Weight Loss Promotion in Individuals with Obesity through Gut Microbiota Alterations with a Multiphase Modified Ketogenic Diet

Abstract

The occurrence of obesity and related metabolic disorders is rising, necessitating effective long-term weight management strategies. With growing interest in the potential role of gut microbes due to their association with responses to different weight loss diets, understanding the mechanisms underlying the interactions between diet, gut microbiota, and weight loss remains a challenge. This study aimed to investigate the potential impact of a multiphase dietary protocol, incorporating an improved ketogenic diet (MDP-i-KD), on weight loss and the gut microbiota. Using metagenomic sequencing, we comprehensively analyzed the taxonomic and functional composition of the gut microbiota in 13 participants before and after a 12-week MDP-i-KD intervention. The results revealed a significant reduction in BMI (9.2% weight loss) among obese participants following the MDP-i-KD intervention. Machine learning analysis identified seven key microbial species highly correlated with MDP-i-KD, with Parabacteroides distasonis exhibiting the highest response. Additionally, the co-occurrence network of the gut microbiota in post-weight-loss participants demonstrated a healthier state. Notably, metabolic pathways related to nucleotide biosynthesis, aromatic amino acid synthesis, and starch degradation were enriched in pre-intervention participants and positively correlated with BMI. Furthermore, species associated with obesity, such as Blautia obeum and Ruminococcus torques, played pivotal roles in regulating these metabolic activities. In conclusion, the MDP-i-KD intervention may assist in weight management by modulating the composition and metabolic functions of the gut microbiota. Parabacteroides distasonis, Blautia obeum, and Ruminococcus torques could be key targets for gut microbiota-based obesity interventions.

Nutraceutical blends predict enhanced health via microbiota reshaping improving cytokines and life quality: a Brazilian double-blind randomized trial

“…Anon, the flavonolignans show a “phytotherapic prebiotic” effect by its chemical structure. Flavonoids, and lignans, provide carbohydrates, amino acids, and other compounds for microbiota fermentation and metabolism, like prebiotic fibers 70 – 73 . Furthermore, minerals such as zinc 74 , magnesium, and selenium 75 serve as vital cofactors in fortifying the intestinal epithelium and immune system, thereby influencing various metabolic pathways conducive to enhancing intestinal health.…”

Chronic Diseases: A Comprehensive Review of Applications for Prediction of Obesity

“…Machine Learning (ML) and other advanced predictive technologies offer promising tools to fill this gap [38,39]. These technologies can analyse vast arrays of data, from genetic profiles to lifestyle habits, providing personalized insights that can guide more effective intervention strategies [39,40].…”

“…Obesity, characterized by excessive fat accumulation, poses serious health risks and challenges, but ML offers innovative solutions for both its understanding and management [32,52]. By integrating ML into obesity research, scientists and healthcare providers can analyse large, diverse data sets to identify patterns and predictors of obesity that are not immediately apparent through conventional statistical methods [40,46]. One of the primary applications of ML in the context of obesity is in the development of predictive models [5,13].…”