More Nutrition Precision, Better Decisions for the Health of Our Nation

Precision Nutrition Unveiled: Gene-Nutrient Interactions, Microbiota Dynamics, and Lifestyle Factors in Obesity Management

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.

A Predictive Tool Based on DNA Methylation Data for Personalized Weight Loss through Different Dietary Strategies: A Pilot Study

BACKGROUND AND AIMS

Obesity is a public health problem. The usual treatment is a reduction in calorie intake and an increase in energy expenditure, but not all individuals respond equally to these treatments. Epigenetics could be a factor that contributes to this heterogeneity. The aim of this research was to determine the association between DNA methylation at baseline and the percentage of BMI loss (%BMIL) after two dietary interventions, in order to design a prediction model to evaluate %BMIL based on methylation data.

METHODS AND RESULTS

Spanish participants with overweight or obesity (n = 306) were randomly assigned to two lifestyle interventions with hypocaloric diets: one moderately high in protein (MHP) and the other low in fat (LF) for 4 months (Obekit study; ClinicalTrials.gov ID: NCT02737267). Basal DNA methylation was analyzed in white blood cells using the Infinium MethylationEPIC array. After identifying those methylation sites associated with %BMIL (p < 0.05 and SD > 0.1), two weighted methylation sub-scores were constructed for each diet: 15 CpGs were used for the MHP diet and 11 CpGs for the LF diet. Afterwards, a total methylation score was made by subtracting the previous sub-scores. These data were used to design a prediction model for %BMIL through a linear mixed effect model with the interaction between diet and total score.

CONCLUSION

Overall, DNA methylation predicts the %BMIL of two 4-month hypocaloric diets and was able to determine which type of diet is the most appropriate for each individual. The results of this pioneer study confirm that epigenetic biomarkers may be further used for precision nutrition and the design of personalized dietary strategies against obesity.

Nutrition and stem cell integrity in aging

Adult stem cells (SCs) represent the regenerative capacity of organisms throughout their lifespan. The maintenance of robust SC populations capable of renewing organs and physiological systems is one hallmark of healthy aging. The local environment of SCs, referred to as the niche, includes the nutritional milieu, which is essential to maintain the quantity and quality of SCs available for renewal and regeneration. There is increased recognition that SCs have unique metabolism and conditional nutrient needs compared to fully differentiated cells. However, the contribution of SC nutrition to overall human nutritional requirements is an understudied and underappreciated area of investigation. Nutrient needs vary across the lifespan and are modified by many factors including individual health, disease, physiological states including pregnancy, age, sex, and during recovery from injury. Although current nutrition guidance is generally derived for apparently healthy populations and to prevent nutritional deficiency diseases, there are increased efforts to establish nutrient-based and food-based recommendations based on reducing chronic disease. Understanding the dynamics of SC nutritional needs throughout the life span, including the role of nutrition in extending biological age by blunting biological systems decay, is fundamental to establishing food and nutrient guidance for chronic disease reduction and health maintenance. This review summarizes a 3-day symposium of the Marabou Foundation (www.marabousymposium.org) held to examine the metabolic properties and unique nutritional needs of adult SCs and their role in healthy aging and age-related chronic disease.

Gut microbiota modulates differential lipid metabolism outcomes associated with FTO gene polymorphisms in response to personalized nutrition intervention

Background

Interindividual differences in response to personalized nutrition (PN) intervention were affected by multiple factors, including genetic backgrounds and gut microbiota. The fat mass and obesity associated (FTO) gene is an important factor related to hyperlipidemia and occurrence of cardiovascular diseases. However, few studies have explored the differences in response to intervention among subjects with different genotypes of FTO, and the associations between gut microbiota and individual responses.

Objective

To explore the differential lipid metabolism outcomes associated with FTO gene polymorphisms in response to PN intervention, the altered taxonomic features of gut microbiota caused by the intervention, and the associations between gut microbiota and lipid metabolism outcomes.

Methods

A total of 400 overweight or obese adults were recruited in the study and randomly divided into the PN group and control group, of whom 318 completed the 12-week intervention. The single nucleotide polymorphism (SNP) of rs1121980 in FTO was genotyped. Gut microbiota and blood lipids were determined at baseline and week 12. Functional property of microbiota was predicted using Tax4Fun functional prediction analysis.

Results

Subjects with the risk genotype of FTO had significantly higher weight and waist circumference (WC) at baseline. Generalized linear regression models showed that the reduction in weight, body mass index (BMI), WC, body fat percentage, total cholesterol (TCHO), and low-density lipoprotein (LDL) was greater in subjects with the risk genotype of FTO and in the PN group. Significant interaction effects between genotype and intervention on weight, BMI, WC, TCHO, and LDL were found after stratifying for specific genotype of FTO. All subjects showed significant increasement in α diversity of gut microbiota after intervention except for those with the non-risk genotype in the control group. Gut microbiota, including Blautia and Firmicutes, might be involved in lipid metabolism in response to interventions. The predicted functions of the microbiota in subjects with different genotypes were related to lipid metabolism-related pathways, including fatty acid biosynthesis and degradation.

Conclusion

Subjects with the risk genotype of FTO had better response to nutrition intervention, and PN intervention showed better amelioration in anthropometric parameters and blood lipids than the control. Gut microbiota might be involved in modulating differential lipid metabolism responses to intervention in subjects with different genotypes.

Trial registration

[Chictr.org.cn], identifier [ChiCTR1900026226].

A strategy for exploring subgroup-specific effects in nutrition science

Nutrients are an essential part of building and maintaining optimal health. Certain nutrient exposure has been shown to be associated with many important health outcomes, although there is variability among studies. Despite the scientific efforts of many, it is unclear why some well-hypothesised nutrients lack sufficient evidence for clear association with health outcomes. One potential reason for conflicting results is that certain subgroups of patients benefit or are harmed more by adequate or inadequate exposure to certain nutrients. These subgroup-specific effects have historically not been studied, or if they are, it is often in a one-off type of approach where the investigator believes that a subgroup effect could exist based on limited previous data. In the era of big data, improvements can be made in efforts to generate new hypotheses for subgroups of patients and recommendations for precision nutrition can be made. In the present paper, we present a strategy for exploring subgroup-specific effects in nutrient-related studies. This data-driven method can be useful in secondarily exploring which subgroups are harmed/helped most by inadequate/adequate nutrient exposure and could suggest target groups for future clinical trials to test the identified hypotheses. We then present an example study utilizing the National Health and Nutrition Examination Survey (NHANES) data from the years 2001–2006. In this example, a limited selection of nutrients is protective in subgroups of participants with diabetes on their self-reported number of poor mental health days.

Multiomics Approach to Precision Sports Nutrition: Limits, Challenges, and Possibilities

Most sports nutrition guidelines are based on group average responses and professional opinion. Precision nutrition for athletes aims to improve the individualization of nutrition practices to optimize long-term performance and health. This is a 2-step process that first involves the acquisition of individual-specific, science-based information using a variety of sources including lifestyle and medical histories, dietary assessment, physiological assessments from the performance lab and wearable sensors, and multiomics data from blood, urine, saliva, and stool samples. The second step consists of the delivery of science-based nutrition advice, behavior change support, and the monitoring of health and performance efficacy and benefits relative to cost. Individuals vary widely in the way they respond to exercise and nutritional interventions, and understanding why this metabolic heterogeneity exists is critical for further advances in precision nutrition. Another major challenge is the development of evidence-based individualized nutrition recommendations that are embraced and efficacious for athletes seeking the most effective enhancement of performance, metabolic recovery, and health. At this time precision sports nutrition is an emerging discipline that will require continued technological and scientific advances before this approach becomes accurate and practical for athletes and fitness enthusiasts at the small group or individual level. The costs and scientific challenges appear formidable, but what is already being achieved today in precision nutrition through multiomics and sensor technology seemed impossible just two decades ago.