Personalized Nutrition Science for Optimal Health 

Today, there is a widely held notion of the universal “healthy” diet: with collective benefits applicable across all individuals. The U.S. federal dietary guidelines have aimed to establish blueprints for proper nutrition, which in theory should apply to all and lead to the same or at least similar results. However, increasing amounts of forthcoming research implicate the one-size-fits-all approach as fundamentally flawed due to its omission of a multitude of vital personal factors including biomarkers, metabolic capabilities, and genetic predispositions. 

In recent years, research has begun to overturn conventional wisdom surrounding nutrition and dieting, complicating decades of weight loss and health advice as well as urging the need for a reexamination of long-established dietary guidelines relied upon to date. Increasingly, patients are turning away from diet fads and meal plans, opting for a more customized approach which incorporates their individual characteristics. In an attempt to better understand the various elements influencing personal dietary best practices, the medical community is examining the burgeoning field of personalized nutrition. 

What is Personalized Nutrition?

Although the definition of “personalized nutrition” is still evolving, it can be described as “an approach that uses information on individual characteristics to develop targeted nutritional advice, products, or services.” The “individual characteristics” are comprised of physiologic features such as age and gender, fluctuating environmental factors like sleep patterns and physical activity, as well as more innovative markers gained from a person’s genetic or microbiome profile. Personalized nutrition combines science and technology to determine the nutritional requirements and dietary restrictions of each individual in order to design the ultimate personalized diet.

Currently, researchers are in the beginning stages of understanding individual food responses to specific foods. In recent studies, investigators have been able to utilize data collected from thousands of people around the world to create algorithm-based prediction models, which reveal surprising disparities in food responses among individuals.

Although most available data focus on glycemic outcomes, the promising results indicate personalized nutrition may grow as an invaluable tool for the development of customized diets for the maintenance of overall health as well as the management and prevention of disease. 

“We envision that in 5-10 years, one-size-fits-all diets would become obsolete and be replaced by diets that will be based on a combination of individual host and microbiome features, the medical condition to be treated, and personal preferences,” says Dr. Eran Elinav, professor of immunology at the Weizmann Institute of Science in Israel and author of many studies in the field.

Progress in the Field – Personalized Nutrition by Prediction of Glycemic Responses 

Thus far, there has been little research conducted on the possibilities and benefits of personalized nutrition. The most compelling data have come from studies investigating the gut microbiome profile, which implicate the possibility that information from a simple stool sample may be able to predict responses to specific foods. In order to further investigate the variability of food responses in different individuals, Dr. Eran Elinav and colleagues conducted a study aimed at devising improved dietary methods for controlling postprandial blood glucose levels (PPGR) – a major risk factor for prediabetes and type 2 diabetes. 

A patient cohort of 800 participants from Israel was selected and closely monitored. Glucose levels were tested after every meal, for a total 46,898 meals, and high variability in PPGR was found in response to identical meals, implicating the inefficacy of universal dietary recommendations. All of the data obtained from the cohort was then inputted into a machine-learning algorithm that incorporated blood parameters, dietary habits, physical activity, age, and microbiome profiles; the algorithm’s ability to accurately predict personal PPGRs was validated in an independent cohort. 

Afterward, the researchers validated the algorithm’s real-world value in a blinded randomized controlled study in which gut microbiomes and clinical data were used to create personalized diets for participants based on predicted PPGR to specific foods. Results revealed significantly lower postprandial responses and consistent alterations to gut microbiota configuration thus, suggesting the potential of personalized diets to modify elevated PPGR and its metabolic repercussions. 

Revolutionizing Nutrition 

The formulation of individual host and microbiome features into nutritional recommendations in a large cohort by Dr. Elinav was unprecedented and has the potential to revolutionize the approach to nutrition worldwide.

In a follow-up industry-sponsored study published this year, the accuracy of the algorithm was further proved by predicting PPGRs in 293 participants without diabetes in a mostly American Midwestern population. Due to crucial differentiating elements such as environmental factors affecting the microbiome, a supporting study in a different population was essential. 

Similar to previous findings, glycemic responses to identical foods varied significantly from person to person. The study measured anthropometric variables, gut microbial composition, and blood glucose levels using a continuous glucose monitor while participants logged food and activity information. A predictive model considering individual features was used to project individualized PPGRs to an array of food items. Researchers concluded that a model predicting each individual’s response to food that considers several factors and biomarkers proved more successful at controlling PPGRs than current approaches which rely on nutritional content alone.

As this research suggests, a personalized predictive model that takes into account several features unique to an individual such as clinical characteristics, physiological variables, and gut microbiome composition, alongside nutritional content is a more efficacious and accurate method of glycemic control than present dietary approaches. Study authors believe that providing individuals with the tools necessary to manage their glycemic responses based on personal predictions of PPGRs may improve blood glucose control, optimize health outcomes for patients, and assist physicians with dietary planning.  

Current Limitations Facing Personalized Nutrition

Despite the remaining need for extensive research on the clinical applications of personalized nutrition, companies have already begun to commercialize the concept and are marketing tools to the general public. Commercial entities such as DayTwo, Inc., Habit, GenoPalate, and Nutrogenomix, are using the technology to provide consumers with personalized dietary recommendations aimed to predict a person’s PPGR to various foods based on DNA or stool testing. 

Although the ease of use and accessibility of direct-to-consumer testing services may be compelling, there has not been any real validation of these proprietary methods and large-scale clinical trials are lacking. Additionally, the lack of standardization among testing kits remains a large concern with commercial direct-to-consumer kits lacking adequate research and evaluation.

However, due to the rising popularity of testing kits among the general public, physicians may expect increased inquiries from patients which can provide the opportunity for productive conversations. Reports generated by a personalized nutrition company should never replace scientific findings; instead, they should be integrated into the tools available to physicians to enhance dietary planning.

Despite current limitations, the emerging research on the benefits of personalized nutrition reveals the need to reevaluate presently held conceptions about dietary models. Replacing uninformative and incomprehensive values currently underlying nutritional advice with precise variable-derived predictions may lead to improved weight management, better glycemic control, and optimized health outcomes. 

The potential use of comprehensive testing to design individually tailored diet plans may also play a significant role in prevention, diagnosis, and treatment of diseases. Given the microbiome’s central function in many aspects of human health, future testing methods may be able to utilize gathered data to track cancer progression, infection susceptibility, neurologic disorders, and many other conditions. 

In order to grow the burgeoning field of personalized nutrition to its full potential, more large-scale studies must be conducted and predictive models need to be validated before direct-to-consumer testing kits are made available and individualized diets are brought to clinical use.  

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