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Perspective: a conceptual framework for adaptive personalized nutrition advice systems (APNASs)
(2023)
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 one-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 dialogue 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.
Metabolism oscillates between catabolic and anabolic states depending on food intake, exercise, or stresses that change a multitude of metabolic pathways simultaneously. We present the HuMet Repository for exploring dynamic metabolic responses to oral glucose/lipid loads, mixed meals, 36-h fasting, exercise, and cold stress in healthy subjects. Metabolomics data from blood, urine, and breath of 15 young, healthy men at up to 56 time points are integrated and embedded within an interactive web application, enabling researchers with and without computational expertise to search, visualize, analyze, and contextualize the dynamic metabolite profiles of 2,656 metabolites acquired on multiple platforms. With examples, we demonstrate the utility of the resource for research into the dynamics of human metabolism, highlighting differences and similarities in systemic metabolic responses across challenges and the complementarity of metabolomics platforms. The repository, providing a reference for healthy metabolite changes to six standardized physiological challenges, is freely accessible through a web portal.
Dysregulated expression of Neuregulin-1 by cortical pyramidal neurons disrupts synaptic plasticity
(2014)
Personalized Nutrition (PN) represents an approach aimed at delivering tailored dietary recommendations, products or services to support both prevention and treatment of nutrition-related conditions and improve individual health using genetic, phenotypic, medical, nutritional, and other pertinent information. However, current approaches have yielded limited scientific success in improving diets or in mitigating diet-related conditions. In addition, PN currently caters to a specific subgroup of the population rather than having a widespread impact on diet and health at a population level. Addressing these challenges requires integrating traditional biomedical and dietary assessment methods with psycho-behavioral, and novel digital and diagnostic methods for comprehensive data collection, which holds considerable promise in alleviating present PN shortcomings. This comprehensive approach not only allows for deriving personalized goals (“what should be achieved”) but also customizing behavioral change processes (“how to bring about change”). We herein outline and discuss the concept of “Adaptive Personalized Nutrition Advice Systems” (APNASs), which blends data from three assessment domains: 1) biomedical/health phenotyping; 2) stable and dynamic behavioral signatures; and 3) food environment data. Personalized goals and behavior change processes are envisaged to no longer be based solely on static data but will adapt dynamically in-time and in-situ based on individual-specific data. To successfully integrate biomedical, behavioral and environmental data for personalized dietary guidance, advanced digital tools (e.g., sensors) and artificial intelligence (AI)-based methods will be essential. In conclusion, the integration of both established and novel static and dynamic assessment paradigms holds great potential for transitioning PN from its current focus on elite nutrition to a widely accessible tool that delivers meaningful health benefits to the general population.
The increasing use of “functional foods” supplemented with plant sterols to lower serum cholesterol levels and on the other hand the discovery of the rare ABCG5/G8 mutation resulting in high phytosterol levels and premature atherosclerosis has renewed the clinical interest on the role of plasma phytosterols in coronary artery disease. It is still unclear if plasma phytosterol levels in the general population may associated with CAD risk. However, some recent reports support this consideration. Therefore, population studies examining the relationship of phytosterol levels to coronary events are necessary to evaluate any contributions of phytosterols to CAD risk. The aim of our study was to assess the association between the serum levels of the phytosterol campesterol and the 10 year risk of incident myocardial infarction in initially healthy middle-aged men from Southern Germany with no myocardial infarction in medical history. Serum concentrations of total campesterol and other sterols were determined using a novel high-throughput LC-MS/MS platform. The study population included 1186 male participants (age at baseline 35–64 years) which were randomly sampled from the general population of the Southern German region of Augsburg in 1994/95 and followed until 2004/2005. During this period 49 men suffered from either a fatal or non-fatal acute CHD event. In a Cox Proportional-Hazards model, after multivariable adjustment for established cardiovascular risk factors the hazard ratio (HR) for incident acute myocardial infarction (including sudden coronary deaths) was 2.38 (95% CI, 0.64–6.01) for third quartile (5.70–7.26 mg/l) and 3.00 (95% CI, 1.16–7.78) for the fourth quartile (>= 7.27 mg/l) of total campesterol in comparison to its first quartile (< 4.42 mg/l), the test on linearity of the association was significant (p<0.001). Our results of a large prospective population-based cohort analysis demonstrate for the first time that plasma campesterol is an independent and highly significant metabolic marker indicating an increased risk for incident myocardial infarction in middle aged men. Further research is needed to elucidate the pathophysiological mechanisms of this observation.
