<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/NCT03775941</url>
  </required_header>
  <id_info>
    <org_study_id>NKI-RS</org_study_id>
    <secondary_id>R01MH094639-01</secondary_id>
    <nct_id>NCT03775941</nct_id>
  </id_info>
  <brief_title>Fitness on White Matter and Cognition in Aging</brief_title>
  <official_title>Neuroprotective Effects of Cardiorespiratory Fitness on White Matter Integrity and Cognition Across the Adult Lifespan</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Suffolk University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Suffolk University</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>
      Cardiorespiratory fitness (CRF) is associated with decreased risk for mild cognitive&#xD;
      impairment (MCI) and dementia. CRF is linked with more conserved gray and white matter (WM)&#xD;
      volume, improved WM microstructural integrity, and better cognitive performance among healthy&#xD;
      older adults. Additional research is needed to determine: (1) which WM tracts are most&#xD;
      strongly related to CRF, (2) whether CRF-related benefits on WM translate to enhanced&#xD;
      cognitive functioning, and (3) factors that mediate and moderate CRF effects. Higher CRF was&#xD;
      hypothesized to be associated with stronger WM integrity, both globally and locally in WM&#xD;
      tracts that connect frontal brain regions. The neuroprotective effects were hypothesized to&#xD;
      be age-dependent, such that the association between CRF and WM integrity would be stronger in&#xD;
      old age compared to younger age. Finally, higher CRF was hypothesized to predict stronger&#xD;
      performance on tests of executive functioning (EF), partially mediated by frontal WM&#xD;
      integrity. Delineation of specific neurocognitive effects of CRF may serve clinicians in&#xD;
      individually tailoring wellness interventions to meet patients' specific cognitive concerns&#xD;
      with aging.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Sample: Participant data from the &quot;Cross-Sectional Lifespan Connectomics Study&quot; of the Nathan&#xD;
      Kline Institute - Rockland Sample (NKI-RS) will be analyzed for the present study. Zip&#xD;
      code-based recruitment and monitoring enrollment for key demographic variables (e.g., age,&#xD;
      sex, ethnicity) were used to maintain adequate representation of Rockland County and prevent&#xD;
      sampling biases (e.g., cohort effects). NKI-RS eligibility was designed for inclusivity.&#xD;
&#xD;
      Procedure: All participants completed a medical evaluation, psychiatric interview,&#xD;
      self-report questionnaires, standardized battery of cognitive tests, and neuroimaging at NKI.&#xD;
      Complete details about the MRI measurement parameters can be located on the NKI-RS website&#xD;
      for DTI and MPRAGE and protocols. Quality assurance of raw data, inclusive of monitoring&#xD;
      standard operating procedures, error-handling, and compiling the data dictionary, is&#xD;
      maintained by NKI-RS. Raw neuroimaging data was acquired by NKI-RS and processed at Suffolk&#xD;
      University using TRACULA and FreeSurfer 5.3.&#xD;
&#xD;
      Statistical Plan: Analyses will be performed on de-identified phenotypic and neuroimaging&#xD;
      data from adult NKI-RS participants available at the start of this study (October 2016).&#xD;
      Analyses will evaluate the potential for CRF to modulate decline in WM integrity and EF&#xD;
      observed with aging. Mixed-effects modeling will investigate the extent to which CRF predicts&#xD;
      WM integrity, as both a global measurement of fractional anisotropy (FA) and FA within nine&#xD;
      major WM tracts. Structural equation modeling will examine whether higher FA within frontal&#xD;
      WM tracts partially mediates a positive relationship between CRF and EF. The role of age and&#xD;
      clinical characteristics (e.g., cardiovascular risk factors, depression) will also be&#xD;
      explored as covariates in the link between CRF, WM, and EF.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">March 2012</start_date>
  <completion_date>July 2016</completion_date>
  <primary_completion_date type="Actual">July 2016</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Ecologic or Community</observational_model>
    <time_perspective>Cross-Sectional</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>white matter (WM) microstructure integrity</measure>
    <time_frame>Measured between 9:00 and 10:00 am on the single assessment day.</time_frame>
    <description>fractional anisotropy (FA) diffusion tensor imaging (DTI)</description>
  </primary_outcome>
  <primary_outcome>
    <measure>executive function (EF)</measure>
    <time_frame>Measured between 12:30 and 2:30 pm on the single assessment day.</time_frame>
    <description>Delis-Kaplan Executive Function System (D-KEFS) subtests will include the Trail Making Test, Design Fluency Test, Color-Word Interference Test, and Tower Tests. Scores from each subtest will be transformed into z-scores to yield the same units of measurement. Then, structural equation modeling (SEM) will aggregate these values quantify a construct of overall EF.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>executive function (EF)</measure>
    <time_frame>Measured between 11:00 am and 12:00 pm on the single assessment day.</time_frame>
    <description>Penn Computerized Neurocognitive Battery (CNB) subtests will include the CNB Letter N-back Test and Conditional Exclusion Test. Scores from each subtest will be transformed into z-scores to yield the same units of measurement. Then, structural equation modeling (SEM) will aggregate these values quantify a construct of overall EF.</description>
  </primary_outcome>
  <number_of_groups>1</number_of_groups>
  <enrollment type="Actual">645</enrollment>
  <condition>Cognitive Decline</condition>
  <condition>Executive Dysfunction</condition>
  <condition>Cardiovascular Risk Factor</condition>
  <arm_group>
    <arm_group_label>Cross-Sectional Lifespan Connectomics Study</arm_group_label>
  </arm_group>
  <eligibility>
    <study_pop>
      <textblock>
        Participants are community-dwelling adults from the &quot;Cross-Sectional Lifespan Connectomics&#xD;
        Study&quot; of the Nathan Kline Institute - Rockland Sample (NKI-RS)-a large cross-sectional&#xD;
        sample of adult brain development. NKI prospectively recruited community-dwelling residents&#xD;
        of Rockland County, New York-a region that is socioeconomically comparable to United States&#xD;
        demographics.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        NKI-RS eligibility criteria was designed for inclusivity. Nearly half of recruited&#xD;
        individuals met criteria for at least one Diagnostic Statistical Manual - 4th Edition&#xD;
        diagnosis based on a semi-structured clinical interview.&#xD;
&#xD;
        Inclusion Criteria (present study):&#xD;
&#xD;
          -  diffusion tensor imaging (DTI) without significant artifacts&#xD;
&#xD;
          -  T1-weighted structural imaging (Magnetization-Prepared Rapid Gradient-Echo; MPRAGE)&#xD;
             without significant artifacts&#xD;
&#xD;
          -  CRF data from a standardized cycle ergometer test (commonly used for predicting&#xD;
             maximal oxygen uptake; VO2 max).&#xD;
&#xD;
        Exclusion Criteria (per NKI-RS protocol):&#xD;
&#xD;
          -  severe psychiatric illness (bipolar disorder, schizophrenia disorder, schizoaffective&#xD;
             disorder)&#xD;
&#xD;
          -  severe developmental disorders (autism spectrum disorders, intellectual disabilities)&#xD;
&#xD;
          -  current suicidal or homicidal ideation&#xD;
&#xD;
          -  severe cerebral trauma (stroke, moderate to severe traumatic brain injury, ischemic&#xD;
             attack in the past two years)&#xD;
&#xD;
          -  severe neurodegenerative disorders (Parkinson's disease, Huntington's Disease,&#xD;
             dementia)&#xD;
&#xD;
          -  a history of substance dependence in the past two years (with an exception for&#xD;
             cannabis)&#xD;
&#xD;
          -  a lifetime history of psychiatric hospitalization&#xD;
&#xD;
          -  current pregnancy&#xD;
&#xD;
          -  MRI contraindications&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>20 Years</minimum_age>
    <maximum_age>85 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <link>
    <url>https://www.census.gov/quickfacts/</url>
    <description>US Census Bureau. (2010). U.S. Census Bureau State &amp; County Quickfacts.</description>
  </link>
  <link>
    <url>http://fcon_1000.projects.nitrc.org/indi/pro/eNKI_RS_TRT/DIff_137.pdf</url>
    <description>NKI-RS DTI protocol</description>
  </link>
  <link>
    <url>http://fcon_1000.projects.nitrc.org/indi/enhanced/NKI_MPRAGE.pdf</url>
    <description>NKI-RS MPRAGE protocol</description>
  </link>
  <link>
    <url>http://fcon_1000.projects.nitrc.org/indi/enhanced/access.html</url>
    <description>NKI-RS data usage agreement</description>
  </link>
  <reference>
    <citation>Nooner KB, Colcombe SJ, Tobe RH, Mennes M, Benedict MM, Moreno AL, Panek LJ, Brown S, Zavitz ST, Li Q, Sikka S, Gutman D, Bangaru S, Schlachter RT, Kamiel SM, Anwar AR, Hinz CM, Kaplan MS, Rachlin AB, Adelsberg S, Cheung B, Khanuja R, Yan C, Craddock CC, Calhoun V, Courtney W, King M, Wood D, Cox CL, Kelly AM, Di Martino A, Petkova E, Reiss PT, Duan N, Thomsen D, Biswal B, Coffey B, Hoptman MJ, Javitt DC, Pomara N, Sidtis JJ, Koplewicz HS, Castellanos FX, Leventhal BL, Milham MP. The NKI-Rockland Sample: A Model for Accelerating the Pace of Discovery Science in Psychiatry. Front Neurosci. 2012 Oct 16;6:152. doi: 10.3389/fnins.2012.00152. eCollection 2012.</citation>
    <PMID>23087608</PMID>
  </reference>
  <verification_date>December 2018</verification_date>
  <study_first_submitted>November 29, 2018</study_first_submitted>
  <study_first_submitted_qc>December 11, 2018</study_first_submitted_qc>
  <study_first_posted type="Actual">December 14, 2018</study_first_posted>
  <last_update_submitted>December 16, 2018</last_update_submitted>
  <last_update_submitted_qc>December 16, 2018</last_update_submitted_qc>
  <last_update_posted type="Actual">December 19, 2018</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Suffolk University</investigator_affiliation>
    <investigator_full_name>Ryan Mace</investigator_full_name>
    <investigator_title>Clinical Psychology Doctoral Candidate</investigator_title>
  </responsible_party>
  <keyword>Neuroimaging</keyword>
  <keyword>White matter</keyword>
  <keyword>Cardiorespiratory fitness</keyword>
  <keyword>Physical activity</keyword>
  <keyword>Cognitive aging</keyword>
  <keyword>Executive function</keyword>
  <keyword>Cognitive reserve</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Cognitive Dysfunction</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>Yes</sharing_ipd>
    <ipd_description>The Nathan Kline Institute - Rockland Sample is a public, open-access data repository that is available upon approval of the NKI data usage agreement.&#xD;
R code for all study analyses will be made available for reproducibility with open-access NKI-RS data.</ipd_description>
    <ipd_info_type>Study Protocol</ipd_info_type>
    <ipd_info_type>Statistical Analysis Plan (SAP)</ipd_info_type>
    <ipd_info_type>Analytic Code</ipd_info_type>
  </patient_data>
  <!-- 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/NCT03775941
org study id: NKI-RS
secondary id: R01MH094639-01
nct id: NCT03775941
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
Cardiorespiratory fitness (CRF) is associated with decreased risk for mild cognitive
      impairment (MCI) and dementia. CRF is linked with more conserved gray and white matter (WM)
      volume, improved WM microstructural integrity, and better cognitive performance among healthy
      older adults. Additional research is needed to determine: (1) which WM tracts are most
      strongly related to CRF, (2) whether CRF-related benefits on WM translate to enhanced
      cognitive functioning, and (3) factors that mediate and moderate CRF effects. Higher CRF was
      hypothesized to be associated with stronger WM integrity, both globally and locally in WM
      tracts that connect frontal brain regions. The neuroprotective effects were hypothesized to
      be age-dependent, such that the association between CRF and WM integrity would be stronger in
      old age compared to younger age. Finally, higher CRF was hypothesized to predict stronger
      performance on tests of executive functioning (EF), partially mediated by frontal WM
      integrity. Delineation of specific neurocognitive effects of CRF may serve clinicians in
      individually tailoring wellness interventions to meet patients' specific cognitive concerns
      with aging.
Sample: Participant data from the "Cross-Sectional Lifespan Connectomics Study" of the Nathan
      Kline Institute - Rockland Sample (NKI-RS) will be analyzed for the present study. Zip
      code-based recruitment and monitoring enrollment for key demographic variables (e.g., age,
      sex, ethnicity) were used to maintain adequate representation of Rockland County and prevent
      sampling biases (e.g., cohort effects). NKI-RS eligibility was designed for inclusivity.

      Procedure: All participants completed a medical evaluation, psychiatric interview,
      self-report questionnaires, standardized battery of cognitive tests, and neuroimaging at NKI.
      Complete details about the MRI measurement parameters can be located on the NKI-RS website
      for DTI and MPRAGE and protocols. Quality assurance of raw data, inclusive of monitoring
      standard operating procedures, error-handling, and compiling the data dictionary, is
      maintained by NKI-RS. Raw neuroimaging data was acquired by NKI-RS and processed at Suffolk
      University using TRACULA and FreeSurfer 5.3.

      Statistical Plan: Analyses will be performed on de-identified phenotypic and neuroimaging
      data from adult NKI-RS participants available at the start of this study (October 2016).
      Analyses will evaluate the potential for CRF to modulate decline in WM integrity and EF
      observed with aging. Mixed-effects modeling will investigate the extent to which CRF predicts
      WM integrity, as both a global measurement of fractional anisotropy (FA) and FA within nine
      major WM tracts. Structural equation modeling will examine whether higher FA within frontal
      WM tracts partially mediates a positive relationship between CRF and EF. The role of age and
      clinical characteristics (e.g., cardiovascular risk factors, depression) will also be
      explored as covariates in the link between CRF, WM, and EF.
observational model: Ecologic or Community
time perspective: Cross-Sectional
measure: white matter (WM) microstructure integrity
time frame: Measured between 9:00 and 10:00 am on the single assessment day.
description: fractional anisotropy (FA) diffusion tensor imaging (DTI)
measure: executive function (EF)
time frame: Measured between 12:30 and 2:30 pm on the single assessment day.
description: Delis-Kaplan Executive Function System (D-KEFS) subtests will include the Trail Making Test, Design Fluency Test, Color-Word Interference Test, and Tower Tests. Scores from each subtest will be transformed into z-scores to yield the same units of measurement. Then, structural equation modeling (SEM) will aggregate these values quantify a construct of overall EF.
measure: executive function (EF)
time frame: Measured between 11:00 am and 12:00 pm on the single assessment day.
description: Penn Computerized Neurocognitive Battery (CNB) subtests will include the CNB Letter N-back Test and Conditional Exclusion Test. Scores from each subtest will be transformed into z-scores to yield the same units of measurement. Then, structural equation modeling (SEM) will aggregate these values quantify a construct of overall EF.
arm group label: Cross-Sectional Lifespan Connectomics Study
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 20 Years
maximum age: 85 Years
healthy volunteers: Accepts Healthy Volunteers
url: https://www.census.gov/quickfacts/
description: US Census Bureau. (2010). U.S. Census Bureau State & County Quickfacts.
url: http://fcon_1000.projects.nitrc.org/indi/pro/eNKI_RS_TRT/DIff_137.pdf
description: NKI-RS DTI protocol
url: http://fcon_1000.projects.nitrc.org/indi/enhanced/NKI_MPRAGE.pdf
description: NKI-RS MPRAGE protocol
url: http://fcon_1000.projects.nitrc.org/indi/enhanced/access.html
description: NKI-RS data usage agreement
citation: Nooner KB, Colcombe SJ, Tobe RH, Mennes M, Benedict MM, Moreno AL, Panek LJ, Brown S, Zavitz ST, Li Q, Sikka S, Gutman D, Bangaru S, Schlachter RT, Kamiel SM, Anwar AR, Hinz CM, Kaplan MS, Rachlin AB, Adelsberg S, Cheung B, Khanuja R, Yan C, Craddock CC, Calhoun V, Courtney W, King M, Wood D, Cox CL, Kelly AM, Di Martino A, Petkova E, Reiss PT, Duan N, Thomsen D, Biswal B, Coffey B, Hoptman MJ, Javitt DC, Pomara N, Sidtis JJ, Koplewicz HS, Castellanos FX, Leventhal BL, Milham MP. The NKI-Rockland Sample: A Model for Accelerating the Pace of Discovery Science in Psychiatry. Front Neurosci. 2012 Oct 16;6:152. doi: 10.3389/fnins.2012.00152. eCollection 2012.
PMID: 23087608
responsible party type: Principal Investigator
investigator affiliation: Suffolk University
investigator full name: Ryan Mace
investigator title: Clinical Psychology Doctoral Candidate
mesh term: Cognitive Dysfunction
sharing ipd: Yes
ipd description: The Nathan Kline Institute - Rockland Sample is a public, open-access data repository that is available upon approval of the NKI data usage agreement.
R code for all study analyses will be made available for reproducibility with open-access NKI-RS data.
ipd info type: Study Protocol
ipd info type: Statistical Analysis Plan (SAP)
ipd info type: Analytic Code