The Microbiome as a Modifiable and Predictive Factor in Obesity Treatment: Impact of Nutritional Intervention With Probiotics and Prebiotics.
Trial Snapshot
- Phase
- Not Applicable
- Status
- Enrolling By Invitation
- Sponsor
- Enrollment
- 230
- Locations
- 1
- Primary Endpoint
- Evaluation of the composition of the intestinal microbiome using metagenomic analysis
Study Overview
Brief Summary
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.
Detailed Description
Obesity: The Epidemic of the 21st Century and a Public Health Concern. Obesity is one of the most severe and prevalent non-communicable diseases of the 21st century, representing a global public health problem that affects all age groups. In Spain, it is estimated that over 39% of adults (aged 25-60) are overweight and 20% are obese, with Andalusia being one of the regions with the highest rates, which continue to rise. Obesity is a multifactorial, recurrent, and progressive disease associated with significant physical and psychological complications, as well as considerable morbidity and mortality. It is a key risk factor for numerous chronic conditions, including metabolic syndrome (type 2 diabetes mellitus, hypertension, dyslipidemia) and the associated elevated risk of cardiovascular diseases.
Moreover, obesity can increase the risk of other diseases, including digestive, respiratory, and joint disorders, as well as various types of cancer (esophagus, colon, pancreas, prostate, and breast). Although the pathogenic mechanisms underlying obesity are not fully elucidated, it is understood that obesity is linked to a state of chronic low-grade systemic inflammation. Dysregulated adipose tissue functionality in obese individuals leads to elevated free fatty acid levels and increased production of inflammatory cytokines, establishing a vicious cycle that promotes the hypertrophy and hyperplasia of adipocytes, hallmarks of obesity.
The excessive production of these mediators and their release into the bloodstream have a profound impact on other organs and systems, contributing to the metabolic (e.g., diabetes) and cardiovascular (e.g., endothelial dysfunction, atherosclerosis) alterations that almost invariably accompany obesity. Consequently, obesity is associated with reduced quality of life and has a significant negative socioeconomic impact. It is also a determinant of several "intermediate risk factors," leading to increased mortality and reduced life expectancy.
The treatment of obesity involves lifestyle and dietary changes, often supplemented by pharmacological therapy, including appetite suppressants and fat absorption inhibitors. However, these strategies may be insufficient, and for severe obesity (BMI >35) or morbid obesity (BMI >40), surgical intervention is often necessary. Bariatric surgery, despite its effectiveness in reducing metabolic and cardiovascular comorbidities and improving survival and quality of life, involves significant complications due to patient characteristics and high costs. Moreover, over the last 30 years, there has been a marked increase in the prevalence of morbid obesity and, consequently, a greater demand for bariatric surgery.
While surgery reduces comorbidities and enhances patient outcomes, its effects on the gut microbiota remain suboptimal. As such, specific dietary interventions before and/or after surgery are needed to improve microbial gene richness and ensure long-term metabolic health.
Study Design
- Study Type
- Interventional
- Allocation
- Randomized
- Intervention Model
- Crossover
- Primary Purpose
- Treatment
- Masking
- Single (Investigator)
Eligibility Criteria
- Ages
- 18 Years to 75 Years (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- Yes
Inclusion Criteria
- •Clinical Diagnosis of Obesity and Associated Comorbidities (Prediabetes, Diabetes, Dyslipidemia, Hypertension).
Exclusion Criteria
- •Antibiotic treatment.
- •Pregnancy.
- •Clinical diagnoses of Inflammatory bowel disease.
- •Clinical diagnosis of Celiac disease
- •Clinical diagnosis of Hematological pathologies.
- •Clinical diagnosis of Autoimmune or immunodeficiency diseases.
Arms & Interventions
Placebo
Placebo treated with 500 mg/capsule/day of maltodextrin
Intervention: Prebiotic (Dietary Supplement)
Symbiotic
A combination of prebiotic and probiotic at the same doses.
Intervention: Prebiotic (Dietary Supplement)
Probiotic
capsules with 10^9 CFU/ day of Limosilactobacillus fermentum CECT5716
Intervention: Prebiotic (Dietary Supplement)
Symbiotic
A combination of prebiotic and probiotic at the same doses.
Intervention: Probiotic (Dietary Supplement)
Prebiotic
500 mg/capsule/day of olive leaf extract, containing 35% oleuropein, an amount comparable to what could be consumed through daily intake of extra virgin olive oil.
Intervention: Synbiotic (Dietary Supplement)
Prebiotic
500 mg/capsule/day of olive leaf extract, containing 35% oleuropein, an amount comparable to what could be consumed through daily intake of extra virgin olive oil.
Intervention: Probiotic (Dietary Supplement)
Probiotic
capsules with 10^9 CFU/ day of Limosilactobacillus fermentum CECT5716
Intervention: Synbiotic (Dietary Supplement)
Placebo
Placebo treated with 500 mg/capsule/day of maltodextrin
Intervention: Synbiotic (Dietary Supplement)
Placebo
Placebo treated with 500 mg/capsule/day of maltodextrin
Intervention: Probiotic (Dietary Supplement)
Outcomes
Primary Outcomes
Evaluation of the composition of the intestinal microbiome using metagenomic analysis
Time Frame: From enrollment (T0) to the end of treatment (6 months(T6))
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.
Evaluation of the treatment using integrated data analysis
Time Frame: From enrollment (T0) to the end of treatment (6 months(T6))
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.
Secondary Outcomes
- Evaluation of serological biochemical profile(From enrollment to the end of treatment (6 months))
- Determination of the treatment impact on the metabolome profile(From enrollment (T0) to the end of treatment (6 months(T6)))
Investigators
Alba Rodriguez Nogales
Full professor
Universidad de Granada
