Wang, Xue

AbstractBackgroundAlzheimer’s disease (AD) is a complex, multicellular disease with immunological and genetic components. Previous studies demonstrated associations between AD and the missense variants ABI3‐rs616338‐T and PLCG2‐rs72824905‐G. The perturbed expression of these genes has been demonstrated to disrupt microglial function. To date, the transcriptomic profiles of variant carriers in the context of microglial subtype and state have not been explored in human brain. This represents a knowledge gap in our understanding of AD risk and resilience. We have developed and optimized a single nucleus RNAseq (snRNAseq) approach to study the impact of ABI3 and PLCG2 variants on microglial enriched nuclei from frozen human brain.MethodDOCK8 was identified as a nuclear microglial marker based on previous brain snRNAseq data. DOCK8 based microglial enrichment using fluorescent activated nuclei sorting (FANS) was validated using RT‐qPCR and snRNAseq in human cerebellum and temporal cortex (TCX), respectively. We are applying this enrichment and snRNAseq approach to TCX tissue from a cohort of 30 donors harboring ABI3 or PLCG2 missense mutations, or neither. Standard snRNAseq alignment and quality control pipelines will be applied, and nuclei annotated based on putative microglial markers. Differential gene expression will be assessed using pseudo bulk and MAST approaches, for association with ABI3 and PLCG2 genotype, diagnosis groups, risk factors, and pathology scores.ResultDOCK8 has several commercially available antibodies, making it an ideal microglia‐selection marker. Using RT‐qPCR in microglia enriched nuclei, we demonstrated an enrichment of microglia marker genes and depletion of other brain cell type markers. This is further supported by snRNA‐seq data from DOCK8‐sorted TCX tissue that yielded a 5x increase in microglia proportion (56% vs. 11% in unselected nuclei), enabling analyses of microglia sub‐populations. Leveraging this approach, we will investigate affected genes and pathways and uncover the resilience and risk mechanisms within microglia sub‐populations in ABI3 and PLCG2 variant‐carriers.ConclusionOur study presents a novel method for enriching microglial nuclei from frozen human brains and enables transcriptomic profiling of microglial subpopulations in ABI3 and PLCG2 missense variant‐carriers. We expect these insights will reveal novel genes and pathways that may play a key role in microglial function in AD.

AbstractBackgroundAlzheimer’s disease (AD) is neuropathologically characterized by amyloid‐β (Aβ) plaques and tau neurofibrillary tangles often quantified by Thal phase and Braak stage, respectively. Aβ also frequently deposits in the cerebrovasculature with severity categorized by a cerebral amyloid angiopathy (CAA) score. These and related measures often show high variability within AD suggesting distinct underlying mechanisms, the identification of which may reveal important biological insights into AD pathophysiology. We hypothesize that, within the AD brain, neuropathology and levels of core AD‐related proteins are influenced by variations in DNA methylation (DNAm). To test this, we performed epigenome‐wide association studies (EWAS) using DNAm clusters from the temporal cortex (TCX) and cerebellum (CER) with AD‐related neuropathologic measures (Braak, Thal, and CAA) and brain biochemical levels of five proteins (apoE, Aβ40, Aβ42, tau, and p‐tau).MethodsDNAm from neuropathologically‐confirmed AD cases available through the Mayo Clinic brain bank was measured by reduced representation bisulfite sequencing (RRBS) from 471 brain samples, 200 of which had both TCX and CER measures. Neuropathology was scored by an experienced neuropathologist. TCX levels of five AD‐related proteins from three tissue fractions (buffer‐, detergent‐, and in‐soluble) were measured by ELISA (Liu 2020). CpG methylation (CpGm) was binned by a 15‐state chromatin model (Kundaje 2015) and averaged. Averaged CpGm clusters were tested for their association with each endophenotype through multi‐variable linear regression. The influence of CpGm clusters on expression levels of nearby genes was also investigated through multi‐variable regression.ResultsOur innovative binning method demonstrated expected and biologically relevant CpGm patterns. We identified multiple epigenome‐wide significant CpGm clusters unique to each AD‐related endophenotype and brain region. Comparisons between the TCX and CER further revealed brain region‐specific enrichment of distinct CpGm clusters. Significant CpGm clusters were further characterized by their influence on gene expression.ConclusionsAlthough all neuropathologic and biochemical endophenotypes tested are core to AD pathophysiology, our results suggest each has a distinct epigenetic architecture underlying their variability in the AD brain. By discovering brain region‐specific DNAm changes that contribute to each neuropathologic or biochemical outcome, we can identify core components of complex mechanisms that individually and jointly contribute to AD.

AbstractBackgroundGene expression changes have been identified in post‐mortem brain tissue of AD cases when compared with controls, implicating various genes and pathways. Such findings provide important insights into molecular dysregulation associated with this disease and nominate therapeutic targets. Here we investigate brain gene and co‐expression network changes in a cohort of AD cases to identify associations with degree of AD neuropathology including Braak stage (Tau), Thal phase (Amyloid beta) and brain tissue levels of five AD‐related proteins (apoE, Aβ40, Aβ42, tau, and p‐tau).MethodGene expression measures were collected from temporal cortex (TCX) tissue of 477 AD cases, available through the Mayo Clinic Brain Bank, using RNA sequencing (Illumina TruSeq mRNA) performed on the HiSeq4000. Following quality control 456 cases remained for analysis. Braak and Thal were provided by an experienced neuropathologist and TCX levels of five AD‐related proteins from three fractions (buffer‐soluble, detergent‐soluble, and insoluble) were measured by ELISA (Liu et al. 2020). Weighted gene coexpression network analysis (WGCNA) R package was used to build co‐expression networks. Genes and networks were tested for association with neuropathology and AD‐related protein levels, adjusting for relevant covariates.ResultA total of 57,353 genes were profiled, of which 19,044 were reliably expressed above background levels and formed 20 co‐expression modules. 36 genes were associated with Braak stage, 10 with Thal phase and up to 9,000 with the AD‐related protein fractions. Brain levels of pTau had the greatest number of associations, with an overrepresentation of genes involved in synaptic signalling and immune response gene ontology biological processes. 16 of the coexpression modules associated with at least one trait after Bonferroni correction for number of tests.ConclusionWe have identified a number of genes and networks associated with different aspects of AD neuropathology and associated proteins, further lending support to the involvement of synaptic and immune biology in AD. However it is not clear whether observed changes cause disease or are a consequence of the neurodegenerative process. Comparison of these findings across different proteins and fractions is expected to reveal common and distinct vulnerabilities associated with amyloid and tau, and different stages of protein aggregation.

AbstractBackgroundMetabolic dysregulation is one of the hallmarks of Alzheimer’s disease (AD). Alterations in metabolism have been associated with AD‐related comorbidities, cognitive decline, and AD brain pathology. Brain regions are differentially affected with AD neuropathology and exhibit metabolic heterogeneity. Therefore, to build a more comprehensive picture of metabolic impact of AD, region‐specific AD‐associated metabolic changes need to be determined.MethodWe profiled 344 brain samples from the Mayo Clinic brain bank using Metabolon’s untargeted metabolomics platform, covering 182 samples from the cerebellum (CER) and 162 samples from the temporal cortex (TCX). Generalized linear models were used to assess the association of metabolic profiles with AD. Models included confounder correction for age at death, sex, and number of APOE‐ε4 alleles. To extend this study to four more brain regions, we included results from previously published brain metabolomics studies based on samples from three independent cohorts, including dorsolateral prefrontal cortex (DLPFC) from ROS/MAP, parietal lobe (PTL) from Washington University School of Medicine (WUSM), inferior temporal gyrus (ITG) and middle frontal gyrus (MFG) from Baltimore Longitudinal Study of Aging (BLSA).ResultIn the Mayo cohort, a total of 190 out of the 658 metabolites were significantly associated with AD. Out of the 190, 127 metabolites associated only in the CER region, 37 metabolites associated only in the TCX region, and 26 metabolites were associated in both brain regions. There were no metabolites commonly regulated in all the 6 brain regions under investigation. DLPFC and CER had the highest overlap of 70 metabolites, followed by DLPFC and PTL with 64 metabolites, and CER and PTL with 47 metabolites. For functional interpretation of our findings, each metabolite was further categorized with a sub‐pathway annotation provided by Metabolon. 3 of the 88 pathways including methionine cycle, phospholipid metabolism, and glutathione metabolism, were commonly regulated in the six brain regions under investigation.ConclusionWe present a first global perspective on AD‐associated metabolic alterations across six brain regions. This study will pave the way to fill the gap in our understanding of region‐specific metabolic deregulations associated with AD pathophysiology.

AbstractBackgroundIn the Alzheimer’s disease sequencing project (ADSP) whole exome dataset, only the well‐known TREM2.pR47H variant shows genome‐wide significance by conventional single variant analysis. To identify novel AD genes related to TREM2, we used gene‐based polygenic score analysis (PGSA) to evaluate an immune, temporal cortical co‐expression network with 229 genes including TREM2.MethodThe most recent whole exome variant call files from the ADSP (NG00067.v7) were subjected to stringent quality control. Post‐QC samples were divided into discovery (4174 samples sequenced at Broad), test (3299 samples sequenced at WashU), and follow‐up (2273 samples sequenced at Baylor) sets. The pruned variants (r2 < 0.2) with a minor allele count over 20 in each gene were analyzed by Broad/WashU PGSA thereby obtaining P‐values (gPbr.wa) for each gene in WashU samples. To assess significance in independent Baylor samples, cumulative Broad/Baylor PGSA was performed using a novel approach in which variants were stratified by both gene (gPbr.wa) and variant (Broad.P).ResultAfter excluding TREM2, the five variants with gPbr.wa ≤ 0.08 and Broad.P ≤ 0.03 showed significant association in Broad/Baylor PGSA. One of these variants showed no evidence of association with AD in the combined dataset. Polygenic scores for the other four variants, which were in three genes, showed significant association in Baylor samples, and significant, essentially identical association in WashU samples. Polygenic scores for nine additional variants in these genes (0.03> Broad.P ≤ 0.13) also showed significant, essentially identical association in Baylor and WashU samples. The association of these 13 variants with AD was driven primarily by six deleterious, protein‐altering variants with minor allele frequencies less than 1%, but the other 7 variants also contributed.ConclusionUsing gene‐based polygenic score analysis to analyze an immune co‐expression network, we identify three novel immune genes with actionable nonsynonymous and stopgain variants that show significant, replicable association with AD in the most recent release of the ADSP whole exome dataset.

AbstractBackgroundAlzheimer’s disease (AD) is a progressive neurodegenerative disorder neuropathologically characterized by amyloid‐β (Aβ) plaques and tau neurofibrillary tangles often measured by Thal phase and Braak stage, respectively. Frequently, Aβ also deposits in the brain vasculature with severity categorized by a cerebral amyloid angiopathy (CAA) score. Assessment of these and related endophenotypes can reveal biological insights into the phenotypic variability in AD. We hypothesize that, amongst AD patients, severity of neuropathology and brain levels of AD‐related proteins are influenced by variation in DNA methylation (DNAm), the identification of which may uncover biological pathways for AD pathogenesis. To test this, we performed epigenome‐wide association studies (EWAS) using DNAm from the temporal cortex (TCX) and cerebellum (CER) with AD‐related neuropathology measures (Braak, Thal, and CAA) and brain levels of five proteins (apoE, Aβ40, Aβ42, tau, and p‐tau).MethodsDNAm from autopsy‐confirmed AD cases available through the Mayo Clinic Brain Bank was measured by reduced representation bisulfite sequencing (RRBS) from 471 brain samples, 200 of which had both TCX and CER measures. Bisulfite converted reads were sequenced on the Illumina High Seq4000 and quality filtered. Neuropathology scoring was performed by an experienced neuropathologist. TCX levels of five AD‐related proteins from three fractions (buffer‐soluble, detergent‐soluble, and insoluble) were measured by ELISA (Liu et al. 2020). Individual CpG methylation ratios were tested for association with each neuropathological and biochemical measure using the R package CpGassoc.ResultsWe identified multiple epigenome‐wide significant CpGs unique to each AD‐related measure. Comparisons between the TCX and CER revealed region specific CpG associations. The effects of sex, age at death, APOE genotype, and presence of genetic variants for each significant CpG association were also identified.ConclusionsAlthough all neuropathological and biochemical measures tested reflect core AD pathologies, our results demonstrate unique associations of epigenetic factors with these individual phenotypes, suggesting that their variability may be governed by distinct epigenetic processes. Discovery of DNAm changes that underlie specific neuropathological or biochemical outcomes can enhance our understanding of AD pathophysiology and may lead to the identification of novel gene or pathway targets for the different facets of this complex condition.

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.