<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03009565</url>
  </required_header>
  <id_info>
    <org_study_id>0622-16-RMC</org_study_id>
    <nct_id>NCT03009565</nct_id>
  </id_info>
  <brief_title>Does the Human Gut Microbiome Serve as a Novel Personalized Therapeutic Target for Coronary Atherosclerosis?</brief_title>
  <official_title>Does the Human Gut Microbiome Serve as a Novel Personalized Therapeutic Target for Coronary Atherosclerosis?</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Rabin Medical Center</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Weizmann Institute of Science</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Rabin Medical Center</source>
  <brief_summary>
    <textblock>
      Background: The human gastrointestinal system is populated with a variety of symbiotic&#xD;
      microorganisms, namely microbiota. The microbiome is the total genetic data of the&#xD;
      microbiota. The human gut microbiota interacts extensively with the host through metabolic&#xD;
      exchange; thereby contribute to a variety of metabolic and immunologic mechanisms in the&#xD;
      human body. Coronary artery disease (CAD) is major cause of morbidity and mortality worldwide&#xD;
      and is a major field of interest in microbiota research. There have been several findings&#xD;
      that connect the gut microbiota to CAD pathophysiology, but these data relates solely to the&#xD;
      interaction between human gut microbiome and cardiovascular risk factors. As far as known ,&#xD;
      data regarding patients who already developed CAD is lacking.&#xD;
&#xD;
      Aims: To investigate gut microbiota of patients with CAD, thereby allowing the adjustment of&#xD;
      personalized treatment by changing the pro-atherosclerotic environment in the gut.&#xD;
&#xD;
      Methods: Study participants will include patients arriving to Rabin Medical Center with&#xD;
      suspected CAD. Patients will provide medical, lifestyle, and nutritional questionnaires.&#xD;
      Vital signs measurements will be taken as well as fecal samples and/or rectal swabs. Blood&#xD;
      samples will be drawn to measure blood chemistry including lipid profile and&#xD;
      trimethylamine-N-oxide (TMAO) levels. Patients will undergo cardiac CT and/or cardiac&#xD;
      catheterization in accordance with the decision of the cardiologist to evaluate and/or treat&#xD;
      CAD. Genomic DNA will be extracted from stool samples for Microbiome analysis.&#xD;
&#xD;
      Innovation: The hypothesis is that there is a unique microbiota pattern in patients with&#xD;
      coronary atherosclerosis, which may contribute to the pathogenesis and/or expression of CAD.&#xD;
      Knowing the unique microbiota in patients with coronary disease, would render it as novel&#xD;
      target for treatment, either primary or secondary prevention.&#xD;
&#xD;
      Collaboration: Between Cardiology department at Rabin Medical Center and the lab of Prof.&#xD;
      Eran Segal located at the Weizmann Institute of Science. The collaboration between these two&#xD;
      groups will combine the clinical expertise of treating cardiac patients with novel scientific&#xD;
      technology and concept.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Introduction:&#xD;
&#xD;
      The human gastrointestinal system is populated with a variety of symbiotic microorganisms,&#xD;
      namely microbiota. Its total weight is approximately 2 kilograms, containing trillions of&#xD;
      microorganisms. The microbiome is the total genetic (metagenomic) data of the microbiota. In&#xD;
      recent years, the development of efficient methods for genome sequencing and bio-informatics&#xD;
      has enabled fast and accurate quantification and qualification of the microbiome, made&#xD;
      microbiome analysis leading method of microbiota research.&#xD;
&#xD;
      Coronary artery disease (CAD) accounted for more than 8 million deaths yearly worldwide. In&#xD;
      particular, acute coronary syndrome (ACS) remains a major cause of morbidity and mortality&#xD;
      and is responsible for more than 1 million hospital admissions in the United States annually.&#xD;
      The pathophysiologic hallmark of ACS is coronary thrombosis caused by atherosclerotic plaque&#xD;
      injury, with two types of injuries being described. The first is plaque rupture, which&#xD;
      remains the most common cause of coronary athero-thrombosis, and the second is superficial&#xD;
      plaque erosion which is recognized with increasing frequency. As opposed to plaque rupture,&#xD;
      lesions that are caused by erosion do not have thin fibrous caps, abundant inflammatory&#xD;
      cells, or a large lipid core, but rather rich in extracellular matrix, such as proteoglycans&#xD;
      and glycosaminoglycans.&#xD;
&#xD;
      Imaging studies such as coronary computed tomographic angiography (CCTA) and diagnostic&#xD;
      coronary catheterizations with or without optical coherence tomography (OCT) are being used&#xD;
      increasingly in clinical practice in order to characterize the mechanism responsible for&#xD;
      unstable/vulnerable atherosclerotic plaque.&#xD;
&#xD;
      The human gut microbiota interacts extensively with the host through metabolic exchange and&#xD;
      co-metabolism of substrates; thereby contribute to a variety of metabolic and immunologic&#xD;
      mechanism in the human body. CAD is a major field of interest in microbiota research, and&#xD;
      there have been several findings that connect the gut microbiota to CAD pathophysiology.&#xD;
      First, microbiota was associated with metabolic syndrome, namely obesity and insulin&#xD;
      resistance. It is hypothesized that gut microbiota may increase short-chain fatty acid, that&#xD;
      eventually increase appetite, thus causing obesity. Another hypothesis is that gut microbiota&#xD;
      endotoxins may translocate into the bloodstream, elicit inflammatory cascade that eventually&#xD;
      promote atherosclerosis. Second, microbiota may also have a role in the development of&#xD;
      atherosclerosis. In patients with symptomatic atherosclerosis, there is a unique microbiome&#xD;
      pattern that may have pro-inflammatory characteristics. Recently, a unique microbial pattern&#xD;
      was found among patients with high cardiovascular risk profile. Third, gut microbiota&#xD;
      metabolize dietary phosphatidylcholine (lecitine) to produce the metabolite&#xD;
      trimethylamine-N-oxide (TMAO), which is associated with increased risk of cardiovascular&#xD;
      events.&#xD;
&#xD;
      The data published so far relates solely to the interaction between human gut microbiome and&#xD;
      cardiovascular risk factors. To the best of the investigator's knowledge and understanding,&#xD;
      the microbiome analysis of patients with an established diagnosis of CAD (including ACS) is&#xD;
      lacking.&#xD;
&#xD;
      Objectives:&#xD;
&#xD;
      The purpose of the current study is to investigate the gut microbiota of patients with&#xD;
      symptomatic CAD, both in stable and during acute phases. The investigators hypothesize that&#xD;
      the study participants would present with a unique microbiome signature that may provide a&#xD;
      novel insight into the pathophysiology of atherosclerotic CAD while affording putative&#xD;
      therapeutic implications.&#xD;
&#xD;
      After establishing the unique microbiome signature in a large cohort of CAD patients, the&#xD;
      investigators would correlate it to TMAO levels to further investigate its part in the&#xD;
      pathophysiology of CAD. In the final stage, the investigators would try to find ways to&#xD;
      adjust personalized treatment options to change the &quot;pro-atherosclerotic&quot; gut microbiota. By&#xD;
      using data from the current study with the investigators' previous 1000 patient cohort with&#xD;
      known microbiome and nutritional profile, it would be able to search for a specific target&#xD;
      for nutritional intervention, such as probiotics. Then, the investigators would monitor the&#xD;
      patients with sequencing the microbiome after the nutritional intervention.&#xD;
&#xD;
      Methods:&#xD;
&#xD;
      Study design and recruitment. Study participants will be patients aged 30-80 arriving to&#xD;
      Rabin Medical Center with suspected CAD and able to provide informed consent. Participants&#xD;
      will provide medical, lifestyle, and nutritional questionnaires. Blood pressure and&#xD;
      heart-rate measurements will be taken during hospitalization as well as blood tests and fecal&#xD;
      samples and/or rectal swabs. In order to evaluate and/or treat suspected atherosclerotic&#xD;
      disease participants will undergo cardiac CT and/or cardiac catheterization in accordance&#xD;
      with the standard of care and based upon the decision of the treating cardiologist.&#xD;
      Diagnostics and treatment options will be based only on participants' medical condition and&#xD;
      regardless of the aforementioned study protocol.&#xD;
&#xD;
      The control group will be selected to represent an age, sex and cardiovascular risk factors&#xD;
      -matched group without current CAD. Further exclusion criteria in the control group will be&#xD;
      antibiotic consumption in the following 3 months, inflammatory bowel disease, or other&#xD;
      significant chronic disease that may influence the microbiota (such as cancer, autoimmune&#xD;
      disease, and chronic immunosuppressive treatment). The control group will undergo cardiac CT&#xD;
      or coronary angiography according to clinical suspicion in order to rule-out CAD and&#xD;
      irrespective of the study protocol.&#xD;
&#xD;
      Blood samples. 10 ml venous blood will be collected into Ethylenediaminetetraacetic acid&#xD;
      (EDTA) and gel with clot activator -containing tubes from the enrolled patients in all study&#xD;
      participants. The concentrations of serum creatinine, troponin, creatine phosphokinase (CPK),&#xD;
      hemoglobin, triglycerides (TG), total cholesterol (TC), high-density lipoproteins (HDL),&#xD;
      low-density lipoproteins (LDL), glucose, c-reactive protein (CRP), b-type natriuretic peptide&#xD;
      (BNP) and hemoglobin A1c (HbA1C) will be measured by automatic biochemistry analyzer.&#xD;
&#xD;
      In addition, the levels of TMAO will be measured from blood plasma by using Ultra-High&#xD;
      Performance Liquid Chromatography - Mass Spectrometric - Multiple Reaction Monitoring&#xD;
      (UHPLC-MS/MRM) as previously described.&#xD;
&#xD;
      Nutritional profiling. All participants will report their habits of food consumption by&#xD;
      filling up the Food Frequency Questionnaire (FFQ).&#xD;
&#xD;
      Cardiac CT analysis. Selected participants will undergo CT angiography for the evaluation and&#xD;
      quantification of CAD using a 256-slice system (Brilliance iCT, Philips Healthcare,&#xD;
      Cleveland, Ohio). Data will be acquired with a collimation of 96 X 0.625 mm and a gantry&#xD;
      rotation time of 330 ms. Intravenous injection of 60 to 90 ml of nonionic contrast agent at a&#xD;
      flow rate of 5 ml/s will be followed by a 30-ml saline chase bolus (3 ml/s). Acquisition will&#xD;
      be performed during an inspiratory breath hold while the electrocardiogram will be recorded&#xD;
      simultaneously to allow, dependent from the heart rate, retrospective or prospective gating&#xD;
      of the data. All images will be reconstructed with a slice thickness of 0.67 mm and a slice&#xD;
      increment of 0.34 mm. The complete dataset will be transmitted to a dedicated CT workstation&#xD;
      with a 3-dimensional reconstruction tool specifically designed for coronary angiography&#xD;
      (Philips Intellispace Portal, version 7.0) to allow for multiplanar reformations and&#xD;
      quantitative plaque analysis. An independent reader will review all studies. Each vessel&#xD;
      containing significant stenosis will be analyzed in curved multiplanar reformatted images in&#xD;
      long-axis and cross-sectional views. Diameters at the site of maximum stenosis and at&#xD;
      proximal and distal references will be measured. Degree of stenosis will be calculated as the&#xD;
      ratio of the difference between the diameter at maximum stenosis and the mean of diameters at&#xD;
      the proximal and distal references divided by the mean of diameters at proximal and distal&#xD;
      references and expressed as percentage. Remodeling index will be calculated as the outer&#xD;
      vessel area at the site of maximum stenosis divided by the mean of outer vessel areas at&#xD;
      proximal and distal references. Positive remodeling will be defined as a remodeling index ≥&#xD;
      1.05. Plaque volume will be automatically calculated as the volume of all voxels segmented&#xD;
      between the luminal and outer vessel boundaries on curved multiplanar reformatted images.&#xD;
      Proximal and distal references will be used as the proximal and distal ends of the plaques.&#xD;
      The investigators will report the total volume of plaque and volumes of plaque subtypes:&#xD;
      calcified, non-calcified, and mixed plaques.&#xD;
&#xD;
      Cardiac catheterization and percutaneous coronary intervention (PCI). Patients will be&#xD;
      admitted to the catheterization laboratory according to their clinical presentation, taking&#xD;
      into account the current ESC/AHA clinical guidelines. The cardiac catheterization procedure&#xD;
      will be performed using standard percutaneous techniques via the radial or femoral artery.&#xD;
      Coronary lesions will be evaluated by the operator in terms of stenosis by visual estimation&#xD;
      or other using objective measurements, such as quantitative coronary analysis (QCA). Coronary&#xD;
      intervention, including balloon angioplasty and stent implantation will be implemented as&#xD;
      needed and according to the severity of coronary stenosis i.e. (≥70% diameter stenosis).&#xD;
      Adjunctive coronary imaging (OCT or intravascular ultrasound) will be performed according to&#xD;
      operator's discretion and regardless of the study protocol. All patients will be treated&#xD;
      during the procedure with anticoagulation (mostly unfractionated heparin) using careful&#xD;
      monitoring of activated clotting time between 250-300 seconds. After the angioplasty&#xD;
      procedure, all patients will be treated with dual anti-platelet therapy combining aspirin and&#xD;
      P2Y12 inhibitor (clopidogrel, prasugrel or ticagrelor, according to the clinical indication)&#xD;
      for 6-12 months, unless there will be contra-indication, such as treatment with oral&#xD;
      anti-coagulants.&#xD;
&#xD;
      Genomic DNA Extraction and Filtering. Genomic DNA from stool samples will be purified using&#xD;
      PowerMag Soil DNA isolation kit (MoBio) optimized for Tecan automated platform. For shotgun&#xD;
      sequencing, 100 ng of purified DNA will be sheared with a Covaris E220X sonicator.&#xD;
&#xD;
      Microbiome analysis. Microbiome samples will be processed by an automated robotic pipeline in&#xD;
      96-well format. Each sample group collected will be processed robotically for both 16S and&#xD;
      metagenomic sequencing.&#xD;
&#xD;
      Generating microbiome-based features. The investigators will employ and further extend a&#xD;
      computational pipeline that was developed for generating a rich set of features from a&#xD;
      metagenomic sample. These features will be the basis for models that identify&#xD;
      microbiome-based signatures.&#xD;
&#xD;
      Bacterial and viral abundances - Mapping the metagenome sample to a reference bacterial&#xD;
      genome database, and then counting the number of reads mapping to each bacteria, resulting in&#xD;
      a vector of relative bacterial abundances for each sample.&#xD;
&#xD;
      Bacterial diversity - Using the relative bacterial abundances derived above, the&#xD;
      investigators will compute several measures of the diversity of bacteria and viruses in a&#xD;
      metagenome sample (e.g., Shannon entropy of the relative abundance vector, number of bacteria&#xD;
      above some minimal abundance level), as sample diversity was shown to be associated with&#xD;
      certain physiological aspects of the host such as overall adiposity and insulin resistance.&#xD;
&#xD;
      Bacterial growth rates - For each metagenome sample, the investigators will compute a vector&#xD;
      that corresponds to the growth rate of each bacteria in the sample, using a novel method that&#xD;
      was recently developed for this purpose. Briefly, by examining the pattern of sequencing read&#xD;
      coverage (depth) across the length of different bacterial genomes, the investigators found&#xD;
      that many bacteria exhibit a prototypical coverage pattern, consisting of a single trough and&#xD;
      a single peak. Notably, the location of the peak coincides with the bacteria's known origin&#xD;
      of replication, suggesting that the added read coverage near the peak represents newly&#xD;
      replicated DNA. For any given bacteria, the ratio between the peak and trough coverage varies&#xD;
      greatly across samples from different human gut microbiomes, with high ratios being similar&#xD;
      to those obtained during exponential growth phase of bacteria grown in culture, and low&#xD;
      ratios being similar to growth in stationary phase.&#xD;
&#xD;
      Gene abundances - The investigators will compute the relative abundances of genes in&#xD;
      metagenome samples by applying a similar approach to that above for deriving relative&#xD;
      abundances of bacteria. To this end, rather than mapping the reads to the reference bacterial&#xD;
      genome database, the investigators will map them to a reference database of bacterial genes&#xD;
      which was recently extended and that collectively contain over 3 million distinct bacterial&#xD;
      genes. The derived gene abundance vectors are complementary to the bacteria abundance&#xD;
      vectors, with the advantage being mapping to genes whose embedding bacterial genome is&#xD;
      unknown and thus allowing more metagenome sequencing reads to be mapped, and with the&#xD;
      disadvantage of producing a much larger feature vector.&#xD;
&#xD;
      Biological pathway abundances - As another set of features that provide information at the&#xD;
      functional level of the microbiota, the investigators will use the KEGG database of&#xD;
      biological pathways51 and the above vector of gene abundance of each sample to compute an&#xD;
      abundance score for each biological pathway. The key advantage of this set of features is&#xD;
      that its associations provide direct hypotheses regarding the underlying mechanisms through&#xD;
      which the microbiota may be involved with the correlated phenotype.&#xD;
&#xD;
      Sample storage. The samples as well as remaining DNA and frozen serums will be stored in -80C&#xD;
      freezers. Unprocessed stool samples (e.g., not all samples collected annually will be&#xD;
      processed initially) will also be stored in -800C freezers.&#xD;
&#xD;
      Statistical analysis. Clinical data such as vital signs, cardiovascular risk factors (age,&#xD;
      gender, lipid profile, glycemic index, smoking status, previous CAD), chronic co-morbidities,&#xD;
      regular drug use, imaging findings on cardiac CT and/or cardiac catheterization as well as&#xD;
      cardiac enzymes levels will be collected at Rabin Medical Center. At the Weizmann institute&#xD;
      of science, in the computer science department by the Segal Lab, the investigators will&#xD;
      analyze the data. For each parameter an association analyses will be performed to identify&#xD;
      all of the microbiome parameters that are associated with these clinical parameters.&#xD;
&#xD;
      After analyzing the microbiome signatures in those patients, where known probiotic and/or&#xD;
      nutritional interventions can lead to the desired change the investigators will intervene and&#xD;
      then monitor with sequencing the microbiome after the intervention.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Not yet recruiting</last_known_status>
  <start_date>January 2017</start_date>
  <completion_date type="Anticipated">January 2019</completion_date>
  <primary_completion_date type="Anticipated">January 2018</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Cohort</observational_model>
    <time_perspective>Cross-Sectional</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>humam gut microbiome analysis</measure>
    <time_frame>immediate</time_frame>
  </primary_outcome>
  <primary_outcome>
    <measure>TMAO levels</measure>
    <time_frame>immediate</time_frame>
  </primary_outcome>
  <number_of_groups>2</number_of_groups>
  <enrollment type="Anticipated">800</enrollment>
  <condition>Coronary (Artery) Disease</condition>
  <arm_group>
    <arm_group_label>study patients</arm_group_label>
    <description>Study participants will be individuals aged 30-80 arriving to Rabin Medical Center with suspected CAD and able to provide informed consent. Participants will provide medical, lifestyle, and nutritional questionnaires. Blood pressure and heart-rate measurements will be taken during hospitalization as well as blood tests and fecal samples and/or rectal swabs. In order to evaluate and/or treat suspected atherosclerotic disease patients will undergo cardiac CT and/or cardiac catheterization in accordance with the standard of care and based upon the decision of the treating cardiologist. Diagnostics and treatment options will be based only on their medical condition and regardless of the aforementioned study protocol.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>control</arm_group_label>
    <description>The control group will be selected to represent an age, sex and cardiovascular risk factors -matched group without current CAD. Further exclusion criteria in the control group will be antibiotic consumption in the following 3 months, inflammatory bowel disease, or other significant chronic disease that may influence the microbiota (such as cancer, autoimmune disease, and chronic immunosuppressive treatment). The control group will undergo cardiac CT or coronary angiography according to clinical suspicion in order to rule-out CAD and irrespective of the study protocol.</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>coronary artery disease</intervention_name>
    <arm_group_label>study patients</arm_group_label>
  </intervention>
  <biospec_retention>Samples With DNA</biospec_retention>
  <biospec_descr>
    <textblock>
      blood rectal swab&#xD;
    </textblock>
  </biospec_descr>
  <eligibility>
    <study_pop>
      <textblock>
        Study participants will be individuals aged 30-80 arriving to Rabin Medical Center with&#xD;
        suspected CAD and able to provide informed consent. Participants will provide medical,&#xD;
        lifestyle, and nutritional questionnaires. Blood pressure and heart-rate measurements will&#xD;
        be taken during hospitalization as well as blood tests and fecal samples and/or rectal&#xD;
        swabs. In order to evaluate and/or treat suspected atherosclerotic disease patients will&#xD;
        undergo cardiac CT and/or cardiac catheterization in accordance with the standard of care&#xD;
        and based upon the decision of the treating cardiologist. Diagnostics and treatment options&#xD;
        will be based only on their medical condition and regardless of the aforementioned study&#xD;
        protocol.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  aged 30-80&#xD;
&#xD;
          -  arriving to Rabin Medical Center with suspected CAD&#xD;
&#xD;
          -  able to provide informed consent&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  antibiotic consumption in the following 3 months&#xD;
&#xD;
          -  inflammatory bowel disease&#xD;
&#xD;
          -  other significant chronic disease that may influence the microbiota (such as cancer,&#xD;
             autoimmune disease, and chronic immunosuppressive treatment)&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>30 Years</minimum_age>
    <maximum_age>80 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_contact>
    <last_name>Aviv A Shaul, Dr.</last_name>
    <phone>+972-54-2562671</phone>
    <email>aviv.shaul3@gmail.com</email>
  </overall_contact>
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  </reference>
  <reference>
    <citation>Wang Z, Levison BS, Hazen JE, Donahue L, Li XM, Hazen SL. Measurement of trimethylamine-N-oxide by stable isotope dilution liquid chromatography tandem mass spectrometry. Anal Biochem. 2014 Jun 15;455:35-40. doi: 10.1016/j.ab.2014.03.016. Epub 2014 Apr 1.</citation>
    <PMID>24704102</PMID>
  </reference>
  <reference>
    <citation>Korem T, Zeevi D, Suez J, Weinberger A, Avnit-Sagi T, Pompan-Lotan M, Matot E, Jona G, Harmelin A, Cohen N, Sirota-Madi A, Thaiss CA, Pevsner-Fischer M, Sorek R, Xavier R, Elinav E, Segal E. Growth dynamics of gut microbiota in health and disease inferred from single metagenomic samples. Science. 2015 Sep 4;349(6252):1101-1106. doi: 10.1126/science.aac4812. Epub 2015 Jul 30.</citation>
    <PMID>26229116</PMID>
  </reference>
  <verification_date>December 2016</verification_date>
  <study_first_submitted>December 26, 2016</study_first_submitted>
  <study_first_submitted_qc>January 1, 2017</study_first_submitted_qc>
  <study_first_posted type="Estimate">January 4, 2017</study_first_posted>
  <last_update_submitted>January 1, 2017</last_update_submitted>
  <last_update_submitted_qc>January 1, 2017</last_update_submitted_qc>
  <last_update_posted type="Estimate">January 4, 2017</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>coronary artery disease</keyword>
  <keyword>human gut microbiota</keyword>
  <keyword>microbiome</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Atherosclerosis</mesh_term>
    <mesh_term>Coronary Artery Disease</mesh_term>
    <mesh_term>Myocardial Ischemia</mesh_term>
    <mesh_term>Coronary Disease</mesh_term>
  </condition_browse>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03009565
org study id: 0622-16-RMC
nct id: NCT03009565
lead sponsor: 
collaborator: 
Background: The human gastrointestinal system is populated with a variety of symbiotic
      microorganisms, namely microbiota. The microbiome is the total genetic data of the
      microbiota. The human gut microbiota interacts extensively with the host through metabolic
      exchange; thereby contribute to a variety of metabolic and immunologic mechanisms in the
      human body. Coronary artery disease (CAD) is major cause of morbidity and mortality worldwide
      and is a major field of interest in microbiota research. There have been several findings
      that connect the gut microbiota to CAD pathophysiology, but these data relates solely to the
      interaction between human gut microbiome and cardiovascular risk factors. As far as known ,
      data regarding patients who already developed CAD is lacking.

      Aims: To investigate gut microbiota of patients with CAD, thereby allowing the adjustment of
      personalized treatment by changing the pro-atherosclerotic environment in the gut.

      Methods: Study participants will include patients arriving to Rabin Medical Center with
      suspected CAD. Patients will provide medical, lifestyle, and nutritional questionnaires.
      Vital signs measurements will be taken as well as fecal samples and/or rectal swabs. Blood
      samples will be drawn to measure blood chemistry including lipid profile and
      trimethylamine-N-oxide (TMAO) levels. Patients will undergo cardiac CT and/or cardiac
      catheterization in accordance with the decision of the cardiologist to evaluate and/or treat
      CAD. Genomic DNA will be extracted from stool samples for Microbiome analysis.

      Innovation: The hypothesis is that there is a unique microbiota pattern in patients with
      coronary atherosclerosis, which may contribute to the pathogenesis and/or expression of CAD.
      Knowing the unique microbiota in patients with coronary disease, would render it as novel
      target for treatment, either primary or secondary prevention.

      Collaboration: Between Cardiology department at Rabin Medical Center and the lab of Prof.
      Eran Segal located at the Weizmann Institute of Science. The collaboration between these two
      groups will combine the clinical expertise of treating cardiac patients with novel scientific
      technology and concept.
Introduction:

      The human gastrointestinal system is populated with a variety of symbiotic microorganisms,
      namely microbiota. Its total weight is approximately 2 kilograms, containing trillions of
      microorganisms. The microbiome is the total genetic (metagenomic) data of the microbiota. In
      recent years, the development of efficient methods for genome sequencing and bio-informatics
      has enabled fast and accurate quantification and qualification of the microbiome, made
      microbiome analysis leading method of microbiota research.

      Coronary artery disease (CAD) accounted for more than 8 million deaths yearly worldwide. In
      particular, acute coronary syndrome (ACS) remains a major cause of morbidity and mortality
      and is responsible for more than 1 million hospital admissions in the United States annually.
      The pathophysiologic hallmark of ACS is coronary thrombosis caused by atherosclerotic plaque
      injury, with two types of injuries being described. The first is plaque rupture, which
      remains the most common cause of coronary athero-thrombosis, and the second is superficial
      plaque erosion which is recognized with increasing frequency. As opposed to plaque rupture,
      lesions that are caused by erosion do not have thin fibrous caps, abundant inflammatory
      cells, or a large lipid core, but rather rich in extracellular matrix, such as proteoglycans
      and glycosaminoglycans.

      Imaging studies such as coronary computed tomographic angiography (CCTA) and diagnostic
      coronary catheterizations with or without optical coherence tomography (OCT) are being used
      increasingly in clinical practice in order to characterize the mechanism responsible for
      unstable/vulnerable atherosclerotic plaque.

      The human gut microbiota interacts extensively with the host through metabolic exchange and
      co-metabolism of substrates; thereby contribute to a variety of metabolic and immunologic
      mechanism in the human body. CAD is a major field of interest in microbiota research, and
      there have been several findings that connect the gut microbiota to CAD pathophysiology.
      First, microbiota was associated with metabolic syndrome, namely obesity and insulin
      resistance. It is hypothesized that gut microbiota may increase short-chain fatty acid, that
      eventually increase appetite, thus causing obesity. Another hypothesis is that gut microbiota
      endotoxins may translocate into the bloodstream, elicit inflammatory cascade that eventually
      promote atherosclerosis. Second, microbiota may also have a role in the development of
      atherosclerosis. In patients with symptomatic atherosclerosis, there is a unique microbiome
      pattern that may have pro-inflammatory characteristics. Recently, a unique microbial pattern
      was found among patients with high cardiovascular risk profile. Third, gut microbiota
      metabolize dietary phosphatidylcholine (lecitine) to produce the metabolite
      trimethylamine-N-oxide (TMAO), which is associated with increased risk of cardiovascular
      events.

      The data published so far relates solely to the interaction between human gut microbiome and
      cardiovascular risk factors. To the best of the investigator's knowledge and understanding,
      the microbiome analysis of patients with an established diagnosis of CAD (including ACS) is
      lacking.

      Objectives:

      The purpose of the current study is to investigate the gut microbiota of patients with
      symptomatic CAD, both in stable and during acute phases. The investigators hypothesize that
      the study participants would present with a unique microbiome signature that may provide a
      novel insight into the pathophysiology of atherosclerotic CAD while affording putative
      therapeutic implications.

      After establishing the unique microbiome signature in a large cohort of CAD patients, the
      investigators would correlate it to TMAO levels to further investigate its part in the
      pathophysiology of CAD. In the final stage, the investigators would try to find ways to
      adjust personalized treatment options to change the "pro-atherosclerotic" gut microbiota. By
      using data from the current study with the investigators' previous 1000 patient cohort with
      known microbiome and nutritional profile, it would be able to search for a specific target
      for nutritional intervention, such as probiotics. Then, the investigators would monitor the
      patients with sequencing the microbiome after the nutritional intervention.

      Methods:

      Study design and recruitment. Study participants will be patients aged 30-80 arriving to
      Rabin Medical Center with suspected CAD and able to provide informed consent. Participants
      will provide medical, lifestyle, and nutritional questionnaires. Blood pressure and
      heart-rate measurements will be taken during hospitalization as well as blood tests and fecal
      samples and/or rectal swabs. In order to evaluate and/or treat suspected atherosclerotic
      disease participants will undergo cardiac CT and/or cardiac catheterization in accordance
      with the standard of care and based upon the decision of the treating cardiologist.
      Diagnostics and treatment options will be based only on participants' medical condition and
      regardless of the aforementioned study protocol.

      The control group will be selected to represent an age, sex and cardiovascular risk factors
      -matched group without current CAD. Further exclusion criteria in the control group will be
      antibiotic consumption in the following 3 months, inflammatory bowel disease, or other
      significant chronic disease that may influence the microbiota (such as cancer, autoimmune
      disease, and chronic immunosuppressive treatment). The control group will undergo cardiac CT
      or coronary angiography according to clinical suspicion in order to rule-out CAD and
      irrespective of the study protocol.

      Blood samples. 10 ml venous blood will be collected into Ethylenediaminetetraacetic acid
      (EDTA) and gel with clot activator -containing tubes from the enrolled patients in all study
      participants. The concentrations of serum creatinine, troponin, creatine phosphokinase (CPK),
      hemoglobin, triglycerides (TG), total cholesterol (TC), high-density lipoproteins (HDL),
      low-density lipoproteins (LDL), glucose, c-reactive protein (CRP), b-type natriuretic peptide
      (BNP) and hemoglobin A1c (HbA1C) will be measured by automatic biochemistry analyzer.

      In addition, the levels of TMAO will be measured from blood plasma by using Ultra-High
      Performance Liquid Chromatography - Mass Spectrometric - Multiple Reaction Monitoring
      (UHPLC-MS/MRM) as previously described.

      Nutritional profiling. All participants will report their habits of food consumption by
      filling up the Food Frequency Questionnaire (FFQ).

      Cardiac CT analysis. Selected participants will undergo CT angiography for the evaluation and
      quantification of CAD using a 256-slice system (Brilliance iCT, Philips Healthcare,
      Cleveland, Ohio). Data will be acquired with a collimation of 96 X 0.625 mm and a gantry
      rotation time of 330 ms. Intravenous injection of 60 to 90 ml of nonionic contrast agent at a
      flow rate of 5 ml/s will be followed by a 30-ml saline chase bolus (3 ml/s). Acquisition will
      be performed during an inspiratory breath hold while the electrocardiogram will be recorded
      simultaneously to allow, dependent from the heart rate, retrospective or prospective gating
      of the data. All images will be reconstructed with a slice thickness of 0.67 mm and a slice
      increment of 0.34 mm. The complete dataset will be transmitted to a dedicated CT workstation
      with a 3-dimensional reconstruction tool specifically designed for coronary angiography
      (Philips Intellispace Portal, version 7.0) to allow for multiplanar reformations and
      quantitative plaque analysis. An independent reader will review all studies. Each vessel
      containing significant stenosis will be analyzed in curved multiplanar reformatted images in
      long-axis and cross-sectional views. Diameters at the site of maximum stenosis and at
      proximal and distal references will be measured. Degree of stenosis will be calculated as the
      ratio of the difference between the diameter at maximum stenosis and the mean of diameters at
      the proximal and distal references divided by the mean of diameters at proximal and distal
      references and expressed as percentage. Remodeling index will be calculated as the outer
      vessel area at the site of maximum stenosis divided by the mean of outer vessel areas at
      proximal and distal references. Positive remodeling will be defined as a remodeling index ≥
      1.05. Plaque volume will be automatically calculated as the volume of all voxels segmented
      between the luminal and outer vessel boundaries on curved multiplanar reformatted images.
      Proximal and distal references will be used as the proximal and distal ends of the plaques.
      The investigators will report the total volume of plaque and volumes of plaque subtypes:
      calcified, non-calcified, and mixed plaques.

      Cardiac catheterization and percutaneous coronary intervention (PCI). Patients will be
      admitted to the catheterization laboratory according to their clinical presentation, taking
      into account the current ESC/AHA clinical guidelines. The cardiac catheterization procedure
      will be performed using standard percutaneous techniques via the radial or femoral artery.
      Coronary lesions will be evaluated by the operator in terms of stenosis by visual estimation
      or other using objective measurements, such as quantitative coronary analysis (QCA). Coronary
      intervention, including balloon angioplasty and stent implantation will be implemented as
      needed and according to the severity of coronary stenosis i.e. (≥70% diameter stenosis).
      Adjunctive coronary imaging (OCT or intravascular ultrasound) will be performed according to
      operator's discretion and regardless of the study protocol. All patients will be treated
      during the procedure with anticoagulation (mostly unfractionated heparin) using careful
      monitoring of activated clotting time between 250-300 seconds. After the angioplasty
      procedure, all patients will be treated with dual anti-platelet therapy combining aspirin and
      P2Y12 inhibitor (clopidogrel, prasugrel or ticagrelor, according to the clinical indication)
      for 6-12 months, unless there will be contra-indication, such as treatment with oral
      anti-coagulants.

      Genomic DNA Extraction and Filtering. Genomic DNA from stool samples will be purified using
      PowerMag Soil DNA isolation kit (MoBio) optimized for Tecan automated platform. For shotgun
      sequencing, 100 ng of purified DNA will be sheared with a Covaris E220X sonicator.

      Microbiome analysis. Microbiome samples will be processed by an automated robotic pipeline in
      96-well format. Each sample group collected will be processed robotically for both 16S and
      metagenomic sequencing.

      Generating microbiome-based features. The investigators will employ and further extend a
      computational pipeline that was developed for generating a rich set of features from a
      metagenomic sample. These features will be the basis for models that identify
      microbiome-based signatures.

      Bacterial and viral abundances - Mapping the metagenome sample to a reference bacterial
      genome database, and then counting the number of reads mapping to each bacteria, resulting in
      a vector of relative bacterial abundances for each sample.

      Bacterial diversity - Using the relative bacterial abundances derived above, the
      investigators will compute several measures of the diversity of bacteria and viruses in a
      metagenome sample (e.g., Shannon entropy of the relative abundance vector, number of bacteria
      above some minimal abundance level), as sample diversity was shown to be associated with
      certain physiological aspects of the host such as overall adiposity and insulin resistance.

      Bacterial growth rates - For each metagenome sample, the investigators will compute a vector
      that corresponds to the growth rate of each bacteria in the sample, using a novel method that
      was recently developed for this purpose. Briefly, by examining the pattern of sequencing read
      coverage (depth) across the length of different bacterial genomes, the investigators found
      that many bacteria exhibit a prototypical coverage pattern, consisting of a single trough and
      a single peak. Notably, the location of the peak coincides with the bacteria's known origin
      of replication, suggesting that the added read coverage near the peak represents newly
      replicated DNA. For any given bacteria, the ratio between the peak and trough coverage varies
      greatly across samples from different human gut microbiomes, with high ratios being similar
      to those obtained during exponential growth phase of bacteria grown in culture, and low
      ratios being similar to growth in stationary phase.

      Gene abundances - The investigators will compute the relative abundances of genes in
      metagenome samples by applying a similar approach to that above for deriving relative
      abundances of bacteria. To this end, rather than mapping the reads to the reference bacterial
      genome database, the investigators will map them to a reference database of bacterial genes
      which was recently extended and that collectively contain over 3 million distinct bacterial
      genes. The derived gene abundance vectors are complementary to the bacteria abundance
      vectors, with the advantage being mapping to genes whose embedding bacterial genome is
      unknown and thus allowing more metagenome sequencing reads to be mapped, and with the
      disadvantage of producing a much larger feature vector.

      Biological pathway abundances - As another set of features that provide information at the
      functional level of the microbiota, the investigators will use the KEGG database of
      biological pathways51 and the above vector of gene abundance of each sample to compute an
      abundance score for each biological pathway. The key advantage of this set of features is
      that its associations provide direct hypotheses regarding the underlying mechanisms through
      which the microbiota may be involved with the correlated phenotype.

      Sample storage. The samples as well as remaining DNA and frozen serums will be stored in -80C
      freezers. Unprocessed stool samples (e.g., not all samples collected annually will be
      processed initially) will also be stored in -800C freezers.

      Statistical analysis. Clinical data such as vital signs, cardiovascular risk factors (age,
      gender, lipid profile, glycemic index, smoking status, previous CAD), chronic co-morbidities,
      regular drug use, imaging findings on cardiac CT and/or cardiac catheterization as well as
      cardiac enzymes levels will be collected at Rabin Medical Center. At the Weizmann institute
      of science, in the computer science department by the Segal Lab, the investigators will
      analyze the data. For each parameter an association analyses will be performed to identify
      all of the microbiome parameters that are associated with these clinical parameters.

      After analyzing the microbiome signatures in those patients, where known probiotic and/or
      nutritional interventions can lead to the desired change the investigators will intervene and
      then monitor with sequencing the microbiome after the intervention.
observational model: Cohort
time perspective: Cross-Sectional
measure: humam gut microbiome analysis
time frame: immediate
measure: TMAO levels
time frame: immediate
arm group label: study patients
description: Study participants will be individuals aged 30-80 arriving to Rabin Medical Center with suspected CAD and able to provide informed consent. Participants will provide medical, lifestyle, and nutritional questionnaires. Blood pressure and heart-rate measurements will be taken during hospitalization as well as blood tests and fecal samples and/or rectal swabs. In order to evaluate and/or treat suspected atherosclerotic disease patients will undergo cardiac CT and/or cardiac catheterization in accordance with the standard of care and based upon the decision of the treating cardiologist. Diagnostics and treatment options will be based only on their medical condition and regardless of the aforementioned study protocol.
arm group label: control
description: The control group will be selected to represent an age, sex and cardiovascular risk factors -matched group without current CAD. Further exclusion criteria in the control group will be antibiotic consumption in the following 3 months, inflammatory bowel disease, or other significant chronic disease that may influence the microbiota (such as cancer, autoimmune disease, and chronic immunosuppressive treatment). The control group will undergo cardiac CT or coronary angiography according to clinical suspicion in order to rule-out CAD and irrespective of the study protocol.
intervention type: Other
intervention name: coronary artery disease
arm group label: study patients
blood rectal swab
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 30 Years
maximum age: 80 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Aviv A Shaul, Dr.
phone: +972-54-2562671
email: aviv.shaul3@gmail.com
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citation: Wang Z, Levison BS, Hazen JE, Donahue L, Li XM, Hazen SL. Measurement of trimethylamine-N-oxide by stable isotope dilution liquid chromatography tandem mass spectrometry. Anal Biochem. 2014 Jun 15;455:35-40. doi: 10.1016/j.ab.2014.03.016. Epub 2014 Apr 1.
PMID: 24704102
citation: Korem T, Zeevi D, Suez J, Weinberger A, Avnit-Sagi T, Pompan-Lotan M, Matot E, Jona G, Harmelin A, Cohen N, Sirota-Madi A, Thaiss CA, Pevsner-Fischer M, Sorek R, Xavier R, Elinav E, Segal E. Growth dynamics of gut microbiota in health and disease inferred from single metagenomic samples. Science. 2015 Sep 4;349(6252):1101-1106. doi: 10.1126/science.aac4812. Epub 2015 Jul 30.
PMID: 26229116
responsible party type: Sponsor
mesh term: Atherosclerosis
mesh term: Coronary Artery Disease
mesh term: Myocardial Ischemia
mesh term: Coronary Disease