Personalized Nutrition and -Omics

Advance computational tools for multiomics data learning

The burgeoning field of bioinformatics has seen a surge in computational tools tailored for omics data analysis driven by the heterogeneous and high-dimensional nature of omics data. In biomedical and plant science research multi-omics data has become pivotal for predictive analytics in the era of big data necessitating sophisticated computational methodologies. This review explores a diverse array of computational approaches which play crucial role in processing, normalizing, integrating, and analyzing omics data. Notable methods such similarity-based methods, network-based approaches, correlation-based methods, Bayesian methods, fusion-based methods and multivariate techniques among others are discussed in detail, each offering unique functionalities to address the complexities of multi-omics data. Furthermore, this review underscores the significance of computational tools in advancing our understanding of data and their transformative impact on research.

Do Personalized Nutrition Interventions Improve Dietary Intake and Risk Factors in Adults With Elevated Cardiovascular Disease Risk Factors? A Systematic Review and Meta-analysis of Randomized Controlled Trials

CONTEXT

Dietary modifications can improve cardiovascular disease (CVD) risk factors. Personalized nutrition (PN) refers to individualized nutrition care based on genetic, phenotypic, medical, behavioral, and/or lifestyle characteristics. PN may be beneficial in improving CVD risk factors, including diet. However, this has not been reviewed previously.

OBJECTIVE

The aim was to evaluate the effectiveness of PN interventions on CVD risk factors and diet in adults at elevated CVD risk.

DATA SOURCES

Six databases were searched for randomized controlled trials published between 2000 and 2023 that tested the impact of PN interventions on CVD risk factors in people at elevated risk.

DATA EXTRACTION

Risk of bias was assessed using the Academy of Nutrition and Dietetics Quality Criteria checklist. Data synthesis of eligible articles included participant characteristics, intervention details, and change in primary CVD risk factor outcomes, including blood pressure (BP), plasma lipids, and CVD risk score, and secondary risk factors, including anthropometric outcomes and diet quality. Random-effects meta-analyses were conducted to explore weighted mean differences (WMDs) in change or final mean values for studies with comparable data (studies with dietary counseling interventions) for outcomes including BP, blood lipids, and anthropometric measurements.

DATA ANALYSIS

Of 7676 identified articles, 16 articles representing 15 studies met the inclusion criteria. Studies included between 40 and 563 participants and reported outcomes for CVD risk factors, including hyperlipidemia (n = 5), elevated BP (n = 3), overweight/obesity (n = 1), and multiple risk factors (n = 6). Risk of bias was low. Results suggested potential benefit of PN on systolic BP (WMD: -1.91; 95% CI: -3.51, -0.31 mmHg) and diastolic BP (WMD: -1.49; 95% CI: -2.39, -0.58 mmHg) and dietary intake in individuals at high CVD risk. Results were inconsistent for plasma lipid and anthropometric outcomes.

CONCLUSION

Results were promising for PN interventions that used dietary counseling on CVD risk factors in at-risk individuals. However, further evidence for other personalization methods is required, including improving methodological quality and longer study duration in future PN interventions.

SYSTEMATIC REVIEW REGISTRATION

OpenScience Framework (https://doi.org/10.17605/OSF.IO/SHVWP).

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.

Comparative Metabolomic Profiling of Eggs from 3 Diverse Chicken Breeds Using GC-MS Analysis

Eggs, as a crucial source of essential nutrients for consumers, possess a high nutritional value owing to their rich composition of vital components essential for human health. While previous research has extensively investigated genetic factors influencing egg quality, there has been a limited focus on exploring the impact of specific strains, particularly within the African context, on the polar metabolite profile of eggs. In this extensive study, we conducted an untargeted analysis of the chemical composition of both albumen and yolk from 3 distinct strains of hens-Blue Holland, Sasso, and Wassache-raised under identical feeding conditions. Utilizing gas chromatography coupled with mass spectrometry (GC-MS), we meticulously examined amino acids, carbohydrates, fatty acids, and other small polar metabolites. In total, 38 and 44 metabolites were identified in the whites and yolk, respectively, of the 3 studied strains. The application of chemometric analysis revealed notable differences in metabolite profiles with 8 relevant metabolites in each egg part. These metabolites include amino acids (N-α-Acetyl-L-lysine, lysine, L-valine, L-Tryptophan), fatty acids (oleic acid, linoleic acid, palmitic acid and stearic acid), and carbohydrates (d-glucose, maltose, lactose). These findings shed light on strain-specific metabolic nuances within eggs, emphasizing potential nutritional implications. The ensuing discussion delves into the diverse metabolic pathways influenced by the identified metabolites, offering insights that contribute to a broader understanding of egg composition and its significance in tailoring nutritional strategies for diverse populations.

Genetics, Nutrition, and Health: A New Frontier in Disease Prevention

The field of nutrition research has traditionally focused on the effects of macronutrients and micronutrients on the body. However, it has become evident that individuals have unique genetic makeups that influence their response to food. Nutritional genomics, which includes nutrigenetics and nutrigenomics, explores the interaction between an individual's genetic makeup, diet, and health outcomes. Nutrigenetics studies the impact of genetic variation on an individual's response to dietary nutrients, while nutrigenomics investigates how dietary components affect gene regulation and expression. These disciplines seek to understand the impact of diet on the genome, transcriptome, proteome, and metabolome. It provides insights into the mechanisms underlying the effect of diet on gene expression. Nutrients can cause the modification of genetic expression through epigenetic changes, such as DNA methylation and histone modifications. The aim of nutrigenomics is to create personalized diets based on the unique metabolic profile of an individual, gut microbiome, and genetic makeup to prevent diseases and promote health. Nutrigenomics has the potential to revolutionize the field of nutrition by combining the practicality of personalized nutrition with knowledge of genetic factors underlying health and disease. Thus, nutrigenomics offers a promising approach to improving health outcomes (in terms of disease prevention) through personalized nutrition strategies based on an individual's genetic and metabolic characteristics.

Economic Evaluation of a Personalized Nutrition Plan Based on Omic Sciences Versus a General Nutrition Plan in Adults with Overweight and Obesity: A Modeling Study Based on Trial Data in Denmark

BACKGROUND

Since there is no diet that is perfect for everyone, personalized nutrition approaches are gaining popularity to achieve goals such as the prevention of obesity-related diseases. However, appropriate choices about funding and encouraging personalized nutrition approaches should be based on sufficient evidence of their effectiveness and cost-effectiveness. In this study, we assessed whether a newly developed personalized plan (PP) could be cost-effective relative to a non-personalized plan in Denmark.

METHODS

Results of a 10-week randomized controlled trial were combined with a validated obesity economic model to estimate lifetime cost-effectiveness. In the trial, the intervention group (PP) received personalized home-delivered meals based on metabolic biomarkers and personalized behavioral change messages. In the control group these meals and messages were not personalized. Effects were measured in body mass index (BMI) and quality of life (EQ-5D-5L). Costs [euros (€), 2020] were considered from a societal perspective. Lifetime cost-effectiveness was assessed using a multi-state Markov model. Univariate, probabilistic sensitivity, and scenario analyses were performed.

RESULTS

In the trial, no significant differences were found in the effectiveness of PP compared with control, but wide confidence intervals (CIs) were seen [e.g., BMI (-0.07, 95% CI -0.51, 0.38)]. Lifetime estimates showed that PP increased costs (€520,102 versus €518,366, difference: €1736) and quality-adjusted life years (QALYs) (15.117 versus 15.106, difference: 0.011); the incremental cost-utility ratio (ICUR) was therefore high (€158,798 to gain one QALY). However, a 20% decrease in intervention costs would reduce the ICUR (€23,668 per QALY gained) below an unofficial gross domestic product (GDP)-based willingness-to-pay threshold (€47,817 per QALY gained).

CONCLUSION

On the basis of the willingness-to-pay threshold and the non-significant differences in short-term effectiveness, PP may not be cost-effective. However, scaling up the intervention would reduce the intervention costs. Future studies should be larger and/or longer to reduce uncertainty about short-term effectiveness.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov registry (NCT04590989).

Biomolecular Actions by Intestinal Endotoxemia in Metabolic Syndrome

Metabolic syndrome (MetS) is a combination of metabolic disorders that concurrently act as factors promoting systemic pathologies such as atherosclerosis or diabetes mellitus. It is now believed to encompass six main interacting conditions: visceral fat, imbalance of lipids (dyslipidemia), hypertension, insulin resistance (with or without impairing both glucose tolerance and fasting blood sugar), and inflammation. In the last 10 years, there has been a progressive interest through scientific research investigations conducted in the field of metabolomics, confirming a trend to evaluate the role of the metabolome, particularly the intestinal one. The intestinal microbiota (IM) is crucial due to the diversity of microorganisms and their abundance. Consequently, IM dysbiosis and its derivate toxic metabolites have been correlated with MetS. By intervening in these two factors (dysbiosis and consequently the metabolome), we can potentially prevent or slow down the clinical effects of the MetS process. This, in turn, may mitigate dysregulations of intestinal microbiota axes, such as the lung axis, thereby potentially alleviating the negative impact on respiratory pathology, such as the chronic obstructive pulmonary disease. However, the biomolecular mechanisms through which the IM influences the host's metabolism via a dysbiosis metabolome in both normal and pathological conditions are still unclear. In this study, we seek to provide a description of the knowledge to date of the IM and its metabolome and the factors that influence it. Furthermore, we analyze the interactions between the functions of the IM and the pathophysiology of major metabolic diseases via local and systemic metabolome's relate endotoxemia.

Inferring personal intake recommendations of phosphorous and potassium for end-stage renal failure patients by simulating with Bayesian hierarchical multivariate model

Most end-stage renal disease (ESRD) patients face a risk of malnutrition, partly due to dietary restrictions on phosphorous and, in some cases, potassium intake. These restrictions aim to regulate plasma phosphate and potassium concentrations and prevent the adverse effects of hyperphosphatemia or hyperkalemia. However, individual responses to nutrition are known to vary, highlighting the need for personalized recommendations rather than relying solely on general guidelines. In this study, our objective was to develop a Bayesian hierarchical multivariate model that estimates the individual effects of nutrients on plasma concentrations and to present a recommendation algorithm that utilizes this model to infer personalized dietary intakes capable of achieving normal ranges for all considered concentrations. Considering the limited research on the reactions of ESRD patients, we collected dietary intake data and corresponding laboratory analyses from a cohort of 37 patients. The collected data were used to estimate the common hierarchical model, from which personalized models of the patients' diets and individual reactions were extracted. The application of our recommendation algorithm revealed substantial variations in phosphorus and potassium intakes recommended for each patient. These personalized recommendations deviate from the general guidelines, suggesting that a notably richer diet may be proposed for certain patients to mitigate the risk of malnutrition. Furthermore, all the participants underwent either hospital, home, or peritoneal dialysis treatments. We explored the impact of treatment type on nutritional reactions by incorporating it as a nested level in the hierarchical model. Remarkably, this incorporation improved the fit of the nutritional effect model by a notable reduction in the normalized root mean square error (NRMSE) from 0.078 to 0.003. These findings highlight the potential for personalized dietary modifications to optimize nutritional status, enhance patient outcomes, and mitigate the risk of malnutrition in the ESRD population.

Current insights into genome-based personalized nutrition technology: a patent review

Unlike general nutritional ranges that meet the nutritional needs essential for maintaining the life of an entire population, personalized nutrition is characterised by maintaining health through providing customized nutrition according to individuals' lifestyles or genetic characteristics. The development of technology and services for personalized nutrition is increasing, owing to the acquisition of knowledge about the differences in nutritional requirements according to the diversity of individuals and an increase in health interest. Regarding genetics, technology is being developed to distinguish the various characteristics of individuals and provide customized nutrition. Therefore, to understand the current state of personalized nutrition technology, understanding genomics is necessary to acquire information on nutrition research based on genomics. We reviewed patents related to personalized nutrition-targeting genomics and examined their mechanisms of action. Using the patent database, we searched 694 patents on nutritional genomics and extracted 561 highly relevant valid data points. Furthermore, an in-depth review was conducted by selecting core patents related to genome-based personalized nutrition technology. A marked increase was observed in personalized nutrition technologies using methods such as genetic scoring and disease-specific dietary recommendations.

Triangulating nutrigenomics, metabolomics and microbiomics toward personalized nutrition and healthy living

The unique physiological and genetic characteristics of individuals influence their reactions to different dietary constituents and nutrients. This notion is the foundation of personalized nutrition. The field of nutrigenetics has witnessed significant progress in understanding the impact of genetic variants on macronutrient and micronutrient levels and the individual's responsiveness to dietary intake. These variants hold significant value in facilitating the development of personalized nutritional interventions, thereby enabling the effective translation from conventional dietary guidelines to genome-guided nutrition. Nevertheless, certain obstacles could impede the extensive implementation of individualized nutrition, which is still in its infancy, such as the polygenic nature of nutrition-related pathologies. Consequently, many disorders are susceptible to the collective influence of multiple genes and environmental interplay, wherein each gene exerts a moderate to modest effect. Furthermore, it is widely accepted that diseases emerge because of the intricate interplay between genetic predisposition and external environmental influences. In the context of this specific paradigm, the utilization of advanced "omic" technologies, including epigenomics, transcriptomics, proteomics, metabolomics, and microbiome analysis, in conjunction with comprehensive phenotyping, has the potential to unveil hitherto undisclosed hereditary elements and interactions between genes and the environment. This review aims to provide up-to-date information regarding the fundamentals of personalized nutrition, specifically emphasizing the complex triangulation interplay among microbiota, dietary metabolites, and genes. Furthermore, it highlights the intestinal microbiota's unique makeup, its influence on nutrigenomics, and the tailoring of dietary suggestions. Finally, this article provides an overview of genotyping versus microbiomics, focusing on investigating the potential applications of this knowledge in the context of tailored dietary plans that aim to improve human well-being and overall health.

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.

Lipidomics in nutrition research

PURPOSE OF REVIEW

This review focuses on the recent findings from lipidomics studies as related to nutrition and health research.

RECENT FINDINGS

Several lipidomics studies have investigated malnutrition, including both under- and overnutrition. Focus has been both on the early-life nutrition as well as on the impact of overfeeding later in life. Multiple studies have investigated the impact of different macronutrients in lipidome on human health, demonstrating that overfeeding with saturated fat is metabolically more harmful than overfeeding with polyunsaturated fat or carbohydrate-rich food. Diet rich in saturated fat increases the lipotoxic lipids, such as ceramides and saturated fatty-acyl-containing triacylglycerols, increasing also the low-density lipoprotein aggregation rate. In contrast, diet rich in polyunsaturated fatty acids, such as n-3 fatty acids, decreases the triacylglycerol levels, although some individuals are poor responders to n-3 supplementation.

SUMMARY

The results highlight the benefits of lipidomics in clinical nutrition research, also providing an opportunity for personalized nutrition. An area of increasing interest is the interplay of diet, gut microbiome, and metabolome, and how they together impact individuals' responses to nutritional challenges.

The fourth industrial revolution in the food industry-part II: Emerging food trends

The food industry has recently been under unprecedented pressure due to major global challenges, such as climate change, exponential increase in world population and urbanization, and the worldwide spread of new diseases and pandemics, such as the COVID-19. The fourth industrial revolution (Industry 4.0) has been gaining momentum since 2015 and has revolutionized the way in which food is produced, transported, stored, perceived, and consumed worldwide, leading to the emergence of new food trends. After reviewing Industry 4.0 technologies (e.g. artificial intelligence, smart sensors, robotics, blockchain, and the Internet of Things) in Part I of this work (Hassoun, Aït-Kaddour, et al. 2022. The fourth industrial revolution in the food industry-Part I: Industry 4.0 technologies. Critical Reviews in Food Science and Nutrition, 1-17.), this complimentary review will focus on emerging food trends (such as fortified and functional foods, additive manufacturing technologies, cultured meat, precision fermentation, and personalized food) and their connection with Industry 4.0 innovations. Implementation of new food trends has been associated with recent advances in Industry 4.0 technologies, enabling a range of new possibilities. The results show several positive food trends that reflect increased awareness of food chain actors of the food-related health and environmental impacts of food systems. Emergence of other food trends and higher consumer interest and engagement in the transition toward sustainable food development and innovative green strategies are expected in the future.

Metabolomics based inferences to unravel phenolic compound diversity in cereals and its implications for human gut health

Background

Scope and approach

Key findings and conclusion

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Phenolic compounds are critical in avoiding metabolic disorders associated with oxidative stress.

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Breeding cereal crops to enrich phenolic compounds in grains contributes to personalized nutrition.

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A diet rich in cereal phenolics likely to increase human gut health, thereby lowering the risk of non-communicable illness.

Sorghum polyphenols: plant stress, human health benefits, and industrial applications

MAIN CONCLUSION

Various phenolic compounds of sorghum are effective in the management of abiotic stress (salt, nutrients) and biotic stress (caused by birds, fungi and aphids). The health and industrial application of phenolics is mainly contributed by inherent antioxidant and nutraceutical potential. In a natural environment, plant growth is affected by various biotic and abiotic stresses. In every ecosystem, the presence of a wide range of harmful biological agents (bacteria, fungi, nematodes, mites, and insects) and undesirable environmental factors (drought, salinity, heat, excessive or low rainfall, etc.) may cause a heavy loss in crop productivity. Being sessile during evolution, plants have evolved multiple defense mechanisms against various types of microbial pathogens and environmental stresses. A plant's natural defense system produces some compounds named secondary metabolites, which include phenolics, terpenes, and nitrogen. The phenolic profile of grain sorghum, the least utilized staple crop, is unique, more diverse, and more abundant than in any other common cereal grain. It mainly contains phenolic acids, 3-deoxyanthocyanidins and condensed tannins. Sorghum polyphenols play a major role in plant defense against biotic and abiotic stresses and have many additional health benefits along with various industrial applications. The objective of this review is to discuss the phenolic compounds derived from grain sorghum and describe their role in plant defense, human health, and industrial applications.

Development of Personalized Nutrition: Applications in Lactose Intolerance Diagnosis and Management

Recent discoveries in the “omics” field and the growing focus on preventive health have opened new avenues for personalized nutrition (PN), which is becoming an important theme in the strategic plans of organizations that are active in healthcare, food, and nutrition research. PN holds great potential for individual health optimization, disease management, public health interventions, and product innovation. However, there are still multiple challenges to overcome before PN can be truly embraced by the public and healthcare stakeholders. The diagnosis and management of lactose intolerance (LI), a common condition with a strong inter-individual component, is explored as an interesting example for the potential role of these technologies and the challenges of PN. From the development of genetic and metabolomic LI diagnostic tests that can be carried out in the home, to advances in the understanding of LI pathology and individualized treatment optimization, PN in LI care has shown substantial progress. However, there are still many research gaps to address, including the understanding of epigenetic regulation of lactase expression and how lactose is metabolized by the gut microbiota, in order to achieve better LI detection and effective therapeutic interventions to reverse the potential health consequences of LI.