Is this the future of healthy dieting?

Health science is advancing at breakneck speed, with new insights touching on all fields—including nutrition. Precision nutrition analyzes an individual’s response to nutritional and lifestyle intervention, with the goal of designing tailored nutritional recommendations based on dynamic factors in one’s internal and external environments.

“From nutrigenomics to deep phenotyping, many factors need to be taken into account in designing personalized and unbiased nutritional solutions for individuals or population sub-groups,” wrote the authors of a comprehensive review published in Nutrients. “Likewise, a concerted effort among basic, clinical scientists and health professionals will be needed to establish a comprehensive framework allowing the implementation of these new findings at the population level.”

With the ballooning prevalence of obesity and comorbid metabolic disturbances, personalized nutritional approaches may be the answer to preventing and managing such illnesses, according to the authors. Precision nutrition strategies encapsulate genetics, food behavior, dietary habits, and the microbiota/metabolome.

Last May, the NIH unveiled a strategic plan focused on precision nutrition, to accelerate nutrition research over the next decade. “The plan reflects the wide range of nutrition research supported across NIH—over $1.9 billion in fiscal year 2019,” the agency wrote. “The strategic plan calls for a multidisciplinary approach through expanded collaboration across NIH Institutes and Centers to accelerate nutrition science and uncover the role of human nutrition in improving public health and reducing disease.”

Here’s a look at some potential applications and advances in the realm of precision nutrition.

Microbiome

Profiling the gut microbiome has been a hot topic in recent years, with investigators focusing on the impact of nutrition variables on gut biodiversity. The goal is to develop dietary interventions that optimize gut microbial composition based on the individual. Recent studies have shown that gut microbiota contribute to risk of diabetes, heart disease, and metabolic syndrome.

“A relevant aspect of the gut microbiome is the fact that its composition and diversity can be modulated by host genetic makeup,” wrote the Nutrition review authors. “But even more relevant for the precision nutrition field is the fact that the interaction between diet and host genetic background is also able to modulate the composition of the gut microbiota.” 

For example, the authors outlined research that showed that Eubacterium rectale abundance predicted healthier postprandial glucose response, while the abundance of Parabacteroides distasonis was not beneficial.

Diet adherence

The principal goal in nutritional intervention is to determine links between feeding behaviors and metabolic outcomes, including insulin sensitivity, body composition, and lipid biomarkers. Based on such causal relationships, conclusions are drawn on the relationship between nutritional recommendations and specific pockets of the population.

One such example was uncovered recently in a study published in the American Journal of Clinical Nutrition. The findings indicated that carriers of PERILIPIN 1 (PLIN1) variants who partake in late lunches shed fewer pounds during a 28-week weight-loss program. 

The authors hypothesized that the effect was due to impaired mobilization of fat from adipose tissue.

Food monitoring

Keeping tabs on food intake is one thing, but precision nutrition researchers really start to gain insights when they further examine the frequency of foods that are consumed throughout the day, the time of lunch/dinner, snacking characteristics, and more. The collection of accurate data is integral to refining evidence-based understanding. 

One innovative technology to measure quantity of food consumed over time is the Universal Eating Monitor (UEM), essentially a food scale concealed in a dining table, used by researchers to record eating behavior. Intriguingly, UEMs have been in development for nearly 30 years. The Liverpool Obesity Research Network (LORN), for example, has been developing one that they describe as a set of hidden scales connected to a computer. 

“Via these scales, the computer measures the weight of the plate at regular intervals as the participant consumes their meal,” the LORN researchers wrote. “UEMs thus generate eating curves (intake [g] against time [min]), which can be defined as decelerating or accelerating based on the coefficient of the curves.” 

These UEMs can also be used to assess hunger, satiety, and palatability at fixed intervals during the course of the meal, which may relate to hormone release and prescription drug intake. 

The researchers added: “Examining within-meal eating rate has been useful in the study of the effects of drugs on eating behavior. Within-meal changes in eating rate also have a long history of use in defining eating behavior. Decelerating cumulative intake curves associated with the normal biological development of satiety are often absent in the obese.” 

Deep phenotyping

This avenue of precision nutrition involves the expatiation of exact and comprehensive analytics of the individual phenotypic characteristics, and extends beyond traditional biomarkers of diabetes and heart disease, such as blood pressure, BMI, and cholesterol levels. 

Instead, researchers concentrate on granular characteristics of phenotype, such as continuous glucose monitoring in diabetes to capture interindividual and time-dependent variables of pathology to stratify disease. Other variables explored include heart electrophysiology, body composition by dual energy X-ray absorptiometry, ocular pressure, corneal confocal microscopy, or spirometry measures.

Deep phenotyping broadens our knowledge of the underpinnings of pathogenesis and aids with clinical decision-making and enhancing intervention outcomes with respect to diet.

Metabolomics

Understanding exactly how nutrients are metabolized by the body in response to the diet is a field of study referred to as metabolomics. Researchers are now able to assess how different individuals metabolize the same foods in varied fashions, which may impact nutrition outcomes in healthful or unhealthful contexts, as well as shed light on food intolerance and allergy. Metabolomes also differ by population subgroups, such as men vs women and the elderly vs younger people.

The authors of the Nutrients review, for example, noted differences in those who consumed the healthiest diets per WHO recommendations, compared with those eating the unhealthiest diets. Specifically, healthy eaters demonstrated higher urinary levels of hippurate (eg, fruit and vegetables), tartrate (eg, grapes) or dimethylamine (eg, fish), and lower levels of carnitine (eg, red meat).