Characterizing the landscape of cell-type specific changes associated with Alzheimer's disease before death with single-cell genomics

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Project Summary Alzheimer’s disease (AD) remains the only illness in the top 10 causes of death with no disease-modifying treatments available. In large part, the dearth of adequate therapies is due to our incomplete understanding of how specific molecular pathways in the brain result in cognitive decline and memory loss. Recent genetic studies implicate multiple neuroimmune populations in the brain as central players in the pathogenesis of AD, yet the precise molecular roles of these cell types remain largely unclear. Advances in single-cell technology have opened up the ability to robustly assay cell states within complex tissues, including the human brain. The ability to measure the precise cellular states in the living brain is key to understanding subtle neuroimmune cell type transcriptional changes that may give rise to AD. To identify molecular changes in these cells in human AD brain tissue, we have deployed single-nuclei RNA-sequencing (snRNA-seq) to profile frontal cortex biopsies from patients with suspected idiopathic normal pressure hydrocephalus (iNPH) and co-morbid AD. These biopsies represent a unique opportunity to measure transcriptional changes associated with AD unconfounded by postmortem artifact and, potentially, prior to the end stage of disease. To date, I have successfully obtained 815,843 single-nuclei profiles from 18 individuals, six of whom have both amyloid and tau pathology, seven with amyloid plaques, and five with no pathology. Here, I propose to employ snRNA-seq and Slide-seq on a total of 62 frontal cortex biopsies, across a range of APOE and amyloid/tau statuses, to uncover molecular alterations specifically associated with AD. Initially, I will determine which cell populations are significantly enriched or depleted in AD pathology and associated with APOE status, identify transcriptional alterations in all cell types, and determine which populations are enriched for heritable risk of AD. With Slide- seq, I will determine how cellular states and transcriptional changes are influenced by the spatial location in relation to amyloid and tau pathology. Finally, using novel computational integration methods, I will benchmark the transcriptional changes seen in a mouse model of AD with those obtained from my human profiling efforts, providing the field a resource of cellular state changes that are recapitulated in this model. If successful, these experiments will provide a comprehensive view of AD before death, nominating new cell state changes and transcriptional pathways associated with the pathogenesis of AD.