Hypertension
Conditions
Keywords
Hypertension, Microbiome, Probiotics, Treatment
Brief summary
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.
Detailed description
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.
Interventions
BIOLOGICALProbiotic powder
Probiotic powder containing 10 strains from Lactobacillus and Bifidobacterium genus.
BIOLOGICALPlacebo powder
Placebo powder containing maltodextrin and no probiotics.
Sponsors
Beijing Municipal Education Commission
Chinese Academy of Medical Sciences, Fuwai Hospital
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
DOUBLE (Subject, Investigator)
Eligibility
Sex/Gender
ALL
Age
18 Years to 60 Years
Healthy volunteers
No
Inclusion criteria
1. Age 18\ 60 years. 2. Grade 1 hypertension and part of prehypertension (initial diagnosis or free from antihypertensive drugs within 2 weeks): 130 mmHg ≤ Average office SBP \< 160 mmHg, and/or 85 mmHg ≤ Average office DBP \< 100 mmHg, according to the 2018 Chinese Guidelines for Prevention and Treatment of Hypertension and National guideline for hypertension management in China (2019). 3. Patients with informed consent after thorough explanation.
Exclusion criteria
1. Antibiotics or probiotics usage within the last 2 weeks. 2. Participants of other clinical trials currently or within last 3 months. 3. Antihypertensive medications usage currently or within last 2 weeks. 4. Diagnosed secondary hypertension 5. History of diabetes mellitus. 6. History of peripheral atherosclerosis. 7. Severe hepatic or renal diseases (ALT \>3 times the upper limit of normal value, or end-stage renal disease on dialysis or eGFR \<30 mL/min/1.73 m2, or serum creatinine \>2.5 mg/dl \[\>221 μmol/L\]). 8. History of stroke (not including lacunar infarction and transient ischemic attack \[TIA\]). 9. History of coronary heart disease. 10. Sustained atrial fibrillation or arrhythmias at recruitment disturbing the electronic BP measurement. 11. NYHA class III-IV heart failure; Hospitalization for chronic heart failure exacerbation within last 6 months. 12. Severe valvular diseases; Potential for surgery or percutaneous valve replacement within the study period. 13. Dilated cardiomyopathy; Hypertrophic cardiomyopathy; Rheumatic heart disease; Congenital heart disease. 14. Other severe diseases influencing the entry or survival of participants, such as malignant tumor or acquired immune deficiency syndrome. 15. Cognitive impairment or severe neuropsychiatric comorbidities who are incapable of providing their own informed consent. 16. Participants preparing for or under pregnancy and/or lactation. 17. With special diet habits, such as vegetarians. 18. Active gastritis or enteritis; gastrointestinal ulcers or bleeding; post-gastrointestinal surgery, such as intestinal excision. 19. Other conditions inappropriate for recruitment according to the investigators.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Change in Office Systolic Blood Pressure (SBP) | From baseline to day 56 | Change in Office Systolic Blood Pressure (SBP) |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Change in Office SBP | Baseline, Day28, Day 56, Day 84 | Change in Office SBP |
| Change in Office Diastolic Blood Pressure (DBP) | Baseline, Day28, Day 56, Day 84 | Change in Office Diastolic Blood Pressure (DBP) |
| Change in average SBP via 24-hour Ambulatory BP Monitoring | Baseline, Day28, Day 56, Day 84 | Change in average SBP via 24-hour Ambulatory BP Monitoring |
| Change in average DBP via 24-hour Ambulatory BP Monitoring | Baseline, Day28, Day 56, Day 84 | Change in average DBP via 24-hour Ambulatory BP Monitoring |
| Change in daytime average SBP via 24-hour Ambulatory BP Monitoring | Baseline, Day28, Day 56, Day 84 | Change in daytime average SBP via 24-hour Ambulatory BP Monitoring |
| Change in daytime average DBP via 24-hour Ambulatory BP Monitoring | Baseline, Day28, Day 56, Day 84 | Change in daytime average DBP via 24-hour Ambulatory BP Monitoring |
| Change in nightime average SBP via 24-hour Ambulatory BP Monitoring | Baseline, Day28, Day 56, Day 84 | Change in nightime average SBP via 24-hour Ambulatory BP Monitoring |
| Change in nightime average DBP via 24-hour Ambulatory BP Monitoring | Baseline, Day28, Day 56, Day 84 | Change in nightime average DBP via 24-hour Ambulatory BP Monitoring |
| Number of Participants with Adverse Events (AEs) as a Measure of Safety | Baseline, Day28, Day 56, Day 84 | Number of Participants with Adverse Events (AEs) as a Measure of Safety |
| Changes in Intestinal Microbiota Composition Pre- and Post-intervention via Metagenomic Analysis | Baseline, Day28, Day 56, Day 84 | 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. |
| Changes in Intestinal Microbiota Function Pre- and Post-intervention via Metagenomic Analysis | Baseline, Day28, Day 56, Day 84 | 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. |
| Changes in Intestinal Metabolite Composition Pre- and Post-intervention via Metabolomic Analysis | Baseline, Day28, Day 56, Day 84 | 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 |
| Changes in Serum Metabolite Composition Pre- and Post-intervention via Metabolomic Analysis | Baseline, Day28, Day 56, Day 84 | 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 |
| Change in Fasting Blood Glucose Level | Baseline, Day 56 | Change in Fasting Blood Glucose Level |
| Change in Blood Lipid Level (Total Cholesterol, Total Triglyceride, Low Density Lipoprotein Cholesterol, High Density Lipoprotein Cholesterol) | Baseline, Day 56 | Change in Blood Lipid Level (Total Cholesterol, Total Triglyceride, Low Density Lipoprotein Cholesterol, High Density Lipoprotein Cholesterol) |
| Change in Blood Uric Acid | Baseline, Day 56 | Change in Blood Uric Acid |
| Change in Body Mass Index | Baseline, Day 56 | Change in Body Mass Index |
Countries
China
Outcome results
None listed