Global dementia diagnoses are steeply increasing. While advances in neuroimaging, neuropathology, and genetics research have improved our understanding of neurodegenerative diseases causing dementia, precise antemortem diagnosis, as well as sensitive and specific biomarkers that can facilitate a differential diagnosis and aid in participant recruitment in clinical trials, remains elusive. The current collection of studies aimed to examine methods of multivariate integration of multimodal neuroimaging measures among novel subgroups of individuals with dementia caused by neurodegenerative disease. In the modeling of local and non-local multivariate associations between neuroimaging measures, we sought to identify brain regions that could serve as biomarkers of longitudinal neurodegeneration. In Study 1, we employed a multivariate canonical correlation analysis to longitudinal MRI and 18FDG-PET data among CSF pathology-defined subgroups along the Alzheimer’s Disease clinical continuum. This work aimed to provide insight into potential non-local (i.e., spatially disjointed) relationships between atrophy and hypometabolism, and how these relationships differ as a function of time point and pathological status. Most notably, we showed that subgroups with markers of tau pathology had spatially overlapping relationships between atrophy and hypometabolism while subgroups with markers of only amyloid did not. In Study 2, we modeled the relationships between longitudinal rates of atrophy and baseline hypometabolism among individuals diagnosed with clinical behavioral variant frontotemporal dementia, most often caused by one of the neuropathologic forms of frontotemporal lobar degeneration (FTLD). We observed a robust relationship between baseline 18FDG-PET hypometabolism and the subsequent rates of cortical atrophy that was highly local and specific to select functional networks. In Study 3, we employed a novel multivariate method to extract multimodal signatures of MRI-derived cortical shape morphometric features among three clinical phenotypes of FTLD. We found that a combination of shape morphometric measures improved discriminability of FTLD clinical syndromes when tested on an independent data set. Together, this multidisciplinary study provides valuable information with regard to the longitudinal drivers of neurodegeneration across multiple pathological or clinical subtypes of neurodegenerative disease. Further, we developed and validated new multivariate markers that can be employed in future studies of longitudinal neurodegeneration. This work will contribute to a growing body of research that aims to clarify the individualized complexities of the neurodegenerative disease process as it interacts with biological etiology.

Creator

• Stocks, Jane

DOI

• https://doi.org/10.21985/n2-97mf-k441

Subject

• Clinical psychology

Language

• en

Alternate Identifier

• etdadmin_upload_993222
• http://dissertations.umi.com/northwestern:16626

Date created

• 2022-01-01

Resource type

• Dissertation

Rights statement

• In Copyright