Effect of Incorporating Genetic Testing Results into Nutrition Counseling and Care on Health Outcomes: An Evidence Analysis Center Systematic Review-Part II

Association Between the Postprandial Response to an Oral Glucose Tolerance Test and Anthropometric Changes After an 8-Week Low-Calorie Formula Diet - Results From the Lifestyle Intervention (LION) Study

SCOPE

Interindividual variations in postprandial metabolism and weight loss outcomes have been reported. The literature suggests links between postprandial metabolism and weight regulation. Therefore, the study aims to evaluate if postprandial glucose metabolism after a glucose load predicts anthropometric outcomes of a weight loss intervention.

METHODS AND RESULTS

Anthropometric data from adults with obesity (18-65 years, body mass index [BMI] 30.0-39.9 kg m-2) are collected pre- and post an 8-week formula-based weight loss intervention. An oral glucose tolerance test (OGTT) is performed at baseline, from which postprandial parameters are derived from glucose and insulin concentrations. Linear regression models explored associations between these parameters and anthropometric changes (∆) postintervention. A random forest model is applied to identify predictive parameters for anthropometric outcomes after intervention. Postprandial parameters after an OGTT of 158 participants (63.3% women, age 45 ± 12, BMI 34.9 ± 2.9 kg m-2) reveal nonsignificant associations with changes in anthropometric parameters after weight loss (p > 0.05). Baseline fat-free mass (FFM) and sex are primary predictors for ∆ FFM [kg].

CONCLUSION

Postprandial glucose metabolism after a glucose load does not predict anthropometric outcomes after short-term weight loss via a formula-based low-calorie diet in adults with obesity.

Specific Genotypes Associated with Differences in Fasting Insulin Levels and Body Mass Index in Healthy Young Males: Implications for Gene-Nutrient Interactions-an Exploratory Study

Background

Genetic variation may significantly impact an individual's susceptibility to diseases, particularly when combined with specific nutrients. Additionally, genetic variations can lead to interindividual differences in metabolic responses.

Objective

The present study explores the association between gene variants and observed interindividual differences in metabolic responses.

Methods

The study included 30 healthy males (aged 20-34) who underwent a fasting period and subsequently consumed a standardized meal. Blood samples were collected both before and after the meal to assess metabolic changes. BMI served as an indirect measure for assessing physiological responses associated with body composition. Appetite changes were assessed using an online Visual Analog 100-point Scale. Buccal swabs were collected to analyze genetic variants in single nucleotide polymorphisms (SNPs).

Results

The data underwent multiple regression analysis, revealing significant associations with 3 SNPs and their metabolic status: the insulin-receptor substrate 1 (IRS1) gene variant rs2943641, genotypes CT and CC, with elevated fasting insulin levels (R2 = 0.639, P = < 0.0001); the mitochondrial uncoupling protein 1 (UCP1) gene variant rs1800592, genotypes GG and GA, with increased BMI (R2 = 0.261, P = 0.007); and the peroxisome proliferator-activated receptor γ2 (PPARγ2) gene variant rs1801282, genotypes GG and GC, with increased BMI (R2 = 0.200, P = 0.024).

Conclusions

Therefore, our study established significant associations between these 3 SNPs and differences in fasting insulin levels and BMI within our cohort.

Characterizing Precision Nutrition Discourse on Twitter: Quantitative Content Analysis

BACKGROUND

It is possible that tailoring dietary approaches to an individual's genomic profile could provide optimal dietary inputs for biological functioning and support adherence to dietary management protocols. The science required for such nutrigenetic and nutrigenomic profiling is not yet considered ready for broad application by the scientific and medical communities; however, many personalized nutrition products are available in the marketplace, creating the potential for hype and misleading information on social media. Twitter provides a unique big data source that provides real-time information. Therefore, it has the potential to disseminate evidence-based health information, as well as misinformation.

OBJECTIVE

We sought to characterize the landscape of precision nutrition content on Twitter, with a specific focus on nutrigenetics and nutrigenomics. We focused on tweet authors, types of content, and presence of misinformation.

METHODS

Twitter Archiver was used to capture tweets from September 1, 2020, to December 1, 2020, using keywords related to nutrition and genetics. A random sample of tweets was coded using quantitative content analysis by 4 trained coders. Codebook-driven, quantified information about tweet authors, content details, information quality, and engagement metrics were compiled and analyzed.

RESULTS

The most common categories of tweets were precision nutrition products and nutrigenomic concepts. About a quarter (132/504, 26.2%) of tweet authors presented themselves as science experts, medicine experts, or both. Nutrigenetics concepts most frequently came from authors with science and medicine expertise, and tweets about the influence of genes on weight were more likely to come from authors with neither type of expertise. A total of 14.9% (75/504) of the tweets were noted to contain untrue information; these were most likely to occur in the nutrigenomics concepts topic category.

CONCLUSIONS

By evaluating social media discourse on precision nutrition on Twitter, we made several observations about the content available in the information environment through which individuals can learn about related concepts and products. Tweet content was consistent with the indicators of medical hype, and the inclusion of potentially misleading and untrue information was common. We identified a contingent of users with scientific and medical expertise who were active in discussing nutrigenomics concepts and products and who may be encouraged to share credible expert advice on precision nutrition and tackle false information as this technology develops.

Association between Genotype and the Glycemic Response to an Oral Glucose Tolerance Test: A Systematic Review

The inter-individual variability of metabolic response to foods may be partly due to genetic variation. This systematic review aims to assess the associations between genetic variants and glucose response to an oral glucose tolerance test (OGTT). Three databases (PubMed, Web of Science, Embase) were searched for keywords in the field of genetics, OGTT, and metabolic response (PROSPERO: CRD42021231203). Inclusion criteria were available data on single nucleotide polymorphisms (SNPs) and glucose area under the curve (gAUC) in a healthy study cohort. In total, 33,219 records were identified, of which 139 reports met the inclusion criteria. This narrative synthesis focused on 49 reports describing gene loci for which several reports were available. An association between SNPs and the gAUC was described for 13 gene loci with 53 different SNPs. Three gene loci were mostly investigated: transcription factor 7 like 2 (TCF7L2), peroxisome proliferator-activated receptor gamma (PPARγ), and potassium inwardly rectifying channel subfamily J member 11 (KCNJ11). In most reports, the associations were not significant or single findings were not replicated. No robust evidence for an association between SNPs and gAUC after an OGTT in healthy persons was found across the identified studies. Future studies should investigate the effect of polygenic risk scores on postprandial glucose levels.

Research at the Academy of Nutrition and Dietetics: What, How, and Why?

Research is essential to further advance our understanding of the role of nutrition and dietetics in maintenance and improvement of health. Research is also essential for nutrition and dietetics professionals to create and provide evidence-based interventions, including medical nutrition therapy (MNT) provided by registered dietitian nutritionists (RDNs). Given this critical role of research, the Academy of Nutrition and Dietetics (Academy) has a variety of resources to assist its members in accessing, understanding, participating in, conducting, and disseminating nutrition research. These resources are comprehensive and include opportunities to participate in research (e.g., Nutrition Research Network (NRN) and Data Science Center (DSC)), tools to aggregate practice data (Nutrition Care Process and Terminology (NCPT) and the Academy of Nutrition and Dietetics Informatics Infrastructure (ANDHII)), funding opportunities to support primary research (e.g., Academy Foundation), resources to understand the latest research informing evidence-based practice (EBP) (e.g., Evidence Analysis Center (EAC)), and avenues for sharing research findings (e.g., Food and Nutrition Conference and Expo (FNCE)). The aim of this paper is to encourage members to get involved in research by describing Academy-based research resources and opportunities to contribute to nutrition and dietetics research, as well as describe specific examples of research conducted at Academy. The information presented can serve as a framework to guide members in engaging in research through the Academy.

Nutrition Concepts for the Treatment of Obesity in Adults

Obesity caused by a positive energy balance is a serious health burden. Studies have shown that obesity is the major risk factor for many diseases like type 2 diabetes mellitus, coronary heart diseases, or various types of cancer. Therefore, the prevention and treatment of increased body weight are key. Different evidence-based treatment approaches considering weight history, body mass index (BMI) category, and co-morbidities are available: lifestyle intervention, formula diet, drugs, and bariatric surgery. For all treatment approaches, behaviour change techniques, reduction in energy intake, and increasing energy expenditure are required. Self-monitoring of diet and physical activity provides an effective behaviour change technique for weight management. Digital tools increase engagement rates for self-monitoring and have the potential to improve weight management. The objective of this narrative review is to summarize current available treatment approaches for obesity, to provide a selective overview of nutrition trends, and to give a scientific viewpoint for various nutrition concepts for weight loss.

A Novel Personalized Systems Nutrition Program Improves Dietary Patterns, Lifestyle Behaviors and Health-Related Outcomes: Results from the Habit Study

Personalized nutrition may be more effective in changing lifestyle behaviors compared to population-based guidelines. This single-arm exploratory study evaluated the impact of a 10-week personalized systems nutrition (PSN) program on lifestyle behavior and health outcomes. Healthy men and women (n = 82) completed the trial. Individuals were grouped into seven diet types, for which phenotypic, genotypic and behavioral data were used to generate personalized recommendations. Behavior change guidance was also provided. The intervention reduced the intake of calories (−256.2 kcal; p < 0.0001), carbohydrates (−22.1 g; p < 0.0039), sugar (−13.0 g; p < 0.0001), total fat (−17.3 g; p < 0.0001), saturated fat (−5.9 g; p = 0.0003) and PUFA (−2.5 g; p = 0.0065). Additionally, BMI (−0.6 kg/m²; p < 0.0001), body fat (−1.2%; p = 0.0192) and hip circumference (−5.8 cm; p < 0.0001) were decreased after the intervention. In the subgroup with the lowest phenotypic flexibility, a measure of the body’s ability to adapt to environmental stressors, LDL (−0.44 mmol/L; p = 0.002) and total cholesterol (−0.49 mmol/L; p < 0.0001) were reduced after the intervention. This study shows that a PSN program in a workforce improves lifestyle habits and reduces body weight, BMI and other health-related outcomes. Health improvement was most pronounced in the compromised phenotypic flexibility subgroup, which indicates that a PSN program may be effective in targeting behavior change in health-compromised target groups.