Myeloid cells of the innate immune system have been strongly implicated in the pathogenesis of neurodegenerative diseases, including Alzheimer’s disease (AD) and Parkinson’s disease (PD). Similarly, several lines of evidence call on the adaptive immune system as a critical driver of disease, particularly in PD. The immune dynamics in both of these diseases are complex, and span across not only the innate and adaptive immune systems, but also across the periphery local action in the central nervous system (CNS). This thesis aims to address critical gaps in our knowledge regarding molecular and functional alterations of immune cells in AD and PD. We apply tools including single nucleus RNA – and ATAC – sequencing as well as protein – level and functional studies to advance our understanding of molecular pathways involved in the innate and adaptive immune dysfunction in these diseases, including both immune cells in the CNS as well as in the periphery. Chapter 1 provides an overview of the evidence implicating myeloid cell dysfunction in AD and PD, including microglia as well as peripheral myeloid cells such as monocytes. It also describes the features of immune dysregulation in both diseases, and evidence implicating the adaptive immune system in PD. Chapter 2 aims to address our currently limited understanding of microglial molecular phenotypes and diversity in PD, by characterizing microglial transcriptomic and chromatin signatures in disease. We demonstrate microglial subpopulation-specific effects, including the focal depletion of a microglial population in the substantia nigra in PD, which open novel avenues for targeted neuroimmune interventions in PD. Chapter 3 aims to identify interactions regulating the infiltration and retention of peripheral immune cells into the CNS in PD; a process which is implicated in the progression of this disease, but the mechanisms of which are not fully understood. We characterized transcriptomic signatures of infiltrating lymphocytes and blood brain barrier cells, and found increased T cell infiltration in PD as well as fibroblast and endothelial populations associated with disease. We further identified transcriptional shifts suggestive of a proinflammatory and profibrotic milieu in disease, in which chemokines and extracellular matrix elements produced by fibroblasts may influence T cell trafficking and retention in the substantia nigra in PD. Chapter 4 aims to address the gap in our knowledge of how myeloid dysfunction in the periphery contributes to AD. While genetics implicate all myeloid cells in AD and PD, contributions of peripheral myeloid cells, such as monocytes, have been largely overlooked in place of microglia, which are resident in the CNS. We evaluate the convergence of the AD genetic risk loci on functional outcomes in monocytes, in the context of Aβ as an immune stimulus. We identified functional convergence of the CD33 and SPI1 AD risk variants in the context of Aβ stress, including reduced phagocytosis and loss of surface TREM2 expression, demonstrating an interaction between genetics and environment to reduce myeloid cell fitness. Finally, Chapter 5 concludes with a summary of key findings from this work, and discusses future directions for modulating innate and adaptive immune populations, both in the CNS and in the periphery, as therapeutic approaches for these neurodegenerative diseases.

No description available.

Human microglia play a pivotal role in neurological diseases, but few targeted therapies that directly modulate microglial state or function exist due to an incomplete understanding of microglial heterogeneity. This thesis aims to advance our understanding of microglial heterogeneity by using single-cell RNA sequencing to profile live human microglia from autopsies or surgical resections across diverse neurological diseases and using computational tools to infer chemical and genetic regulators of specific microglial substates. Chapter 1 provides an overview of microglial ontogeny, function, and known heterogeneity, especially in disease contexts. It also describes the steadily increasing disease burden seen in neurological disease as well as the lack of efficacious treatments and future directions for microglia-targeted therapies. Chapter 2 focuses on microglial heterogeneity in an understudied disease, ALS, describing population structure shifts seen in ALS across cortex and spinal cord. Chapter 3 instead focuses on exploring underlying cross-disease microglial population structure, identifying subsets with metabolic and functional properties, as well as subsets enriched in susceptibility genes for neurodegenerative disease. We then demonstrate applications of this type of data by using our resource to annotate other datasets. Chapter 4 leverages this data in another way, by identifying and validating candidates for chemically and genetically inducing subtype-specific states in vitro. Notably, we show that Camptothecin downregulates the transcriptional signature of disease-enriched subsets and upregulates a signature previously shown to be depleted in Alzheimer’s. Finally, I review our findings and discuss future directions for the field.

Microglia are the brain’s immunocompetent macrophages with a unique feature that allows surveillance of the surrounding microenvironment and subsequent reactions to tissue damage, infection, or homeostatic perturbations. Thereby, microglia’s striking morphological plasticity is one of their prominent characteristics and the categorization of microglial cell function based on morphology is well established. Frequently, automated classification of microglial morphological phenotypes is performed by using quantitative parameters. As this process is typically limited to a few and especially manually chosen criteria, a relevant selection bias may compromise the resulting classifications. In our study, we describe a novel microglial classification method by morphological evaluation using a convolutional neuronal network on the basis of manually selected cells in addition to classical morphological parameters. We focused on four microglial morphologies, ramified, rod-like, activated and amoeboid microglia within the murine hippocampus and cortex. The developed method for the classification was confirmed in a mouse model of ischemic stroke which is already known to result in microglial activation within affected brain regions. In conclusion, our classification of microglial morphological phenotypes using machine learning can serve as a time-saving and objective method for post-mortem characterization of microglial changes in healthy and disease mouse models, and might also represent a useful tool for human brain autopsy samples.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.