Metabolomic profiles as reliable biomarkers of dietary composition

The mediating role of key amino acid and vitamin metabolite ratios in the effects of 5 dietary habits on psoriatic arthritis: A Mendelian randomization study

The causal relationship between dietary habits and psoriatic arthritis (PsA) remains unclear, and the mediating role of human plasma metabolites in this relationship is unexamined. This study aims to elucidate the causal relationship between 80 dietary patterns and PsA using a 2-sample Mendelian randomization (MR) analysis. A 2-step MR approach was employed to investigate whether 1400 human plasma metabolites could serve as potential mediators between dietary habits and PsA. To ensure the reliability of the results, heterogeneity and pleiotropy tests were conducted. Our MR analysis identified 5 dietary factors exhibiting significant inverse causal associations with PsA risk (P < .05): red wine intake (odds ratio (OR) = 0.62), total alcohol intake (OR = 0.59), cheese intake (OR = 0.56), monthly alcohol drinks (OR = 0.66), and decaffeinated coffee preference (OR = 0.62). Mediation analysis revealed distinct metabolite pathways underlying these associations. Red wine intake-PsA relationship: Gamma/beta-tocopherol levels mediated 17.8% of the protective effect, followed by citrate (7.2% mediation). Cheese intake-PsA association: Arginine levels accounted for 7.4% of the effect, with phosphate-to-threonine ratio mediating an additional 7.2%. Decaffeinated coffee preference-PsA link: Three amino acid ratios demonstrated significant mediation-glutamate/alanine (12.2%), ornithine/glutamate (10.9%), and arginine/glutamate (8.9%). These results underscore the potential role of plasma metabolites as mediators in the causal relationship between these 5 dietary habits and PsA.

Rapid and Reagent-Free Analysis of Dried Blood Spot by Paper Spray Mass Spectrometry Reveals Sex: Implications in Forensic Investigations

Identifying sex from an unknown dried blood spot (DBS), especially when the corpse remains undiscovered, often provides valuable evidence in forensic casework. While DNA-based sex determination is a reliable method in forensic settings, it requires expensive reagents and is time-consuming. To develop a rapid reagent-free blood test for sex, we employed paper spray ionization mass spectrometry (PSI-MS) to capture sex-discriminatory lipid profiles from 200 DBS samples comprising 100 males and 100 females. We conducted a supervised machine learning (ML) analysis on all detected lipid signals to hunt biomarkers of sex within the data set. This analysis unveiled significant differences in specific sphingomyelin and phospholipid species levels between male and female DBS samples. Using the parsimonious set of 60 lipid signals, we constructed a classifier that achieved 100% overall accuracy in predicting sex from DBS on paper. Additionally, we assessed three-day-old air-exposed DBS on glass and granite surfaces, simulating the typical blood samples available for forensic investigations. Consequently, we achieved ∼92% overall sex prediction accuracy from the holdout test data set of DBS on glass and granite surfaces. As a highly sensitive detection tool, PSI-MS combined with ML has the potential to revolutionize forensic methods by rapidly analyzing blood molecules encoding personal information.

Metabolomic profiling of a cholesterol lowering plant-based diet from two randomized controlled feeding trials

BACKGROUND

Objective biomarkers of diet, such as metabolomics, may improve dietary assessment and provide additional insight into how diet influences disease risk. The portfolio diet, a cholesterol-lowering plant-based diet, is recommended for lowering low-density lipoprotein cholesterol (LDL-C). This diet is low in saturated fat and includes nuts, plant protein (legumes), viscous fiber, and phytosterols.

OBJECTIVE

We examined metabolomic profiles in response to the portfolio diet in two randomized controlled trials (RCTs), where all foods were provided to the participants, compared to a control vegetarian diet and the same control diet with a statin.

METHODS

The first RCT included 34 adults (age 58.4 ± 8.6 y) and the second RCT included 25 adults (age 61.0 ± 9.6 y), all with high LDL-C (>4.1 mmol/L). Plasma samples were obtained at baseline, week 2, and week 4 in both RCTs for metabolomics analysis using liquid chromatography-tandem mass spectrometry. Linear mixed models were used to examine effects of the interventions on the metabolites in each RCT, applying a Bonferroni correction.

RESULTS

Of 496 known metabolites, 145 and 63 metabolites significantly changed within the portfolio diet interventions in the first and second RCT, respectively. The majority were glycerophosphocholines (32%), triacylglycerols (20%), glycerophosphoethanolamines (14%), sphingomyelins (8%), and amino acids and peptides (8%) in the first RCT, and glycerophosphocholines (48%), glycerophosphoethanolamines (17%), and amino acids and peptides (8%) in the second RCT. Fifty-two metabolites were consistently changed in the same direction with the portfolio diet intervention across both RCTs, after Bonferroni correction.

CONCLUSIONS

Many of these metabolites likely reflect the plant-based nature, low saturated fat content, and cholesterol-lowering effects of the diet, such as increased N2-acetylornithine, L-pipecolic acid, lenticin, and decreased C18:0 lipids and cholesteryl esters. Further research is needed to validate these metabolites as biomarkers of a plant-based dietary pattern.

Diet Item Details: Reporting Checklist for Feeding Studies Measuring the Dietary Metabolome (DID-METAB Checklist)-Explanation and Elaboration Report on the Development of the Checklist by the DID-METAB Delphi Working Group

Metabolomics is a postgenomic, systems-based discipline offering valuable applications in nutrition research, including the use of objective biomarkers to characterize dietary intake and metabolic responses more accurately. A scoping review identified the need for reporting guidance on dietary information in the form of a checklist to ensure reproducibility of human feeding studies that are measuring the diet-related metabolome. In this study, we aimed to gain consensus on a core outcome set pertaining to diet-related item details (DIDs) and recommendations for reporting DIDs to inform development of a reporting checklist. The goal of this checklist is to guide researchers on the minimum level of content and detail required for reporting dietary information in human feeding studies measuring the metabolome. A 2-stage online Delphi process encompassing 5 survey rounds with international experts in clinical trial design, feeding study intervention implementation, metabolomics, and/or human biospecimen analyses was conducted. A core outcome set encompassing 29 DIDs and accompanying recommendations was developed across 5 domains: dietary intervention-modeling (8 DIDs), dietary intervention-implementation (3 DIDs), dietary assessment (9 DIDs), adherence and compliance monitoring (4 DIDs), and bias (5 DIDs). The reporting guideline (DID-METAB Checklist) was generated and accepted by the international expert working group in the final survey round. All experts agreed that relevant journals should include the checklist as a suggested reporting tool for relevant studies and/or used alongside existing reporting tools. This report provides examples, explanations and elaboration for each recommendation including examples from published literature and references. The DID-METAB Checklist will be a key tool to advance the standardized reporting for feeding studies assessing the metabolome. Implementation of this tool will enable the ability to better interpret data and ensure global utility of results for furthering the advancement of metabolomics in nutrition research and future precision and personalized nutrition strategies.

Human metabolic chambers reveal a coordinated metabolic-physiologic response to nutrition

Human studies linking metabolism with organism-wide physiologic function have been challenged by confounding, adherence, and precisionHere, we united physiologic and molecular phenotypes of metabolism during controlled dietary intervention to understand integrated metabolic-physiologic responses to nutrition. In an inpatient study of individuals who underwent serial 24-hour metabolic chamber experiments (indirect calorimetry) and metabolite profiling, we mapped a human metabolome onto substrate oxidation rates and energy expenditure across up to 7 dietary conditions (energy balance, fasting, multiple 200% caloric excess overfeeding of varying fat, protein, and carbohydrate composition). Diets exhibiting greater fat oxidation (e.g., fasting, high-fat) were associated with changes in metabolites within pathways of mitochondrial β-oxidation, ketogenesis, adipose tissue fatty acid liberation, and/or multiple anapleurotic substrates for tricarboxylic acid cycle flux, with inverse associations for diets with greater carbohydrate availability. Changes in each of these metabolite classes were strongly related to 24-hour respiratory quotient (RQ) and substrate oxidation rates (e.g., acylcarnitines related to lower 24-hour RQ and higher 24-hour lipid oxidation), underscoring links between substrate availability, physiology, and metabolism in humans. Physiologic responses to diet determined by gold-standard human metabolic chambers are strongly coordinated with biologically consistent, interconnected metabolic pathways encoded in the metabolome.

Dietary and lifestyle insulinemic potentials, plasma metabolome, and risk of diverticulitis: a prospective cohort study

BACKGROUND

Diet and lifestyle factors have been linked to developing diverticulitis. However, it remains largely unknown whether the associations are mediated by metabolic disturbance, such as hyperinsulinemia and corresponding metabolomic perturbations.

OBJECTIVES

We investigated associations of the insulinemic potential of diet, lifestyle (diet, physical activity, body weight), and metabolomic patterns with the risk of incident diverticulitis.

METHODS

We conducted a prospective cohort study including participants in 3 nationwide cohorts of United States health professionals. The risk of incident diverticulitis was estimated according to quintiles of the empirical dietary index for hyperinsulinemia (EDIH) and empirical lifestyle index for hyperinsulinemia (ELIH). In a subset of participants with metabolomic measurements, we developed metabolomic dietary index for hyperinsulinemia (MDIH) and metabolomic lifestyle index for hyperinsulinemia (MLIH), metabolite profile scores correlating with EDIH and ELIH, respectively, and tested their associations with subsequent risk of diverticulitis. We also examined whether the associations of EDIH and ELIH with diverticulitis were mediated by the metabolite profile scores.

RESULTS

Among 184,508 participants [median age, 51 (interquartile range, 46-56) y], we documented 9123 incident diverticulitis cases over 3,419,945 person-years. Compared with those in the lowest quintile, participants with the most hyperinsulinemic diets and lifestyles (highest quintiles of EDIH and ELIH) had a hazard ratio for the risk of diverticulitis of 1.22 [95% confidence interval (CI): 1.13, 1.31] and 1.69 (95% CI: 1.57, 1.81), respectively. Similarly, the metabolite profile scores were significantly associated with the diverticulitis risk with odds ratio of 1.96 for MDIH (95% CI: 1.47, 2.60) and 1.93 for MLIH (95% CI: 1.48, 2.51) when comparing extreme quintiles. The explainable proportions of EDIH- and ELIH-related diverticulitis risk by MDIH and MLIH were 70% (95% CI: 6%, 99%) and 57% (95% CI: 23%, 86%), respectively (P < 0.0001 for both).

CONCLUSIONS

Participants with dietary and lifestyle patterns corresponding to higher insulinemic potential had an increased risk of diverticulitis, which might be mediated by metabolomic profiles.

Mediterranean Diet Pattern: Potential Impact on the Different Altered Pathways Related to Cardiovascular Risk in Advanced Chronic Kidney Disease

BACKGROUND

Cardiovascular disease (CVD) remains the most common cause of mortality in chronic kidney disease (CKD) patients. Several studies suggest that the Mediterranean diet reduces the risk of CVD due to its influence on endothelial function, inflammation, lipid profile, and blood pressure. Integrating metabolomic and proteomic analyses of CKD could provide insights into the pathways involved in uremia-induced CVD and those pathways modifiable by the Mediterranean diet.

METHODS

We performed metabolomic and proteomic analyses on serum samples from 19 patients with advanced CKD (aCKD) and 27 healthy volunteers. The metabolites were quantified using four different approaches, based on their properties. Proteomic analysis was performed after depletion of seven abundant serum proteins (Albumin, IgG, antitrypsin, IgA, transferrin, haptoglobin, and fibrinogen). Integrative analysis was performed using MetaboAnalyst 4.0 and STRING 11.0 software to identify the dysregulated pathways and biomarkers.

RESULTS

A total of 135 metabolites and 75 proteins were differentially expressed in aCKD patients, compared to the controls. Pathway enrichment analysis showed significant alterations in the innate immune system pathways, including complement, coagulation, and neutrophil degranulation, along with disrupted linoleic acid and cholesterol metabolism. Additionally, certain key metabolites and proteins were altered in aCKD patients, such as glutathione peroxidase 3, carnitine, homocitrulline, 3-methylhistidine, and several amino acids and derivatives.

CONCLUSIONS

Our findings reveal significant dysregulation of the serum metabolome and proteome in aCKD, particularly in those pathways associated with endothelial dysfunction and CVD. These results suggest that CVD prevention in CKD may benefit from a multifaceted approach, including dietary interventions such as the Mediterranean diet.

Metabolomic characterization of human glioblastomas and patient plasma: a pilot study

Background

Glioblastoma (GBM) is a clinically challenging primary brain tumor with poor survival outcome despite surgical resection and intensive chemoradiation. The metabolic heterogeneity of GBM can become biomarkers for treatment response, resistance, and outcome prediction. The aim of the study is to investigate metabolic distinctions between primary and recurrent GBM tissue and patient plasma to establish feasibility for metabolic profiling.

Methods

A single-center cohort study analyzed tissue and blood samples from 15 patients with GBM using untargeted metabolomic/lipidomic assays. Metabolomic, lipidomic, and biogenic amine analyses were conducted on GBM tissue and patient plasma at diagnosis and recurrence using untargeted mass spectrometry. The study utilized a small but longitudinally collected cohort to evaluate alteration in metabolites, lipids, and biogenic amines between specimens at diagnosis and recurrence.

Results

Exploratory analysis revealed significant alteration in metabolites, lipids, and biogenic amines between diagnostic and recurrent states in both tumor and plasma specimens. Notable metabolites differed at recurrence, including N-alpha-methylhistamine, glycerol-3-phosphate, phosphocholine, and succinic acid in tissue, and indole-3-acetate, and urea in plasma. Principal component analysis revealed distinct metabolomic profiles between tumor tissue and patient plasma. Distinct metabolic profiles were observed in GBM tissue and patient plasma at recurrence, demonstrating the feasibility of using metabolomic methodologies for longitudinal studies. One patient exhibited a unique tumor resistance signature at diagnosis, possibly indicating a high-risk metabolomic phenotype.

Conclusions

In this small cohort, the findings suggest the potential of metabolomic signatures of GBM tissue and patient plasma for risk stratification, outcome prediction, and the development of novel adjuvant metabolic-targeting therapies. The findings suggest metabolic discrepancies at diagnosis and recurrence in tissue and plasma, highlighting potential implications for evaluation of clinical response. The identification of significant changes in metabolite abundance emphasizes the need for larger studies using targeted metabolomics to validate and further explore these profiles.

Double Cyclization Tandem Mass for Identification and Quantification of Phosphatidylcholines Using Isobaric Six-Plex Capillary nLC-MS/MS

Multiplexing of phosphatidylcholine analysis is hindered by a lack of appropriate derivatization. Presented here is a tagging scheme that uses a quaternary amine tag and targets the hydroxy group of the phosphate, which switches the net charge from neutral to +2. Quantitative yields were achieved from >99% reaction completion derived by dimethoxymethyl morpholinium (DMTMM) activation. Fragmentation of phosphatidylcholines (PCs) and lysophosphatidylcholines (LPCs) releases two trimethylamines and the acyl chains through neutral loss and generates a unique double cyclization constant mass reporter. Selective incorporation of isotopes onto the tag produces a six-plex set of isobaric reagents. For equivalent six-plex-labeled samples, <14% RSD was achieved, followed by a dynamic range of 1:10 without signal compression. Quantification of PCs/LPCs in human hepatic cancer cells was conducted as six-plex using data-dependent analysis tandem MS. We report a six-plex qualitative and quantitative isobaric tagging strategy expanding the limits of analyzing PCs/LPCs.

The consumption of animal products is associated with plasma levels of alpha-aminoadipic acid (2-AAA)

BACKGROUND AND AIMS

The cardiometabolic disease-associated metabolite, alpha-aminoadipic acid (2-AAA) is formed from the breakdown of the essential dietary amino acid lysine. However, it was not known whether elevated plasma levels of 2-AAA are related to dietary nutrient intake. We aimed to determine whether diet is a determinant of circulating 2-AAA in healthy individuals, and whether 2-AAA is altered in response to dietary modification.

METHODS AND RESULTS

We investigated the association between 2-AAA and dietary nutrient intake in a cross-sectional study of healthy individuals (N = 254). We then performed a randomized cross-over dietary intervention trial to investigate the effect of lysine supplementation (1 week) on 2-AAA in healthy individuals (N = 40). We further assessed the effect of a vegetarian diet on 2-AAA in a short-term (4-day) dietary intervention trial in healthy omnivorous women (N = 35). We found that self-reported dietary intake of animal products, including meat, poultry, and seafood, was associated with higher plasma 2-AAA cross-sectionally (P < 0.0001). Supplementary dietary lysine (5g/day) caused no significant increase in plasma 2-AAA; however, plasma 2-AAA was altered by general dietary modification. Further, plasma 2-AAA was significantly reduced by a short-term vegetarian diet (P = 0.003).

CONCLUSION

We identified associations between plasma 2-AAA and consumption of animal products, which were validated in a vegetarian dietary intervention trial, but not in a trial designed to specifically increase the 2-AAA amino acid precursor lysine. Further studies are warranted to investigate whether implementation of a vegetarian diet improves cardiometabolic risk in individuals with elevated 2-AAA.

Biomarkers for ideal protein: rabbit diet metabolomics varying key amino acids

With the main aim of identifying biomarkers that contribute to defining the concept of ideal protein in growing rabbits under the most diverse conditions possible this work describes two different experiments. Experiment 1: 24 growing rabbits are included at 56 days of age. The rabbits are fed ad libitum one of the two experimental diets only differing in lysine levels. Experiment 2: 53 growing rabbits are included at 46 days of age, under a fasting and eating one of the five experimental diets, with identical chemical composition except for the three typically limiting amino acids (being fed commercial diets ad libitum in both experiments). Blood samples are taken for targeted and untargeted metabolomics analysis. Here we show that the metabolic phenotype undergoes alterations when animals experience a rapid dietary shift in the amino acid levels. While some of the differential metabolites can be attributed directly to changes in specific amino acids, creatinine, urea, hydroxypropionic acid and hydroxyoctadecadienoic acid are suggested as a biomarker of amino acid imbalances in growing rabbits' diets, since its changes are not attributable to a single amino acid. The fluctuations in their levels suggest intricate amino acid interactions. Consequently, we propose these metabolites as promising biomarkers for further research into the concept of the ideal protein using rabbit as a model.

Intake Biomarkers for Nutrition and Health: Review and Discussion of Methodology Issues

Metabolomics profiles from blood, urine, or other body fluids have the potential to assess intakes of foods and nutrients objectively, thereby strengthening nutritional epidemiology research. Metabolomics platforms may include targeted components that estimate the relative concentrations for individual metabolites in a predetermined set, or global components, typically involving mass spectrometry, that estimate relative concentrations more broadly. While a specific metabolite concentration usually correlates with the intake of a single food or food group, multiple metabolites may be correlated with the intake of certain foods or with specific nutrient intakes, each of which may be expressed in absolute terms or relative to total energy intake. Here, I briefly review the progress over the past 20 years on the development and application intake biomarkers for foods/food groups, nutrients, and dietary patterns, primarily by drawing from several recent reviews. In doing so, I emphasize the criteria and study designs for candidate biomarker identification, biomarker validation, and intake biomarker application. The use of intake biomarkers for diet and chronic disease association studies is still infrequent in nutritional epidemiology research. My comments here will derive primarily from our research group's recent contributions to the Women's Health Initiative cohorts. I will complete the contribution by describing some opportunities to build on the collective 20 years of effort, including opportunities related to the metabolomics profiling of blood and urine specimens from human feeding studies that approximate habitual diets.

Human metabolic chambers reveal a coordinated metabolic-physiologic response to nutrition

The emerging field of precision nutrition is based on the notion that inter-individual responses across diets of different calorie-macronutrient content may contribute to inter-individual differences in metabolism, adiposity, and weight gain. Free-living diet studies have been traditionally challenged by difficulties in controlling adherence to prescribed calories and macronutrient content and rarely allow a period of metabolic stability prior to metabolic measures (to minimize influences of weight changes). In this context, key physiologic measures central to precision nutrition responses may be most precisely quantified via whole room indirect calorimetry over 24-h, in which precise control of activity and nutrition can be achieved. In addition, these studies represent unique "N of 1" human crossover metabolic-physiologic experiments during which specific molecular pathways central to nutrient metabolism may be discerned. Here, we quantified 263 circulating metabolites during a ≈40-day inpatient admission in which up to 94 participants underwent seven monitored 24-h nutritional interventions of differing macronutrient composition in a whole-room indirect calorimeter to capture precision metabolic responses. Broadly, we observed heterogenous responses in metabolites across dietary chambers, with the exception of carnitines which tracked with 24-h respiratory quotient. We identified excursions in shared metabolic species (e.g., carnitines, glycerophospholipids, amino acids) that mapped onto gold-standard calorimetric measures of substrate oxidation preference and lipid availability. These findings support a coordinated metabolic-physiologic response to nutrition, highlighting the relevance of these controlled settings to uncover biological pathways of energy utilization during precision nutrition studies.

Determining predictive metabolomic biomarkers of meniscal injury in dogs with cranial cruciate ligament rupture

OBJECTIVES

This study used hydrogen nuclear magnetic resonance spectroscopy for the first time to examine differences in the metabolomic profile of stifle joint synovial fluid from dogs with cranial cruciate ligament rupture with and without meniscal injuries, in order to identify biomarkers of meniscal injury. Identifying a biomarker of meniscal injury could then ultimately be used to design a minimally invasive diagnostic test for meniscal injuries in dogs.

MATERIALS AND METHODS

Stifle joint synovial fluid was collected from dogs undergoing stifle joint surgery or arthrocentesis for lameness investigations. We used multi-variate statistical analysis using principal component analysis and univariate statistical analysis using one-way analysis of variance and analysis of co-variance to identify differences in the metabolomic profile between dogs with cranial cruciate ligament rupture and meniscal injury, cranial cruciate ligament rupture without meniscal injury, and neither cranial cruciate ligament rupture nor meniscal injury, taking into consideration clinical variables.

RESULTS

A total of 154 samples of canine synovial fluid were included in the study. Sixty-four metabolites were annotated to the hydrogen nuclear magnetic resonance spectroscopy spectra. Six spectral regions were found to be significantly altered (false discovery rate adjusted P-value <0.05) between groups with cranial cruciate ligament rupture with and without meniscal injury, including three attributed to nuclear magnetic resonance mobile lipids [mobile lipid -CH3 (P=0.016), mobile lipid -n(CH3 )3 (P=0.017), mobile unsaturated lipid (P=0.031)].

CLINICAL SIGNIFICANCE

We identified an increase in nuclear magnetic resonance mobile lipids in the synovial fluid of dogs with meniscal injury which are of interest as potential biomarkers of meniscal injury.

Benefits of Mediterranean and Japanese Diets among Nurses: A Scoping Literature Review

INTRODUCTION

The present study aimed at all the benefits induced by taking the Mediterranean or Japanese diet among nurses and whether any beneficial differences in intakes between the two diets were considered.

METHODS

The author searched PubMed and Embase databases for medical subheadings terms and free full text referring to "Diet," "Mediterranean," "Japanese," and "Nurses" before 31st December 2022.

RESULTS

A total of 14 studies were included in this scoping review, which better underlined all the benefits implicated in the Mediterranean or Japanese diets assumption and also if there were any differences between the two diets. These eating behaviors were exclusively investigated among nurses.

CONCLUSION

The nursing profession has always been considered the most stressful healthcare activity. However, some important concerns in the regular lifestyle, such as eating and physical activity, might help to live better.

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).

Effects of ketone bodies on energy expenditure, substrate utilization, and energy intake in humans

The potential of ketogenic approaches to regulate energy balance has recently gained attention since ketones may influence both energy expenditure and energy intake. In this narrative review, we summarized the most relevant evidence about the role of ketosis on energy expenditure, substrate utilization, and energy intake in humans. We considered different strategies to induce ketosis, such as fasting, dietary manipulation, and exogenous ketone sources. In general, ketosis does not have a major influence on energy expenditure but promotes a shift in substrate utilization towards ketone body oxidation. The strategies to induce ketosis by reduction of dietary carbohydrate availability (e.g., ketogenic diets) do not independently influence energy intake, being thus equally effective for weight loss as diets with higher carbohydrate content. In contrast, the intake of medium-chain triglycerides and ketone esters induces ketosis and appears to increase energy expenditure and reduce energy intake in the context of high carbohydrate availability. These latter strategies lead to slightly enhanced weight loss. Unfortunately, distinguishing the effects of the various ketogenic strategies per se from the effects of other physiological responses is not possible with the available human data. Highly controlled, inpatient studies using targeted strategies to isolate the independent effects of ketones are required to adequately address this knowledge gap.

Metabolomic Profile of the Healthy Eating Index-2015 in the Multiethnic Study of Atherosclerosis

BACKGROUND

Poor diet quality is a risk factor for type 2 diabetes and cardiovascular disease. However, knowledge of metabolites marking adherence to Dietary Guidelines for Americans (2015 version) are limited.

OBJECTIVES

The goal was to determine a pattern of metabolites associated with the Healthy Eating Index (HEI)-2015, which measures adherence to the Dietary Guidelines for Americans.

METHODS

The analysis examined 3557 adult men and women from the longitudinal cohort Multiethnic Study of Atherosclerosis (MESA), without known cardiovascular disease and with complete dietary data. Fasting serum specimens and diet and demographic questionnaires were assessed at baseline. Untargeted 1H 1-dimensional nuclei magnetic resonance spectroscopy (600 MHz) was used to generate metabolomics and lipidomics. A metabolome-wide association study specified each spectral feature as outcomes, HEI-2015 score as predictor, adjusting for age, sex, race, and study site in linear regression analyses. Subsequently, hierarchical clustering defined the discrete groups of correlated nuclei magnetic resonance features associated with named metabolites, and the linear regression analysis assessed for associations with HEI-2015 total and component scores.

RESULTS

The sample included 50% women with an mean age of 63 years, with 40% identifying as White, 23% as Black, 24% as Hispanic, and 13% as Chinese American. The mean HEI-2015 score was 66. The metabolome-wide association study identified 179 spectral features significantly associated with HEI-2015 score. The cluster analysis identified 7 clusters representing 4 metabolites; HEI-2015 score was significantly associated with all. HEI-2015 score was associated with proline betaine [β = 0.12 (SE = 0.02); P = 4.70 × 10-13] and was inversely related to proline [β = -0.13 (SE = 0.02); P = 4.45 × 10-14], 1,5 anhydrosorbitol [β = -0.08 (SE = 0.02); P = 4.37 × 10-7] and unsaturated fatty acyl chains [β = 0.08 (SE = 0.02); P = 8.98 × 10-7]. Intake of total fruit, whole grains, and seafood and plant proteins was associated with proline betaine.

CONCLUSIONS

Diet quality is significantly associated with unsaturated fatty acyl chains, proline betaine, and proline. Further analysis may clarify the link between diet quality, metabolites, and pathogenesis of cardiometabolic disease.

Untargeted metabolomics profiling in pediatric patients and adult populations indicates a connection between lipid imbalance and epilepsy

Introduction

Epilepsy is a common central nervous system disorder characterized by abnormal brain electrical activity. We aimed to compare the metabolic profiles of plasma from patients with epilepsy across different etiologies, seizure frequency, seizure type, and patient age to try to identify common disrupted pathways.

Material and methods

We used data from three separate cohorts. The first cohort (PED-C) consisted of 31 pediatric patients with suspicion of a genetic disorder with unclear etiology; the second cohort (AD-C) consisted of 250 adults from the Estonian Biobank (EstBB), and the third cohort consisted of 583 adults ≥ 69 years of age from the EstBB (ELD-C). We compared untargeted metabolomics and lipidomics data between individuals with and without epilepsy in each cohort.

Results

In the PED-C, significant alterations (p-value <0.05) were detected in sixteen different glycerophosphatidylcholines (GPC), dimethylglycine and eicosanedioate (C20-DC). In the AD-C, nine significantly altered metabolites were found, mainly triacylglycerides (TAG), which are also precursors in the GPC synthesis pathway. In the ELD-C, significant changes in twenty metabolites including multiple TAGs were observed in the metabolic profile of participants with previously diagnosed epilepsy. Pathway analysis revealed that among the metabolites that differ significantly between epilepsy-positive and epilepsy-negative patients in the PED-C, the lipid superpathway (p = 3.2*10-4) and phosphatidylcholine (p = 9.3*10-8) and lysophospholipid (p = 5.9*10-3) subpathways are statistically overrepresented. Analogously, in the AD-C, the triacylglyceride subclass turned out to be statistically overrepresented (p = 8.5*10-5) with the lipid superpathway (p = 1.4*10-2). The presented p-values are FDR-corrected.

Conclusion

Our results suggest that cell membrane fluidity may have a significant role in the mechanism of epilepsy, and changes in lipid balance may indicate epilepsy. However, further studies are needed to evaluate whether untargeted metabolomics analysis could prove helpful in diagnosing epilepsy earlier.

Dietary metabolic signatures and cardiometabolic risk

AIMS

Observational studies of diet in cardiometabolic-cardiovascular disease (CM-CVD) focus on self-reported consumption of food or dietary pattern, with limited information on individual metabolic responses to dietary intake linked to CM-CVD. Here, machine learning approaches were used to identify individual metabolic patterns related to diet and relation to long-term CM-CVD in early adulthood.

METHODS AND RESULTS

In 2259 White and Black adults (age 32.1 ± 3.6 years, 45% women, 44% Black) in the Coronary Artery Risk Development in Young Adults (CARDIA) study, multivariate models were employed to identify metabolite signatures of food group and composite dietary intake across 17 food groups, 2 nutrient groups, and healthy eating index-2015 (HEI2015) diet quality score. A broad array of metabolites associated with diet were uncovered, reflecting food-related components/catabolites (e.g. fish and long-chain unsaturated triacylglycerols), interactions with host features (microbiome), or pathways broadly implicated in CM-CVD (e.g. ceramide/sphingomyelin lipid metabolism). To integrate diet with metabolism, penalized machine learning models were used to define a metabolite signature linked to a putative CM-CVD-adverse diet (e.g. high in red/processed meat, refined grains), which was subsequently associated with long-term diabetes and CVD risk numerically more strongly than HEI2015 in CARDIA [e.g. diabetes: standardized hazard ratio (HR): 1.62, 95% confidence interval (CI): 1.32-1.97, P < 0.0001; CVD: HR: 1.55, 95% CI: 1.12-2.14, P = 0.008], with associations replicated for diabetes (P < 0.0001) in the Framingham Heart Study.

CONCLUSION

Metabolic signatures of diet are associated with long-term CM-CVD independent of lifestyle and traditional risk factors. Metabolomics improves precision to identify adverse consequences and pathways of diet-related CM-CVD.

Healthy lifestyle, plasma metabolites, and risk of cardiovascular disease among individuals with diabetes

BACKGROUND AND AIMS

Lifestyle management is a fundamental aspect of diabetes care to prevent cardiovascular disease (CVD); however, the underlying metabolic mechanism is not well established. We aimed to identify metabolites associated with different lifestyle factors, and estimate their mediating roles between lifestyle and CVD risk among people with diabetes.

METHODS

Lifestyle and metabolomic data were available for 5072 participants with diabetes who were free of CVD at baseline in the UK Biobank. The healthy level of 5 lifestyle factors was defined as non-central obesity, non-current smoking, moderate alcohol intake, physically active, and healthy diet. A total of 44 biomarkers across 7 metabolic pathways including lipoprotein particles, fatty acids, amino acids, fluid balance, inflammation, ketone bodies, and glycolysis were quantified by nuclear magnetic resonance (NMR) spectroscopy.

RESULTS

All 44 assayed metabolites were significantly associated with at least one lifestyle factor. Approximately half of metabolites, which were mostly lipoprotein particles and fatty acids, showed a mediating effect between at least one lifestyle factor and CVD risk. NMR metabolites jointly mediated 43.4%, 30.0%, 16.8%, 43.4%, and 65.5% of the association of non-central obesity, non-current smoking, moderate alcohol intake, physically active, and healthy diet with lower CVD risk, respectively. In general, though metabolites that significantly associated with lifestyle were mostly different across the 5 lifestyle factors, the pattern of association was consistent between fatty acids and all 5 lifestyle factors. Further, fatty acids showed significant mediating effects in the association between all 5 lifestyle factors and CVD risk with mediation proportion ranging from 12.2% to 26.8%.

CONCLUSIONS

There were large-scale differences in circulating NMR metabolites between individuals with diabetes who adhered to a healthy lifestyle and those did not. Differences in metabolites, especial fatty acids, could partially explain the association between adherence to multiple healthy lifestyle and lower CVD risk among people with diabetes.

Associations between Conventional and Emerging Indicators of Dietary Carbohydrate Quality and New-Onset Type 2 Diabetes Mellitus in Chinese Adults

Dietary glycemic index (GI), carbohydrate to fiber ratio (CF) and carbohydrate quality index (CQI) are conventional and emerging indicators for carbohydrate quality. We aimed to investigate the associations between these indicators and new-onset type 2 diabetes mellitus (T2DM) risk among Chinese adults. This prospective cohort study included 14,590 adults from the China Health and Nutrition Survey without cardiometabolic diseases at baseline. The associations between dietary GI, CF and CQI and T2DM risk were assessed using Cox proportional hazard regression analysis and dose-response relationships were explored using restricted cubic spline and threshold analysis. After a mean follow-up duration of 10 years, a total of 1053 new-onset T2DM cases occurred. There were U-shaped associations between dietary GI and CF and T2DM risk (both P-nonlinear < 0.0001), and T2DM risk was lowest when dietary GI was 72.85 (71.40, 74.05) and CF was 20.55 (17.92, 21.91), respectively (both P-log likelihood ratio < 0.0001). Inverse associations between CQI and T2DM risk specifically existed in participants < 60 y or attended middle school or above (both P-trend < 0.05). These findings indicated that moderate dietary GI and CF range and a higher dietary CQI score may be suggested for T2DM prevention in Chinese adults.

Differences in Metabolomic Profiles Between Black and White Women and Risk of Coronary Heart Disease: an Observational Study of Women From Four US Cohorts

BACKGROUND

Racial differences in metabolomic profiles may reflect underlying differences in social determinants of health by self-reported race and may be related to racial disparities in coronary heart disease (CHD) among women in the United States. However, the magnitude of differences in metabolomic profiles between Black and White women in the United States has not been well-described. It also remains unknown whether such differences are related to differences in CHD risk.

METHODS

Plasma metabolomic profiles were analyzed using liquid chromatography-tandem mass spectrometry in the WHI-OS (Women's Health Initiative-Observational Study; 138 Black and 696 White women), WHI-HT trials (WHI-Hormone Therapy; 156 Black and 1138 White women), MESA (Multi-Ethnic Study of Atherosclerosis; 114 Black and 219 White women), JHS (Jackson Heart Study; 1465 Black women with 107 incident CHD cases), and NHS (Nurses' Health Study; 2506 White women with 136 incident CHD cases). First, linear regression models were used to estimate associations between self-reported race and 472 metabolites in WHI-OS (discovery); findings were replicated in WHI-HT and validated in MESA. Second, we used elastic net regression to construct a racial difference metabolomic pattern (RDMP) representing differences in the metabolomic patterns between Black and White women in the WHI-OS; the RDMP was validated in the WHI-HT and MESA. Third, using conditional logistic regressions in the WHI (717 CHD cases and 719 matched controls), we examined associations of metabolites with large differences in levels by race and the RDMP with risk of CHD, and the results were replicated in Black women from the JHS and White women from the NHS.

RESULTS

Of the 472 tested metabolites, levels of 259 (54.9%) metabolites, mostly lipid metabolites and amino acids, significantly differed between Black and White women in both WHI-OS and WHI-HT after adjusting for baseline characteristics, socioeconomic status, lifestyle factors, baseline health conditions, and medication use (false discovery rate <0.05); similar trends were observed in MESA. The RDMP, composed of 152 metabolites, was identified in the WHI-OS and showed significantly different distributions between Black and White women in the WHI-HT and MESA. Higher RDMP quartiles were associated with an increased risk of incident CHD (odds ratio=1.51 [0.97-2.37] for the highest quartile comparing to the lowest; Ptrend=0.02), independent of self-reported race and known CHD risk factors. In race-stratified analyses, the RDMP-CHD associations were more pronounced in White women. Similar patterns were observed in Black women from the JHS and White women from the NHS.

CONCLUSIONS

Metabolomic profiles significantly and substantially differ between Black and White women and may be associated with CHD risk and racial disparities in US women.

Individuality and ethnicity eclipse a short-term dietary intervention in shaping microbiomes and viromes

Many diseases linked with ethnic health disparities associate with changes in microbial communities in the United States, but the causes and persistence of ethnicity-associated microbiome variation are not understood. For instance, microbiome studies that strictly control for diet across ethnically diverse populations are lacking. Here, we performed multiomic profiling over a 9-day period that included a 4-day controlled vegetarian diet intervention in a defined geographic location across 36 healthy Black and White females of similar age, weight, habitual diets, and health status. We demonstrate that individuality and ethnicity account for roughly 70% to 88% and 2% to 10% of taxonomic variation, respectively, eclipsing the effects a short-term diet intervention in shaping gut and oral microbiomes and gut viromes. Persistent variation between ethnicities occurs for microbial and viral taxa and various metagenomic functions, including several gut KEGG orthologs, oral carbohydrate active enzyme categories, cluster of orthologous groups of proteins, and antibiotic-resistant gene categories. In contrast to the gut and oral microbiome data, the urine and plasma metabolites tend to decouple from ethnicity and more strongly associate with diet. These longitudinal, multiomic profiles paired with a dietary intervention illuminate previously unrecognized associations of ethnicity with metagenomic and viromic features across body sites and cohorts within a single geographic location, highlighting the importance of accounting for human microbiome variation in research, health determinants, and eventual therapies. Trial Registration: ClinicalTrials.gov ClinicalTrials.gov Identifier: NCT03314194.

Compilation of longitudinal gut microbiome, serum metabolome, and clinical data in acute myeloid leukemia

Induction chemotherapy for patients with acute myeloid leukemia (AML) is a unique clinical scenario. These patients spend several weeks in the hospital, receiving multiple antibiotics, experiencing gastrointestinal mucosal damage, and suffering severe impairments in their immune system and nutrition. These factors cause major disruptions to the gut microbiota to a level rarely seen in other clinical conditions. Thus, the study of the gut microbiota in these patients can reveal novel aspects of microbiota-host relationships. When combined with the circulating metabolome, such studies could shed light on gut microbiota contribution to circulating metabolites. Collectively, gut microbiota and circulating metabolome are known to regulate host physiology. We have previously deposited amplicon sequences from 566 fecal samples from 68 AML patients. Here, we provide sample-level details and a link, using de-identified patient IDs, to additional data including serum metabolomics (260 samples from 36 patients) and clinical metadata. The detailed information provided enables comprehensive multi-omics analysis. We validate the technical quality of these data through 3 examples and demonstrate a method for integrated analysis.

Plasma Metabolite Response to Simple, Refined and Unrefined Carbohydrate-Enriched Diets in Older Adults-Randomized Controlled Crossover Trial

Food intake data collected using subjective tools are prone to inaccuracies and biases. An objective assessment of food intake, such as metabolomic profiling, may offer a more accurate method if unique metabolites can be identified. To explore this option, we used samples generated from a randomized and controlled cross-over trial during which participants (N = 10; 65 ± 8 year, BMI, 29.8 ± 3.2 kg/m²) consumed each of the three diets enriched in different types of carbohydrate. Plasma metabolite concentrations were measured at the end of each diet phase using gas chromatography/time-of-flight mass spectrometry and ultra-high pressure liquid chromatography/quadrupole time-of-flight tandem mass spectrometry. Participants were provided, in random order, with diets enriched in three carbohydrate types (simple carbohydrate (SC), refined carbohydrate (RC) and unrefined carbohydrate (URC)) for 4.5 weeks per phase and separated by two-week washout periods. Data were analyzed using partial least square-discrimination analysis, receiver operating characteristics (ROC curve) and hierarchical analysis. Among the known metabolites, 3-methylhistidine, phenylethylamine, cysteine, betaine and pipecolic acid were identified as biomarkers in the URC diet compared to the RC diet, and the later three metabolites were differentiated and compared to SC diet. Hierarchical analysis indicated that the plasma metabolites at the end of each diet phase were more strongly clustered by the participant than the carbohydrate type. Hence, although differences in plasma metabolite concentrations were observed after participants consumed diets differing in carbohydrate type, individual variation was a stronger predictor of plasma metabolite concentrations than dietary carbohydrate type. These findings limited the potential of metabolic profiling to address this variable.

Lipidomics Reveals That Rice or Flour as a Single Source of Carbohydrates Cause Adverse Health Effects in Rats

The type of diet is very important for the maintenance of health and nutrition. How the sole source of carbohydrates from rice- or flour-based diet affect blood sugar has not been elucidated for a long time. In order to explore the effects of these diets, sixty SD rats were randomly divided into three groups: control group (C group, AIN-93, standard diet), rice diet group (R group), and flour diet group (F group). All the rats were fed for 7 weeks in total by the assigned diets for 4 weeks (stage 1, S1) and all by the AIN-93 diet for 3 weeks (stage 2, S2). The body weights of all the rats were monitored and serum samples were taken for testing blood glucose, biochemical indicators and untargeted lipidome. It was found that both rice and flour-based diets caused weight gain, but the flour diet had a significant increase in blood sugar and low-density lipoprotein (LDL), while a significant decrease in albumin (ALB) and triglycerides (TG). Twenty-three and 148 lipids were changed by lipidomics in the rice diet group and flour diet group, respectively, and two lipids showed the same changes in the two groups, all belonging to TGs, namely TG (16:0/16:0/16:1) and TG (16:0/16:1/18:2), which showed that a single diet source had a significant effect on the health of rats. Fortunately, we can recover this effect through the subsequent standard diet, allowing the rats to return to normal blood sugar, weight and biochemical indicators. A model can predict the diet types through the logistic regression method. Finally, we proposed that a single diet increased blood sugar and weight through a decrease in TGs, and blood sugar and weight returned to normal after a standard diet. Taken together, the short-term negative effects caused by a single diet can be recovered by a standard diet and further proves the importance of diet types.

Serum metabolomic analysis of men on a low-carbohydrate diet for biochemically recurrent prostate cancer reveals the potential role of ketogenesis to slow tumor growth: a secondary analysis of the CAPS2 diet trial

BACKGROUND

Systemic treatments for prostate cancer (PC) have significant side effects. Thus, newer alternatives with fewer side effects are urgently needed. Animal and human studies suggest the therapeutic potential of low carbohydrate diet (LCD) for PC. To test this possibility, Carbohydrate and Prostate Study 2 (CAPS2) trial was conducted in PC patients with biochemical recurrence (BCR) after local treatment to determine the effect of a 6-month LCD intervention vs. usual care control on PC growth as measured by PSA doubling time (PSADT). We previously reported the LCD intervention led to significant weight loss, higher HDL, and lower triglycerides and HbA1c with a suggested longer PSADT. However, the metabolic basis of these effects are unknown.

METHODS

To identify the potential metabolic basis of effects of LCD on PSADT, serum metabolomic analysis was performed using baseline, month 3, and month 6 banked sera to identify the metabolites significantly altered by LCD and that correlated with varying PSADT.

RESULTS

LCD increased the serum levels of ketone bodies, glycine and hydroxyisocaproic acid. Reciprocally, LCD reduced the serum levels of alanine, cytidine, asymmetric dimethylarginine (ADMA) and 2-oxobutanoate. As high ADMA level is shown to inhibit nitric oxide (NO) signaling and contribute to various cardiovascular diseases, the ADMA repression under LCD may contribute to the LCD-associated health benefit. Regression analysis of the PSADT revealed a correlation between longer PSADT with higher level of 2-hydroxybutyric acids, ketone bodies, citrate and malate. Longer PSADT was also associated with LCD reduced nicotinamide, fructose-1, 6-biphosphate (FBP) and 2-oxobutanoate.

CONCLUSION

These results suggest a potential association of ketogenesis and TCA metabolites with slower PC growth and conversely glycolysis with faster PC growth. The link of high ketone bodies with longer PSADT supports future studies of ketogenic diets to slow PC growth.

Amino Acid-Related Metabolic Signature in Obese Children and Adolescents

The growing interest in metabolomics has spread to the search for suitable predictive biomarkers for complications related to the emerging issue of pediatric obesity and its related cardiovascular risk and metabolic alteration. Indeed, several studies have investigated the association between metabolic disorders and amino acids, in particular branched-chain amino acids (BCAAs). We have performed a revision of the literature to assess the role of BCAAs in children and adolescents' metabolism, focusing on the molecular pathways involved. We searched on Pubmed/Medline, including articles published until February 2022. The results have shown that plasmatic levels of BCAAs are impaired already in obese children and adolescents. The relationship between BCAAs, obesity and the related metabolic disorders is explained on one side by the activation of the mTORC1 complex-that may promote insulin resistance-and on the other, by the accumulation of toxic metabolites, which may lead to mitochondrial dysfunction, stress kinase activation and damage of pancreatic cells. These compounds may help in the precocious identification of many complications of pediatric obesity. However, further studies are still needed to better assess if BCAAs may be used to screen these conditions and if any other metabolomic compound may be useful to achieve this goal.

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.

Mendelian Randomization Identifies the Potential Causal Impact of Dietary Patterns on Circulating Blood Metabolites

Nutrition plays an important role in the development and progress of several health conditions, but the exact mechanism is often still unclear. Blood metabolites are likely candidates to be mediating these relationships, as their levels are strongly dependent on the frequency of consumption of several foods/drinks. Understanding the causal effect of food on metabolites is thus of extreme importance. To establish these effects, we utilized two-sample Mendelian randomization using the genetic variants associated with dietary traits as instrumental variables. The estimates of single-nucleotide polymorphisms' effects on exposures were obtained from a recent genome-wide association study (GWAS) of 25 individual and 15 principal-component dietary traits, whereas the ones for outcomes were obtained from a GWAS of 123 blood metabolites measured by nuclear magnetic resonance spectroscopy. We identified 413 potentially causal links between food and metabolites, replicating previous findings, such as the association between increased oily fish consumption and higher DHA, and highlighting several novel associations. Most of the associations were related to very-low-density, intermediate-density (IDL), and low-density lipoproteins (LDL). For example, we found that constituents of IDL particles and large LDL particles were raised by coffee and alcohol while lowered by an overall healthier diet and fruit consumption. Our findings provide a strong base of evidence for planning future RCTs aimed at understanding the role of diet in determining blood metabolite levels.

Personalized Behavioral Nutrition Among Older Asian Americans: Study Protocol

BACKGROUND

Metabolomics profiling is an objective assessment of metabolic responses to intricate dietary patterns. However, few studies have investigated the potential benefits associated with personalized behavioral nutrition (PBN) interventions incorporating the metabolomics approach for improving diabetes outcomes for older Asian Americans with Type 2 diabetes.

OBJECTIVE

This article describes the protocol for a pilot study testing self-management of a nutrition intervention-provided personalized dietary advice incorporating metabolites phenotypic feedback and digital self-monitoring of diet and blood glucose.

METHODS

A total of 60 older Asian Americans will be randomized into two groups: a PBN group and a control group. Participants in the PBN group will receive personalized dietary advice based on dietary and phenotypic feedback-used metabolic profiles. This study aims to examine the feasibility and preliminary effects of the PBN on diabetes outcomes.

RESULTS

The study began in September 2020, with estimated complete data collection by late 2021.

DISCUSSION

Findings from this pilot study will inform future research for developing personalized nutrition interventions for people with Type 2 diabetes.

Partial Substitution of Meat with Insect (Alphitobius diaperinus) in a Carnivore Diet Changes the Gut Microbiome and Metabolome of Healthy Rats

Insects are suggested as a sustainable protein source of high nutritional quality, but the effects of insect ingestion on processes in the gastrointestinal tract and gut microbiota (GM) remain to be established. We examined the effects of partial substitution of meat with insect protein (Alphitobius diaperinus) in a four-week dietary intervention in a healthy rat model (n = 30). GM composition was characterized using' 16S rRNA gene amplicon profiling while the metabolomes of stomach, small intestine, and colon content, feces and blood were investigated by 1H-NMR spectroscopy. Metabolomics analyses revealed a larger escape of protein residues into the colon and a different microbial metabolization pattern of aromatic amino acids when partly substituting pork with insect. Both for rats fed a pork diet and rats fed a diet with partial replacement of pork with insect, the GM was dominated by Lactobacillus, Clostridium cluster XI and Akkermansia. However, Bray-Curtis dissimilarity metrics were different when insects were included in the diet. Introduction of insects in a common Western omnivore diet alters the gut microbiome diversity with consequences for endogenous metabolism. This finding highlights the importance of assessing gastrointestinal tract effects when evaluating new protein sources as meat replacements.

Molecular Aspects of Lifestyle and Environmental Effects in Patients With Diabetes: JACC Focus Seminar

Diabetes is characterized as an integrated condition of dysregulated metabolism across multiple tissues, with well-established consequences on the cardiovascular system. Recent advances in precision phenotyping in biofluids and tissues in large human observational and interventional studies have afforded a unique opportunity to translate seminal findings in models and cellular systems to patients at risk for diabetes and its complications. Specifically, techniques to assay metabolites, proteins, and transcripts, alongside more recent assessment of the gut microbiome, underscore the complexity of diabetes in patients, suggesting avenues for precision phenotyping of risk, response to intervention, and potentially novel therapies. In addition, the influence of external factors and inputs (eg, activity, diet, medical therapies) on each domain of molecular characterization has gained prominence toward better understanding their role in prevention. Here, the authors provide a broad overview of the role of several of these molecular domains in human translational investigation in diabetes.

Molecular Portrait of an Athlete

Sequencing of the human genome and further developments in "omics" technologies have opened up new possibilities in the study of molecular mechanisms underlying athletic performance. It is expected that molecular markers associated with the development and manifestation of physical qualities (speed, strength, endurance, agility, and flexibility) can be successfully used in the selection systems in sports. This includes the choice of sports specialization, optimization of the training process, and assessment of the current functional state of an athlete (such as overtraining). This review summarizes and analyzes the genomic, proteomic, and metabolomic studies conducted in the field of sports medicine.

Metabolomic profiling identifies complex lipid species and amino acid analogues associated with response to weight loss interventions

Obesity is an epidemic internationally. While weight loss interventions are efficacious, they are compounded by heterogeneity with regards to clinically relevant metabolic responses. Thus, we sought to identify metabolic biomarkers that are associated with beneficial metabolic changes to weight loss and which distinguish individuals with obesity who would most benefit from a given type of intervention. Liquid chromatography mass spectrometry-based profiling was used to measure 765 metabolites in baseline plasma from three different weight loss studies: WLM (behavioral intervention, N = 443), STRRIDE-PD (exercise intervention, N = 163), and CBD (surgical cohort, N = 125). The primary outcome was percent change in insulin resistance (as measured by the Homeostatic Model Assessment of Insulin Resistance [%ΔHOMA-IR]) over the intervention. Overall, 92 individual metabolites were associated with %ΔHOMA-IR after adjustment for multiple comparisons. Concordantly, the most significant metabolites were triacylglycerols (TAGs; p = 2.3e-5) and diacylglycerols (DAGs; p = 1.6e-4), with higher baseline TAG and DAG levels associated with a greater improvement in insulin resistance with weight loss. In tests of heterogeneity, 50 metabolites changed differently between weight loss interventions; we found amino acids, peptides, and their analogues to be most significant (4.7e-3) in this category. Our results highlight novel metabolic pathways associated with heterogeneity in response to weight loss interventions, and related biomarkers which could be used in future studies of personalized approaches to weight loss interventions.

Genetic and environmental influences on covariation in reproducible diet-metabolite associations

BACKGROUND

Early applications of metabolomics in nutrition and health research identified associations between dietary patterns and metabolomic profiles. Twin studies show that diet-related phenotypes and diet-associated metabolites are influenced by genes. However, studies have not examined whether diet-metabolite associations are explained by genetic or environmental factors and whether these associations are reproducible over multiple time points.

OBJECTIVE

This research aims to examine the genetic and environmental factors influencing covariation in diet-metabolite associations that are reproducible over time in healthy twins.

METHODS

The UCD Twin Study is a semi-longitudinal classic twin study that collected repeated dietary, anthropometric, and urinary data over 2 months. Correlation analysis identified associations between diet quality measured using the Healthy Eating Index (HEI) and urinary metabolomic profiles at 3 time points. Diet-associated metabolites were examined using linear regression to identify those significantly influenced by familial factors between twins and those significantly influenced by unique factors. Cholesky decomposition modeling quantified the genetic and environmental path coefficients through associated dietary components onto the metabolites.

RESULTS

The HEI was associated with 14 urinary metabolites across 3 metabolomic profiles (r: ±0.15-0.49). For 8 diet-metabolite associations, genetic or shared environmental factors influencing HEI component scores significantly influenced variation in metabolites (β: 0.40-0.52). A significant relation was observed between dietary intakes of whole grain and acetoacetate (β: -0.50, P < 0.001) and β-hydroxybutyrate (β: -0.46, P < 0.001), as well as intakes of saturated fat and acetoacetate (β: 0.47, P < 0.001) and β-hydroxybutyrate (β: 0.52, P < 0.001). For these diet-metabolite associations a common shared environmental factor explained 66-69% of variance in the metabolites.

CONCLUSIONS

This study shows that diet-metabolite associations are reproducible in 3 urinary metabolomic profiles. Components of the HEI covary with metabolites, and covariation is largely due to the shared environment.

Classifying Individuals Into a Dietary Pattern Based on Metabolomic Data

SCOPE

The objectives are to develop a metabolomic-based model capable of classifying individuals into dietary patterns and to investigate the reproducibility of the model.

METHODS AND RESULTS

K-means cluster analysis is employed to derive dietary patterns using metabolomic data. Differences across the dietary patterns are examined using nutrient biomarkers. The model is used to assign individuals to a dietary pattern in an independent cohort, A-DIET Confirm (n = 175) at four time points. The stability of participants to a dietary pattern is assessed. Four dietary patterns are derived: moderately unhealthy, convenience, moderately healthy, and prudent. The moderately unhealthy and convenience patterns has lower adherence to the alternative healthy eating index (AHEI) and the alternative mediterranean diet score (AMDS) compared to the moderately healthy and prudent patterns (AHEI = 24.5 and 22.9 vs 26.7 and 28.4, p < 0.001). The dietary patterns are replicated in A-DIET Confirm, with good reproducibility across four time points. The stability of participants' dietary pattern membership ranged from 25.0% to 61.5%.

CONCLUSION

The multivariate model classifies individuals into dietary patterns based on metabolomic data. In an independent cohort, the model classifies individuals into dietary patterns at multiple time points furthering the potential of such an approach for nutrition research.

Comparison of 24-Hour Recall and 3-Day Food Records during the Complementary Feeding Period in Thai Infants and Evaluation of Plasma Amino Acids as Markers of Protein Intake

Background: An accurate and reliable measurement of nutrient intake is the first and foremost step in order to optimise infant nutrition and evaluate its impact on health outcomes. However, research on the validity of dietary assessment tools used during the weaning period is limited, especially in lower-middle income countries. The primary aim of this study was to evaluate relative validity of a 24-h recall method (24-HR) using a 3-day food record (3-DFR). A secondary aim was to investigate association between protein intake from 3-DFR and plasma amino acids as a potential protein biomarker. Methods A multicentre, prospective cohort study was conducted in Chiang Mai, Thailand from June 2018 to May 2019. Food consumption data were collected in healthy infants using 24-HR and 3-DFR at 9 and 12 months of age. Blood samples were obtained at 12 months (M). Plasma amino acids were analysed using high performance liquid chromatography. Results Of 145 infants, 49% were female. At group level, paired t-tests/Wilcoxon signed rank tests did not show significant differences between average nutrient intakes from the 2 dietary assessment methods, except for vitamin A and vitamin C. Weighted kappa (Kw) was acceptable for all nutrients, except for vitamin A intake at 9 M (Kw = 0.15). The Bland–Altman analyses were unbiased for most nutrients with variable limits of agreement. At individual level, correlation coefficients (r) ranged from acceptable to excellent (r = 0.37–0.87) while cross-classifications showed acceptable outcomes, except for vitamin A. Multivariate analyses showed significant associations between protein intake at 12 M from the 3-DFR and plasma concentrations of branched-chain amino acids (BCAA) and essential amino acids (EAA), even after adjusting for gender, milk feeding type and energy intake. Conclusions For infants aged 9–12 M, a 24-HR can be used as a more practical alternative to a 3-DFR for most nutrients although caution is required for some micronutrients, especially vitamin A. A repeated interview might further improve the accuracy. Furthermore, protein intake, particularly animal-based protein, significantly predicted plasma BCAA and EAA concentrations regardless of gender, type of milk feeding and energy consumption.

Fasting plasma metabolomic profiles are altered by three days of standardized diet and restricted physical activity

Objective

Few studies have examined the effects of participants' diet and activity prior to sample collection on metabolomics profiles, and results have been conflicting. We compared the effects of overnight fasting with or without 3 days of standardized diet and restricted physical activity on the human blood metabolome, and examined the effects of these protocols on our ability to detect differences in metabolomics profiles in adolescent girls with obesity and polycystic ovary syndrome (PCOS) vs. sex and BMI-matched controls.

Methods

This was a cross-sectional study of 16 adolescent girls with obesity and PCOS and 5 sex and BMI-matched controls. Fasting plasma metabolomic profiles were measured twice in each participant: once without preceding restriction of physical activity or control of macronutrient content ("typical fasting visit"), and again after 12 h of monitored inpatient fasting with 3 days of standardized diet and avoidance of vigorous exercise ("controlled fasting visit"). Moderated paired t-tests with FDR correction for multiple testing and multilevel sparse partial least-squares discriminant analysis (sPLS-DA) were used to examine differences between the 2 visits and to compare the PCOS and control groups with the 2 visits combined and again after stratifying by visit.

Results

Twenty-three known metabolites were significantly different between the controlled fasting and typical fasting visits. Hypoxanthine and glycochenodeoxycholic acid had the largest increases in relative abundance at the controlled fasting visit compared to the typical fasting visit, while oleoyl-glycerol and oleamide had the largest increases in relative abundance at the typical fasting visit compared to the controlled fasting visit. sPLS-DA showed excellent discrimination between the 2 visits; however, when the samples from the 2 visits were combined, differences between the PCOS and control groups could not be detected. After stratifying by visit, discrimination of PCOS status was improved.

Conclusions

There were differences in fasting metabolomic profiles following typical fasting vs monitored fasting with preceding restriction of physical activity and control of macronutrient content, and combining samples from the two visits obscured differences by PCOS status. In studies performing metabolomics analysis, careful attention should be paid to acute diet and activity history. Depending on the sample size of the study and the expected effect size of the outcomes of interest, control of diet and physical activity beyond typical outpatient fasting may not be required.

Plasma Metabolomic Profiles of Glycemic Index, Glycemic Load, and Carbohydrate Quality Index in the PREDIMED Study

BACKGROUND

The quality of carbohydrate consumed, assessed by the glycemic index (GI), glycemic load (GL), or carbohydrate quality index (CQI), affects the postprandial glycemic and insulinemic responses, which have been implicated in the etiology of several chronic diseases. However, it is unclear whether plasma metabolites involved in different biological pathways could provide functional insights into the role of carbohydrate quality indices in health.

OBJECTIVES

We aimed to identify plasma metabolomic profiles associated with dietary GI, GL, and CQI.

METHODS

The present study is a cross-sectional analysis of 1833 participants with overweight/obesity (mean age = 67 y) from 2 case-cohort studies nested within the PREDIMED (Prevención con Dieta Mediterránea) trial. Data extracted from validated FFQs were used to estimate the GI, GL, and CQI. Plasma concentrations of 385 metabolites were profiled with LC coupled to MS and associations of these metabolites with those indices were assessed with elastic net regression analyses.

RESULTS

A total of 58, 18, and 57 metabolites were selected for GI, GL, and CQI, respectively. Choline, cotinine, γ-butyrobetaine, and 36:3 phosphatidylserine plasmalogen were positively associated with GI and GL, whereas they were negatively associated with CQI. Fructose-glucose-galactose was negatively and positively associated with GI/GL and CQI, respectively. Consistent associations of 21 metabolites with both GI and CQI were found but in opposite directions. Negative associations of kynurenic acid, 22:1 sphingomyelin, and 38:6 phosphatidylethanolamine, as well as positive associations of 32:1 phosphatidylcholine with GI and GL were also observed. Pearson correlation coefficients between GI, GL, and CQI and the metabolomic profiles were 0.30, 0.22, and 0.27, respectively.

CONCLUSIONS

The GI, GL, and CQI were associated with specific metabolomic profiles in a Mediterranean population at high cardiovascular disease risk. Our findings may help in understanding the role of dietary carbohydrate indices in the development of cardiometabolic disorders. This trial was registered at isrctn.com as ISRCTN35739639.

Hypoglycemic Effect of Prolamin from Cooked Foxtail Millet (Setaria italic) on Streptozotocin-Induced Diabetic Mice

Millet proteins have been demonstrated to possess glucose-lowering and lipid metabolic disorder modulation functions against diabetes; however, the molecular mechanisms underlying their anti-diabetic effects remain unclear. The present study aimed to investigate the hypoglycemic effect of prolamin from cooked foxtail millet (PCFM) on type 2 diabetic mice, and explore the gut microbiota and serum metabolic profile changes that are associated with diabetes attenuation by PCFM. Our diabetes model was established using a high-fat diet combined with streptozotocin before PCFM or saline was daily administrated by gavage for 5 weeks. The results showed that PCFM ameliorated glucose metabolism disorders associated with type 2 diabetes. Furthermore, the effects of PCFM administration on gut microbiota and serum metabolome were investigated. 16S rRNA gene sequencing analysis indicated that PCFM alleviated diabetes-related gut microbiota dysbiosis in mice. Additionally, the serum metabolomics analysis revealed that the metabolite levels disturbed by diabetes were partly altered by PCFM. Notably, the decreased D-Glucose level caused by PCFM suggested that its anti-diabetic potential can be associated with the activation of glycolysis and the inhibition of gluconeogenesis, starch and sucrose metabolism and galactose metabolism. In addition, the increased serotonin level caused by PCFM may stimulate insulin secretion by pancreatic β-cells, which contributed to its hypoglycemic effect. Taken together, our research demonstrated that the modulation of gut microbiota composition and the serum metabolomics profile was associated with the anti-diabetic effect of PCFM.

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.

Molecular Signature of Multisystem Cardiometabolic Stress and Its Association With Prognosis

Importance

Cardiometabolic disease is responsible for decreased longevity and poorer cardiovascular outcomes in the modern era. Metabolite profiling provides a specific measure of global metabolic function to examine specific metabolic mechanisms and pathways of cardiometabolic disease beyond its clinical definitions.

Objectives

To define a molecular basis for cardiometabolic stress and assess its association with cardiovascular prognosis.

Design, Setting, and Participants

A prospective observational cohort study was conducted in a population-based setting across 2 geographically distinct centers (Boston Puerto Rican Health Study [BPRHS], an ongoing study of individuals enrolled between June 1, 2004, and October 31, 2009; and Atherosclerosis Risk in Communities [ARIC] study, whose participants were originally sampled between November 24, 1986, and February 10, 1990, and followed up through December 31, 2017). Participants in the BPRHS were 668 Puerto Rican individuals with metabolite profiling living in Massachusetts, and participants in the ARIC study were 2152 individuals with metabolite profiling and long-term follow-up for mortality and cardiovascular outcomes. Statistical analysis was performed from October 1, 2018, to March 13, 2020.

Exposure

The primary exposure was metabolite profiles across both cohorts.

Main Outcomes and Measures

Outcomes included associations with multisystem cardiometabolic stress and all-cause mortality and incident coronary heart disease (in the ARIC study).

Results

Participants in the BPRHS (N = 668; 491 women; mean [SD] age, 57.0 [7.4] years; mean [SD] body mass index [calculated as weight in kilograms divided by height in meters squared], 32.0 [6.5]) had higher prevalent cardiometabolic risk relative to those in the ARIC study (N = 2152; 599 African American individuals; 1213 women; mean [SD] age, 54.3 [5.7] years; mean [SD] body mass index, 28.0 [5.5]). Multisystem cardiometabolic stress was defined for 668 Puerto Rican individuals in the BPRHS as a multidimensional composite of hypothalamic-adrenal axis activity, sympathetic activation, blood pressure, proatherogenic dyslipidemia, insulin resistance, visceral adiposity, and inflammation. A total of 260 metabolites associated with cardiometabolic stress were identified in the BPRHS, involving known and novel pathways of cardiometabolic disease (eg, amino acid metabolism, oxidative stress, and inflammation). A parsimonious metabolite-based score associated with cardiometabolic stress in the BPRHS was subsequently created; this score was applied to shared metabolites in the ARIC study, demonstrating significant associations with coronary heart disease and all-cause mortality after multivariable adjustment at a 30-year horizon (per SD increase in metabolomic score: hazard ratio, 1.14; 95% CI, 1.00-1.31; P = .045 for coronary heart disease; and hazard ratio, 1.15; 95% CI, 1.07-1.24; P < .001 for all-cause mortality).

Conclusions and Relevance

Metabolites associated with cardiometabolic stress identified known and novel pathways of cardiometabolic disease in high-risk, community-based cohorts and were associated with coronary heart disease and survival at a 30-year time horizon. These results underscore the shared molecular pathophysiology of metabolic dysfunction, cardiovascular disease, and longevity and suggest pathways for modification to improve prognosis across all linked conditions.

Investigation of Plasma Metabolic and Lipidomic Characteristics of a Chinese Cohort and a Pilot Study of Renal Cell Carcinoma Biomarker

Plasma metabolomics and lipidomics have been commonly used for biomarker discovery. Studies in white and Japanese populations suggested that gender and age can affect circulating plasma metabolite profiles; however, the metabolomics characteristics in Chinese population has not been surveyed. In our study, we applied liquid chromatography-mass spectrometry-based approach to analyze Chinese plasma metabolome and lipidome in a cohort of 534 healthy adults (aging from 15 to 79). Fatty-acid metabolism was found to be gender- and age-dependent in Chinese, similar with metabolomics characteristics in Japanese and white populations. Differently, lipids, such as TGs and DGs, were found to be gender-independent in Chinese population. Moreover, nicotinate and nicotinamide metabolism was found to be specifically age-related in Chinese. The application of plasma metabolome and lipidome for renal cell carcinoma diagnosis (143 RCC patients and 34 benign kidney tumor patients) showed good accuracy, with an area under the curve (AUC) of 0.971 for distinction from healthy control, and 0.839 for distinction from the benign. Bile acid metabolism was found to be related to RCC probably combination with intestinal microflora. Definition of the variation and characteristics of Chinese normal plasma metabolome and lipidome might provide a basis for disease biomarker analysis.

Replacing soybean meal with rapeseed meal and faba beans in a growing-finishing pig diet: Effect on growth performance, meat quality and metabolite changes

Rapeseed meal and faba beans (RSM/FB) can serve as an alternative to imported soybean meal (SBM). In this study, forty Norwegian crossbred ([Landrace x Yorkshire] x Duroc) growing-finishing pigs (108.7 ± 4.2 kg final BW) were fed a diet with either SBM or RSM/FB as protein sources. RSM/FB increased feed conversion ratio (P = .04) in the finishing period, reduced lightness (P = .04) and yellowness (P = .004) of meat, changed amounts of individual fatty acids, but not of total SFA, MUFA and PUFA. Importantly, RSM/FB reduced the glucose level (P < .05) in meat. Lower pyroglutamic acid (P = .06) in RSM/FB indicate lower oxidative stress in pre-rigor muscle cell. Increased abundance of free amino acids, sweet tasting metabolites, reduced warmed-over flavor and flavor attributes indicated desirable properties of RSM/FB meat. To conclude, RSM/FB in pig diet supported growth performance and carcass quality comparable to SBM and had a positive effect on meat quality.

The Mediterranean diet, plasma metabolome, and cardiovascular disease risk

AIMS

To investigate whether metabolic signature composed of multiple plasma metabolites can be used to characterize adherence and metabolic response to the Mediterranean diet and whether such a metabolic signature is associated with cardiovascular disease (CVD) risk.

METHODS AND RESULTS

Our primary study cohort included 1859 participants from the Spanish PREDIMED trial, and validation cohorts included 6868 participants from the US Nurses' Health Studies I and II, and Health Professionals Follow-up Study (NHS/HPFS). Adherence to the Mediterranean diet was assessed using a validated Mediterranean Diet Adherence Screener (MEDAS), and plasma metabolome was profiled by liquid chromatography-tandem mass spectrometry. We observed substantial metabolomic variation with respect to Mediterranean diet adherence, with nearly one-third of the assayed metabolites significantly associated with MEDAS (false discovery rate < 0.05). Using elastic net regularized regressions, we identified a metabolic signature, comprised of 67 metabolites, robustly correlated with Mediterranean diet adherence in both PREDIMED and NHS/HPFS (r = 0.28-0.37 between the signature and MEDAS; P = 3 × 10-35 to 4 × 10-118). In multivariable Cox regressions, the metabolic signature showed a significant inverse association with CVD incidence after adjusting for known risk factors (PREDIMED: hazard ratio [HR] per standard deviation increment in the signature = 0.71, P < 0.001; NHS/HPFS: HR = 0.85, P = 0.001), and the association persisted after further adjustment for MEDAS scores (PREDIMED: HR = 0.73, P = 0.004; NHS/HPFS: HR = 0.85, P = 0.004). Further genome-wide association analysis revealed that the metabolic signature was significantly associated with genetic loci involved in fatty acids and amino acids metabolism. Mendelian randomization analyses showed that the genetically inferred metabolic signature was significantly associated with risk of coronary heart disease (CHD) and stroke (odds ratios per SD increment in the genetically inferred metabolic signature = 0.92 for CHD and 0.91 for stroke; P < 0.001).

CONCLUSIONS

We identified a metabolic signature that robustly reflects adherence and metabolic response to a Mediterranean diet, and predicts future CVD risk independent of traditional risk factors, in Spanish and US cohorts.

Genetics and Not Shared Environment Explains Familial Resemblance in Adult Metabolomics Data

Metabolites are small molecules involved in cellular metabolism where they act as reaction substrates or products. The term 'metabolomics' refers to the comprehensive study of these molecules. The concentrations of metabolites in biological tissues are under genetic control, but this is limited by environmental factors such as diet. In adult mono- and dizygotic twin pairs, we estimated the contribution of genetic and shared environmental influences on metabolite levels by structural equation modeling and tested whether the familial resemblance for metabolite levels is mainly explained by genetic or by environmental factors that are shared by family members. Metabolites were measured across three platforms: two based on proton nuclear magnetic resonance techniques and one employing mass spectrometry. These three platforms comprised 237 single metabolic traits of several chemical classes. For the three platforms, metabolites were assessed in 1407, 1037 and 1116 twin pairs, respectively. We carried out power calculations to establish what percentage of shared environmental variance could be detected given these sample sizes. Our study did not find evidence for a systematic contribution of shared environment, defined as the influence of growing up together in the same household, on metabolites assessed in adulthood. Significant heritability was observed for nearly all 237 metabolites; significant contribution of the shared environment was limited to 6 metabolites. The top quartile of the heritability distribution was populated by 5 of the 11 investigated chemical classes. In this quartile, metabolites of the class lipoprotein were significantly overrepresented, whereas metabolites of classes glycerophospholipids and glycerolipids were significantly underrepresented.

Nutritional Metabolomics in Cancer Epidemiology: Current Trends, Challenges, and Future Directions

PURPOSE OF REVIEW

Metabolomics offers several opportunities for advancement in nutritional cancer epidemiology; however, numerous research gaps and challenges remain. This narrative review summarizes current research, challenges, and future directions for epidemiologic studies of nutritional metabolomics and cancer.

RECENT FINDINGS

Although many studies have used metabolomics to investigate either dietary exposures or cancer, few studies have explicitly investigated diet-cancer relationships using metabolomics. Most studies have been relatively small (≤ ~ 250 cases) or have assessed a limited number of nutritional metabolites (e.g., coffee or alcohol-related metabolites). Nutritional metabolomic investigations of cancer face several challenges in study design; biospecimen selection, handling, and processing; diet and metabolite measurement; statistical analyses; and data sharing and synthesis. More metabolomics studies linking dietary exposures to cancer risk, prognosis, and survival are needed, as are biomarker validation studies, longitudinal analyses, and methodological studies. Despite the remaining challenges, metabolomics offers a promising avenue for future dietary cancer research.