Min, Yuhao

AbstractBackgroundInter‐cellular communication within the gliovascular unit (GVU) is critical for cerebral blood flow regulation, and maintenance of the blood‐brain‐barrier (BBB) properties. The breakdown of BBB in Alzheimer’s disease (AD) is well‐established, but precise underlying molecular changes remain unclear. Additionally, whether GVU molecular alterations observed in AD brains are also detected in blood from living patients is unknown. Further, these GVU molecular perturbations require further investigation in different model systems to identify both human brain‐specific and cross‐species conserved alterations. In this study, we investigated prioritized GVU molecules altered in AD brains for their conservation in blood and cross‐species model systems.MethodsWe performed single nucleus RNA sequencing (snRNAseq) of temporal cortex tissue in AD and control brains. We analyzed this data to detect cell‐specific GVU molecular perturbations and their interactions. We investigated molecular interactions between vascular and astrocyte clusters, the major cell types of the GVU of the BBB. To determine whether GVU transcriptional alterations detected in the brain are preserved in the blood, existing blood expression, genetic, and neuroimaging data from two longitudinal antemortem cohorts were analyzed. Using model systems, including mouse, drosophila, and zebrafish, we evaluated the cross‐species conservation of the top GVU alterations detected in AD brains.ResultsBrain snRNAseq revealed transcriptional profiles of 6,541 astrocytes and 2,210 vascular cells. The latter formed three distinct vascular clusters characterized as pericytes, endothelia and perivascular fibroblasts. We identified differentially expressed genes and their enriched pathways within these clusters and observed the highest levels of transcriptional changes within pericytes. Vascular targets that interact with astrocytic ligands have biological functions in cell signaling, angiogenesis, amyloid ß metabolism, and cytoskeletal architecture. We discovered that genetic variants influencing blood expression levels of some of the prioritized GVU genes were associated with neuroimaging burden of cerebrovascular disease in living human cohorts. Our ongoing studies in model systems revealed conservation of some of the top prioritized molecular perturbations across species.ConclusionOur findings prioritized by multiscale, cross‐tissue human data revealed GVU perturbations within interacting pericyte and astrocyte molecules, which are conserved across multiple cross‐species models. These results nominate new molecular targets and mechanistic insights for BBB disruptions in AD.

AbstractBackgroundNeurodegenerative disorders affect different brain regions at different time points and to varying degrees, although the underlying reasons for this variability in regional susceptibility is unknown. Brain regions have different proportions of cell types. This cell proportion variability may be further influenced by presence and degree of brain disorders, including neurodegenerative diseases. We postulate that genetic and other factors that influence brain cell type proportions may also provide insights into brain regional susceptibility to neurodegenerative diseases.MethodsUtilizing bulk transcriptomics data from 7 brain regions obtained from 3 cohorts and corresponding whole genome sequencing (WGS) data, genetic variants were evaluated for association with cell type proportions across brain regions. Utilizing cell type specific marker genes for deconvolution provided by McKenzie et.al, we estimated surrogate variables for proportion (SVP) of various cell types using BRETIGEA. We then evaluated relationship between SVP and AD as well as Age, Sex, APOE ε4 and neuropathology measures. Genetic variants from WGS were then tested for association with SVP to identify distinct and conserved patterns across 6 cell types and 7 brain regions.ResultsAnalysis of SVP by diagnosis, sex, age, APOE ε4 and neuropathology measures identified significant differences in cell proportions in various cell types and brain regions. GWAS of SVP identified 134 loci that reached genome‐wide significance (5e‐8). After conservative adjustment for multiple testing (6 cell types and 7 brain regions; 42 tests), variants proximal to SYNPR and VENTXP7 remained significant (p‐value<1.19E‐09). Variants proximal to SYNPR were associated with increased proportion of oligodendrocytes in cerebellum whereas variants near VENTXP7 were associated with reduced proportion of astrocytes in DLPFC. Variants in SYNPR have previously been associated with neurofibrillary tangles and diffuse plaque measurements while variants in VENTXP7 have been associated with measurement of neurofibrillary tangles, cognitive decline, unipolar depression, and bipolar disorder.ConclusionsIt is likely that there are genetic variants associated with cell proportion in brain, may vary by cell type and brain region, while others may act more broadly. Identification of genetic variants associated with cell proportions in different brain regions may provide insights into affected cells and regional vulnerabilities.

AbstractBackgroundContext‐specific networks can capture functionally important genes that may not be differentially expressed. Leveraging seven different gene expression datasets of Alzheimer’s disease (AD) and healthy control brains, we constructed a novel pipeline that includes such network analysis, augmented by in vivo validations and in silico drug repurposing to facilitate prioritization of AD therapeutic targets.MethodWe utilized publicly available gene expression data from 733 AD and 454 control brains across 7 datasets and the NetDecoder (PMID: 26975659) network biology platform to build context‐specific networks. Based on the known protein‐protein interaction and gene expression correlations, information flow from the top differentially expressed genes (DEG) to transcriptional regulator genes was calculated using a process‐guided flow algorithm. Genes with the greatest informational flow changes across AD cohorts were systematically prioritized. We next validated these genes in a medium‐throughput screen of a tau‐transgenic Drosophila model (PMID: 11408621). Further, we identified existing small‐molecule drugs to target the candidate genes utilizing curated databases.ResultsA total of 14 context‐specific networks were constructed across 7 datasets. We found AD‐related genes, such as APP, to have high flow differences between AD and control networks and high connectivity. Notably, many such genes were not DEGs between AD and control, suggesting that the information flow captures novel aspects of AD pathophysiology. We nominated 224 unique genes with the greatest flow differences for functional validation. We screened 111 of the 224 candidate genes with readily available, high‐confidence orthologs in Drosophila. We identified genes that suppress (N = 68) or enhance (N = 27) tau‐related neurodegeneration in this model. We confirmed the effects of previously nominated genes, such as HDAC1, which enhances tau‐neurodegeneration if overexpressed and suppresses it if knocked down. We also identified and validated additional therapeutic targets. Lastly, we applied a network‐proximity‐based algorithm and identified small molecule drugs for the candidate genes.ConclusionWe present a novel pipeline that integrates analytic approaches, experimental validation, and drug repurposing to facilitate therapeutic discovery in AD. We applied this pipeline and nominated previously known and novel genes implicated in AD pathogenesis. Our pipeline demonstrates a cross‐species, systems‐level approach to therapeutic nomination in AD and related neurodegenerative diseases.

AbstractBackgroundProgressive supranuclear palsy (PSP) is a neurodegenerative disorder characterized by cell‐type‐specific tau lesions in neurons and glia. Using bulk brain RNAseq, we previously identified PSP‐associated genes and co‐expression networks that are enriched with cell‐type marker genes. We extended our work to identify cell‐type‐specific expression perturbations in PSP using a systems approach and in vivo validations in a model system.MethodSingle‐nucleus RNAseq (snRNAseq) was performed using 33 frozen brain temporal cortex (TCX) samples from PSP and control brains. After quality control (QC), integration, and clustering of nuclei, each cluster was annotated for its cell type. We identified differentially expressed genes (DEG) in PSP and further investigated them using an independent bulk RNAseq dataset comprising 408 PSP and control TCX samples for replication and assessing co‐expression patterns. Top DEGs were identified and then validated using external bulk RNAseq datasets from a tau transgenic mouse model. Further, the ability of the validated DEGs to rescue tau‐mediated cellular toxicity was evaluated in a tau transgenic Drosophila model.ResultAfter QC, 30 clusters comprised of 27,284 nuclei were obtained, encompassing two neuronal and six glial cell types. DEGs of each cluster revealed cell‐type‐specific PSP associations. Notably, many of the up‐regulated DEGs in the astroglial clusters were members of the bulk RNAseq co‐expression modules that were also up‐regulated in PSP and enriched with astrocytic markers. There were also consistent findings for the up‐regulated DEGs in the endothelial and microglial clusters, and for down‐regulated DEGs in the oligodendroglial clusters. Subsequently, we prioritized 240 DEGs with congruent cell‐type‐specific perturbations in snRNAseq and bulk RNAseq and validated 29 of those using transgenic mouse model data. Lastly, a significant number of the up‐regulated glial genes, when knocked down in a tau transgenic Drosophila model, led to reduced tau‐mediated cellular toxicity, suggesting novel potential therapeutic avenues.ConclusionPSP brains demonstrated robust cell‐type‐specific gene expression perturbations in the glial cells populations that were validated across different datasets. Importantly, inhibiting the up‐regulated expression perturbations rescued tau‐mediated toxicity in a Drosophila model. Our findings highlight the cell‐type‐specific transcriptome changes in PSP and provide potential therapeutic options for primary tauopathies.

AbstractBackgroundInter‐cellular communication within the gliovascular unit (GVU) is critical for cerebral blood flow regulation, maintenance of the blood‐brain‐barrier (BBB) properties, and brain energy metabolism. Although numerous cell biology studies demonstrate the role of the GVU for BBB breakdown in Alzheimer’s disease (AD), the precise molecular changes contributing to its pathophysiology are unclear.MethodWe performed single nucleus RNA sequencing (snRNAseq) of temporal cortex tissue in 24 AD and control brains to understand the transcriptional changes in the cells of GVU. We acquired the snRNAseq profile of 79,751 total brain cells that comprise 6,541 astrocytes and 2,210 vascular cells. The latter formed three distinct vascular clusters characterized as activated pericytes, endothelia and resting pericytes. We identified differentially expressed genes (DEGs) and their enriched pathways in these clusters and detected the most transcriptional changes within activated pericytes. Using our data and a knowledge‐based predictive algorithm, we discovered and prioritized molecular interactions between vascular and astrocyte clusters, the main cell types of the GVU of the BBB.ResultsVascular targets predicted to interact with astrocytic ligands have biological functions in signalling, angiogenesis, amyloid ß metabolism and cytoskeletal structure. Top astrocytic and vascular interacting molecules include both novel and known AD risk genes such as APOE, APP and ECE1. We validated gene expression changes using qPCR. We are in the process of evaluating these gene expression changes in antemortem blood from AD and control participants.ConclusionOur findings provide valuable information into the transcriptional changes in predicted vascular‐astrocytic partners at the GVU, highlighting insights into the molecular mechanisms of BBB breakdown in AD.

AbstractMicroglia have fundamental roles in health and disease; however, effects of age, sex, and genetic factors on human microglia have not been fully explored. We applied bulk and single‐cell approaches to comprehensively characterize human microglia transcriptomes and their associations with age, sex, and APOE. We identified a novel microglial signature, characterized its expression in bulk tissue and single‐cell microglia transcriptomes. We discovered microglial co‐expression network modules associated with age, sex, and APOE‐ε4 that are enriched for lipid and carbohydrate metabolism genes. Integrated analyses of modules with single‐cell transcriptomes revealed significant overlap between age‐associated module genes and both pro‐inflammatory and disease‐associated microglial clusters. These modules and clusters harbor known neurodegenerative disease genes including APOE, PLCG2, and BIN1. Meta‐analyses with published bulk and single‐cell microglial datasets further supported our findings. Thus, these data represent a well‐characterized human microglial transcriptome resource and highlight age, sex, and APOE‐related microglial immunometabolism perturbations with potential relevance in neurodegeneration.

Abstract Microglia have fundamental roles in health and disease, however effects of age, sex and genetic factors on human microglia have not been fully explored. We applied bulk and single cell approaches to comprehensively characterize human microglia transcriptomes and their associations with age, sex and APOE . We identified a novel microglial signature, characterized its expression in bulk data from 1,306 brain samples across 6 regions and in single cell microglia transcriptome. We discovered microglial co-expression network modules associated with age, sex and APOE -ε4 that are enriched for lipid and carbohydrate metabolism genes. Integrated analyses of modules with single cell transcriptomes revealed significant overlap between age-associated module genes and both pro-inflammatory and disease-associated microglial clusters. These modules and clusters harbor known neurodegenerative disease genes including APOE, PLCG2 and BIN1 . These data represent a well-characterized human microglial transcriptome resource; and highlight age, sex and APOE -related microglial immunometabolism perturbations with potential relevance in neurodegeneration.