Publications
522 results found
Jia W, Li B, Xu Q, et al., 2024, Image-based volume estimation for food in a bowl, Journal of Food Engineering, Vol: 372, ISSN: 0260-8774
Image-assisted dietary assessment has become popular in dietary monitoring studies in recent years. However, food volume estimation is still a challenging problem due to the lack of 3D information in a 2D image and the occlusion of the food by itself or container (e.g., bowl, cup). This study aims to investigate the relationship between the observable surface of food in a bowl and a normalized index (i.e., bowl fullness) to represent its volume. A mathematical model is established for describing different shapes of bowls, and a convenient experimental method is proposed to determine the bowl shape. An image feature called Food Area Ratio (FAR) is used to estimate the volume of food in a bowl based on the relationship between bowl fullness and the FAR calculated from the image. Both simulations and experiments with real food/liquid demonstrate the feasibility and accuracy of the proposed approach.
O'Donovan SD, Rundle M, Thomas EL, et al., 2024, Quantifying the effect of nutritional interventions on metabolic resilience using personalized computational models., iScience, Vol: 27
The manifestation of metabolic deteriorations that accompany overweight and obesity can differ greatly between individuals, giving rise to a highly heterogeneous population. This inter-individual variation can impede both the provision and assessment of nutritional interventions as multiple aspects of metabolic health should be considered at once. Here, we apply the Mixed Meal Model, a physiology-based computational model, to characterize an individual's metabolic health in silico. A population of 342 personalized models were generated using data for individuals with overweight and obesity from three independent intervention studies, demonstrating a strong relationship between the model-derived metric of insulin resistance (ρ = 0.67, p < 0.05) and the gold-standard hyperinsulinemic-euglycemic clamp. The model is also shown to quantify liver fat accumulation and β-cell functionality. Moreover, we show that personalized Mixed Meal Models can be used to evaluate the impact of a dietary intervention on multiple aspects of metabolic health at the individual level.
Frost G, 2024, Glycaemic index as part of the diabetes prevention strategy., Lancet Diabetes Endocrinol
Gressier M, Frost G, Hill Z, et al., 2024, The effectiveness of mandatory vs. voluntary food reformulation policies: a rapid review, The British Journal of Nutrition: an international journal of nutritional science, ISSN: 0007-1145
Gressier M, Frost G, HIll Z, et al., 2024, Supply- and demand-side drivers of the change in the sugar density of food purchased between 2015 and 2018 in Great Britain, The British Journal of Nutrition: an international journal of nutritional science, ISSN: 0007-1145
Steinert RE, Mueller M, Serra M, et al., 2024, Effect of inulin on breath hydrogen, postprandial glycemia, gut hormone release, and appetite perception in RYGB patients: a prospective, randomized, cross-over pilot study., Nutr Diabetes, Vol: 14
BACKGROUND AND OBJECTIVE: Large intestinal fermentation of dietary fiber may control meal-related glycemia and appetite via the production of short-chain fatty acids (SCFA) and the secretion of glucagon-like peptide-1 (GLP-1) and peptide YY (PYY). We investigated whether this mechanism contributes to the efficacy of the Roux-en-Y gastric bypass (RYGB) by assessing the effect of oligofructose-enriched inulin (inulin) vs. maltodextrin (MDX) on breath hydrogen (a marker of intestinal fermentation), plasma SCFAs, gut hormones, insulin and blood glucose concentrations as well as appetite in RYGB patients. METHOD: Eight RYGB patients were studied on two occasions before and ~8 months after surgery using a cross-over design. Each patient received 300 ml orange juice containing 25 g inulin or an equicaloric load of 15.5 g MDX after an overnight fast followed by a fixed portion snack served 3 h postprandially. Blood samples were collected over 5 h and breath hydrogen measured as well as appetite assessed using visual analog scales. RESULTS: Surgery increased postprandial secretion of GLP-1 and PYY (P ≤ 0.05); lowered blood glucose and plasma insulin increments (P ≤ 0.05) and reduced appetite ratings in response to both inulin and MDX. The effect of inulin on breath hydrogen was accelerated after surgery with an increase that was earlier in onset (2.5 h vs. 3 h, P ≤ 0.05), but less pronounced in magnitude. There was, however, no effect of inulin on plasma SCFAs or plasma GLP-1 and PYY after the snack at 3 h, neither before nor after surgery. Interestingly, inulin appeared to further potentiate the early-phase glucose-lowering and second-meal (3-5 h) appetite-suppressive effect of surgery with the latter showing a strong correlation with early-phase breath hydrogen concentrations. CONCLUSION: RYGB surgery accelerates large intestinal fermentation of inulin, however
Serrano-Contreras JI, Lindon JC, Frost G, et al., 2024, Implementation of pure shift 1 H NMR in metabolic phenotyping for structural information recovery of biofluid metabolites with complex spin systems, NMR in Biomedicine, Vol: 37, ISSN: 0952-3480
NMR spectroscopy is a mainstay of metabolic profiling approaches to investigation of physiological and pathological processes. The one-dimensional proton pulse sequences typically used in phenotyping large numbers of samples generate spectra that are rich in information but where metabolite identification is often compromised by peak overlap. Recently developed pure shift (PS) NMR spectroscopy, where all J-coupling multiplicities are removed from the spectra, has the potential to simplify the complex proton NMR spectra that arise from biosamples and hence to aid metabolite identification. Here we have evaluated two complementary approaches to spectral simplification: the HOBS (band-selective with real-time acquisition) and the PSYCHE (broadband with pseudo-2D interferogram acquisition) pulse sequences. We compare their relative sensitivities and robustness for deconvolving both urine and serum matrices. Both methods improve resolution of resonances ranging from doublets, triplets and quartets to more complex signals such as doublets of doublets and multiplets in highly overcrowded spectral regions. HOBS is the more sensitive method and takes less time to acquire in comparison with PSYCHE, but can introduce unavoidable artefacts from metabolites with strong couplings, whereas PSYCHE is more adaptable to these types of spin system, although at the expense of sensitivity. Both methods are robust and easy to implement. We also demonstrate that strong coupling artefacts contain latent connectivity information that can be used to enhance metabolite identification. Metabolite identification is a bottleneck in metabolic profiling studies. In the case of NMR, PS experiments can be included in metabolite identification workflows, providing additional capability for biomarker discovery.
Chambers E, Frampton J, Serrano-Contreras JI, et al., 2024, The impact of acute exercise on appetite regulation: Unravelling the potential involvement of gut microbial activity, The Journal of Physiology, Vol: 602, Pages: 529-530, ISSN: 0022-3751
Sharma A, Papanikolaou N, Abou Sherif S, et al., 2024, Improvements in sperm motility following low or high intensity dietary interventions in men with obesity, Journal of Clinical Endocrinology and Metabolism, Vol: 109, Pages: 449-460, ISSN: 0021-972X
Introduction:Obesity increases risks of male infertility, but bariatric surgery does not improve semen quality. Recent uncontrolled studies suggest that a low-energy diet (LED) improves semen quality. Further evaluation within a randomized, controlled setting is warranted.Methods:Men with obesity (18-60 years) with normal sperm concentration (normal count) (n = 24) or oligozoospermia (n = 43) were randomized 1:1 to either 800 kcal/day LED for 16 weeks or control, brief dietary intervention (BDI) with 16 weeks’ observation. Semen parameters were compared at baseline and 16 weeks.Results:Mean age of men with normal count was 39.4 ± 6.4 in BDI and 40.2 ± 9.6 years in the LED group. Mean age of men with oligozoospermia was 39.5 ± 7.5 in BDI and 37.7 ± 6.6 years in the LED group. LED caused more weight loss than BDI in men with normal count (14.4 vs 6.3 kg; P < .001) and men with oligozoospermia (17.6 vs 1.8 kg; P < .001). Compared with baseline, in men with normal count total motility (TM) increased 48 ± 17% to 60 ± 10% (P < .05) after LED, and 52 ± 8% to 61 ± 6% (P < .0001) after BDI; progressive motility (PM) increased 41 ± 16% to 53 ± 10% (P < .05) after LED, and 45 ± 8% to 54 ± 65% (P < .001) after BDI. In men with oligozoospermia compared with baseline, TM increased 35% [26] to 52% [16] (P < .05) after LED, and 43% [28] to 50% [23] (P = .0587) after BDI; PM increased 29% [23] to 46% [18] (P < .05) after LED, and 33% [25] to 44% [25] (P < .05) after BDI. No differences in postintervention TM or PM were observed between LED and BDI groups in men with normal count or oligozoospermia.Conclusion:LED or BDI may be sufficient to improve sperm motility in men with obesity. The effects of paternal dietary intervention on fertility outcomes requires investigation.
Wedlake L, Mellor D, Marriott T, et al., 2023, What do readers want? Results of an online survey to involve readers in updating the seventh edition of the Manual of dietetic practice, JOURNAL OF HUMAN NUTRITION AND DIETETICS, ISSN: 0952-3871
Jobarteh ML, McCrory MA, Lo B, et al., 2023, Evaluation of acceptability, functionality, and validity of a passive image-based dietary intake assessment method in adults and children of Ghanaian and Kenyan origin living in London, UK, Nutrients, Vol: 15, ISSN: 2072-6643
BACKGROUND: Accurate estimation of dietary intake is challenging. However, whilst some progress has been made in high-income countries, low- and middle-income countries (LMICs) remain behind, contributing to critical nutritional data gaps. This study aimed to validate an objective, passive image-based dietary intake assessment method against weighed food records in London, UK, for onward deployment to LMICs. METHODS: Wearable camera devices were used to capture food intake on eating occasions in 18 adults and 17 children of Ghanaian and Kenyan origin living in London. Participants were provided pre-weighed meals of Ghanaian and Kenyan cuisine and camera devices to automatically capture images of the eating occasions. Food images were assessed for portion size, energy, nutrient intake, and the relative validity of the method compared to the weighed food records. RESULTS: The Pearson and Intraclass correlation coefficients of estimates of intakes of food, energy, and 19 nutrients ranged from 0.60 to 0.95 and 0.67 to 0.90, respectively. Bland-Altman analysis showed good agreement between the image-based method and the weighed food record. Under-estimation of dietary intake by the image-based method ranged from 4 to 23%. CONCLUSIONS: Passive food image capture and analysis provides an objective assessment of dietary intake comparable to weighed food records.
Rundle M, Fiamoncini J, Thomas EL, et al., 2023, Diet-induced Weight Loss and Phenotypic Flexibility Among Healthy Overweight Adults: A Randomized Trial, AMERICAN JOURNAL OF CLINICAL NUTRITION, Vol: 118, Pages: 591-604, ISSN: 0002-9165
Stanner S, Spiro A, Ahmadi K, et al., 2023, Translational research to identify solutions to the UK's key diet, health and nutrition challenges: The Diet and Health Open Innovation Research Club Innovation Hubs., Nutr Bull, Vol: 48, Pages: 310-313
Brown AA, Fernandez-Tajes JJ, Hong M-G, et al., 2023, Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits, NATURE COMMUNICATIONS, Vol: 14
Frampton J, Serrano Contreras J, Garcia Perez I, et al., 2023, The metabolic interplay between dietary carbohydrate and exercise and its role in acute appetite-regulation in males: a randomised controlled study, The Journal of Physiology, Vol: 601, Pages: 3461-3480, ISSN: 0022-3751
An understanding of the metabolic determinants of postexercise appetite regulation would facilitate development of adjunctive therapeutics to suppress compensatory eating behaviours and improve the efficacy of exercise as a weight-loss treatment. Metabolic responses to acute exercise are, however, dependent on pre-exercise nutritional practices, including carbohydrate intake. We therefore aimed to determine the interactive effects of dietary carbohydrate and exercise on plasma hormonal and metabolite responses and explore mediators of exercise-induced changes in appetite regulation across nutritional states. In this randomized crossover study, participants completed four 120 min visits: (i) control (water) followed by rest; (ii) control followed by exercise (30 min at ∼75% of maximal oxygen uptake); (iii) carbohydrate (75 g maltodextrin) followed by rest; and (iv) carbohydrate followed by exercise. An ad libitum meal was provided at the end of each 120 min visit, with blood sample collection and appetite assessment performed at predefined intervals. We found that dietary carbohydrate and exercise exerted independent effects on the hormones glucagon-like peptide 1 (carbohydrate, 16.8 pmol/L; exercise, 7.4 pmol/L), ghrelin (carbohydrate, −48.8 pmol/L; exercise: −22.7 pmol/L) and glucagon (carbohydrate, 9.8 ng/L; exercise, 8.2 ng/L) that were linked to the generation of distinct plasma 1H nuclear magnetic resonance metabolic phenotypes. These metabolic responses were associated with changes in appetite and energy intake, and plasma acetate and succinate were subsequently identified as potential novel mediators of exercise-induced appetite and energy intake responses. In summary, dietary carbohydrate and exercise independently influence gastrointestinal hormones associated with appetite regulation. Future work is warranted to probe the mechanistic importance of plasma acetate and succinate in postexercise appetite regulation.
Hernandez YAT, Julian A, Weekes EC, et al., 2023, Developing a consensus to support health and social care professionals and patients manage nutrition in the context of COVID-19 recovery, JOURNAL OF HUMAN NUTRITION AND DIETETICS, Vol: 36, Pages: 1242-1252, ISSN: 0952-3871
Ghosh T, McCrory MA, Marden T, et al., 2023, I2N: image to nutrients, a sensor guided semi-automated tool for annotation of images for nutrition analysis of eating episodes, Frontiers in Nutrition, Vol: 10, Pages: 1-9, ISSN: 2296-861X
INTRODUCTION: Dietary assessment is important for understanding nutritional status. Traditional methods of monitoring food intake through self-report such as diet diaries, 24-hour dietary recall, and food frequency questionnaires may be subject to errors and can be time-consuming for the user. METHODS: This paper presents a semi-automatic dietary assessment tool we developed - a desktop application called Image to Nutrients (I2N) - to process sensor-detected eating events and images captured during these eating events by a wearable sensor. I2N has the capacity to offer multiple food and nutrient databases (e.g., USDA-SR, FNDDS, USDA Global Branded Food Products Database) for annotating eating episodes and food items. I2N estimates energy intake, nutritional content, and the amount consumed. The components of I2N are three-fold: 1) sensor-guided image review, 2) annotation of food images for nutritional analysis, and 3) access to multiple food databases. Two studies were used to evaluate the feasibility and usefulness of I2N: 1) a US-based study with 30 participants and a total of 60 days of data and 2) a Ghana-based study with 41 participants and a total of 41 days of data). RESULTS: In both studies, a total of 314 eating episodes were annotated using at least three food databases. Using I2N's sensor-guided image review, the number of images that needed to be reviewed was reduced by 93% and 85% for the two studies, respectively, compared to reviewing all the images. DISCUSSION: I2N is a unique tool that allows for simultaneous viewing of food images, sensor-guided image review, and access to multiple databases in one tool, making nutritional analysis of food images efficient. The tool is flexible, allowing for nutritional analysis of images if sensor signals aren't available.
Allesoe RL, Lundgaard AT, Hernandez Medina R, et al., 2023, Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models (vol 41, pg 399, 2023), NATURE BIOTECHNOLOGY, Vol: 41, Pages: 1026-1026, ISSN: 1087-0156
Shahid M, Gaines A, Coyle D, et al., 2023, The effect of mycoprotein intake on biomarkers of human health: a systematic review and meta-analysis, American Journal of Clinical Nutrition, Vol: 118, Pages: 141-150, ISSN: 0002-9165
BackgroundMycoprotein is a fungal source of protein that is increasingly consumed as an ingredient in meat analogs.ObjectivesThis study aimed to systematically review and meta-analyze the effects of mycoprotein intake on selected biomarkers of human health.MethodsThis study was registered in PROSPERO (CRD42022308980). We searched the PubMed, Scopus, and Embase databases to identify randomized control trials in any language until 16 August, 2022. Trials were included if they administered a mycoprotein intervention against a nonmycoprotein control arm and if reported outcomes included blood lipids, blood glucose, insulin, blood pressure, or body weight. Eligible trials were assessed for risk of bias using the Cochrane risk-of-bias tool for randomized trials. An inverse-variance–weighted, random-effects meta-analysis model was used to assess the effects of intake across each biomarker.ResultsNine trials that included 178 participants with a mean follow-up of 13 d were included, with 4 reporting on blood lipids and 5 reporting on postprandial blood glucose or insulin. The overall reduction of total cholesterol was −0.55 mmol/L (95% CI: −0.85 to −0.26; P < 0.001) in the mycoprotein group compared to control, but no clear effects on HDL cholesterol, LDL cholesterol, or TGs were found (all P > 0.05). There were no reductions in postprandial blood glucose concentrations at 30, 60, 90 or 120 min. Postprandial blood insulin concentration was reduced by −76.51 pmol/L (95% CI: −150.75 to −2.28; P = 0.043) at 30 min, with no detectable effects at 60, 90, or 120 min.ConclusionsMycoprotein intake may have important effects on blood lipids, but the evidence base is limited by the small sample sizes and short intervention periods of the contributing trials.
Cherta-Murillo A, Danckert NP, Valdivia-Garcia M, et al., 2023, Gut microbiota fermentation profiles of pre-digested mycoprotein (Quorn) using faecal batch cultures <i>in vitro</i>: a preliminary study, INTERNATIONAL JOURNAL OF FOOD SCIENCES AND NUTRITION, Vol: 74, Pages: 327-337, ISSN: 0963-7486
Pugh J, Cai M, Altieri N, et al., 2023, A comparison of the effects of resistant starch types on glycaemic response in individuals with type 2 diabetes or prediabetes: a systematic review and meta-analysis, Frontiers in Nutrition, Vol: 10, Pages: 1-11, ISSN: 2296-861X
Background: Type 2 diabetes (T2D) diagnoses are predicted to reach 643 million by 2030, increasing incidences of cardiovascular disease and other comorbidities. Rapidly digestible starch elevates postprandial glycemia and impinges glycemic homeostasis, elevating the risk of developing T2D. Starch can escape digestion by endogenous enzymes in the small intestine when protected by intact plant cell walls (resistant starch type 1), when there is a high concentration of amylose (resistant starch type 2) and when the molecule undergoes retrogradation (resistant starch type 3) or chemical modification (resistant starch type 4). Dietary interventions using resistant starch may improve glucose metabolism and insulin sensitivity. However, few studies have explored the differential effects of resistant starch type. This systematic review and meta-analysis aims to compare the effects of the resistant starch from intact plant cell structures (resistant starch type 1) and resistant starch from modified starch molecules (resistant starch types 2–5) on fasting and postprandial glycemia in subjects with T2D and prediabetes.Methods: Databases (PubMed, SCOPUS, Ovid MEDLINE, Cochrane, and Web of Science) were systematically searched for randomized controlled trials. Standard mean difference (SMD) with 95% confidence intervals (CI) were determined using random-effects models. Sub-group analyses were conducted between subjects with T2D versus prediabetes and types of resistant starch.Results: The search identified 36 randomized controlled trials (n = 982), 31 of which could be included in the meta-analysis. Resistant starch type 1 and type 2 lowered acute postprandial blood glucose [SMD (95% CI) = -0.54 (–1.0, –0.07)] and [–0.96 (–1.61, –0.31)]. Resistant starch type 2 improved acute postprandial insulin response [–0.71 (–1.31, –0.11)]. In chronic studies, resistant starch type 1 and 2 lowered postprandial glucose [–0.38 (&ndas
Qiu J, Lo FP-W, Gu X, et al., 2023, Egocentric image captioning for privacy-preserved passive dietary intake monitoring, IEEE Transactions on Cybernetics, Vol: PP, Pages: 1-14, ISSN: 1083-4419
Camera-based passive dietary intake monitoring is able to continuously capture the eating episodes of a subject, recording rich visual information, such as the type and volume of food being consumed, as well as the eating behaviors of the subject. However, there currently is no method that is able to incorporate these visual clues and provide a comprehensive context of dietary intake from passive recording (e.g., is the subject sharing food with others, what food the subject is eating, and how much food is left in the bowl). On the other hand, privacy is a major concern while egocentric wearable cameras are used for capturing. In this article, we propose a privacy-preserved secure solution (i.e., egocentric image captioning) for dietary assessment with passive monitoring, which unifies food recognition, volume estimation, and scene understanding. By converting images into rich text descriptions, nutritionists can assess individual dietary intake based on the captions instead of the original images, reducing the risk of privacy leakage from images. To this end, an egocentric dietary image captioning dataset has been built, which consists of in-the-wild images captured by head-worn and chest-worn cameras in field studies in Ghana. A novel transformer-based architecture is designed to caption egocentric dietary images. Comprehensive experiments have been conducted to evaluate the effectiveness and to justify the design of the proposed architecture for egocentric dietary image captioning. To the best of our knowledge, this is the first work that applies image captioning for dietary intake assessment in real-life settings.
Allesoe RL, Lundgaard AT, Medina RH, et al., 2023, Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models, NATURE BIOTECHNOLOGY, Vol: 41, Pages: 399-+, ISSN: 1087-0156
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Garcia-Perez I, Posma JM, Chambers ES, et al., 2023, Dietary metabotype modelling predicts individual responses to dietary interventions (Vol 1, pg 355, 2020) (Retraction of Vol 1, Pg 355, 2020), NATURE FOOD, Vol: 4, Pages: 269-269
Chew W, Lim YP, Lim WS, et al., 2023, Gut-muscle crosstalk. A perspective on influence of microbes on muscle function, FRONTIERS IN MEDICINE, Vol: 9
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Fard SE, Ghosh T, Hossain D, et al., 2023, Development of a Method for Compliance Detection in Wearable Sensors
One of the crucial elements in studies relying on wearable sensors for quantification of human activities (like physical activity or food intake) is the assessment of wear time (compliance). In this paper, we propose a novel method based on the Automatic Ingestion Monitor v2 (AIM-2), deployed for measuring nutrient and energy intake. The proposed method was developed using data from a study of 30 participants for two days each (US dataset) and tested with an independent dataset (Ghana dataset) on 10 households (30 Participants, 3 days for each, a total of 90 days). The signals from the accelerometer sensor of the AIM-2 were used to extract features and train the gradient-boosting tree classifier. To reduce the error in the classification of non-compliance in situations where the sensor changes its position with respect to gravity, a two-stage classifier followed by post-processing was introduced. Previously, we developed an offline compliance classifier, and this work aimed to develop a classifier for a cloud-based feedback system. The accuracy and F1-score of the developed two-phase classifier based on K-fold validation for the training and validation dataset were 95.37% and 96.93%, and for the Ghana dataset, were 95.86% and 92.56%, respectively, showing satisfactory performance results. The trained classifier can be deployed to monitor compliance with device wear in realtime applications. Clinical Relevance- Food Intake and physical activity studies can contribute to detecting, controlling, and even improving eating or physical activity-related problems, like obesity, diabetes, and eating planning. To ensure effective monitoring, compliance with the wearing of the device is crucial.
Brand-Miller J, Frost G, Dornhorst A, 2023, Glycemic index, Encyclopedia of Human Nutrition: Volume 1-4, Fourth Edition, Pages: 422-429, ISBN: 9780323908160
In the past 10 years, epidemiological and experimental studies have linked the glycemic index of staple carbohydrate foods to postprandial glucose metabolism, insulin resistance, diabetes and cardiovascular risk factors. Beliefs about the glycemic index have been polarized, but many organizations, including the World Health Organization (WHO), recommend that the physiological effects of dietary carbohydrates be classified according to their glycemic index. This review examines the historical and scientific background of the glycemic index.
Cai M, Edwards C, Tashkova M, et al., 2023, Cell wall matrices in chickpeas and their effects on starch digestion and postprandial metabolism, Winter Conference 2022/23,Architecture of food: processing, structure and health, Publisher: Cambridge University Press, ISSN: 0029-6651
Dawed AY, Mari A, Brown A, et al., 2023, Pharmacogenomics of GLP-1 receptor agonists: a genome-wide analysis of observational data and large randomised controlled trials, LANCET DIABETES & ENDOCRINOLOGY, Vol: 11, Pages: 33-41, ISSN: 2213-8587
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Rowley CE, Lodge S, Egan S, et al., 2023, Altered dietary behaviour during pregnancy impacts systemic metabolic phenotypes., Front Nutr, Vol: 10, ISSN: 2296-861X
RATIONALE: Evidence suggests consumption of a Mediterranean diet (MD) can positively impact both maternal and offspring health, potentially mediated by a beneficial effect on inflammatory pathways. We aimed to apply metabolic profiling of serum and urine samples to assess differences between women who were stratified into high and low alignment to a MD throughout pregnancy and investigate the relationship of the diet to inflammatory markers. METHODS: From the ORIGINS cohort, 51 pregnant women were stratified for persistent high and low alignment to a MD, based on validated MD questionnaires. 1H Nuclear Magnetic Resonance (NMR) spectroscopy was used to investigate the urine and serum metabolite profiles of these women at 36 weeks of pregnancy. The relationship between diet, metabolite profile and inflammatory status was investigated. RESULTS: There were clear differences in both the food choice and metabolic profiles of women who self-reported concordance to a high (HMDA) and low (LMDA) Mediterranean diet, indicating that alignment with the MD was associated with a specific metabolic phenotype during pregnancy. Reduced meat intake and higher vegetable intake in the HMDA group was supported by increased levels of urinary hippurate (p = 0.044) and lower creatine (p = 0.047) levels. Serum concentrations of the NMR spectroscopic inflammatory biomarkers GlycA (p = 0.020) and GlycB (p = 0.016) were significantly lower in the HDMA group and were negatively associated with serum acetate, histidine and isoleucine (p < 0.05) suggesting a greater level of plant-based nutrients in the diet. Serum branched chain and aromatic amino acids were positively associated with the HMDA group while both urinary and serum creatine, urine creatinine and dimethylamine were positively associated with the LMDA group. CONCLUSION: Metabolic phenotypes of pregnant women who had a high alignment with the MD were signifi
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