Zala Jenko Pražnikar

Obesity and its associated complications require various lifestyle changes and treatment options. Dietary supplements are considered an attractive alternative to traditional therapy, mainly because they are accessible to the general population. The aim of this study was to investigate the additive effects of a combination of energy restriction (ER) and four dietary supplements on changes in the anthropometric and biochemical parameters in 100 overweight or obese participants who were randomly assigned one of the dietary fibre supplements containing different dietary fibres or a placebo for 8 weeks. The results confirmed that fibre supplements plus ER significantly (p < 0.01) reduced the body weight, body mass index (BMI), fat mass, and visceral fat and ameliorated the lipid profile and inflammation at 4 and 8 weeks after the start of the study, while in the placebo group, significant differences in some parameters were observed only after 8 weeks of ER. A fibre supplement containing glucomannan, inulin, psyllium, and apple fibre was the most effective at reducing the BMI, body weight, and CRP (p = 0.018 for BMI and body weight and p = 0.034 for CRP compared to placebo at the end of the intervention). Overall, the results suggest that dietary fibre supplements in combination with ER may have additional effects on weight loss and the metabolic profile. Therefore, taking dietary fibre supplements may be a feasible approach to improve weight and metabolic health in obese and overweight individuals.

Despite the known effects of diet on gut microbiota composition, not many studies have evaluated the relationship between distinct dietary patterns and gut microbiota. The aim of our study was to determine whether gut microbiota composition could be a useful indicator of a long-term dietary pattern. We collected data from 89 subjects adhering to omnivorous, vegetarian, vegan, and low-carbohydrate, high-fat diet that were equally distributed between groups and homogenous by age, gender, and BMI. Gut microbiota composition was analyzed with a metabarcoding approach using V4 hypervariable region of the 16S rRNA gene. K-means clustering of gut microbiota at the genus level was performed and the nearest neighbor classifier was applied to predict microbiota clustering classes. Our results suggest that gut microbiota composition at the genus level is not a useful indicator of a subject’s dietary pattern, with the exception of a vegan diet that is represented by a high abundance of Prevotella 9. Based on our model, a combination of 26 variables (anthropometric measurements, serum biomarkers, lifestyle factors, gastrointestinal symptoms, psychological factors, specific nutrients intake) is more important to predict an individual’s microbiota composition cluster, with 91% accuracy, than the dietary intake alone. Our findings could serve to develop strategies to educate individuals about changes of some modifiable lifestyle factors, aiming to classify them into clusters with favorable health markers, independent of their dietary pattern.