Metabolic Trajectories Following Contrasting Prudent and Western Diets from Food Provisions: Identifying Robust Biomarkers of Short-Term Changes in Habitual Diet

Oxidative gaseous air pollutant exposure interacts with PNPLA3-I148M genotype to influence liver fat fraction and multi-omics profiles in young adults

PNPLA3-I148M genotype is the strongest predictive single-nucleotide polymorphism for liver fat. We examine whether PNPLA3-I148M modifies associations between oxidative gaseous air pollutant exposure (Oxwt) with i) liver fat and ii) multi-omics profiles of miRNAs and metabolites linked to liver fat. Participants were 69 young adults (17-22 years) from the Meta-AIR cohort. Prior-month residential Oxwt exposure (redox-weighted oxidative capacity of nitrogen dioxide and ozone) was spatially interpolated from monitoring stations via inverse-distance-squared weighting. Liver fat fraction was assessed by MRI. Serum miRNAs and metabolites were assayed via NanoString nCounter and LC-HRMS, respectively. Multi-omics factor analysis (MOFA) was used to identify latent factors with shared variance across omics layers. Multivariable linear regression models adjusted for age, sex, body mass index, and genotype with liver fat or MOFA factors as an outcome and examined PNPLA3 (rs738409; CC/CG vs. GG) as a multiplicative interaction term. Overall, a standard deviation difference in Oxwt exposure was associated with 8.9% relative increase in liver fat (p = 0.04) and this relationship differed by PNPLA3 genotype (p-value for interaction term: pintx<0.001), whereby relative increases in liver fat for GG and CC/CG participants were 71.8% and 2.4%, respectively. There was no main effect of Oxwt on MOFA Factor 1 expression (p = 0.85), but there was an interaction with PNPLA3 genotype (pintx = 0.01), whereby marginal slopes were 0.211 and -0.017 for GG and CC/CG participants, respectively. MOFA Factor 1 in turn was associated with liver fat (p = 0.006). MOFA Factor 1 miRNAs targeted genes in Fatty Acid Biosynthesis and Metabolism and Lysine Degradation pathways. MOFA Factor 9 was also associated with liver fat and was comprised of branched-chain keto acid and amino acid metabolites. The effects of Oxwt exposure on liver fat is exacerbated in young adults with two PNPLA3 risk alleles, potentially through differential effects on miRNA and/or metabolite profiles.

A Software Tool for Rapid and Automated Preprocessing of Large-Scale Serum Metabolomic Data by Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry

Mass spectrometry (MS)-based metabolomics often rely on separation techniques when analyzing complex biological specimens to improve method resolution, metabolome coverage, quantitative performance, and/or unknown identification. However, low sample throughput and complicated data preprocessing procedures remain major barriers to affordable metabolomic studies that are scalable to large populations. Herein, we introduce PeakMeister as a new software tool in the R statistical environment to enable standardized processing of serum metabolomic data acquired by multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS), a high-throughput separation platform (<4 min/sample) which takes advantage of a serial injection format of 13 samples within a single analytical run. We performed a rigorous validation of PeakMeister by analyzing 47 cationic metabolites consistently measured in 5,000 serum and 420 quality control samples from the Brazilian National Survey on Child Nutrition (ENANI-2019) comprising a total of 224,983 metabolite peaks acquired in 40 days across three batches over an eight-month period. A migration time index using a panel of 11 internal standards was introduced to correct for large variations in migration times, which allowed for reliable peak annotation, peak integration, and sample position assignment for serum metabolites having two flanking internal standards or a single comigrating stable-isotope internal standard. PeakMeister accelerated data preprocessing times by 30-fold compared to manual processing of MSI-CE-MS data by an experienced analyst using vendor software, while also achieving excellent peak annotation fidelity (median accuracy >99.9%), acceptable intermediate precision (median CV = 16.0%), consistent metabolite peak integration (mean bias = -2.1%), and good mutual agreement when quantifying 16 plasma metabolites from NIST SRM-1950 (mean bias = -1.3%). Reference ranges are also reported for 40 serum metabolites in a national nutritional survey of Brazilian children under 5 years of age from the ENANI-2019 study. MSI-CE-MS in conjunction with PeakMeister allows for rapid and automated processing of large-scale metabolomic studies that tolerate nonlinear migration time shifts without complicated dynamic time warping or effective mobility scale transformations.

Dietary Assessment and Metabolomic Methodologies in Human Feeding Studies: A Scoping Review

Dietary metabolomics is a relatively objective approach to identifying new biomarkers of dietary intake and for use alongside traditional methods. However, methods used across dietary feeding studies vary, thus making it challenging to compare results. The objective of this study was to synthesize methodological components of controlled human feeding studies designed to quantify the diet-related metabolome in biospecimens, including plasma, serum, and urine after dietary interventions. Six electronic databases were searched. Included studies were as follows: 1) conducted in healthy adults; 2) intervention studies; 3) feeding studies focusing on dietary patterns; and 4) measured the dietary metabolome. From 12,425 texts, 50 met all inclusion criteria. Interventions were primarily crossover (n = 25) and parallel randomized controlled trials (n = 22), with between 8 and 395 participants. Seventeen different dietary patterns were tested, with the most common being the "High versus Low-Glycemic Index/Load" pattern (n = 11) and "Typical Country Intake" (n = 11); with 32 providing all or the majority (90%) of food, 16 providing some food, and 2 providing no food. Metabolites were identified in urine (n = 31) and plasma/serum (n = 30). Metabolites were quantified using liquid chromatography, mass spectroscopy (n = 31) and used untargeted metabolomics (n = 37). There was extensive variability in the methods used in controlled human feeding studies examining the metabolome, including dietary patterns tested, biospecimen sample collection, and metabolomic analysis techniques. To improve the comparability and reproducibility of controlled human feeding studies examining the metabolome, it is important to provide detailed information about the dietary interventions being tested, including information about included or restricted foods, food groups, and meal plans provided. Strategies to control for individual variability, such as a crossover study design, statistical adjustment methods, dietary-controlled run-in periods, or providing standardized meals or test foods throughout the study should also be considered. The protocol for this review has been registered at Open Science Framework (https://doi.org/10.17605/OSF.IO/DAHGS).

The Relationship Between Diet, Gut Microbiota, and Serum Metabolome of South Asian Infants at 1 Year

BACKGROUND

Diet is known to affect the gut microbiota and the serum metabolome in adults, but this has not been fully explored in infants. Infancy is an important developmental period that may influence a person's long-term health. Infant development can be affected by diet, which also interacts with the developing gut microbiota.

OBJECTIVES

This study aimed to explore the associations between diet, the gut microbiota, and the serum metabolome of 1-y-old infants with the overarching goal of identifying serum biomarkers of diet and/or the gut microbiota.

METHODS

We derived dietary patterns of 1-y-old infants (n = 182) participating in the Canadian South Asian Birth Cohort (START) study. We compared gut microbiota α-diversity and β-diversity and taxa relative abundance from 16S rRNA gene profiles with dietary patterns (PERMANOVA, Envfit) and investigated diet-serum metabolite associations using a multivariate analysis (partial least squares-discriminant analysis) and univariate analysis (t test). We explored the effect of nondietary factors on diet-serum metabolite relationships by incorporating diet, the gut microbiota, and maternal, perinatal, and infant characteristics in a multivariable forward stepwise regression. We replicated this analysis in White European infants, from the CHILD Cohort Study (n = 81).

RESULTS

A dietary pattern characterized by formula consumption and negatively associated with breastfeeding most strongly predicted variation in the gut microbiota (R² = 0.109) and serum metabolome (R² = 0.547). Breastfed participants showed higher abundance of microbes from the genera Bifidobacterium (3.29 log2-fold) and Lactobacillus (7.93 log2-fold) and higher median concentrations of the metabolites S-methylcysteine (1.38 μM) and tryptophan betaine (0.43 μM) than nonbreastfed participants. Formula consuming infants showed higher median concentrations of branched-chain/aromatic amino acids (average 48.3 μM) than non-formula-consuming infants.

CONCLUSIONS

Formula consumption and breastfeeding most strongly predicted the serum metabolites of 1-y-old infants, even when the gut microbiota, solid food consumption, and other covariates were considered.

Assessing Adherence to Healthy Dietary Habits Through the Urinary Food Metabolome: Results From a European Two-Center Study

Background

Diet is one of the most important modifiable lifestyle factors in human health and in chronic disease prevention. Thus, accurate dietary assessment is essential for reliably evaluating adherence to healthy habits.

Objectives

The aim of this study was to identify urinary metabolites that could serve as robust biomarkers of diet quality, as assessed through the Alternative Healthy Eating Index (AHEI-2010).

Design

We set up two-center samples of 160 healthy volunteers, aged between 25 and 50, living as a couple or family, with repeated urine sampling and dietary assessment at baseline, and 6 and 12 months over a year. Urine samples were subjected to large-scale metabolomics analysis for comprehensive quantitative characterization of the food-related metabolome. Then, lasso regularized regression analysis and limma univariate analysis were applied to identify those metabolites associated with the AHEI-2010, and to investigate the reproducibility of these associations over time.

Results

Several polyphenol microbial metabolites were found to be positively associated with the AHEI-2010 score; urinary enterolactone glucuronide showed a reproducible association at the three study time points [false discovery rate (FDR): 0.016, 0.014, 0.016]. Furthermore, other associations were found between the AHEI-2010 and various metabolites related to the intake of coffee, red meat and fish, whereas other polyphenol phase II metabolites were associated with higher AHEI-2010 scores at one of the three time points investigated (FDR < 0.05 or β ≠ 0).

Conclusion

We have demonstrated that urinary metabolites, and particularly microbiota-derived metabolites, could serve as reliable indicators of adherence to healthy dietary habits.

Clinical Trail Registration

www.ClinicalTrials.gov, Identifier: NCT03169088.

Sources of Variation in Food-Related Metabolites during Pregnancy

The extent to which variation in food-related metabolites are attributable to non-dietary factors remains unclear, which may explain inconsistent food-metabolite associations observed in population studies. This study examined the association between non-dietary factors and the serum concentrations of food-related biomarkers and quantified the amount of variability in metabolite concentrations explained by non-dietary factors. Pregnant women (n = 600) from two Canadian birth cohorts completed a validated semi-quantitative food frequency questionnaire, and serum metabolites were measured by multisegment injection-capillary electrophoresis-mass spectrometry. Hierarchical linear modelling and principal component partial R-square (PC-PR2) were used for data analysis. For proline betaine and DHA (mainly exogenous), citrus foods and fish/fish oil intake, respectively, explained the highest proportion of variability relative to non-dietary factors. The unique contribution of dietary factors was similar (15:0, 17:0, hippuric acid, TMAO) or lower (14:0, tryptophan betaine, 3-methylhistidine, carnitine) compared to non-dietary factors (i.e., ethnicity, maternal age, gestational age, pre-pregnancy BMI, physical activity, and smoking) for metabolites that can either be produced endogenously, biotransformed by gut microbiota, and/or derived from multiple food sources. The results emphasize the importance of adjusting for non-dietary factors in future analyses to improve the accuracy and precision of the measures of food intake and their associations with health and disease.

The Integration of Metabolomics with Other Omics: Insights into Understanding Prostate Cancer

Our understanding of prostate cancer (PCa) has shifted from solely caused by a few genetic aberrations to a combination of complex biochemical dysregulations with the prostate metabolome at its core. The role of metabolomics in analyzing the pathophysiology of PCa is indispensable. However, to fully elucidate real-time complex dysregulation in prostate cells, an integrated approach based on metabolomics and other omics is warranted. Individually, genomics, transcriptomics, and proteomics are robust, but they are not enough to achieve a holistic view of PCa tumorigenesis. This review is the first of its kind to focus solely on the integration of metabolomics with multi-omic platforms in PCa research, including a detailed emphasis on the metabolomic profile of PCa. The authors intend to provide researchers in the field with a comprehensive knowledge base in PCa metabolomics and offer perspectives on overcoming limitations of the tool to guide future point-of-care applications.

Serum metabolomic signatures of gestational diabetes in South Asian and white European women

INTRODUCTION

This study aimed to identify serum metabolomic signatures associated with gestational diabetes mellitus (GDM), and to examine if ethnic-specific differences exist between South Asian and white European women.

RESEARCH DESIGN AND METHODS

Prospective cohort study with a nested case-control analysis of 600 pregnant women from two Canadian birth cohorts; using an untargeted approach, 63 fasting serum metabolites were measured and analyzed using multisegment injection-capillary electrophoresis-mass spectrometry. Multivariate logistic regression modeling was conducted overall and by cohort.

RESULTS

The proportion of women with GDM was higher in South Asians (27.1%) compared with white Europeans (17.9%). Several amino acid, carbohydrate, and lipid pathways related to GDM were common to South Asian and white European women. Elevated circulating concentrations of glutamic acid, propionylcarnitine, tryptophan, arginine, 2-hydroxybutyric acid, 3-hydroxybutyric acid, and 3-methyl-2-oxovaleric acid were associated with higher odds of GDM, while higher glutamine, ornithine, oxoproline, cystine, glycine with lower odds of GDM. Per SD increase in glucose concentration, the odds of GDM increased (OR=2.07, 95% CI 1.58 to 2.71), similarly for metabolite ratios: glucose to glutamine (OR=2.15, 95% CI 1.65 to 2.80), glucose to creatinine (OR=1.79, 95% CI 1.39 to 2.32), and glutamic acid to glutamine (OR=1.46, 95% CI 1.16 to 1.83). South Asians had higher circulating ratios of glucose to glutamine, glucose to creatinine, arginine to ornithine, and citrulline to ornithine, compared with white Europeans.

CONCLUSIONS

We identified a panel of serum metabolites implicated in GDM pathophysiology, consistent in South Asian and white European women. The metabolic alterations leading to larger ratios of glucose to glutamine, glucose to creatinine, arginine to ornithine, and citrulline to ornithine in South Asians likely reflect the greater burden of GDM among South Asians compared with white Europeans.

Plasma Metabolites Associated with a Protein-Rich Dietary Pattern: Results from the OmniHeart Trial

Scope

Lack of biomarkers is a challenge for the accurate assessment of protein intake and interpretation of observational study data. The study aims to identify biomarkers of a protein‐rich dietary pattern.

Methods and Results

The Optimal Macronutrient Intake Trial to Prevent Heart Disease (OmniHeart) trial is a randomized cross‐over feeding study which tested three dietary patterns with varied macronutrient content (carbohydrate‐rich; protein‐rich with about half from plant sources; and unsaturated fat‐rich). In 156 adults, differences in log‐transformed plasma metabolite levels at the end of the protein‐ and carbohydrate‐rich diet periods using paired t‐tests is examined. Partial least‐squares discriminant analysis is used to identify a set of metabolites which are influential in discriminating between the protein‐rich versus carbohydrate‐rich dietary patterns. Of 839 known metabolites, 102 metabolites differ significantly between the protein‐rich and the carbohydrate‐rich dietary patterns after Bonferroni correction, the majority of which are lipids (n = 35), amino acids (n = 27), and xenobiotics (n = 24). Metabolites which are the most influential in discriminating between the protein‐rich and the carbohydrate‐rich dietary patterns represent plant protein intake, food or beverage intake, and preparation methods.

Conclusions

The study identifies many plasma metabolites associated with the protein‐rich dietary pattern. If replicated, these metabolites may be used to assess level of adherence to a similar dietary pattern.

Dietary determinants of healthy/unhealthy metabolic phenotype in individuals with normal weight or overweight/obesity: a systematic review

Objectives: Nutritional factors are amongst the major determinants in the onset and development of obesity and metabolic complications. Nevertheless, the dietary determinants of metabolic health are not completely elucidated. The aim of this systematic review is to investigate nutritional and dietary factors that may contribute to metabolic heterogeneity in individuals with obesity or normal weight. Methods: A literature search was performed in PubMed, Scopus, EMBASE, and google scholar databases until August 2021, to locate studies that examined metabolic health and its association with intakes of specific foods or food groups, nutrient intakes or status, as well as adherence to certain dietary patterns. Two researchers had independently screened titles and abstracts, examined full-text studies, conducted data extraction, and evaluated their quality using the Newcastle-Ottawa Scale. Results: Twenty-seven studies, with a total of 39518 subjects, were included. Of these studies, 11 articles evaluated the association between different dietary patterns and metabolic phenotypes, while 15 had investigated the association of single food/nutrients intakes or nutrient status with metabolic phenotype, and one paper evaluated the association of dietary inflammatory index with metabolic health. The findings of these studies propose that healthy dietary patterns such as the Mediterranean pattern, Dietary Approaches to Stop Hypertension, and population-derived patterns (such as the "Healthy" and "Fruit and vegetable" patterns) were associated with higher odds of the metabolically healthy phenotype. Higher intakes of fruits, vegetables, dairy products, coffee/tea, vitamin D, magnesium, and flavonoids, were suggested to lower the risk of developing metabolically unhealthy phenotype, while, higher consumption of saturated fat, carbohydrate and sugar-sweetened beverages, fast foods, organ meats, and a pro-inflammatory diet increased the risk. Conclusion: Results from published studies, which were mostly cross-sectional, suggest that higher adherence to unhealthier dietary patterns, characterized by the consumption of refined and processed foods, was associated with a lower likelihood of having a healthy metabolic phenotype, while the opposite was observed for healthier dietary patterns. Findings may be used in developing nutritional strategies aimed at improving metabolic health in the population.

OUP accepted manuscript

Context

Most methods for assessing dietary intake have considerable measurement error. Dietary biomarkers are objective tools for dietary assessment. Dietary biomarkers of dietary patterns have not been well described, despite modern dietary guidelines endorsing dietary patterns.

Objective

This systematic review sought to describe the dietary biomarkers commonly used to assess dietary patterns, and the novel biomarkers of dietary patterns identified by exploratory studies.

Data Sources

MEDLINE, Embase, Cochrane Central, PreMEDLINE, and CINAHL databases were searched.

Data Extraction

Data extraction and bias assessment were undertaken in duplicate.

Data Analysis

A qualitative approach was applied, without statistical analysis.

Conclusion

In controlled settings, dietary biomarkers of single nutrients or of individual foods or food groups are commonly used to assess compliance with dietary patterns. However, currently, there are no dietary biomarkers or biomarker profiles that are able to identify the specific dietary pattern that has been consumed by an individual. Future work should seek to validate novel dietary biomarkers and biomarker profiles that are indicative of specific dietary patterns and their characteristics. A dietary biomarker panel consisting of multiple biomarkers is almost certainly necessary to capture the complexity of dietary patterns.

Systematic Review Registration

PROSPERO registration no. CRD42019129839.

Nutritional Metabolomics and the Classification of Dietary Biomarker Candidates: A Critical Review

Recent advances in metabolomics allow for more objective assessment of contemporary food exposures, which have been proposed as an alternative or complement to self-reporting of food intake. However, the quality of evidence supporting the utility of dietary biomarkers as valid measures of habitual intake of foods or complex dietary patterns in diverse populations has not been systematically evaluated. We reviewed nutritional metabolomics studies reporting metabolites associated with specific foods or food groups; evaluated the interstudy repeatability of dietary biomarker candidates; and reported study design, metabolomic approach, analytical technique(s), and type of biofluid analyzed. A comprehensive literature search of 5 databases (PubMed, EMBASE, Web of Science, BIOSIS, and CINAHL) was conducted from inception through December 2020. This review included 244 studies, 169 (69%) of which were interventional studies (9 of these were replicated in free-living participants) and 151 (62%) of which measured the metabolomic profile of serum and/or plasma. Food-based metabolites identified in ≥1 study and/or biofluid were associated with 11 food-specific categories or dietary patterns: 1) fruits; 2) vegetables; 3) high-fiber foods (grain-rich); 4) meats; 5) seafood; 6) pulses, legumes, and nuts; 7) alcohol; 8) caffeinated beverages, teas, and cocoas; 9) dairy and soya; 10) sweet and sugary foods; and 11) complex dietary patterns and other foods. We conclude that 69 metabolites represent good candidate biomarkers of food intake. Quantitative measurement of these metabolites will advance our understanding of the relation between diet and chronic disease risk and support evidence-based dietary guidelines for global health.

Comprehensive Metabolome and Volatilome Analyses in Eggplant and Tomato Reveal Their Differential Responses to Tuta absoluta Infestation

The South American tomato pinworm, Tuta absoluta, is one of the most destructive insect pests in Solanaceae crops, particularly in tomatoes. Current methods of management have proven somewhat effective but still require a more efficacious management strategy to limit its havoc on crop yield. Tomato is much more predisposed to T. absoluta as compared with other plants such as eggplants, but the underlying causes have not been fully determined. We conducted this study to unravel the volatile organic compounds (VOCs) and primary/secondary metabolites that account for the differential response of tomatoes and eggplants to T. absoluta infestation. We performed widely targeted comparative metabolome and volatilome profiling by ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and headspace solid-phase microextraction coupled to gas chromatography-mass spectrometry (HS-SPME/GC-MS), respectively, on eggplants and tomatoes under control and T. absoluta infestation conditions. Overall, 141 VOCs and 797 primary/secondary metabolites were identified, largely dominated by aldehyde, alcohols, alkanes, amine, aromatics, a heterocyclic compound, ketone, olefin, phenol, and terpenes. Most of the VOCs and primary/secondary metabolites from the terpene class were largely differentially regulated in eggplants compared with tomatoes. Eggplants emitted several compounds that were lower or completely absent in tomatoes either under control conditions or after T. absoluta infestation. The results from an electroantennogram showed that 35 differentially accumulated VOCs could elicit female T. absoluta response, implying that these volatile compounds significantly alter the behavior of this pest. These findings demonstrated that differentially accumulated metabolites and volatile compounds play major roles in eggplant resistance to T. absoluta infestation as these compounds were regulated upon attack by T. absoluta. Our findings can assist in integrated pest management efforts by developing appropriate control measures against T. absoluta in Solanaceae production.

New Advances in Tissue Metabolomics: A Review

Metabolomics offers a hypothesis-generating approach for biomarker discovery in clinical medicine while also providing better understanding of the underlying mechanisms of chronic diseases. Clinical metabolomic studies largely rely on human biofluids (e.g., plasma, urine) as a more convenient specimen type for investigation. However, biofluids are non-organ specific reflecting complex biochemical processes throughout the body, which may complicate biochemical interpretations. For these reasons, tissue metabolomic studies enable deeper insights into aberrant metabolism occurring at the direct site of disease pathogenesis. This review highlights new advances in metabolomics for ex vivo analysis, as well as in situ imaging of tissue specimens, including diverse tissue types from animal models and human participants. Moreover, we discuss key pre-analytical and post-analytical challenges in tissue metabolomics for robust biomarker discovery with a focus on new methodological advances introduced over the past six years, including innovative clinical applications for improved screening, diagnostic testing, and therapeutic interventions for cancer.

Post-weight loss changes in fasting appetite- and energy balance-related hormone concentrations and the effect of the macronutrient content of a weight maintenance diet: a randomised controlled trial

PURPOSE

We investigated the effects of the macronutrient composition of diets with differing satiety values on fasting appetite-related hormone concentrations after weight loss and examined whether the hormone secretion adapted to changes in body fat mass (FM) and fat-free mass (FFM) during the weight maintenance period (WM).

METHODS

Eighty-two men and women with obesity underwent a 7-week very-low-energy diet (VLED) and were then randomised to a higher-satiety food (HSF) group or a lower-satiety food (LSF) group during 24-weeks of the WM. The groups consumed isoenergetic foods with different satiety ratings and macronutrient compositions.

RESULTS

During the WM, the HSF group consumed more protein and dietary fibre and less fat than the LSF group, but the groups showed similar changes in body weight and fasting appetite-related hormones. In the whole study sample, VLED induced 12 kg (p < 0.001) weight loss. At the end of the WM, weight regain was 1.3 kg (p = 0.004), ghrelin concentration increased, whereas leptin, insulin, and glucose concentrations decreased compared to pre-VLED levels (p < 0.001 for all). Peptide YY did not differ from pre-VLED levels. Changes in ghrelin levels were inversely associated with changes in FFM during weeks 0-12 of the WM (p = 0.002), while changes in leptin and insulin levels were positively associated with changes in FM during weeks 0-12 (p = 0.015 and p = 0.038, respectively) and weeks 12-24 (p < 0.001 and p = 0.022) of the WM.

CONCLUSIONS

The macronutrient composition of an isoenergetic WM diet did not affect fasting appetite-related hormone concentrations. Leptin and insulin adjusted to the reduced FM, whereas ghrelin reflected FFM during the first months of the WM.

TRIAL REGISTRATION

isrctn.com, ID 67529475.

Urinary Metabolites Enable Differential Diagnosis and Therapeutic Monitoring of Pediatric Inflammatory Bowel Disease

Rates of pediatric Crohn's disease (CD) and ulcerative colitis (UC) are increasing globally. Differentiation of these inflammatory bowel disease (IBD) subtypes however can be challenging when relying on invasive endoscopic approaches. We sought to identify urinary metabolic signatures of pediatric IBD at diagnosis, and during induction treatment. Nontargeted metabolite profiling of urine samples from CD (n = 18) and UC (n = 8) in a pediatric retrospective cohort study was performed using multisegment injection-capillary electrophoresis-mass spectrometry. Over 122 urinary metabolites were reliably measured from pediatric IBD patients, and unknown metabolites were identified by tandem mass spectrometry. Dynamic changes in sum-normalized urinary metabolites were also monitored following exclusive enteral nutrition (EEN) or corticosteroid therapy (CS) in repeat urine samples collected over 8 weeks. Higher urinary excretion of indoxyl sulfate, hydroxyindoxyl sulfate, phenylacetylglutamine, and sialic acid were measured in CD as compared to UC patients, but lower threonine, serine, kynurenine, and hypoxanthine (p < 0.05). Excellent discrimination of CD from UC was achieved based on the urinary serine:indoxylsulfate ratio (AUC = 0.972; p = 3.21 × 10^-5). Urinary octanoyl glucuronide, pantothenic acid, and pyridoxic acid were also identified as specific dietary biomarkers of EEN in pediatric IBD patients who achieved clinical remission. This work may complement or replace existing strategies in the diagnosis and early management of children with IBD.

The maternal serum metabolome by multisegment injection-capillary electrophoresis-mass spectrometry: a high-throughput platform and standardized data workflow for large-scale epidemiological studies

A standardized data workflow is described for large-scale serum metabolomic studies using multisegment injection-capillary electrophoresis-mass spectrometry. Multiplexed separations increase throughput (<4 min/sample) for quantitative determination of 66 polar/ionic metabolites in serum filtrates consistently detected (coefficient of variance (CV) <30%) with high frequency (>75%) from a multi-ethnic cohort of pregnant women (n = 1,004). We outline a validated protocol implemented in four batches over a 7-month period that includes details on preventive maintenance, sample workup, data preprocessing and metabolite authentication. We achieve stringent quality control (QC) and robust batch correction of long-term signal drift with good mutual agreement for a wide range of metabolites, including serum glucose as compared to a clinical chemistry analyzer (mean bias = 11%, n = 668). Control charts for a recovery standard (mean CV = 12%, n = 2,412) and serum metabolites in QC samples (median CV = 13%, n = 202) demonstrate acceptable intermediate precision with a median intraclass coefficient of 0.87. We also report reference intervals for 53 serum metabolites from a diverse population of women in their second trimester of pregnancy.

Urine Metabolites Associated with the Dietary Approaches to Stop Hypertension (DASH) Diet: Results from the DASH-Sodium Trial

SCOPE

Serum metabolomic markers of the Dietary Approaches to Stop Hypertension (DASH) diet are previously reported. In an independent study, the similarity of urine metabolomic markers are investigated.

METHODS AND RESULTS

In the DASH-Sodium trial, participants are randomly assigned to the DASH diet or control diet, and received three sodium interventions (high, intermediate, low) within each randomized diet group in random order for 30 days each. Urine samples are collected at the end of each intervention period and analyzed for 938 metabolites. Two comparisons are conducted: 1) DASH-high sodium (n = 199) versus control-high sodium (n = 193), and 2) DASH-low sodium (n = 196) versus control-high sodium. Significant metabolites identified using multivariable linear regression are compared and the top 10 influential metabolites identified using partial least-squares discriminant analysis to the results from the DASH trial. Nine out of 10 predictive metabolites of the DASH-high sodium and DASH-low sodium diets are identical. Most candidate biomarkers from the DASH trial replicated. N-methylproline, chiro-inositol, stachydrine, and theobromine replicated as influential metabolites of DASH diets.

CONCLUSIONS

Candidate biomarkers of the DASH diet identified in serum replicated in urine. Replicated influential metabolites are likely to be objective biomarkers of the DASH diet.

Postprandial Dried Blood Spot-Based Nutritional Metabolomic Analysis Discriminates a High-Fat, High-Protein Meat-Based Diet from a High Carbohydrate Vegan Diet: A Randomized Controlled Crossover Trial

BACKGROUND

Due to the challenges associated with accurate monitoring of dietary intake in humans, nutritional metabolomics (including food intake biomarkers) analysis as a complementary tool to traditional dietary assessment methods has been explored. Food intake biomarker assessment using postprandial dried blood spot (DBS) collection can be a convenient and accurate means of monitoring dietary intake vs 24-hour urine collection.

OBJECTIVE

The objective of this study was to use nutritional metabolomics analysis to differentiate a high-fat, high-protein meat (HFPM) diet from a high-carbohydrate vegan (HCV) diet in postprandial DBS and 24-hour urine.

DESIGN

This was a randomized controlled crossover feeding trial.

PARTICIPANTS/SETTING

Participants were healthy young adult volunteers (n = 8) in California. The study was completed in August 2019.

INTERVENTION

The standardized isocaloric diet interventions included an HFPM and an HCV diet. Participants attended 2 intervention days, separated by a 2-week washout.

MAIN OUTCOME MEASURES

During each intervention day, a finger-prick blood sample was collected in the fasting state, 3 hours post breakfast, and 3 hours post lunch. Participants also collected their urine for 24 hours. DBS and urine samples were analyzed by ultra-performance liquid chromatography mass spectrometry to identify potential food intake biomarkers.

STATISTICAL ANALYSES PERFORMED

Principal component analysis for discriminatory analysis and univariate analysis using paired t tests were performed.

RESULTS

Principal component analysis found no discrimination of baseline DBS samples. In both the postprandial DBS and 24-hour urine, post-HFPM consumption had higher (P < 0.05) levels of acylcarnitines, creatine, and cis-trans hydroxyproline, and the HCV diet was associated with elevated sorbitol (P < 0.05). The HFPM diet had higher concentrations of triacylglycerols with fewer than 54 total carbons in DBS, and 24-hour urine had higher nucleoside mono- and di-phosphates (P < 0.05).

CONCLUSIONS

Nutritional metabolomics profiles of postprandial DBS and 24-hour urine collections were capable of differentiating the HFPM and HCV diets. The potential use of postprandial DBS-based metabolomic analysis deserves further investigation for dietary intake monitoring.

Serum Metabolites Associated with Healthy Diets in African Americans and European Americans

BACKGROUND

High diet quality is associated with a lower risk of chronic diseases. Metabolomics can be used to identify objective biomarkers of diet quality.

OBJECTIVES

We used metabolomics to identify serum metabolites associated with 4 diet indices and the components within these indices in 2 samples from African Americans and European Americans.

METHODS

We studied cross-sectional associations between known metabolites and Healthy Eating Index (HEI)-2015, Alternative Healthy Eating Index (AHEI)-2010, the Dietary Approaches to Stop Hypertension Trial (DASH) diet, alternate Mediterranean diet (aMED), and their components using untargeted metabolomics in 2 samples (n1 = 1,806, n2 = 2,056) of the Atherosclerosis Risk in Communities study (aged 45-64 y at baseline). Dietary intakes were assessed using an FFQ. We used multivariable linear regression models to examine associations between diet indices and serum metabolites in each sample, adjusting for participant characteristics. Metabolites significantly associated with diet indices were meta-analyzed across 2 samples. C-statistics were calculated to examine if these candidate biomarkers improved prediction of individuals in the highest compared with lowest quintile of diet scores beyond participant characteristics.

RESULTS

Seventeen unique metabolites (HEI: n = 6; AHEI: n = 5; DASH: n = 14; aMED: n = 2) were significantly associated with higher diet scores after Bonferroni correction in sample 1 and sample 2. Six of 17 significant metabolites [glycerate, N-methylproline, stachydrine, threonate, pyridoxate, 3-(4-hydroxyphenyl)lactate)] were associated with ≥1 dietary pattern. Candidate biomarkers of HEI, AHEI, and DASH distinguished individuals with highest compared with lowest quintile of diet scores beyond participant characteristics in samples 1 and 2 (P value for difference in C-statistics <0.02 for all 3 diet indices). Candidate biomarkers of aMED did not improve C-statistics beyond participant characteristics (P value = 0.930).

CONCLUSIONS

A considerable overlap of metabolites associated with HEI, AHEI, DASH, and aMED reflects the similar food components and similar metabolic pathways involved in the metabolism of healthy diets in African Americans and European Americans.

Maternal Diet and the Serum Metabolome in Pregnancy: Robust Dietary Biomarkers Generalizable to a Multiethnic Birth Cohort

BACKGROUND

Advances in metabolomics are anticipated to decipher associations between dietary exposures and health. Replication biomarker studies in different populations are critical to demonstrate generalizability.

OBJECTIVES

To identify and validate robust serum metabolites associated with diet quality and specific foods in a multiethnic cohort of pregnant women.

DESIGN

In this cross-sectional analysis of 3 multiethnic Canadian birth cohorts, we collected semiquantitative FFQ and serum data from 900 women at the second trimester of pregnancy. We calculated a diet quality score (DQS), defined as daily servings of "healthy" minus "unhealthy" foods. Serum metabolomics was performed by multisegment injection-capillary electrophoresis-mass spectrometry, and specific serum metabolites associated with maternal DQSs were identified. We combined the results across all 3 cohorts using meta-analysis to classify robust dietary biomarkers (r > ± 0.1; P < 0.05).

RESULTS

Diet quality was higher in the South Asian birth cohort (mean DQS = 7.1) than the 2 white Caucasian birth cohorts (mean DQS <3.2). Sixty-six metabolites were detected with high frequency (>75%) and adequate precision (CV <30%), and 47 were common to all cohorts. Hippuric acid was positively associated with healthy diet score in all cohorts, and with the overall DQS only in the primarily white Caucasian cohorts. We observed robust correlations between: 1) proline betaine-citrus foods; 2) 3-methylhistidine-red meat, chicken, and eggs; 3) hippuric acid-fruits and vegetables; 4) trimethylamine N-oxide (TMAO)-seafood, meat, and eggs; and 5) tryptophan betaine-nuts/legumes.

CONCLUSIONS

Specific serum metabolites reflect intake of citrus fruit/juice, vegetables, animal foods, and nuts/legumes in pregnant women independent of ethnicity, fasting status, and delays to storage across multiple collection centers. Robust biomarkers of overall diet quality varied by cohort. Proline betaine, 3-methylhistidine, hippuric acid, TMAO, and tryptophan betaine were robust dietary biomarkers for investigations of maternal nutrition in diverse populations.

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.

Serum Metabolic Signatures of Chronic Limb-Threatening Ischemia in Patients with Peripheral Artery Disease

Peripheral artery disease (PAD) is characterized by the atherosclerotic narrowing of lower limb vessels, leading to ischemic muscle pain in older persons. Some patients experience progression to advanced chronic limb-threatening ischemia (CLTI) with poor long-term survivorship. Herein, we performed serum metabolomics to reveal the mechanisms of PAD pathophysiology that may improve its diagnosis and prognosis to CLTI complementary to the ankle-brachial index (ABI) and clinical presentations. Non-targeted metabolite profiling of serum was performed by multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS) from age and sex-matched, non-diabetic, PAD participants who were recruited and clinically stratified based on the Rutherford classification into CLTI (n = 18) and intermittent claudication (IC, n = 20). Compared to the non-PAD controls (n = 20), PAD patients had lower serum concentrations of creatine, histidine, lysine, oxoproline, monomethylarginine, as well as higher circulating phenylacetylglutamine (p < 0.05). Importantly, CLTI cases exhibited higher serum concentrations of carnitine, creatinine, cystine and trimethylamine-N-oxide along with lower circulating fatty acids relative to well matched IC patients. Most serum metabolites associated with PAD progression were also correlated with ABI (r = ±0.24-0.59, p < 0.05), whereas the ratio of stearic acid to carnitine, and arginine to propionylcarnitine differentiated CLTI from IC with good accuracy (AUC = 0.87, p = 4.0 × 10^-5). This work provides new biochemical insights into PAD progression for the early detection and surveillance of high-risk patients who may require peripheral vascular intervention to prevent amputation and premature death.

Serum nonesterified fatty acids have utility as dietary biomarkers of fat intake from fish, fish oil, and dairy in women

Nutritional studies rely on various biological specimens for FA determination, yet it is unclear how levels of serum NEFAs correlate with other circulating lipid pools. Here, we used a high-throughput method (<4 min/sample) based on multisegment injection-nonaqueous capillary electrophoresis-mass spectrometry (MSI-NACE-MS) to investigate whether specific serum NEFAs have utility as biomarkers of dietary fat intake in women. We first identified circulating NEFAs correlated with long-term/habitual food intake among pregnant women with contrasting dietary patterns (n = 50). Acute changes in serum NEFA trajectories were also studied in nonpregnant women (n = 18) following high-dose (5 g/day) fish oil (FO) supplementation or isoenergetic sunflower oil placebo over 56 days. In the cross-sectional study, serum ω-3 FAs correlated with self-reported total ω-3 daily intake, notably EPA as its NEFA (r = 0.46; P = 0.001), whereas pentadecanoic acid was associated with full-fat dairy intake (r = 0.43; P = 0.002), outcomes consistent with results from total FA serum hydrolysates. In the intervention cohort, serum ω-3 NEFAs increased 2.5-fold from baseline within 28 days following FO supplementation, and this increase was most pronounced for EPA (P = 0.0004). Unlike for DHA, circulating EPA as its NEFA also strongly correlated to EPA concentrations measured from erythrocyte phospholipid hydrolysates (r = 0.66; P = 4.6 × 10-10) and was better suited to detect dietary nonadherence. We conclude that MSI-NACE-MS offers a rapid method to quantify serum NEFAs and objectively monitor dietary fat intake in women that is complementary to food-frequency questionnaires.

Metabolomics for improved treatment monitoring of phenylketonuria: urinary biomarkers for non-invasive assessment of dietary adherence and nutritional deficiencies

Management of phenylketonuria (PKU) requires lifelong restriction of phenylalanine (Phe) intake using specialized medical foods to prevent neurocognitive impairment in affected patients. However, dietary adherence is challenging to maintain while ensuring adequate nutrition, which can lead to sub-optimal clinical outcomes. Metabolomics offers a systematic approach to identify new biomarkers of disease progression in PKU when using urine as a surrogate for blood specimens that is more accurate than self-reported diet records. Herein, the plasma and urine metabolome of a cohort of classic PKU patients (median age = 11 years; n = 22) mainly prescribed (78%) a Phe-restricted diet were characterized using multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS). Overall, there was good mutual agreement between plasma Phe and tyrosine (Tyr) concentrations measured from PKU patients when using an amino acid analyzer based on UPLC-UV as compared to MSI-CE-MS with a mean bias of 12% (n = 82). Longitudinal measurements of recently diagnosed PKU infants (n = 3) revealed good long-term regulation of blood Phe with dietary management, and only occasional episodes exceeding the recommended therapeutic range (>360 μM) unlike older PKU patients. Plasma metabolomic studies demonstrated that non-adherent PKU patients had lower circulating concentrations of Tyr, arginine, 2-aminobutyric acid, and propionylcarnitine (q < 0.05, FDR) that were inversely correlated to Phe (r ≈ -0.600 to -0.830). Nontargeted metabolite profiling also revealed urinary biomarkers associated with poor dietary adherence among PKU patients, including elevated concentrations of catabolites indicative of Phe intoxication (e.g., phenylpyruvic acid, phenylacetylglutamine, hydroxyphenylacetic acid). Additionally, PKU patients with poor blood Phe control had lower excretion of urinary compounds derived from co-metabolism of Tyr due to microbiota activity (e.g., cresol sulfate, phenylsulfate), as well as several metabolites associated with inadequate nutrient intake, including low carnitine and B vitamin status (e.g., folic acid, vitamin B12). Interestingly, an unknown urinary metabolite was strongly correlated with Phe excretion in PKU patients (r = 0.861), which was subsequently identified as imidazole lactic acid when using high resolution MS/MS. Overall, urine profiling offers a non-invasive approach for better treatment monitoring of individual PKU patients, which can also guide the design of novel therapies that improve adherence to Phe-restricted diets without acquired nutritional deficiencies.

Circulating Pro- and Anti-Inflammatory Metabolites and Its Potential Role in Rheumatoid Arthritis Pathogenesis

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease that affects synovial joints, leading to inflammation, joint destruction, loss of function, and disability. Although recent pharmaceutical advances have improved the treatment of RA, patients often inquire about dietary interventions to improve RA symptoms, as they perceive pain and/or swelling after the consumption or avoidance of certain foods. There is evidence that some foods have pro- or anti-inflammatory effects mediated by diet-related metabolites. In addition, recent literature has shown a link between diet-related metabolites and microbiome changes, since the gut microbiome is involved in the metabolism of some dietary ingredients. But diet and the gut microbiome are not the only factors linked to circulating pro- and anti-inflammatory metabolites. Other factors including smoking, associated comorbidities, and therapeutic drugs might also modify the circulating metabolomic profile and play a role in RA pathogenesis. This article summarizes what is known about circulating pro- and anti-inflammatory metabolites in RA. It also emphasizes factors that might be involved in their circulating concentrations and diet-related metabolites with a beneficial effect in RA.

Effect of eating habits on obesity in adolescents: a study among Chinese college students

Objective

Obesity has been linked to cardiovascular disease, diabetes, and osteoarthritis. Obesity and overweight pose a serious threat to human health, with an estimated 190 million overweight and obese people worldwide. Thus, we investigated the influence of certain eating habits on weight among Chinese college students.

Methods

We conducted a cross-sectional survey of 536 college students in Shijiazhuang, China. The survey included questions about eating habits. We analyzed the relationship between participants’ responses and obesity.

Results

Sex, residence, speed of eating, number of meals eaten per day, and a diet high in sugar were found to be correlated with obesity. Our results suggest that increasing the number of meals per day, slowing down the pace of eating, and reducing the intake of high-sugar foods have potential benefits for reducing obesity among college students.

Conclusions

In the present study, we found that some dietary habits are related to the occurrence of obesity among college-aged individuals.