Study: AI-assisted personalized diet program supports weight loss and gut microbiome health

The U.S.-based digital therapeutics platform, which uses artificial intelligence (AI) models within a scientific framework, sought to investigate the efficacy and impact of its personalized weight-loss program on the gut microbiome. 

“Specific microbial genera, functional pathways and communities associated with BMI changes and the program’s effectiveness were identified," the study authors reported in the journal Frontiers in Nutrition​. "[Eighty percent] of participants achieved weight loss."

Study details​

The six-month study involved 103 adults (75.7% female, with an average age of 53.55) who all had a body mass index (BMI) of 30 or more, or a BMI between 25 and 30 with a cardiometabolic comorbidity, or diagnosed with prediabetes or type 2 diabetes, non-alcoholic fatty live disease (NAFLD) or pancreatitis. Thirty five percent were on prescribed antidepressants or anxiolytics, and 14.6% were using recreational drugs at baseline. Those with antibiotic consumption at enrollment were excluded.

All participants were enrolled in Digbi Control, a personalized weight-loss program that employs the Digbi Health app. All completed a health questionnaire and were sent a digital weighing scale, buccal swab for genetic profiling and stool sampling kits to assess the microbiome.

The study had three time points—baseline/enrollment (T0), early phase (T1) and follow-up phase (T2). Samples were obtained at T1 and T2.

“Genetic profiling helps assess predisposition to diseases like obesity, chronic gastrointestinal disorders, cardiometabolic conditions, behavioral and mental health traits, as well as food allergies and intolerances,” the researchers wrote. “Digbi Health utilizes gut microbiome data to identify taxonomic and functional markers of health, such as anti-inflammatory compounds, beneficial keystone species, metabolic pathways and food tolerances. This enables an evaluation of how different foods may impact the gut microbial community, supporting personalized food recommendations for weight loss and improved overall health.”

The app was used to track weight, assess dietary intake and monitor metrics such as sleep quality and quantity, exercise type and duration, stress and meditation, energy levels, cravings and recommended foods consumed/avoided. Coaches assessed the dietary intake and assigned a nutrient-density score to meals based on their inflammatory response, fiber diversity and expected insulin response.

Program participants were sent recipes and meal plans that also suited their profile, which included food preferences, cooking styles (family or alone) and food allergies.

Results​

Approximately 80% of participants lost weight, with an average reduction of 2.57 BMI units from T0 to T2. Of these, 14.6% lost 3% to 5% of their bodyweight, 34% lost 5% to 10% and 28.2% lost more than 10%.

There was an average reduction of 1.6 BMI units between T1 and T2: 17.5% lost 3% to 5% of their bodyweight, 31.1% lost 5% to 10% and 14.6% lost more than 10% from T1 to T2.

In addition, the researchers found that BMI is associated with alpha and beta gut microbial diversity. “The change in BMI is the main correlate of microbiome change,” they wrote.

They also found that gut microbial genera and pathways are associated with weight loss.

“Analysis of the gut microbiome identified genera and functional pathways associated with a reduction in BMI, including Akkermansia, Christensenella, Oscillospiraceae, Alistipes and Sutterella​, short-chain fatty acid production, and degradation of simple sugars like arabinose, sucrose and melibiose,” they wrote. “Network analysis identified a microbiome community associated with BMI, which includes multiple taxa known for associations with BMI and obesity.”

The researchers noted several limitations of the study, including the findings being derived from a weight-loss cohort, information not being collected on longitudinal changes in factors that influence microbiome composition such as medication changes or disease diagnosis, not including a control group as all participants took part in the intervention, and the two-time-point design that limited the ability to capture fluctuations in the microbiome. 

“Nonetheless, our findings provide new insights into the effects of dietary and lifestyle changes on the longitudinal evolution of the gut microbiome and its potential involvement in weight loss and warrant consideration by the broader scientific community,” the study concluded.

Source: Frontiers​
doi: 10.3389/fnut.2024.1363079​
“Longitudinal gut microbial signals are associated with weight loss: insights from a digital therapeutics program”
Authors: SV Kumbhare et al.