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Personalized nutrition holds tremendous potential to improve human health. Despite exponential growth, the field has yet to be clearly delineated and a consensus definition of the term “personalized nutrition” (PN) has not been developed. Defining and delineating the field will foster standardization and scalability in research, data, training, pro...
Contexts in source publication
Context 1
... and more robust data can lead to more targeted recommendations and interventions (Figure 2). Ã Results can be achieved to enhance quality of life and health outcomes with protocols developed based on standard nutrition intakes and assessments. ...
Context 2
... "omics sciences" -nutritional genomics, epigenomics, transcriptomics, metabolomics, proteomics, microbiomics, and others -inform the elements of PN: PN research, PN education and PN practice. PN considers omics analyses that identify relevant molecules (metabolites, proteins, microbes, genes) in conjunction with analyses of body system function, nutritional, and environmental inputs, allowing for a more comprehensive understanding of an individual's health circumstances and needs (10, 41, 42). Bland, Minich, and Eck describe how these omics sciences and technologies inform personalized practice by allowing PN practitioners to evaluate, track and map complex gene expression, proteins, and metabolites noting that, while promising, our ability to translate omics data into relevant, personalized guidance and clinical interventions is still nascent and both the data and any resulting recommendations require scrutiny (10). ...
Citations
... Clinical practice guidelines for overweight and obesity management highlight the importance of customized interventions and patientcentered care [2••]. Precision nutrition aims to personalize dietary recommendations based not only on phenotype but also on genotype or additional molecular factors such as gene expression, microbiome, proteome, and metabolome [3][4][5]. This novel approach can be considered to occur at three levels; Level 1 is the traditional diet based on general guidelines for populations by age, sex, and social determinants, Level 2 adds in phenotypic information about the individual's current nutritional status (e.g. ...
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.
Summary
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.
... Проблема повышения культуры питания и качества пищевых продуктов является актуальной для всех стран мира [1][2][3][4][5][6][7]. Корреляция между качеством пищевой продукции и качеством жизни населения находит подтверждение в работах ученых повсеместно [8][9][10][11]. Актуальным направлением является создание безопасных и качественных разработок на основе продуктов массового потребления, таких как продукты переработки зерна, в том числе смеси для домашнего хлебопечения и приготовления мучных кондитерских изделий [12,13]. Качеству таких мучных смесей стоит уделить пристальное внимание. ...
The food industry is currently demonstrating a tendency to substitute traditional high-humidity raw materials with their dry analogues. This research introduces new designs of vertical vibrating mixers that could preprogram flour mix quality. The vertical continuous vibration mixers designed for granular materials showed a good potential for a wider scope of application. The experiment involved high-quality wheat flour, sugar, salt, egg powder, and powdered milk, as well as three vertical mixers, i.e., a lifting mixer, a flow mixer, and a cascade mixer. Wheat flour entered the working body of the mixer and came into a stable vibration-boiling state in layers of ≤ 35 mm with a vibration amplitude of 4.5 mm and a frequency of ≥ 20 Hz. The speed rate of the flour increased together with the oscillation frequency of the working body and the size of the perforation area but went down as the layer grew wider. The efficiency increased following the increase in the perforation area on the spiral surface and depended on the maximal thickness of the dough layer. The flow vibrating mixer proved to be the most effective one. The frequency of pulse feeding of ingredients into the mixer was ≤ 50% (Vc ≤ 14.5%) to obtain flour mixes of satisfactory quality while good-quality mixes required 25% average time the particles spent in the mixer (Vc ≤ 6%). The results obtained can be used to design technological lines for flour mix production.
... level with a person's genotype, lifestyle, health status, preferences, and physiological status, a novel platform was developed and integrated into third-party applications. This integration resulted in three PREVENTOMICS interventions (9), which included the following: [1] integration of the platform for personalized food delivery, [2] integration of the platform at the retailer level for personalized recommendations when shopping, and [3] integration of the platform with a software to support healthcare professionals with formulating personalized dietary plans for consumers (10). ...
... For example, the ISPOR Value Flower, which offers a broader perspective on factors contributing to value in healthcare, was not chosen because it predominantly centers on the concept and measurement of value rather than on the process and execution of HTA (23). The methodological framework of the HTA Core Model includes three components: [1] an HTA ontology including standardized questions (i.e., assessment elements) organized within a framework featuring nine domains that encompass all aspects that may be relevant for HTA and thereby value assessment, [2] methodological guidance, and [3] a common reporting structure. We used the first two components of the framework wherever possible. ...
... A summary of domain-specific methods is given below. In general, information for the different domains was gathered via [1] different statistical analyses (i.e., analyses of health outcomes and questionnaires) and modeling studies (i.e., cost-effectiveness modeling and choice modeling); [2] questions asked via email to partners of the PREVENTOMICS project, who are experts in this field; or [3] other (un)published materials. Published materials included literature published in scientific journals, PREVENTOMICS blog posts, and presentations. ...
Objectives
Poor nutrition links to chronic diseases, emphasizing the need for optimized diets. The EU-funded project PREVENTOMICS, introduced personalized nutrition to address this. This study aims to perform a health technology assessment (HTA) comparing personalized nutrition interventions developed through this project, with non-personalized nutrition interventions (control) for people with normal weight, overweight, or obesity. The goal is to support decisions about further development and implementation of personalized nutrition.
Methods
The PREVENTOMICS interventions were evaluated using the European Network for HTA Core Model, which includes a methodological framework that encompasses different domains for value assessment. Information was gathered via [1] different statistical analyses and modeling studies, [2] questions asked of project partners and, [3] other (un)published materials.
Results
Clinical trials of PREVENTOMICS interventions demonstrated different body mass index changes compared to control; differences ranged from −0.80 to 0.20 kg/m ² . Long-term outcome predictions showed generally improved health outcomes for the interventions; some appeared cost-effective (e.g., interventions in UK). Ethical concerns around health inequality and the lack of specific legal regulations for personalized nutrition interventions were identified. Choice modeling studies indicated openness to personalized nutrition interventions; decisions were primarily affected by intervention’s price.
Conclusions
PREVENTOMICS clinical trials have shown promising effectiveness with no major safety concerns, although uncertainties about effectiveness exist due to small samples (n=60–264) and short follow-ups (10–16 weeks). Larger, longer trials are needed for robust evidence before implementation could be considered. Among other considerations, developers should explore financing options and collaborate with policymakers to prevent exclusion of specific groups due to information shortages.
... Despite the therapeutic potential of diet and its involvement in the inflammation process of autoimmune diseases, there is currently no consensus about specific dietary recommendations for the attenuation of clinical manifestation in SLE patients. Precision nutrition is an important part of precision medicine that considers genetic and epigenetic information and environmental conditions [50] and drives nutrition strategies for disease prevention, management, and treatment focused on optimizing health [89]. The primary goal of precision nutrition is to use dietary interventions to preserve or ameliorate health and wellbeing by considering genetic and epigenetic variability [90,91]. ...
Background: The pathoetiology of systemic lupus erythematosus (SLE) involves a multifactorial interaction consisting of various genetic, epigenetic and environmental factors. Considering epigenetic characteristics, notable alterations in DNA methylation, particularly hypomethylation in immune-related pathways, such as T cell receptor have been observed. In turn, these alterations are associated with the overexpression of genes related to autoimmunity and a loss of immunological self-tolerance. Furthermore, DNA hypomethylation levels in SLE may contribute to disease progression and also impact disease activity and clinical manifestations. Summary: It is well-established that nutritional epigenetics elucidates the role of nutrition and dietary factors on the interactions of metabolic systems with the molecules that bind to DNA, regulating gene expression. Specific nutritional interventions may reverse initial epigenetic patterns, thereby significantly impacting the chronic disease´s treatment and prognostic. In fact, dietary nutrients and bioactive food compounds may influence DNA methylation patterns by inhibiting enzymes related to DNA methylation reactions or by altering the availability of different substrates involved in DNA methylation process (e.g methyl-donor nutrients). Key Messages: The knowledge of how diet plays a role in changing DNA methylation patterns in SLE is in the early stages. While a few studies in the literature have assessed the effects of nutrient intake, supplementation, or treatment on DNA methylation levels and have demonstrated their relevance, further research is imperative to deepen our comprehension of the interactions between epigenetics and nutrients, which is vital for the development of novel precision nutrition approaches.
... 9,11 Personalized nutrition interventions are targeted nutritional advice, products, or services according to individual characteristics. 12,13 Personalizing can also ameliorate the effects of certain standardized interventions by counteracting the individual's high variability in responses to nutrition interventions. 14,15 A major component of any personalized nutrition intervention lies not only in the content but also in the manner of delivery, by tailoring information to each affected individual based on their feedback to ensure a "better fit." 16 However, the traditional face-to-face method is very laborintensive, poses transportation challenges, is time-consuming, and restricts to a large population. ...
... Nutrition Care Model 13 and Behaviour Change Wheel. 20 The Personalised Nutrition Care model includes four stage cyclic processes of assessment, analysis, implementation, and evaluation. ...
... 20 The Personalised Nutrition Care model includes four stage cyclic processes of assessment, analysis, implementation, and evaluation. 13 The Behaviour Change Wheel suggests an individual's capability and opportunity to increase motivation to promote healthy dietary behavior 20 through behavior change techniques. 21 The unique function of technology platforms, including a website, mobile applications (apps), short message service (SMS), videoconference, email, social media, or wearable devices, for delivering personalized nutrition advice and/or feedback through various behavior change techniques. ...
The prevalence of overweight and obesity has continued to increase globally, and one-size-fits-all dietary recommendations may not be suitable for different individual characteristics. A personalized nutrition intervention may be a potential solution. This review aims to evaluate the effects of the technology-delivered personalized nutrition intervention on energy, fat, vegetable, and fruit intakes among adults with overweight and obesity. A three-step comprehensive search strategy was performed from 10 databases and seven clinical registries in published and unpublished trials. A total of 46 randomized controlled trials (RCTs) involving 19,670 adults with overweight and obesity from 14 countries are included. Subgroup and meta-regression analyses were conducted. Meta-analyses showed a reduction of energy intake (−128.05, 95% CI: −197.08, −59.01) and fat intake (−1.81% energy/days, 95% CI: −3.38, −0.24, and −0.19 scores, 95% CI: −0.40, 0.02) in the intervention compared with the comparator. Significant improvements in vegetable and fruit intakes with 0.12–0.15 servings/day were observed in the intervention. Combined one- and two-way interactions had a greater effect on energy intake reduction compared with their counterparts. Meta-regression analyses revealed that no significant covariates were found. Given that the certainty of the evidence was rated as low or very low, further well-designed RCTs with long-term follow-up are warranted.
... In addition, metabolomics analysis allows us to identify galactitol and galactonate, two metabolites produced by hepatic galactose metabolism, whose serum and urine postprandial levels increase in LP, but not in LNP, subjects who ingested lactose, being proposed as novel and non-invasive lactose digestion test for LI screening [140]. Therefore, metabolomics help us to analyze the effect of single nutrients, and their metabolic products, on individual's health, leading to comprehend how the same foods are metabolized differently by different individuals in healthy or unhealthy conditions, such as LI, and so to plan a personalized nutrition or PN program [141]. ...
Cow’s milk (CM) is a healthy food consumed worldwide by individuals of all ages. Unfortunately, “lactase-deficient” individuals cannot digest milk’s main carbohydrate, lactose, depriving themselves of highly beneficial milk proteins like casein, lactoalbumin, and lactoglobulin due to lactose intolerance (LI), while other individuals develop allergies specifically against these proteins (CMPA). The management of these conditions differs, and an inappropriate diagnosis or treatment may have significant implications for the patients, especially if they are infants or very young children, resulting in unnecessary dietary restrictions or avoidable adverse reactions. Omics technologies play a pivotal role in elucidating the intricate interactions between nutrients and the human body, spanning from genetic factors to the microbiota profile and metabolites. This comprehensive approach enables the precise delineation and identification of distinct cohorts of individuals with specific dietary requirements, so that tailored nutrition strategies can be developed. This is what is called personalized nutrition or precision nutrition (PN), the area of nutrition that focuses on the effects of nutrients on the genome, proteome, and metabolome, promoting well-being and health, preventing diseases, reducing chronic disease incidence, and increasing life expectancy. Here, we report the opinion of the scientific community proposing to replace the “one size fits all” approach with tailor-made nutrition programs, designed by integrating nutrigenomic data together with clinical parameters and microbiota profiles, taking into account the individual lactose tolerance threshold and needs in terms of specific nutrients intake. This customized approach could help LI patients to improve their quality of life, overcoming depression or anxiety often resulting from the individual perception of this condition as different from a normal state.
... However, this approach often ignores differences between individuals in terms of dietary needs. Taking these differences into account opens the possibility of achieving better health outcomes in the general population [10][11][12]. ...
The aim of this research was to select apple varieties suitable for allergy sufferers and diabetics. We first conducted a comprehensive analysis of several apple varieties. The total polyphenol content, sugar content, acidity, and antioxidant activity of the apple fruit juices were determined using spectrophotometric techniques. We also measured the amounts of polyphenols in the apple skins and their antioxidant potential, as well as the allergenic content in the apple juices. The strength of sensitization was assessed using the ELISA method. The lowest amounts of Bet v 1 homologues were found in the varieties Kosztela (4.21 ± 0.71 µg/g), Koksa Pomarańczowa (4.24 ± 0.08 µg/g), and Reneta z Brownlee (4.86 ± 0.18 µg/g). Low values for profilin were observed for Renet Harbert (1.74 ± 0.22 ng/g) and Schieblers Taubenapfel (2.26 ± 0.12 ng/g). The highest values for profilins and Bet v 1 homologues were found in the Złotka Kwidzyńska variety (12.40 µg/g), followed by Malinowa Oberlandzka (9.86 µg/g) and Jakub Lebel (8.87 µg/g). The varieties richest in profilin were Reneta Blenheimska (8.81 ng/g), Szara Reneta (7.88 ng/g), Pepina Ribston (7.67 ng/g), and Reneta z Brownlee (7 .63 ng/g). Given their minimal content of both profilins and Bet v 1 homologues, Koksa Pomarańczowa (4.24 ± 0.08 µg/g Bet v 1 and 4.49 ± 0.82 ng/g profilins) and Książę Albrecht Pruski (5.57 µg/g Bet v 1 and 3.34 ng/g profilins) were identified as suitable for people with allergies. For diabetics, the most suitable apple variety was found to be Jakub Lebel, providing large doses of antioxidants and polyphenols (41.1 ± 2.0 and 5.16 ± 0.42, respectively) and a relatively low sugar content (9.06). Similar results were measured for Kingfish, with 10.2 sugars, 5.68 ± 0.49 antioxi-dants, and 46.2 ± 1.5 polyphenols. The Galowany Pipping variety was found to have a low sugar content (9.71), corresponding to a perceived sweetness of 2.5. Prince Albert of Prussia apples had high antioxidant potential (5.70 ± 0.77) and a low sugar content (11.09). The James Grieve apple variety provided a high polyphenol content of 63.3 ± 1.1 with a high antioxidant level of 5.34 ± 0.45. Grochówka offers a combination of a high polyphenol content (48.6 ± 1.9), a high level of antiox-idant protection (5.50 ± 0.34), and a very low perceived sweetness (from 3.0).
... In addition, metabolomics analysis allows us to identify galactitol and galactonate, two metabolites produced by hepatic galactose metabolism, whose serum and urine postprandial levels increase in LP, but not in LNP, subjects who ingested lactose, being proposed as novel and non-invasive lactose digestion test for LI screening [136]. Therefore, metabolomics help us to analyze the effect of single nutrients, and their metabolic products, on individual's health, leading to comprehend how the same foods are metabolized differently by different individuals in healthy or unhealthy conditions, such as LI, and so to plan a personalized nutrition or PN program [137]. ...
Cow’s Milk (CM) is a healthy food consumed worldwide by individuals of all ages. Unfortunately, 'lactase deficient' individuals cannot digest milk's carbohydrate lactose depriving themselves of highly beneficial milk proteins like casein, lactoalbumin and lactoglobulin, due to lactose intolerance (LI), while other individuals develop cow milk allergy specifically against these proteins (CMPA). The management of these conditions is distinctly different and an inappropriate diagnosis or treatment may have significant implications for the patients, especially if they are infants or very young children, resulting in unnecessary dietary restriction or avoidable adverse reactions. Omics technologies play a pivotal role in elucidating the intricate interactions between nutrients and the human body, spanning from genetic factors to the microbiota profile and metabolites. This comprehensive approach enables the precise delineation and identification of distinct cohorts of individuals with specific dietary requirements, so that tailored nutrition strategies can be developed. This is what is called personalized nutrition or precision nutrition (PN), the area of nutrition that focuses on the effects of the nutrients over the genome, proteome and metabolome, promoting well-being and health, preventing diseases, reducing chronic disease incidence, and so increasing life expectancy. Here, we report the scientific community opinion proposing to replace the approach “one size fits all” with tailor-made nutrition programs, designed by integrating nutrigenomic data together with clinical parameters and microbiota profiles, taking into account the individual lactose tolerance threshold and needs in terms of specific nutrients intake. This customized approach could help LI patients to improve their quality of life, overcoming depression or anxiety, often resulting from the individual perception of this condition as different from a normal state.
... However, obesity is a complex multifactorial disorder, which makes its management a challenging task [16]. One single 'perfect' diet suitable for everyone may not exist because of the interindividual variation in a dietary treatment response (i.e., how the body utilizes and metabolizes nutrients), due to multiple phenotypic factors and genetic variants [17][18][19]. Therefore, there is an increasing demand for studies investigating personalized nutrition approaches, rather than approaches on a population level [20]. ...
... Overall, there are only small increases in QALYs observed when PP was compared with control and the incremental costs were relatively high. This can mainly be explained because personalization of nutrition is labor intensive, which makes intervention costs high; data need to be collected, organized, and analyzed [19]. For some intervention costs (i.e., the production costs of the meals, indirect costs of the meals, costs for testing and costs for the DSS), the costs per participant, and thereby the total intervention costs, could be reduced by increasing the volume (i.e., number of users). ...
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.
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.
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).
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.
ClinicalTrials.gov registry (NCT04590989).
... The technologies on which PN are based may display substantial imprecision, for example, discordant glycemic responses recorded in individuals using different continuous glucose monitors simultaneously, suggesting that some of the apparent biological variability may be due to methodological limitations [62]. Whilst clinicians are required to keep pace with current evidence, the clinical application of huge amounts of complex data to convey personalized recommendations based on omics technologies is challenging [63]. There is also uncertainty over how PN would be initiated within the clinical environment. ...
