Soilless cultivation systems to produce tailored microgreens for specific nutritional needs

BACKGROUND

The awareness of the importance of following dietary recommendations that meet specific biological requirements related to an individual's health status has significantly increased interest in personalized nutrition. The aim of this research was to test agronomic protocols based on soilless cultivation for providing consumers with new dietary sources of iodine (I), as well as alternative vegetable products to limit dietary potassium (K) intake; proposed cultivation techniques were evaluated according to their suitability to obtain such products without compromising agronomic performance.

RESULTS

Two independent experiments, focused on I and K respectively, were conducted in a commercial greenhouse specializing in soilless production. Four different species were cultivated using three distinct concentrations of I (0, 1.5 and 3 mg L-1 ) and K (0, 60 and 120 mg L-1 ). Microgreens grown in I-rich nutrient solution accumulate more I, and the increase is dose-dependent. Compared to unbiofortified microgreens, the treatments with 1.5 and 3 mg L-1 of I resulted in 4.5 and 14 times higher I levels, respectively. Swiss chard has the highest levels of K (14 096 mg kg-1 of FW), followed by rocket, pea and radish. In radish, rocket and Swiss chard, a total reduction of K content in the nutrient solution (0 mg L-1 ) resulted in an average reduction of 45% in K content.

CONCLUSION

It is possible to produce I-biofortified microgreens to address I deficiency, and K-reduced microgreens for chronic kidney disease-affected people. Species selection is crucial to customize nutritional profiles according to specific dietary requirements due to substantial mineral content variations across different species. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

A health technology assessment of personalized nutrition interventions using the EUnetHTA HTA Core Model

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/m2. 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.

Understanding and applying gene-environment interactions: a guide for nutrition professionals with an emphasis on integration in African research settings

Noncommunicable diseases (NCDs) are influenced by the interplay between genetics and environmental exposures, particularly diet. However, many healthcare professionals, including nutritionists and dietitians, have limited genetic background and, therefore, they may lack understanding of gene-environment interactions (GxEs) studies. Even researchers deeply involved in nutrition studies, but with a focus elsewhere, can struggle to interpret, evaluate, and conduct GxE studies. There is an urgent need to study African populations that bear a heavy burden of NCDs, demonstrate unique genetic variability, and have cultural practices resulting in distinctive environmental exposures compared with Europeans or Americans, who are studied more. Although diverse and rapidly changing environments, as well as the high genetic variability of Africans and difference in linkage disequilibrium (ie, certain gene variants are inherited together more often than expected by chance), provide unparalleled potential to investigate the omics fields, only a small percentage of studies come from Africa. Furthermore, research evidence lags behind the practices of companies offering genetic testing for personalized medicine and nutrition. We need to generate more evidence on GxEs that also considers continental African populations to be able to prevent unethical practices and enable tailored treatments. This review aims to introduce nutrition professionals to genetics terms and valid methods to investigate GxEs and their challenges, and proposes ways to improve quality and reproducibility. The review also provides insight into the potential contributions of nutrigenetics and nutrigenomics to the healthcare sphere, addresses direct-to-consumer genetic testing, and concludes by offering insights into the field's future, including advanced technologies like artificial intelligence and machine learning.

Potential Mechanisms of Precision Nutrition-Based Interventions for Managing Obesity

Precision nutrition (PN) considers multiple individual-level and environmental characteristics or variables to better inform dietary strategies and interventions for optimizing health, including managing obesity and metabolic disorders. Here, we review the evidence on potential mechanisms-including ones to identify individuals most likely to respond-that can be leveraged in the development of PN interventions addressing obesity. We conducted a review of the literature and included laboratory, animal, and human studies evaluating biochemical and genetic data, completed and ongoing clinical trials, and public programs in this review. Our analysis describes the potential mechanisms related to 6 domains including genetic predisposition, circadian rhythms, physical activity and sedentary behavior, metabolomics, the gut microbiome, and behavioral and socioeconomic characteristics, i.e., the factors that can be leveraged to design PN-based interventions to prevent and treat obesity-related outcomes such as weight loss or metabolic health as laid out by the NIH 2030 Strategic Plan for Nutrition Research. For example, single nucleotide polymorphisms can modify responses to certain dietary interventions, and epigenetic modulation of obesity risk via physical activity patterns and macronutrient intake have also been demonstrated. Additionally, we identified limitations including questions of equitable implementation across a limited number of clinical trials. These include the limited ability of current PN interventions to address systemic influences such as supply chains and food distribution, healthcare systems, racial or cultural inequities, and economic disparities, particularly when designing and implementing PN interventions in low- and middle-income communities. PN has the potential to help manage obesity by addressing intra- and inter-individual variation as well as context, as opposed to "one-size fits all" approaches though there is limited clinical trial evidence to date.

Adaptation of nutritional risk screening tools may better predict response to nutritional treatment: a secondary analysis of the randomized controlled trial Effect of early nutritional therapy on Frailty, Functional Outcomes, and Recovery of malnourished medical inpatients Trial (EFFORT)

BACKGROUND

Nutritional screening tools have proven valuable for predicting clinical outcomes but have failed to determine which patients would be most likely to benefit from nourishment interventions. The Nutritional Risk Screening 2002 (NRS) and the Mini Nutritional Assessment (MNA) are 2 of these tools, which are based on both nutritional parameters and parameters reflecting disease severity.

OBJECTIVES

We hypothesized that the adaptation of nutritional risk scores, by removing parameters reflecting disease severity, would improve their predictive value regarding response to a nutritional intervention while providing similar prognostic information regarding mortality at short and long terms.

METHODS

We reanalyzed data of 2028 patients included in the Swiss-wide multicenter, randomized controlled trial EFFORT (Effect of early nutritional therapy on Frailty, Functional Outcomes, and Recovery of malnourished medical inpatients Trial) comparing individualized nutritional support with usual care nutrition in medical inpatients. The primary endpoint was 30-d all-cause mortality.

RESULTS

Although stratifying patients by high compared with low NRS score showed no difference in response to nutritional support, patients with high adapted NRS showed substantial benefit, whereas patients with low adapted NRS showed no survival benefit [adjusted hazard ratio: 0.55 [95% confidence interval (CI): 0.37, 0.80]] compared with 1.17 (95% CI: 0.70, 1.93), a finding that was significant in an interaction analysis [coefficient: 0.48 (95% CI: 0.25, 0.94), P = 0.031]. A similar effect regarding treatment response was found when stratifying patients on the basis of MNA compared with the adapted MNA. Regarding the prognostic performance, both original scores were slightly superior in predicting mortality than the adapted scores.

CONCLUSIONS

Adapting the NRS and MNA by including nutritional parameters only improves their ability to predict response to a nutrition intervention, but slightly reduces their overall prognostic performance. Scores dependent on disease severity may best be considered prognostic scores, whereas nutritional risk scores not including parameters reflecting disease severity may indeed improve a more personalized treatment approach for nourishment interventions. The trial was registered at clinicaltrials.gov as NCT02517476.

Effects of a Novel Applet-Based Personalized Dietary Intervention on Dietary Intakes: A Randomized Controlled Trial in a Real-World Scenario

The objective of this study was to assess the feasibility and effectiveness of a novel WeChat applet-based personalized dietary intervention aimed at promoting healthier dietary intakes. A two-arm parallel, randomized, controlled trial was conducted in a real-world scenario and involved a total of 153 participants (the intervention group, n = 76; the control group, n = 77), lasting for 4 months in Shanghai, China. The intervention group had access to visualized nutrition evaluations through the applet during workday lunch time, while the control group received no interventions. A total of 3413 lunch dietary intake records were captured through the applet. Linear mixed models were utilized to assess the intervention effects over time. At baseline, the participants' lunchtime dietary intakes were characterized by insufficient consumption of plant foods (86.9% of the participants) and excessive intake of animal foods (79.7% of the participants). Following the commencement of the intervention, the intervention group showed a significant decrease in the animal/plant food ratio (β = -0.03/week, p = 0.024) and the consumption of livestock and poultry meat (β = -1.80 g/week, p = 0.035), as well as a borderline significant increase in the consumption of vegetables and fruits (β = 3.22 g/week, p = 0.055) and plant foods (β = 3.26 g/week, p = 0.057) over time at lunch compared to the control group. The applet-based personalized dietary intervention was feasible and effective in improving dietary intakes and, consequently, possibly may manage body weight issues in real-world scenarios.

The Impact of Glucomannan, Inulin, and Psyllium Supplementation (SolowaysTM) on Weight Loss in Adults with FTO, LEP, LEPR, and MC4R Polymorphisms: A Randomized, Double-Blind, Placebo-Controlled Trial

This study aimed to determine the impact of a fiber supplement on body weight and composition in individuals with obesity with specific genetic polymorphisms. It involved 112 adults with obesity, each with at least one minor allele in the FTO, LEP, LEPR, or MC4R polymorphism. Participants were randomized to receive either a fiber supplement (glucomannan, inulin, and psyllium) or a placebo for 180 days. The experimental group showed significant reductions in body weight (treatment difference: -4.9%; 95% CI: -6.9% to -2.9%; p < 0.01) and BMI (treatment difference: -1.4 kg/m2; 95% CI: -1.7 to -1.2; p < 0.01) compared to placebo. Further significant decreases in fat mass (treatment difference: -13.0%; 95% CI: -14.4 to -11.7; p < 0.01) and visceral fat rating (treatment difference: -1.3; 95% CI: -1.6 to -1.0; p < 0.01) were noted. Homozygous minor allele carriers experienced greater decreases in body weight (treatment difference: -3.2%; 95% CI: -4.9% to -1.6%; p < 0.01) and BMI (treatment difference: -1.2 kg/m2; 95% CI: -2.0 to -0.4; p < 0.01) compared to heterozygous allele carriers. These carriers also had a more significant reduction in fat mass (treatment difference: -9.8%; 95% CI: -10.6 to -9.1; p < 0.01) and visceral fat rating (treatment difference: -0.9; 95% CI: -1.3 to -0.5; p < 0.01). A high incidence of gastrointestinal events was reported in the experimental group (74.6%), unlike the placebo group, which reported no side effects. Dietary supplementation with glucomannan, inulin, and psyllium effectively promotes weight loss and improves body composition in individuals with obesity, particularly those with specific genetic polymorphisms.

Effect of Personalized Sodium Replacement on Fluid and Sodium Balance and Thermophysiological Strain During and After Ultraendurance Running in the Heat

PURPOSE

To investigate the effect of personalized sweat sodium replacement on drinking behavior, sodium and water balance, and thermophysiological responses during and after ultraendurance running in hot conditions.

METHODS

Nine participants (7 male, 2 female) completed two 5-hour treadmill runs (60% maximum oxygen uptake, 30°C ambient temperature), in a double-blind randomized crossover design, consuming sodium chloride (SODIUM) capsules to replace 100% of previously assessed losses or placebo (PLACEBO). Fluid was consumed ad libitum.

RESULTS

No effect of SODIUM was observed for ad libitum fluid intake or net fluid balance (P > .05). Plasma sodium concentration increased in both trials, but to a greater extent in SODIUM at 2.5 hours (mean [SD]: 4 [4] mmol·L-1 vs 1 [5] mmol·L-1; P < .05) and postexercise (4 [3] mmol·L-1 vs 1 [5] mmol·L-1; P < .05). Plasma volume change was not different between trials (P > .05) but was strongly correlated with sodium balance in SODIUM (r = .880, P < .01). No effect of sodium replacement was observed for heart rate, rectal temperature, thermal comfort, perceived exertion, or physiological strain index. During the 24 hours postexercise, ad libitum fluid intake was greater following SODIUM (2541 [711] mL vs 1998 [727] mL; P = .04), as was urinary sodium excretion (NaCl: 66 [35] mmol, Pl: 21 [12] mmol; P < .01).

CONCLUSIONS

Personalized sweat sodium replacement during ultraendurance running in hot conditions, with ad libitum fluid intake, exacerbated the rise in plasma sodium concentration compared to no sodium replacement but did not substantially influence overall body-water balance or thermophysiological strain. A large sodium deficit incurred during exercise leads to substantial renal sodium conservation postexercise.

Genetic Variability Impacts Genotoxic and Transcriptome Responses in the Human Colon after the Consumption of Processed Red Meat Products and Those with Added Phytochemical Extracts

The PHYTOME study investigated the effect of consuming processed meat products on outcomes related to colorectal cancer risk without testing the impact of genetic variability on these responses. This research aims to elucidate the genetic impact on apparent total N-nitroso compound (ATNC) excretion, colonic DNA adduct formation, ex vivo-induced DNA damage, and gene expression changes in colon biopsies of healthy participants. Through a systematic literature review, candidate polymorphisms were selected and then detected using TaqMan and PCR analysis. The effect of genotype on study outcomes was determined via a linear mixed model and analysis of variance. Machine learning was used to evaluate relative allele importance concerning genotoxic responses, which established a ranking of the most protective alleles and a combination of genotypes (gene scores). Participants were grouped by GSTM1 genotype and differentially expressed genes (DEGs), and overrepresented biological pathways were compared between groups. Stratifying participants by ten relevant genes revealed significant variations in outcome responses. After consumption of processed red meat, variations in NQO1 and COMT impacted responses in ATNC levels (µmol/L) (+9.56 for wildtype vs. heterozygous) and DNA adduct levels (pg/µg DNA) (+1.26 for variant vs. wildtype and +0.43 for variant vs. heterozygous), respectively. After phytochemicals were added to the meat, GSTM1 variation impacted changes in DNA adduct levels (-6.12 for deletion vs. wildtype). The gene scores correlated with these responses and DEGs were identified by GSTM1 genotype. The altered pathways specific to the GSTM1 wildtype group included 'metabolism', 'cell cycle', 'vitamin D receptor', and 'metabolism of water-soluble vitamins and co-factors'. Genotype impacted both the potential genotoxicity of processed red meat and the efficacy of protective phytochemical extracts.

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

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

Data-driven analysis and prediction of dynamic postprandial metabolic response to multiple dietary challenges using dynamic mode decomposition

Motivation

In the field of precision nutrition, predicting metabolic response to diet and identifying groups of differential responders are two highly desirable steps toward developing tailored dietary strategies. However, data analysis tools are currently lacking, especially for complex settings such as crossover studies with repeated measures.Current methods of analysis often rely on matrix or tensor decompositions, which are well suited for identifying differential responders but lacking in predictive power, or on dynamical systems modeling, which may be used for prediction but typically requires detailed mechanistic knowledge of the system under study. To remedy these shortcomings, we explored dynamic mode decomposition (DMD), which is a recent, data-driven method for deriving low-rank linear dynamical systems from high dimensional data.Combining the two recent developments "parametric DMD" (pDMD) and "DMD with control" (DMDc) enabled us to (i) integrate multiple dietary challenges, (ii) predict the dynamic response in all measured metabolites to new diets from only the metabolite baseline and dietary input, and (iii) identify inter-individual metabolic differences, i.e., metabotypes. To our knowledge, this is the first time DMD has been applied to analyze time-resolved metabolomics data.

Results

We demonstrate the potential of pDMDc in a crossover study setting. We could predict the metabolite response to unseen dietary exposures on both measured (R2 = 0.40) and simulated data of increasing size (R max 2 = 0.65), as well as recover clusters of dynamic metabolite responses. We conclude that this method has potential for applications in personalized nutrition and could be useful in guiding metabolite response to target levels.

Availability and implementation

The measured data analyzed in this study can be provided upon reasonable request. The simulated data along with a MATLAB implementation of pDMDc is available at https://github.com/FraunhoferChalmersCentre/pDMDc.

Effects of different foods and cooking methods on the gut microbiota: an in vitro approach

To support personalized diets targeting the gut microbiota, we employed an in vitro digestion-fermentation model and 16S rRNA gene sequencing to analyze the microbiota growing on representative foods of the Mediterranean and Western diets, as well as the influence of cooking methods. Plant- and animal-derived foods had significantly different impacts on the abundances of bacterial taxa. Animal and vegetable fats, fish and dairy products led to increases in many taxa, mainly within the Lachnospiraceae. In particular, fats favored increases in the beneficial bacteria Faecalibacterium, Blautia, and Roseburia. However, butter, as well as gouda cheese and fish, also resulted in the increase of Lachnoclostridium, associated to several diseases. Frying and boiling produced the most distinct effects on the microbiota, with members of the Lachnospiraceae and Ruminococcaceae responding the most to the cooking method employed. Nevertheless, cooking effects were highly individualized and food-dependent, challenging the investigation of their role in personalized diets.

Human Nutrition Research in the Data Era: Results of 11 Reports on the Effects of a Multiple-Micronutrient-Intervention Study

Large datasets have been used in molecular and genetic research for decades, but only a few studies have included nutrition and lifestyle factors. Our team conducted an n-of-1 intervention with 12 vitamins and five minerals in 9- to 13-year-old Brazilian children and teens with poor healthy-eating indices. A unique feature of the experimental design was the inclusion of a replication arm. Twenty-six types of data were acquired including clinical measures, whole-genome mapping, whole-exome sequencing, and proteomic and a variety of metabolomic measurements over two years. A goal of this study was to use these diverse data sets to discover previously undetected physiological effects associated with a poor diet that include a more complete micronutrient composition. We summarize the key findings of 11 reports from this study that (i) found that LDL and total cholesterol and fasting glucose decreased in the population after the intervention but with inter-individual variation; (ii) associated a polygenic risk score that predicted baseline vitamin B12 levels; (iii) identified metabotypes linking diet intake, genetic makeup, and metabolic physiology; (iv) found multiple biomarkers for nutrient and food groups; and (v) discovered metabolites and proteins that are associated with DNA damage. This summary also highlights the limitations and lessons in analyzing diverse omic data.

Obesity-Resistant Mice on a High-Fat Diet Display a Distinct Phenotype Linked to Enhanced Lipid Metabolism

Individually, metabolic variations can significantly influence predisposition to obesity in the form of the obesity-prone (super-responders) and obesity-resistant (non-responders) phenotypes in response to modern calorie-dense diets. In this study, C57BL/6J mice (n = 76) were randomly assigned to either a low-fat diet (LFD) or a high-fat diet (HFD) for 6 weeks, followed by selection of the normally obese (HFD), non-responders (NR), super-responders (SR), or super-responders switched back to the low-fat diet (SR-LFD) for an additional 8 weeks. SR mice showed the highest gains in body weight, lean and fat body mass, and total and free water, in part due to increased feed efficiency, despite having a respiratory exchange ratio (RER) similar to that of NR mice. A switch to the LFD was sufficient to revert most of the observed physiological changes in the SR-LFD mice; however, voluntary physical activity and exercise capacity did not return to the basal level. NR mice showed the highest food intake, lowest feed efficiency, increased oxygen consumption during the light (rest) cycle, increased physical activity during the dark (active) cycle, and increased heat production during both cycles. These variations were observed in the absence of changes in food intake and fecal parameters; however, NR fecal lipid content was lower, and the NR fecal microbiome profile was characterized by reduced abundance of Actinobacteria. Taken together, our findings suggest that NR mice showed an increased ability to metabolize excessive dietary fats in skeletal muscle at the expense of reduced exercise capacity that persisted for the duration of the study. These findings underscore the need for further comprehensive investigations into the mechanisms of obesity resistance, as they hold potential implications for weight-loss strategies in human subjects.

Inflammation and response to nutrition interventions

The complex interplay between nutrition and inflammation has become a major focus of research in recent years across different clinical settings and patient populations. Inflammation has been identified as a key driver for disease-related malnutrition promoting anorexia, reduced food intake, muscle loss, and on a cellular level, insulin resistance, which together stimulate catabolism. However, these effects may well be bidirectional, and there is strong evidence showing that nutrition influences inflammation. Several single nutrients and dietary patterns with either proinflammatory or anti-inflammatory properties have been studied, such as the long-chain ω-3 fatty acids eicosapentaenoic acid or docosahexaenoic acid. The Mediterranean diet combines several such nutrients and has been shown to improve medical outcomes in the outpatient setting. In addition, there is increasing evidence suggesting that inflammation affects the metabolism and modulates the response to nutrition support interventions. In fact, recent studies from the medical inpatient setting suggest that inflammation, mirrored by high levels of C-reactive protein, diminishes the positive effects of nutrition support. This may explain the lack of positive effects of some nutrition trials in severely ill patients, whereas similar approaches to nutritional support have shown positive results in less severely ill patients. The use of biomarkers, such as C-reactive protein, may help to identify patients with a lower response to nutrition, in whom other treatment options need to be used. There is need for additional research to understand how to best address the malnourished patient with inflammation by specifically lowering inflammation through anti-inflammatory medical treatments and/or nutrition interventions.

Imprecision nutrition? Duplicate meals result in unreliable individual glycemic responses measured by continuous glucose monitors across four dietary patterns in adults without diabetes

Background

Continuous glucose monitors (CGMs) are being used to characterize postprandial glycemic responses and thereby provide personalized dietary advice to minimize glycemic excursions. However, the efficacy of such advice depends on reliable CGM responses.

Objective

To explore within-subject variability of CGM responses to duplicate meals in an inpatient setting.

Methods

CGM data were collected in two controlled feeding studies (NCT03407053 and NCT03878108) in 30 participants without diabetes capturing 1056 meal responses in duplicate ~1 week apart from four dietary patterns. One study used two different CGMs (Abbott Freestyle Libre Pro and Dexcom G4 Platinum) whereas the other study used only Dexcom. We calculated the incremental area under the curve (iAUC) for each 2-h post-meal period and compared within-subject iAUCs using the same CGM for the duplicate meals using linear correlations, intra-class correlation coefficients (ICC), Bland-Altman analyses, and compared individual variability of glycemic responses to duplicate meals versus different meals using standard deviations (SDs).

Results

There were weak to moderate positive linear correlations between within- subject iAUCs for duplicate meals (Abbott r=0.47, p<0.0001, Dexcom r=0.43, p<0.0001), with low within-participant reliability indicated by ICC (Abbott 0.31, Dexcom 0.14). Bland-Altman analyses indicated wide limits of agreement (Abbott -31.3 to 31.5 mg/dL, Dexcom -30.8 to 30.4 mg/dL) but no significant bias of mean iAUCs for duplicate meals (Abbott 0.1 mg/dL, Dexcom -0.2 mg/dL). Individual variability of glycemic responses to duplicate meals was similar to that of different meals evaluated each diet week for both Abbott (SDduplicate = 10.7 mg/dL , SDweek 1 =12.4 mg/dL, SDweek 2 =11.6 mg/dL, p=0.38) and Dexcom (SDduplicate = 11.1 mg/dL, SDweek 1 = 11.5 mg/dL, SDweek 2 =11.9 mg/dL, p=0.60).

Conclusions

Individual postprandial CGM responses to duplicate meals were unreliable in adults without diabetes. Personalized diet advice based on CGM measurements in adults without diabetes requires more reliable methods involving aggregated repeated measurements.

Functional profiling of gut microbial and immune responses toward different types of dietary fiber: a step toward personalized dietary interventions

Dietary fiber plays a crucial role in maintaining gut and overall health. The objective of this study was to investigate whether different types of dietary fiber elicited specific changes in gut microbiota composition and the production of short-chain fatty acids. To test this, a longitudinal crossover study design was employed, in which healthy adult women consumed three distinct dietary fiber supplements: Inulin (fructo-oligosaccharide), Vitafiber (isomalto-oligosaccharide), and Fibremax (mixture of different fiber) during a one-week intervention period, followed by a 2-week washout period. A total of 15 g of soluble fiber was consumed daily for each supplement. Samples were collected before and after each intervention to analyze the composition of the gut microbiota by 16S rRNA sequencing and fecal levels of short-chain fatty acids measured using nuclear magnetic resonance. Phenotypic changes in peripheral blood mononuclear cells were studied in subsets of participants with higher SCFA levels post-intervention using spectral flow cytometry. The results revealed substantial stability and resilience of the overall gut bacterial community toward fiber-induced changes. However, each supplement had specific effects on gut bacterial alpha and beta diversity, SCFA production, and immune changes. Inulin consistently exerted the most pronounced effect across individuals and certain taxa were identified as potential indicators of SCFA production in response to inulin supplementation. This distinguishing feature was not observed for the other fiber supplements. Further large-scale studies are required to confirm these findings. Overall, our study implies that personalized dietary fiber intervention could be tailored to promote the growth of beneficial bacteria to maximize SCFA production and associated health benefits.

Design, analysis, and interpretation of treatment response heterogeneity in personalized nutrition and obesity treatment research

It is increasingly assumed that there is no one-size-fits-all approach to dietary recommendations for the management and treatment of chronic diseases such as obesity. This phenomenon that not all individuals respond uniformly to a given treatment has become an area of research interest given the rise of personalized and precision medicine. To conduct, interpret, and disseminate this research rigorously and with scientific accuracy, however, requires an understanding of treatment response heterogeneity. Here, we define treatment response heterogeneity as it relates to clinical trials, provide statistical guidance for measuring treatment response heterogeneity, and highlight study designs that can quantify treatment response heterogeneity in nutrition and obesity research. Our goal is to educate nutrition and obesity researchers in how to correctly identify and consider treatment response heterogeneity when analyzing data and interpreting results, leading to rigorous and accurate advancements in the field of personalized medicine.

Effects of an Individualized vs. Standardized Vitamin D Supplementation on the 25(OH)D Level in Athletes

Vitamin D is crucial to the health and performance of athletes. Although the exact vitamin D requirements for athletes have not been established, maintaining a 25(OH)D level of at least 40 ng/mL is considered beneficial. This randomized controlled intervention study aimed to determine whether an individual loading dose formula for vitamin D supplementation is more effective than standardized supplementation and suitable enough for athletes to meet a target value of 40 ng/mL. In a 10-week supplementation study conducted during the winter months in Germany, 90 athletes with insufficient vitamin D levels (25(OH)D < 30 ng/mL) were randomly assigned to receive either a universal dose of 2000 IU/day of vitamin D or a loading dose of 4000 IU/day, followed by a maintenance dose of 1000 IU/day. The total 25(OH)D concentration was measured from dried blood spots at three time points: at baseline, at the computed date of 40 ng/mL, and after the 10-week period. Additionally, a vitamin-D-specific questionnaire was issued. On the day when 25(OH)D blood concentrations of 40 ng/mL were calculated to prevail, the individualized group had a significantly higher 25(OH)D level than the standardized group (41.1 ± 10.9 ng/mL vs. 32.5 ± 6.4 ng/mL, p < 0.001). This study demonstrated that the examined formula is suitable enough for athletes to achieve a 25(OH)D concentration of 40 ng/mL. This indicates that a personalized approach is more effective than a one-size-fits-all approach in restoring adequate vitamin D levels in athletes.

Nutrigenomics: SNPs Correlated to Lipid and Carbohydrate Metabolism

Background

Nutrigenomics - the study of the interactions between genetics and nutrition - has emerged as a pivotal field in personalized nutrition. Among various genetic variations, single-nucleotide polymorphisms (SNPs) have been extensively studied for their probable relationship with metabolic traits.

Methods

Throughout this review, we have employed a targeted research approach, carefully handpicking the most representative and relevant articles on the subject. Our methodology involved a systematic review of the scientific literature to ensure a comprehensive and accurate overview of the available sources.

Results

SNPs have demonstrated a significant influence on lipid metabolism, by impacting genes that encode for enzymes involved in lipid synthesis, transport, and storage. Furthermore, they have the ability to affect enzymes in glycolysis and insulin signaling pathways: in a way, they can influence the risk of type 2 diabetes. Thanks to recent advances in genotyping technologies, we now know numerous SNPs linked to lipid and carbohydrate metabolism. The large-scale studies on this topic have unveiled the potential of personalized dietary recommendations based on an individual's genetic makeup. Personalized nutritional interventions hold promise to mitigate the risk of various chronic diseases; however, translating these scientific insights into actionable dietary guidelines is still challenging.

Conclusions

As the field of nutrigenomics continues to evolve, collaborations between geneticists, nutritionists, and healthcare providers are essential to harness the power of genetic information for improving metabolic health. By unraveling the genetic basis of metabolic responses to diet, this field holds the potential to revolutionize how we approach dietary recommendations and preventive healthcare practices.

Structural, rheological, and gelling characteristics of starch-based materials in context to 3D food printing applications in precision nutrition

Starch-based materials have viscoelasticity, viscous film-forming, dough pseudoplasticity, and rheological properties, which possess the structural characteristics (crystal structure, double helix structure, and layered structure) suitable for three-dimensional (3D) food printing inks. 3D food printing technology has significant advantages in customizing personalized and precise nutrition, expanding the range of ingredients, designing unique food appearances, and simplifying the food supply chain. Precision nutrition aims to consider individual nutritional needs and individual differences, which include special food product design and personalized precise nutrition, thus expanding future food resources, then simplifying the food supply chain, and attracting extensive attention in food industry. Different types of starch-based materials with different structures and rheological properties meet different 3D food printing technology requirements. Starch-based materials suitable for 3D food printing technology can accurately deliver and release active substances or drugs. These active substances or drugs have certain regulatory effects on the gut microbiome and diabetes, so as to maintain personalized and accurate nutrition.

Differential Responders to a Mixed Meal Tolerance Test Associated with Type 2 Diabetes Risk Factors and Gut Microbiota-Data from the MEDGI-Carb Randomized Controlled Trial

The global prevalence of type 2 diabetes mellitus (T2DM) has surged in recent decades, and the identification of differential glycemic responders can aid tailored treatment for the prevention of prediabetes and T2DM. A mixed meal tolerance test (MMTT) based on regular foods offers the potential to uncover differential responders in dynamical postprandial events. We aimed to fit a simple mathematical model on dynamic postprandial glucose data from repeated MMTTs among participants with elevated T2DM risk to identify response clusters and investigate their association with T2DM risk factors and gut microbiota. Data were used from a 12-week multi-center dietary intervention trial involving high-risk T2DM adults, comparing high- versus low-glycemic index foods within a Mediterranean diet context (MEDGICarb). Model-based analysis of MMTTs from 155 participants (81 females and 74 males) revealed two distinct plasma glucose response clusters that were associated with baseline gut microbiota. Cluster A, inversely associated with HbA1c and waist circumference and directly with insulin sensitivity, exhibited a contrasting profile to cluster B. Findings imply that a standardized breakfast MMTT using regular foods could effectively distinguish non-diabetic individuals at varying risk levels for T2DM using a simple mechanistic model.

Associations between Metabolomic Biomarkers of Avocado Intake and Glycemia in the Multi-Ethnic Study of Atherosclerosis

BACKGROUND

Avocado consumption is linked to better glucose homeostasis, but small associations suggest potential population heterogeneity. Metabolomic data capture the effects of food intake after digestion and metabolism, thus accounting for individual differences in these processes.

OBJECTIVES

To identify metabolomic biomarkers of avocado intake and to examine their associations with glycemia.

METHODS

Baseline data from 6224 multi-ethnic older adults (62% female) included self-reported avocado intake, fasting glucose and insulin, and untargeted plasma proton nuclear magnetic resonance metabolomic features (metabolomic data were available for a randomly selected subset; N = 3438). Subsequently, incident type 2 diabetes (T2D) was assessed over an ∼18 y follow-up period. A metabolome-wide association study of avocado consumption status (consumer compared with nonconsumer) was conducted, and the relationship of these features with glycemia via cross-sectional associations with fasting insulin and glucose and longitudinal associations with incident T2D was examined.

RESULTS

Three highly-correlated spectral features were associated with avocado intake at metabolome-wide significance levels (P < 5.3 ∗ 10-7) and combined into a single biomarker. We did not find evidence that these features were additionally associated with overall dietary quality, nor with any of 47 other food groups (all P > 0.001), supporting their suitability as a biomarker of avocado intake. Avocado intake showed a modest association only with lower fasting insulin (β = -0.07 +/- 0.03, P = 0.03), an association that was attenuated to nonsignificance when additionally controlling for body mass index (kg/m2). However, our biomarker of avocado intake was strongly associated with lower fasting glucose (β = -0.22 +/- 0.02, P < 2.0 ∗ 10-16), lower fasting insulin (β = -0.17 +/- 0.02, P < 2.0 ∗ 10-16), and a lower incidence of T2D (hazard ratio: 0.68; 0.63-074, P < 2.0 ∗ 10-16), even when adjusting for BMI.

CONCLUSIONS

Highly significant associations between glycemia and avocado-related metabolomic features, which serve as biomarkers of the physiological impact of dietary intake after digestion and absorption, compared to modest relationships between glycemia and avocado consumption, highlights the importance of considering individual differences in metabolism when considering diet-health relationships.

Ratings of the Effectiveness of 13 Therapeutic Diets for Autism Spectrum Disorder: Results of a National Survey

This study presents the results of the effectiveness of 13 therapeutic diets for autism spectrum disorder from 818 participants of a national survey, including benefits, adverse effects, and symptom improvements. The average Overall Benefit of diets was 2.36 (0 = no benefit, 4 = great benefit), which was substantially higher than for nutraceuticals (1.59/4.0) and psychiatric/seizure medications (1.39/4.0), p < 0.001. The average Overall Adverse Effects of diets was significantly lower than psychiatric/seizure medications (0.10 vs. 0.93, p < 0.001) and similar to nutraceuticals (0.16). Autism severity decreased slightly over time in participants who used diet vs. increasing slightly in those that did not (p < 0.001). Healthy and Feingold diets were the two top-rated diets by Overall Benefit; the ketogenic diet was the highest for nine symptoms (though had fewer respondents); and the gluten-free/casein-free diet was among the top for overall symptom improvements. Different diets were reported to affect different symptoms, suggesting that an individual's symptoms could be used to guide which diet(s) may be the most effective. The results suggest that therapeutic diets can be safe and effective interventions for improving some ASD-related symptoms with few adverse effects. We recommend therapeutic diets that include healthy foods and exclude problematic foods. Therapeutic diets are inexpensive treatments that we recommend for consideration by most people with ASD.

The efficacy of genotype-based dietary or physical activity advice in changing behavior to reduce the risk of cardiovascular disease, type II diabetes mellitus or obesity: a systematic review and meta-analysis

CONTEXT

Despite clear evidence that adherence to dietary and physical activity advice can reduce the risk of cardiometabolic disease, a significant proportion of the population do not follow recommendations. Personalized advice based on genetic variation has been proposed for motivating behavior change, although research on its benefits to date has been contradictory.

OBJECTIVE

To evaluate the efficacy of genotype-based dietary or physical activity advice in changing behavior in the general population and in individuals who are at risk of cardiovascular disease (CVD) or type II diabetes mellitus (T2DM).

DATA SOURCES

MEDLINE, EMBASE, PsycInfo, and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched up to January 7, 2022. Randomized controlled trials of a genotype-based dietary and/or physical activity advice intervention that aimed to change dietary and/or physical activity behavior were included.

DATA EXTRACTION

Abstracts of 7899 records were screened, and 14 reports from 11 studies met the inclusion criteria.

DATA ANALYSIS

Genotype-based dietary or physical activity advice was found to have no effect on dietary behavior in any of the studies (standardized mean difference [SMD] .00 [-.11 to .11], P = .98), even when analyzed by subgroup: "at risk" (SMD .00 [-.16 to .16, P = .99]; general population (SMD .01 [-.14 to .16], P = .87). The physical activity behavior findings were similar for all studies (SMD -.01 [-.10 to .08], P = .88), even when analyzed by subgroup: "at risk" (SMD .07 [-.18 to .31], P = .59); general population (SMD -.02 [-.13 to .10], P = .77). The quality of the evidence for the dietary behavior outcome was low; for the physical activity behavior outcome it was moderate.

CONCLUSIONS

Genotype-based advice does not affect dietary or physical activity behavior more than general advice or advice based on lifestyle or phenotypic measures. This was consistent in studies that recruited participants from the general population as well as in studies that had recruited participants from populations at risk of CVD or T2DM.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration no. CRD42021231147.

Perspective: A Conceptual Framework for Adaptive Personalized Nutrition Advice Systems (APNASs)

Nearly all approaches to personalized nutrition (PN) use information such as the gene variants of individuals to deliver advice that is more beneficial than a generic "1-size-fits-all" recommendation. Despite great enthusiasm and the increased availability of commercial services, thus far, scientific studies have only revealed small to negligible effects on the efficacy and effectiveness of personalized dietary recommendations, even when using genetic or other individual information. In addition, from a public health perspective, scholars are critical of PN because it primarily targets socially privileged groups rather than the general population, thereby potentially widening health inequality. Therefore, in this perspective, we propose to extend current PN approaches by creating adaptive personalized nutrition advice systems (APNASs) that are tailored to the type and timing of personalized advice for individual needs, capacities, and receptivity in real-life food environments. These systems encompass a broadening of current PN goals (i.e., what should be achieved) to incorporate "individual goal preferences" beyond currently advocated biomedical targets (e.g., making sustainable food choices). Moreover, they cover the "personalization processes of behavior change" by providing in situ, "just-in-time" information in real-life environments (how and when to change), which accounts for individual capacities and constraints (e.g., economic resources). Finally, they are concerned with a "participatory dialog between individuals and experts" (e.g., actual or virtual dieticians, nutritionists, and advisors) when setting goals and deriving measures of adaption. Within this framework, emerging digital nutrition ecosystems enable continuous, real-time monitoring, advice, and support in food environments from exposure to consumption. We present this vision of a novel PN framework along with scenarios and arguments that describe its potential to efficiently address individual and population needs and target groups that would benefit most from its implementation.

The Role of Diet and Gut Microbiota Interactions in Metabolic Homeostasis

Diet is a pivotal determinant in shaping the structure and function of resident microorganisms in the gut through different food components, nutritive proportion, and calories. The effects of diet on host metabolism and physiology can be mediated through the gut microbiota. Gut microbiota-derived metabolites have been shown to regulate glucose and lipid metabolism, energy consumption, and the immune system. On the other hand, emerging evidence indicates that baseline gut microbiota could predict the efficacy of diet intervention, highlighting gut microbiota can be harnessed as a biomarker in personalized nutrition. In this review, the alterations of gut microbiota in different dietary components and dietary patterns, and the potential mechanisms in the diet-microbiota crosstalk are summarized to understand the interactions of diet and gut microbiota on the impact of metabolic homeostasis.

The Role of Artificial Intelligence in Deciphering Diet-Disease Relationships: Case Studies

Modernization of society from a rural, hunter-gatherer setting into an urban and industrial habitat, with the associated dietary changes, has led to an increased prevalence of cardiometabolic and additional noncommunicable diseases, such as cancer, inflammatory bowel disease, and neurodegenerative and autoimmune disorders. However, while dietary sciences have been rapidly evolving to meet these challenges, validation and translation of experimental results into clinical practice remain limited for multiple reasons, including inherent ethnic, gender, and cultural interindividual variability, among other methodological, dietary reporting-related, and analytical issues. Recently, large clinical cohorts with artificial intelligence analytics have introduced new precision and personalized nutrition concepts that enable one to successfully bridge these gaps in a real-life setting. In this review, we highlight selected examples of case studies at the intersection between diet-disease research and artificial intelligence. We discuss their potential and challenges and offer an outlook toward the transformation of dietary sciences into individualized clinical translation.

Revealing the Acute Effects of Dietary Components on Mood and Cognition: The Role of Autonomic Nervous System Responses

A growing body of literature suggests dietary components can support mood and cognitive function through the impact of their bioactive or sensorial properties on neural pathways. Of interest, objective measures of the autonomic nervous system-such as those regulating bodily functions related to heartbeat and sweating-can be used to assess the acute effects of dietary components on mood and cognitive function. Technological advancements in the development of portable and wearable devices have made it possible to collect autonomic responses in real-world settings, creating an opportunity to study how the intake of dietary components impacts mood and cognitive function at an individual level, day-to-day. In this paper, we aimed to review the use of autonomic nervous system responses such as heart rate or skin galvanic response to investigate the acute effects of dietary components on mood and cognitive performance in healthy adult populations. In addition to examining the existing methodologies, we also propose new state-of-the-art techniques that use autonomic nervous system responses to detect changes in proxy patterns for the automatic detection of stress, alertness, and cognitive performance. These methodologies have potential applications for home-based nutrition interventions and personalized nutrition, enabling individuals to recognize the specific dietary components that impact their mental and cognitive health and tailor their nutrition accordingly.

A monocentric, randomized, double-blind, controlled crossover trial of nasturtium (Tropaeolum majus) on the lipid regulator prostaglandin E2

Scope

As prostaglandin E2 (PGE2) has important roles in physiological and inflammatory functions, a double-blind randomized controlled crossover study to investigate the potential of nasturtium (Tropaeolum majus) for modulating PGE2 was conducted, aiming at clarifying the role of benzyl isothiocyanate (BITC). As secondary parameters leukotriene 4 (LTB4), and cytokine release (tumor necrosis factor alpha, TNF-α; interleukins IL-1β, IL-10, and IL-12) were quantified.

Methods and results

Thirty-four healthy female participants consumed 1.5 g nasturtium containing BITC, (verum) or no BITC (control) twice a day for 2 weeks each. Nasturtium intervention resulted in an increase in mean PGE2 levels in serum samples (verum: 1.76-fold, p ≤ 0.05; control: 1.78-fold, p ≤ 0.01), and ex vivo stimulated peripheral blood mononuclear cells (PBMC) (verum: 1.71-fold, p ≤ 0.01; control: 1.43-fold). Using a pre-to-post responder analysis approach, 18 of 34 subjects showed a > 25% PGE2 increase in serum, while it was >25% decreased for 9 subjects (stimulated PBMC: 14 and 8 of 28, respectively). Under the selected conditions, the BITC content of nasturtium did not affect the observed changes in PGE2. Verum intervention also increased mean LTB4 serum level (1.24-fold, p ≤ 0.01), but not in LPS stimulated PBMC, and significantly increased TNF-α release in stimulated PBMC after 3 h (verum: 1.65-fold, p = 0.0032; control: 1.22-fold, p = 0.7818). No change was seen in the anti-inflammatory cytokine IL-10, or the pro-inflammatory cytokines IL-1β, and IL-12.

Conclusion

In contrast to the previously reported in vitro results, on average, LPS activated PBMC and serum from both groups showed increased PGE2 levels. Further analyses suggest that PGE2 release after intervention could possibly depend on the baseline PGE2 level. Identification of phenotypes that respond differently to the nasturtium intervention could be useful to establish personalized approaches for dosing phytopharmaceuticals medicines.

A randomized clinical trial comparing low-fat with precision nutrition-based diets for weight loss: impact on glycemic variability and HbA1c

BACKGROUND

Recent studies have demonstrated considerable interindividual variability in postprandial glucose response (PPGR) to the same foods, suggesting the need for more precise methods for predicting and controlling PPGR. In the Personal Nutrition Project, the investigators tested a precision nutrition algorithm for predicting an individual's PPGR.

OBJECTIVE

This study aimed to compare changes in glycemic variability (GV) and HbA1c in 2 calorie-restricted weight loss diets in adults with prediabetes or moderately controlled type 2 diabetes (T2D), which were tertiary outcomes of the Personal Diet Study.

METHODS

The Personal Diet Study was a randomized clinical trial to compare a 1-size-fits-all low-fat diet (hereafter, standardized) with a personalized diet (hereafter, personalized). Both groups received behavioral weight loss counseling and were instructed to self-monitor diets using a smartphone application. The personalized arm received personalized feedback through the application to reduce their PPGR. Continuous glucose monitoring (CGM) data were collected at baseline, 3 mo and 6 mo. Changes in mean amplitude of glycemic excursions (MAGEs) and HbA1c at 6 mo were assessed. We performed an intention-to-treat analysis using linear mixed regressions.

RESULTS

We included 156 participants [66.5% women, 55.7% White, 24.1% Black, mean age 59.1 y (standard deviation (SD) = 10.7 y)] in these analyses (standardized = 75, personalized = 81). MAGE decreased by 0.83 mg/dL per month for standardized (95% CI: 0.21, 1.46 mg/dL; P = 0.009) and 0.79 mg/dL per month for personalized (95% CI: 0.19, 1.39 mg/dL; P = 0.010) diet, with no between-group differences (P = 0.92). Trends were similar for HbA1c values.

CONCLUSIONS

Personalized diet did not result in an increased reduction in GV or HbA1c in patients with prediabetes and moderately controlled T2D, compared with a standardized diet. Additional subgroup analyses may help to identify patients who are more likely to benefit from this personalized intervention. This trial was registered at clinicaltrials.gov as NCT03336411.

Bioavailable Microbial Metabolites of Flavanols Demonstrate Highly Individualized Bioactivity on In Vitro β-Cell Functions Critical for Metabolic Health

Dietary flavanols are known for disease preventative properties but are often poorly absorbed. Gut microbiome flavanol metabolites are more bioavailable and may exert protective activities. Using metabolite mixtures extracted from the urine of rats supplemented with flavanols and treated with or without antibiotics, we investigated their effects on INS-1 832/13 β-cell glucose stimulated insulin secretion (GSIS) capacity. We measured insulin secretion under non-stimulatory (low) and stimulatory (high) glucose levels, insulin secretion fold induction, and total insulin content. We conducted treatment-level comparisons, individual-level dose responses, and a responder vs. non-responder predictive analysis of metabolite composition. While the first two analyses did not elucidate treatment effects, metabolites from 9 of the 28 animals demonstrated significant dose responses, regardless of treatment. Differentiation of responders vs. non-responder revealed that levels of native flavanols and valerolactones approached significance for predicting enhanced GSIS, regardless of treatment. Although treatment-level patterns were not discernable, we conclude that the high inter-individual variability shows that metabolite bioactivity on GSIS capacity is less related to flavanol supplementation or antibiotic treatment and may be more associated with the unique microbiome or metabolome of each animal. These findings suggest flavanol metabolite activities are individualized and point to the need for personalized nutrition practices.

Trial protocol for the study of recommendation system DiaCompanion with personalized dietary recommendations for women with gestational diabetes mellitus (DiaCompanion I)

Background

Gestational diabetes mellitus (GDM) is a common complication of pregnancy associated with serious adverse outcomes for mothers and their offspring. Achieving glycaemic targets is the mainstream in the treatment of GDM in order to improve pregnancy outcomes. As GDM is usually diagnosed in the third trimester of pregnancy, the time frame for the intervention is very narrow. Women need to get new knowledge and change their diet very quickly. Usually, these patients require additional frequent visits to healthcare professionals. Recommender systems based on artificial intelligence could partially substitute healthcare professionals in the process of educating and controlling women with GDM, thus reducing the burden on the women and healthcare systems. We have developed a mobile-based personalized recommendation system DiaCompanion I with data-driven real time personal recommendations focused primarily on postprandial glycaemic response prediction. The study aims to clarify the effect of using DiaCompanion I on glycaemic levels and pregnancy outcomes in women with GDM.

Methods

Women with GDM are randomized to 2 treatment groups: utilizing and not utilizing DiaCompanion I. The app provides women in the intervention group the resulting data-driven prognosis of 1-hour postprandial glucose level every time they input their meal data. Based on the predicted glucose level, they can adjust their current meal so that the predicted glucose level falls within the recommended range below 7 mmol/L. The app also provides reminders and recommendations on diet and lifestyle to the participants of the intervention group. All the participants are required to perform 6 blood glucose measurements a day. Capillary glucose values are retrieved from the glucose meter and if not available, from the woman's diary. Additionally, data on glycaemic levels during the study and consumption of major macro- and micronutrients will be collected using the mobile app with electronic report forms in the intervention group. Women from the control group receive standard care without the mobile app. All participants are prescribed with insulin therapy if needed and modifications in their lifestyle. A total of 216 women will be recruited. The primary outcome is the percentage of postprandial capillary glucose values above target (>7.0 mmol/L). Secondary outcomes include the percentage of patients requiring insulin therapy during pregnancy, maternal and neonatal outcomes, glycaemic control using glycated hemoglobin (HbA1c), continuous glucose monitoring data and other blood glucose metrics, the number of patient visits to endocrinologists and acceptance/satisfaction of the two strategies assessed using a questionnaire.

Discussion

We believe that the approach including DiaCompanion I will be more effective in patients with GDM for improving glycaemic levels and pregnancy outcomes. We also expect that the use of the app will help reduce the number of clinic visits.

Trial registration number

ClinicalTrials.gov, Identifier NCT05179798.

Supplementation with inulin-type fructans affects gut microbiota and attenuates some of the cardiometabolic benefits of a plant-based diet in individuals with overweight or obesity

Background

The gut microbiota has emerged as a potential therapeutic target to improve the management of obesity and its comorbidities.

Objective

We investigated the impact of a high fiber (∼38 g/d) plant-based diet, consumed ad libitum, with or without added inulin-type fructans (ITF), on the gut microbiota composition and cardiometabolic outcomes in subjects with obesity. We also tested if baseline Prevotella/Bacteroides (P/B) ratio predicts weight loss outcomes.

Methods

This is a secondary exploratory analysis from the PREVENTOMICS study, in which 100 subjects (82 completers) aged 18-65 years with body mass index 27-40 kg/m2 were randomized to 10 weeks of double-blinded treatment with a personalized or a generic plant-based diet. Changes from baseline to end-of-trial in gut microbiota composition (16S rRNA gene amplicon sequencing), body composition, cardiometabolic health and inflammatory markers were evaluated in the whole cohort (n = 82), and also compared in the subgroup of subjects who were supplemented with an additional 20 g/d ITF-prebiotics (n = 21) or their controls (n = 22).

Results

In response to the plant-based diet, all subjects lost weight (-3.2 [95% CI -3.9, -2.5] kg) and experienced significant improvements in body composition and cardiometabolic health indices. Addition of ITF to the plant-based diet reduced microbial diversity (Shannon index) and selectively increased Bifidobacterium and Faecalibacterium (q < 0.05). The change in the latter was significantly associated with higher values of insulin and HOMA-IR and lower HDL cholesterol. In addition, the LDL:HDL ratio and the concentrations of IL-10, MCP-1 and TNFα were significantly elevated in the ITF-subgroup. There was no relationship between baseline P/B ratio and changes in body weight (r = -0.07, p = 0.53).

Conclusion

A plant-based diet consumed ad libitum modestly decreases body weight and has multiple health benefits in individuals with obesity. Addition of ITF-prebiotics on top this naturally fiber-rich background selectively changes gut microbiota composition and attenuates some of the realized cardiometabolic benefits.

Clinical trial registration

[https://clinicaltrials.gov/ct2/show/NCT04590989], identifier [NCT04590989].

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

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

A Tailored and Engaging mHealth Gamified Framework for Nutritional Behaviour Change

Mobile health applications (apps) have been shown to be effective for improving eating habits. However, most of the existing apps rely on calorie and nutrient counting which have several limitations including the difficulty in sustaining long-term use, inaccuracy, and the risk of developing eating disorders. We designed and developed a mHealth framework for nutritional behaviour change, integrated into the CarpeDiem app, that focuses on the intake of key food groups which are known to have a higher impact on health indicators instead of the intake of nutrients. This framework is mainly based on a gamified system that delivers personalized dietary missions to the user and provides motivational recommendations that help the user to achieve these missions. Its design was guided by an evidenced-based theory of behavioural change, the HAPA model, and it is also characterized by the personalization of the system and the use of a recommender system based on advanced artificial intelligence techniques. Overall, the approach used in the present app could foster a sustained improvement of eating habits among the general population, which is the main challenge of dietary interventions, decreasing the risk of developing the chronic diseases associated with unhealthy dietary habits.

Nutrition-Related N-of-1 Studies Warrant Further Research to Provide Evidence for Dietitians to Practice Personalized (Precision) Medical Nutrition Therapy: A Systematic Review

N-of-1 trials provide a higher level of evidence than randomized controlled trials for determining which treatment works best for an individual, and the design readily accommodates testing of personalized nutrition. The aim of this systematic review was to synthesize nutrition-related studies using an N-of-1 design. The inclusion criterion was adult participants; the intervention/exposure was any nutrient, food, beverage, or dietary pattern; the comparators were baseline values, a control condition untreated or placebo, or an alternate treatment, alongside any outcomes such as changes in diet, body weight, biochemical outcomes, symptoms, quality of life, or a disease outcome resulting from differences in nutritional conditions. The information sources used were Medline, Embase, Scopus, Cochrane Central, and PsychInfo. The quality of study reporting was assessed using the Consort Extension for N-of-1 trials (CENT) statement or the STrengthening Reporting of OBservational Studies in Epidemiology (STROBE) guidelines, as appropriate. From 211 articles screened, a total of 7 studies were included and were conducted in 5 countries with a total of 83 participants. The conditions studied included prediabetes, diabetes, irritable bowel syndrome, weight management, and investigation of the effect of diet in healthy people. The quality of reporting was mostly adequate, and dietary assessment quality varied from poor to good. The evidence base is small, but served to illustrate the main characteristics of N-of-1 study designs and considerations for moving research forward in the era of personalized medical nutrition therapy.

Associations Between Dietary Vitamin C, Serum Ascorbic Acid, and GSTT1 Genotype and Premenstrual Symptoms

OBJECTIVE

Premenstrual symptoms are a cyclically occurring combination of adverse psychological and somatic symptoms that impact the quality of life for most females of childbearing age. Growing evidence suggests that diet may attenuate premenstrual symptoms; however, the relationship between vitamin C and premenstrual symptoms remains unclear. The aim of the research was to determine the association between different measures of vitamin C status and premenstrual symptoms.

METHOD

Females (n = 555) aged 20 to 29 years from the Toronto Nutrigenomics and Health Study completed a General Health and Lifestyle Questionnaire, capturing 15 premenstrual symptoms. Dietary intake was measured using a 196-item Toronto-modified Harvard food frequency questionnaire. Serum ascorbic acid concentrations were measured, and participants were categorized into deficient (<11 µmol/L), suboptimal (11-28 µmol/L), and adequate (>28 µmol/L) ascorbic acid levels. DNA was genotyped for the GSTT1 (Ins/Del) polymorphism. Using logistic regression, odds of experiencing premenstrual symptoms were compared between vitamin C intake levels above and below the recommended daily allowance (75 mg/d) between ascorbic acid levels and between GSTT1 genotypes.

RESULTS

Increased vitamin C intake was associated with premenstrual appetite changes (OR, 1.65; 95% CI, 1.01-2.68). Compared to deficient ascorbic acid levels, suboptimal levels were associated with premenstrual appetite changes (OR, 2.59; 95% CI, 1.02-6.58) and bloating/swelling (OR, 3.00; 95% CI, 1.09-8.22). Adequate serum ascorbic acid levels were not associated with premenstrual appetite changes (OR, 1.69; 95% CI, 0.73-3.94) or bloating/swelling (OR, 1.92; 95% CI, 0.79-4.67). Those with the GSTT1 functional variant (Ins*Ins) had an increased risk of premenstrual bloating/swelling (OR, 1.96; 95% CI, 1.10-3.48); however, the interaction between vitamin C intake and GSTT1 was not significant for any premenstrual symptoms.

CONCLUSIONS

Our findings suggest that indicators of higher vitamin C status are associated with increased premenstrual appetite changes and bloating/swelling. The observed associations with GSTT1 genotype suggest that these observations are not likely due to reverse causation.

Investigation into the Physicochemical and Textural Properties of an Iron-Rich 3D-Printed Hybrid Food

In the context of dietary transition, blending animal-source protein with plant-source protein offers a promising way to exploit their nutritional complementarity. This study investigates the feasibility of formulating an iron-rich hybrid food product blending plant-source and animal-source protein ingredients for iron-deficient populations. Using a commercial 3D-food printer, two different-shaped products composed mainly of pork and chicken liver and red lentils were designed. After baking at 180 °C with 70% steam, the 3D-printed products were packed under two different modified atmospheres (MAP): O₂-MAP (70% oxygen + 30% carbon dioxide) and N₂-MAP (70% nitrogen + 30% carbon dioxide) and stored at 4 °C. pH, water content, a_w, lipid oxidation, heme iron and non-heme iron contents and textural properties were measured after 0, 7, 14 and 21 days in storage. After 21 days in storage, the 3D-printed hybrid products had an iron content of around 13 mg/100 g, regardless of the product form and packaging method. However, O₂-MAP products showed significant (p < 0.05) time-course changes from day 0 to day 7, i.e., an increase in lipid oxidation, a decrease in heme iron content and an increase in product hardness, gumminess and chewiness. This work opens prospects for developing hybrid food products that upvalue animal by-products.

Inflammation and Nutrition: Friend or Foe?

The importance of the interplay between inflammation and nutrition has generated much interest in recent times. Inflammation has been identified as a key driver for disease-related malnutrition, leading to anorexia, reduced food intake, muscle catabolism, and insulin resistance, which are stimulating a catabolic state. Interesting recent data suggest that inflammation also modulates the response to nutritional treatment. Studies have demonstrated that patients with high inflammation show no response to nutritional interventions, while patients with lower levels of inflammation do. This may explain the contradictory results of nutritional trials to date. Several studies of heterogeneous patient populations, or in the critically ill or advanced cancer patients, have not found significant benefits on clinical outcome. Vice versa, several dietary patterns and nutrients with pro- or anti-inflammatory properties have been identified, demonstrating that nutrition influences inflammation. Within this review, we summarize and discuss recent advances in both the role of inflammation in malnutrition and the effect of nutrition on inflammation.

Bitter- and Umami-Related Genes are Differentially Associated with Food Group Intakes: the Framingham Heart Study

BACKGROUND

As suboptimal diet quality remains the leading modifiable contributor to chronic disease risk, it is important to better understand the individual-level drivers of food choices. Recently, a genetic component of food choices was proposed based on variants (SNPs) in genes related to taste perception (taste-related SNPs).

OBJECTIVES

This study aimed to determine the cumulative contribution of taste-related SNPs for basic tastes (bitter, sweet, umami, salt, and sour), summarized as "polygenic taste scores," to food group intakes among adults.

METHODS

Cross-sectional analyses were performed on 6230 Framingham Heart Study participants (mean age ± SD: 50 ± 14 y; 54% female). Polygenic taste scores were derived for tastes with ≥2 related SNPs identified in prior genome-wide association studies, and food group intakes (servings per week [sev/wk]) were tabulated from food frequency questionnaires. Associations were determined via linear mixed-effects models, using false discovery rates and bootstrap resampling to determine statistical significance.

RESULTS

Thirty-three taste-related SNPs (9 bitter, 19 sweet, 2 umami, 2 sour, 1 salt) were identified and used to derive polygenic taste scores for bitter, sweet, umami, and sour. Per additional allele for higher bitter perception, whole grain intakes were lower by 0.17 (95% CI: -0.28, -0.06) sev/wk, and for higher umami perception, total and red/orange vegetable intakes were lower by 0.73 (95% CI: -1.12, -0.34) and 0.25 (95% CI: -0.40, -0.10) sev/wk, respectively. Subsequent analyses at the SNP level identified four novel SNP-diet associations-two bitter-related SNPs with whole grains (rs10960174 and rs6782149) and one umami-related SNP with total and red/orange vegetables (rs7691456)-which may have been driving the identified associations.

CONCLUSIONS

Taste-related genes for bitter and umami were differentially associated with food choices that may impact diet quality. Hence, a benefit could be derived from leveraging knowledge of taste-related genes when developing personalized risk reduction dietary guidance.

Chrono-Nutrition: Circadian Rhythm and Personalized Nutrition

The human circadian system has a period of approximately 24 h and studies on the consequences of "chornodisruption" have greatly expanded. Lifestyle and environmental factors of modern societies (i.e., artificial lighting, jetlag, shift work, and around-the-clock access to energy-dense food) can induce disruptions of the circadian system and thereby adversely affect individual health. Growing evidence demonstrates a complex reciprocal relationship between metabolism and the circadian system, in which perturbations in one system affect the other one. From a nutritional genomics perspective, genetic variants in clock genes can both influence metabolic health and modify the individual response to diet. Moreover, an interplay between the circadian rhythm, gut microbiome, and epigenome has been demonstrated, with the diet in turn able to modulate this complex link suggesting a remarkable plasticity of the underlying mechanisms. In this view, the study of the impact of the timing of eating by matching elements from nutritional research with chrono-biology, that is, chrono-nutrition, could have significant implications for personalized nutrition in terms of reducing the prevalence and burden of chronic diseases. This review provides an overview of the current evidence on the interactions between the circadian system and nutrition, highlighting how this link could in turn influence the epigenome and microbiome. In addition, possible nutritional strategies to manage circadian-aligned feeding are suggested.

Personalized Dietary Regimens for Inflammatory Bowel Disease: Current Knowledge and Future Perspectives

Inflammatory bowel diseases (IBD) are chronic and incurable conditions of the gastro-intestinal tract with an increasing incidence and prevalence worldwide. Common symptoms are abdominal pain, diarrhea, and weight loss. Despite recent advances in medical management, many patients fail to achieve clinical remission and healing of the mucosa of the bowel. The cause is thought to involve an inappropriate reaction of the immune system, the microbiome and the environment in genetically susceptible individuals, leading to chronic bowel inflammation. Evidence is emerging that diet is a key environmental factor that might influence disease onset and course, and therefore may become a therapeutic strategy to mitigate inflammation and symptoms. Since IBD is a heterogeneous disease on a clinical and a molecular level, personalizing dietary advice could be the crucial factor to achieve long-lasting changes in dietary behaviors that could not only improve nutritional status but also tackle gut inflammation and abdominal symptoms on an individual level. In this review, we first discuss different aspects of personalized nutrition, namely the level, focus, and scope of personalized dietary regimens. Then, we provide a framework for the different goals of nutritional therapy in IBD and current evidence for personalized dietary approaches. Lastly, we discuss the need for adequate trial designs, access to the right data types and the bioinformatic tools that are necessary to develop algorithms that will allow us to move from general "healthy eating" advice to truly personalized nutritional plans for the individual IBD patient.

A Review of Digital Innovations for Diet Monitoring and Precision Nutrition

This article provides an up-to-date review of technological advances in 3 key areas related to diet monitoring and precision nutrition. First, we review developments in mobile applications, with a focus on food photography and artificial intelligence to facilitate the process of diet monitoring. Second, we review advances in 2 types of wearable and handheld sensors that can potentially be used to fully automate certain aspects of diet logging: physical sensors to detect moments of dietary intake, and chemical sensors to estimate the composition of diets and meals. Finally, we review new programs that can generate personalized/precision nutrition recommendations based on measurements of gut microbiota and continuous glucose monitors with artificial intelligence. The article concludes with a discussion of potential pitfalls of some of these technologies.

Personalized Diets based on the Gut Microbiome as a Target for Health Maintenance: from Current Evidence to Future Possibilities

Recently, the concept of personalized nutrition has been developed, which states that food components do not always lead to the same metabolic responses, but vary from person to person. Although this concept has been studied based on individual genetic backgrounds, researchers have recently explored its potential role in the gut microbiome. The gut microbiota physiologically communicates with humans by forming a bidirectional relationship with the micronutrients, macronutrients, and phytochemicals consumed by the host. Furthermore, the gut microbiota can vary from person to person and can be easily shifted by diet. Therefore, several recent studies have reported the application of personalized nutrition to intestinal microflora. This review provides an overview of the interaction of diet with the gut microbiome and the latest evidence in understanding the inter-individual differences in dietary responsiveness according to individual baseline gut microbiota and microbiome-associated dietary intervention in diseases. The diversity of the gut microbiota and the presence of specific microorganisms can be attributed to physiological differences following dietary intervention. The difference in individual responsiveness based on the gut microbiota has the potential to become an important research approach for personalized nutrition and health management, although further well-designed large-scale studies are warranted.

Lactoferrin-The Health-Promoting Properties and Contemporary Application with Genetic Aspects

The aim of the study is to present a review of literature data on lactoferrin's characteristics, applications, and multiple health-promoting properties, with special regard to nutrigenomics and nutrigenetics. The article presents a new approach to food ingredients. Nowadays, lactoferrin is used as an ingredient in food but mainly in pharmaceuticals and cosmetics. In the European Union, bovine lactoferrin has been legally approved for use as a food ingredient since 2012. However, as our research shows, it is not widely used in food production. The major producers of lactoferrin and the few available food products containing it are listed in the article. Due to anti-inflammatory, antibacterial, antiviral, immunomodulatory, antioxidant, and anti-tumour activity, the possibility of lactoferrin use in disease prevention (as a supportive treatment in obesity, diabetes, as well as cardiovascular diseases, including iron deficiency and anaemia) is reported. The possibility of targeted use of lactoferrin is also presented. The use of nutrition genomics, based on the identification of single nucleotide polymorphisms in genes, for example, FTO, PLIN1, TRAP2B, BDNF, SOD2, SLC23A1, LPL, and MTHFR, allows for the effective stratification of people and the selection of the most optimal bioactive nutrients, including lactoferrin, whose bioactive potential cannot be considered without taking into account the group to which they will be given.