Developing a Food Exposure and Urine Sampling Strategy for Dietary Exposure Biomarker Validation in Free-Living Individuals

Nutritional Assessment of Hospital Meals by Food-Recording Applications

Mobile food records are currently used to determine the nutrition of healthy subjects. To determine the accuracy of such records, we evaluated the nutritional composition of a test meal (noodles and fruit juice) and a hospital meal (Japanese set meal) using two types of mobile food records. Eighteen healthy subjects (2 males and 16 females) were enrolled. Using these diets and validated nutrient-composition information, we evaluated the accuracy of the dietary assessments made by two dietary-record applications, Asken^® and Calomeal^®, over 5 days. For the test meal, the values provided by the two applications were close to the actual values. In contrast, for the hospital meal, the values provided by the two applications were approximately 1.5 times higher than the actual values. A linear-mixed-model analysis showed that the total energy, carbohydrate, and salt contents were significantly overestimated in the hospital meal. Protein also tended to be overestimated, while the fat content was not significantly overestimated. Furthermore, the total energy and fat contents increased significantly over time. No association with age was observed. A comparison of the coefficients of variation (CVs) for each nutrient in the hospital meal indicated that the fat levels were significantly higher than those in the test meal. In conclusion, the accuracy of mobile food records depends on the type of meal. Our data will provide lessons for the use of meal-recording applications in special cases, such as hospital food.

Healthy for My Baby Research Protocol- a Randomized Controlled Trial Assessing a Preconception Intervention to Improve the Lifestyle of Overweight Women and Their Partners

Background: Preconception lifestyle interventions appear promising to reduce pregnancy complications, prevent adult cardiometabolic diseases, and prevent childhood obesity. These interventions have almost exclusively been studied in populations of obese infertile women. The development of preconception lifestyle interventions targeting a broader population of overweight and obese women without a history infertility and their partners is needed.

Methods: This study is a multicenter open label parallel group randomized controlled trial. Sixty-eight non-infertile women with overweight or obesity in the preconception period and their partners will be recruited from the Sherbrooke and Quebec City regions. The couples will be randomized in a 1:1 ratio to receive the Healthy for my Baby intervention or standard care in the preconception period and pregnancy. Women and their partners will be invited to take part in this lifestyle intervention which includes motivational interviews and daily self-monitoring of lifestyle goals through a mobile phone application. The primary endpoint of this study is the diet quality of women during the preconception period, which will be evaluated using the C-HEI 2007 score at baseline, 2, 4- and 6-months following study enrolment. Women's dietary quality will also be evaluated through the measure of urinary biomarkers of habitual dietary intake at baseline and 2 months in preconception, and 24–26 weeks in pregnancy. Additional indicators of women's lifestyle as well as anthropometric measures will be documented in preconception and pregnancy. For the pregnancy period, the main secondary endpoint is the pattern of gestational weight gain. Pregnancy and neonatal complications will also be evaluated. For partners, diet quality, other lifestyle habits, and anthropometric measures will be documented in the preconception and pregnancy periods.

Discussion: This study will evaluate the effectiveness of a low-cost intervention designed to improve diet and other lifestyle characteristics of women in the preconception period who are overweight or obese. If the Healthy for my Baby intervention is efficacious regarding dietary measures, larger trials will be needed to evaluate the impact of this intervention on the rates of pregnancy complications, childhood obesity, and adult cardiometabolic disease.

Clinical Trial Registration:clinicaltrials.gov (NCT04242069).

Association of Postoperative Clinical Outcomes With Sarcopenia, Frailty, and Nutritional Status in Older Patients With Colorectal Cancer: Protocol for a Prospective Cohort Study

Background

Older patients account for a significant proportion of patients undergoing colorectal cancer surgery and are vulnerable to a number of preoperative risk factors that are not often present in younger patients. Further, three preoperative risk factors that are more prevalent in older adults include frailty, sarcopenia, and malnutrition. Although each of these has been studied in isolation, there is little information on the interplay between them in older surgical patients. A particular area of increasing interest is the use of urine metabolomics for the objective evaluation of dietary profiles and malnutrition.

Objective

Herein, we describe the design, cohort, and standard operating procedures of a planned prospective study of older surgical patients undergoing colorectal cancer resection across multiple institutions in the United Kingdom. The objectives are to determine the association between clinical outcomes and frailty, nutritional status, and sarcopenia.

Methods

The procedures will include serial frailty evaluations (Clinical Frailty Scale and Groningen Frailty Indicator), functional assessments (hand grip strength and 4-meter walk test), muscle mass evaluations via computerized tomography morphometric analysis, and the evaluation of nutritional status via the analysis of urinary dietary biomarkers. The primary feasibility outcome is the estimation of the incidence rate of postoperative complications, and the primary clinical outcome is the association between the presence of postoperative complications and frailty, sarcopenia, and nutritional status. The secondary outcome measures are the length of hospital stay, 30-day hospital readmission rate, and mortality rate at days 30 and 90.

Results

Our study was approved by the National Health Service Research Ethics Committee (reference number: 19/WA/0190) via the Integrated Research Application System (project ID: 231694) prior to subject recruitment. Cardiff University is acting as the study sponsor. Our study is financially supported through an external, peer-reviewed grant from the British Geriatrics Society and internal funding resources from Cardiff University. The results will be disseminated through peer-review publications, social media, and conference proceedings.

Conclusions

As frailty, sarcopenia, and malnutrition are all areas of common derangement in the older surgical population, prospectively studying these risk factors in concert will allow for the analysis of their interplay as well as the development of predictive models for those at risk of commonly tracked surgical complications and outcomes.

International Registered Report Identifier (IRRID)

PRR1-10.2196/16846

UK Nutrition Research Partnership (NRP) workshop: Forum on advancing dietary intake assessment

The development of better and more robust measures of dietary intake in free living situations was identified as a priority for advancing nutrition research by the Office of Strategic Coordination for Health Research (OSCHR) Review of Nutrition and Human Health Research in 2017. The UK Nutrition Research Partnership (NRP) sponsored a workshop on Dietary Intake Assessment methodology alongside its series of ‘Hot Topic’ workshops designed to accelerate progress in nutrition research by bringing together people from a range of different disciplines. The workshop on Dietary Intake Assessment methodology took place via Zoom over two half‐days in January 2021 and included 50 scientists from a wide range of disciplines. The problems with current methods of dietary assessment and how emerging technologies might address them were set out in pre‐recorded presentations and explored in panel discussions. Participants then worked in breakout groups to discuss and prioritise the research questions that should be addressed to best further the field and lead to improvements in dietary assessment methodology. Five priority research questions were selected. Participants were asked to brainstorm potential approaches for addressing them and were then asked to focus on one approach and develop it further. At the end of these sessions, participants presented their project ideas to the rest of the workshop and these will be reported back to the Medical Research Council. It is hoped that potential collaborative projects arising from these discussions will be taken forward in response to future funding calls.

Derivation and Validation of a Total Fruit and Vegetable Intake Prediction Model to Identify Targets for Biomarker Discovery Using the UK National Diet and Nutrition Survey

BACKGROUND

Dietary assessments in research and clinical settings are largely reliant on self-reported questionnaires. It is acknowledged that these are subject to measurement error and biases and that objective approaches would be beneficial. Dietary biomarkers have been purported as a complementary approach to improve the accuracy of dietary assessments. Tentative biomarkers have been identified for many individual fruits and vegetables (FVs), but an objective total FV intake assessment tool has not been established.

OBJECTIVES

To derive and validate a prediction model of total FV intake (TFVpred) to inform future biomarker studies.

METHODS

Data from the National Diet and Nutrition Survey (NDNS) were used for this analysis. A modeling group (MG) consisting of participants aged >11 years from the NDNS years 5-6 was created (n = 1746). Intake data for 96 FVs were analyzed by stepwise regression to derive a model that satisfied 3 selection criteria: SEE ≤80, R2 >0.7, and ≤10 predictors. The TFVpred model was validated using comparative data from a validation group (VG) created from the NDNS years 7-8 (n = 1865). Pearson's correlation coefficients were assessed between observed and predicted values in the MG and VG. Bland-Altman plots were used to assess agreement between TFVpred estimates and total FV intake.

RESULTS

A TFVpred model, comprised of tomatoes, apples, carrots, bananas, pears, strawberries, and onions, satisfied the selection criteria (R2 = 0.761; SEE = 78.81). Observed and predicted total FV intake values were positively correlated in the MG (r = 0.872; P < 0.001; R2 = 0.761) and the VG (r = 0.838; P < 0.001; R2 = 0.702). In the MG and VG, 95.0% and 94.9%, respectively, of TFVpred model residuals were within the limits of agreement.

CONCLUSIONS

Intakes of a concise FV list can be used to predict total FV intakes in a UK population. The individual FVs included in the TFVpred model present targets for biomarker discovery aimed at objectively assessing total FV intake.

Challenges Associated With the Design and Deployment of Food Intake Urine Biomarker Technology for Assessment of Habitual Diet in Free-Living Individuals and Populations-A Perspective

Improvement of diet at the population level is a cornerstone of national and international strategies for reducing chronic disease burden. A critical challenge in generating robust data on habitual dietary intake is accurate exposure assessment. Self-reporting instruments (e.g., food frequency questionnaires, dietary recall) are subject to reporting bias and serving size perceptions, while weighed dietary assessments are unfeasible in large-scale studies. However, secondary metabolites derived from individual foods/food groups and present in urine provide an opportunity to develop potential biomarkers of food intake (BFIs). Habitual dietary intake assessment in population surveys using biomarkers presents several challenges, including the need to develop affordable biofluid collection methods, acceptable to participants that allow collection of informative samples. Monitoring diet comprehensively using biomarkers requires analytical methods to quantify the structurally diverse mixture of target biomarkers, at a range of concentrations within urine. The present article provides a perspective on the challenges associated with the development of urine biomarker technology for monitoring diet exposure in free-living individuals with a view to its future deployment in "real world" situations. An observational study (n = 95), as part of a national survey on eating habits, provided an opportunity to explore biomarker measurement in a free-living population. In a second food intervention study (n = 15), individuals consumed a wide range of foods as a series of menus designed specifically to achieve exposure reflecting a diversity of foods commonly consumed in the UK, emulating normal eating patterns. First Morning Void urines were shown to be suitable samples for biomarker measurement. Triple quadrupole mass spectrometry, coupled with liquid chromatography, was used to assess simultaneously the behavior of a panel of 54 potential BFIs. This panel of chemically diverse biomarkers, reporting intake of a wide range of commonly-consumed foods, can be extended successfully as new biomarker leads are discovered. Towards validation, we demonstrate excellent discrimination of eating patterns and quantitative relationships between biomarker concentrations in urine and the intake of several foods. In conclusion, we believe that the integration of information from BFI technology and dietary self-reporting tools will expedite research on the complex interactions between dietary choices and health.

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.

Calystegines are Potential Urine Biomarkers for Dietary Exposure to Potato Products

SCOPE

Metabolites derived from specific foods present in urine samples can provide objective biomarkers of food intake (BFIs). This study investigated the possibility that calystegines (a class of iminosugars) may provide BIFs for potato (Solanum tuberosum L.) product exposure.

METHODS AND RESULTS

Calystegine content is examined in published data covering a wide range of potato cultivars. Rapid methods are developed for the quantification of calystegines in cooked potato products and human urine using triple quadrupole mass spectrometry. The potential of calystegines as BFIs for potato consumption is assessed in a controlled food intervention study in the United Kingdom and validated in an epidemiological study in Portugal. Calystegine concentrations are reproducibly above the quantification limit in first morning void urines the day after potato consumption, showing a good dose-response relationship, particularly for calystegine A₃ . The design of the controlled intervention mimicks exposure to a typical UK diet and showed that neither differences in preparation/cooking method or influence of other foods in the diet has significant impact on biomarker performance. Calystegine biomarkers also perform well in the independent validation study.

CONCLUSION

It is concluded that calystegines have many of the characteristics needed to be considered as specific BFIs for potato product intake.

A Standardized Strategy for Simultaneous Quantification of Urine Metabolites to Validate Development of a Biomarker Panel Allowing Comprehensive Assessment of Dietary Exposure

SCOPE

Metabolites derived from individual foods found in human biofluids after consumption could provide objective measures of dietary intake. For comprehensive dietary assessment, quantification methods would need to manage the structurally diverse mixture of target metabolites present at wide concentration ranges.

METHODS AND RESULTS

A strategy for selection of candidate dietary exposure biomarkers is developed. An analytical method for 62 food biomarkers is validated by extensive analysis of chromatographic and ionization behavior characteristics using triple quadrupole mass spectrometry. Urine samples from two food intervention studies are used: a controlled, inpatient study (n = 19) and a free-living study where individuals (n = 15) are provided with food as a series of menu plans. As proof-of-principle, it is demonstrated that the biomarker panel could discriminate between menu plans by detecting distinctive changes in the concentration in urine of targeted metabolites. Quantitative relationships between four biomarker concentrations in urine and dietary intake are shown.

CONCLUSION

Design concepts for an analytical strategy are demonstrated, allowing simultaneous quantification of a comprehensive panel of chemically-diverse biomarkers of a wide range of commonly-consumed foods. It is proposed that integration of self-reported dietary recording tools with biomarker approaches will provide more robust assessment of dietary exposure.

Developing community-based urine sampling methods to deploy biomarker technology for the assessment of dietary exposure

OBJECTIVE

Obtaining objective, dietary exposure information from individuals is challenging because of the complexity of food consumption patterns and the limitations of self-reporting tools (e.g., FFQ and diet diaries). This hinders research efforts to associate intakes of specific foods or eating patterns with population health outcomes.

DESIGN

Dietary exposure can be assessed by the measurement of food-derived chemicals in urine samples. We aimed to develop methodologies for urine collection that minimised impact on the day-to-day activities of participants but also yielded samples that were data-rich in terms of targeted biomarker measurements.

SETTING

Urine collection methodologies were developed within home settings.

PARTICIPANTS

Different cohorts of free-living volunteers.

RESULTS

Home collection of urine samples using vacuum transfer technology was deemed highly acceptable by volunteers. Statistical analysis of both metabolome and selected dietary exposure biomarkers in spot urine collected and stored using this method showed that they were compositionally similar to urine collected using a standard method with immediate sample freezing. Even without chemical preservatives, samples can be stored under different temperature regimes without any significant impact on the overall urine composition or concentration of forty-six exemplar dietary exposure biomarkers. Importantly, the samples could be posted directly to analytical facilities, without the need for refrigerated transport and involvement of clinical professionals.

CONCLUSIONS

This urine sampling methodology appears to be suitable for routine use and may provide a scalable, cost-effective means to collect urine samples and to assess diet in epidemiological studies.

Recommendations and Best Practices for Standardizing the Pre-Analytical Processing of Blood and Urine Samples in Metabolomics

Metabolomics can be significantly influenced by a range of pre-analytical factors, such as sample collection, pre-processing, aliquoting, transport, storage and thawing. This therefore shows the crucial need for standardizing the pre-analytical phase with the aim of minimizing the inter-sample variability driven by these technical issues, as well as for maintaining the metabolic integrity of biological samples to ensure that metabolomic profiles are a direct expression of the in vivo biochemical status. This review article provides an updated literature revision of the most important factors related to sample handling and pre-processing that may affect metabolomics results, particularly focusing on the most commonly investigated biofluids in metabolomics, namely blood plasma/serum and urine. Finally, we also provide some general recommendations and best practices aimed to standardize and accurately report all these pre-analytical aspects in metabolomics research.

Addressing the pitfalls when designing intervention studies to discover and validate biomarkers of habitual dietary intake

INTRODUCTION

Dietary exposure monitoring within populations is reliant on self-reported measures such as Food Frequency Questionnaires and diet diaries. These methods often contain inaccurate information due to participant misreporting, non-compliance and bias. Urinary metabolites derived from individual foods could provide additional objective indicators of dietary exposure. For biomarker approaches to have utility it is essential that they cover a wide-range of commonly consumed foods and the methodology works in a real-world environment.

OBJECTIVES

To test that the methodology works in a real-world environment and to consider the impact of the major sources of likely variance; particularly complex meals, different food formulations, processing and cooking methods, as well as the dynamics of biomarker duration in the body.

METHODS

We designed and tested a dietary exposure biomarker discovery and validation strategy based on a food intervention study involving free-living individuals preparing meals and collecting urine samples at home. Two experimental periods were built around three consecutive day menu plans where all foods and drinks were provided (n = 15 and n = 36).

RESULTS

The experimental design was validated by confirming known consumption biomarkers in urinary samples after the first menu plan. We tested biomarker performance with different food formulations and processing methods involving meat, wholegrain, fruits and vegetables.

CONCLUSION

It was demonstrated that spot urine samples, together with robust dietary biomarkers, despite major sources of variance, could be used successfully for dietary exposure monitoring in large epidemiological studies.