Biomarkers of Nutrition and Health: New Tools for New Approaches

Exhaustive Search of Dietary Intake Biomarkers as Objective Tools for Personalized Nutrimetabolomics and Precision Nutrition Implementation

OBJECTIVE

To conduct an exhaustive scoping search of existing literature, incorporating diverse bibliographic sources to elucidate the relationships between metabolite biomarkers in human fluids and dietary intake.

BACKGROUND

The search for biomarkers linked to specific dietary food intake holds immense significance for precision health and nutrition research. Using objective methods to track food consumption through metabolites offers a more accurate way to provide dietary advice and prescriptions on healthy dietary patterns by healthcare professionals. An extensive investigation was conducted on biomarkers associated with the consumption of several food groups and consumption patterns. Evidence is integrated from observational studies, systematic reviews, and meta-analyses to achieve precision nutrition and metabolism personalization.

METHODS

Tailored search strategies were applied across databases and gray literature, yielding 158 primary research articles that met strict inclusion criteria. The collected data underwent rigorous analysis using STATA and Python tools. Biomarker-food associations were categorized into 5 groups: cereals and grains, dairy products, protein-rich foods, plant-based foods, and a miscellaneous group. Specific cutoff points (≥3 or ≥4 bibliographic appearances) were established to identify reliable biomarkers indicative of dietary consumption.

RESULTS

Key metabolites in plasma, serum, and urine revealed intake from different food groups. For cereals and grains, 3-(3,5-dihydroxyphenyl) propanoic acid glucuronide and 3,5-dihydroxybenzoic acid were significant. Omega-3 fatty acids and specific amino acids showcased dairy and protein foods consumption. Nuts and seafood were linked to hypaphorine and trimethylamine N-oxide. The miscellaneous group featured compounds like theobromine, 7-methylxanthine, caffeine, quinic acid, paraxanthine, and theophylline associated with coffee intake.

CONCLUSIONS

Data collected from this research demonstrate potential for incorporating precision nutrition into clinical settings and nutritional advice based on accurate estimation of food intake. By customizing dietary recommendations based on individualized metabolic profiles, this approach could significantly improve personalized food consumption health prescriptions and support integrating multiple nutritional data.This article is part of a Nutrition Reviews special collection on Precision Nutrition.

Evaluating modifiable hypertension risk in Nigerian adults-The Nigerian diet risk score

AIMS

Our study aimed to derive and validate a diet risk score for clinical use in Nigeria to screen for hypertension risk and evaluate its association against a panel of cardiovascular biomarkers.

METHODS

The Nigerian dietary screening tool was used to collect dietary intake data from 151 participants visiting the River State University Teaching Hospital, Port Harcourt, Nigeria, for routine medical care. Blood samples were collected from a subsample (n = 94) for biomarker assessment. Multiple logistic regression was used to derive the Nigerian diet risk score for hypertension. Internal validation of the Nigerian diet risk score for hypertension was performed using measures of discrimination and calibration. Mediation analysis was used to evaluate the biomarker-mediated effects of the diet risk score for hypertension on hypertension. All statistical analyses were performed in R.

RESULTS

Each one-point increment in Nigerian diet risk score (on a scale of 0 to 30) was associated with a twofold increase in odds of hypertension (odds ratio: 2.04, 95% confidence interval [CI]: 1.16, 3.58, p = 0.01), with the highest score associated with >18-fold increased odds of hypertension, compared to lowest Nigerian diet risk score for hypertension. The score demonstrated good discrimination (area under the curve: 0.92, 95% CI: 0.80, 1.00) with a high sensitivity (0.85) and specificity (0.94). Additionally, mediation analysis suggested that the association between Nigerian diet risk score for hypertension and blood pressure is partly explained by shared biological pathways that mediate cholesterol, triglycerides, LDL-C, CRP and homocysteine levels.

CONCLUSION

The resulting Nigerian diet risk score for hypertension is a valuable tool for clinicians to identify individuals at risk of hypertension, and will advance community efforts in the prevention and management of hypertension in Nigeria.

Comparison of the capillary and venous blood plasma lipidomes: validation of self-collected blood for plasma lipidomics

Venipuncture of the upper extremities is commonly used to collect blood for plasma lipidomics. However, self-administered blood collection devices such as the Tasso+™ system for capillary blood sampling and plasma separation are convenient and enable frequent sampling without a clinical blood draw. The purpose of this study is to validate Tasso+ sampling for plasma lipidomics by comparing the venous blood and Tasso+-sampled capillary blood plasma lipidomes. Lipids are proven or putative biomarkers of human health and disease and indicators of nutritional and toxicological status. Because exchange of blood components including lipids occurs in capillaries, the capillary and venous blood lipidomes might be different, which could confound use of Tasso+-sampled blood as a surrogate for venous blood plasma. Here we compared the lipidomes of Tasso+-drawn capillary blood plasma and venous blood plasma in 10 male subjects using high-resolution mass spectrometry-based lipidomics. While there was substantial interindividual variability between lipidomes, comprehensive statistical approaches with cross-validation and multiple testing adjustments showed no difference (adjusted P-value > 0.05) in lipid composition of the paired blood samples. A linear regression model with Spearman correlation analysis also showed a significant-to-near-perfect level (r = 0.95-0.99) of concordance between the samples. Aside from monoacylglycerols and cardiolipins, every class of lipid was strongly correlated (r = 0.9-0.99) between paired venous and capillary blood plasma. In summary, the capillary and venous blood plasma lipidomes are essentially identical making self-administered collection of capillary blood a viable approach for clinical blood plasma lipidomics.

Biochemical validation of a food frequency questionnaire measuring immune modulating nutrient intake in patients with peripheral arterial disease

BACKGROUND AND AIMS

Peripheral arterial disease (PAD) is a cardiovascular disease affecting approximately 6 % of the population. The condition is associated with claudication, non-healing ischemic ulceration, and a systemic pro-inflammatory and pro-oxidative state. Recently, nutrition therapy is exploring immunonutrition as a novel dietary strategy to reduce the progression of atherosclerosis. A 21-item food frequency questionnaire (FFQ) has been developed and previously validated in the PAD population against a dietitian collected seven-day diet history method showing good agreement. The aim of this study was to determine whether the FFQ accurately predicts serum levels of six routinely analysed immune-modulating nutrients (vitamins A, C, D, and E, zinc, iron).

METHODS AND RESULTS

Dietary intake measured by the validated FFQ was compared to fasting serum blood levels of their respective biomarkers. Correlation coefficients and quartile agreements were performed to determine the relationship between dietary intake and serum levels. The mean age of participants (n = 100) was 75 years with 76 % being male. Correlation coefficients and quartile agreements indicated poor agreement between intake measured by FFQ and serum biomarkers and were not statistically significant.

CONCLUSION

These results suggest that intake measured by the FFQ is not an accurate reflection of serum levels of these immune-modulating nutrients in this population, possibly due to endogenous physiological processes specific to PAD. Further research into the utilisation of nutrients is warranted to inform dietary recommendations in this population.

Exploring Biomarkers for Malaria: Advances in Early Detection and Asymptomatic Diagnosis

Malaria is a tropical disease caused by the Plasmodium parasite, which was responsible for 249 million cases worldwide in 2022. Malaria is currently diagnosed using RDTs, PCR-based methods, or blood smear microscopy. Ideal biomarkers have been identified for malaria, with the potential for improving treatment, diagnosis, and overall clinical outcomes. This review discusses the types of existing biomarkers and the opportunities for new biomarkers to be used as diagnostic components in detecting Plasmodium, including in terms of sensitivity, detection limit, specificity, and the species of Plasmodium that can be detected. Following a comparison, five main ideal malaria biomarkers were identified, namely HRP2, pLDH, hemozoin, aldolase, and pGDH. These biomarkers distinguished themselves markedly from the others in terms of specificity in Plasmodium detection, sensitivity in analysis, and the use of non-invasive samples. Several other biomarkers, such as CRP, Ang-1, Ang-2, and PCT, show potential for malaria detection in terms of their ability to differentiate disease severity, and the levels of these biomarkers can be determined in the body for comparison with malaria parasitemia. Of the five ideal biomarkers, hemozoin and aldolase can still be developed regarding the types of samples used and their sensitivity to different Plasmodium species. Further research on the biomarkers CRP, Ang-1, Ang-2, and PCT is still needed to evaluate their potential.

Personalized nutrition: perspectives on challenges, opportunities, and guiding principles for data use and fusion

Personalized nutrition (PN) delivers tailored dietary guidance by integrating health, lifestyle, and behavioral data to improve individual health outcomes. Recent technological advances have enhanced access to diverse data sources, yet challenges remain in collecting, integrating, and analyzing complex datasets. To address these, the Personalized Nutrition Initiative at Illinois organized a workshop titled "Personalized Nutrition Data: Challenges & Opportunities," which gathered experts to explore three essential data domains in PN: 1) health and biological, 2) social, behavioral, and environmental, and 3) consumer purchasing data. Discussions underscored the importance of cross-disciplinary collaboration to standardize data collection, enable secure data sharing, and develop data fusion techniques that respect privacy and build trust. Participants emphasized the need for representative datasets that include underserved populations, ensuring that PN services are accessible and equitable. Key principles for responsible data integration were proposed, alongside strategies to overcome barriers to effective data use. By addressing these challenges, PN can enhance health outcomes through precise, personalized recommendations tailored to diverse population needs.

Artificial sweeteners and Type 2 Diabetes Mellitus: A review of current developments and future research directions

While artificial sweeteners are Generally Regarded as Safe (GRAS), the scientific community remains divided on their safety status. The previous assumption that artificial sweeteners are inert within the body is no longer valid. Artificial sweeteners, known for their high intense sweetness and low or zero calories, are extensively used today in food and beverage products as sugar substitutes and are sometimes recommended for weight management and Type 2 Diabetes Mellitus (T2DM) patients. The general omission of information about the concentration of artificial sweeteners on market product labels makes it challenging to determine the amounts of artificial sweeteners consumed by people. Despite regulatory authorization for their usage, such as from the United States Food and Drug Administration (FDA), concerns remain about their potential association with metabolic diseases, such as T2DM, which the artificial sweeteners were supposed to reduce. This review discusses the relationship between artificial sweetener consumption and the risk of developing T2DM. With the increasing number of recent scientific studies adding to the debate on this subject matter, we assessed recent literature and up-to-date evidence. Importantly, we highlight future research directions toward furthering knowledge in this field of study.

Modifications to the Geriatric Nutritional Risk Index Predicts Complications After Total Joint Arthroplasty

BACKGROUND

Preoperative malnutrition is a known risk factor for postoperative complications following total joint arthroplasty (TJA); however, there is scant literature comparing which nutritional index is best at predicting these outcomes. The purpose of this study was to investigate the utility of the Maastricht index, Onodera's Prognostic Nutritional Index, the Geriatric Nutritional Risk index, and a novel, modified Geriatric Nutritional Risk Index (mGNRI) in predicting periprosthetic joint infection (PJI), wound complications (WCs), readmission, and reoperation rates after TJA.

METHODS

A single-center, retrospective cohort study was performed of patients who underwent primary TJA from January 2016 to December 2021. The 90-day preoperative albumin, prealbumin, and total lymphocyte count were collected. Outcome measures were PJI, WC, readmission, and return to the operating room. Youden's index (YI) and Receiver operator characteristic curves were used to determine optimal cutoff points. Multivariable logistic regression was used to adjust for potential confounders, including body mass index, age, and the Charlson comorbidity index.

RESULTS

There were 1,575 patients included in the study. The mGNRI had the greatest accuracy (area under the curve = 0.633; optimal cutoff point = 92.8) in predicting postoperative adverse outcomes. Complication rates were significantly higher in the low mGNRI group (≤ 92.8). When controlled for body mass index, Charlson comorbidity index, and age, the odds of PJI, WC, readmission, and reoperation in patients who had low mGNRI were 6.61 (P = 0.005), 3.04 (P = 0.021), 2.25 (P = 0.020), and 2.75 (P = 0.024), respectively.

CONCLUSIONS

The mGNRI is an easy-to-calculate nutritional index and an excellent predictor of postoperative complications following TJA. The mGNRI outperformed Geriatric Nutritional Risk index, Maastricht index, and Onodera's Prognostic Nutritional Index in predicting postoperative complications. Our results suggest that patients who fall below the mGNRI threshold of 92.8 should be carefully considered for nutritional optimization prior to TJA.

Foodomics: A sustainable approach for the specific nutrition and diets for human health

Foodomics is an interdisciplinary field that integrates various omics technologies to explore the complex relationship between food and human health in depth. This approach offers valuable insights into the biochemical, molecular, and cellular composition of food by employing advanced omics techniques. Its applications span the food industry and human health, including efforts to combat malnutrition, provide dietary recommendations, and ensure food safety. This paper critically examines the successful applications of foodomics across areas such as food safety, quality, traceability, processing, and bioactivity. It highlights the crucial role of metabolomics, proteomics, and transcriptomics in achieving a comprehensive understanding of food components, their functions, and their interactions with human biology.

Evaluating the Impact of a Novel Program to Address Acute Food Insecurity Among Cancer Patients

INTRODUCTION

Acute food insecurity (FI) significantly impacts cancer patients' health, exacerbating physical and psychological burdens. While current interventions address chronic FI, acute cases remain undermanaged. Legacy of Hope, a Philadelphia-based non-profit, addresses this gap through its Emergency Patient Support Network (EPSN), offering free bi-weekly groceries to patients facing acute FI.

MATERIALS AND METHODS

The pilot study evaluated EPSN's impact utilizing the Legacy of Hope Acute Food Insecurity (LOHAFI) survey, which was performed at baseline and two weeks post-intervention. The survey combines the Functional Assessment of Cancer Therapy-General (FACT-G7) and questions on food and financial security. Mean scores and frequencies were calculated.

RESULTS

Fifty patients (n = 50) completed the LOHAFI survey. The mean age was 55.1 years; 70% were female; 33 (66%) identified as Black. Two weeks after receiving groceries, patients reported a decrease in nausea (pre: 1.34; post: 1.18) and anxiety related to their cancer (pre: 2.49; post: 2.41) and an increase in the availability (pre: 1.70; post: 1.84) and consumption (pre: 2.26; post: 2.30) of healthy food. However, patient overall quality of life did not improve (pre: 13.14; post: 12.76).

CONCLUSIONS

Legacy of Hope's EPSN shows potential in alleviating acute FI among cancer patients, although larger studies are needed to fully assess its impact.

Urinary Metabolite Profiles of Participants with Overweight and Obesity Prescribed a Weight Loss High Fruit and Vegetable Diet: A Single Arm Intervention Study

BACKGROUND/OBJECTIVES

Thus far, no studies have examined the relationship between fruit and vegetable (F and V) intake, urinary metabolite quantities, and weight change. Therefore, the aim of the current study was to explore changes in urinary metabolomic profiles during and after a 10-week weight loss intervention where participants were prescribed a high F and V diet (7 servings daily).

METHODS

Adults with overweight and obesity (n = 34) received medical nutrition therapy counselling to increase their F and V intakes to national targets (7 servings a day). Data collection included weight, dietary intake, and urine samples at baseline at week 2 and week 10. Urinary metabolite profiles were quantified using 1H NMR spectroscopy. Machine learning statistical approaches were employed to identify novel urine-based metabolite biomarkers associated with high F and V diet patterns at weeks 2 and 10. Metabolic changes appearing in urine in response to diet were quantified using Metabolite Set Enrichment Analysis (MSEA).

RESULTS

Energy intake was significantly lower (p = 0.02) at week 10 compared with baseline. Total F and V intake was significantly higher at week 2 and week 10 (p < 0.05). In total, 123 urinary metabolites were quantified. At week 10, 21 metabolites showed significant changes relative to baseline. Of these, 11 metabolites also significantly changed at week 2. These overlapping metabolites were acetic acid, dimethylamine, choline, fumaric acid, glutamic acid, L-tyrosine, histidine, succinic acid, uracil, histamine, and 2-hydroxyglutarate. Ridge Classifier and Linear Discriminant Analysis provided best prediction accuracy values of 0.96 when metabolite level of baseline was compared to week 10.

CONCLUSIONS

Urinary metabolites quantified represent potential candidate biomarkers of high F and V intake, associated with a reduction in energy intake. Further studies are needed to validate these findings in larger population studies.

Metabolic pathway and network analysis integration for discovering the biomarkers in pig feces after a controlled fruit-vegetable dietary intervention

This study aimed to establish a strategy for identifying dietary intake biomarkers using a non-targeted metabolomic approach, including metabolic pathway and network analysis. The strategy was successfully applied to identify dietary intake biomarkers in fecal samples from pigs fed two doses of a polyphenol-rich fruit and vegetable (FV) diet following the Dietary Guidelines for Americans (DGA) recommendations. Potential biomarkers were identified among dietary treatment groups using liquid chromatography-high resolution mass spectrometry (LC-HRMS) based on a non-targeted metabolomic approach with metabolic pathway and network analysis. Principal component analysis (PCA) results showed significant differences in fecal metabolite profiles between the control and two FV intervention groups, indicating a diet-induced differential fecal metabolite profile after FV intervention. Metabolites from common flavonoids, e.g., (epi)catechin and protocatechuic acid, or unique flavonoids, e.g., 5,3',4'-trihydroxy-3-methoxy-6,7-methylenedioxyflavone and 3,5,3',4'-tetrahydroxy-6,7-methylenedioxyflavone, were identified as highly discriminating factors, confirming their potential as fecal markers for the FV dietary intervention. Microbiota pathway prediction using targeted flavonoids provided valuable and reliable biomarker exploration with high confidence. A correlation network analysis between these discriminatory ion features was applied to find connections to possible dietary biomarkers, further validating these biomarkers with biochemical insights. This study demonstrates that integrating metabolic pathways and network analysis with a non-targeted metabolomic approach is highly effective for rapid and accurate identification and prediction of fecal biomarkers under controlled dietary conditions in animal studies. This approach can also be utilized to study microbial metabolisms in human clinical research.

The Future of Pharmacogenomics: Integrating Epigenetics, Nutrigenomics, and Beyond

Pharmacogenomics (PGx) has revolutionized personalized medicine by empowering the tailoring of drug treatments based on individual genetic profiles. However, the complexity of drug response mechanisms necessitates the integration of additional biological and environmental factors. This article explores integrating epigenetics, nutrigenomics, microbiomes, protein interactions, exosomes, and metabolomics with PGx to enhance personalized medicine. In addition to discussing these scientific advancements, we examine the regulatory and ethical challenges of translating multi-omics into clinical practice, including considerations of data privacy, regulatory oversight, and equitable access. By framing these factors within the context of Medication Adherence, Medication Appropriateness, and Medication Adverse Events (MA3), we aim to refine therapeutic strategies, improve drug efficacy, and minimize adverse effects, with the goal of improving personalized medicine. This approach has the potential to benefit patients, healthcare providers, payers, and the healthcare system as a whole by enabling more precise and effective treatments.

Biomarker-Guided Dietary Supplementation: A Narrative Review of Precision in Personalized Nutrition

Background: Dietary supplements (DS) are widely used to address nutritional deficiencies and promote health, yet their indiscriminate use often leads to reduced efficacy, adverse effects, and safety concerns. Biomarker-driven approaches have emerged as a promising strategy to optimize DS prescriptions, ensuring precision and reducing risks associated with generic recommendations. Methods: This narrative review synthesizes findings from key studies on biomarker-guided dietary supplementation and the integration of artificial intelligence (AI) in biomarker analysis. Key biomarker categories-genomic, proteomic, metabolomic, lipidomic, microbiome, and immunological-were reviewed, alongside AI applications for interpreting these biomarkers and tailoring supplement prescriptions. Results: Biomarkers enable the identification of deficiencies, metabolic imbalances, and disease predispositions, supporting targeted and safe DS use. For example, genomic markers like MTHFR polymorphisms inform folate supplementation needs, while metabolomic markers such as glucose and insulin levels guide interventions in metabolic disorders. AI-driven tools streamline biomarker interpretation, optimize supplement selection, and enhance therapeutic outcomes by accounting for complex biomarker interactions and individual needs. Limitations: Despite these advancements, AI tools face significant challenges, including reliance on incomplete training datasets and a limited number of clinically validated algorithms. Additionally, most current research focuses on clinical populations, limiting generalizability to healthier populations. Long-term studies remain scarce, raising questions about the sustained efficacy and safety of biomarker-guided supplementation. Regulatory ambiguity further complicates the classification of supplements, especially when combinations exhibit pharmaceutical-like effects. Conclusions: Biomarker-guided DS prescription, augmented by AI, represents a cornerstone of personalized nutrition. While offering significant potential for precision and efficacy, advancing these strategies requires addressing challenges such as incomplete AI data, regulatory uncertainties, and the lack of long-term studies. By overcoming these obstacles, clinicians can better meet individual health needs, prevent diseases, and integrate precision nutrition into routine care.

Translational Algorithms for Technological Dietary Quality Assessment Integrating Nutrimetabolic Data with Machine Learning Methods

Recent advances in machine learning technologies and omics methodologies are revolutionizing dietary assessment by integrating phenotypical, clinical, and metabolic biomarkers, which are crucial for personalized precision nutrition. This investigation aims to evaluate the feasibility and efficacy of artificial intelligence tools, particularly machine learning (ML) methods, in analyzing these biomarkers to characterize food and nutrient intake and to predict dietary patterns.

METHODS

We analyzed data from 138 subjects from the European Dietary Deal project through comprehensive examinations, lifestyle questionnaires, and fasting blood samples. Clustering was based on 72 h dietary recall, considering sex, age, and BMI. Exploratory factor analysis (EFA) assigned nomenclature to clusters based on food consumption patterns and nutritional indices from food frequency questionnaires. Elastic net regression identified biomarkers linked to these patterns, helping construct algorithms.

RESULTS

Clustering and EFA identified two dietary patterns linked to biochemical markers, distinguishing pro-Mediterranean (pro-MP) and pro-Western (pro-WP) patterns. Analysis revealed differences between pro-MP and pro-WP clusters, such as vegetables, pulses, cereals, drinks, meats, dairy, fish, and sweets. Markers related to lipid metabolism, liver function, blood coagulation, and metabolic factors were pivotal in discriminating clusters. Three computational algorithms were created to predict the probabilities of being classified into the pro-WP pattern. The first is the main algorithm, followed by a supervised algorithm, which is a simplified version of the main model that focuses on clinically feasible biochemical parameters and practical scientific criteria, demonstrating good predictive capabilities (ROC curve = 0.91, precision-recall curve = 0.80). Lastly, a reduced biochemical-based algorithm is presented, derived from the supervised algorithm.

CONCLUSIONS

This study highlights the potential of biochemical markers in predicting nutritional patterns and the development of algorithms for classifying dietary clusters, advancing dietary intake assessment technologies.

Can mindful eating be a psycho-marker of obesity in bipolar disorder?

Introduction

Background and aim: obesity is a very important problem in individuals with bipolar disorder. The study was aimed to determine the prevalence of obesity in individuals with bipolar disorder and to evaluate the effects of factors affecting eating behavior such as mindful eating, impulsivity and eating disorders on the development of obesity in these individuals. Methods: this study is a cross-sectional study. A total of 109 individuals (52 female; 57 male) with bipolar disorder who were in a euthymic state at the time of the interview and underwent outpatient follow-up, treatment and monitorization, and 109 age- and sex-matched healthy individuals as the control group were included in the study. The Mindful Eating Questionnaire-30 (MEQ-30), Three-Factor Eating Questionnaire (TFEQ-21), Barratt Impulsiveness Scale 11-Short Form (BIS-11-SF), and Eating Attitude Test-26 (EAT-26) were used, and anthropometric measurements (height, bodyweight, etc.) were taken. Results: the obesity rate was 50.4 % among the cases and 24.8 % in the control group. Moreover, disinhibition (3.4 ± 0.93), emotional eating (3.5 ± 1.13), and mindfulness (2.6 ± 0.54) scores of individuals with BD were significantly lower than for healthy individuals (3.7 ± 0.82, 4.0 ± 0.93, 2.8 ± 0.55, respectively). The risk of obesity was 5.19 times higher in cases compared to the age- and gender-matched controls (OR = 5.19, 95 % CI (2.01-13.37), p = 0.001). The risk of obesity was 2.76 times higher in those with low mindful eating level (OR = 2.76, 95 % CI (1.07-5.47), p = 0.014) and 4.29 times higher in those using antipsyhotics/mood stabilizers (OR = 4.29, 95 % CI (1.12-12.24), p < 0.001). Conclusion: A comprehensive education program on mindful eating and healthy eating would be helpful in elucidating the mechanisms of the possible relationships between bipolar disorder-specific risk factors and mindful eating.

Tailoring the Nutritional Composition of Italian Foods to the US Nutrition5k Dataset for Food Image Recognition: Challenges and a Comparative Analysis

BACKGROUND

Training of machine learning algorithms on dish images collected in other countries requires possible sources of systematic discrepancies, including country-specific food composition databases (FCDBs), to be tackled. The US Nutrition5k project provides for ~5000 dish images and related dish- and ingredient-level information on mass, energy, and macronutrients from the US FCDB. The aim of this study is to (1) identify challenges/solutions in linking the nutritional composition of Italian foods with food images from Nutrition5k and (2) assess potential differences in nutrient content estimated across the Italian and US FCDBs and their determinants.

METHODS

After food matching, expert data curation, and handling of missing values, dish-level ingredients from Nutrition5k were integrated with the Italian-FCDB-specific nutritional composition (86 components); dish-specific nutrient content was calculated by summing the corresponding ingredient-specific nutritional values. Measures of agreement/difference were calculated between Italian- and US-FCDB-specific content of energy and macronutrients. Potential determinants of identified differences were investigated with multiple robust regression models.

RESULTS

Dishes showed a median mass of 145 g and included three ingredients in median. Energy, proteins, fats, and carbohydrates showed moderate-to-strong agreement between Italian- and US-FCDB-specific content; carbohydrates showed the worst performance, with the Italian FCDB providing smaller median values (median raw difference between the Italian and US FCDBs: -2.10 g). Regression models on dishes suggested a role for mass, number of ingredients, and presence of recreated recipes, alone or jointly with differential use of raw/cooked ingredients across the two FCDBs.

CONCLUSIONS

In the era of machine learning approaches for food image recognition, manual data curation in the alignment of FCDBs is worth the effort.

The future backbone of nutritional science: integrating public health priorities with system-oriented precision nutrition

Adopting policies that promote health for the entire biosphere (One Health) requires human societies to transition towards a more sustainable food supply as well as to deepen the understanding of the metabolic and health effects of evolving food habits. At the same time, life sciences are experiencing rapid and groundbreaking technological developments, in particular in laboratory analytics and biocomputing, placing nutrition research in an unprecedented position to produce knowledge that can be translated into practice in line with One Health policies. In this dynamic context, nutrition research needs to be strategically organised to respond to these societal expectations. One key element of this strategy is to integrate precision nutrition into epidemiological research. This position article therefore reviews the recent developments in nutrition research and proposes how they could be integrated into cohort studies, with a focus on the Swiss research landscape specifically.

Effect of Oral Nutritional Supplementation on Health-Related Outcomes and Nutritional Biomarkers in Children and Adolescents with Undernutrition: A Systematic Review and Meta-Analysis

This systematic review aims to synthesize scientific evidence on the effects of oral nutritional supplementation (ONS) on health-related outcomes and nutritional biomarkers among children and adolescents with undernutrition. The review protocol was reported following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) guidelines. A comprehensive keyword and reference search was conducted in seven electronic bibliographic databases: PubMed, Academic Search Complete, Academic Search Premier, CINAHL, Global Health, Web of Science, and Scopus. We identified 14 peer-reviewed articles reporting results from 13 unique studies (eight randomized controlled trials, four pre-post studies, and one observational study). Study participants were recruited from 14 countries/regions, with ages ranging from 1 to 14 years. Outcomes of interest include health-related outcomes (acute diseases and infections) and nutritional biomarkers (e.g., serum iron and zinc). Six of the eight studies examining acute diseases/infections and five of the seven examining nutritional biomarkers reported statistically significant improvement in some, but not all, outcomes. A meta-analysis of three studies found that ONS interventions reduce the incidence of upper respiratory tract infection (URTI) by 39% (95% CI, 0.42-0.91) in children at nutritional risk when compared to dietary counseling (DC) alone. This systematic review suggests that ONS interventions can improve certain health-related outcomes and nutritional biomarkers in undernourished children and adolescents. Specifically, the use of ONS significantly reduces the risk of URTI, highlighting its potential to enhance immune function and break the cycle of undernutrition and infection.

Precision or Personalized Nutrition: A Bibliometric Analysis

Food systems face the challenge of maintaining adequate nutrition for all populations. Inter-individual responses to the same diet have made precision or personalized nutrition (PN) an emerging and relevant topic. The aim of this study is to analyze the evolution of the PN field, identifying the principal actors and topics, and providing a comprehensive overview. Therefore, a bibliometric analysis of the scientific research available through the Web of Science (WOS) database was performed, revealing 2148 relevant papers up to June 2024. VOSviewer and the WOS platform were employed for the processing and analysis, and included an evaluation of diverse data such as country, author or most frequent keywords, among others. The analysis revealed a period of exponential growth from 2015 to 2023, with the USA, Spain, and England as the top contributors. The field of "Nutrition and Dietetics" is particularly significant, comprising nearly 33% of the total publications. The most highly cited institutions are the universities of Tufts, College Dublin, and Navarra. The relationship between nutrition, genetics, and omics sciences, along with dietary intervention studies, has been a defining factor in the evolution of PN. In conclusion, PN represents a promising field of research with significant potential for further advancement and growth.

The Future of Obesity Management through Precision Nutrition: Putting the Individual at the Center

PURPOSE OF REVIEW: The prevalence of obesity continues to rise steadily. While obesity management typically relies on dietary and lifestyle modifications, individual responses to these interventions vary widely. Clinical guidelines for overweight and obesity stress the importance of personalized approaches to care. This review aims to underscore the role of precision nutrition in delivering tailored interventions for obesity management. RECENT FINDINGS: Recent technological strides have expanded our ability to detect obesity-related genetic polymorphisms, with machine learning algorithms proving pivotal in analyzing intricate genomic data. Machine learning algorithms can also predict postprandial glucose, triglyceride, and insulin levels, facilitating customized dietary interventions and ultimately leading to successful weight loss. Additionally, given that adherence to dietary recommendations is one of the key predictors of weight loss success, employing more objective methods for dietary assessment and monitoring can enhance sustained long-term compliance. Biomarkers of food intake hold promise for a more objective dietary assessment. Acknowledging the multifaceted nature of obesity, precision nutrition stands poised to transform obesity management by tailoring dietary interventions to individuals' genetic backgrounds, gut microbiota, metabolic profiles, and behavioral patterns. However, there is insufficient evidence demonstrating the superiority of precision nutrition over traditional dietary recommendations. The integration of precision nutrition into routine clinical practice requires further validation through randomized controlled trials and the accumulation of a larger body of evidence to strengthen its foundation.

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.

MicroRNAs and the Mediterranean diet: a nutri-omics perspective for lung cancer

Lung cancer is the deadliest cancer type worldwide with ~ 1.8 million deaths per-year. Smoking accounts for ~ 85% of all cases, with a described joint effect with unhealthy diet in lung cancer risk increase. Public health policies to prevent carcinogens exposure, promote smoking cessation and advocacy for healthy nutrition, are therefore highly recommended. Here we have examined the benefits of the Mediterranean Diet (MedDiet) in protecting against some non-communicable diseases including lung cancer, highlighting the epidemiological and biomolecular aspects of MedDiet anti-inflammatory effect and its interaction with smoking habits closely linked to risk of lung cancer. Considering the high incidence and mortality rates of lung cancer, we discussed also about the global impact that a Planeterranean extension of the benefits of MedDiet could have on controlling lung cancer risk. We also debated the impact of personalized nutrition on lung cancer prevention, considering individual heterogeneity in response to diet plans as well as recent advancements on nutri-omics in lung cancer research, with a specific focus on the role of microRNAs (miRNAs) as a promising nutritional molecular hub for lung cancer prevention. We strongly believe that a deep understanding of the molecular link between food components and genetic/epigenetics factors can expand effective intervention strategies.

Impact of a keto diet on symptoms of Parkinson's disease, biomarkers, depression, anxiety and quality of life: a longitudinal study

Aim: Evidence suggests low-carbohydrate diets (LCHF) may assist in treating neurodegenerative diseases such as Parkinson's disease (PD); however, gaps exist in the literature.Patients & methods: We conducted a small 24-week pilot study to investigate the effects of an LCHF diet on motor and nonmotor symptoms, health biomarkers, anxiety, and depression in seven people with PD. We also captured patient experiences during the process (quality of life [QoL]).Results: Participants reported improved biomarkers, enhanced cognition, mood, motor and nonmotor symptoms, and reduced pain and anxiety. Participants felt improvements enhanced their QoL.Conclusion: We conclude that an LCHF intervention is safe, feasible, and potentially effective in mitigating the symptoms of this disorder. However, more extensive randomized controlled studies are needed to create generalizable recommendations.

Multi Omics Applications in Biological Systems

Traditional methodologies often fall short in addressing the complexity of biological systems. In this regard, system biology omics have brought invaluable tools for conducting comprehensive analysis. Current sequencing capabilities have revolutionized genetics and genomics studies, as well as the characterization of transcriptional profiling and dynamics of several species and sample types. Biological systems experience complex biochemical processes involving thousands of molecules. These processes occur at different levels that can be studied using mass spectrometry-based (MS-based) analysis, enabling high-throughput proteomics, glycoproteomics, glycomics, metabolomics, and lipidomics analysis. Here, we present the most up-to-date techniques utilized in the completion of omics analysis. Additionally, we include some interesting examples of the applicability of multi omics to a variety of biological systems.

Implementation of multiomic mass spectrometry approaches for the evaluation of human health following environmental exposure

Omics analyses collectively refer to the possibility of profiling genetic variants, RNA, epigenetic markers, proteins, lipids, and metabolites. The most common analytical approaches used for detecting molecules present within biofluids related to metabolism are vibrational spectroscopy techniques, represented by infrared, Raman, and nuclear magnetic resonance (NMR) spectroscopies and mass spectrometry (MS). Omics-based assessments utilizing MS are rapidly expanding and being applied to various scientific disciplines and clinical settings. Most of the omics instruments are operated by specialists in dedicated laboratories; however, the development of miniature portable omics has made the technology more available to users for field applications. Variations in molecular information gained from omics approaches are useful for evaluating human health following environmental exposure and the development and progression of numerous diseases. As MS technology develops so do statistical and machine learning methods for the detection of molecular deviations from personalized metabolism, which are correlated to altered health conditions, and they are intended to provide a multi-disciplinary overview for researchers interested in adding multiomic analysis to their current efforts. This includes an introduction to mass spectrometry-based omics technologies, current state-of-the-art capabilities and their respective strengths and limitations for surveying molecular information. Furthermore, we describe how knowledge gained from these assessments can be applied to personalized medicine and diagnostic strategies.

Human Intervention Study: Alkylresorcinol Metabolites as Potential Biomarkers for Grain Intake and the Occurrence of Alkylresorcinols in Commonly Consumed Foods in the German Retail Sector

Grains are one of the primary nutrients and are associated with many health benefits. To reflect the intake of grain-based products, two promising potential biomarkers are alkylresorcinol (AR) metabolites 3,5-dihydroxybenzoic acid (3,5-DHBA) and 3-(3,5-dihydroxyphenyl)-propanoic acid (3,5-DHPPA). The aim of this study was to validate the occurrence of AR in food samples and investigate the suitability of their metabolites as potential biomarkers in human intervention studies. In the first step, the AR content in different grain products from the German retail sector was analyzed by GC-MS. ARs were found in higher concentrations in whole grain products and in moderate contents in refined grains and quinoa. Based on these results, human intervention studies were performed in the next step, and the AR metabolites 3,5-DHBA and 3,5-DHPPA were analyzed by LC-MS/MS in urine samples. The intake of only whole grain products leads to an increasing level of both potential biomarkers, while a refined grain diet shows decreasing levels of the AR metabolites. The excretion of 3,5-DHBA after a whole grain-rich diet differs significantly (p = 0.043) from no grain intake.

Thigh muscle mass evaluated by point-of-care ultrasound is associated with short-term mortality in patients with sepsis in the emergency department

Muscle mass depletion is associated with mortality and morbidity in various conditions including sepsis. However, few studies have evaluated muscle mass using point-of-care ultrasound in patients with sepsis. This study aimed to evaluate the association between thigh muscle mass, evaluated using point-of-care ultrasound with panoramic view in patients with sepsis in the emergency department, and mortality. From March 2021 to October 2022, this prospective observational study used sepsis registry. Adult patients who were diagnosed with sepsis at the emergency department and who underwent point-of-care ultrasounds for lower extremities were included. The thigh muscle mass was evaluated by the cross-sectional area of the quadriceps femoris (CSA-QF) on point-of-care ultrasound using panoramic view. The primary outcome was 28 day mortality. Multivariable Cox proportional hazard model was performed. Of 112 included patients with sepsis, mean CSA-QF was significantly lower in the non-surviving group than surviving group (49.6 [34.3-56.5] vs. 63.2 [46.9-79.6] cm2, p = 0.002). Each cm2 increase of mean CSA-QF was independently associated with decreased 28 day mortality (adjusted hazard ratio 0.961, 95% CI 0.928-0.995, p = 0.026) after adjustment for potential confounders. The result of other measurements of CSA-QF were similar. The muscle mass of the quadriceps femoris evaluated using point-of-care ultrasound with panoramic view was associated with mortality in patients with sepsis. It might be a promising tool for determining risk factors for mortality in sepsis patients in the early stages of emergency department.

Change analysis for intermediate disease markers in nutritional epidemiology: a causal inference perspective

BACKGROUND

Several approaches are commonly used to estimate the effect of diet on changes of various intermediate disease markers in prospective studies, including "change-score analysis", "concurrent change-change analysis" and "lagged change-change analysis". Although empirical evidence suggests that concurrent change-change analysis is most robust, consistent, and biologically plausible, in-depth dissection and comparison of these approaches from a causal inference perspective is lacking. We intend to explicitly elucidate and compare the underlying causal model, causal estimand and interpretation of these approaches, intuitively illustrate it with directed acyclic graph (DAG), and further clarify strengths and limitations of the recommended concurrent change-change analysis through simulations.

METHODS

Causal model and DAG are deployed to clarify the causal estimand and interpretation of each approach theoretically. Monte Carlo simulation is used to explore the performance of distinct approaches under different extents of time-invariant heterogeneity and the performance of concurrent change-change analysis when its causal identification assumptions are violated.

RESULTS

Concurrent change-change analysis targets the contemporaneous effect of exposure on outcome (measured at the same survey wave), which is more relevant and plausible in studying the associations of diet and intermediate biomarkers in prospective studies, while change-score analysis and lagged change-change analysis target the effect of exposure on outcome after one-period timespan (typically several years). Concurrent change-change analysis always yields unbiased estimates even with severe unobserved time-invariant confounding, while the other two approaches are always biased even without time-invariant heterogeneity. However, concurrent change-change analysis produces almost linearly increasing estimation bias with violation of its causal identification assumptions becoming more serious.

CONCLUSIONS

Concurrent change-change analysis might be the most superior method in studying the diet and intermediate biomarkers in prospective studies, which targets the most plausible estimand and circumvents the bias from unobserved individual heterogeneity. Importantly, careful examination of the vital identification assumptions behind it should be underscored before applying this promising method.

Precision Nutrition Unveiled: Gene-Nutrient Interactions, Microbiota Dynamics, and Lifestyle Factors in Obesity Management

BACKGROUND

Obesity is a complex metabolic disorder that is associated with several diseases. Recently, precision nutrition (PN) has emerged as a tailored approach to provide individualised dietary recommendations.

AIM

This review discusses the major intrinsic and extrinsic components considered when applying PN during the management of obesity and common associated chronic conditions.

RESULTS

The review identified three main PN components: gene-nutrient interactions, intestinal microbiota, and lifestyle factors. Genetic makeup significantly contributes to inter-individual variations in dietary behaviours, with advanced genome sequencing and population genetics aiding in detecting gene variants associated with obesity. Additionally, PN-based host-microbiota evaluation emerges as an advanced therapeutic tool, impacting disease control and prevention. The gut microbiome's composition regulates diverse responses to nutritional recommendations. Several studies highlight PN's effectiveness in improving diet quality and enhancing adherence to physical activity among obese patients. PN is a key strategy for addressing obesity-related risk factors, encompassing dietary patterns, body weight, fat, blood lipids, glucose levels, and insulin resistance.

CONCLUSION

PN stands out as a feasible tool for effectively managing obesity, considering its ability to integrate genetic and lifestyle factors. The application of PN-based approaches not only improves current obesity conditions but also holds promise for preventing obesity and its associated complications in the long term.

Metabolome biomarkers linking dietary fibre intake with cardiometabolic effects: results from the Danish Diet, Cancer and Health-Next Generations MAX study

Biomarkers associated with dietary fibre intake, as complements to traditional dietary assessment tools, may improve the understanding of its role in human health. Our aim was to discover metabolite biomarkers related to dietary fibre intake and investigate their association with cardiometabolic risk factors. We used data and samples from the Danish Diet Cancer and Health Next Generation (DCH-NG) MAX-study, a one-year observational study with evaluations at baseline, six and 12 months (n = 624, 55% female, mean age: 43 years, 1353 observations). Direct associations between fibre intake and plasma concentrations of 2,6-dihydroxybenzoic acid (2,6-DHBA) and indolepropionic acid were observed at the three time-points. Both metabolites showed an intraclass-correlation coefficient (ICC) > 0.50 and were associated with the self-reported intake of wholegrain cereals, and of fruits and vegetables, respectively. Other metabolites associated with dietary fibre intake were linolenoyl carnitine, 2-aminophenol, 3,4-DHBA, and proline betaine. Based on the metabolites associated with dietary fibre intake we calculated predicted values of fibre intake using a multivariate, machine-learning algorithm. Metabolomics-based predicted fibre, but not self-reported fibre values, showed negative associations with cardiometabolic risk factors (i.e. high sensitivity C-reactive protein, systolic and diastolic blood pressure, all FDR-adjusted p-values <0.05). Furthermore, different correlations with gut microbiota composition were observed. In conclusion, 2,6-DHBA and indolepropionic acid in plasma may better link dietary fibre intake with its metabolic effects than self-reported values. These metabolites may represent a novel class of biomarkers reflecting both dietary exposure and host and/or gut microbiota characteristics providing a read-out that is differentially related to cardiometabolic risk.

The genomic landscape of chronic obstructive pulmonary disease: Insights from nutrigenomics

Chronic obstructivе pulmonary disеasе (COPD), a rеspiratory disеasе, is influenced by a combination of gеnеtic and еnvironmеntal factors. Thе fiеld of nutrigеnomics, which studiеs thе intеrplay bеtwееn diеt and gеnеs, provides valuable insights into thе gеnomic landscapе of COPD and its implications for production and managеmеnt. This rеviеw providеs a comprеhеnsivе ovеrviеw of thе gеnеtic aspеcts of COPD and thе rolе of nutrigеnomics in advancing our undеrstanding of thе undеrlying mеchanisms. Through studies of gеnomе-widе associations, researchers have identified gеnеtic factors that contribute to suscеptibility to COPD. Thеsе gеnеs arе associatеd with oxidativе strеss, inflammation, and antioxidant dеfеnsе mеchanisms. Nutrigеnomics rеsеarch is currеntly invеstigating how diеtary componеnts interact with gеnеtic variations to modulatе thе dеvеlopmеnt of COPD. Antioxidants, omеga-3 fatty acids and vitamin D havе dеmonstratеd potеntial bеnеfits in rеducing inflammation, improving lung function, and minimizing еxacеrbations in patients with COPD. Therefore, there are sеvеral challеngеs that must be added to the nutrigеnomic rеsеarch. The challenges include thе nееd for largеr clinical trials, adding hеtеrogеnеity and validating biomarkеrs. In the tеrms of futurе dirеctions, prеcision nutrition, gеnе-basеd thеrapiеs, biomarkеr dеvеlopmеnt, intеgration of multi-omics data, systеms biology analysis, longitudinal studiеs, and public hеalth implications arе important arеas to еxplorе. Pеrsonalizеd nutritional intеrvеntions based on an individual's gеnеtic profilе hold grеat promisе for optimizing COPD managеmеnt. In conclusion, nutrigеnomics provides valuable insights into the gеnomic landscapе of COPD and its intеraction with the disease. This knowlеdgе can guidе thе dеvеlopmеnt of pеrsonalizеd diеtary stratеgiеs and gеnе-basеd thеrapiеs for thе prеvеntion and managеmеnt of COPD. Howеvеr, morе rеsеarch is nееdеd to validatе thеsе findings, dеvеlop еffеctivе intеrvеntions, and implеmеnt thеm еffеctivеly in clinical practicе to improvе thе quality of lifе for pеoplе with COPD.

Alterations in anthropometric, inflammatory and mental health parameters during Ramadan intermittent fasting in a group of healthy people: a prospective cohort study

Fasting has been practiced with different time span in different areas of the world and for various reasons. One of the types of fasting regimens is Ramadan intermittent fasting (RIF), which is described as intermittent dry fasting and known as the most commonly practiced form of religious fasting. Different studies have shown its effects on body composition parameters and mental health, fatigue and quality of life (QoL). Elucidating the relationship of RIF on biological parameters would also be of importance to show its mechanism. Therefore, we evaluated several biological mediators related to mental health, such as ß-nerve growth factor (ß-NGF), brain-derived neurotrophic factor (BDNF), glial cell line-derived neurotrophic factor (GDNF), and insulin-like growth factor-1 (IGF-1), interleukin-8 (IL-8), tumor necrosis factor-α (TNF-α), and matrix-metalloproteinase-9 (MMP-9). This study consisted of fasting (FG; n = 25) and non-fasting group (NFG; n = 25). Four different time points were assessed for FG: one week before (T1), mid (T2), last days (T3), and one week after (T4) RIF. T1 and T3 were the assessment time points for NFG. Biological mediators were determined from serum samples by using Human Magnetic Luminex and enzyme-linked immunosorbent assay. Furthermore, we then performed correlation analyses between biological mediators and our previously published clinical parameters including body composition and mental health parameters at all time points. Significant alterations were shown in FG for ß-NGF (T2vsT3, p < 0.05; T2vsT4, p < 0.05), GDNF (T1vsT4, p < 0.05; T2vsT4, p < 0.05), IL-8 (T2vsT3, p < 0.05; T3vsT4, p < 0.05), TNF-α (T1vsT3, p < 0.05; T1vsT4, p < 0.001; T2vsT4, p < 0.001), and MMP-9 (T1vsT4, p < 0.01). There were no statistically significant differences between FG and NFG in all biological mediators at T1 and T3. Correlation analysis showed that MMP-9 levels had negative correlation with body mass index (BMI) at T3. At T3 BDNF levels had negative correlation with Epworth Sleepiness Scale (ESS) as one of measured QoL parameters. ß-NGF, GDNF, TNF-α, and MMP-9 had positive correlation with some of body composition and mental health parameters. Findings demonstrate that RIF altered different biological mediators could give benefit to health. Its benefit is mediated by the alteration of biological mediators.

Wearable biosensors for human health: A bibliometric analysis from 2007 to 2022

Objective

This study aimed to determine the status of scientific production on biosensor usage for human health monitoring.

Methods

We used bibliometrics based on the data and metadata retrieved from the Web of Science between 2007 and 2022. Articles unrelated to health and medicine were excluded. The databases were processed using the VOSviewer software and auxiliary spreadsheets. Data extraction yielded 275 articles published in 161 journals, mainly concentrated on 13 journals and 881 keywords plus.

Results

The keywords plus of high occurrences were estimated at 27, with seven to 30 occurrences. From the 1595 identified authors, 125 were consistently connected in the coauthorship network in the total set and were grouped into nine clusters. Using Lotka's law, we identified 24 prolific authors, and Hirsch index analysis revealed that 45 articles were cited more than 45 times. Crosses were identified between 17 articles in the Hirsch index and 17 prolific authors, highlighting the presence of a large set of prolific authors from various interconnected clusters, a triad, and a solitary prolific author.

Conclusion

An exponential trend was observed in biosensor research for health monitoring, identifying areas of innovation, collaboration, and technological challenges that can guide future research on this topic.

Evaluation of Food Intake Biomarkers for Red Bell Peppers in Human Urine Based on HPLC-MS/MS Analysis

SCOPE

The validation of dietary biomarkers is essential for the use in objective and quantitative assessment of the human dietary intake. In this study, the urinary excretion of previously identified potential biomarkers after intake of red bell peppers is analyzed.

METHODS AND RESULTS

The urine samples obtained after a two-phase dietary intervention study in which 14 volunteers participated are quantitatively analyzed by high-performance liquid chromatography with tandem mass spectrometry (HPLC-MS/MS) after an extensive validation. In the first phase, the volunteers abstain completely from bell peppers and paprika products (control group) and in the second phase, the volunteers consume a defined amount of fresh red bell peppers (case group). After analysis, all potential biomarkers show high dispersions of their concentration, indicating interindividual differences. The glucuronidated apocarotenoid (compound 1), which probably resulted from the main carotenoids of red Capsicum fruits, shows a rapid urinary excretion. The other glucuronidated metabolites (compounds 2-8), described as potential derivatives of capsianosides from Capsicum, show a slightly delayed but longer urinary excretion.

CONCLUSIONS

A correlation between an intake of red bell pepper and the urinary excretion of recently described potential biomarkers is observed. Due to large interindividual differences, it is reasonable to assume that at least the qualitative detection of the consumption of bell peppers and possibly all Capsicum fruits is feasible.

Development of a rapid, sensitive, and selective LC-MS/MS method for quantifying curcumin levels in healthy human urine: Effect of pepper on curcumin bioavailability

Curcumin (CCM), a culinary spice, is widely consumed for its health benefits for managing oxidative and inflammatory conditions, metabolic syndrome, arthritis, and hyperlipidemia. However, due to its extensive metabolism, the oral bioavailability of CCM is very low. In this study, we developed a rapid, sensitive, and selective assay to examine the hypothesis that piperine improves CCM bioavailability after piperine co-ingestion. We developed a selective, sensitive, and robust LC-MS/MS method to quantify CCM in human urine. The method was linear over a concentration range 0.625-40 ng/mL with LLOQ and LLOD of 0.625 ng/mL and 0.312 ng/mL, respectively. Healthy volunteers have consumed test meals of CCM as turmeric powder with and without black pepper with 1 week wash out. Urine samples were collected for 24 hours and analyzed for CCM excretion. Black pepper increased CCM half-life from 2.2 ± 0.79 h (CCM alone) to 4.5 ± 0.80 h (CCM + pepper). The CCM 24-h urinary excreted amount was higher in individuals consuming CCM + pepper (218.14 ± 94.98 μg) than those who received CCM only (49.45 ± 12.94 μg). This preliminary study indicates that piperine significantly increased CCM oral absorption, reduced systemic clearance, and improved bioavailability.

Using Crowdsourced Food Image Data for Assessing Restaurant Nutrition Environment: A Validation Study

Crowdsourced online food images, when combined with food image recognition technologies, have the potential to offer a cost-effective and scalable solution for the assessment of the restaurant nutrition environment. While previous research has explored this approach and validated the accuracy of food image recognition technologies, much remains unknown about the validity of crowdsourced food images as the primary data source for large-scale assessments. In this paper, we collect data from multiple sources and comprehensively examine the validity of using crowdsourced food images for assessing the restaurant nutrition environment in the Greater Hartford region. Our results indicate that while crowdsourced food images are useful in terms of the initial assessment of restaurant nutrition quality and the identification of popular food items, they are subject to selection bias on multiple levels and do not fully represent the restaurant nutrition quality or customers' dietary behaviors. If employed, the food image data must be supplemented with alternative data sources, such as field surveys, store audits, and commercial data, to offer a more representative assessment of the restaurant nutrition environment.

Comparing the web-based and traditional self-reported 24-hour dietary recall data in the PakNutriStudy

BACKGROUND

The flaws in dietary assessment methods can generate misleading information and thus may impact on the interventions planned based on that information. Context specific digitalization of dietary assessment tools is a potential way forward to reduce biases and resources involved in data handling.

METHODS

Two versions of Twenty-Four Hour Recall (24HR) (traditional [24HR Ver-01] and digital [24HR Ver-02]) were tested for data agreement and feasibility by gathering cross sectional paired data on both the versions from 102 participants (18-25 years age). The web based 24HR was setup using the system of Intake24 (New Castle University) with incorporation of South Asian food data base for beverages.

RESULTS

The data sets obtained from 24HR Ver-01 and 24HR Ver-02 on beverage consumption (food items as well as portion sizes) were compared for agreement. The highest percentage of agreement of food item reporting between 24HR Ver-01 and 24HR Ver-01 was during the lunch time. The average kappa value (κ =0.375833) for all the meals indicated a fair agreement betweenVer-01 and 24HR Ver-02 The correlation of portion sizes reported using 24HR Ver-01 and 24 HR Ver-02 was statisticallysignificant for morning snack, lunch and dinner (r = 0.465; r = 0.324; r = 0.407 respectively). According to Bland Altman plot, least agreement between the two versions was found in the portion sizes reported for morning snacks. Data collectors found 24 HR Ver-02 easier in terms of data processing but it was regarded time taking and less convenient by the participants.

CONCLUSION

The Intake 24 (digital version of 24HR) can be a preferred tool of data collection as the data collected through it may reach fairly good levels of accuracy. Future directions for research like conducting a follow up study with cross over design, expanding the study using food items other than beverages, and testing the digital dietary assessment tool against an objective gold standard of dietary intake can be helpful in reaching more conclusive evidence.

Modified Korean MIND Diet: A Nutritional Intervention for Improved Cognitive Function in Elderly Women through Mitochondrial Respiration, Inflammation Suppression, and Amino Acid Metabolism Regulation

SCOPE

Mild cognitive impairment is associated with a high prevalence of dementia. The study examines the benefits of a modified Korean MIND (K-MIND) diet and explores biomarkers using multi-omics analysis.

METHODS AND RESULTS

The K-MIND diet, tailored to the elderly Korean population, includes perilla oil, milk, or fermented milk, and avoids alcohol consumption. As a result, the K-MIND diet significantly improves subjects "orientation to place" in the Korean version of the Mini-Mental State Examination, 2nd edition test. According to multi-omics analysis, the K-MIND diet upregulates genes associated with mitochondrial respiration, including ubiquinone oxidoreductase, cytochrome C oxidase, and ATP synthase, and immune system processes, and downregulates genes related to nuclear factor kappa B activity and inflammatory responses. In addition, K-MIND affects the metabolic pathways of glycine, serine, threonine, tryptophan, and sphingolipids, which are closely linked to cognitive function through synthesis of neurotransmitters and structures of brain cell membranes.

CONCLUSION

The findings imply that the K-MIND diet improves cognitive function by upregulating key genes involved in oxidative phosphorylation and downregulating pro-inflammatory cytokines.

Study protocol: Identification and validation of integrative biomarkers of physical activity level and health in children and adolescents (INTEGRActiv)

Background

Physical activity (PA) provides health benefits across the lifespan and improves many established cardiovascular risk factors that have a significant impact on overall mortality. However, discrepancies between self-reported and device-based measures of PA make it difficult to obtain consistent results regarding PA and its health effects. Moreover, PA may produce different health effects depending on the type, intensity, duration, and frequency of activities and individual factors such as age, sex, body weight, early life conditions/exposures, etc. Appropriate biomarkers relating the degree of PA level with its effects on health, especially in children and adolescents, are required and missing. The main objective of the INTEGRActiv study is to identify novel useful integrative biomarkers of PA and its effects on the body health in children and adolescents, who represent an important target population to address personalized interventions to improve future metabolic health.

Methods/design

The study is structured in two phases. First, biomarkers of PA and health will be identified at baseline in a core cohort of 180 volunteers, distributed into two age groups: prepubertal (n = 90), and postpubertal adolescents (n = 90). Each group will include three subgroups (n = 30) with subjects of normal weight, overweight, and obesity, respectively. Identification of new biomarkers will be achieved by combining physical measures (PA and cardiorespiratory and muscular fitness, anthropometry) and molecular measures (cardiovascular risk factors, endocrine markers, cytokines and circulating miRNA in plasma, gene expression profile in blood cells, and metabolomics profiling in plasma). In the second phase, an educational intervention and its follow-up will be carried out in a subgroup of these subjects (60 volunteers), as a first validation step of the identified biomarkers.

Discussion

The INTEGRActiv study is expected to provide the definition of PA and health-related biomarkers (PA-health biomarkers) in childhood and adolescence. It will allow us to relate biomarkers to factors such as age, sex, body weight, sleep behavior, dietary factors, and pubertal status and to identify how these factors quantitatively affect the biomarkers' responses. Taken together, the INTEGRActiv study approach is expected to help monitor the efficacy of interventions aimed to improve the quality of life of children/adolescents through physical activity.

Clinical Trial Registration

ClinicalTrials.gov, Identifier NCT05907785.

Assessing Repeated Urinary Proline Betaine Measures as a Biomarker of Usual Citrus Intake during Pregnancy: Sources of Within-Person Variation and Correlation with Reported Intake

Proline betaine (Pro-B) has been identified as a biomarker of dietary citrus intake, yet gaps remain in its validation as a quantitative predictor of intake during various physiological states. This study quantified sources of within-individual variation (WIV) in urinary Pro-B concentration during pregnancy and assessed its correlation with the reported usual intake of citrus fruit and juice. Pro-B concentrations were determined by 1H-NMR spectroscopy in spot and 24-h urine specimens (n = 255) collected throughout pregnancy from women participating in the MARBLES cohort study. Adjusted linear or log mixed effects models quantified WIV and tested potential temporal predictors of continuous or elevated Pro-B concentration. Pearson or Spearman correlations assessed the relationship between averaged repeated biomarker measures and usual citrus intake reported by food frequency questionnaires. The proportion of variance in urinary Pro-B attributable to WIV ranged from 0.69 to 0.74 in unadjusted and adjusted models. Citrus season was a significant predictor of Pro-B in most analyses (e.g., adjusted β [95% CI]: 0.52 [0.16, 0.88] for non-normalized Pro-B), while gestational age predicted only non-normalized Pro-B (adjusted β [95% CI]: -0.093 [-0.18, -0.0038]). Moderate correlations (rs of 0.40 to 0.42) were found between reported usual citrus intake and averaged repeated biomarker measurements, which were stronger compared to using a single measurement. Given the high degree of WIV observed in urinary Pro-B, multiple samples per participant are likely needed to assess associations between citrus consumption and health outcomes.

Nutritional redundancy in the human diet and its application in phenotype association studies

Studying human dietary intake may help us identify effective measures to treat or prevent many chronic diseases whose natural histories are influenced by nutritional factors. Here, by examining five cohorts with dietary intake data collected on different time scales, we show that the food intake profile varies substantially across individuals and over time, while the nutritional intake profile appears fairly stable. We refer to this phenomenon as 'nutritional redundancy' and attribute it to the nested structure of the food-nutrient network. This network enables us to quantify the level of nutritional redundancy for each diet assessment of any individual. Interestingly, this nutritional redundancy measure does not strongly correlate with any classical healthy diet scores, but its performance in predicting healthy aging shows comparable strength. Moreover, after adjusting for age, we find that a high nutritional redundancy is associated with lower risks of cardiovascular disease and type 2 diabetes.

Prospective observational studies on nutrition intake and the incidence of cognitive impairment in middle-aged and older adults: A protocol for systematic review and meta-analysis

INTRODUCTION

According to several studies, a specific dietary pattern can reduce the risk of dementia and cognitive impairment. However, the robustness of these results has not been tested. The study intends to investigate the association between nutrition intake and cognitive impairment in middle-aged and older adults (≥45-years) and provide reliable, evidence-based references for healthcare decision-makers, researchers, and policymakers.

REVIEW QUESTION

Are the dietary characteristics of community-dwelling adults (≥45-years) associated with the occurrence of cognitive impairment?

OBJECTIVES

The primary objective of this protocol is to synthesize the longitudinal observational evidence on the relationship between nutrition intake patterns and the incidence of cognitive impairment in middle-aged and older adults (≥45-years), and to provide detailed dietary recommendations for the prevention of cognitive impairment in this population.

METHODS AND ANALYSIS

Cohort studies conducted among adults (≥45-years) will be included. The following electronic databases will be searched for relevant records published by July 2023, with a restriction on language to English: Pubmed, Medline, Embase, Web of science, Cochrane Library. The studies will be selected, the data will be extracted, and the bias risk will be assessed by two independent investigators. The Meta-analysis of Observational Studies in Epidemiology guidelines will be followed to summarize observational studies, and the protocol will adhere to the recommendations from the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols 2015 statement. Endnote X9 will be used to manage data screening. We will use Review Manager 5.4 and Stata 16.0 to conduct data analysis, and a random-effects model will be applied to pool clinically homogenous studies. The results will be presented based on the form of nutrition intake. For assessing publication bias, Egger's test and visual inspection of funnel plots will be utilized.

ETHICS AND DISSEMINATION

As this study does not involve primary data, ethical approval is not required. The final report will be published in a peer-reviewed journal.

PROSPERO REGISTRATION NUMBER

A registration number of DOI 10.17605/OSF.IO/NAKC3 was assigned to it on October 15, 2022 on Prospero.

Metagenome-assembled genomes for biomarkers of bio-functionalities in Laal dahi, an Indian ethnic fermented milk product

Laal dahi is a sweetened and soft pudding-like fermented milk product of the Eastern regions of India, which has not been studied for its microbial community structures and health promoting functionality in terms of 'omics' approaches. We applied metagenomic and metagenomes-assembled genomes (MAGs) tools to decipher the biomarkers for genes encoding for different health promoting functionalities in laal dahi. Abundance of bacterial domains was observed with negligible presence of eukaryotes and viruses. Bacillota was the most abundant phylum with different bacterial species viz., Enterococcus italicus, Lactococcus raffinolactis, Lactobacillus helveticus, Bifidobacterium mongoliense, Hafnia alvei, Lactococcus lactis, Acetobacter okinawensis, Streptococcus thermophilus, Thermus thermophilus, Leuconostoc citreum, Leuconostoc pseudomesenteroides, Acetobacter orientalis, Lactobacillus gallinarum, Lactococcus chungangensis and Lactobacillus delbrueckii. Comparison of laal dahi microbiome with that of similar fermented milk products was also carried out after retrieving the metagenomic datasets from public databases. Significant abundance of Lb. helveticus, E. italicus, Lc. raffinolactis and Lc. lactis in laal dahi. Interestingly, Bifidobacterium mongoliense, Lb. gallinarum, Lc. chungangensis and Acetobacter okinawensis were only detected in laal dahi but Streptococcus infantarius, Lacticaseibacillus rhamnosus and Lb. johnsonii were absent. Reconstruction of putative single environment-specific genomes from metagenomes in addition to subsampling of the abundant species resulted in five high-quality MAGs identified as Lactobacillus delbrueckii, Lactobacillus helveticus, Lactococcus chungangensis, Lactococcus lactis and Streptococcus thermophilus. All MAGs showed the presence of various genes with several putative functions corresponding to different probiotic and prebiotic functions, short-chain fatty acids production, immunomodulation, antitumor genes, essential amino acid and vitamin biosynthesis. Genes for γ-Aminobutyric acid (GABA) production were only detected in MAG of Lactococcus lactis. Gene clusters for secondary metabolites (antimicrobial peptides) were detected in all MAGs except Lc. chungangensis. Additionally, detection of clustered regularly interspaced short palindromic repeats (CRISPR)-associated (Cas) elements was observed only in Lactobacillus delbrueckii and Streptococcus thermophilus. Annotation of several genes with potential health beneficial properties in all five MAGs may support the need to explore the culturability of these MAGs for future use in controlled fermentation of functional dairy products.

Omics biomarkers and an approach for their practical implementation to delineate health status for personalized nutrition strategies

Personalized nutrition (PN) has gained much attention as a tool for empowerment of consumers to promote changes in dietary behavior, optimizing health status and preventing diet related diseases. Generalized implementation of PN faces different obstacles, one of the most relevant being metabolic characterization of the individual. Although omics technologies allow for assessment the dynamics of metabolism with unprecedented detail, its translatability as affordable and simple PN protocols is still difficult due to the complexity of metabolic regulation and to different technical and economical constrains. In this work, we propose a conceptual framework that considers the dysregulation of a few overarching processes, namely Carbohydrate metabolism, lipid metabolism, inflammation, oxidative stress and microbiota-derived metabolites, as the basis of the onset of several non-communicable diseases. These processes can be assessed and characterized by specific sets of proteomic, metabolomic and genetic markers that minimize operational constrains and maximize the information obtained at the individual level. Current machine learning and data analysis methodologies allow the development of algorithms to integrate omics and genetic markers. Reduction of dimensionality of variables facilitates the implementation of omics and genetic information in digital tools. This framework is exemplified by presenting the EU-Funded project PREVENTOMICS as a use case.

Future lines of research on phase angle: Strengths and limitations

Bioelectrical impedance analysis (BIA) is the most widely used technique in body composition analysis. When we focus the use of phase sensitive BIA on its raw parameters Resistance (R), Reactance (Xc) and Phase Angle (PhA), we eliminate the bias of using predictive equations based on reference models. In particular PhA, have demonstrated their prognostic utility in multiple aspects of health and disease. In recent years, as a strong association between prognostic and diagnostic factors has been observed, scientific interest in the utility of PhA has increased. In the different fields of knowledge in biomedical research, there are different ways of assessing the impact of a scientific-technical aspect such as PhA. Single frequency with phase detection bioimpedance analysis (SF-BIA) using a 50 kHz single frequency device and tetrapolar wrist-ankle electrode placement is the most widely used bioimpedance approach for characterization of whole-body composition. However, the incorporation of vector representation of raw bioelectrical parameters and direct mathematical calculations without the need for regression equations for the analysis of body compartments has been one of the most important aspects for the development of research in this area. These results provide new evidence for the validity of phase-sensitive bioelectrical measurements as biomarkers of fluid and nutritional status. To enable the development of clinical research that provides consistent results, it is essential to establish appropriate standardization of PhA measurement techniques. Standardization of test protocols will facilitate the diagnosis and assessment of the risk associated with reduced PhA and the evaluation of changes in response to therapeutic interventions. In this paper, we describe and overview the value of PhA in biomedical research, technical and instrumental aspects of PhA research, analysis of Areas of clinical research (cancer patients, digestive and liver diseases, critical and surgical patients, Respiratory, infectious, and COVID-19, obesity and metabolic diseases, Heart and kidney failure, Malnutrition and sarcopenia), characterisation of the different research outcomes, Morphofunctional assessment in disease-related malnutrition and other metabolic disorders: validation of PhA with reference clinical practice techniques, strengths and limitations. Based on the detailed study of the measurement technique, some of the key issues to be considered in future PhA research. On the other hand, it is important to assess the clinical conditions and the phenotype of the patients, as well as to establish a disease-specific clinical profile. The appropriate selection of the most critical outcomes is another fundamental aspect of research.

The Effect of Dietary Factors on Cancer

The effects of dietary factors on cancer have been widely studied for several decades [...]

KLB and NOX4 expression levels as potential blood-based transcriptional biomarkers of physical activity in children

Insufficient physical activity (PA) in children is considered one of the major contributors to obesity and cardiometabolic complications later in life. Although regular exercise may contribute to disease prevention and health promotion, reliable early biomarkers are required to objectively discern people performing low PA from those who exercise enough. Here, we aimed to identify potential transcript-based biomarkers through the analysis of a whole-genome microarray in peripheral blood cells (PBC) from physically less active (n = 10) comparing with more active (n = 10) children. A set of genes differentially expressed (p < 0.01, Limma test) in less physically active children were identified, including the down-regulation of genes related to cardiometabolic benefits and improved skeletal function (KLB, NOX4, and SYPL2), and the up-regulation of genes whose elevated expression levels are associated with metabolic complications (IRX5, UBD, and MGP). The analysis of the enriched pathways significantly affected by PA levels were those associated with protein catabolism, skeletal morphogenesis, and wound healing, among others, which may suggest a differential impact of low PA on these processes. Microarray analysis comparing children according to their usual PA has revealed potential PBC transcript-based biomarkers that may be useful in early discerning children expending high sedentary time and its associated negative consequences.