Plasma Metabolites Associated with Frequent Red Wine Consumption: A Metabolomics Approach within the PREDIMED Study

Plasma metabolite profile of legume consumption and future risk of type 2 diabetes and cardiovascular disease

BACKGROUND

Legume consumption has been linked to a reduced risk of type 2 diabetes (T2D) and cardiovascular disease (CVD), while the potential association between plasma metabolites associated with legume consumption and the risk of cardiometabolic diseases has never been explored. Therefore, we aimed to identify a metabolite signature of legume consumption, and subsequently investigate its potential association with the incidence of T2D and CVD.

METHODS

The current cross-sectional and longitudinal analysis was conducted in 1833 PREDIMED study participants (mean age 67 years, 57.6% women) with available baseline metabolomic data. A subset of these participants with 1-year follow-up metabolomics data (n = 1522) was used for internal validation. Plasma metabolites were assessed through liquid chromatography-tandem mass spectrometry. Cross-sectional associations between 382 different known metabolites and legume consumption were performed using elastic net regression. Associations between the identified metabolite profile and incident T2D and CVD were estimated using multivariable Cox regression models.

RESULTS

Specific metabolic signatures of legume consumption were identified, these included amino acids, cortisol, and various classes of lipid metabolites including diacylglycerols, triacylglycerols, plasmalogens, sphingomyelins and other metabolites. Among these identified metabolites, 22 were negatively and 18 were positively associated with legume consumption. After adjustment for recognized risk factors and legume consumption, the identified legume metabolite profile was inversely associated with T2D incidence (hazard ratio (HR) per 1 SD: 0.75, 95% CI 0.61-0.94; p = 0.017), but not with CVD incidence risk (1.01, 95% CI 0.86-1.19; p = 0.817) over the follow-up period.

CONCLUSIONS

This study identified a set of 40 metabolites associated with legume consumption and with a reduced risk of T2D development in a Mediterranean population at high risk of cardiovascular disease.

TRIAL REGISTRATION

ISRCTN35739639.

Olive oil consumption, plasma metabolites, and risk of type 2 diabetes and cardiovascular disease

BACKGROUND

Olive oil consumption has been inversely associated with the risk of type 2 diabetes (T2D) and cardiovascular disease (CVD). However, the impact of olive oil consumption on plasma metabolites remains poorly understood. This study aims to identify plasma metabolites related to total and specific types of olive oil consumption, and to assess the prospective associations of the identified multi-metabolite profiles with the risk of T2D and CVD.

METHODS

The discovery population included 1837 participants at high cardiovascular risk from the PREvención con DIeta MEDiterránea (PREDIMED) trial with available metabolomics data at baseline. Olive oil consumption was determined through food-frequency questionnaires (FFQ) and adjusted for total energy. A total of 1522 participants also had available metabolomics data at year 1 and were used as the internal validation sample. Plasma metabolomics analyses were performed using LC-MS. Cross-sectional associations between 385 known candidate metabolites and olive oil consumption were assessed using elastic net regression analysis. A 10-cross-validation (CV) procedure was used, and Pearson correlation coefficients were assessed between metabolite-weighted models and FFQ-derived olive oil consumption in each pair of training-validation data sets within the discovery sample. We further estimated the prospective associations of the identified plasma multi-metabolite profile with incident T2D and CVD using multivariable Cox regression models.

RESULTS

We identified a metabolomic signature for the consumption of total olive oil (with 74 metabolites), VOO (with 78 metabolites), and COO (with 17 metabolites), including several lipids, acylcarnitines, and amino acids. 10-CV Pearson correlation coefficients between total olive oil consumption derived from FFQs and the multi-metabolite profile were 0.40 (95% CI 0.37, 0.44) and 0.27 (95% CI 0.22, 0.31) for the discovery and validation sample, respectively. We identified several overlapping and distinct metabolites according to the type of olive oil consumed. The baseline metabolite profiles of total and extra virgin olive oil were inversely associated with CVD incidence (HR per 1SD: 0.79; 95% CI 0.67, 0.92 for total olive oil and 0.70; 0.59, 0.83 for extra virgin olive oil) after adjustment for confounders. However, no significant associations were observed between these metabolite profiles and T2D incidence.

CONCLUSIONS

This study reveals a panel of plasma metabolites linked to the consumption of total and specific types of olive oil. The metabolite profiles of total olive oil consumption and extra virgin olive oil were associated with a decreased risk of incident CVD in a high cardiovascular-risk Mediterranean population, though no associations were observed with T2D incidence.

TRIAL REGISTRATION

The PREDIMED trial was registered at ISRCTN ( http://www.isrctn.com/ , ISRCTN35739639).

Exploring Human Metabolome after Wine Intake-A Review

Wine has a rich history dating back to 2200 BC, originally recognized for its medicinal properties. Today, with the aid of advanced technologies like metabolomics and sophisticated analytical techniques, we have gained remarkable insights into the molecular-level changes induced by wine consumption in the human organism. This review embarks on a comprehensive exploration of the alterations in human metabolome associated with wine consumption. A great number of 51 studies from the last 25 years were reviewed; these studies systematically investigated shifts in metabolic profiles within blood, urine, and feces samples, encompassing both short-term and long-term studies of the consumption of wine and wine derivatives. Significant metabolic alterations were observed in a wide variety of metabolites belonging to different compound classes, such as phenolic compounds, lipids, organic acids, and amino acids, among others. Within these classes, both endogenous metabolites as well as diet-related metabolites that exhibited up-regulation or down-regulation following wine consumption were included. The up-regulation of short-chain fatty acids and the down-regulation of sphingomyelins after wine intake, as well as the up-regulation of gut microbial fermentation metabolites like vanillic and syringic acid are some of the most important findings reported in the reviewed literature. Our results confirm the intact passage of certain wine compounds, such as tartaric acid and other wine acids, to the human organism. In an era where the health effects of wine consumption are of growing interest, this review offers a holistic perspective on the metabolic underpinnings of this centuries-old tradition.

Plasma metabolite profiles associated with the World Cancer Research Fund/American Institute for Cancer Research lifestyle score and future risk of cardiovascular disease and type 2 diabetes

BACKGROUND

A healthy lifestyle (HL) has been inversely related to type 2 diabetes (T2D) and cardiovascular disease (CVD). However, few studies have identified a metabolite profile associated with HL. The present study aims to identify a metabolite profile of a HL score and assess its association with the incidence of T2D and CVD in individuals at high cardiovascular risk.

METHODS

In a subset of 1833 participants (age 55-80y) of the PREDIMED study, we estimated adherence to a HL using a composite score based on the 2018 Word Cancer Research Fund/American Institute for Cancer Research recommendations. Plasma metabolites were analyzed using LC-MS/MS methods at baseline (discovery sample) and 1-year of follow-up (validation sample). Cross-sectional associations between 385 known metabolites and the HL score were assessed using elastic net regression. A 10-cross-validation procedure was used, and correlation coefficients or AUC were assessed between the identified metabolite profiles and the self-reported HL score. We estimated the associations between the identified metabolite profiles and T2D and CVD using multivariable Cox regression models.

RESULTS

The metabolite profiles that identified HL as a dichotomous or continuous variable included 24 and 58 metabolites, respectively. These are amino acids or derivatives, lipids, and energy intermediates or xenobiotic compounds. After adjustment for potential confounders, baseline metabolite profiles were associated with a lower risk of T2D (hazard ratio [HR] and 95% confidence interval (CI): 0.54, 0.38-0.77 for dichotomous HL, and 0.22, 0.11-0.43 for continuous HL). Similar results were observed with CVD (HR, 95% CI: 0.59, 0.42-0.83 for dichotomous HF and HR, 95%CI: 0.58, 0.31-1.07 for continuous HL). The reduction in the risk of T2D and CVD was maintained or attenuated, respectively, for the 1-year metabolomic profile.

CONCLUSIONS

In an elderly population at high risk of CVD, a set of metabolites was selected as potential metabolites associated with the HL pattern predicting the risk of T2D and, to a lesser extent, CVD. These results support previous findings that some of these metabolites are inversely associated with the risk of T2D and CVD.

TRIAL REGISTRATION

The PREDIMED trial was registered at ISRCTN ( http://www.isrctn.com/ , ISRCTN35739639).

Plasma Metabolite Profiles Associated with the Amount and Source of Meat and Fish Consumption and the Risk of Type 2 Diabetes

SCOPE

Consumption of meat has been associated with a higher risk of type 2 diabetes (T2D), but if plasma metabolite profiles associated with these foods reflect this relationship is unknown. The objective is to identify a metabolite signature of consumption of total meat (TM), red meat (RM), processed red meat (PRM), and fish and examine if they are associated with T2D risk.

METHODS AND RESULTS

The discovery population includes 1833 participants from the PREDIMED trial. The internal validation sample includes 1522 participants with available 1-year follow-up metabolomic data. Associations between metabolites and TM, RM, PRM, and fish are evaluated with elastic net regression. Associations between the profiles and incident T2D are estimated using Cox regressions. The profiles included 72 metabolites for TM, 69 for RM, 74 for PRM, and 66 for fish. After adjusting for T2D risk factors, only profiles of TM (Hazard Ratio (HR): 1.25, 95% CI: 1.06-1.49), RM (HR: 1.27, 95% CI: 1.07-1.52), and PRM (HR: 1.27, 95% CI: 1.07-1.51) are associated with T2D.

CONCLUSIONS

The consumption of TM, its subtypes, and fish is associated with different metabolites, some of which have been previously associated with T2D. Scores based on the identified metabolites for TM, RM, and PRM show a significant association with T2D risk.

Lipidomic Signatures of Dairy Consumption and Associated Changes in Blood Pressure and Other Cardiovascular Risk Factors Among Chinese Adults

BACKGROUND

Omics data may provide a unique opportunity to discover dairy-related biomarkers and their linked cardiovascular health.

METHODS

Dairy-related lipidomic signatures were discovered in baseline data from a Chinese cohort study (n=2140) and replicated in another Chinese study (n=212). Dairy intake was estimated by a validated food-frequency questionnaire. Lipidomics was profiled by high-coverage liquid chromatography-tandem mass spectrometry. Associations of dairy-related lipids with 6-year changes in cardiovascular risk factors were examined in the discovery cohort, and their causalities were analyzed by 2-sample Mendelian randomization using available genome-wide summary data.

RESULTS

Of 350 lipid metabolites, 4 sphingomyelins, namely sphingomyelin (OH) C32:2, sphingomyelin C32:1, sphingomyelin (2OH) C30:2, and sphingomyelin (OH) C38:2, were identified and replicated to be positively associated with total dairy consumption (β=0.130 to 0.148; P<1.43×10^-4), but not or weakly with nondairy food items. The score of 4 sphingomyelins showed inverse associations with 6-year changes in systolic (-2.68 [95% CI, -4.92 to -0.43]; P=0.019), diastolic blood pressures (-1.86 [95% CI, -3.12 to -0.61]; P=0.004), and fasting glucose (-0.25 [95% CI, -0.41 to -0.08]; P=0.003). Mendelian randomization analyses further revealed that genetically inferred sphingomyelin (OH) C32:2 was inversely associated with systolic (-0.57 [95% CI, -0.85 to -0.28]; P=9.16×10^-5) and diastolic blood pressures (-0.39 [95% CI, -0.59 to -0.20]; P=7.09×10^-5).

CONCLUSIONS

The beneficial effects of dairy products on cardiovascular health might be mediated through specific sphingomyelins among Chinese with overall low dairy consumption.

Amino Acids and Lipids Associated with Long-Term and Short-Term Red Meat Consumption in the Chinese Population: An Untargeted Metabolomics Study

Red meat (RM) consumption is correlated with multiple health outcomes. This study aims to identify potential biomarkers of RM consumption in the Chinese population and evaluate their predictive ability. We selected 500 adults who participated in the 2015 China Health and Nutrition Survey and examined their overall metabolome differences by RM consumption by using elastic-net regression, then evaluate the predictivity of a combination of filtered metabolites; 1108 metabolites were detected. In the long-term RM consumption analysis 12,13-DiHOME, androstenediol (3α, 17α) monosulfate 2, and gamma-Glutamyl-2-aminobutyrate were positively associated, 2-naphthol sulfate and S-methylcysteine were negatively associated with long-term high RM consumption, the combination of metabolites prediction model evaluated by area under the receiver operating characteristic curve (AUC) was 70.4% (95% CI: 59.9–80.9%). In the short-term RM consumption analysis, asparagine, 4-hydroxyproline, and 3-hydroxyisobutyrate were positively associated, behenoyl sphingomyelin (d18:1/22:0) was negatively associated with short-term high RM consumption. Combination prediction model AUC was 75.6% (95% CI: 65.5–85.6%). We identified 10 and 11 serum metabolites that differed according to LT and ST RM consumption which mainly involved branch-chained amino acids, arginine and proline, urea cycle and polyunsaturated fatty acid metabolism. These metabolites may become a mediator of some chronic diseases among high RM consumers and provide new evidence for RM biomarkers.

Circulating amino acids and amino acid-related metabolites and risk of breast cancer among predominantly premenopausal women

Known modifiable risk factors account for a small fraction of premenopausal breast cancers. We investigated associations between pre-diagnostic circulating amino acid and amino acid-related metabolites (N = 207) and risk of breast cancer among predominantly premenopausal women of the Nurses' Health Study II using conditional logistic regression (1057 cases, 1057 controls) and multivariable analyses evaluating all metabolites jointly. Eleven metabolites were associated with breast cancer risk (q-value < 0.2). Seven metabolites remained associated after adjustment for established risk factors (p-value < 0.05) and were selected by at least one multivariable modeling approach: higher levels of 2-aminohippuric acid, kynurenic acid, piperine (all three with q-value < 0.2), DMGV and phenylacetylglutamine were associated with lower breast cancer risk (e.g., piperine: ORadjusted (95%CI) = 0.84 (0.77-0.92)) while higher levels of creatine and C40:7 phosphatidylethanolamine (PE) plasmalogen were associated with increased breast cancer risk (e.g., C40:7 PE plasmalogen: ORadjusted (95%CI) = 1.11 (1.01-1.22)). Five amino acids and amino acid-related metabolites (2-aminohippuric acid, DMGV, kynurenic acid, phenylacetylglutamine, and piperine) were inversely associated, while one amino acid and a phospholipid (creatine and C40:7 PE plasmalogen) were positively associated with breast cancer risk among predominately premenopausal women, independent of established breast cancer risk factors.

Dairy consumption, plasma metabolites, and risk of type 2 diabetes

BACKGROUND

Epidemiologic studies have reported a modest inverse association between dairy consumption and the risk of type 2 diabetes (T2D). Whether plasma metabolite profiles associated with dairy consumption reflect this relationship remains unknown.

OBJECTIVES

We aimed to identify the plasma metabolites associated with total and specific dairy consumption, and to evaluate the association between the identified multi-metabolite profiles and T2D.

METHODS

The discovery population included 1833 participants from the Prevención con Dieta Mediterránea (PREDIMED) trial. The confirmatory cohorts included 1522 PREDIMED participants at year 1 of the trial and 4932 participants from the Nurses' Health Studies (NHS), Nurses' Health Study II (NHSII), and Health Professionals Follow-Up Study US-based cohorts. Dairy consumption was assessed using validated FFQs. Plasma metabolites (n = 385) were profiled using LC-MS. We identified the dairy-related metabolite profiles using elastic net regularized regressions with a 10-fold cross-validation procedure. We evaluated the associations between the metabolite profiles and incident T2D in the discovery and the confirmatory cohorts.

RESULTS

Total dairy intake was associated with 38 metabolites. C14:0 sphingomyelin (positive coefficient), C34:0 phosphatidylethanolamine (positive coefficient), and γ-butyrobetaine (negative coefficient) were associated in a directionally similar fashion with total and specific (milk, yogurt, cheese) dairy consumption. The Pearson correlation coefficients between self-reported total dairy intake and predicted total dairy intake based on the corresponding multi-metabolite profile were 0.37 (95% CI, 0.33-0.40) in the discovery cohort and 0.16 (95% CI, 0.13-0.19) in the US confirmatory cohort. After adjusting for T2D risk factors, a higher total dairy intake-related metabolite profile score was associated with a lower T2D risk [HR per 1 SD; discovery cohort: 0.76 (95% CI, 0.63-0.90); US confirmatory cohort: 0.88 (95% CI, 0.78-0.99)].

CONCLUSIONS

Total dairy intake was associated with 38 metabolites, including 3 consistently associated with dairy subtypes (C14:0 sphingomyelin, C34:0 phosphatidylethanolamine, γ-butyrobetaine). A score based on the 38 identified metabolites showed an inverse association with T2D risk in Spanish and US populations.

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

SCOPE

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

METHODS AND RESULTS

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

CONCLUSIONS

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

Deep dive to the secrets of the PREDIMED trial

PURPOSE OF REVIEW

The aim of this study was to briefly summarize the contribution of the PREDIMED (PREvención con DIeta MEDiterránea) trial on cardiovascular evidence and examine in depth its groundbreaking trajectory.PREDIMED was conducted during 2003-2010 and represented the largest primary prevention trial ever testing the effects of changes in a complete food pattern (namely, the Mediterranean diet) on cardiovascular disease (CVD). Major contributions relied on the relevant changes in the food pattern attained by the behavioural intervention and their robust effect in reducing hard clinical end-points. Given some potential concerns, which were appropriately addressed with supporting analyses, this review is timely and relevant.

RECENT FINDINGS

PREDIMED has continued contributing to the existing literature with extensive, robust and abundant new evidence on the benefits of the Mediterranean diet, particularly on cardiovascular health, including recent studies using high-throughput metabolomic techniques. After robustly addressing some controversies, the conclusions of the original trial remained unaltered.

SUMMARY

The Mediterranean diet represents an effective and robust nutritional strategy against CVD in high cardiovascular risk populations. Recent findings from the PREDIMED have identified a metabolic signature of the Mediterranean diet that can objectively determine dietary adherence and predict CVD risk. This metabolomic signature opens up a new era for nutritional epidemiology and personalized nutrition.

Walnut Consumption, Plasma Metabolomics, and Risk of Type 2 Diabetes and Cardiovascular Disease

BACKGROUND

Walnut consumption is associated with lower risk of type 2 diabetes (T2D) and cardiovascular disease (CVD). However, it is unknown whether plasma metabolites related to walnut consumption are also associated with lower risk of cardiometabolic diseases.

OBJECTIVES

The study aimed to identify plasma metabolites associated with walnut consumption and evaluate the prospective associations between the identified profile and risk of T2D and CVD.

METHODS

The discovery population included 1833 participants at high cardiovascular risk from the PREvención con DIeta MEDiterránea (PREDIMED) study with available metabolomics data at baseline. The study population included 57% women (baseline mean BMI (in kg/m2): 29.9; mean age: 67 y). A total of 1522 participants also had available metabolomics data at year 1 and were used as the internal validation population. Plasma metabolomics analyses were performed using LC-MS. Cross-sectional associations between 385 known metabolites and walnut consumption were assessed using elastic net continuous regression analysis. A 10-cross-validation (CV) procedure was used, and Pearson correlation coefficients were assessed between metabolite weighted models and self-reported walnut consumption in each pair of training-validation data sets within the discovery population. We further estimated the prospective associations between the identified metabolite profile and incident T2D and CVD using multivariable Cox regression models.

RESULTS

A total of 19 metabolites were significantly associated with walnut consumption, including lipids, purines, acylcarnitines, and amino acids. Ten-CV Pearson correlation coefficients between self-reported walnut consumption and the plasma metabolite profile were 0.16 (95% CI: 0.11, 0.20) in the discovery population and 0.15 (95% CI: 0.10, 0.20) in the validation population. The metabolite profile was inversely associated with T2D incidence (HR per 1 SD: 0.83; 95% CI: 0.71, 0.97; P = 0.02). For CVD incidence, the HR per 1-SD was 0.71 (95% CI: 0.60, 0.85; P < 0.001).

CONCLUSIONS

A metabolite profile including 19 metabolites was associated with walnut consumption and with a lower risk of incident T2D and CVD in a Mediterranean population at high cardiovascular risk.

Promoting Human Nutrition and Health through Plant Metabolomics: Current Status and Challenges

Simple Summary

This review summarizes the status, applications, and challenges of plant metabolomics in the context of crop breeding, food quality and safety, and human nutrition and health. It also highlights the importance of plant metabolomics in elucidating biochemical and genetic bases of traits associated with nutritive and healthy beneficial foods and other plant products to secure food supply, to ensure food quality, to protect humans from malnutrition and other diseases. Meanwhile, this review calls for comprehensive collaborations to accelerate relevant researches and applications in the context of human nutrition and health.

Abstract

Plant metabolomics plays important roles in both basic and applied studies regarding all aspects of plant development and stress responses. With the improvement of living standards, people need high quality and safe food supplies. Thus, understanding the pathways involved in the biosynthesis of nutritionally and healthily associated metabolites in plants and the responses to plant-derived biohazards in humans is of equal importance to meet people’s needs. For each, metabolomics has a vital role to play, which is discussed in detail in this review. In addition, the core elements of plant metabolomics are highlighted, researches on metabolomics-based crop improvement for nutrition and safety are summarized, metabolomics studies on plant natural products including traditional Chinese medicine (TCM) for health promotion are briefly presented. Challenges are discussed and future perspectives of metabolomics as one of the most important tools to promote human nutrition and health are proposed.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

The Effects of a Mediterranean Diet Intervention on Targeted Plasma Metabolic Biomarkers among US Firefighters: A Pilot Cluster-Randomized Trial

Metabolomics is improving the understanding of the mechanisms of the health effects of diet. Previous research has identified several metabolites associated with the Mediterranean Diet (MedDiet), but knowledge about longitudinal changes in metabolic biomarkers after a MedDiet intervention is scarce. A subsample of 48 firefighters from a cluster-randomized trial at Indianapolis fire stations was randomly selected for the metabolomics study at 12 months of follow up (time point 1), where Group 1 (n = 24) continued for another 6 months in a self-sustained MedDiet intervention, and Group 2 (n = 24), the control group at that time, started with an active MedDiet intervention for 6 months (time point 2). A total of 225 metabolites were assessed at the two time points by using a targeted NMR platform. The MedDiet score improved slightly but changes were non-significant (intervention: 24.2 vs. 26.0 points and control group: 26.1 vs. 26.5 points). The MedDiet intervention led to favorable changes in biomarkers related to lipid metabolism, including lower LDL-C, ApoB/ApoA1 ratio, remnant cholesterol, M-VLDL-CE; and higher HDL-C, and better lipoprotein composition. This MedDiet intervention induces only modest changes in adherence to the MedDiet and consequently in metabolic biomarkers. Further research should confirm these results based on larger study samples in workplace interventions with powerful study designs.

Supercritical fluid chromatography - Mass spectrometry in metabolomics: Past, present, and future perspectives

Metabolomics, which consists of the comprehensive analysis of metabolites within a biological system, has been playing a growing role in the implementation of personalized medicine in modern healthcare. A wide range of analytical approaches are used in metabolomics, notably mass spectrometry (MS) combined to liquid chromatography (LC), gas chromatography (GC), or capillary electrophoresis (CE). However, none of these methods enable a comprehensive analysis of the metabolome, due to its extreme complexity and the large differences in physico-chemical properties between metabolite classes. In this context, supercritical fluid chromatography (SFC) represents a promising alternative approach to improve the metabolome coverage, while further increasing the analysis throughput. SFC, which uses supercritical CO₂ as mobile phase, leads to numerous advantages such as improved kinetic performance and lower environmental impact. This chromatographic technique has gained a significant interest since the introduction of advanced instrumentation, together with the introduction of dedicated interfaces for hyphenating SFC to MS. Moreover, new developments in SFC column chemistry (including sub-2 µm particles), as well as the use of large amounts of organic modifiers and additives in the CO₂-based mobile phase, significantly extended the application range of SFC, enabling the simultaneous analysis of a large diversity of metabolites. Over the last years, several applications have been reported in metabolomics using SFC-MS - from lipophilic compounds, such as steroids and other lipids, to highly polar compounds, such as carbohydrates, amino acids, or nucleosides. With all these advantages, SFC-MS is promised to a bright future in the field of metabolomics.