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

Emerging and established biomarkers of oculopharyngeal muscular dystrophy

Oculopharyngeal muscular dystrophy (OPMD) is a rare, primarily autosomal dominant, late onset muscular dystrophy commonly presenting with ptosis, dysphagia, and subsequent weakness of proximal muscles. Although OPMD diagnosis can be confirmed with high confidence by genetic testing, the slow progression of OPMD poses a significant challenge to clinical monitoring and a barrier to assessing the efficacy of treatments during clinical trials. Accordingly, there is a pressing need for more sensitive measures of OPMD progression, particularly those which do not require a muscle biopsy. This review provides an overview of progress in OPMD biomarkers from clinical assessment, quantitative imaging, histological assessments, and genomics, as well as hypothesis-generating "omics" approaches. The ongoing search for biomarkers relevant to OPMD progression needs an integrative, longitudinal approach combining validated and experimental approaches which may include clinical, imaging, demographic, and biochemical assessment methods. A multi-omics approach to biochemical biomarker discovery could help provide context for differences found between individuals with varying levels of disease activity and provide insight into pathomechanisms and prognosis of OPMD.

D-dimer to Creatinine Ratio: A Novel Biomarker Associated with Gensini Score in ST-Segment Elevation Myocardial Infarction Patients

Objective

We propose for the first time that D-dimer to creatinine ratio (DCR) may serve as a new clinical biomarker and explore its association with ST-segment elevation myocardial infarction (STEMI).

Methods

347 STEMI patients with complete D-dimer and creatinine were included in the analysis. According to the median of DCR value, patients were divided into the lower DCR group (DCR < 1.402, n = 173) and the higher DCR group (DCR ≥ 1.402, n = 174), and the differences between the two groups were compared. In addition, patients were divided into four groups according to the quartiles of Gensini score: Group 1(Gensini score ≤ 34, n = 88); Group 2(34 < Gensini score ≤ 65, n = 88); Group 3(65 < Gensini score ≤100, n = 87); Group 4(Gensini score ＞100, n = 84). Multivariate linear and multivariate logistic regression analyzes were performed to determine independent predictors of the Gensini score.

Results

High DCR group had higher Gensini score compared with the low DCR group ( P < .05). DCR was positively correlated with Gensini score (r = 0.493, P < .001). Multiple linear regression analysis showed that Previous MI (r = 11.312, P = .035) and DCR (r = 5.129, P < .001) were independent risk factors associated with the Gensini score. Multivariate logistic regression analysis showed that, compared to Group 1, DCR was an independent risk factor in Group 2, Group 3, Group 4 ( P < .001).

Conclusions

As a new and useful clinical biomarker, DCR was positively correlated with coronary Gensini score in STEMI patients.

Urine Metabolites as a Predictor of Warfarin Response Based on INR in Atrial Fibrillation

Background:

Warfarin is an anticoagulant with wide inter-individual variations in drug responses monitored based on the International Normalized Ratio (INR). It is commonly prescribed for atrial fibrillation (AF) and stroke. Oral anticoagulants (e.g., warfarin) reduce the risk of getting a stroke but increase the risk of hemorrhage. The proton nuclear magnetic resonance (1H-NMR) pharmacometabonomics technique is useful for determining drug responses. Furthermore, pharmacometabonomics analysis can help identify novel biomarkers of warfarin outcome/INR stability in urine.

Objectives:

The focus of this research was to determine if urine metabolites could predict the warfarin response based on INR in patients who were already taking warfarin (identification; phase I) and to determine if urine metabolites could distinguish between unstable and stable INR in patients who had just started taking warfarin (validation; phase II).

Methods:

A cross-sectional study was conducted. Ninety urine samples were collected for phase 1, with 49 having unstable INR and 41 having stable INR. In phase II, 21 urine samples were obtained, with 13 having an unstable INR and eight having a stable INR. The metabolites associated with unstable INR and stable INR could be determined using univariate and multivariate logistic regression analysis.

Results:

Multivariate logistic regression (MVLR) analysis showed that unstable INR was linked with seven regions.

Discussion:

The urine pharmacometabonomics technique utilized could differentiate between the urine metabolite profiles of the patients on warfarin for INR stability.

Conclusion:

1H-NMR-based pharmacometabonomics can help lead to a more individualized, controlled side effect for warfarin, thus minimizing undesirable effects in the future.

Different Isocaloric Meals and Adiposity Modify Energy Expenditure, Clinical and Metabolomic Biomarkers During Resting and Exercise States in a Randomized Cross-over Acute Trial of Normal Weight and Overweight/obese Men

BACKGROUND

Few studies have assessed the integrative effects of diet, BMI, and exercise on postprandial changes of energy and circulating metabolic profiles.

OBJECTIVES

We aimed to assess the collective effects of three isocaloric diets high in carbohydrate (74.2% energy), fat (64.6% energy), or protein (39.5% energy) on energy expenditure, clinical and metabolomic biomarkers under resting and exercise conditions in normal-weight and overweight/obese men.

METHODS

This cross-over controlled acute trial included 20 normal-weight (BMI: 18.5- <24) and 20 overweight/obese (BMI ≥ 24 kg/m2) men aged 18-45 years. Each of three test meals was provided for two continuous days: "Resting Day" without exercise, followed by "Exercise Day" with a bicycling exercise of 50% maximal oxygen consumption (postprandial 90-120 min). Energy expenditure (exploratory outcome of primary interest) was measured using indirect calorimetry. Fasting and postprandial 2-hour serum clinical and metabolomic biomarkers (secondary interest) were measured. Mixed models were used to examine the effects of diet, time, and/or BMI category.

RESULTS

On Resting Day, no significant between-meal differences were detected for energy expenditure. However, high-carbohydrate and high-fat meals induced the highest postprandial 2-hour increase in glucose (0.34 ± 0.15 mmol/L) and triglyceride (0.95 ± 0.09 mmol/L) respectively, while high-protein meal reduced glucose (-0.48 ± 0.08 mmol/L) and total cholesterol (-0.01 ± 0.03 mmol/L, all Pdiet < 0.001). On Exercise Day, high-carbohydrate diet significantly promoted carbohydrate oxidation rate but suppressed fat oxidation rate (Pdiet < 0.05), while its postprandial glucose response was attenuated by bicycling (-0.31 ± 0.03 mmol/L, Pexercise < 0.001). 69 metabolites were identified as key features in discriminating the three meals, and overweight/obese men had more varieties of metabolites than normal-weight men.

CONCLUSIONS

Three isocaloric meals induced unique postprandial changes in clinical and metabolomic biomarkers, while exercise prevented high-carbohydrate meal induced hyperglycemia. Overweight/obese men were more responsive to the meal challenges than normal-weight men. This trial was registered at clinicaltrials.gov as NCT03231618.

OUP accepted manuscript

Context

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

Objective

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

Data Sources

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

Data Extraction

Data extraction and bias assessment were undertaken in duplicate.

Data Analysis

A qualitative approach was applied, without statistical analysis.

Conclusion

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

Systematic Review Registration

PROSPERO registration no. CRD42019129839.

Habitual Choline Intakes across the Childbearing Years: A Review

Choline is an important nutrient during the first 1000 days post conception due to its roles in brain function. An increasing number of studies have measured choline intakes at the population level. We collated the evidence focusing on habitual choline intakes in the preconceptual, pregnancy, and lactation life stages. We conducted a review including studies published from 2004 to 2021. Twenty-six relevant publications were identified. After excluding studies with a high choline intake (>400 mg/day; two studies) or low choline intake (<200 mg/day; one study), average choline intake in the remaining 23 studies ranged from 233 mg/day to 383 mg/day, even with the inclusion of choline from supplements. Intakes were not higher in studies among pregnant and lactating women compared with studies in nonpregnant women. To conclude, during the childbearing years and across the globe, habitual intakes of choline from foods alone and foods and supplements combined appear to be consistently lower than the estimated adequate intakes for this target group. Urgent measures are needed to (1) improve the quality of choline data in global food composition databases, (2) encourage the reporting of choline intakes in dietary surveys, (3) raise awareness about the role(s) of choline in foetal–maternal health, and (4) consider formally advocating the use of choline supplements in women planning a pregnancy, pregnant, or lactating.

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

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

A Scoping Review of the Application of Metabolomics in Nutrition Research: The Literature Survey 2000-2019

Nutrimetabolomics is an emerging field in nutrition research, and it is expected to play a significant role in deciphering the interaction between diet and health. Through the development of omics technology over the last two decades, the definition of food and nutrition has changed from sources of energy and major/micro-nutrients to an essential exposure factor that determines health risks. Furthermore, this new approach has enabled nutrition research to identify dietary biomarkers and to deepen the understanding of metabolic dynamics and the impacts on health risks. However, so far, candidate markers identified by metabolomics have not been clinically applied and more efforts should be made to validate those. To help nutrition researchers better understand the potential of its application, this scoping review outlined the historical transition, recent focuses, and future prospects of the new realm, based on trends in the number of human research articles from the early stage of 2000 to the present of 2019 by searching the Medical Literature Analysis and Retrieval System Online (MEDLINE). Among them, objective dietary assessment, metabolic profiling, and health risk prediction were positioned as three of the principal applications. The continued growth will enable nutrimetabolomics research to contribute to personalized nutrition in the future.

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

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

A Scoping Review: Metabolomics Signatures Associated with Animal and Plant Protein Intake and Their Potential Relation with Cardiometabolic Risk

The dietary shift from animal protein (AP) to plant protein (PP) sources is encouraged for both environmental and health reasons. For instance, PPs are associated with lower cardiovascular and diabetes risks compared with APs, although the underlying mechanisms mostly remain unknown. Metabolomics is a valuable tool for globally and mechanistically characterizing the impact of AP and PP intake, given its unique ability to provide integrated signatures and specific biomarkers of metabolic effects through a comprehensive snapshot of metabolic status. This scoping review is aimed at gathering and analyzing the available metabolomics data associated with PP- and AP-rich diets, and discusses the metabolic effects underlying these metabolomics signatures and their potential implication for cardiometabolic health. We selected 24 human studies comparing the urine, plasma, or serum metabolomes associated with diets with contrasted AP and PP intakes. Among the 439 metabolites reported in those studies as able to discriminate AP- and PP-rich diets, 46 were considered to provide a robust level of evidence, according to a scoring system, especially amino acids (AAs) and AA-related products. Branched-chain amino acids, aromatic amino acids (AAAs), glutamate, short-chain acylcarnitines, and trimethylamine-N-oxide, which are known to be related to an increased cardiometabolic risk, were associated with AP-rich diets, whereas glycine (rather related to a reduced risk) was associated with PP-rich diets. Tricarboxylic acid (TCA) cycle intermediates and products from gut microbiota AAA degradation were also often reported, but the direction of their associations differed across studies. Overall, AP- and PP-rich diets result in different metabolomics signatures, with several metabolites being plausible candidates to explain some of their differential associations with cardiometabolic risk. Additional studies specifically focusing on protein type, with rigorous intake control, are needed to better characterize the associated metabolic phenotypes and understand how they could mediate differential AP and PP effects on cardiometabolic risk.

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.

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

BACKGROUND

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

OBJECTIVE

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

DESIGN

This was a randomized controlled crossover feeding trial.

PARTICIPANTS/SETTING

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

INTERVENTION

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

MAIN OUTCOME MEASURES

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

STATISTICAL ANALYSES PERFORMED

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

RESULTS

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

CONCLUSIONS

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

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.

Human urine 1H NMR metabolomics reveals alterations of protein and carbohydrate metabolism when comparing habitual Average Danish diet vs. healthy New Nordic diet

OBJECTIVES

The aim of this study was to investigate the alteration of the human urine metabolome by means of diet and to compare the metabolic effects of the nutritionally healthy New Nordic Diet (NND) with an Average Danish Diet (ADD). The NND was designed a decade ago by scientists and chefs, based on local and sustainable foods, including fish, shellfish, vegetables, roots, fruit, and berries. The NND has been proven to lower blood pressure, reduce glycemia, and lead to weight loss.

METHODS

The human urine metabolome was measured by untargeted proton nuclear magnetic resonance spectroscopy in samples from 142 centrally obese Danes (20-66 years old), randomized to consume the ADD or the NND. The resulting metabolomics data was processed and analyzed using advanced multivariate data analysis methods to reveal effects related to the design factors, including diet, season, sex, and changes in body weight.

RESULTS

Exploration of the nuclear magnetic resonance profiles revealed unique metabolite markers reflecting changes in protein and carbohydrate metabolism between the two diets. Glycine betaine, glucose, trimethylamine N-oxide and creatinine were increased in urine of the individuals following the NND compared with the ADD population, whereas relative concentrations of tartrate, dimethyl sulfone, and propylene glycol were decreased. Propylene glycol had a strong association with the homeostatic model assessment for insulin resistance in the NND group. The food intake biomarkers found in this study confirm the importance of these as tools for nutritional research.

CONCLUSIONS

Findings from this study provided new insights into the effects of a healthy diet on glycemia, reduction of inflammation, and weight loss among obese individuals, and alteration of the gut microbiota metabolism.

Urinary Metabolomic Profiling Analysis and Evaluation of the Effect of Ecklonia cava Extract Intake

Metabolomics is a powerful tool for the investigation of interactions between diet, nutrients, and human metabolism. Ecklonia cava is an edible brown alga that is abundantly found in Korea and Japan and contains unique polyphenols referred to as phlorotannins. However, there are few metabolomics studies related to the effects of polyphenols in humans. In this study, we performed a mass spectrometry-based metabolomics analysis of urine samples from participants with a body mass index (BMI) higher than 25 kg/m2 and lower than 30 kg/m2 to investigate the effects of the intake of seapolynol isolated from E. cava. Metabolomic profiling showed that the levels of riboflavin, urocanic acid, 5-hydroxy-6-methoxyindole glucuronide, and guanidino valeric acid were significantly increased in the seapolynol intake group compared with the placebo group. A correlation analysis was performed to identify the association between the metabolites' levels and clinical characteristics related to body fat. Among the metabolites whose concentrations changed in the seapolynol intake group, riboflavin was associated with BMI, body weight, fat mass, and percent body fat. These findings suggest that the decreased body fat induced by the intake of seapolynol is related to an increase in the antioxidant effect of riboflavin.

Plasma Metabolites as Predictors of Warfarin Outcome in Atrial Fibrillation

BACKGROUND

Warfarin is prescribed as an oral anticoagulant to treat/prevent thromboembolism in conditions such as atrial fibrillation. As there is a narrow therapeutic window, treatment with warfarin is challenging. Pharmacometabonomics using nuclear magnetic resonance (NMR) spectroscopy may provide novel techniques for the identification of novel biomarkers of warfarin.

PURPOSE

The aim was to determine the metabolic fingerprint that predicts warfarin response based on the international normalized ratio (INR) in patients who are already receiving warfarin (phase I: identification) and to ascertain the metabolic fingerprint that discriminates stable from unstable INR in patients starting treatment with warfarin (phase II: validation).

EXPERIMENTAL APPROACH

A total of 94 blood samples were collected for phase I: 44 patients with stable INR and 50 with unstable INR. Meanwhile, 23 samples were collected for phase II: nine patients with stable INR and 14 with unstable INR. Data analysis was performed using multivariate analysis including principal component analysis and partial least square-discriminate analysis (PLS-DA), followed by univariate and multivariate logistic regression (MVLR) to develop a model to identify unstable INR biomarkers.

KEY RESULTS

For phase I, the PLS-DA model showed the following results: sensitivity 93.18%, specificity 91.49% and accuracy 92.31%. In the MVLR analysis of phase I, ten regions were associated with unstable INR. For phase II, the PLS-DA model showed the following results: sensitivity 66.67%, specificity 61.54% and accuracy 63.64%.

CONCLUSIONS AND IMPLICATIONS

We have shown that the pharmacometabonomics technique was able to differentiate between unstable and stable INR with good accuracy. NMR-based pharmacometabonomics has the potential to identify novel biomarkers in plasma, which can be useful in individualizing treatment and controlling warfarin side effects, thus, minimizing undesirable effects in the future.

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

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

Total Water-Soluble Choline Concentration Does Not Differ in Milk from Vegan, Vegetarian, and Nonvegetarian Lactating Women

BACKGROUND

Choline is an essential nutrient for brain growth and other processes in the developing neonate. The impact of a maternal plant-based diet on the choline composition of breast milk is unknown.

OBJECTIVE

We assessed the water-soluble choline content of milk from lactating women in the United States following 3 dietary patterns: vegan, vegetarian, and nonvegetarian.

METHODS

We conducted a cross-sectional study of 74 healthy lactating women who provided a single breast-milk sample using a standardized collection protocol. Participants completed a food-frequency screener and were classified as follows: nonvegetarians (NONVEG) consumed meat; vegetarians (VEGT) consumed milk, dairy, and/or fish; and vegans (VEGAN) consumed animal products less than monthly. Primary outcomes measured were the concentration (in milligrams per liter) and distribution (percentage) of choline from the following water-soluble forms: free choline, phosphocholine (PCho), and glycerophosphocholine (GPC). Differences between diet groups were evaluated with ANOVA.

RESULTS

There was a wide range in breast-milk total water-soluble choline (4-301 mg/L), with no significant difference (P > 0.05) by maternal diet pattern. There were differences in choline forms, with VEGAN having a greater mean ± SD concentration and distribution of choline derived from GPC (62.7 ± 25.3 mg/L) than VEGT (47.7 ± 21.2 mg/L) and NONVEG (42.4 ± 14.9 mg/L) (P = 0.0052). There was a lower mean ± SD percentage of choline from PCho (P = 0.0106) in VEGAN (32.5% ± 18.3%) than in VEGT (46.1% ± 18.3%) and NONVEG (44.8% ± 15.7%). Lactation stage and maternal BMI were significantly associated with some choline forms.

CONCLUSIONS

There was a wide range of water-soluble choline concentrations in the milk of healthy lactating women following vegan, vegetarian, and nonvegetarian diets, with no observed difference in total water-soluble choline concentration by maternal diet. This suggests that maternal plant-based diet by itself is not a risk factor for low breast-milk choline.

The effect of sampling procedures and day-to-day variations in metabolomics studies of biofluids

Metabolomics analysis of biofluids is a feasible tool for disease characterization and monitoring due to its minimally invasive nature. To reduce unwanted variation in biobanks and clinical studies, it is important to determine the effect of external factors on metabolic profiles of biofluids. In this study we examined the effect of sample collection and sample processing procedures on NMR measured serum lipoproteins and small-molecule metabolites in serum and urine, using a cohort of men diagnosed with either prostate cancer or benign prostatic hyperplasia. We determined day-to-day reliability of metabolites by systematic sample collection at two different days, in both fasting and non-fasting conditions. Study participants received prostate massage the first day to assess the differences between urine with and without prostate secretions. Further, metabolic differences between first-void and mid-stream urine samples, and the effect of centrifugation of urine samples before storage were assessed. Our results show that day-to-day reliability is highly variable between metabolites in both serum and urine, while lipoprotein subfractions possess high reliability. Further, fasting status clearly influenced the metabolite concentrations, demonstrating the importance of keeping this condition constant within a study cohort. Day-to-day reliabilities were however comparable in fasting and non-fasting samples. Urine sampling procedures such as sampling of first-void or mid-stream urine, and centrifugation or not before sample storage, were shown to only have minimal effect on the overall metabolic profile, and is thus unlikely to constitute a confounder in clinical studies utilizing NMR derived metabolomics.