The overall goals and objectives of this proposal are to integrate digital histopathology and structural neuroimaging data to model patterns of spread of molecular pathology associated with frontotemporal dementia (FTD). FTD is an incurable progressive neurodegenerative disorder that is a common form of dementia in patients between the ages of 40-65. FTD clinical syndromes include the behavioral-variant (bvFTD) and primary progressive aphasia (PPA). The underlying neuropathology associated with FTD clinical syndromes is classified as frontotemporal lobar degeneration (FTLD) with either tau (FTLD-Tau) or TDP-43 (FTLD-TDP) proteinaceous intracellular incisions in brain cells, which currently can only be detected at autopsy. These disparate proteinopathies can result in clinically indistinguishable FTD clinical bvFTD and PPA syndromes during life. Cell-to-cell spread of pathogenic forms of these proteins contributes to disease pathogenesis and thus, a major obstacle for disease modifying therapies targeting this process is the ability to detect and track these specific protein aggregations antemortem. A network science approach to neuroimaging in living patients finds bvFTD and PPA patients have disease in brain regions corresponding to neurocognitive networks for social/executive and language functioning, respectively, but the patterns of disease progression of these specific proteinopathies within these neurocognitive networks is unknown. The overarching hypothesis of this proposal is that FTLD-Tau and FTLD-TDP have partially dissociable patterns of cellular pathology in microscopic networks of neurons and glia that selectively impact large-scale regional cognitive networks, and this can be used to differentiate and track these pathologies antemortem.
The aims of this study are to first perform a detailed digital histopathological study to quantify and compare the cellular and regional pattern of FTLD-Tau and FTLD-TDP pathology in the cerebrum. Next, network-science analytics will be performed to study the microscopic connectivity patterns of spread of these disparate pathologies in high-density sampling from multiple frontotemporal regions in each hemisphere. Finally, network analytics will be applied to longitudinal antemortem structural imaging to define ?signatures? of progressive FTLD-Tau and FTLD-TDP neuropathology networks in clinical bvFTD and PPA. These findings will discover histopathology-validated markers of progressive disease that inform theories of spreading pathology in humans with FTLD-tau and FTLD-TDP, and provide pathology-validated clinical and anatomical models of in vivo disease progression that will be useful for diagnosis, staging and prognosis in FTD-spectrum disorders.
Frontotemporal dementia (FTD) is a common cause of dementia in the non-elderly population caused by two disparate frontotemporal lobar degeneration (FTLD) pathologies including tauopathies (FTLD-Tau) and TDP-43 proteinopathies (FTLD-TDP) which can only be detected at autopsy. This proposal uses a novel application of network science analysis using digital histology and autopsy-confirmed imaging data to study and compare the patterns of spread of FTLD-Tau and FTLD-TDP pathology in clinical FTD. The overarching goal is to develop pathology-validated neuroimaging biomarkers to detect and track these two different pathologies in living patients to improve clinical trials aimed at tau or TDP-43 in FTD.