xml: <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/NCT06037759</url>
    </required_header>
    <id_info>
      <org_study_id>LHS0082</org_study_id>
      <nct_id>NCT06037759</nct_id>
    </id_info>
    <brief_title>Novel Cardiovascular Biomarkers in Patients With Kidney Disease</brief_title>
    <acronym>CBKD</acronym>
    <official_title>Novel Cardiovascular Biomarkers in Patients With Kidney Disease</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Liverpool University Hospitals NHS Foundation Trust</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
    </sponsors>
    <source>Liverpool University Hospitals NHS Foundation Trust</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>
        Chronic kidney disease (CKD) is a long-term condition where the kidneys do not work as well&#xD;
        as they should. End-stage kidney failure (ESKD) is the final, irreparable stage of chronic&#xD;
        kidney disease (CKD), where kidney function has worsened, so the kidneys can no longer&#xD;
        function independently.&#xD;
  &#xD;
        At this stage, dialysis is required to remove waste products and excess fluid from the blood.&#xD;
        There are two types of dialysis. In haemodialysis (HD), blood is pumped out of the body to an&#xD;
        artificial kidney machine and returned to the body by tubes that connect a person to the&#xD;
        machine. In peritoneal dialysis (PD), the inside lining of the belly acts as a natural&#xD;
        filter. PD has the advantage of being gentler on the heart. HD causes significant stress to&#xD;
        the heart by reducing the blood flow to the heart muscle, resulting in heart failure,&#xD;
        irregular rhythms, and eventually sudden heart death. A large observational study showed that&#xD;
        HD patients had 48% worse survival in the first two years than PD patients.&#xD;
  &#xD;
        Several molecules ('biomarkers') can be detected in blood and inform doctors of heart damage.&#xD;
        Studying the form and function of proteins (Proteomics), including how they work and interact&#xD;
        with each other inside cells in patients, could help identify the onset of heart problems. HD&#xD;
        patients are also prone to body fat changes (cholesterol/lipids). Due to high cholesterol,&#xD;
        there is build-up on the walls of arteries, causing their hardening. In HD patients, this&#xD;
        process is faster due to abnormalities in lipid structure. Therefore, studying the heart&#xD;
        biomarkers, protein, and lipid makeup of HD patients may help to find people at substantial&#xD;
        risk of heart and vascular problems and if they are likely to become unwell due to these&#xD;
        heart problems.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        Currently, there is no specific approach to stratify CV risk in HD patients; therefore,&#xD;
        patients are not offered targeted preventative interventions. This novel project will&#xD;
        characterise circulating biomarkers and proteomics of myocyte damage, cardiac stress,&#xD;
        fibrosis, and inflammation, including lipid composition. Understanding the cardiac&#xD;
        biomarkers, targeted proteomics and lipidomics in HD patients as early predictors of CV&#xD;
        outcomes will help better decisions on treatment choices and earlier interventions to improve&#xD;
        outcomes in these patients. Proteomics and lipidomics, analysed with machine learning&#xD;
        techniques, may offer new opportunities to improve risk stratification in these patients. The&#xD;
        successful introduction of novel agents, comprising proprotein convertase&#xD;
        subtilisin-like/kexin type 9 inhibitors, low-dose oral anticoagulants, sodium-glucose&#xD;
        cotransporter 2 inhibitors, glucagon-like peptide-1 agonists, anti-inflammatory agents, and&#xD;
        icosapent ethyl, offers an opportunity to reduce the burden of recurrent CV risk further&#xD;
        based on their risk stratification. This study aims to obtain pilot data for promising&#xD;
        cardiac biomarkers, proteomics and lipidomics, validating them against control groups and&#xD;
        establishing prospective changes of the new markers and their relation to the major adverse&#xD;
        cardiac events (MACE).&#xD;
  &#xD;
        Study Objectives&#xD;
  &#xD;
          1. To determine circulating plasma levels of new cardiac biomarkers (cMyC, galectin 3) in&#xD;
             incident HD patients by comparing them to control groups (PD and CKD 3-4 (not on&#xD;
             dialysis)) and to correlate with traditional biomarkers (hsTnT).&#xD;
  &#xD;
          2. To evaluate the lipidome as a marker of CVD risk in incident HD patients by studying the&#xD;
             indices of HDL quality and quantity, including HDL-particle number, HDL cholesterol,&#xD;
             apolipoprotein (apo) A-I levels, serum amyloid A (SAA) content and HDL-cholesterol&#xD;
             efflux capacity, and paraoxonase activity of apoB-depleted serum.&#xD;
  &#xD;
          3. To evaluate proteomic signature as a marker of cardiac disease risk in incident HD&#xD;
             patients by studying the proteomic platform of untargeted high-value proteins for CVD&#xD;
             risk (as an exploratory analysis).&#xD;
  &#xD;
          4. To explore the association between proposed cardiac biomarkers, proteomics, lipidome and&#xD;
             MACE (as an exploratory analysis).&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Not yet recruiting</overall_status>
    <start_date type="Anticipated">November 1, 2023</start_date>
    <completion_date type="Anticipated">November 1, 2026</completion_date>
    <primary_completion_date type="Anticipated">November 1, 2025</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>Major Adverse Cardiac Events</measure>
      <time_frame>12 months</time_frame>
      <description>An exploratory analysis of all-cause mortality and Major Adverse Cardiac Events (MACE). MACE is defined as a composite of CV death, Ischemic Heart Disease (IHD), myocardial infarction (MI), stroke/TIA, Heart Failure, Cardiac revascularisation (percutaneous coronary intervention and coronary artery bypass graft), carotid endarterectomy. The follow-up will be 12 months for all patients. This will be correlated with biomarker, proteomic and lipidomic data.</description>
    </primary_outcome>
    <number_of_groups>2</number_of_groups>
    <enrollment type="Anticipated">100</enrollment>
    <condition>Haemodialysis Complication</condition>
    <condition>Major Adverse Cardiac Events</condition>
    <arm_group>
      <arm_group_label>Cases (N=50):</arm_group_label>
      <description>Patients with incident ESKD managed by HD (n=50)</description>
    </arm_group>
    <arm_group>
      <arm_group_label>Controls (N=50)</arm_group_label>
      <description>Patients with Incident ESKD managed by PD (n=20) Patients with CKD stage 3-4 (not on dialysis) with hypertension as a key risk factor for CKD and CVD (n=30)</description>
    </arm_group>
    <intervention>
      <intervention_type>Diagnostic Test</intervention_type>
      <intervention_name>Cardiac Biomarkers</intervention_name>
      <description>Blood samples will be collected at baseline (within 6 weeks of dialysis start), at 6 months post-commencement and 12 months post-commencement of haemodialysis. The blood sampling will be mid-week samples taken at the dialysis start for haemodialysis patients, with a similar approach for the PD controls. For the CKD controls, the blood samples will be scheduled around routine clinic attendance, adhering where possible to the time intervals for HD cases and PD controls.</description>
      <arm_group_label>Cases (N=50):</arm_group_label>
      <arm_group_label>Controls (N=50)</arm_group_label>
    </intervention>
    <intervention>
      <intervention_type>Diagnostic Test</intervention_type>
      <intervention_name>Lipidomics</intervention_name>
      <description>Blood samples will be collected at baseline (within 6 weeks of dialysis start), at 6 months post-commencement and 12 months post-commencement of haemodialysis. The blood sampling will be mid-week samples taken at the dialysis start for haemodialysis patients, with a similar approach for the PD controls. For the CKD controls, the blood samples will be scheduled around routine clinic attendance, adhering where possible to the time intervals for HD cases and PD controls.</description>
      <arm_group_label>Cases (N=50):</arm_group_label>
      <arm_group_label>Controls (N=50)</arm_group_label>
    </intervention>
    <intervention>
      <intervention_type>Diagnostic Test</intervention_type>
      <intervention_name>Proteomics</intervention_name>
      <description>Blood samples will be collected at baseline (within 6 weeks of dialysis start), at 6 months post-commencement and 12 months post-commencement of haemodialysis. The blood sampling will be mid-week samples taken at the dialysis start for haemodialysis patients, with a similar approach for the PD controls. For the CKD controls, the blood samples will be scheduled around routine clinic attendance, adhering where possible to the time intervals for HD cases and PD controls.</description>
      <arm_group_label>Cases (N=50):</arm_group_label>
      <arm_group_label>Controls (N=50)</arm_group_label>
    </intervention>
    <biospec_retention>Samples Without DNA</biospec_retention>
    <biospec_descr>
      <textblock>
        Up to 30ml of blood will be collected for processing to serum or plasma/red cell pellet for&#xD;
        downstream analysis.&#xD;
  &#xD;
        Novel Biomarkers: Galactin-3, cMyC, Troponin. Lipidomics Proteomics&#xD;
      </textblock>
    </biospec_descr>
    <eligibility>
      <study_pop>
        <textblock>
          Adults aged ≥45 years (or ≥18 with a history of diabetes) for both cases and controls.&#xD;
          Cardiovascular risk steeply increases after the age of 45 years. For this exploratory&#xD;
          analysis, we intend to target patients at high risk of cardiovascular disease.&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
          Patients aged≥45 years (or ≥18 with a history of diabetes). b. Cases: Incident&#xD;
          haemodialysis patients c. A comparative arm of peritoneal dialysis patients and CKD 3-4&#xD;
          (not on dialysis) with hypertension as a key risk factor for CVD.&#xD;
  &#xD;
          d. Capable of understanding the purpose and risks of the study, fully informed, and given&#xD;
          informed consent.&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            1. Patients with pre-existing heart disease will be excluded.&#xD;
  &#xD;
            2. Patients with active cancer.&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>18 Years</minimum_age>
      <maximum_age>N/A</maximum_age>
      <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
    </eligibility>
    <overall_official>
      <last_name>Anirudh Rao, PhD</last_name>
      <role>Principal Investigator</role>
      <affiliation>Liverpool University Hospital NHS Trust</affiliation>
    </overall_official>
    <overall_contact>
      <last_name>Anirudh Rao, PhD</last_name>
      <phone>01517063487</phone>
      <email>anirudh.rao@liverpoolft.nhs.uk</email>
    </overall_contact>
    <verification_date>August 2023</verification_date>
    <study_first_submitted>September 7, 2023</study_first_submitted>
    <study_first_submitted_qc>September 7, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">September 14, 2023</study_first_posted>
    <last_update_submitted>September 14, 2023</last_update_submitted>
    <last_update_submitted_qc>September 14, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">September 18, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <keyword>Chronic Kidney Disease</keyword>
    <keyword>End Stage Kidney Disease</keyword>
    <keyword>Haemodialysis</keyword>
    <keyword>Biomarkers</keyword>
    <keyword>Major Adverse Cardiac Events</keyword>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Kidney Diseases</mesh_term>
      <mesh_term>Cardiovascular Diseases</mesh_term>
    </condition_browse>
    <patient_data>
      <sharing_ipd>No</sharing_ipd>
      <ipd_description>However, the samples will be bio-banked at Liverpool University Biobank which can be shared with researchers.</ipd_description>
    </patient_data>
    <!-- Results have not yet been posted for this study                                          -->
  </clinical_study>
  
  
text: 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/NCT06037759
  org study id: LHS0082
  nct id: NCT06037759
  lead sponsor: 
  has dmc: No
  is fda regulated drug: No
  is fda regulated device: No
  Chronic kidney disease (CKD) is a long-term condition where the kidneys do not work as well
        as they should. End-stage kidney failure (ESKD) is the final, irreparable stage of chronic
        kidney disease (CKD), where kidney function has worsened, so the kidneys can no longer
        function independently.
  
        At this stage, dialysis is required to remove waste products and excess fluid from the blood.
        There are two types of dialysis. In haemodialysis (HD), blood is pumped out of the body to an
        artificial kidney machine and returned to the body by tubes that connect a person to the
        machine. In peritoneal dialysis (PD), the inside lining of the belly acts as a natural
        filter. PD has the advantage of being gentler on the heart. HD causes significant stress to
        the heart by reducing the blood flow to the heart muscle, resulting in heart failure,
        irregular rhythms, and eventually sudden heart death. A large observational study showed that
        HD patients had 48% worse survival in the first two years than PD patients.
  
        Several molecules ('biomarkers') can be detected in blood and inform doctors of heart damage.
        Studying the form and function of proteins (Proteomics), including how they work and interact
        with each other inside cells in patients, could help identify the onset of heart problems. HD
        patients are also prone to body fat changes (cholesterol/lipids). Due to high cholesterol,
        there is build-up on the walls of arteries, causing their hardening. In HD patients, this
        process is faster due to abnormalities in lipid structure. Therefore, studying the heart
        biomarkers, protein, and lipid makeup of HD patients may help to find people at substantial
        risk of heart and vascular problems and if they are likely to become unwell due to these
        heart problems.
  Currently, there is no specific approach to stratify CV risk in HD patients; therefore,
        patients are not offered targeted preventative interventions. This novel project will
        characterise circulating biomarkers and proteomics of myocyte damage, cardiac stress,
        fibrosis, and inflammation, including lipid composition. Understanding the cardiac
        biomarkers, targeted proteomics and lipidomics in HD patients as early predictors of CV
        outcomes will help better decisions on treatment choices and earlier interventions to improve
        outcomes in these patients. Proteomics and lipidomics, analysed with machine learning
        techniques, may offer new opportunities to improve risk stratification in these patients. The
        successful introduction of novel agents, comprising proprotein convertase
        subtilisin-like/kexin type 9 inhibitors, low-dose oral anticoagulants, sodium-glucose
        cotransporter 2 inhibitors, glucagon-like peptide-1 agonists, anti-inflammatory agents, and
        icosapent ethyl, offers an opportunity to reduce the burden of recurrent CV risk further
        based on their risk stratification. This study aims to obtain pilot data for promising
        cardiac biomarkers, proteomics and lipidomics, validating them against control groups and
        establishing prospective changes of the new markers and their relation to the major adverse
        cardiac events (MACE).
  
        Study Objectives
  
          1. To determine circulating plasma levels of new cardiac biomarkers (cMyC, galectin 3) in
             incident HD patients by comparing them to control groups (PD and CKD 3-4 (not on
             dialysis)) and to correlate with traditional biomarkers (hsTnT).
  
          2. To evaluate the lipidome as a marker of CVD risk in incident HD patients by studying the
             indices of HDL quality and quantity, including HDL-particle number, HDL cholesterol,
             apolipoprotein (apo) A-I levels, serum amyloid A (SAA) content and HDL-cholesterol
             efflux capacity, and paraoxonase activity of apoB-depleted serum.
  
          3. To evaluate proteomic signature as a marker of cardiac disease risk in incident HD
             patients by studying the proteomic platform of untargeted high-value proteins for CVD
             risk (as an exploratory analysis).
  
          4. To explore the association between proposed cardiac biomarkers, proteomics, lipidome and
             MACE (as an exploratory analysis).
  observational model: Cohort
  time perspective: Prospective
  measure: Major Adverse Cardiac Events
  time frame: 12 months
  description: An exploratory analysis of all-cause mortality and Major Adverse Cardiac Events (MACE). MACE is defined as a composite of CV death, Ischemic Heart Disease (IHD), myocardial infarction (MI), stroke/TIA, Heart Failure, Cardiac revascularisation (percutaneous coronary intervention and coronary artery bypass graft), carotid endarterectomy. The follow-up will be 12 months for all patients. This will be correlated with biomarker, proteomic and lipidomic data.
  arm group label: Cases (N=50):
  description: Patients with incident ESKD managed by HD (n=50)
  arm group label: Controls (N=50)
  description: Patients with Incident ESKD managed by PD (n=20) Patients with CKD stage 3-4 (not on dialysis) with hypertension as a key risk factor for CKD and CVD (n=30)
  intervention type: Diagnostic Test
  intervention name: Cardiac Biomarkers
  description: Blood samples will be collected at baseline (within 6 weeks of dialysis start), at 6 months post-commencement and 12 months post-commencement of haemodialysis. The blood sampling will be mid-week samples taken at the dialysis start for haemodialysis patients, with a similar approach for the PD controls. For the CKD controls, the blood samples will be scheduled around routine clinic attendance, adhering where possible to the time intervals for HD cases and PD controls.
  arm group label: Cases (N=50):
  arm group label: Controls (N=50)
  intervention type: Diagnostic Test
  intervention name: Lipidomics
  description: Blood samples will be collected at baseline (within 6 weeks of dialysis start), at 6 months post-commencement and 12 months post-commencement of haemodialysis. The blood sampling will be mid-week samples taken at the dialysis start for haemodialysis patients, with a similar approach for the PD controls. For the CKD controls, the blood samples will be scheduled around routine clinic attendance, adhering where possible to the time intervals for HD cases and PD controls.
  arm group label: Cases (N=50):
  arm group label: Controls (N=50)
  intervention type: Diagnostic Test
  intervention name: Proteomics
  description: Blood samples will be collected at baseline (within 6 weeks of dialysis start), at 6 months post-commencement and 12 months post-commencement of haemodialysis. The blood sampling will be mid-week samples taken at the dialysis start for haemodialysis patients, with a similar approach for the PD controls. For the CKD controls, the blood samples will be scheduled around routine clinic attendance, adhering where possible to the time intervals for HD cases and PD controls.
  arm group label: Cases (N=50):
  arm group label: Controls (N=50)
  Up to 30ml of blood will be collected for processing to serum or plasma/red cell pellet for
        downstream analysis.
  
        Novel Biomarkers: Galactin-3, cMyC, Troponin. Lipidomics Proteomics
  study pop: 
  sampling method: Probability Sample
  criteria: 
  gender: All
  minimum age: 18 Years
  maximum age: N/A
  healthy volunteers: Accepts Healthy Volunteers
  last name: Anirudh Rao, PhD
  role: Principal Investigator
  affiliation: Liverpool University Hospital NHS Trust
  last name: Anirudh Rao, PhD
  phone: 01517063487
  email: anirudh.rao@liverpoolft.nhs.uk
  responsible party type: Sponsor
  mesh term: Kidney Diseases
  mesh term: Cardiovascular Diseases
  sharing ipd: No
  ipd description: However, the samples will be bio-banked at Liverpool University Biobank which can be shared with researchers.