Does the Human Gut Microbiome Serve as a Novel Personalized Therapeutic Target for Coronary Atherosclerosis?
Does the Human Gut Microbiome Serve as a Novel Personalized Therapeutic Target for Coronary Atherosclerosis?
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.
Inclusion Criteria:

 -  aged 30-80

 -  arriving to Rabin Medical Center with suspected CAD

 -  able to provide informed consent

 Exclusion Criteria:

 -  antibiotic consumption in the following 3 months

 -  inflammatory bowel disease

 -  other significant chronic disease that may influence the microbiota (such as cancer,
 autoimmune disease, and chronic immunosuppressive treatment)