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Because of their role in regulating and fine-tuning gene expression in the posttranscriptional period, microRNA (miRNA) may represent a mediating factor that connects diet and metabolic regulation. Given the vast number of miRNAs and that modulations in miRNA happen in response to a variety of stimuli, a comprehensive registry of miRNAs impacted by diet and the food items that modulate them, would have utility in the identification of miRNA complements for analysis of diet interventions and in helping to establish linkages between the specific impacts of diet components. A scoping literature search of online databases (PubMed, SCOPUS, EMBASE, and Web of Science) was performed. Only studies in human populations, those that used a diet intervention or meal challenge, and those that measured miRNA profiles in the same subject at multiple time points were included. Of the 6167 studies screened, only 25 met the study criteria and were included in the review. Seven studies examined miRNA following a meal challenge, whereas 18 investigated miRNA following a sustained diet intervention. The results demonstrated that miRNA are modulated following a variety of diet interventions and that intensity of miRNA response is greater in metabolically healthy subjects. Heterogeneity in the intensity and length of the diet intervention, the study populations being observed, and the methodology through which target miRNA are identified contribute to a lack of comparability across studies. The findings of this review highlight the need for more study of miRNA responsiveness to intake and provide recommendations for future research.

High fructose consumption is associated with an increased risk of cardiometabolic disease, and fructose feeding dose-dependently induces markers reflective of poor metabolic health. However, unlike glucose, surprisingly little is known about person-to-person differences in postprandial plasma fructose patterns. Herein, we performed post hoc analyses of two published studies to address this question. In the first cohort, 16 participants' all-day plasma fructose concentration patterns (08:00-23:30) were determined (8 women and 8 men) while consuming mixed meals (breakfast, lunch, and dinner) with a fructose-sweetened beverage at each meal (30% of calories). Individually plotted results demonstrate remarkably disparate fructose patterns with respect to peak concentration and timing. A secondary study confirmed substantial interindividual variability in plasma fructose patterns over 240 min in 16 adults consuming Ensure®, a commercially available mixed macronutrient drink containing a low dose of fructose. The health ramifications of interindividual variations in postprandial fructose metabolism and the underlying physiological mechanisms driving differences in post-meal blood patterns remain to be explored. Future research is warranted to determine if interindividual variability in fructose digestion, metabolism, and postprandial blood concentration patterns is associated with cardiometabolic health phenotypes and disease risk.

• Controversy exists concerning the blood glucose-lowering activity of whole grains. • Whole grains elicit high inter-individual variability in blood glucose tolerance. • Gut microbiota and host metabolism likely influence individuals' responses to whole grains. • Machine learning of multi-omics analyses will help to identify whole grain benefits. • Our planned trial could establish a precision nutrition framework for recommendations. Randomized controlled trials (RCT) demonstrate that whole wheat consumption improves glycemia. However, substantial inter-individual variation is often observed, highlighting that dietary whole grain recommendations may not support the health of all persons. The objective of this report is to describe the rationale and design of a planned RCT aimed at establishing the gut microbiota and metabolome signatures that predict whole wheat-mediated improvements in glucose tolerance in adults with prediabetes. It is hypothesized that a controlled diet containing wheat bread (WHEAT; 160 g/day) compared with refined bread (WHITE) will improve glucose tolerance in a gut microbiota-mediated manner. Biospecimens will be collected before and after each 2-week study arm. Testing for oral glucose tolerance and gastrointestinal permeability will be performed post-intervention. Assessments will include oral glucose tolerance (primary outcome) and secondary outcomes including gut microbiota, targeted and untargeted metabolomics of fecal and plasma samples, intestinal and host inflammatory responses, and intestinal permeability. WHEAT is predicted to alleviate glucose intolerance by shifting microbiota composition to increase short-chain fatty acid-producing bacteria while reducing populations implicated in intestinal inflammation, barrier dysfunction, and systemic endotoxemia. Further, benefits from WHEAT are anticipated to correlate with gut-level and systemic metabolomic responses that can help to explain the expected inter-individual variability in glucose tolerance. Thus, knowledge gained from integrating multi-omic responses associating with glucose tolerance could help to establish a precision nutrition-based framework that can alleviate cardiometabolic risk. This framework could inform novel dietary whole grain recommendations by enhancing our understanding of inter-individual responsiveness to whole grain consumption. This report describes the rationale and design of a planned randomized, controlled trial examining the benefits of WHEAT on glucose tolerance in adults with prediabetes. It is hypothesized that WHEAT will improve glucose tolerance in a gut-mediated manner. Machine learning approaches will identify the metagenomic and metabolomic signatures predicting inter-individual responses to WHEAT. Outcomes are expected to inform a precision nutrition framework for whole wheat to alleviate prediabetes. Abbreviation: WHEAT, whole wheat bread. Created in BioRender. Bruno, R. (2024) BioRender.com/h45v815 [Display omitted] [ABSTRACT FROM AUTHOR]

Dietary fats influence gene expression and several metabolic pathways. Therefore, it is crucial to study the role of personal genotypes in the interaction between fat consumption and cardiometabolic markers. This research aimed to determine the interaction of the rs708272 polymorphism of CETP and the fatty acid intake with changes in the HOMA-IR in adults living with overweight or obesity. The current study was a secondary analysis of an 8-week controlled clinical trial. The final sample for this analysis comprised 78 Mexican adults with the Cholesteryl Ester Transfer Protein (CETP) rs708272 polymorphism who followed a dietary intervention. Using an interaction analysis, we evaluated the fatty acid intake and the genotypes of rs708272, with changes in blood glucose, insulin, and the HOMA-IR from baseline to endpoint. Our findings suggest a significant interaction between the trans fatty acid intake and the GG genotype with changes in glucose (p = 0.024), insulin (p = 0.004), and the HOMA-IR (p = 0.002). The higher the consumption of trans fatty acids, the less these markers of glucose metabolism were reduced. carriers of the GG genotype may benefit from limiting dietary trans fatty acid intake, as there was no reduction in plasma glucose and insulin despite a hypocaloric dietary intervention in adults with overweight and obesity. [ABSTRACT FROM AUTHOR]

The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. Most trace minerals (TM) are fed above dairy cow requirements in commercial herds but their fate and effects on dairy cows have not been well documented. In this study, we evaluated the effects of feeding short-term sulfate TM above recommendations on apparent total-tract digestibility of nutrients, rumen fermentation characteristics, serum concentrations, and milk yield and composition, as well as milk, fecal, and urinary TM excretion in midlactation dairy cows. Eight multiparous Holstein cows with an average body weight (± SD) of 684 ± 29 kg at 82 ± 10 DIM in a quadruple 2 × 2 crossover design were fed a basal diet, differing in sulfate TM supplement concentrations, to provide either 0.11, 17, and 63 (control; CON) or 0.95, 114, and 123 (high trace minerals; HTM) mg of dietary Co, Mn, and Zn per kilogram of DM, respectively. Each experimental period had a 21-d adaptation to the diet, followed by a 10-d sample collection period. Feed ingredients and total feces and urine were collected during 4 consecutive d and rumen fluid was collected 0, 1, 2, 4, and 6 h relative to feeding. Milk yield was recorded daily, and milk samples were collected on 4 consecutive milkings. Ingestion of Co, Mn, and Zn was higher for the HTM group compared with the CON group by 216%, 233%, and 93%, respectively. Dry matter intake averaged 25.0 (SE = 0.6) kg/d, and apparent total-tract digestibility of major nutrients was similar between treatments. High trace minerals had no measurable effect on ruminal pH, major volatile fatty acids, and protozoa counts. Isovalerate molar proportion was 9.4% greater for the HTM group compared with the CON group. Neither milk yield (43.5 kg/d; SE = 0.8) nor milk fat and protein concentrations differed between treatments. Milk urea nitrogen concentration was significantly higher for HTM (11.7 mg/dL) compared with CON (9.7 mg/dL; SE = 0.7). Fecal excretion of Co, Mn, and Zn increased by 223%, 198%, and 75%, respectively, for the HTM group compared with the CON group. Urinary excretions of TM were marginal compared with feces, and only urinary Co and Mn were significantly higher for HTM cows than CON cows, as was similarly obtained for serum Co and Mn concentrations. Milk TM yields were not modified by treatments. In summary, short-term dietary sulfate TM supply over the recommendation did not improve cow performance but significantly increased fecal TM excretion, which could affect TM accumulation in soils where manure is applied and could potentially result in leaching into nearby watersheds. Further studies are needed to evaluate the impact of high fecal TM excretion on the environment using the One Health approach. Moreover, the effects of TM oversupply on milk production and cow health should be evaluated by long-term experiments. [ABSTRACT FROM AUTHOR]

Background: Working during the night interferes with the timing of normal daily activities and is associated with an increased risk of chronic diseases. Under controlled experimental conditions, interventions focusing on sleep and nutrition can mitigate the short-term adverse effects of shift work. However, it is unclear how these results translate to real-life, how they can be targeted to individual conditions, and how they relate to long-term health. Therefore, the current study aims to implement a personalized sleep and nutritional intervention among night shift workers in the field. Methods: A non-blinded controlled intervention study is used, consisting of a run-in period, an intervention of 3 months, post-intervention measurements, and a follow-up after 12 months. Three study arms are included: sleep intervention, nutritional intervention, and control group (n = 25 each). Participants are healthy 18–60-year male night shift workers, with at least one year of experience in night shift work. Information from the run-in period will be used to personalize the interventions. The main outcomes are sleep measurements and continuous interstitial glucose levels. Furthermore, general health biomarkers and parameters will be determined to further evaluate effects on long-term health. Discussion: This study aims to mitigate negative health consequences associated with night shift work by introducing two personalized preventive interventions. If proven effective, the personalized interventions may serve as practical solutions that can have a meaningful impact on the sustainable health and employability of night shift workers. This study will thereby contribute to the current need for high–quality data on preventative strategies for night shift work in a real-life context. Trial registration: This trial has been registered under ClinicalTrials.gov Identifier NCT06147089. Registered 27 November 2023. [ABSTRACT FROM AUTHOR]

Addressing the critical need for swift and precise nutritional profiling in healthcare and in food industry, this study pioneers the integration of vision‐language models (VLMs) with chemical analysis techniques. A cutting‐edge VLM is unveiled, utilizing the expansive UMDFood‐90k database, to significantly improve the speed and accuracy of nutrient estimation processes. Demonstrating a macro‐AUCROC of 0.921 for lipid quantification, the model exhibits less than 10% variance compared to traditional chemical analyses for over 82% of the analyzed food items. This innovative approach not only accelerates nutritional screening by 36.9% when tested amongst students but also sets a new benchmark in the precision of nutritional data compilation. This research marks a substantial leap forward in food science, employing a blend of advanced computational models and chemical validation to offer a rapid, high‐throughput solution for nutritional analysis. [ABSTRACT FROM AUTHOR]

The study of nutrient metabolism of ruminants is inseparable from the study of rumen fermentation. In recent years, the prices of corn and soybean meal are high, and often rely on imports. In order to avoid human and animal competition for food, in the environment of cost saving and efficiency, people are seeking precision nutrition. Dietary energy and protein levels are important for ruminants to maintain normal physiological requirements and ensure rumen fermentation. Volatile fatty acids are the main products of rumen fermentation and important substances of energy metabolism in ruminants, and microbial proteins in rumen provide the main protein nutrition for ruminants. Therefore, the effects of different energy nitrogen levels on rumen fermentation in ruminants were reviewed in this paper from two aspects (energy to nitrogen ratio and simultaneous release of energy to nitrogen), so as to provide reference for formulating precise diets. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The concept of precision nutrition was first proposed almost a decade ago. Current research in precision nutrition primarily focuses on comprehending individualized variations in response to dietary intake, with little attention being given to other crucial aspects of precision nutrition. Moreover, there is a dearth of comprehensive review studies that portray the landscape and framework of precision nutrition. This review commences by tracing the historical trajectory of nutritional science, with the aim of dissecting the challenges encountered in nutrition science within the new era of disease profiles. This review also deconstructs the field of precision nutrition into four key components: the proposal of the theory for individualized nutritional requirement phenotypes; the establishment of precise methods for measuring dietary intake and evaluating nutritional status; the creation of multidimensional nutritional intervention strategies that address the aspects of what, how, and when to eat; and the construction of a pathway for the translation and integration of scientific research into healthcare practices, utilizing artificial intelligence and information platforms. Incorporating these four components, this review further discusses prospective avenues that warrant exploration to achieve the objective of enhancing health through precision nutrition.

ABSTRACT: Most trace minerals (TM) are fed above dairy cow requirements in commercial herds but their fate and effects on dairy cows have not been well documented. In this study, we evaluated the effects of feeding short-term sulfate TM above recommendations on apparent total-tract digestibility of nutrients, rumen fermentation characteristics, serum concentrations, and milk yield and composition, as well as milk, fecal, and urinary TM excretion in midlactation dairy cows. Eight multiparous Holstein cows with an average body weight (± SD) of 684 ± 29 kg at 82 ± 10 DIM in a quadruple 2 × 2 crossover design were fed a basal diet, differing in sulfate TM supplement concentrations, to provide either 0.11, 17, and 63 (control; CON) or 0.95, 114, and 123 (high trace minerals; HTM) mg of dietary Co, Mn, and Zn per kilogram of DM, respectively. Each experimental period had a 21-d adaptation to the diet, followed by a 10-d sample collection period. Feed ingredients and total feces and urine were collected during 4 consecutive d and rumen fluid was collected 0, 1, 2, 4, and 6 h relative to feeding. Milk yield was recorded daily, and milk samples were collected on 4 consecutive milkings. Ingestion of Co, Mn, and Zn was higher for the HTM group compared with the CON group by 216%, 233%, and 93%, respectively. Dry matter intake averaged 25.0 (SE = 0.6) kg/d, and apparent total-tract digestibility of major nutrients was similar between treatments. High trace minerals had no measurable effect on ruminal pH, major volatile fatty acids, and protozoa counts. Isovalerate molar proportion was 9.4% greater for the HTM group compared with the CON group. Neither milk yield (43.5 kg/d; SE = 0.8) nor milk fat and protein concentrations differed between treatments. Milk urea nitrogen concentration was significantly higher for HTM (11.7 mg/dL) compared with CON (9.7 mg/dL; SE = 0.7). Fecal excretion of Co, Mn, and Zn increased by 223%, 198%, and 75%, respectively, for the HTM group compared with the CON group. Urinary excretions of TM were marginal compared with feces, and only urinary Co and Mn were significantly higher for HTM cows than CON cows, as was similarly obtained for serum Co and Mn concentrations. Milk TM yields were not modified by treatments. In summary, short-term dietary sulfate TM supply over the recommendation did not improve cow performance but significantly increased fecal TM excretion, which could affect TM accumulation in soils where manure is applied and could potentially result in leaching into nearby watersheds. Further studies are needed to evaluate the impact of high fecal TM excretion on the environment using the One Health approach. Moreover, the effects of TM oversupply on milk production and cow health should be evaluated by long-term experiments.

Abstract Background Working during the night interferes with the timing of normal daily activities and is associated with an increased risk of chronic diseases. Under controlled experimental conditions, interventions focusing on sleep and nutrition can mitigate the short-term adverse effects of shift work. However, it is unclear how these results translate to real-life, how they can be targeted to individual conditions, and how they relate to long-term health. Therefore, the current study aims to implement a personalized sleep and nutritional intervention among night shift workers in the field. Methods A non-blinded controlled intervention study is used, consisting of a run-in period, an intervention of 3 months, post-intervention measurements, and a follow-up after 12 months. Three study arms are included: sleep intervention, nutritional intervention, and control group (n = 25 each). Participants are healthy 18–60-year male night shift workers, with at least one year of experience in night shift work. Information from the run-in period will be used to personalize the interventions. The main outcomes are sleep measurements and continuous interstitial glucose levels. Furthermore, general health biomarkers and parameters will be determined to further evaluate effects on long-term health. Discussion This study aims to mitigate negative health consequences associated with night shift work by introducing two personalized preventive interventions. If proven effective, the personalized interventions may serve as practical solutions that can have a meaningful impact on the sustainable health and employability of night shift workers. This study will thereby contribute to the current need for high–quality data on preventative strategies for night shift work in a real-life context. Trial registration This trial has been registered under ClinicalTrials.gov Identifier NCT06147089. Registered 27 November 2023.

Purpose of reviewEmerging evidence supports the promise of precision nutritional approaches for cardiovascular disease (CVD) prevention. Here, we discuss current findings from precision nutrition trials and studies reporting substantial inter-individual variability in responses to diets and dietary components relevant to CVD outcomes. We highlight examples where early precision nutrition research already points to actionable intervention targets tailored to an individual's biology and lifestyle. Finally, we make the case for high-density lipoproteins (HDL) as a compelling next generation target for precision nutrition aimed at CVD prevention. HDL possesses complex structural features including diverse protein components, lipids, size distribution, extensive glycosylation, and interacts with the gut microbiome, all of which influence HDL's anti-inflammatory, antioxidant, and cholesterol efflux properties. Elucidating the nuances of HDL structure and function at an individual level may unlock personalized dietary and lifestyle strategies to optimize HDL-mediated atheroprotection and reduce CVD risk.Recent findingsRecent human studies have demonstrated that HDL particles are key players in the reduction of CVD risk. Our review highlights the role of HDL and the importance of personalized therapeutic approaches to improve their potential for reducing CVD risk. Factors such as diet, genetics, glycosylation, and gut microbiome interactions can modulate HDL structure and function at the individual level. We emphasize that fractionating HDL into size-based subclasses and measuring particle concentration are necessary to understand HDL biology and for developing the next generation of diagnostics and biomarkers. These discoveries underscore the need to move beyond a one-size-fits-all approach to HDL management. Precision nutrition strategies that account for personalized metabolic, genetic, and lifestyle data hold promise for optimizing HDL therapies and function to mitigate CVD risk more potently. While human studies show HDL play a key role in reducing CVD risk, recent findings indicate that factors such as diet, genetics, glycosylation, and gut microbes modulate HDL function at the individual level, underscoring the need for precision nutrition strategies that account for personalized variability to optimize HDL's potential for mitigating CVD risk.

Consumption of nuts and berries are considered part of a healthy eating pattern. Nuts and berries contain a complex nutrient profile consisting of essential vitamins and minerals, fiber, polyunsaturated fatty acids, and phenolics in quantities that improve physiological outcomes. The spectrum of health outcomes that may be impacted by the consumptions of nuts and berries includes cardiovascular, gut microbiome, and cognitive, among others. Recently, new insights regarding the bioactive compounds found in both nuts and berries have reinforced their role for use in precision nutrition efforts. However, challenges exist that can affect the generalizability of outcomes from clinical studies, including inconsistency in study designs, homogeneity of test populations, variability in test products and control foods, and assessing realistic portion sizes. Future research centered on precision nutrition and multi-omics technologies will yield new insights. These and other topics such as funding streams and perceived risk-of-bias were explored at an international nutrition conference focused on the role of nuts and berries in clinical nutrition. Successes, challenges, and future directions with these foods are presented here.

Abstract Background Obesity is a global health concern associated with increased risk of diseases like cardiovascular conditions including ischemic heart disease, a leading cause of mortality. The ketogenic diet (KD) has potential therapeutic applications in managing obesity and related disorders. However, the intricate effects of KD on diverse physiological conditions remain incompletely understood. The PI3K-Akt signaling pathway is critical for heart health, and its dysregulation implicates numerous cardiac diseases. Methods We developed comprehensive mathematical models of the PI3K-Akt signaling pathway under high-fat diet (HFD) and KD conditions to elucidate their differential impacts and quantify apoptosis. Simulations and sensitivity analysis were performed. Results Simulations demonstrate that KD can reduce the activation of key molecules like Erk and Trp53 to mitigate apoptosis compared to HFD. Findings align with experimental data, highlighting the potential cardiac benefits of KD. Sensitivity analysis identifies regulators like Trp53 and Bcl2l1 that critically influence apoptosis under HFD. Conclusions Mathematical modeling provides quantitative insights into the contrasting effects of HFD and KD on cardiac PI3K-Akt signaling and apoptosis. Findings have implications for precision nutrition and developing novel therapeutic strategies to address obesity-related cardiovascular diseases. Graphical abstract

Abstract Background The Diabetes Telemedicine Mediterranean Diet (DiaTeleMed) Study is a fully remote randomized clinical trial evaluating personalized dietary management in individuals with type 2 diabetes (T2D). The study aims to test the efficacy of a personalized behavioral approach for dietary management of moderately controlled T2D, versus a standardized behavioral intervention that uses one-size-fits-all dietary recommendations, versus a usual care control (UCC). The primary outcome will compare the impact of each intervention on the mean amplitude of glycemic excursions (MAGE). Methods Eligible participants are between 21 and 80 years of age diagnosed with moderately controlled T2D (HbA1c: 6.0 to 8.0%) and managed on lifestyle alone or lifestyle plus metformin. Participants must be willing and able to attend virtual counseling sessions and log meals into a dietary tracking smartphone application (DayTwo), and wear a continuous glucose monitor (CGM) for up to 12 days. Participants are randomized with equal allocation (n = 255, n = 85 per arm) to one of three arms: (1) Personalized, (2) Standardized, or (3) UCC. Measurements occur at 0 (baseline), 3, and 6 months. All participants receive isocaloric energy and macronutrient targets to meet Mediterranean diet guidelines, in addition to 14 intervention contacts over 6 months (4 weekly then 10 biweekly) to cover diabetes self-management education. The first 4 UCC intervention contacts are delivered via synchronous videoconferences followed by educational video links. Participants in Standardized receive the same educational content as those in the UCC arm, following the same schedule. However, all intervention contacts are conducted via synchronous videoconferences, paired with Social Cognitive Theory (SCT)-based behavioral counseling, plus dietary self-monitoring of planned meals using a mobile app that provides real-time feedback on calories and macronutrients. Participants in the Personalized arm receive all elements of the Standardized intervention, in addition to real-time feedback on predicted post-prandial glycemic response (PPGR) to meals and snacks logged into the mobile app. Discussion The DiaTeleMed Study aims to address an important gap in the current landscape of precision nutrition by determining the contributions of behavioral counseling and personalized nutrition recommendations on glycemic control in individuals with T2D. The fully remote methodology of the study allows for scalability and innovative delivery of personalized dietary recommendations at a population level. Trial registration ClinicalTrials.gov NCT05046886. Registered on September 16, 2021.

The rising incidence of type 2 diabetes underscores the need for technological innovations aimed at enhancing diabetes management by aiding individuals in monitoring their dietary intake. This has resulted in the development of technologies capable of tracking the timing and content of an individual's meals. However, the ability to use non-invasive wearables to estimate or classify the carbohydrate content of the food an individual has just consumed remains a relatively unexplored area. This study investigates carbohydrate content classification using postprandial heart rate responses from non-invasive wearables. We designed and developed timeStampr, an iOS application for collecting timestamps essential for data labeling and establishing ground truth. We then conducted a pilot study in controlled, yet naturalistic settings. Data were collected from 23 participants using an Empatica E4 device worn on the upper arm, while each participant consumed either low-carbohydrate or carbohydrate-rich foods. Due to sensor irregularities with dark skin tones and non-compliance with the study's health criteria, we excluded data from three participants. Finally, we configured and trained a Light Gradient Boosting Machine (LGBM) model for carbohydrate content classification. Our classifiers demonstrated robust performance, with the carbohydrate content classification model consistently achieving at least 84% in accuracy, precision, recall, and AUCROC within a 60 s window. The results of this study demonstrate the potential of postprandial heart rate responses from non-invasive wearables in carbohydrate content classification. [ABSTRACT FROM AUTHOR]

Obesity, a significant public health concern with high prevalence in both adults and children, is a complex disorder arising from the interaction of multiple genes and environmental factors. Advances in genome-wide association studies (GWAS) and sequencing technologies have identified numerous polygenic causes of obesity, particularly genes involved in hunger, satiety signals, adipocyte differentiation, and energy expenditure. This study investigates the relationship between six obesity-related genes (CLOCK, FTO, GHRL, LEP, LEPR, MC4R) and their impact on BMI, WC, HC, WHR, and emotional eating behavior in 220 Romanian adults. Emotional eating was assessed using the validated Emotional Eating Questionnaire (EEQ). Our analysis revealed significant variability in obesity-related phenotypes and emotional eating behaviors across different genotypes. Specifically, CLOCK/CC, FTO/AA, and LEP/AA genotypes were strongly associated with higher obesity metrics and emotional eating scores, while GHRL/TT and MC4R/CC were linked to increased BMI and WHR. The interplay between genetic predisposition and emotional eating behavior significantly influenced BMI and WHR, indicating a complex relationship between genetic and behavioral factors. This study, the first of its kind in Romania, provides a foundation for targeted interventions to prevent and reduce obesity and suggests potential strategies for gene expression modulation to mitigate the effects of emotional eating. Adopting a 'One Health' approach by creating an evidence base derived from both human and animal studies is crucial for understanding how to control obesity. [ABSTRACT FROM AUTHOR]

Background: Obesity is a global health concern associated with increased risk of diseases like cardiovascular conditions including ischemic heart disease, a leading cause of mortality. The ketogenic diet (KD) has potential therapeutic applications in managing obesity and related disorders. However, the intricate effects of KD on diverse physiological conditions remain incompletely understood. The PI3K-Akt signaling pathway is critical for heart health, and its dysregulation implicates numerous cardiac diseases. Methods: We developed comprehensive mathematical models of the PI3K-Akt signaling pathway under high-fat diet (HFD) and KD conditions to elucidate their differential impacts and quantify apoptosis. Simulations and sensitivity analysis were performed. Results: Simulations demonstrate that KD can reduce the activation of key molecules like Erk and Trp53 to mitigate apoptosis compared to HFD. Findings align with experimental data, highlighting the potential cardiac benefits of KD. Sensitivity analysis identifies regulators like Trp53 and Bcl2l1 that critically influence apoptosis under HFD. Conclusions: Mathematical modeling provides quantitative insights into the contrasting effects of HFD and KD on cardiac PI3K-Akt signaling and apoptosis. Findings have implications for precision nutrition and developing novel therapeutic strategies to address obesity-related cardiovascular diseases. [ABSTRACT FROM AUTHOR]

Background and Aims: We investigated circulating homocysteine (Hcy), a cardiovascular disease (CVD) risk factor, examining its dietary associations to provide personalized nutrition advice. This study addressed the inadequacy of current dietary interventions to ultimately address the disproportionately high incidence of CVD in Black populations. Methods and Results: Cross-sectional analyses of 1,867 Black individuals of the PURE-SA study allowed the identification of dietary intake and cardiovascular measure interactions on three sub-categories: (1) normal blood pressure (BP), hypertension or Hcy-related hypertension (H-type), (2) low, normal or high Hcy concentrations, and (3) Hcy-related genetic combinations. Favorable body composition, but adverse dietary intake and cardiovascular determinants, were observed in higher Hcy categories. H-types, compared to regular hypertensives, had higher alcohol and lower macronutrient and micronutrient consumption. Inverse associations with carotid-radial pulse wave velocity were evident between monounsaturated fatty acid (FA) consumption and H-type hypertension as well as polyunsaturated FA and CBS883/ins68 TT carriers. Energy intake was positively associated with vascular cell adhesion molecule-1 (VCAM-1) in variant CBST883C/ins68 and CBS9276 GG carriers. VCAM-1 was also positively associated with plant protein intake in CBS9276 GG and MTR2756 AA carriers and negatively with total protein intake and CBS9276 GG carriers. Alcohol intake was positively associated with intercellular adhesion molecule-1 in MTR2756 minor allele carriers. Conclusion: Because Hcy gene-diet interactions are evident, personalized nutrition, by adjusting diets based on genetic profiles (e.g., CBS and MTR variations) and dietary interactions (e.g., FAs and proteins), can enhance cardiovascular outcomes by managing Hcy and related hypertension in genetically susceptible individuals. [ABSTRACT FROM AUTHOR]

Background: The Diabetes Telemedicine Mediterranean Diet (DiaTeleMed) Study is a fully remote randomized clinical trial evaluating personalized dietary management in individuals with type 2 diabetes (T2D). The study aims to test the efficacy of a personalized behavioral approach for dietary management of moderately controlled T2D, versus a standardized behavioral intervention that uses one-size-fits-all dietary recommendations, versus a usual care control (UCC). The primary outcome will compare the impact of each intervention on the mean amplitude of glycemic excursions (MAGE). Methods: Eligible participants are between 21 and 80 years of age diagnosed with moderately controlled T2D (HbA1c: 6.0 to 8.0%) and managed on lifestyle alone or lifestyle plus metformin. Participants must be willing and able to attend virtual counseling sessions and log meals into a dietary tracking smartphone application (DayTwo), and wear a continuous glucose monitor (CGM) for up to 12 days. Participants are randomized with equal allocation (n = 255, n = 85 per arm) to one of three arms: (1) Personalized, (2) Standardized, or (3) UCC. Measurements occur at 0 (baseline), 3, and 6 months. All participants receive isocaloric energy and macronutrient targets to meet Mediterranean diet guidelines, in addition to 14 intervention contacts over 6 months (4 weekly then 10 biweekly) to cover diabetes self-management education. The first 4 UCC intervention contacts are delivered via synchronous videoconferences followed by educational video links. Participants in Standardized receive the same educational content as those in the UCC arm, following the same schedule. However, all intervention contacts are conducted via synchronous videoconferences, paired with Social Cognitive Theory (SCT)-based behavioral counseling, plus dietary self-monitoring of planned meals using a mobile app that provides real-time feedback on calories and macronutrients. Participants in the Personalized arm receive all elements of the Standardized intervention, in addition to real-time feedback on predicted post-prandial glycemic response (PPGR) to meals and snacks logged into the mobile app. Discussion: The DiaTeleMed Study aims to address an important gap in the current landscape of precision nutrition by determining the contributions of behavioral counseling and personalized nutrition recommendations on glycemic control in individuals with T2D. The fully remote methodology of the study allows for scalability and innovative delivery of personalized dietary recommendations at a population level. Trial registration: ClinicalTrials.gov NCT05046886. Registered on September 16, 2021. [ABSTRACT FROM AUTHOR]

Humans are the result of an evolutionary process, and because of this, many biological processes are interconnected with each other. The intestine–brain axis consists of an intricately connected neuronal–neuroendocrine circuit that regulates the sensation of hunger and satiety. Genetic variations and the consumption of unnatural diets (ultra-processed foods, high contents of sugars, etc.) can override this circuit and cause addiction to certain foods and/or the inability to feel satiety in certain situations. The patients who come to consultations (mainly psychology or nutrition) in an attempt to resolve this problem sometimes fail, which leads to them looking for new strategies based on biological predisposition. This investigation aims to evaluate the genetic studies regarding the microbiota carried out in the last 12 years in humans to try to determine which genes and microbes that have been recently studied are related to patients diagnosed with binge eating disorder or compulsive eating (presenting obesity or not). The protocol followed the PRISMA statement, and the following databases were searched from 2012 until the present day: PubMed, PsycINFO, SCOPUS, and Web of Science. Twenty-four international articles were analyzed, including cross-sectional or exploratory studies; five of them referred to the microbial composition, and in nineteen, the existence of genetic polymorphisms present in binge eating disorder or in compulsive eating could be observed: DRD2, OPRM1, COMT, MC4R, BNDF, FTO, SLC6A3, GHRL, CARTPT, MCHR2, and LRP11. Even though there is still much to investigate on the subject, it must be highlighted that, in the last 4 years, a two-fold increase has been observed in potential markers and in studies related to the matter, also highlighting the importance of different analyses in relation to psychosocial factors and their interaction with the genetic and microbial factors, for which research on the matter must be continued. [ABSTRACT FROM AUTHOR]

Translational research has documented the conjoint beneficial relationships between dietary and physical activity habits concerning weight maintenance. However, the precise interplay between diet and exercise impacting body composition remains unclear, challenging personalized interventions. This study aimed to explore potential interactions and effect modifications of these factors affecting the body mass index (BMI) within an online adult cohort. Data from 11,883 NUTRiMDEA cohort participants were analyzed in this cross-sectional study, categorizing individuals by age, sex, and BMI using linear regression models to assess the interactions between lifestyle factors and adiposity. Significant differences emerged in anthropometry, lifestyle, and health-related quality of life (HRQoL) across categories. The combined effect of diet and physical activity had a greater impact on BMI than physical activity or Mediterranean diet adherence alone, with lower BMI as physical activity levels increased (β: −0.5) and adherence to the Mediterranean diet decreased, where a modification effect between them was identified (β: −0.28). Participants with lower Mediterranean diet adherence displayed superior BMI when physical activity was low, but when activity levels were higher, their BMI aligned with those with healthier dietary habits. An interaction link between lifestyle factors and BMI was found, showing the differential effects of the Mediterranean diet and physical activity combination concerning adiposity. [ABSTRACT FROM AUTHOR]

Abstract Ion consumption plays key roles in maintaining bodily homeostasis and health. Here passive wireless, multimineral comonitoring arrays are studied that may potentially be utilized for emerging applications in precision nutrition. RF biosensors targeting select minerals (calcium or magnesium demonstrated herein) are built from integrating ion‐selective membranes within a broadside‐coupled split ring resonator architecture. RF sensors are typically monitored one at a time and such platforms often are incapable of comeasuring multiple confounding components. To address this challenge, this sensor arrays are further directly integrated alongside a conformal, custom readout coil that optimizes multi‐RF sensor readout. Such optimized networks exhibit enhanced signal clarity, further facilitating coextraction of multiple ion components. A simple method of extracting multimineral concentrations from food even despite the imperfect selectivity of divalent ion‐selective membranes is introduced. This passive wireless, zero‐electronic ion‐monitoring platform integrates seamlessly on foodware or packaging, possessing many applications in food measurement.

Abstract Addressing the critical need for swift and precise nutritional profiling in healthcare and in food industry, this study pioneers the integration of vision‐language models (VLMs) with chemical analysis techniques. A cutting‐edge VLM is unveiled, utilizing the expansive UMDFood‐90k database, to significantly improve the speed and accuracy of nutrient estimation processes. Demonstrating a macro‐AUCROC of 0.921 for lipid quantification, the model exhibits less than 10% variance compared to traditional chemical analyses for over 82% of the analyzed food items. This innovative approach not only accelerates nutritional screening by 36.9% when tested amongst students but also sets a new benchmark in the precision of nutritional data compilation. This research marks a substantial leap forward in food science, employing a blend of advanced computational models and chemical validation to offer a rapid, high‐throughput solution for nutritional analysis.

Nutrient databases are a critical component of nutrition science and the basis of exciting new research in precision nutrition (PN). To identify the most critical components needed for improvement of nutrient databases, food composition data were analyzed for quality, with completeness being the most important measure, and for FAIRness, how well the data conformed with the data science criteria of findable, accessible, interoperable, and reusable (FAIR). Databases were judged complete if they provided data for all 15 nutrition fact panel (NFP) nutrient measures and all 40 National Academies of Sciences, Engineering, and Medicine (NASEM) essential nutrient measures for each food listed. Using the gold standard the USDA standard reference (SR) Legacy database as surrogate, it was found that SR Legacy data were not complete for either NFP or NASEM nutrient measures. In addition, phytonutrient measures in the 4 USDA Special Interest Databases were incomplete. To evaluate data FAIRness, a set of 175 food and nutrient data sources were collected from worldwide. Many opportunities were identified for improving data FAIRness, including creating persistent URLs, prioritizing usable data storage formats, providing Globally Unique Identifiers for all foods and nutrients, and implementing citation standards. This review demonstrates that despite important contributions from the USDA and others, food and nutrient databases in their current forms do not yet provide truly comprehensive food composition data. We propose that to enhance the quality and usage of food and nutrient composition data for research scientists and those fashioning various PN tools, the field of nutrition science must step out of its historical comfort zone and improve the foundational nutrient databases used in research by incorporating data science principles, the most central being data quality and data FAIRness.

Almond consumption can improve cardiometabolic (CM) health. However, the mechanisms underlying those benefits are not well characterized. This study explored the effects of consuming a snack of almonds vs. crackers for 8 weeks on changes in metabolomic profiles in young adults (clinicaltrials.gov ID: NCT03084003).Participants (n = 73, age: 18-19 years, BMI: 18-41 kg/m2) were randomly assigned to consume either almonds (2 oz/d, n = 38) or an isocaloric control snack of graham crackers (325 kcal/d, n = 35) daily for 8 weeks. Blood samples were collected at baseline prior to and at 4 and 8 weeks after the intervention. Metabolite abundances in the serum were quantified by hydrophilic interaction chromatography quadrupole (Q) time-of-flight (TOF) mass spectrometry (MS/MS), gas chromatography (GC) TOF MS, CSH-ESI (electrospray) QTOF MS/MS, and targeted analyses for free PUFAs, total fatty acids, oxylipins and endocannabinoids. Linear mixed model analyses with baseline-adjustment were conducted, and those results were used for enrichment and network analyses. Microbial community pathway predictions from 16S rRNA sequencing of fecal samples was done using PICRUST2.Almond consumption enriched unsaturated triglycerides, unsaturated phosphatidylcholines, saturated and unsaturated lysophosphatidylcholines, tricarboxylic acids, and tocopherol clusters (p

Introduction: It has been suggested that capsaicin (CAP), a major pungent component in chili peppers, can be used as an anti-obesity ingredient due to effects on energy metabolism, but evidence is not consistent. Genetics may account for differences in CAP tolerance and its impact on adiposity status. The aim of this study was to systematically review current evidence concerning the role of genetic polymorphisms influencing CAP tolerance. Methods: The present systematic review analyzed and synthesized available evidence concerning associations between genetic polymorphisms and CAP tolerance following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) guidelines. Databases such as PubMed/MEDLINE, Cochrane, Scopus, Google Scholar, SciELO, and LILACS were screened. Out of 228 publications identified, only 6 meet inclusion criteria and were finally included in the final report. Results: Overall, a total of 28 single nucleotide polymorphisms were associated with several CAP tolerance traits including sensitivity to burning/stinging, heat pain, and cough reactions, and detection of bitter taste thresholds. These genetic variants were located within 6 genes involved in key physiological processes such synthesis of tetrahydrobiopterin and nitric oxide production (GCH1), CAP uptake and transduction of thermal stimuli (TRPV1), and bitter taste perception (TAS2R38, TAS2R3, TAS2R4, and TAS2R5). Conclusion: There is evidence about the influence of genetic polymorphisms on CAP tolerance by affecting nociceptive signaling, CAP binding, and bitter tasting. This knowledge may facilitate the design and implementation of innovative CAP-based nutrigenetic strategies for a more precise clinical management of obesity.

Given the worldwide epidemic of overweight and obesity among children, evidence-based dietary recommendations are fundamentally important for obesity prevention. Although the significance of the human gut microbiome in shaping the physiological effects of diet and obesity has been widely recognized, nutritional therapeutics for the mitigation of pediatric obesity globally are only just starting to leverage advancements in the nutritional microbiology field. In this review, we extracted data from PubMed, EMBASE, Scopus, Web of Science, Google Scholar, CNKI, Cochrane Library and Wiley online library that focuses on the characterization of gut microbiota (including bacteria, fungi, viruses, and archaea) in children with obesity. We further review host-microbe interactions as mechanisms mediating the physiological effects of dietary fibers and how fibers alter the gut microbiota in children with obesity. Contemporary nutritional recommendations for the prevention of pediatric obesity are also discussed from a gut microbiological perspective. Finally, we propose an experimental framework for integrating gut microbiota into nutritional interventions for children with obesity and provide recommendations for the design of future studies on precision nutrition for pediatric obesity.

Resistant starch (RS) consumption can have beneficial effects on metabolic health, but the response, in terms of effects on the gut microbiota and host physiology, varies between individuals. Factors predicting the response to RS are not yet established and would be useful for developing precision nutrition approaches that maximize the benefits of dietary fiber intake. We sought to identify predictors of gut microbiota response to RS supplementation. We enrolled 76 healthy adults into a 7-week crossover study with 59 individuals completing the study. Participants consumed RS type 2 (RS2), RS type 4 (RS4), and digestible starch, for 10 d each with 5-d washout periods in between. We collected fecal and saliva samples and food records during each treatment period. We performed 16S rRNA gene sequencing and measured fecal short-chain fatty acids (SCFAs), salivary amylase (AMY1) gene copy number, and salivary amylase activity (SAA). Dietary fiber intake was predictive of the relative abundance of several amplicon sequence variants (ASVs) at the end of both RS treatments. AMY1-related metrics were not predictive of response to RS. SAA was only predictive of the relative abundance of one ASV after digestible starch supplementation. Interestingly, SCFA concentrations increased the most during digestible starch supplementation. Treatment order (the order of consumption of RS2 and RS4), alpha diversity, and a subset of ASVs were predictive of SCFA changes after RS supplementation. Based on our findings, dietary fiber intake and gut microbiome composition would be informative if assessed prior to recommending RS supplementation because these data can be used to predict changes in specific ASVs and fecal SCFA concentrations. These findings lay a foundation to support the premise that using a precision nutrition approach to optimize the benefits of dietary fibers such as RS could be an effective strategy to compensate for the low consumption of dietary fiber nationwide.

Plasma trimethylamine n-oxide (TMAO) concentration increases in responses to feeding TMAO, choline, phosphatidylcholine, L-carnitine, and betaine but it is unknown whether concentrations change following a mixed macronutrient tolerance test (MMTT) with limited amounts of TMAO precursors. In this proof-of-concept study, we provided healthy female and male adults (n = 97) ranging in age (18-65 years) and BMI (18-44 kg/m2) a MMTT (60% fat, 25% sucrose; 42% of a standard 2000 kilo calorie diet) and recorded their metabolic response at fasting and at 30 min, 3 h, and 6 h postprandially. We quantified total exposure to TMAO (AUC-TMAO) and classified individuals by the blood draw at which they experienced their maximal TMAO concentration (TMAO-response groups). We related AUC-TMAO to the 16S rRNA microbiome, to two SNPs in the exons of the FMO3 gene (rs2266782, G>A, p.Glu158Lys; and rs2266780, A>G, p.Glu308Gly), and to a priori plasma metabolites. We observed varying TMAO responses (timing and magnitude) and identified a sex by age interaction such that AUC-TMAO increased with age in females but not in males (p-value = 0.0112). Few relationships between AUC-TMAO and the fecal microbiome and FMO3 genotype were identified. We observed a strong correlation between AUC-TMAO and TNF-α that depended on TMAO-response group. These findings promote precision nutrition and have important ramifications for the eating behavior of adults who could benefit from reducing TMAO exposure, and for understanding factors that generate plasma TMAO.

This review aimed to synthesise existing literature on the efficacy of personalised or precision nutrition (PPN) interventions, including medical nutrition therapy (MNT), in improving outcomes related to glycaemic control (HbA1c, post-prandial glucose [PPG], and fasting blood glucose), anthropometry (weight, BMI, and waist circumference [WC]), blood lipids, blood pressure (BP), and dietary intake among adults with prediabetes or metabolic syndrome (MetS). Six databases were systematically searched (Scopus, Medline, Embase, CINAHL, PsycINFO, and Cochrane) for randomised controlled trials (RCTs) published from January 2000 to 16 April 2023. The Academy of Nutrition and Dietetics Quality Criteria were used to assess the risk of bias. Seven RCTs (n = 873), comprising five PPN and two MNT interventions, lasting 3–24 months were included. Consistent and significant improvements favouring PPN and MNT interventions were reported across studies that examined outcomes like HbA1c, PPG, and waist circumference. Results for other measures, including fasting blood glucose, HOMA-IR, blood lipids, BP, and diet, were inconsistent. Longer, more frequent interventions yielded greater improvements, especially for HbA1c and WC. However, more research in studies with larger sample sizes and standardised PPN definitions is needed. Future studies should also investigate combining MNT with contemporary PPN factors, including genetic, epigenetic, metabolomic, and metagenomic data. [ABSTRACT FROM AUTHOR]

Summary: While the "precision nutrition" movement is at an early stage of development, several investigations have compared low‐fat versus carbohydrate (CHO)‐modified diets (i.e., low‐or‐reduced‐CHO, low glycemic index/load diets, and high‐fiber) in people with normal versus impaired glucose metabolism. The purpose of this scoping review was to summarize evidence in support of the hypothesis that CHO‐modified diets are more effective for weight loss among people with impaired glucose metabolism. Fifteen articles were included in this review: seven retrospective analyses of randomized clinical trials and eight prospective randomized clinical trials with prespecified hypotheses related to a diet (low‐fat vs. CHO‐modified) × phenotype (normal vs. impaired) interaction. Evidence in support of the hypothesis was identified in six of seven retrospective and three of eight prospective studies, which led to a recommendation of CHO‐modified diets as a first‐line option for people with impaired glucose metabolism. However, the evidence in support of this recommendation is relatively weak, and dietary prescriptions should consider additional contextual information that may influence overall dietary adherence. Additional and rigorous research using innovative randomized experimental approaches is needed for stronger dietary weight loss recommendations based on pretreatment glycemic status. [ABSTRACT FROM AUTHOR]

In the last few decades, vitamin D has undeniably been one of the most studied nutrients. Despite our ability to produce vitamin D through sunlight exposure, its presence in several natural food sources and fortified foods, and its widespread availability as a dietary supplement, vitamin D deficiency is a serious public health problem, affecting nearly 50% of the global population. Low serum levels of vitamin D are being associated with increased susceptibility to numerous health conditions, including respiratory infections, mental health, autoimmune diseases, and different cancer types. Although the association between vitamin D status and health is well-established, the exact beneficial effects of vitamin D are still inconclusive and indefinite, especially when considering the prevention and treatment of different health conditions and the determination of an appropriate dosage to exert those beneficial effects in various population groups. Therefore, further research is needed. With constant improvements in our understanding of individual variations in vitamin D metabolism and requirements, in the future, precision nutrition and personalized supplementation plans could prove beneficial. [ABSTRACT FROM AUTHOR]

The rise of artificial intelligence (AI) has revolutionized various scientific fields, particularly in medicine, where it has enabled the modeling of complex relationships from massive datasets. Initially, AI algorithms focused on improved interpretation of diagnostic studies such as chest X-rays and electrocardiograms in addition to predicting patient outcomes and future disease onset. However, AI has evolved with the introduction of transformer models, allowing analysis of the diverse, multimodal data sources existing in medicine today. Multimodal AI holds great promise in more accurate disease risk assessment and stratification as well as optimizing the key driving factors in cardiometabolic disease: blood pressure, sleep, stress, glucose control, weight, nutrition, and physical activity. In this article we outline the current state of medical AI in cardiometabolic disease, highlighting the potential of multimodal AI to augment personalized prevention and treatment strategies in cardiometabolic disease. [ABSTRACT FROM AUTHOR]

Meal timing emerges as a crucial factor influencing metabolic health that can be explained by the tight interaction between the endogenous circadian clock and metabolic homeostasis. Mistimed food intake, such as delayed or nighttime consumption, leads to desynchronization of the internal circadian clock and is associated with an increased risk for obesity and associated metabolic disturbances such as type 2 diabetes and cardiovascular diseases. Conversely, meal timing aligned with cellular rhythms can optimize the performance of tissues and organs. In this review, we provide an overview of themetabolic effects ofmeal timing and discuss the underlying mechanisms. Additionally, we explore factors influencing meal timing, including internal determinants such as chronotype and genetics, aswell as external influences like social factors, cultural aspects, andwork schedules. This review could contribute to defining meal-timing-based recommendations for public health initiatives and developing guidelines for effective lifestyle modifications targeting the prevention and treatment of obesity and associated metabolic diseases. Furthermore, it sheds light on crucial factors that must be considered in the design of future food timing intervention trials. [ABSTRACT FROM AUTHOR]

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Background and Objectives: Modern classification and categorization of individuals' health requires personalized variables such as nutrition, physical activity, lifestyle, and medical data through advanced analysis and clustering methods involving machine learning tools. The objective of this project was to categorize Mediterranean dwellers' health factors and design metabotypes to provide personalized well-being in order to develop professional implementation tools in addition to characterizing nutritional and lifestyle features in such populations. Materials and Methods: A two-phase observational study was conducted by the Pharmacists Council to identify Spanish nutritional and lifestyle characteristics. Adults over 18 years of age completed questionnaires on general lifestyle habits, dietary patterns (FFQ, MEDAS-17 p), physical activity (IPAQ), quality of life (SF-12), and validated well-being indices (LS7, MEDLIFE, HHS, MHL). Subsequently, exploratory factor, clustering, and random forest analysis methods were conducted to objectively define the metabotypes considering population determinants. Results: A total of 46.4% of the sample (n = 5496) had moderate-to-high adherence to the Mediterranean diet (>8 points), while 71% of the participants declared that they had moderate physical activity. Almost half of the volunteers had a good self-perception of health (49.9%). Regarding lifestyle index, population LS7 showed a fair cardiovascular health status (7.9 ± 1.7), as well as moderate quality of life by MEDLIFE (9.3 ± 2.6) and MHL scores (2.4 ± 0.8). In addition, five metabotype models were developed based on 26 variables: Westernized Millennial (28.6%), healthy (25.1%), active Mediterranean (16.5%), dysmetabolic/pre-morbid (11.5%), and metabolically vulnerable/pro-morbid (18.3%). Conclusions: The support of tools related to precision nutrition and lifestyle integrates well-being characteristics and contributes to reducing the impact of unhealthy lifestyle habits with practical implications for primary care. Combining lifestyle, metabolic, and quality of life traits will facilitate personalized precision interventions and the implementation of targeted public health policies. [ABSTRACT FROM AUTHOR]

Mounting evidence progressively appreciates the vital interplay between immunity and metabolism in a wide array of immunometabolic chronic disorders, both autoimmune and non-autoimmune mediated. The immune system regulates the functioning of cellular metabolism within organs like the brain, pancreas and/or adipose tissue by sensing and adapting to fluctuations in the microenvironment's nutrients, thereby reshaping metabolic pathways that greatly impact a pro- or antiinflammatory immunophenotype. While it is agreed that the immune system relies on an adequate nutritional status to function properly, we are only just starting to understand how the supply of single or combined nutrients, all of them termed immunonutrients, can steer immune cells towards a less inflamed, tolerogenic immunophenotype. Polyphenols, a class of secondary metabolites abundant in Mediterranean foods, are pharmacologically active natural products with outstanding immunomodulatory actions. Upon binding to a range of receptors highly expressed in immune cells (e.g. AhR, RAR, RLR), they act in immunometabolic pathways through a mitochondria-centered multi-modal approach. First, polyphenols activate nutrient sensing via stress-response pathways, essential for immune responses. Second, they regulate mammalian target of rapamycin (mTOR)/AMP-activated protein kinase (AMPK) balance in immune cells and are well-tolerated caloric restriction mimetics. Third, polyphenols interfere with the assembly of NLR family pyrin domain containing 3 (NLRP3) in endoplasmic reticulum-mitochondria contact sites, inhibiting its activation while improving mitochondrial biogenesis and autophagosomelysosome fusion. Finally, polyphenols impact chromatin remodeling and coordinates both epigenetic and metabolic reprogramming. This work moves beyond the well-documented antioxidant properties of polyphenols, offering new insights into the multifaceted nature of these compounds. It proposes a mechanistical appraisal on the regulatory pathways through which polyphenols modulate the immune response, thereby alleviating chronic low-grade inflammation. Furthermore, it draws parallels between pharmacological interventions and polyphenol-based immunonutrition in their modes of immunomodulation across a wide spectrum of socioeconomically impactful immunometabolic diseases such as Multiple Sclerosis, Diabetes (type 1 and 2) or even Alzheimer's disease. Lastly, it discusses the existing challenges that thwart the translation of polyphenols-based immunonutritional interventions into long-term clinical studies. Overcoming these limitations will undoubtedly pave the way for improving precision nutrition protocols and provide personalized guidance on tailored polyphenol-based immunonutrition plans. [ABSTRACT FROM AUTHOR]

Drosophila melanogaster is unique among animal models because it has a fully defined synthetic diet available to study nutrient-gene interactions. However, use of this diet is limited to adult studies due to impaired larval development and survival. Here, we provide an adjusted formula that reduces the developmental period, restores fat levels, enhances body mass, and fully rescues survivorship without compromise to adult lifespan. To demonstrate an application of this formula, we explored pre-adult diet compositions of therapeutic potential in a model of an inherited metabolic disorder affecting the metabolism of branched-chain amino acids. We reveal rapid, specific, and predictable nutrient effects on the disease state consistent with observations from mouse and patient studies. Together, our diet provides a powerful means with which to examine the interplay between diet and metabolism across all life stages in an animal model. [ABSTRACT FROM AUTHOR]

Animals often regulate the intake and quantity of nutrients to maximise fitness through life‐history traits such as lifespan, but we still lack a proper understanding of how specific nutrients influence these traits. Here, I developed an algorithm which allowed me to create a nutrient‐specific database from literature data, and investigated how the requirements of protein (P) and carbohydrate (C) needed to maximise lifespan evolved across nine insect species. I found moderate evidence of a phylogenetic signal on the optimal ratio of protein to carbohydrate ratio (PC ratio) that maximised lifespan, suggesting that optimal PC ratio for lifespan could have evolved non‐independently among related species. I also found evidence for weak‐to‐strong sex‐specific optimal PC ratios for lifespan, suggesting that sex‐specific nutritional needs to maximise lifespan can emerge and persist in some species. Although limited in the number of species, the approach adopted here is portable to experiments with n number of nutrients and, thus, can be used in complex comparative precision nutrition studies for insights into the evolution of animal nutrition. [ABSTRACT FROM AUTHOR]

The importance of diet and lifestyle in maintaining overall health has long been recognised. MicroRNAs (miRNAs) have emerged as key players in the intricate interplay between health and disease. This study, including 305 participants, examined the role of miRNAs from capillary blood as indicators of individual physiological characteristics, diet, and lifestyle influences. Key findings include specific miRNAs associated with inflammatory processes and dietary patterns. Notably, miR-155 was associated with subjects with metabolic diseases and upregulated in age. Additionally, the study revealed diet-related miRNA expressions: high consumption of vegetables, fruits, and whole grains correlated with increased levels of miR-let-7a and miR-328, both implicated in anti-inflammatory pathways, and decreased expression of pro-inflammatory miR-21. In the context of smoking, we found a significant decrease in miRNA-142, known for its downregulation in lung cancer. We observed a sex-biased expression of various miRNAs with significant upregulation of miR-151a in females and a higher expression of miR-155 in ageing females, representing a possible mechanism for the increased susceptibility to autoimmune diseases. In conclusion, the study underscores the significant influence of lifestyle, nutrition, and sex on miRNA profiles. Circulating miRNAs demonstrate significant potential as biomarkers in personalized medicine, highlighting their utility in tailoring healthcare to individual needs. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objectives: Innovative precision dietary procedures are required to promote healthy aging. This study aimed to evaluate the effects of a personalised strategy based on the inclusion of individualised foods and digital tools on overall health status and quality of life within a follow-up of 3 months in older adults with overweight or obesity. Methods: 127 men and women aged between 50 and 80 years with overweight/obesity participated in the study—between January 2020 and September 2020 at the Center for Nutrition Research-University of Navarra and IMDEA-ALIMENTACIÓN—and were randomly assigned to a usual-care group (standard recommendations) or precision group (precision nutrition strategy based on the inclusion of individualised foods and a mobile application). Anthropometry, body fat percentage, biochemical parameters, diet, and quality of life (SF-36 Health Survey) were assessed at baseline and after 3 months. Results: Both strategies were found to improve overall metabolic health; however, the precision approach demonstrated significantly better outcomes. The precision strategy reduced body weight at 3 months (−4.3 kg; p

In recent years there has been increased interest in identifying biological signatures of food consumption for use as biomarkers. Traditional metabolomics-based biomarker discovery approaches rely on multivariate statistics which cannot differentiate between host- and food-derived compounds, thus novel approaches to biomarker discovery are required to advance the field. To this aim, we have developed a new method that combines global untargeted stable isotope traced metabolomics and a machine learning approach to identify biological signatures of cruciferous vegetable consumption. Participants consumed a single serving of broccoli (n = 16), alfalfa sprouts (n = 16) or collard greens (n = 26) which contained either control unlabeled metabolites, or that were grown in the presence of deuterium-labeled water to intrinsically label metabolites. Mass spectrometry analysis indicated 133 metabolites in broccoli sprouts and 139 metabolites in the alfalfa sprouts were labeled with deuterium isotopes. Urine and plasma were collected and analyzed using untargeted metabolomics on an AB SCIEX TripleTOF 5,600 mass spectrometer. Global untargeted stable isotope tracing was completed using openly available software and a novel random forest machine learning based classifier. Among participants who consumed labeled broccoli sprouts or collard greens, 13 deuterium-incorporated metabolomic features were detected in urine representing 8 urine metabolites. Plasma was analyzed among collard green consumers and 11 labeled features were detected representing 5 plasma metabolites. These deuterium-labeled metabolites represent potential biological signatures of cruciferous vegetables consumption. Isoleucine, indole-3-acetic acid-N-O-glucuronide, dihydrosinapic acid were annotated as labeled compounds but other labeled metabolites could not be annotated. This work presents a novel framework for identifying biological signatures of food consumption for biomarker discovery. Additionally, this work presents novel applications of metabolomics and machine learning in the life sciences.

Based on the essential fatty acids (EFA) precision nutrition, a blend oil (BO) of fish oil and terrestrial oils was developed, and applied successfully to the low marine diets of golden pompano (Trachinotus ovatus). To evaluate whether medium- and short-chain fatty acids (MCFA and SCFA), efficient energy supplements for animals, can spare the dietary EFA, four iso-proteic (48%) and iso-lipidic (11%) low fishmeal (FM) diets (D1-D4, contained 6% FM) were formulated and fed T. ovatus juveniles (initial weight ∼8.50 g) for 9 weeks in sea cages. Control diets (D1) contained 8% BO, while the BO of diets D2-D4 were replaced 50% with coconut oil, coconut oil + sodium butyrate, and coconut oil + n-3 LC-PUFA enriched oil, respectively. The results showed that compared to the D1 group, the growth performance of D2 and D3 were significantly lower, while a comparable growth was detected in the D4 group. The muscle and hepatic n-3 PUFA levels in the D2 and D3 groups were significantly low, and these fatty acid contents were modified in the D4 group. Meanwhile, the muscle textural firmness of the D2-D4 groups was decreased. Regarding the health index of fish, compared to the D1 group, high serum triglyceride (TG) contents and low HDL/LDL ratio were detected in the D2-D4 groups, and high ACP, AST, and ALT activities were observed in these groups. Meanwhile, high HSI and low hepatic enzymatic activities of CAT and ALT were measured in the D2-D3 groups. Additionally, the mRNA levels of hepatic fatty acid synthesis-related genes (fas, acc, and pparγ) were significantly increased in D2-D4 groups, and the expression levels of lipid catabolism genes (cpt-1 and lpl) showed an upward trend. Moreover, the D2 group exhibited the lowest intestinal wall thickness, the mRNA levels of intestine anti-inflammatory cytokines (il-10) were up-regulated in the D2-D4 groups, and the highest mRNA levels of pro-inflammatory cytokines (il-8) were detected in the D2 group. In conclusion, the EFA deficiency leads to a decline in the growth and muscle quality of T. ovatus fed low marine diets, which cannot be mitigated by the addition of medium-short chain fatty acids. The results indicated that MCFA and SCFA cannot spare the EFA of low marine diets in T. ovatus.