Intestinal Microbiome and Extremes of Atherosclerosis

Completed

• Conditions: Renal Function; Gastrointestinal Microbiome, Atherosclerosis, Nutrients
• Interventions: Diagnostic Test: Plasma levels of metabolites; Behavioral: Dietary questionnaire; Diagnostic Test: Intestinal microbiome

• Registration Number: NCT03398889
• Lead Sponsor: Lawson Health Research Institute

Brief Summary

Patients attending stroke prevention clinics and a premature atherosclerosis clinic at University Hospital in London, ON, Canada were recruited to the study. They completed a dietary questionnaire, provided stool samples and had blood drawn to measure plasma levels of metabolites produced by the intestinal bacteria.

Detailed Description

Patients were phenotyped by their residual score in linear multiple regression with measured carotid plaque burden as the dependent variable and coronary risk factors were predictors. The residual score essentially represents the distance off the regression line of predicted plaque. They were grouped into three categories: Unexplained atherosclerosis (with more plaque than predicted by risk factors; residual score \>2); Explained (the amount of plaque predicted by risk factors, residual score \>-2 and \<2); and Protected (less plaque than predicted by risk factors, residual score \<-2).

DNA was extracted from stool samples in the lab of Dr. Allen-Vercoe at University of Guelph. RNA makeup of the intestinal microbiome was assessed in the lab of Dr. Gregory Gloor at Western. Plasma levels of trimethylamine n-oxide, p-cresylsulfate, hippuric acid, p-cresyl glucuronide, pheny acetyl glutamine and phenyl sulfate were measured by ultra-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry in the lab of Dr. Bradley Urquhart at Western.

Nutrient intake over the past year was calculated at the Harvard School of Public Health from the 131 item self-reported and semi-quantitative Harvard Food Frequency Questionnaire (FFQ).

Estimated glomerular filtration rate was calculated from the Chronic Kidney Disease Epidemiological (CKD-EPI) equations.

Study Timeline

• Study Start: 2014-07-01
• Primary Completion: 2016-10-15
• Study Completion: 2016-10-15
• Status Verified: 2017-12
• Study First Submitted: 2017-12-12
• Study First Submitted QC: 2018-01-11
• Last Update Submitted: 2018-01-11
• Study First Posted: 2018-01-16
• Last Update Posted: 2018-01-16

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 316

Inclusion Criteria

• Patients attending stroke prevention clinics and a Premature Atherosclerosis Clinic at University Hospital, London, ON, Canada,
• with measurements of carotid plaque burden and the risk factors used in the linear regression model.
• Willing to consent to the protocol approved by the Ethics board

Exclusion Criteria

• Missing data on variables used in the regression model,

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
Unexplained Atherosclerosis phenotype	Plasma levels of metabolites	Residual score in linear regression \>2
Unexplained Atherosclerosis phenotype	Dietary questionnaire	Residual score in linear regression \>2
Explained Atherosclerosis phenotype	Plasma levels of metabolites	Residual score in linear regression \<-2, \<2
Explained Atherosclerosis phenotype	Dietary questionnaire	Residual score in linear regression \<-2, \<2
Explained Atherosclerosis phenotype	Intestinal microbiome	Residual score in linear regression \<-2, \<2
Protected Atherosclerosis phenotype	Dietary questionnaire	Residual score \<-2
Protected Atherosclerosis phenotype	Plasma levels of metabolites	Residual score \<-2
Protected Atherosclerosis phenotype	Intestinal microbiome	Residual score \<-2
Unexplained Atherosclerosis phenotype	Intestinal microbiome	Residual score in linear regression \>2

Primary Outcome Measures

Name	Time	Method
Plasma levels of metabolites in the three phenotypes	Day 1	Plasma levels of trimethylamine n-oxide, p-cresylsulfate, hippuric acid, p-cresyl glucuronide, pheny acetyl glutamine and phenyl sulfate

Secondary Outcome Measures

Name	Time	Method
Bacterial profile of the intestinal microbiome	Day 1	Amplification and sequencing of 16S rRNA gene variable regions
Effect of renal function on plasma levels of metabolites	Day 1	eGFR from CKD-EPI equations
Effect of nutrient intake on plasma levels of metabolites	Day 1	Nutrient analysis from food frequency questionnaire

Trial Locations

Locations (1)

Stroke Prevention & Atherosclerosis Research Centre; 🇨🇦 London, Ontario, Canada