Jesse A. Brown - US grants

DESCRIPTION (provided by applicant): Traditional diagnosis of Alzheimer Disease (AD) has depended on the postmortem identification of beta-amyloid plaques, tau neurofibrillary tangles, and neuronal loss. Recent efforts to characterize the progression of AD in the aging brain have revealed significant degradation of specific myelinated (white matter) tracts. This pattern of degradation is in close accordance with the spatial distribution of late-myelinating tracts that interconnect associative regions of the cortex. Interestingly, patterns of amyloid deposition in AD appear to follow a similar trajectory. This convergence of observations has led to the hypothesis that myelin degradation may be a primary component of AD, impairing brain connectivity and contributing to deficits in memory, language, and visuospatial processing. These effects tend to be more pronounced and develop earlier in subjects defined as at risk, based on a family history of the disease and/or carriage of the APOE e4 allele. Current treatment options aimed at slowing disease progression are highly dependent on early diagnosis and drug deployment. Hence, an extensive research program is underway to detect manifestations of AD that appear in the brains of asymptomatic at-risk individuals and to longitudinally track these changes. Central to this effort will be assessments of a) differences in white matter integrity between healthy aging subjects and at-risk subjects using diffusion-weighted MRI and b) alterations in functional connectivity in the same subjects performing an episodic memory task during functional MRI scanning. Integration of structural and functional neuroimaging modalities will allow assessment of impairments in network connectivity. This connectivity profiling should contribute to more reliable early detection of AD and emphasize the importance of myelin-protecting treatment efforts. Relevance to public health: Early detection of Alzheimer Disease is largely dependent on non-invasive neuroimaging techniques that reveal altered structure and function in the brains of subjects with higher risk for developing the disease before overt symptoms have manifested. The integration of new neuroimaging techniques for studying connectivity in the brain is beginning to reveal patterns of degradation affecting specific tissue types. Understanding the trajectory of this degradation should improve early detection of the disease and focus treatment on slowing disease progression in the vulnerable tissues.

PROJECT SUMMARY/ABSTRACT This is an application for a K01 award for Dr. Jesse Brown, a postdoctoral scholar in clinical neuroimaging at the University of California, San Francisco (UCSF) in the Memory and Aging Center (MAC). Dr. Brown is an early-career neuroscientist focusing on brain network neuroanatomy involved in neurodegenerative disease. This K01 award will provide Dr. Brown with the support necessary to accomplish the following goals: 1) gain experience in the network neuroanatomy of dementia, 2) achieve proficiency in PET data analysis with an emphasis on tau imaging, 3) become an expert in longitudinal statistical modeling, 4) expand knowledge of new MRI neuroimaging methods, and 5) develop an independent research career. To achieve these goals, Dr. Brown has assembled a mentorship team including a primary mentor, Dr. William Seeley, a behavioral neurologist who conducts neuroimaging and neuropathological studies on selective regional vulnerability in neurodegenerative disease; a co-mentor, Dr. Gil Rabinovici, a behavioral neurologist who investigates how molecular brain imaging techniques can be used to improve diagnostic accuracy in dementia; a collaborator, Dr. Howard Rosen, a behavioral neurologist who uses neuroimaging to track how neurodegenerative diseases affect the brain over time; a collaborator, Dr. John Kornak, a biostatistician who is an expert in longitudinal data analysis; and a collaborator, Dr. Christopher Hess, a neuroradiologist focused on the translational application of MR imaging techniques to brain degeneration. This proposal describes a multimodal neuroimaging approach to predict neurodegenerative disease progression in individual patients with frontotemporal dementia (FTD) and Alzheimer's disease (AD). The central hypothesis of this proposal is that each of these diseases originates in a selectively vulnerable brain region or ?epicenter? and spreads outwards along network connections, with affected regions first showing elevated tau protein binding, followed by an increased rate of gray matter loss, and eventually a high degree of cumulative atrophy. We will first develop methods to detect patient-tailored epicenters in FTD/AD patients with different clinical syndromes and use clustering methods to identify atrophy subtypes (Aim 1). We will then test a model predicting that as disease spreads from an epicenter throughout the network, nodes that become affected will show a greater longitudinal rate of atrophy before they show high cumulative atrophy (Aim 2). Finally, we will use 18F-AV1451 PET imaging to examine the relative timing of tau spread and regional atrophy spread from the epicenter. The goal of this project is to improve prognostic accuracy in individual dementia patients. This proposal includes innovative imaging and statistical methods that will help us evaluate different biomarkers of network-based neurodegenerative disease progression in a clinical trial. The K01 training will prepare Dr. Brown to build translational neuroimaging tools enabling next-generation monitoring of brain disease.