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.

The prevalence of obesity and its associated diseases is increasing. In the current study, 15 obese subjects took part in a 12-week multiphase dietetic protocol incorporating an improved ketogenic diet (MDP-i-KD) (KYLLKS 201806). We investigated the effects of the MDP-i-KD on the anthropometric parameters and the gut microbiota of obese subjects. Our results showed that the MDP-i-KD led to significant reductions in body mass index in obese subjects. The MDP-i-KD significantly decreased the relative abundance of the Lachnospiraceae_ND3007_group, the Eubacterium_hallii_group, and Pseudomonas and Blautia. In addition, gut microbiota co-occurrence networks in obese subjects were restructured to a more healthy condition after weight loss. These results show that the MDP-i-KD enhanced weight loss, which may be associated with dietary-induced changes in the gut microbiome. Our results emphasise the importance of determining the interaction between the host and microbial cells to comprehensively understand the mechanism by which diet affects host physiology and the microbiota.

This study aimed to investigate the effects of a hypocaloric balanced diet (HBD) on anthropometric measures and gut microbiota of 43 people with obesity. Fecal samples were collected from the study subjects at weeks 0 and 12, and a detailed analysis of gut microbiota was performed using 16S rRNA gene sequencing. By comparing anthropometric measures and microbiota changes in subjects before and after the HBD intervention, we revealed the potential effects of HBD on weight loss and gut microbiota. Our results indicated that the HBD resulted in a significant decrease in body mass index (BMI), and most of the physiological indicators were decreased to a greater degree in the effective HBD group (EHBD, weight loss ≥ 5%) than in the ineffective HBD group (IHBD, weight loss < 5%). The HBD intervention also modified the gut microbiota of the subjects with obesity. Specifically, Blautia, Lachnoclostridium, Terrisporobacter, Ruminococcus (R. torques, R. gnavus), and Pseudomonas were significantly reduced. In addition, we employed machine learning models, such as XGBRF and GB models, to rank the importance of various features and identified the top 10 key bacterial genera involved. Gut microbiota co-occurrence networks showed the dominance of healthier microbiota following successful weight loss. These results suggested that the HBD intervention enhanced weight loss, which may be related to diet-induced changes in the gut microbiota.

Objective: To explore the characteristics of cardiopulmonary exercise capacity in adults with different degrees of obesity through cardiopulmonary exercise test (CPET).Methods: From September 2019 to January 2024, the data of patients undergoing CPET in the Rehabilitation Department of the Affiliated Wuxi People’s Hospital of Nanjing Medical University were analyzed retrospectively. A total of 231 cases were included. They were categorized into five groups based on their body mass index (BMI): the control group (18.5 ≤ BMI < 24 kg/m², n = 28), the overweight group (24.0 ≤ BMI < 28 kg/m², n = 48), the mild obesity group (28 ≤ BMI < 35 kg/m², n = 75), the moderate obesity group (35.0 ≤ BMI < 40 kg/m², n = 47), and the severe obesity group (BMI ≥ 40 kg/m², n = 33). Collected informations on the age, gender, height, and weight of five groups of participants. The VO₂ at anaerobic threshold (VO_2AT), percentage of predicted VO_2AT (VO_2AT% Pred), peak oxygen consumption (VO_2peak), percentage of predicted VO_2peak (VO_2peak% Pred), peak kilogram oxygen consumption (VO_2peak/kg), maximum exercise power (WR_max), breathing reserve (BR), maximum heart rate (HR_max), percentage of predicted HR_max (HR_max% Pred), maximum O₂ pulse (VO₂/HR_max), percentage of predicted maximum O₂ pulse (VO₂/HR_max%Pred), maximum relative O₂ pulse (VO₂/HR_max/kg),heart rate response (HRr), forced vital capacity (FVC), ratio of forced expiratory volume to vital capacity in 1 s (FEV1/FVC), percentage of predicted forced vital capacity (FVC% Pred), percentage of predicted forced expiratory volume ratio of 1 s (FEV1% Pred), peak expiratory flow rate (PEF), maximum exercise ventilation (VE_max), maximum voluntary ventilation (MVV) and other indicators during the CPET were collected. Single factor analysis of variance was used to compare the mean of each index between groups. Spearman correlation analysis was used to analyze the correlation between BMI and various indicators.Results: There was no statistical significance in gender composition, age, height, and exercise habit of the five groups of participants (P > 0.05). The body mass and BMI of the five groups had significant differences (P < 0.001). In terms of cardiopulmonary exercise capacity, there were statistical differences among the five groups in the overall distribution of VO_2AT (H = 37.370,P < 0.001), VO_2AT/kg (H = 34.747, P < 0.001), VO_2peak (H = 23.018,P< 0.001), VO_2peak/kg (H = 66.606, P < 0.001) and WR_max%Pred (H = 45.136, P < 0.001). There was no significant difference among the five groups in the overall distribution of VO_2AT%Pred, VO_2peak%Pred and WR_max. There were statistical significant difference among the five groups in HR_max (F = 2.443, P = 0.048), HR_max%Pred (F = 6.920, P < 0.001), VO₂/HR_max (F = 8.803, P < 0.001), VO₂/HR_max%Pred (F = 11.354, P < 0.001), VO2/HRmax/kg (F = 18.688, P < 0.001) and BR (F = 6.147, P < 0.001) and HRr (F = 9.467, P < 0.001). There were no significant differences among the five groups in RER_max (F = 0.336, P > 0.05). In terms of static pulmonary function, there were significant differences among the five groups in FVC%Pred (F = 4.577, P = 0.001), FEV1%Pred (F = 3.681, P = 0.006) and FEV1/FVC (F = 3.344, P = 0.011). There was no differences among the five groups in MVV(P> 0.05), and there were significant differences among the five groups in VE_max (P = 0.005) In terms of correlation analysis, BMI was positively correlated with VO_2AT,VO_2peak, VE_max and VO₂/HR_max, and negatively correlated with VO_2AT/kg, VO_2peak/kg,WR_max%Pred, HR_max%Pred, VO₂/HR_max%Pred, VO₂/HR_max/kg,BR and HRr. In terms of static pulmonary function, BMI was negatively correlated with FVC%Pred, FEV1%Pred.Conclusion: With the aggravation of obesity, the maximum exercise ability of adults decreases, VO_2peak/kg and VO₂/HR_max%Pred decreases, and the breathing reserve decreases.