrial innovation, and regulatory policy oversight to propel yogurt into the central role for health-promoting food products. The ability of yogurt to provide the nourishing properties of milk together with the live microorganisms from fermentation provides a unique combination of food assets. Academic research must now define the various targets on which these biological assets act to improve health and develop the metrics that can quantitatively document their benefits. The food industry must reconcile that yogurt and its microorganisms cannot be expected to provide measurable benefits for all consumers, at all doses, and at all times. A supportive regulatory oversight must demand safety and yet encourage innovations that support a value proposition for yogurt in health. Health valuation in the marketplace will be driven by parallel innovations, including accurate assessment technologies, validated microbial ingredients, and health-aware consumers.

A preliminary report on oral fat tolerance test in rhesus monkeys

Background

Oral fat tolerance test (OFTT) has been widely used to assess the postprandial lipemia in human beings, but there is few studies concerning OFTT in nonhuman primates. This study is designed to explore the feasibility of OFTT in rhesus monkeys.

Methods

In a cross-over study, a total of 8 adult female rhesus monkeys were fed with normal monkey diet (NND), high sugar high fat diet (HHD), and extremely high fat diet (EHD), respectively. Each monkey consumed NND, HHD and EHD respectively, each weighing 60 g. Serial blood samples were collected at 1, 2, 3, 4, 5, and 6 h after ingesting each kind of food. Triglyceride, cholesterol, glucose, and insulin at each time point were measured. The area under the curve of triglyceride (TG-AUC) and triglyceride peak response (TG-PR) were also calculated.

Results

All monkeys ingested 3 kinds of foods within 15 minutes. TG-AUC and TG-PR of HHD group were higher than those of the other two groups. Postprandial triglyceride levels at 2, 3, 4, and 5 hours in HHD group during OFTT were also higher than those in NND and EHD group.

Conclusions

HHD diet can be used in OFTT for nonhuman primates.

Nutritional lipidomics: molecular metabolism, analytics, and diagnostics

The field of lipidomics is providing nutritional science a more comprehensive view of lipid intermediates. Lipidomics research takes advantage of the increase in accuracy and sensitivity of mass detection of MS with new bioinformatics toolsets to characterize the structures and abundances of complex lipids. Yet, translating lipidomics to practice via nutritional interventions is still in its infancy. No single instrumentation platform is able to solve the varying analytical challenges of the different molecular lipid species. Biochemical pathways of lipid metabolism remain incomplete and the tools to map lipid compositional data to pathways are still being assembled. Biology itself is dauntingly complex and simply separating biological structures remains a key challenge to lipidomics. Nonetheless, the strategy of combining tandem analytical methods to perform the sensitive, high-throughput, quantitative, and comprehensive analysis of lipid metabolites of very large numbers of molecules is poised to drive the field forward rapidly. Among the next steps for nutrition to understand the changes in structures, compositions, and function of lipid biomolecules in response to diet is to describe their distribution within discrete functional compartments lipoproteins. Additionally, lipidomics must tackle the task of assigning the functions of lipids as signaling molecules, nutrient sensors, and intermediates of metabolic pathways.

Mass spectrometry-based metabolomics for the discovery of biomarkers of fruit and vegetable intake: citrus fruit as a case study

Elucidation of the relationships between genotype, diet, and health requires accurate dietary assessment. In intervention and epidemiological studies, dietary assessment usually relies on questionnaires, which are susceptible to recall bias. An alternative approach is to quantify biomarkers of intake in biofluids, but few such markers have been validated so far. Here we describe the use of metabolomics for the discovery of nutritional biomarkers, using citrus fruits as a case study. Three study designs were compared. Urinary metabolomes were profiled for volunteers that had (a) consumed an acute dose of orange or grapefruit juice, (b) consumed orange juice regularly for one month, and (c) reported high or low consumption of citrus products for a large cohort study. Some signals were found to reflect citrus consumption in all three studies. Proline betaine and flavanone glucuronides were identified as known biomarkers, but various other biomarkers were revealed. Further, many signals that increased after citrus intake in the acute study were not sensitive enough to discriminate high and low citrus consumers in the cohort study. We propose that urine profiling of cohort subjects stratified by consumption is an effective strategy for discovery of sensitive biomarkers of consumption for a wide range of foods.

Inter-individual differences in response to dietary intervention: integrating omics platforms towards personalised dietary recommendations

Technologic advances now make it possible to collect large amounts of genetic, epigenetic, metabolomic and gut microbiome data. These data have the potential to transform approaches towards nutrition counselling by allowing us to recognise and embrace the metabolic, physiologic and genetic differences among individuals. The ultimate goal is to be able to integrate these multi-dimensional data so as to characterise the health status and disease risk of an individual and to provide personalised recommendations to maximise health. To this end, accurate and predictive systems-based measures of health are needed that incorporate molecular signatures of genes, transcripts, proteins, metabolites and microbes. Although we are making progress within each of these omics arenas, we have yet to integrate effectively multiple sources of biologic data so as to provide comprehensive phenotypic profiles. Observational studies have provided some insights into associative interactions between genetic or phenotypic variation and diet and their impact on health; however, very few human experimental studies have addressed these relationships. Dietary interventions that test prescribed diets in well-characterised study populations and that monitor system-wide responses (ideally using several omics platforms) are needed to make correlation-causation connections and to characterise phenotypes under controlled conditions. Given the growth in our knowledge, there is the potential to develop personalised dietary recommendations. However, developing these recommendations assumes that an improved understanding of the phenotypic complexities of individuals and their responses to the complexities of their diets will lead to a sustainable, effective approach to promote health and prevent disease - therein lies our challenge.

Within-person variation in the postprandial lipemic response of healthy adults

BACKGROUND

The response to dietary fat plays a key role in metabolic health. Although this can vary widely between individuals, variation within an individual and the associated contribution of phenotypic and genotypic factors to this variation are less defined.

OBJECTIVES

The objectives were to quantify within-person variation in triacylglycerol response by means of a novel variation score (S(v)) and to explore the phenotypic and genotypic factors associated with this score.

DESIGN

Two consecutive 5-h oral-lipid-tolerance tests (OLTTs) were conducted in 51 healthy adults aged 18-60 y with a BMI (in kg/m²) of 18.5 to 49.8. Detailed body composition, physical function, biochemistry, and genotype data were gathered.

RESULTS

The postprandial triacylglycerol response profile did not differ (P = 0.64) across OLTTs for the group; nor did average concentrations of functional markers apolipoprotein C2 (P = 0.73) and apolipoprotein C3 (P = 0.74). S(v) was low in most (82%) of the adults and was significantly (P < 0.05) associated with age, fasting triacylglycerol, triacylglycerol AUC, and fasting nonessential fatty acids. Significant associations were also observed between S(v) and single nucleotide polymorphisms in 7 genes (APOA1, IL1α, IL1β, TLR4, TCF7L2, CCK1Rec, and STAT3) after correction for phenotypic differences.

CONCLUSIONS

This work showed that the within-person variability in postprandial lipemic response is low in most healthy adults. It also showed that variability in this response is associated with a defined set of phenotypic and genotypic characteristics.

1H NMR-based metabolic fingerprinting of urine metabolites after consumption of lingonberries (Vaccinium vitis-idaea) with a high-fat meal

The use of NMR metabolomics in clinical trials is growing; however, reports of postprandial experiments in humans are scarce. The present study investigated whether consumption of lingonberries as a supplement to an oil-rich meal modifies the postprandial fingerprints of human urine. Urine samples were analysed by (1)H NMR, and untargeted multivariate analysis was applied to the data for comprehensive fingerprinting. A clear separation of postprandial lingonberry meal samples was revealed. To evaluate statistical differences, a targeted approach was applied for the informative spectral areas. Significantly (p<0.05) increased levels of polyphenol metabolites, hippuric acid and 4-hydroxyhippuric acid, and decreased creatinine and dimethylamine levels were the major explanations for the grouping of the postprandial samples after the different meals. Thus, inclusion of polyphenol-rich lingonberry powder in a rapeseed oil-rich meal modifies the metabolic profile of urine which may be used to reveal both consumption of berries and health-promoting changes in the common metabolism.

Effects of chemosignals from sad tears and postprandial plasma on appetite and food intake in humans

Chemosignals from human body fluids may modulate biological functions in humans. The objective of this study was to examine whether chemosignals from human sad tears and postprandial plasma modulate appetite. We obtained fasting and postprandial plasma from male participants and sad tears and saline, which was trickled below the eyelids, from female volunteers. These samples were then randomly distributed to male participants to sniff with a band-aid containing 100 µl of each fluid on four consecutive days in a double-blind fashion. We checked appetite by a visual analogue scale (VAS) and food intake by measuring the consumption of a test meal. In addition, the serum levels of total testosterone and LH were measured. Twenty men (mean age 26.3±4.6 years) were enrolled in this study. They could not discriminate between the smell of fasting and postprandial plasma and the smell of sad tears and trickled saline. Appetite and the amount of food intake were not different between the groups. Although the VAS ratings of appetite correlated with the food intake upon sniffing fasting plasma, postprandial plasma, and trickled saline, there was no such correlation upon sniffing sad tears. In addition, the decrease in serum testosterone levels from the baseline was greater with sad tears than with the trickled saline (−28.6±3.3% vs. −14.0±5.2%; P = 0.019). These data suggest that chemosignals from human sad tears and postprandial plasma do not appear to reduce appetite and food intake. However, further studies are necessary to examine whether sad tears may alter the appetite-eating behavior relation.

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

We introduce the metabolomics and proteomics based Postprandial Challenge Test (PCT) to quantify the postprandial response of multiple metabolic processes in humans in a standardized manner. The PCT comprised consumption of a standardized 500 ml dairy shake containing respectively 59, 30 and 12 energy percent lipids, carbohydrates and protein. During a 6 h time course after PCT 145 plasma metabolites, 79 proteins and 7 clinical chemistry parameters were quantified. Multiple processes related to metabolism, oxidation and inflammation reacted to the PCT, as demonstrated by changes of 106 metabolites, 31 proteins and 5 clinical chemistry parameters. The PCT was applied in a dietary intervention study to evaluate if the PCT would reveal additional metabolic changes compared to non-perturbed conditions. The study consisted of a 5-week intervention with a supplement mix of anti-inflammatory compounds in a crossover design with 36 overweight subjects. Of the 231 quantified parameters, 31 had different responses over time between treated and control groups, revealing differences in amino acid metabolism, oxidative stress, inflammation and endocrine metabolism. The results showed that the acute, short term metabolic responses to the PCT were different in subjects on the supplement mix compared to the controls. The PCT provided additional metabolic changes related to the dietary intervention not observed in non-perturbed conditions. Thus, a metabolomics based quantification of a standardized perturbation of metabolic homeostasis is more informative on metabolic status and subtle health effects induced by (dietary) interventions than quantification of the homeostatic situation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0320-5) contains supplementary material, which is available to authorized users.

Variation in metabolic responses to meal challenges differing in glycemic index in healthy women: Is it meaningful?

BACKGROUND

Established clinical tests are commonly used in disease diagnosis, but tools that enhance identification of metabolic dysfunctions are needed. This study was conducted to identify typical and atypical metabolite temporal patterns in response to paired meal challenge tests.

DESIGN

Metabolic responses to high and low glycemic index (GI) meals were tested in 24 healthy pre-menopausal women, aged 20-50 y, with BMI of 25-30 kg/m2 using a cross-over design. On test days, blood glucose, insulin, leptin and non-esterified fatty acids were measured after an overnight fasting, and for 8 h following test meal consumption. The data were range scaled, and multivariate statistics were used to assess the presence of distinct response groups to the meal challenge tests.

RESULTS

As expected, participants showed higher circulating glucose and insulin in response to the high GI compared to the low GI meal challenge. However, using range-scaling and Principal Component Analysis, three distinct groups were identified based on differential responses to the paired challenges. Members of the most populated group (n = 18) displayed little deviation from the expected response to the two meal challenges. Two minor groups (n = 3/group) with distinct responses were observed, one suggestive of sub-clinical insulin resistance, and the other suggestive of hyperleptinemia.

CONCLUSIONS

The differential responses of glucose, insulin and leptin to low and high glycemic test meals revealed three response groups. Dietary intervention studies traditionally evaluate group responses, and aim to identify the overall effect in the population studied. In contrast, our study analyzed the variance in the meal challenge responses, using an integrated physiological approach, rather than a reductionist approach. This phenotyping approach may be useful for detecting subclinical metabolic dysfunctions, and it could contribute to improved personalized nutrition management. This study is registered in ClinicalTrials.gov, record #200210295.

The Effect of LC-MS Data Preprocessing Methods on the Selection of Plasma Biomarkers in Fed vs. Fasted Rats

The metabolic composition of plasma is affected by time passed since the last meal and by individual variation in metabolite clearance rates. Rat plasma in fed and fasted states was analyzed with liquid chromatography quadrupole-time-of-flight mass spectrometry (LC-QTOF) for an untargeted investigation of these metabolite patterns. The dataset was used to investigate the effect of data preprocessing on biomarker selection using three different softwares, MarkerLynx^TM, MZmine, XCMS along with a customized preprocessing method that performs binning of m/z channels followed by summation through retention time. Direct comparison of selected features representing the fed or fasted state showed large differences between the softwares. Many false positive markers were obtained from custom data preprocessing compared with dedicated softwares while MarkerLynx^TM provided better coverage of markers. However, marker selection was more reliable with the gap filling (or peak finding) algorithms present in MZmine and XCMS. Further identification of the putative markers revealed that many of the differences between the markers selected were due to variations in features representing adducts or daughter ions of the same metabolites or of compounds from the same chemical subclasses, e.g., lyso-phosphatidylcholines (LPCs) and lyso-phosphatidylethanolamines (LPEs). We conclude that despite considerable differences in the performance of the preprocessing tools we could extract the same biological information by any of them. Carnitine, branched-chain amino acids, LPCs and LPEs were identified by all methods as markers of the fed state whereas acetylcarnitine was abundant during fasting in rats.

Nutrigenomics and personalized diets: What will they mean for food?

The modern food system feeds six billion people with remarkable diversity, safety, and nutrition. Yet, the current rise in diet-related diseases is compromising health and devaluing many aspects of modern agriculture. Steps to increase the nutritional quality of individual foods will assist in personalizing health and in guiding individuals to achieve superior health. Nutrigenomics is the scientific field of the genetic basis for varying susceptibilities to disease and the diverse responses to foods. Although some of these genetic determinants will be simple and amenable to personal genotyping as the means to predict health, in practice most will not. As a result, genotyping will not be the secret to personalizing diet and health. Human assessment technologies from imaging to proteomics and metabolomics are providing tools to both understand and accurately assess the nutritional phenotype of individuals. The business models are also emerging to bring these assessment capabilities to industrial practice, in which consumers will know more about their personal health and seek personal solutions.

Getting personal: considering variable interindividual responsiveness to dietary lipid-lowering therapies

PURPOSE OF REVIEW

There is substantial interindividual variation in the response of blood lipids to dietary therapies. The purpose of this review is to highlight recent developments in identifying patient-specific factors that contribute to the significant heterogeneity of responsiveness in lipids to dietary changes and consumption of dietary bioactive compounds.

RECENT FINDINGS

Recent findings suggest that a variety of patient-specific physiological, pathological, environmental, and genetic factors influence the effectiveness of dietary lipid-lowering therapies.

SUMMARY

Although genetic markers of responsiveness will revolutionize future personalized nutrition therapies, current research priorities should emphasize the identification of readily accessible metabolic biomarkers of responsiveness in patient subgroups.

Effects of sample handling and storage on quantitative lipid analysis in human serum

There is sparse information about specific storage and handling protocols that minimize analytical error and variability in samples evaluated by targeted metabolomics. Variance components that affect quantitative lipid analysis in a set of human serum samples were determined. The effects of freeze-thaw, extraction state, storage temperature, and freeze-thaw prior to density-based lipoprotein fractionation were quantified. The quantification of high abundance metabolites, representing the biologically relevant lipid species in humans, was highly repeatable (with coefficients of variation as low as 0.01 and 0.02) and largely unaffected by 1-3 freeze-thaw cycles (with 0-8% of metabolites affected in each lipid class). Extraction state had effects on total lipid class amounts, including decreased diacylglycerol and increased phosphatidylethanolamine in thawed compared with frozen samples. The effects of storage temperature over 1 week were minimal, with 0-4% of metabolites affected by storage at 4 degrees C, -20 degrees C, or -80 degrees C in most lipid classes, and 19% of metabolites in diacylglycerol affected by storage at -20 degrees C. Freezing prior to lipoprotein fractionation by density ultracentrifugation decreased HDL free cholesterol by 37% and VLDL free fatty acid by 36%, and increased LDL cholesterol ester by 35% compared with fresh samples. These findings suggest that density-based fractionation should preferably be undertaken in fresh serum samples because up to 37% variability in HDL and LDL cholesterol could result from a single freeze-thaw cycle. Conversely, quantitative lipid analysis within unfractionated serum is minimally affected even with repeated freeze-thaw cycles.

Metabolomics for assessment of nutritional status

PURPOSE OF REVIEW

The current rise in diet-related diseases continues to be one of the most significant health problems facing both the developed and the developing world. The use of metabolomics - the accurate and comprehensive measurement of a significant fraction of important metabolites in accessible biological fluids - for the assessment of nutritional status is a promising way forward. The basic toolset, targets and knowledge are all being developed in the emerging field of metabolomics, yet important knowledge and technology gaps will need to be addressed in order to bring such assessment to practice.

RECENT FINDINGS

Dysregulation within the principal metabolic organs (e.g. intestine, adipose, skeletal muscle and liver) are at the center of a diet-disease paradigm that includes metabolic syndrome, type 2 diabetes and obesity. The assessment of both essential nutrient status and the more comprehensive systemic metabolic response to dietary, lifestyle and environmental influences (e.g. metabolic phenotype) are necessary for the evaluation of status in individuals that can identify the multiple targets of intervention needed to address metabolic disease.

SUMMARY

The first proofs of principle building the knowledge to bring actionable metabolic diagnostics to practice through metabolomics are now appearing.