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/NCT06014567</url>
    </required_header>
    <id_info>
      <org_study_id>322446</org_study_id>
      <nct_id>NCT06014567</nct_id>
    </id_info>
    <brief_title>Twins MR Imaging Study</brief_title>
    <official_title>Characterising Biomarkers of Disease and Ageing in Twins Using Magnetic Resonance Imaging</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>King's College London</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
      <collaborator>
        <agency>Guy's and St Thomas' NHS Foundation Trust</agency>
        <agency_class>Other</agency_class>
      </collaborator>
    </sponsors>
    <source>King's College London</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 aims to create a comprehensive Magnetic Resonance Imaging data resource in twins&#xD;
        aged 18 years and older. The data will be used alone or in conjunction with existing data to&#xD;
        explore organ-specific ageing and twin-pair differences related to ageing and disease.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        BACKGROUND Diverse interactions between environmental, genetic, and epigenetic factors shape&#xD;
        individual paths of ageing and disease. In young adulthood, twins are highly similar in most&#xD;
        organ structures, but their similarity decreases over time as they are progressively exposed&#xD;
        to different environments. Twin studies provide an ideal way to investigate how the body ages&#xD;
        and how age-related diseases (such as Alzheimer's disease, heart failure, fatty liver&#xD;
        disease, and cancer) develop. Magnetic Resonance Imaging (MRI) is a type of scan that&#xD;
        produces detailed images of the inside of the body. MRI enables non-invasive and safe&#xD;
        visualisation of age and disease-related changes in the body, often long before clinical&#xD;
        symptoms are perceived. MRI-derived biological features/biomarkers can be used to understand&#xD;
        the influence of environmental exposures on ageing and disease.&#xD;
  &#xD;
        PARTICIPANTS 2500 adult (age 18 and older) volunteers of TwinsUK, the UK's largest adult twin&#xD;
        Biobank and the most clinically detailed globally, will be invited to participate. Interested&#xD;
        individuals will complete screening to confirm study eligibility and their safety for MRI&#xD;
        scanning. Eligible participants will complete informed consent prior to undertaking research&#xD;
        MRI scans of their brain, spine, heart, abdomen and parts of their skeleton and muscles. 350&#xD;
        twins with differences in their data will be invited to repeat the MRI scans about two years&#xD;
        later to explore longitudinal multi-organ imaging correlates of key environmental exposures&#xD;
        based on cross-sectional signals and existing literature.&#xD;
  &#xD;
        PROCEDURES Two 45-minute MRI scans of (1) the head and spine and (2) the abdomen to the upper&#xD;
        thigh.&#xD;
  &#xD;
        OUTCOMES Imaging-derived measures of morphology and function of the brain, spine, abdominal&#xD;
        organs and musculoskeletal tissue. These measures will be used to identify twin pair&#xD;
        differences related to ageing and disease. A comprehensive repository of MRI data will be&#xD;
        created using protocols harmonised with the UK biobank. This will facilitate subsequent&#xD;
        linkage with concurrently acquired samples and historic exposome data in longitudinal twin&#xD;
        cohort.&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Not yet recruiting</overall_status>
    <start_date type="Anticipated">September 2023</start_date>
    <completion_date type="Anticipated">March 2028</completion_date>
    <primary_completion_date type="Anticipated">March 2028</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>BrainAGE score</measure>
      <time_frame>At time of scan (duration 45 mins)</time_frame>
      <description>BrainAGE will be calculated using MRI-derived phenotypes of brain volumetric changes (Cole et al, 2017).</description>
    </primary_outcome>
    <primary_outcome>
      <measure>BodyAGE score</measure>
      <time_frame>At time of scan (duration 45 mins)</time_frame>
      <description>BodyAGE will be calculated using MRI-derived phenotypes of organ and tissue changes in the heart, liver, pancreas, kidneys, spine and muscle (Linge et al, 2018).</description>
    </primary_outcome>
    <enrollment type="Anticipated">2500</enrollment>
    <condition>Aging</condition>
    <intervention>
      <intervention_type>Procedure</intervention_type>
      <intervention_name>Magnetic Resonance Imaging</intervention_name>
      <description>A single (≤45 minutes) brain MRI will include T1w and T2w imaging to assess the morphology and structure of the brain, as well as inflammatory processes. Diffusion-weighted imaging will be used to gain information about internal brain connectivity related to brain functions. MRI, MR angiography (MRA) and fMRI pulse sequences will also be acquired to detect vascular pathologies and brain lesions. T2w morphological images of the whole spine will also be obtained.&#xD;
  A single (≤45 minutes) MR imaging investigation to include cardiovascular, abdominal, and musculoskeletal regions. MRI will be performed to assess the structure and function of these body regions and organs, including functional imaging of the heart. These investigations will include T1w and T2w imaging to assess morphology and structure, mapping studies of T1, T2 and T2*, perfusion imaging and cine imaging to assess the heart dynamically.</description>
    </intervention>
    <eligibility>
      <study_pop>
        <textblock>
          TwinsUK Biobank longitudinal registry twin volunteers.&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Non-Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  Identical or non-identical twins&#xD;
  &#xD;
            -  Gender: Male or Female&#xD;
  &#xD;
            -  Age: 18 years or above at the time of recruitment&#xD;
  &#xD;
            -  Must be able to understand the study information and provide informed consent&#xD;
  &#xD;
            -  Participation in the TwinsUK Biobank&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            -  Pregnancy&#xD;
  &#xD;
            -  Unable to tolerate MRI Procedures, e.g., claustrophobia, severe anxiety&#xD;
  &#xD;
            -  Contraindication to MRI Scanning, e.g., presence of non-MR conditional implants&#xD;
  &#xD;
            -  Any additional condition declared voluntarily by the participant that the principal&#xD;
               investigator (PI) deems likely to affect the study's outcome.&#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>Claire Steves</last_name>
      <role>Study Chair</role>
      <affiliation>King's College London</affiliation>
    </overall_official>
    <overall_contact>
      <last_name>Vicky Bowyer</last_name>
      <phone>+44 (0) 20 7848 4444</phone>
      <email>vicky.bowyer@kcl.ac.uk</email>
    </overall_contact>
    <location>
      <facility>
        <name>King's College London</name>
        <address>
          <city>London</city>
          <zip>SE1 7EH</zip>
          <country>United Kingdom</country>
        </address>
      </facility>
      <contact>
        <last_name>Vicky Bowyer</last_name>
        <phone>+44 (0) 20 7848 4444</phone>
        <email>vicky.bowyer@kcl.ac.uk</email>
      </contact>
      <investigator>
        <last_name>Claire Steves</last_name>
        <role>Principal Investigator</role>
      </investigator>
      <investigator>
        <last_name>Amedeo Chiribiri</last_name>
        <role>Principal Investigator</role>
      </investigator>
      <investigator>
        <last_name>Sebastien Ourselin</last_name>
        <role>Sub-Investigator</role>
      </investigator>
      <investigator>
        <last_name>Joseph Hajnal</last_name>
        <role>Sub-Investigator</role>
      </investigator>
      <investigator>
        <last_name>Vicky Goh</last_name>
        <role>Sub-Investigator</role>
      </investigator>
      <investigator>
        <last_name>Tim Spector</last_name>
        <role>Sub-Investigator</role>
      </investigator>
      <investigator>
        <last_name>Sharon Giles</last_name>
        <role>Sub-Investigator</role>
      </investigator>
      <investigator>
        <last_name>Marc Modat</last_name>
        <role>Sub-Investigator</role>
      </investigator>
      <investigator>
        <last_name>Deborah Hart</last_name>
        <role>Sub-Investigator</role>
      </investigator>
      <investigator>
        <last_name>John Maynard</last_name>
        <role>Sub-Investigator</role>
      </investigator>
      <investigator>
        <last_name>Asif Mazumder</last_name>
        <role>Sub-Investigator</role>
      </investigator>
      <investigator>
        <last_name>Aishah Azam</last_name>
        <role>Sub-Investigator</role>
      </investigator>
      <investigator>
        <last_name>Amanda Isaac</last_name>
        <role>Sub-Investigator</role>
      </investigator>
      <investigator>
        <last_name>Davide Prezzi</last_name>
        <role>Sub-Investigator</role>
      </investigator>
      <investigator>
        <last_name>Olwen Westerland</last_name>
        <role>Sub-Investigator</role>
      </investigator>
      <investigator>
        <last_name>Fiammetta Fedele</last_name>
        <role>Sub-Investigator</role>
      </investigator>
    </location>
    <location_countries>
      <country>United Kingdom</country>
    </location_countries>
    <reference>
      <citation>Cole JH, Poudel RPK, Tsagkrasoulis D, Caan MWA, Steves C, Spector TD, Montana G. Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker. Neuroimage. 2017 Dec;163:115-124. doi: 10.1016/j.neuroimage.2017.07.059. Epub 2017 Jul 29.</citation>
      <PMID>28765056</PMID>
    </reference>
    <reference>
      <citation>Linge J, Borga M, West J, Tuthill T, Miller MR, Dumitriu A, Thomas EL, Romu T, Tunon P, Bell JD, Dahlqvist Leinhard O. Body Composition Profiling in the UK Biobank Imaging Study. Obesity (Silver Spring). 2018 Nov;26(11):1785-1795. doi: 10.1002/oby.22210. Epub 2018 May 22.</citation>
      <PMID>29785727</PMID>
    </reference>
    <verification_date>July 2023</verification_date>
    <study_first_submitted>July 4, 2023</study_first_submitted>
    <study_first_submitted_qc>August 23, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 28, 2023</study_first_posted>
    <last_update_submitted>August 23, 2023</last_update_submitted>
    <last_update_submitted_qc>August 23, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 28, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <keyword>Magnetic resonance imaging (MRI)</keyword>
    <keyword>Twins</keyword>
    <patient_data>
      <sharing_ipd>Yes</sharing_ipd>
      <ipd_description>Access to the data may be requested by application to the TwinsUK Resource Executive Committee (TREC).</ipd_description>
      <ipd_info_type>Study Protocol</ipd_info_type>
      <ipd_info_type>Informed Consent Form (ICF)</ipd_info_type>
      <ipd_time_frame>The data will be available after the primary analyses have been reported and as determined by TREC based on the application data sharing policies. The data will remain available for the foreseeable future with no end date, at present</ipd_time_frame>
      <ipd_access_criteria>See the information in the link.</ipd_access_criteria>
      <ipd_url>https://twinsuk.ac.uk/resources-for-researchers/our-data.</ipd_url>
    </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/NCT06014567
  org study id: 322446
  nct id: NCT06014567
  lead sponsor: 
  collaborator: 
  has dmc: No
  is fda regulated drug: No
  is fda regulated device: No
  This study aims to create a comprehensive Magnetic Resonance Imaging data resource in twins
        aged 18 years and older. The data will be used alone or in conjunction with existing data to
        explore organ-specific ageing and twin-pair differences related to ageing and disease.
  BACKGROUND Diverse interactions between environmental, genetic, and epigenetic factors shape
        individual paths of ageing and disease. In young adulthood, twins are highly similar in most
        organ structures, but their similarity decreases over time as they are progressively exposed
        to different environments. Twin studies provide an ideal way to investigate how the body ages
        and how age-related diseases (such as Alzheimer's disease, heart failure, fatty liver
        disease, and cancer) develop. Magnetic Resonance Imaging (MRI) is a type of scan that
        produces detailed images of the inside of the body. MRI enables non-invasive and safe
        visualisation of age and disease-related changes in the body, often long before clinical
        symptoms are perceived. MRI-derived biological features/biomarkers can be used to understand
        the influence of environmental exposures on ageing and disease.
  
        PARTICIPANTS 2500 adult (age 18 and older) volunteers of TwinsUK, the UK's largest adult twin
        Biobank and the most clinically detailed globally, will be invited to participate. Interested
        individuals will complete screening to confirm study eligibility and their safety for MRI
        scanning. Eligible participants will complete informed consent prior to undertaking research
        MRI scans of their brain, spine, heart, abdomen and parts of their skeleton and muscles. 350
        twins with differences in their data will be invited to repeat the MRI scans about two years
        later to explore longitudinal multi-organ imaging correlates of key environmental exposures
        based on cross-sectional signals and existing literature.
  
        PROCEDURES Two 45-minute MRI scans of (1) the head and spine and (2) the abdomen to the upper
        thigh.
  
        OUTCOMES Imaging-derived measures of morphology and function of the brain, spine, abdominal
        organs and musculoskeletal tissue. These measures will be used to identify twin pair
        differences related to ageing and disease. A comprehensive repository of MRI data will be
        created using protocols harmonised with the UK biobank. This will facilitate subsequent
        linkage with concurrently acquired samples and historic exposome data in longitudinal twin
        cohort.
  observational model: Cohort
  time perspective: Prospective
  measure: BrainAGE score
  time frame: At time of scan (duration 45 mins)
  description: BrainAGE will be calculated using MRI-derived phenotypes of brain volumetric changes (Cole et al, 2017).
  measure: BodyAGE score
  time frame: At time of scan (duration 45 mins)
  description: BodyAGE will be calculated using MRI-derived phenotypes of organ and tissue changes in the heart, liver, pancreas, kidneys, spine and muscle (Linge et al, 2018).
  intervention type: Procedure
  intervention name: Magnetic Resonance Imaging
  description: A single (≤45 minutes) brain MRI will include T1w and T2w imaging to assess the morphology and structure of the brain, as well as inflammatory processes. Diffusion-weighted imaging will be used to gain information about internal brain connectivity related to brain functions. MRI, MR angiography (MRA) and fMRI pulse sequences will also be acquired to detect vascular pathologies and brain lesions. T2w morphological images of the whole spine will also be obtained.
  A single (≤45 minutes) MR imaging investigation to include cardiovascular, abdominal, and musculoskeletal regions. MRI will be performed to assess the structure and function of these body regions and organs, including functional imaging of the heart. These investigations will include T1w and T2w imaging to assess morphology and structure, mapping studies of T1, T2 and T2*, perfusion imaging and cine imaging to assess the heart dynamically.
  study pop: 
  sampling method: Non-Probability Sample
  criteria: 
  gender: All
  minimum age: 18 Years
  maximum age: N/A
  healthy volunteers: Accepts Healthy Volunteers
  last name: Claire Steves
  role: Study Chair
  affiliation: King's College London
  last name: Vicky Bowyer
  phone: +44 (0) 20 7848 4444
  email: vicky.bowyer@kcl.ac.uk
  facility: 
  contact: 
  investigator: 
  investigator: 
  investigator: 
  investigator: 
  investigator: 
  investigator: 
  investigator: 
  investigator: 
  investigator: 
  investigator: 
  investigator: 
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  investigator: 
  investigator: 
  investigator: 
  investigator: 
  country: United Kingdom
  citation: Cole JH, Poudel RPK, Tsagkrasoulis D, Caan MWA, Steves C, Spector TD, Montana G. Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker. Neuroimage. 2017 Dec;163:115-124. doi: 10.1016/j.neuroimage.2017.07.059. Epub 2017 Jul 29.
  PMID: 28765056
  citation: Linge J, Borga M, West J, Tuthill T, Miller MR, Dumitriu A, Thomas EL, Romu T, Tunon P, Bell JD, Dahlqvist Leinhard O. Body Composition Profiling in the UK Biobank Imaging Study. Obesity (Silver Spring). 2018 Nov;26(11):1785-1795. doi: 10.1002/oby.22210. Epub 2018 May 22.
  PMID: 29785727
  responsible party type: Sponsor
  sharing ipd: Yes
  ipd description: Access to the data may be requested by application to the TwinsUK Resource Executive Committee (TREC).
  ipd info type: Study Protocol
  ipd info type: Informed Consent Form (ICF)
  ipd time frame: The data will be available after the primary analyses have been reported and as determined by TREC based on the application data sharing policies. The data will remain available for the foreseeable future with no end date, at present
  ipd access criteria: See the information in the link.
  ipd url: https://twinsuk.ac.uk/resources-for-researchers/our-data.