Syringol metabolites as new biomarkers for smoked meat intake

Dietary biomarkers-an update on their validity and applicability in epidemiological studies

The aim of this literature review was to identify and provide a summary update on the validity and applicability of the most promising dietary biomarkers reflecting the intake of important foods in the Western diet for application in epidemiological studies. Many dietary biomarker candidates, reflecting intake of common foods and their specific constituents, have been discovered from intervention and observational studies in humans, but few have been validated. The literature search was targeted for biomarker candidates previously reported to reflect intakes of specific food groups or components that are of major importance in health and disease. Their validity was evaluated according to 8 predefined validation criteria and adapted to epidemiological studies; we summarized the findings and listed the most promising food intake biomarkers based on the evaluation. Biomarker candidates for alcohol, cereals, coffee, dairy, fats and oils, fruits, legumes, meat, seafood, sugar, tea, and vegetables were identified. Top candidates for all categories are specific to certain foods, have defined parent compounds, and their concentrations are unaffected by nonfood determinants. The correlations of candidate dietary biomarkers with habitual food intake were moderate to strong and their reproducibility over time ranged from low to high. For many biomarker candidates, critical information regarding dose response, correlation with habitual food intake, and reproducibility over time is yet unknown. The nutritional epidemiology field will benefit from the development of novel methods to combine single biomarkers to generate biomarker panels in combination with self-reported data. The most promising dietary biomarker candidates that reflect commonly consumed foods and food components for application in epidemiological studies were identified, and research required for their full validation was summarized.

Knowledge translation and knowledge mobilization from the FoodBAll project

This report describes the knowledge mobilization and translation outcomes of the Canadian-funded portion of a large, international project called the Food Biomarker Alliance (FoodBAll), which ran from 2015 to 2019. This remarkably successful project led to a large number of important findings, outputs, and impacts. In particular, FoodBAll unequivocally demonstrated that metabolomics could be used to not only discover biomarkers of food intake (BFIs), but also to measure diet in a more objective manner. FoodBAll also created standards for assessing and validating BFIs, papers and databases describing BFIs, and kits for measuring BFIs and it laid the groundwork for many global studies exploring food composition and precision nutrition.

Fasting plasma metabolites reflecting meat consumption and their associations with incident type 2 diabetes in two Swedish cohorts

BACKGROUND

Consumption of processed red meat has been associated with increased risk of developing type 2 diabetes (T2D), but challenges in dietary assessment call for objective intake biomarkers.

OBJECTIVES

This study aimed to investigate metabolite biomarkers of meat intake and their associations with T2D risk.

METHODS

Fasting plasma samples were collected from a case-control study nested within Västerbotten Intervention Program (VIP) (214 females and 189 males) who developed T2D after a median follow-up of 7 years. Panels of biomarker candidates reflecting the consumption of total, processed, and unprocessed red meat and poultry were selected from the untargeted metabolomics data collected on the controls. Observed associations were then replicated in Swedish Mammography clinical subcohort in Uppsala (SMCC) (n = 4457 females). Replicated metabolites were assessed for potential association with T2D risk using multivariable conditional logistic regression in the discovery and Cox regression in the replication cohorts.

RESULTS

In total, 15 metabolites were associated with ≥1 meat group in both cohorts. Acylcarnitines 8:1, 8:2, 10:3, reflecting higher processed meat intake [r > 0.22, false discovery rate (FDR) < 0.001 for VIP and r > 0.05; FDR < 0.001 for SMCC) were consistently associated with higher T2D risk in both data sets. Conversely, lysophosphatidylcholine 17:1 and phosphatidylcholine (PC) 15:0/18:2 were associated with lower processed meat intake (r < -0.12; FDR < 0.023, for VIP and r < -0.05; FDR < 0.001, for SMCC) and with lower T2D risk in both data sets, except for PC 15:0/18:2, which was significant only in the VIP cohort. All associations were attenuated after adjustment for BMI (kg/m2).

CONCLUSIONS

Consistent associations of biomarker candidates involved in lipid metabolism between higher processed red meat intake with higher T2D risk and between those reflecting lower intake with the lower risk may suggest a relationship between processed meat intake and higher T2D risk. However, attenuated associations after adjusting for BMI indicates that such a relationship may at least partly be mediated or confounded by BMI.

A prospective case-cohort analysis of plasma metabolites and breast cancer risk

BACKGROUND

Breast cancer incidence rates have not declined despite an improvement in risk prediction and the identification of modifiable risk factors, suggesting the need to identify novel risk factors and etiological pathways involved in this cancer. Metabolomics has emerged as a promising tool to find circulating metabolites associated with breast cancer risk.

METHODS

Untargeted metabolomic analysis was done on prediagnostic plasma samples from a case-cohort study of 1695 incident breast cancer cases and a 1983 women subcohort drawn from Cancer Prevention Study 3. The associations of 868 named metabolites (per one standard deviation increase) with breast cancer were determined using Prentice-weighted Cox proportional hazards regression modeling.

RESULTS

A total of 11 metabolites were associated with breast cancer at false discovery rate (FDR) < 0.05 with the majority having inverse association [ranging from RR = 0.85 (95% CI 0.80-0.92) to RR = 0.88 (95% CI 0.82-0.94)] and one having a positive association [RR = 1.14 (95% CI 1.06-1.23)]. An additional 50 metabolites were associated at FDR < 0.20 with inverse associations ranging from RR = 0.88 (95% CI 0.81-0.94) to RR = 0.91 (95% CI 0.85-0.98) and positive associations ranging from RR = 1.13 (95% CI 1.05-1.22) to RR = 1.11 (95% CI 1.02-1.20). Several of these associations validated the findings of previous metabolomic studies. These included findings that several progestogen and androgen steroids were associated with increased risk of breast cancer in postmenopausal women and four phospholipids, and the amino acids glutamine and asparagine were associated with decreased risk of this cancer in pre- and postmenopausal women. Several novel associations were also identified, including a positive association for syringol sulfate, a biomarker for smoked meat, and 3-methylcatechol sulfate and 3-hydroxypyridine glucuronide, which are metabolites of xenobiotics used for the production of pesticides and other products.

CONCLUSIONS

Our study validated previous metabolite findings and identified novel metabolites associated with breast cancer risk, demonstrating the utility of large metabolomic studies to provide new leads for understanding breast cancer etiology. Our novel findings suggest that consumption of smoked meats and exposure to catechol and pyridine should be investigated as potential risk factors for breast cancer.

Characterization of the degree of food processing in the European Prospective Investigation into Cancer and Nutrition: Application of the Nova classification and validation using selected biomarkers of food processing

Background

Epidemiological studies have demonstrated an association between the degree of food processing in our diet and the risk of various chronic diseases. Much of this evidence is based on the international Nova classification system, which classifies food into four groups based on the type of processing: (1) Unprocessed and minimally processed foods, (2) Processed culinary ingredients, (3) Processed foods, and (4) "Ultra-processed" foods (UPF). The ability of the Nova classification to accurately characterise the degree of food processing across consumption patterns in various European populations has not been investigated so far. Therefore, we applied the Nova coding to data from the European Prospective Investigation into Cancer and Nutrition (EPIC) in order to characterize the degree of food processing in our diet across European populations with diverse cultural and socio-economic backgrounds and to validate this Nova classification through comparison with objective biomarker measurements.

Methods

After grouping foods in the EPIC dataset according to the Nova classification, a total of 476,768 participants in the EPIC cohort (71.5% women; mean age 51 [standard deviation (SD) 9.93]; median age 52 [percentile (p)25-p75: 58-66] years) were included in the cross-sectional analysis that characterised consumption patterns based on the Nova classification. The consumption of food products classified as different Nova categories were compared to relevant circulating biomarkers denoting food processing, measured in various subsamples (N between 417 and 9,460) within the EPIC cohort via (partial) correlation analyses (unadjusted and adjusted by sex, age, BMI and country). These biomarkers included an industrial transfatty acid (ITFA) isomer (elaidic acid; exogenous fatty acid generated during oil hydrogenation and heating) and urinary 4-methyl syringol sulfate (an indicator for the consumption of smoked food and a component of liquid smoke used in UPF).

Results

Contributions of UPF intake to the overall diet in % grams/day varied across countries from 7% (France) to 23% (Norway) and their contributions to overall % energy intake from 16% (Spain and Italy) to >45% (in the UK and Norway). Differences were also found between sociodemographic groups; participants in the highest fourth of UPF consumption tended to be younger, taller, less educated, current smokers, more physically active, have a higher reported intake of energy and lower reported intake of alcohol. The UPF pattern as defined based on the Nova classification (group 4;% kcal/day) was positively associated with blood levels of industrial elaidic acid (r = 0.54) and 4-methyl syringol sulfate (r = 0.43). Associations for the other 3 Nova groups with these food processing biomarkers were either inverse or non-significant (e.g., for unprocessed and minimally processed foods these correlations were -0.07 and -0.37 for elaidic acid and 4-methyl syringol sulfate, respectively).

Conclusion

These results, based on a large pan-European cohort, demonstrate sociodemographic and geographical differences in the consumption of UPF. Furthermore, these results suggest that the Nova classification can accurately capture consumption of UPF, reflected by stronger correlations with circulating levels of industrial elaidic acid and a syringol metabolite compared to diets high in minimally processed foods.

Development and validation of a metabolite score for red meat intake: an observational cohort study and randomized controlled dietary intervention

BACKGROUND

Self-reported meat consumption is associated with disease risk but objective assessment of different dimensions of this heterogeneous dietary exposure in observational and interventional studies remains challenging.

OBJECTIVES

We aimed to derive and validate scores based on plasma metabolites for types of meat consumption. For the most predictive score, we aimed to test whether the included metabolites varied with change in meat consumption, and whether the score was associated with incidence of type 2 diabetes (T2D) and other noncommunicable diseases.

METHODS

We derived scores based on 781 plasma metabolites for red meat, processed meat, and poultry consumption assessed with 7-d food records among 11,432 participants in the EPIC-Norfolk (European Prospective Investigation into Cancer and Nutrition-Norfolk) cohort. The scores were then tested for internal validity in an independent subset (n = 853) of the same cohort. In focused analysis on the red meat metabolite score, we examined whether the metabolites constituting the score were also associated with meat intake in a randomized crossover dietary intervention trial of meat (n = 12, Lyon, France). In the EPIC-Norfolk study, we assessed the association of the red meat metabolite score with T2D incidence (n = 1478) and other health endpoints.

RESULTS

The best-performing score was for red meat, comprising 139 metabolites which accounted for 17% of the explained variance of red meat consumption in the validation set. In the intervention, 11 top-ranked metabolites in the red meat metabolite score increased significantly after red meat consumption. In the EPIC-Norfolk study, the red meat metabolite score was associated with T2D incidence (adjusted HR per SD: 1.17; 95% CI: 1.10, 1.24).

CONCLUSIONS

The red meat metabolite score derived and validated in this study contains metabolites directly derived from meat consumption and is associated with T2D risk. These findings suggest the potential for objective assessment of dietary components and their application for understanding diet-disease associations.The trial in Lyon, France, was registered at clinicaltrials.gov as NCT03354130.

Consumption of Boiled, but Not Grilled, Roasted, or Barbecued Beef Modifies the Urinary Metabolite Profiles in Rats

SCOPE

The consumption of processed meat is associated with increased risk of chronic diseases, but determining how the exposure to specific cooking processes alters the metabolome is an analytical challenge. This study aims to evaluate the impact of four typical cooking methods for beef (boiling, barbecuing, grilling, and roasting) on the urinary metabolite profiles in rats, using a non-targeted approach.

METHODS AND RESULTS

Male Wistar rats (n  =  48) are fed for 3 weeks with experimental diets containing either raw or cooked (boiled, barbecued, grilled, and roasted) beef. A control group is fed with milk proteins. The 24 h-urines are analyzed using LC-MS. The consumption of boiled meat leads to the specific excretion of di- and tri-peptides (aspartyl-leucine, glycyl-aspartate, and aspartyl-prolyl-threonine) and a cyclo-prolyl-proline (p < 0.001). No singular metabolite specifically associated with the groups "grilled," "roasted," and "barbecued" meat is observed.

CONCLUSION

Urinary metabolite profiles of rats fed boiled beef are clearly distinct from those of rats fed with raw, grilled, roasted, or barbecued beef. The specific metabolites include the products of non-digested proteins and may be useful as potential intake biomarkers of this meat cooking method.

Association of Red Meat Consumption, Metabolic Markers, and Risk of Cardiovascular Diseases

Objective

The metabolic mechanism of harmful effects of red meat on the cardiovascular system is still unclear. The objective of the present study is to investigate the associations of self-reported red meat consumption with plasma metabolic markers, and of these markers with the risk of cardiovascular diseases (CVD).

Methods

Plasma samples of 4,778 participants (3,401 CVD cases and 1,377 controls) aged 30-79 selected from a nested case-control study based on the China Kadoorie Biobank were analyzed by using targeted nuclear magnetic resonance to quantify 225 metabolites or derived traits. Linear regression was conducted to evaluate the effects of self-reported red meat consumption on metabolic markers, which were further compared with the effects of these markers on CVD risk assessed by logistic regression.

Results

Out of 225 metabolites, 46 were associated with red meat consumption. Positive associations were observed for intermediate-density lipoprotein (IDL), small high-density lipoprotein (HDL), and all sizes of low-density lipoprotein (LDL). Cholesterols, phospholipids, and apolipoproteins within various lipoproteins, as well as fatty acids, total choline, and total phosphoglycerides, were also positively associated with red meat consumption. Meanwhile, 29 out of 46 markers were associated with CVD risk. In general, the associations of metabolic markers with red meat consumption and of metabolic markers with CVD risk showed consistent direction.

Conclusions

In the Chinese population, red meat consumption is associated with several metabolic markers, which may partially explain the harmful effect of red meat consumption on CVD.

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.

Pepper Alkaloids and Processed Meat Intake: Results from a Randomized Trial and the European Prospective Investigation into Cancer and Nutrition (EPIC) Cohort

SCOPE

Processed meat intake has been associated with adverse health outcomes. However, little is known about the type of processed meat more particularly responsible for these effects. This study aims to identify novel biomarkers for processed meat intake.

METHODS AND RESULTS

In a controlled randomized cross-over dietary intervention study, 12 healthy volunteers consume different processed and non-processed meats for 3 consecutive days each. Metabolomics analyses are applied on post-intervention fasting blood and urine samples to identify discriminating molecular features of processed meat intake. Nine and five pepper alkaloid metabolites, including piperine, are identified as major discriminants of salami intake in urine and plasma, respectively. The associations with processed meat intake are tested for replication in a cross-sectional study (n = 418) embedded within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Three of the serum metabolites including piperine are associated with habitual intake of sausages and to a lesser extent of total processed meat.

CONCLUSION

Pepper alkaloids are major discriminants of intake for sausages that contain high levels of pepper used as ingredient. Further work is needed to assess if pepper alkaloids in combination with other metabolites may serve as biomarkers of processed meat intake.

Design and Characterisation of a Randomized Food Intervention That Mimics Exposure to a Typical UK Diet to Provide Urine Samples for Identification and Validation of Metabolite Biomarkers of Food Intake

Poor dietary choices are major risk factors for obesity and non-communicable diseases, which places an increasing burden on healthcare systems worldwide. To monitor the effectiveness of healthy eating guidelines and strategies, there is a need for objective measures of dietary intake in community settings. Metabolites derived from specific foods present in urine samples can provide objective biomarkers of food intake (BFIs). Whilst the majority of biomarker discovery/validation studies have investigated potential biomarkers for single foods only, this study considered the whole diet by using menus that delivered a wide range of foods in meals that emulated conventional UK eating patterns. Fifty-one healthy participants (range 19-77 years; 57% female) followed a uniquely designed, randomized controlled dietary intervention, and provided spot urine samples suitable for discovery of BFIs within a real-world context. Free-living participants prepared and consumed all foods and drinks in their own homes and were asked to follow the protocols for meal consumption and home urine sample collection. This study also assessed the robustness, and impact on data quality, of a minimally invasive urine collection protocol. Overall the study design was well-accepted by participants and concluded successfully without any drop outs. Compliance for urine collection, adherence to menu plans, and observance of recommended meal timings, was shown to be very high. Metabolome analysis using mass spectrometry coupled with data mining demonstrated that the study protocol was well-suited for BFI discovery and validation. Novel, putative biomarkers for an extended range of foods were identified including legumes, curry, strongly-heated products, and artificially sweetened, low calorie beverages. In conclusion, aspects of this study design would help to overcome several current challenges in the development of BFI technology. One specific attribute was the examination of BFI generalizability across related food groups and across different preparations and cooking methods of foods. Furthermore, the collection of urine samples at multiple time points helped to determine which spot sample was optimal for identification and validation of BFIs in free-living individuals. A further valuable design feature centered on the comprehensiveness of the menu design which allowed the testing of biomarker specificity within a biobank of urine samples.

25-Hydroxyvitamin D status, vitamin D intake, and skin cancer risk: a systematic review and dose-response meta-analysis of prospective studies

Sun exposure is a major environmental risk factor for skin cancers and is also an important source of vitamin D. However, while experimental evidence suggests that vitamin D may have a protective effect on skin cancer risk, epidemiologic studies investigating the influence of 25-hydroxyvitamin D (25(OH)D) level and/or vitamin D intake on skin cancer risk are conflicting. A systematic review and dose–response meta-analyses of prospective studies was conducted to clarify these associations. Relevant studies were identified by searching the PubMed database up to 30th August 2019. Random effects dose–response meta-analyses were used to estimate summary relative risks (SRRs) and 95% confidence intervals (CIs). Overall, thirteen prospective studies were included. Circulating level of 25(OH)D was associated with higher risks of melanoma (SRR (95% CI) per 30 nmol = 1.42 (1.17–1.72)) and keratinocyte cancer (KC) (SRR (95% CI) per 30 nmol/L = 1.30 (1.13–1.49)). The SRR (95% CI) per 30 nmol/L increase in 25(OH) D level was 1.41 (1.19–1.67), and 1.57 (0.64–3.86), for basal cell carcinomas (BCCs) and squamous cell carcinomas (SCCs), respectively. However, while we found that vitamin D intake (from diet, supplemental and total) was not associated with risks of melanoma and SCC, vitamin D intake was associated with slightly increased BCC risk, albeit with no heterogeneity across skin cancer type. This meta-analysis suggests positive associations between circulating 25(OH)D level and risk of melanoma and KC, however, this finding is most likely confounded by sun exposure. We found no associations between vitamin D intake skin cancers, except positive associations with BCC risk.

A metabolomic study of red and processed meat intake and acylcarnitine concentrations in human urine and blood

BACKGROUND

Acylcarnitines (ACs) play a major role in fatty acid metabolism and are potential markers of metabolic dysfunction with higher blood concentrations reported in obese and diabetic individuals. Diet, and in particular red and processed meat intake, has been shown to influence AC concentrations but data on the effect of meat consumption on AC concentrations is limited.

OBJECTIVES

To investigate the effect of red and processed meat intake on AC concentrations in plasma and urine using a randomized controlled trial with replication in an observational cohort.

METHODS

In the randomized crossover trial, 12 volunteers successively consumed 2 different diets containing either pork or tofu for 3 d each. A panel of 44 ACs including several oxidized ACs was analyzed by LC-MS in plasma and urine samples collected after the 3-d period. ACs that were associated with pork intake were then measured in urine (n = 474) and serum samples (n = 451) from the European Prospective Investigation into Cancer and nutrition (EPIC) study and tested for associations with habitual red and processed meat intake derived from dietary questionnaires.

RESULTS

In urine samples from the intervention study, pork intake was positively associated with concentrations of 18 short- and medium-chain ACs. Eleven of these were also positively associated with habitual red and processed meat intake in the EPIC cross-sectional study. In blood, C18:0 was positively associated with red meat intake in both the intervention study (q = 0.004, Student's t-test) and the cross-sectional study (q = 0.033, linear regression).

CONCLUSIONS

AC concentrations in urine and blood were associated with red meat intake in both a highly controlled intervention study and in subjects of a cross-sectional study. Our data on the role of meat intake on this important pathway of fatty acid and energy metabolism may help understanding the role of red meat consumption in the etiology of some chronic diseases. This trial was registered at Clinicaltrials.gov as NCT03354130.

Metabolic Signatures of 10 Processed and Non-processed Meat Products after In Vitro Digestion

The intake of processed meat has been associated with several adverse health outcomes such as type II diabetes and cancer; however, the mechanisms are not fully understood. A better knowledge of the metabolite profiles of different processed and non-processed meat products from this heterogeneous food group could help in elucidating the mechanisms associated with these health effects. Thirty-three different commercial samples of ten processed and non-processed meat products were digested in triplicate with a standardized static in vitro digestion method in order to mimic profiles of small molecules formed in the gut upon digestion. A metabolomics approach based on high-resolution mass spectrometry was used to identify metabolite profiles specific to the various meat products. Processed meat products showed metabolite profiles clearly distinct from those of non-processed meat. Several discriminant features related to either specific ingredients or processing methods were identified. Those were, in particular, syringol compounds deposited in meat during smoking, biogenic amines formed during meat fermentation and piperine and related compounds characteristic of pepper used as an ingredient. These metabolites, characteristic of specific processed meat products, might be used as potential biomarkers of intake for these foods. They may also help in understanding the mechanisms linking processed meat intake and adverse health outcomes such as cancer.