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  Glial and vascular contributions to neurodegenerative diseases
Modeling Lewy body disease using human iPSC-derived cerebral organoids
Yunjung Jin1
1Mayo Clinic, Jacksonville, USA
 Background: Lewy body disease (LBD), including Parkinson’s disease and Lewy body dementia, is the second most common neurodegenerative disease after Alzheimer’s disease. The neuropathological hallmark of LBD is Lewy bodies mainly composed of aggregated α-synuclein (α-SYN) proteins, which is encoded by SNCA gene. It was reported that the triplication of SNCA gene can cause LBD within the same kindred, suggesting that aberrant α-SYN expression is sufficient for parkinsonism and highlighting the potential of generating LBD human models using the induced pluripotent stem cells (iPSC) from patients with SNCA gene triplication.
Materials and Methods: In this study, we used two iPSC lines from LBD patients carrying SNCA triplication that were collected by Mayo Clinic Neuroregeneration Lab. The iPSCs from healthy individuals were used as controls. The iPSC lines were differentiated into cerebral organoids and harvested after 8 weeks of culture. To characterize the α-SYN pathology, we performed biochemical analysis measuring total and phosphorylated α-SYN levels. We further fractionated the soluble proteins using size exclusion chromatography to identify the size distribution of α-SYN species. Finally, the single cell RNA sequencing was performed to identify the molecular pathways related with α-SYN pathogenesis in these organoids.
Results: We found significantly increased levels of total and phosphorylated α-SYN in the cerebral organoids derived from SNCA triplication iPSCs. The increased high-molecular-weight insoluble α-SYN aggregates were also found in these organoids with SNCA triplication. Additionally, ~45% of α-SYN species were existed at the size of 55 kDa which is consistent with the size distribution of α-SYN in human brains. Finally, the single cell RNA sequencing confirmed significantly higher SNCA gene levels in neuronal populations of SNCA triplication organoids, but not in other cell types such as astrocytes.
Conclusions: These findings suggest the iPSC-derived cerebral organoids from SNCA triplication patients can be a potential model for human LBD.
PSEN1. Several known AD-risk genes were differentially expressed in at least one cell type transcriptional state, including TMEM163, APP, and BIN1 in microglia (fold-change range 2.15 to 19.00), indicating that these genes are dynamically regulated during AD and are influenced by the genetic background of AD risk variants in other genes. We used public snRNA-seq data to replicate our differential expression results (dataset agreement odds-ratio per cell type range 3.21 to 94.82, p-values 4.8e-11 to 0.02; Fisher’s ET). Using snATAC-seq data, we identified multiple cell- type-specific enhancers harboring fine-mapped variants co-accessible with differentially expressed genes, such as rs6733839-BIN1 (microglia) and rs143080277-NCK2 (neurons).
Discussion: This work helps dissect the contributions of AD GWAS variants to gene expression heterogeneity at the cellular level, adding a layer of transcriptional subtype classification to distinguish neurodegeneration signatures of neuroglia in AD. We highlight cell types which do not necessarily have the highest expression levels for AD-related genes but have significant differences among transcriptional states likely contribute to mediating AD genetic risk.
Characterizing the transcriptional profile of Pick’s Disease, a 3R Tauopathy
Nicole Tamvaka1,2, Alexandra Soto-Beasley1, Zachary Quicksall3, Shanu Roemer1, Evan Udine1,2, Marka van Blitterswijk1,2, Dennis Dickson1, Owen Ross1,2
1Department of Neuroscience, Mayo Clinic, Jacksonville, USA, 2Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Jacksonville, USA, 3Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, USA
Characterizing the cellular states mediating Alzheimer’s Disease risk variants using single- cell omics
Ricardo D'oliveira Albanus1, Logan Brase1, Anjali Garg1, Shi-Feng You1, Carolina Soriano-Tarraga1, Bruno Benitez2, Carlos Cruchaga1, Celeste Karch1, Oscar Harari1
1Department of Psychiatry, Washington University School of Medicine, St. Louis, USA, 2Department of Neurology, Beth Israel Deaconess Medical Center, Boston, USA
 Background: Genetics and molecular studies identified multiple genetic loci associated with Alzheimer’s disease (AD) risk and progression. However, the cell types and molecular pathways mediating these effects are still poorly understood.
Methods: We analyzed single-nucleus transcriptomic profiles (snRNA- seq) from the parietal cortex from the Knight ADRC and DIAN brain banks[1] and public snRNA-seq and chromatin accessibility (snATAC- seq) profiles from prefrontal cortex[2] to study gene expression and chromatin accessibility in genes under AD risk loci
Results: We jointly analyzed a total of ~294K high-quality nuclei and identified six major cell populations ranging from 1.1% (endothelial) to 55.8% (oligodendrocytes) of all nuclei, as well as multiple transcriptional states for each cell type. We performed differential cell proportion analyses and identified multiple microglia and astrocyte expression states enriched for carriers of AD-risk variants in TREM2, MS4A, and APP/
Background: Pick’s Disease (PiD) is a rare neurodegenerative disorder characterized by fulminant dementia, frontotemporal degeneration and pathognomonic tau cytoplasmic inclusions known as Pick bodies. PiD is a type of primary tauopathy along with Progressive Supranuclear Palsy (PSP) and Corticobasal Degeneration (CBD). Tauopathies can be further classified as 3-Repeat (3R; PiD), 4-Repeat (4R; PSP, CBD), and 3R+4R (Primary Age Related Tauopathy, PART; Alzheimer’s disease, AD) based on the predominance of the tau isoform present in the inclusions characterizing each disease. Due to disease rarity, PiD remains significantly understudied and the causes that are driving the preferential 3R tau accumulation in PiD remain unclear. Furthermore, no study has characterized the transcriptomic profile of PiD, which is imperative for gaining insight into disease-specific mechanisms. Methods: Bulk RNA sequencing was performed in 28 PiD cases and 15 controls to identify changes in gene expression associated with PiD pathology. Additionally, PacBio long-read RNA sequencing (IsoSeq) was used in a subset of PiD cases and controls to explore isoform expression. Results: We identified 7 significantly differentially expressed genes between our groups (CCL2, SOCS3, SERPINA3, RNY1, U1, WIF1, SNORA63) and used IsoSeq to determine which specific isoforms are driving the observed effect. Interestingly, CCL2, SOCS3, and SERPINA3, which are glial-specific genes involved in inflammation and immunity, were shown to have significant positive correlation of expression in our dataset, as well as significant overlap in upstream regulator analysis. This is pointing to their potential common involvement in a pathway that could either be modulating disease pathogenesis or is dysregulated because of PiD pathology.
Discussion: We are further investigating the relationship between CCL2, SOCS3, and SERPINA3 and incorporating this data in our analyses of single-nuclei RNA Seq data and spatial transcriptomics data on the same cases, to better define 3R tau-specific disease relevant pathways and nominate molecular therapeutic targets.
80 • ISMND 2022

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