Neuroprotective Effects of Cardiorespiratory Fitness on White Matter Integrity and Cognition Across the Adult Lifespan
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Cognitive Decline
- Sponsor
- Suffolk University
- Enrollment
- 645
- Primary Endpoint
- white matter (WM) microstructure integrity
- Status
- Completed
- Last Updated
- 7 years ago
Overview
Brief Summary
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.
Detailed Description
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.
Investigators
Ryan Mace
Clinical Psychology Doctoral Candidate
Suffolk University
Eligibility Criteria
Inclusion Criteria
- Not provided
Exclusion Criteria
- Not provided
Outcomes
Primary Outcomes
white matter (WM) microstructure integrity
Time Frame: Measured between 9:00 and 10:00 am on the single assessment day.
fractional anisotropy (FA) diffusion tensor imaging (DTI)
executive function (EF)
Time Frame: Measured between 11:00 am and 12:00 pm on the single assessment day.
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.