Clinical trial
Impact of Nutritional Intervention With Probiotics and Prebiotics on Obesity.
Invitation only · Not applicable · 1 countries · Registry ID NCT06722443
What this study is about
Obesity is one of the most severe and prevalent non-communicable diseases worldwide, affecting an estimated one-third of the population in Spain. It is a multifactorial disease that, in extreme cases such as morbid obesity, can become highly disabling and is associated with significant morbidity and mortality. This is because it serves as a risk factor for numerous chronic diseases, including metabolic conditions (type 2 diabetes mellitus), cardiovascular diseases (hypertension, atherosclerosis, etc.), and even cancer. The exact etiopathogenic mechanisms are not fully understood, but subclinical inflammation is considered to form the basis of the metabolic (diabetes) and cardiovascular (endothelial dysfunction, dyslipidemia, etc.) disturbances that almost invariably accompany obesity. Additionally, alterations in the composition of the gut microbiota, or dysbiosis, are now recognized as playing a key role in the pathogenesis of obesity. This makes the gut microbiota a highly attractive therapeutic target for both the prevention and treatment of obesity, including less severe forms and morbid obesity. In this context, the use of probiotics or extracts with prebiotic properties represents a particularly interesting strategy against obesity, offering a combination of efficacy and safety for treating these patients. Consequently, the general objective is proposed to evaluate the impact of dietary interventions aimed at modulating dysbiosis through the administration of a probiotic (Lactobacillus fermentum CECT5716), a standardized olive leaf extract with prebiotic properties, or a synbiotic (a combination of the olive leaf extract and L. fermentum CECT5716) on the clinical response of patients with moderate or morbid obesity. This will include determining its relationship with the immuno-metabolic system and the characteristic cardiovascular complications of obesity. Furthermore, the evaluation of these treatments in experimental models of obesity, including morbid obesity requiring surgery, is also proposed. These models will include trials involving fecal material transfer into germ-free mice. These results will add significant value to the project by advancing our understanding of the underlying mechanisms of the disease. This will aid in the establishment of new diagnostic, prognostic, and therapeutic biomarkers, which are of great interest in reducing the incidence and prevalence of this current obesity epidemic. The estimated duration for completing the project is 12 months, with its conclusion anticipated by March 2024.
Basic eligibility
Full registry criteria
Treatments and study arms
Probiotic
Treatment with capsules with 10\^9 CFU/ day of Limosilactobacillus fermentum CECT5716 during 6 months
Prebiotic
Treatment with capsules 500 mg/capsule/day of olive leaf extract, containing 35% oleuropein during 6 months
Synbiotic
A pill with a combination of prebiotic and probiotic at the same doses during 6 months
Primary outcomes
Microbial DNA will be isolated from the intestinal contents (feces) of different groups at various time points (T0 and T6). Taxonomic group identification will be performed through metagenomic sequencing using the Nextera XT Library Preparation Kit (Illumina). Sequencing will be conducted on a NovaSeq-6000 platform. To analyze the microbiota taxonomy, the RAST platform will be used to classify reads into different amplicon sequence variants (ASVs). A dynamic threshold will be applied to filter out false or incorrect ASVs, eliminating those contributing less than 0.1% of the total sequence count. The ASVs table will then be normalized per sample using subsampling (or rarefaction) to a minimum read count. QIIME wrapper scripts (v1.9.1) will be employed to classify reads into taxonomic units and to identify taxa with differential abundance between groups.
The data obtained from the different determinations conducted will be automated for integrated analysis. Variables will be normalized, and qualitative variables will be categorized. Integrated bioinformatics analysis will compare and functionally correlate nutritional data, omics data (microbiomics, metabolomics, and immunological profiles) with clinical phenotypes (obese and morbidly obese patients) and treatments (probiotic, prebiotic, and synbiotic). This analysis will be based on Bayesian methods, which provide a statistical framework enabling the probabilistic integration of information across multiple analysis steps. All data will be analyzed using R and GraphPad Prism (version 8.4.1). This approach will allow the identification of relationships between microbiota impact and the administered treatments, as well as determine which treatment demonstrated the highest efficacy.
Study locations
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