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.ย
โSpecific microbial genera, functional pathways and communities associated with BMI changes and the programโs effectiveness were identified,” the study authors reported in the journal Frontiers in Nutritionโ. “[Eighty percent] of participants achieved weight loss.”
Study detailsโ
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 pointsโbaseline/enrollment (T0), early phase (T1) and follow-up phase (T2). Samples were obtained at T1 and T2.
โGenetic 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,โ the researchers wrote.ย โDigbi 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.โ
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.
Resultsโ
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%.
FREE Personalized Nutrition webinarโ
Interested in learning more about the biohacking and personalized nutrition trend? NutraIngredients will host a webinar on the topic on Thursday July 25th at 4 p.m. CET.ย
Presenters will include: Mariรซtte Abrahams,ย CEO and founder atย Qina;ย James Brown, director of nutrigenetics and founder atย Muhdo;ย Sabina Bruehlmann,ย CEO atย Nimble Science andย Grรฉgory Dubourg,ย CEO atย Nutrikรฉo.
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% lostโmore than 10% from T1 to T2.
In addition, the researchers found that BMI is associated with alpha and beta gut microbial diversity. โThe change in BMI is the main correlate of microbiome change,โ they wrote.
They also found that gut microbial genera and pathways are associated with weight loss.
โAnalysis of the gut microbiome identified genera and functional pathways associated with a reduction in BMI, including Akkermansia, Christensenella, Oscillospiraceae, Alistipes and Sutterellaโ, short-chain fatty acid production, and degradation of simple sugars like arabinose, sucrose and melibiose,โ they wrote.ย โNetwork analysis identified a microbiome community associated with BMI, which includes multiple taxa known for associations with BMI and obesity.โ
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.ย
โNonetheless, 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,โ the study concluded.
Source: Frontiersโ
doi:ย 10.3389/fnut.2024.1363079โ
โLongitudinal gut microbial signals are associated with weight loss: insights from a digital therapeutics programโ
Authors: SV Kumbhare et al.
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