<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/NCT03797339</url>
  </required_header>
  <id_info>
    <org_study_id>2017YFC0909301</org_study_id>
    <nct_id>NCT03797339</nct_id>
  </id_info>
  <brief_title>Multi-omics Study of Clinical Endpoints in CHD</brief_title>
  <acronym>OmiDETCHD</acronym>
  <official_title>Multi-omics Study of the Individual Differences of Drug Efficacy and Toxicity in Patients With Coronary Heart Disease</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Guangdong Provincial People's Hospital</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>RenJi Hospital</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>West China Hospital</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Xiangya Hospital of Central South University</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>First Affiliated Hospital, Sun Yat-Sen University</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Guangdong Provincial People's Hospital</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      This study aimed to explore underlying mechanisms of individual differences in drugs for&#xD;
      coronary heart disease treatment and its association with adverse consequences. It will&#xD;
      enroll approximately 4000 coronal heart disease patients aged between 18 and 80 years in&#xD;
      mainland China and follow-up for at least 1 years. Questionnaires, anthropometric measures,&#xD;
      laboratory tests, and biomaterials will be collected . The principal clinical outcomes of the&#xD;
      study consist of ischemia attack , cardiac death, renal injury,and myotoxic activity.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The study is a multicenter prospective cohort study, aimed to explore underlying mechanisms&#xD;
      of individual differences in drugs for coronary heart disease treatment and its association&#xD;
      with adverse consequences.The genomic genotype, DNA methylation and metabolome of 1000&#xD;
      patients with coronary heart disease were determined using illumina high-density genotyping&#xD;
      chip, high-throughput sequencing and high-resolution mass spectrometry. Blood exposures of&#xD;
      statins and metoprolol and its metabolites was determined by UPLC-MS/MS.&#xD;
&#xD;
      The biological network using cross-omics analysis was reconstructed to identify potential&#xD;
      causative key genes, bacteria, and endogenous metabolite targets that cause differences in&#xD;
      individual responses. A machine identification algorithm selecting clinical factors and&#xD;
      multi-omics targets was used to establish a predictive mathematical model.&#xD;
&#xD;
      A multi-center clinical cohort of 3000 coronal heart disease patients was used to verify the&#xD;
      effects of various levels of omic targets on drug blood exposures, efficacy and toxic side&#xD;
      effects. A comprehensive model based on multi-target combination of individualized drugs was&#xD;
      constructed, and the predictive effect was clinically analyzed.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Recruiting</last_known_status>
  <start_date type="Actual">July 1, 2017</start_date>
  <completion_date type="Anticipated">December 31, 2020</completion_date>
  <primary_completion_date type="Anticipated">December 31, 2019</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>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Death</measure>
    <time_frame>from date of baseline examination until the date of first documented death,up to 48 months</time_frame>
    <description>All-cause death</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>MACE</measure>
    <time_frame>from date of baseline examination until the date of first documented cardiovascular events,up to 48 months</time_frame>
    <description>MACE was defined as the occurrence of cardiac death, nonfatal myocardial infarctions, coronary revascularisation and cerebral infraction.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Bleeding</measure>
    <time_frame>from date of baseline examination until the date of first documented bleeding,up to 48 months</time_frame>
    <description>Bleeding was the six-month incidence of combined alarming, internal, and nuisance bleeding events defined according to Serebruany et al15. Alarming bleeding included bleeding requiring a transfusion, intracranial bleeding, and life-threatening bleeding. Internal bleeding included haematoma, epistaxis, blood loss from the mouth, vagina, melaena, eye bleed, haematuria, and haematemesis. Nuisance bleeding included easy bruising, bleeding from small cuts, petechiae, and ecchymosis.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Statin-induced myopathy (SIM)</measure>
    <time_frame>from date of baseline examination until the date of first documented SIM,up to 48 months</time_frame>
    <description>The definition of SIM from statin treatment was based on the patients' subjective sense of muscular pain as well as CK elevations. These muscular side effects included myalgia (muscle pain/ache without serum CK elevations), other muscle-related symptoms such as weakness, cramps, spasms, soreness and twitching, CK elevations without physical symptoms, myositis or other muscle symptoms with CK elevations, and rhabdomyolysis.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>CI-AKI</measure>
    <time_frame>more than 6 h within 48 h after Coronary Angiography</time_frame>
    <description>CI-AKI was diagnosed if a patient had an absolute increase in serum creatinine (sCr) concentration ≥ 0.3 mg/dl (26.4 μmol/L) from baseline or a relative increase ≥ 50 % in sCr concentration for more than 6 h within 48 h after surgery</description>
  </secondary_outcome>
  <other_outcome>
    <measure>SYNTAX score</measure>
    <time_frame>more than 6 h within 48 h after Coronary Angiography</time_frame>
    <description>It is mainly used for the treatment of left main coronary artery lesions and/or three-vessel lesions.Patients with a score of ≥33 are recommended for CABG. Patients with a score between 23 and 32 can choose either PCI or CABG. Patients with a score of ≤22 are recommended for PCI and CABG.</description>
  </other_outcome>
  <number_of_groups>2</number_of_groups>
  <enrollment type="Anticipated">4000</enrollment>
  <condition>Coronary Heart Disease</condition>
  <arm_group>
    <arm_group_label>Discovery cohort</arm_group_label>
    <description>1000 cases of coronary heart disease follow-up cohort was used for multi-omics target discovery.During the follow-up period, the information about the occurrence and risk factors of adverse cardiovascular events will be collected.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Validation corhort</arm_group_label>
    <description>3000 coronary heart disease follow-up cohorts was used for validating the results from the discovery corhort. During the follow-up period, the occurrence and risk factors of adverse cardiovascular events.Predictive mathematical models based on multi-omics combination will be constructed finally.</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>risk factors of adverse cardiovascular events</intervention_name>
    <description>During the follow-up period,general information(age, sex, BMI, blood pressure, the history of drink and smoke, medical history, etc).Blood biochemistry parameters（Lipid, hsCRP levels, etc）and other laboratory examination parameters will be collected</description>
    <arm_group_label>Discovery cohort</arm_group_label>
    <arm_group_label>Validation corhort</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>multi-omics target discovery</intervention_name>
    <description>Genome-wide genotype , DNA methylation and metabolomes were determined using illumina high-density genotyping chips, high-throughput sequencing, and high-resolution mass spectrometry respectly. Blood exposure of statins and metoprolol and its metabolites was determined by UPLC-MS/MS.</description>
    <arm_group_label>Discovery cohort</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>validation</intervention_name>
    <description>The genome-wide genotype of patients with coronary heart disease was detected using the illumina chip. The methylation level of the functional region was detected by the target region enrichment methylation sequencing method. Intestinal flora differences were detected using 16SrDNA high-throughput sequencing.</description>
    <arm_group_label>Validation corhort</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>Predictive mathematical models</intervention_name>
    <description>Machine learning algorithms such as multiple linear regression or Bayesian classification are used to optimize clinical factors and multi-group targets to establish predictive mathematical models.</description>
    <arm_group_label>Validation corhort</arm_group_label>
  </intervention>
  <biospec_retention>Samples With DNA</biospec_retention>
  <biospec_descr>
    <textblock>
      Feces,urine,and blood are from patients with coronary heart disease.&#xD;
    </textblock>
  </biospec_descr>
  <eligibility>
    <study_pop>
      <textblock>
        Chinese Han patients with coronary artery disease who have ingested metoprolol and statins&#xD;
        were prospectively recruited from Guangdong General Hospital, Shanghai Jiao Tong&#xD;
        University, Central South University, Sun Yat-sen University and Sichuan University.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  age: 18-80 years&#xD;
&#xD;
          -  Chinese Han patients with coronary artery disease&#xD;
&#xD;
          -  inpatients undergoing coronary angiography or percutaneous coronary intervention&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  renal insufficiency (defined as serum creatinine concentration &gt; 2 times the upper&#xD;
             limit of normal [230 μmol/L], renal transplantation or dialysis)&#xD;
&#xD;
          -  hepatic insufficiency (defined as serum transaminase concentration &gt; 2 times the upper&#xD;
             limit of normal [80 U/L], or a diagnosis of cirrhosis)&#xD;
&#xD;
          -  pre-existing bleeding disorders&#xD;
&#xD;
          -  being pregnant or lactating&#xD;
&#xD;
          -  advanced cancer or haemodialysis&#xD;
&#xD;
          -  history of thyroid problems, and use of antithyroid drugs or thyroid hormone&#xD;
             medication&#xD;
&#xD;
          -  incomplete information about cardiovascular events during follow-up&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>80 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Shilong Zhong, Ph.D</last_name>
    <role>Principal Investigator</role>
    <affiliation>Guangdong Provincial People's Hospital</affiliation>
  </overall_official>
  <overall_contact>
    <last_name>Shilong Zhong, Ph.D</last_name>
    <phone>862083827812</phone>
    <phone_ext>51157</phone_ext>
    <email>zhongsl@hotmail.com</email>
  </overall_contact>
  <overall_contact_backup>
    <last_name>Juer Liu, master</last_name>
    <phone>13430267895</phone>
    <phone_ext>51157</phone_ext>
    <email>liujesysu@163.com</email>
  </overall_contact_backup>
  <location>
    <facility>
      <name>Guangdong General Hospital</name>
      <address>
        <city>Guangzhou</city>
        <state>Guangdong</state>
        <zip>510080</zip>
        <country>China</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Shilong Zhong, Ph.D</last_name>
      <phone>8618620819696</phone>
      <email>zhongsl@hotmail.com</email>
    </contact>
  </location>
  <location>
    <facility>
      <name>The First Affiliated Hospital of Sun Yat-sen University</name>
      <address>
        <city>Guangzhou</city>
        <state>Guangdong</state>
        <zip>510080</zip>
        <country>China</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Chen Liu, MD, PhD</last_name>
      <phone>8615013270269</phone>
      <email>chenliu81@hotmail.com</email>
    </contact>
  </location>
  <location>
    <facility>
      <name>XiangYa Hospital Central South University</name>
      <address>
        <city>Changsha</city>
        <state>Hunan</state>
        <zip>410008</zip>
        <country>China</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Qilin Ma, MD</last_name>
      <phone>86731-84327203</phone>
      <email>mqilin2004@163.com</email>
    </contact>
  </location>
  <location>
    <facility>
      <name>Renji Hospital Affiliated to Shanghai Jiaotong University</name>
      <address>
        <city>Shanghai</city>
        <state>Shanghai</state>
        <zip>200233</zip>
        <country>China</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Linghong Shen, MD, PhD</last_name>
      <phone>8613916495713</phone>
      <email>drshenlinghong@126.com</email>
    </contact>
  </location>
  <location>
    <facility>
      <name>West China Hospital, Sichuan University</name>
      <address>
        <city>Chengdu</city>
        <state>Sichuan</state>
        <zip>610041</zip>
        <country>China</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Liang Ouyang, PhD</last_name>
      <phone>8613880674611</phone>
      <email>ouyangliang@scu.edu.cn</email>
    </contact>
  </location>
  <location_countries>
    <country>China</country>
  </location_countries>
  <verification_date>February 2019</verification_date>
  <study_first_submitted>January 5, 2019</study_first_submitted>
  <study_first_submitted_qc>January 5, 2019</study_first_submitted_qc>
  <study_first_posted type="Actual">January 9, 2019</study_first_posted>
  <last_update_submitted>February 11, 2019</last_update_submitted>
  <last_update_submitted_qc>February 11, 2019</last_update_submitted_qc>
  <last_update_posted type="Actual">February 12, 2019</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Guangdong Provincial People's Hospital</investigator_affiliation>
    <investigator_full_name>ShiLong Zhong</investigator_full_name>
    <investigator_title>Professor</investigator_title>
  </responsible_party>
  <keyword>epigenome</keyword>
  <keyword>metabolome</keyword>
  <keyword>microbiome</keyword>
  <keyword>genome</keyword>
  <keyword>multi-omics targets</keyword>
  <keyword>individual drug use</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Heart Diseases</mesh_term>
    <mesh_term>Coronary Disease</mesh_term>
    <mesh_term>Coronary Artery Disease</mesh_term>
    <mesh_term>Myocardial Ischemia</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/NCT03797339
org study id: 2017YFC0909301
nct id: NCT03797339
lead sponsor: 
collaborator: 
collaborator: 
collaborator: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
This study aimed to explore underlying mechanisms of individual differences in drugs for
      coronary heart disease treatment and its association with adverse consequences. It will
      enroll approximately 4000 coronal heart disease patients aged between 18 and 80 years in
      mainland China and follow-up for at least 1 years. Questionnaires, anthropometric measures,
      laboratory tests, and biomaterials will be collected . The principal clinical outcomes of the
      study consist of ischemia attack , cardiac death, renal injury,and myotoxic activity.
The study is a multicenter prospective cohort study, aimed to explore underlying mechanisms
      of individual differences in drugs for coronary heart disease treatment and its association
      with adverse consequences.The genomic genotype, DNA methylation and metabolome of 1000
      patients with coronary heart disease were determined using illumina high-density genotyping
      chip, high-throughput sequencing and high-resolution mass spectrometry. Blood exposures of
      statins and metoprolol and its metabolites was determined by UPLC-MS/MS.

      The biological network using cross-omics analysis was reconstructed to identify potential
      causative key genes, bacteria, and endogenous metabolite targets that cause differences in
      individual responses. A machine identification algorithm selecting clinical factors and
      multi-omics targets was used to establish a predictive mathematical model.

      A multi-center clinical cohort of 3000 coronal heart disease patients was used to verify the
      effects of various levels of omic targets on drug blood exposures, efficacy and toxic side
      effects. A comprehensive model based on multi-target combination of individualized drugs was
      constructed, and the predictive effect was clinically analyzed.
observational model: Cohort
time perspective: Prospective
measure: Death
time frame: from date of baseline examination until the date of first documented death,up to 48 months
description: All-cause death
measure: MACE
time frame: from date of baseline examination until the date of first documented cardiovascular events,up to 48 months
description: MACE was defined as the occurrence of cardiac death, nonfatal myocardial infarctions, coronary revascularisation and cerebral infraction.
measure: Bleeding
time frame: from date of baseline examination until the date of first documented bleeding,up to 48 months
description: Bleeding was the six-month incidence of combined alarming, internal, and nuisance bleeding events defined according to Serebruany et al15. Alarming bleeding included bleeding requiring a transfusion, intracranial bleeding, and life-threatening bleeding. Internal bleeding included haematoma, epistaxis, blood loss from the mouth, vagina, melaena, eye bleed, haematuria, and haematemesis. Nuisance bleeding included easy bruising, bleeding from small cuts, petechiae, and ecchymosis.
measure: Statin-induced myopathy (SIM)
time frame: from date of baseline examination until the date of first documented SIM,up to 48 months
description: The definition of SIM from statin treatment was based on the patients' subjective sense of muscular pain as well as CK elevations. These muscular side effects included myalgia (muscle pain/ache without serum CK elevations), other muscle-related symptoms such as weakness, cramps, spasms, soreness and twitching, CK elevations without physical symptoms, myositis or other muscle symptoms with CK elevations, and rhabdomyolysis.
measure: CI-AKI
time frame: more than 6 h within 48 h after Coronary Angiography
description: CI-AKI was diagnosed if a patient had an absolute increase in serum creatinine (sCr) concentration ≥ 0.3 mg/dl (26.4 μmol/L) from baseline or a relative increase ≥ 50 % in sCr concentration for more than 6 h within 48 h after surgery
measure: SYNTAX score
time frame: more than 6 h within 48 h after Coronary Angiography
description: It is mainly used for the treatment of left main coronary artery lesions and/or three-vessel lesions.Patients with a score of ≥33 are recommended for CABG. Patients with a score between 23 and 32 can choose either PCI or CABG. Patients with a score of ≤22 are recommended for PCI and CABG.
arm group label: Discovery cohort
description: 1000 cases of coronary heart disease follow-up cohort was used for multi-omics target discovery.During the follow-up period, the information about the occurrence and risk factors of adverse cardiovascular events will be collected.
arm group label: Validation corhort
description: 3000 coronary heart disease follow-up cohorts was used for validating the results from the discovery corhort. During the follow-up period, the occurrence and risk factors of adverse cardiovascular events.Predictive mathematical models based on multi-omics combination will be constructed finally.
intervention type: Other
intervention name: risk factors of adverse cardiovascular events
description: During the follow-up period,general information(age, sex, BMI, blood pressure, the history of drink and smoke, medical history, etc).Blood biochemistry parameters（Lipid, hsCRP levels, etc）and other laboratory examination parameters will be collected
arm group label: Discovery cohort
arm group label: Validation corhort
intervention type: Other
intervention name: multi-omics target discovery
description: Genome-wide genotype , DNA methylation and metabolomes were determined using illumina high-density genotyping chips, high-throughput sequencing, and high-resolution mass spectrometry respectly. Blood exposure of statins and metoprolol and its metabolites was determined by UPLC-MS/MS.
arm group label: Discovery cohort
intervention type: Other
intervention name: validation
description: The genome-wide genotype of patients with coronary heart disease was detected using the illumina chip. The methylation level of the functional region was detected by the target region enrichment methylation sequencing method. Intestinal flora differences were detected using 16SrDNA high-throughput sequencing.
arm group label: Validation corhort
intervention type: Other
intervention name: Predictive mathematical models
description: Machine learning algorithms such as multiple linear regression or Bayesian classification are used to optimize clinical factors and multi-group targets to establish predictive mathematical models.
arm group label: Validation corhort
Feces,urine,and blood are from patients with coronary heart disease.
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 18 Years
maximum age: 80 Years
healthy volunteers: No
last name: Shilong Zhong, Ph.D
role: Principal Investigator
affiliation: Guangdong Provincial People's Hospital
last name: Shilong Zhong, Ph.D
phone: 862083827812
phone ext: 51157
email: zhongsl@hotmail.com
last name: Juer Liu, master
phone: 13430267895
phone ext: 51157
email: liujesysu@163.com
facility: 
status: Recruiting
contact: 
facility: 
status: Recruiting
contact: 
facility: 
status: Recruiting
contact: 
facility: 
status: Recruiting
contact: 
facility: 
status: Recruiting
contact: 
country: China
responsible party type: Principal Investigator
investigator affiliation: Guangdong Provincial People's Hospital
investigator full name: ShiLong Zhong
investigator title: Professor
mesh term: Heart Diseases
mesh term: Coronary Disease
mesh term: Coronary Artery Disease
mesh term: Myocardial Ischemia