Welcome to the AD/PD™ 2021 Interactive Program
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- Live Session | 
- On Demand Session | 
- On Demand with Live Q&A
The viewing of sessions, cannot be accessed from this conference calendar. All sessions are accessible via the Main Lobby.
FOLLOWING THE LIVE DISCUSSION, THE RECORDING WILL BE AVAILABLE IN THE ON-DEMAND SECTION OF THE AUDITORIUM.
SYSTEMIC IMMUNE CHECKPOINT BLOCKADE INDUCES APOLIPOPROTEIN E EXPRESSION AT THE CHOROID PLEXUS IN A MOUSE MODEL OF ALZHEIMER’S DISEASE
Abstract
Aims
Apolipoprotein E (APOE) is the major lipid carrier in the brain, and the choroid plexus (CP) is one of its main sources. Lipidated APOE is known to participate in Aβ clearance. We previously found that activating peripheral immunity by targeting the inhibitory immune checkpoint PD-1/PD-L1 elicits an IFNγ-dependent response at the CP, leading to cognitive improvement and reduction in disease pathology in mouse models of Alzheimer’s disease (AD) and tauopathy. Here, we found that systemic PD-L1 blockade in 5xFAD mice induces pathways in the CP associated with Aβ clearance.
Methods
Symptomatic 5xFAD mice received a single intraperitoneal injection of anti-PD-L1 antibody, and we analyzed the expression of candidate genes by qPCR at different time-points following treatment. We measured CP APOE by ELISA and quantified cholesterol-rich lipoproteins in the cerebrospinal fluid (CSF) by fluorometric assay. To attain mechanistic insight, we also performed bulk RNA-sequencing on primary CP epithelial cultures.
Results
We found that anti-PD-L1 induced an early and transient increase of CP APOE, and increased lipoproteins within the CSF in 5xFAD mice. The cholesterol derivative 24-hydroxycholesterol (24-OH) is a known inducer of APOE in the brain, generated by the neuronal enzyme, CYP46A1 hydroxylase. We verified that 24-OH induces Apoe gene expression in primary CP cultures. Furthermore, we found that PD-L1 blockade transiently elevates Cyp46a1 gene expression at the CP.
Conclusions
Our findings suggest that APOE elevation at the CP contributes, at least in part, to the beneficial effect of anti-PD-L1 treatment in disease modification.
IRON-LOADING IS A PROMINENT FEATURE OF ACTIVATED MICROGLIA IN ALZHEIMER’S DISEASE PATIENTS
Abstract
Aims
Iron accumulation in Alzheimer’s disease (AD) has been reported to correlate with Aβ and tau spreading, and to accelerate cognitive decline. Additionally, transcriptomic studies identified altered expression of iron-metabolism genes in activated microglia subtypes. Therefore, we aimed to study the prevalence of iron-accumulating microglia in AD and their activation state. Secondly we aimed to study the relation of iron-accumulatingmicroglia with Aβ-plaques.
Methods
We created a multiplex immunofluorescence-panel with markers for P2RY12, TMEM119, Light-Chain Ferritin (FTL), Aβ, Iba1 and DAPI, and stained brain tissue of 12 AD and 9 control patients (Fig. 1A). Cells were automatically segmented, phenotyped, and spatially mapped for further analysis.
Results
Segmentation allowed for identification of 69227 microglia, which were phenotyped into 13 clusters (Fig. 1B). Cluster 1 showed increased FTL and Iba1 expression and decreased TMEM119 and P2RY12 expression, and was significantly more present in AD-patients (P=0.0264; Fig 1C). Further investigation showed this FTL+Iba1+-cluster to be the predominant Aβ-plaque infiltrating microglia-cluster (P<0.0001; Fig. 1D,E). These microglia reflected iron-accumulating microglia (Fig. 1F) and showed advanced dystrophic morphology (Fig. 1G). Finally, these microglia were primarily present in subjects with high Aβ-load and Tau-load (Fig. 1H,I), and were found to be more present in APOE4-carriers (P=0.0667) and to infiltrate Aβ-plaques more (P=0.0381; Fig. 1J,K).
Conclusions
Using multi-marker phenotype evaluation on single cell level, while preserving morphological and spatial information of microglia with relation to Aβ-plaques, we identified activated P2RY12-TMEM119-FTL+Iba1+-microglia, which reflect iron-accumulating microglia in AD and predominantly infiltrate Aβ-plaques. These findings suggest iron to be taken up by microglia and to influence the functional phenotype, especially in conjunction with Aβ.
LOSS OF SYNAPTOGYRIN-3 RESCUES TAU-INDUCED MEMORY DEFECTS AND SYNAPTIC LOSS IN THE PRESENCE OF MICROGLIAL ACTIVATION
Abstract
Aims
Tauopathies are characterized by synaptic loss and neuroinflammation, but it is unclear if these pathological events are causally linked. We have previously shown that Tau binds to Synaptogyrin-3 on synaptic vesicles, leading to imapired vesicle mobility and pre-synaptic dysfunction. Here we aim to determine the consequences of preventing the binding of Tau to synaptic vesicles in a tauopathy mouse model, and whether this has any benefits in regard to different aspects of Tau-induced pathology.
Methods
We generated a synaptogyrin-3 knockout mouse line using CRISPR/Cas9 technology. We crossed synaptogyrin-3 knockout mice and human P301S Tau-expressing mice, and evaluated the effect of reducing Synaptogyrin-3 levels on different Tau-induced phenotypes. Given that Synaptogyrin-3 is uniquely present at pre-synaptic terminals, this allows us to decipher the contribution of pre-synaptic Tau to overall Tau-induced pathology.
Results
We show that loss of Synaptogyrin-3 rescues Tau-induced defects in long-term potentiation and working memory. It also significantly rescues the synaptic loss in the stratum lucidum caused by mutant Tau. However, hyper-phosphorylated Tau still accumulates at synapses and Tau-induced neuroinflammation remains clearly upregulated when we remove synaptogyrin-3.
Conclusions
We conclude that neuroinflammation is not sufficient to induce synaptic loss and these processes are separately induced in response to mutant Tau. In addition, the presynaptic defects caused by mutant Tau drive cognitive decline.
MICROGLIAL CONTRIBUTION IN AMYLOID-FACILITATED TAU-PATHOLOGY AND DOWNSTREAM NEURODEGENERATION ALONG THE A/T/N AXIS
Abstract
Aims
Brains of AD patients are characterized by the presence of amyloid pathology, Tau-pathology and neurodegeneration, referred to as A-, T- and N-pathology, respectively. AD brains are also characterized by microgliosis, which may contribute differently at different stages of the AD process. In this work, we aimed to identify microglial phenotypes and the active contribution of microglia on amyloid-facilitated Tau-pathology and subsequent Tau-induced neurodegeneration in an in vivo model.
Methods
To assess the effect of amyloid pathology on Tau-seeding, we performed Tau-seeding in the presence and absence of amyloid pathology (in TauP301S.5xFAD mice (F+/T+) and parental TauP301S mice) at 4 months. Tau-seeded Tau-pathology and its propagation were significantly increased in the presence of amyloid pathology 3 months post-seeding. Strikingly, significant hippocampal and cortical atrophy were detected only in the presence of amyloid pathology, recapitulating A/T/N pathology. To assess microglial contributions in Tau-pathology and neurodegeneration in the presence of amyloid pathology we used microglial depletion by CSF1R inhibition (PLX3397), and identified the microglial phenotypes using single cell sequencing.
Results
Tau-seeded Tau-pathology downstream of amyloid pathology was significantly decreased in Tau-seeded mice by PLX3397 treatment. Similarly, in PLX3397 treated mice, attenuated cerebral atrophy was observed. Analysis of microglial phenotypes is currently ongoing.
Conclusions
We here demonstrate that microglia actively contribute to Tau-pathology and Tau-induced neurodegeneration in the presence of amyloid pathology in an in vivo model recapitulating combined ATN pathologies.
A MOLECULAR NETWORK FOR LIVING HUMAN MICROGLIAL SUBSETS IN AGING AND NEURODEGENERATIVE DISEASES
Abstract
Aims
The goal of the project involved empirically determining (1) the population structure of living human microglia, (2) the genetic architecture of microglial gene expression, and (3) the key regulator genes for microglial function.
Methods
We have purified live human microglia from autopsy tissue of 75 subjects - including 41 with a diagnosis of Alzheimer’s disease or MCI and 8 with a Parkinsonian syndrome - for single cell RNAseq. We sampled the neocortex (BA4, BA9, BA20/21), substantia nigra, hippocampus, and spinal cord. ARACNE-AP was used to map regulatory networks, and the VIPER algorithm was used to identify candidate regulators.
Results
We had 215,680 individual microglial transcriptomes after QC. We identified 13 discrete subtypes of microglia. There are two families of microglial subtypes, suggesting that there may be two primary paths of differentiation, which then lead to a diverse array of terminally differentiated states. To date, we have found one cluster, marked by high expression of CD74, to be reduced in frequency in AD, and have validated this result in histological data and brain single nucleus data. We have mapped cis-expression quantitative trait loci (cis-eQTL) in each subtype. Finally, we defined modules of co-expressed genes within and across the 13 clusters. We then used these modules to derive a network map of microglial subsets and their relation to different diseases and to identify candidate master regulators associated with each subtype.
Conclusions
We have generated an initial map of human microglial regulatory networks from 13 subsets of live microglia, highlighting key nodes that contribute to aging and neurodegeneration.
SYSTEMS APPROACH TO NEUROINLAMMATION — COMPUTABLE BIOLOGICAL NETWORK MODEL FOR REACTIVE ASTROGLIOSIS
Abstract
Aims
Our objective is to provide a new computational tool that can simplify the detection of reactive astrogliosis in high-throughput datasets. Astrocytes respond to CNS insults with a broad variety of molecular and morphological changes. Traditional endpoints have focused on the production of inflammatory proteins and changes in key astrocyte markers. High-throughput technologies enable the capture of changes in thousands of molecules (e.g., RNA) triggered by reactive astrogliosis; but, interpretation of such data is challenging.
Methods
Causal biological network (CBN) models assemble biological knowledge in a structured computable format that facilitates mechanistic interpretation of molecular data. The network model consists of biological entities (nodes) and relationships between the nodes (edges). Information regarding gene expression regulation by some of the nodes in the network backbone is employed to build a second, scorable layer to the network model. This layer is used to infer the activity of the backbone nodes from transcriptomic data, and the impact on the network as a whole can be assessed by using the network perturbation amplitude algorithm.
Results
We introduce CBN models for reactive astrogliosis. These models capture key signaling pathways involved in i) pan-insult astrocyte reactivity, ii) neurotoxic A1-specific reactivity, iii) neurotrophic A2-specific reactivity, iv) loss of homeostatic functions, and v) glial scar formation. CBN models can be scored with transcriptomic data to derive a quantitative measure and mechanistic understanding of the key molecules that drive astrocyte reactivity in CNS studies.
Conclusions
This is the first step towards comprehensively modeling reactive astrogliosis in a computable form.
DISSECTING THE COMPLEXITY OF ASTROCYTE HETEROGENEITY IN THE AGED HUMAN BRAIN
Abstract
Aims
Neuroinflammation plays a critical role in the pathophysiology of neurodegenerative disorders, and astrocyte activity impairment has been implicated in the initiation and progression of Alzheimer’s Disease (AD). However, understanding the astrocyte heterogeneity in the aged human brain and identifying the subtypes relevant to AD remain challenging due inter-individual variability. This study aims to characterize astrocyte heterogeneity among aged individuals with or without AD and investigate the association of astrocyte subtypes with AD traits at RNA and protein levels.
Methods
We used single nucleus RNASeq (snRNAseq) to characterize subtypes of astrocytes in the dorsolateral prefrontal cortex of 24 aged individuals with or without AD from the Religious Orders Study and the Rush Memory and Aging Project cohorts. Then, a marker for each cluster was selected and stained by immunohistochemistry on post-mortem brain tissue from the same 24 individuals.
Results
We identified five different astrocyte subtypes that we classified in four categories: homeostatic, reactive, fibrous-like and inflammatory. The snRNAseq data revealed an association between increased fibrous-like astrocytes and cognitive decline, especially in individuals with AD pathology. No significant association was detected between AD traits and other astrocytes subtypes. Both snRNAseq and immunohistochemistry demonstrated that not all astrocyte subtypes were detected in all 24 individuals. SOCS3, a marker for reactive-like astrocyte was only detected in few individuals at RNA and protein levels.
Conclusions
Fibrous-like astrocyte subtype was associated with cognitive decline in AD. Further, combined snRNAseq and immunohistochemistry demonstrated the complexity of astrocyte heterogeneity, that is driven by high inter-individual variability.
THE PHENOTYPIC TRANSFORMATION OF ASTROCYTES IN ALZHEIMER’S DISEASE UNRAVELED BY THE BIOINFORMATIC COMPARTMENTALIZATION OF CORTICAL TRANSCRIPTOMES FROM PATIENTS INTO CELL-SPECIFIC GENE CLUSTERS
Abstract
Aims
The lack of astrocyte-specific transcriptomics from patients with Alzheimer’s disease (AD) hinders our understanding of the impact of astrocytes in AD. Here, we sought to identify changes in astrocytes using whole-brain transcriptomes from human patients and bioinformatic tools.
Methods
An astrocytic gene cluster was generated from a RNAseq database of healthy human brain cells (Zhang et al., Neuron, 2016. 89(1): p. 37-53) using a cell-type enrichment score and hierarchical clustering. The astrocyte cluster was co-localized in whole-brain transcriptomes from 766 subjects with mild cognitive impairment (MCI), AD or controls obtained from three databases (MtSINAI, Mayo Clinic and ROSMAP). Comparison of astrocytic genes among cohorts was performed by gene set and principal component analyses.
Results
All cohorts were molecularly heterogeneous, suggesting coexistence of disease types or stages within each cohort. Astrocytes in MCI and AD showed downregulation of ‘mitochondria’ and ‘endomembrane system’, and upregulation of ‘stress responses’, ‘plasticity’, and ‘perisynaptic astrocyte processes’/’gliotransmission’.
Conclusions
Astrocytes undergo a profound transcriptional change in MCI and AD, affecting organelles, particularly the endolysosomal system and mitochondria, as well as astrocyte-neuron interactions. The analysis suggests that therapies preventing organelle dysfunction in astrocytes may protect neural circuits in AD.