Gut microbiota was found to play a causal role in the pathogenesis of hypertension. Probiotics were shown to have a potential anti-hypertensive effect in human/rodent studies. This study aims to explore the effect, safety, and underlying mechanisms of the combination of probiotics, containing 10 strains from Lactobacillus and Bifidobacterium, on hypertension, compared with placebo.
Background: Primary hypertension is the leading risk factor of cardiovascular diseases and all-cause mortality, and contributes to severe global health burden. Emerging evidence has shown a close association between gut microbiota and hypertension. Fecal transplantation from hypertensive patients/animals to germ-free mice caused elevation of blood pressure, indicating a causal role of gut dysbiosis in hypertension. Probiotics were found to have a potential anti-hypertensive effect in both human and rodent studies. Based on the investigators' previous findings of metagenomics analysis of hypertensive, prehypertensive patients and healthy control, hypertensive and prehypertensive patients were lack of probiotics. Therefore, the investigators developed this study to explore the effect, safety, and underlying mechanisms of the combination of probiotics, containing 10 strains from Lactobacillus and Bifidobacterium, on hypertension, compared with placebo. Objective: To explore the effect, safety, and underlying mechanisms of the combination of probiotics on grade 1 primary hypertension and prehypertension. Study Design: A multicenter, randomized, double-blinded, placebo-controlled pilot study. Data quality control and statistical analysis: The investigators have invited professional statistic analysts to assist in analyzing data and a third party to supervise data quality. Ethics: The Ethics Committee of Fuwai Hospital approved this study. Informed consent before patient enrollment is required.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
DOUBLE
Enrollment
115
Probiotic powder containing 10 strains from Lactobacillus and Bifidobacterium genus.
Placebo powder containing maltodextrin and no probiotics.
Fu Wai Hospital, Chinese Academy of Medical Sciences
Beijing, Beijing Municipality, China
Longgang District People's Hospital of Shenzhen
Shenzhen, Guangdong, China
Renmin Hospital of Wuhan University
Wuhan, Hubei, China
The Second Affiliated Hospital of Baotou Medical Collage
Baotou, Neimenggu, China
Change in Office Systolic Blood Pressure (SBP)
Change in Office Systolic Blood Pressure (SBP)
Time frame: From baseline to day 56
Change in Office SBP
Change in Office SBP
Time frame: Baseline, Day28, Day 56, Day 84
Change in Office Diastolic Blood Pressure (DBP)
Change in Office Diastolic Blood Pressure (DBP)
Time frame: Baseline, Day28, Day 56, Day 84
Change in average SBP via 24-hour Ambulatory BP Monitoring
Change in average SBP via 24-hour Ambulatory BP Monitoring
Time frame: Baseline, Day28, Day 56, Day 84
Change in average DBP via 24-hour Ambulatory BP Monitoring
Change in average DBP via 24-hour Ambulatory BP Monitoring
Time frame: Baseline, Day28, Day 56, Day 84
Change in daytime average SBP via 24-hour Ambulatory BP Monitoring
Change in daytime average SBP via 24-hour Ambulatory BP Monitoring
Time frame: Baseline, Day28, Day 56, Day 84
Change in daytime average DBP via 24-hour Ambulatory BP Monitoring
Change in daytime average DBP via 24-hour Ambulatory BP Monitoring
Time frame: Baseline, Day28, Day 56, Day 84
Change in nightime average SBP via 24-hour Ambulatory BP Monitoring
Change in nightime average SBP via 24-hour Ambulatory BP Monitoring
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Renji Hospital, Shanghai Jiaotong University School of Medicine
Shanghai, Shanghai Municipality, China
Sichuan Provincial People's Hospital
Chengdu, Sichuan, China
Time frame: Baseline, Day28, Day 56, Day 84
Change in nightime average DBP via 24-hour Ambulatory BP Monitoring
Change in nightime average DBP via 24-hour Ambulatory BP Monitoring
Time frame: Baseline, Day28, Day 56, Day 84
Number of Participants with Adverse Events (AEs) as a Measure of Safety
Number of Participants with Adverse Events (AEs) as a Measure of Safety
Time frame: Baseline, Day28, Day 56, Day 84
Changes in Intestinal Microbiota Composition Pre- and Post-intervention via Metagenomic Analysis
Intestinal microbiota composition is obtained through sequencing of DNAs from feces samples and bioinformatic analysis. Changes in the intestinal microbiota composition before and after intervention (probiotics or placebo) is defined as a secondary outcome. This is stratified by: 1. Randomization (probiotics or placebo); 2. Changes in office SBP.
Time frame: Baseline, Day28, Day 56, Day 84
Changes in Intestinal Microbiota Function Pre- and Post-intervention via Metagenomic Analysis
Intestinal microbiota function is obtained through sequencing of DNAs from feces samples and bioinformatic analysis according to functions related to detected genes. Changes in the intestinal microbiota function before and after intervention (probiotics or placebo) is defined as a secondary outcome. This is stratified by: 1. Randomization (probiotics or placebo); 2. Changes in office SBP.
Time frame: Baseline, Day28, Day 56, Day 84
Changes in Intestinal Metabolite Composition Pre- and Post-intervention via Metabolomic Analysis
Metabolomics analysis is a quantitative analysis of all metabolites in the sample. Metabolites in feces are detected using liquid or gas chromatography combined with mass spectrometry, and the composition and abundance of each metabolite are obtained. Changes in the intestinal metabolite composition before and after intervention (probiotics or placebo) is defined as a secondary outcome. This is stratified by: 1. Randomization (probiotics or placebo); 2. Changes in office SBP. Randomisation Change in Office SBP
Time frame: Baseline, Day28, Day 56, Day 84
Changes in Serum Metabolite Composition Pre- and Post-intervention via Metabolomic Analysis
Metabolomics analysis is a quantitative analysis of all metabolites in the sample. Metabolites in serum are detected using liquid or gas chromatography combined with mass spectrometry, and the composition and abundance of each metabolite are obtained. Changes in the serum metabolite composition before and after intervention (probiotics or placebo) is defined as a secondary outcome. This is stratified by: 1. Randomization (probiotics or placebo); 2. Changes in office SBP. Randomisation Change in Office SBP
Time frame: Baseline, Day28, Day 56, Day 84
Change in Fasting Blood Glucose Level
Change in Fasting Blood Glucose Level
Time frame: Baseline, Day 56
Change in Blood Lipid Level (Total Cholesterol, Total Triglyceride, Low Density Lipoprotein Cholesterol, High Density Lipoprotein Cholesterol)
Change in Blood Lipid Level (Total Cholesterol, Total Triglyceride, Low Density Lipoprotein Cholesterol, High Density Lipoprotein Cholesterol)
Time frame: Baseline, Day 56
Change in Blood Uric Acid
Change in Blood Uric Acid
Time frame: Baseline, Day 56
Change in Body Mass Index
Change in Body Mass Index
Time frame: Baseline, Day 56