AI-driven personalized nutrition shows promise in improving gut health

AI-driven personalized nutrition shows promise in improving gut health

A six-week pilot study shows that tailored diets powered by artificial intelligence can improve gut microbiome diversity and reduce diet-related health risks, although more research is needed.

Artificial intelligence (AI)-based personalized nutrition programs have the potential to positively impact the gut microbiome in humans. However, additional research is needed to determine the use of microbiome-shaped gut tactics for personalized nutrition.

A current oneNutrientsStudy examines the effects of AI-powered personalized nutrition programs on the gut microbiome of healthy individuals.

The health benefits of personalized nutrition

A healthy diet and lifestyle are crucial to reducing the risk of non-communicable diseases such as diabetes, cancer, obesity and cardiovascular disease. Despite these guidelines, rates of diet-related illnesses continue to rise, reflecting significant variability in each person's response to food. Therefore, there remains an urgent need for new personalized strategies as an alternative to the ineffective “one-diet-fits-all” approach.

In recent years, researchers have become increasingly interested in the potential of personalized nutritional plans to alleviate health conditions such as cardiometabolic diseases and promote healthy aging.

AI technology in nutrition

Food scientists and nutrition experts have recently implemented AI technologies to promote sustainable, eco-friendly and personalized diets. For example, AI-driven chatbots have been developed to create optimal diet plans for weight loss and manage diabetes, while an evidence-based AI Virtual Dietsian was recently created to answer diet-related questions for cancer patients.

For personalized nutrition, robust machine learning models can support digital health systems, wearable sensors and mobile applications, which are now monitored to assess the effectiveness of generated nutritional recommendations customized for an individual's needs and characteristics.

However, modern personalized nutrition programs appear to underestimate the importance of biological factors that influence the variability of an individual's responses to food in relation to their health.

About the study

Researchers in the current study evaluated the effects of a six-week AI-based personalized nutrition program intervention on the gut microbiota composition of healthy individuals. Diet-driven changes in macronutrient levels, anthropometric and biochemical traits, and other gut microbial modifications were also assessed.

A pilot study was conducted with twenty-nine healthy participants recruited from the Center for Research and Technology (CERTH) in Greece. The Protein Project instructed selected candidates to use a digital smartphone health application that provides guidelines for maintaining a healthy, nutritionally sound and active lifestyle.

The Protein Mobile App delivered daily and weekly meal recommendations based on a novel AI-personalized nutritionist. This AI-based application takes into account the user's dietary preferences, health conditions and physical characteristics to suggest personalized appropriate diet plans.

At baseline (pre-protein), nutrition and study participants set nutrition and physical activity (PA) goals that could be achieved through an active lifestyle and adherence to a Mediterranean diet designed to meet the individual's specific needs. Personalized nutrition and PA plans were automatically generated by the AI ​​advisor and delivered to participants via the Protein app on smartphones.

After this period (post-protein), the dietitian assessed the participants' progress at the follow-up visit.

Study results

The average age of the study cohort was 35 years, all of whom lived above the poverty line. Most study participants were married and non-smokers. Of 29 people, 20 exceeded the recommended daily energy intake.

Genomic sequencing of V3-V4 regions of 16S ribosomal ribonucleic acid (rRNA) was performed on 58 samples collected from 29 individuals. In total, three phyla, 19 classes, 44 orders, 82 families and 231 genera were identified.

FirmlyAndBacteroidotawere dominant gut microbiomes identified at baseline and the six-week follow-up visit. At both points in time,Prevotella, BacteroidesAndFaCalibacteriumwere frequently identified. However, higher gut microbiota diversity and abundance were observed at the post-protein TimePoint compared to pre-protein baseline levels.

Rhodospirillaleswere the most upregulated amplicon sequence variants (ASVs) ranked by significance, followed byEubacterium Coprostanoligenes groupAndRuminococcusGenera. The functional potential of the observed taxonomic changes was assessed through metagenomic analyses, which identified 12 pathways of nominal significance, most of which were associated with microbial metabolic processes and purine degradation.

The post-protein time point was associated with significant reductions in carbohydrate, protein, and total energy intake. The mean decreases of 39%, 33% and 14% in alcohol/beverage, sweets and fast food intake were also observed at the end of the intervention. Notably, adherence to the Mediterranean diet did not change between time points.

No significant changes in anthropometric measurements were observed, except for a small but significant reduction in mean waist circumference. PA levels were consistently variable both before and after protein in the study cohort.

Changes in sweet intake were positively correlated with body weight, fat, waist circumference and hemoglobin measurements. A robust positive association between fat intake and fullnessOscillospiraceaewas observed.

A strong positive association between urea andLachnospiraceae wasobservedwhereasa negative correlation between cholesterol levels andOscillibacterwas reported.

Conclusions

AI-assisted personalized nutritional interventions have the potential to promote overall health by facilitating the healthy proliferation of the gut microbiome. In the current study, these changes in the gut microbial ecosystem resulted in reduced constipation, bloating, and inflammatory bowel syndrome symptoms while supporting immune function.

To validate these results and provide a holistic assessment of the impact of personalized nutrition approaches on AI-based nutrients, future studies with longer follow-up periods and larger sample sizes are needed.

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