Cognitive symptoms in Parkinson's disease (PD) are often overlooked despite their frequency and the high risk they incur for the development of mild cognitive impairment (MCI) or dementia. However, considerable heterogeneity exists in the cognitive domains that are affected, suggesting that patterns of neurodegeneration may differ amongst individuals. The reasons for individual differences in cognitively-related neurodegeneration are not well understood in PD, which is essential because altered functioning in some domains (executive) is a risk factor for future cognitive decline, whereas changes in other domains (visuospatial, semantic memory) predict the development of dementia. There is an urgent need to elucidate the neurobiological mechanisms underlying cognitive heterogeneity in PD, especially before clinical symptoms manifest, since optimal therapeutic approaches will depend on early detection and individualized treatments that target specific brain networks. Changes in patterns of brain functioning that predate the development of MCI and dementia are not well understood in PD, nor is heterogeneity of neurodegeneration, which may be mediated by genetic factors that carry different prognostic significance. Cognitive heterogeneity in PD is associated with common genetic variants in an enzyme that degrades prefrontal cortex dopamine (catchol-O-methyl transferase; COMT) and the microtubule-associated protein tau (MAPT). Both genes exert strong effects on cognition in PD and are risk factors for future cognitive decline (COMT) and dementia (MAPT). Little is known about how the expression of these genes mediates patterns of abnormal intrinsic functional connectivity at rest and context-dependent connectivity during effortful mental processing. The goals of this project are to characterize disturbances in the functional connectivity of key brain networks in cognitively normal PD patients (PD-CN) and to determine their association with genes that may presage future cognitive decline or dementia. PD-CN patients and healthy volunteers will be studied using resting-state fMRI (rsfMRI), three task-activated fMRI (tafMRI), and diffusion weighted imaging (dMRI). The tafMRI protocols will characterize context-dependent disturbances in executive, visuospatial and semantic memory networks in PD-CN, which will then be correlated with abnormalities in task- positive and negative rsfMRI networks. COMT and MAPT mediation of functional changes during tafMRI and rsfMRI will also be studied, as will genetic mediation of associations between functional connectivity markers and structural changes in the brain (dMRI). In a pilot secondary aim, cognitive testing will be repeated 2 years post-baseline in a subsample of PD patients to explore if aberrant brain functioning, together with genetic factors, predict various indices of cognitive decline. This research will lead to a more cohesive understanding of individual differences in neuropathological changes that predate domain-specific cognitive impairment in PD, which is critical for clinical applications to move forward. Project outcomes will lay the foundation for longitudinal studies that characterize patterns of neurodegenerative change overtime and their association with genetic risk factors known to mediate the rate of cognitive decline.
Parkinson's disease (PD) is second only to Alzheimer's disease as a neurodegenerative disorder. There are over 80,000 Veterans with PD and the incidence is projected to increase substantially by 2020, placing even greater demands on the VA healthcare system. PD leads to cognitive deficits and most patients eventually develop dementia, which is up to five times more prevalent than in normal aging. In early stages of PD, there is considerable heterogeneity in the types of cognitive deficits, which may be related to genetic factors that carry different prognostic significance. The goals of this project are to identify neurodegenerative changes in brain networks of cognitively-normal PD patients and to determine their association with genes that may portend future cognitive decline or dementia. It is vital to identify brain imaging and genetic phenotypes related to cognitive heterogeneity, before cognitive symptoms manifest, as optimal interventions will depend on early detection and individualized treatments, which will ultimately lead to better healthcare for Veterans.
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