Biology subjects

Shwab, E. K.

Publications and source records attributed to Shwab, E. K..

4 recordsLinked to original sources

bioRxiv2025

Single cell transcriptomics reveals enrichment of aggregation-prone alpha-synuclein isoforms across synucleinopathies

Alpha-synuclein (-Syn) is the primary component of Lewy bodies, the pathological hallmark of neurodegenerative synucleinopathies, including Parkinsons disease (PD) and dementia with Lewy bodies (DLB). Dysregulated expression of its encoding gene, SNCA, has been identified in association with both PD and DLB in short-read sequencing studies. However, such studies do not capture variation in transcript isoforms expressed. Here we combine for the first time SNCA-targeted long-read multiplexed arrays isoform sequencing (MAS-Iso-seq) with unbiased short-read single nucleus (sn) RNA-seq for simultaneous characterization of the SNCA transcript isoform landscape and mapping of isoform expression to specific cell types and subtypes in PD, DLB, and control sample cortical tissues. This approach enabled discovery of numerous SNCA transcript isoforms displaying novel splicing patterns and incorporating novel exons. We further identified an abundant class of transcript isoforms encoding a previously unreported -Syn protein variant (-Syn-115) and displaying increased proportional detection in excitatory neurons of PD and DLB tissues in comparison to controls. The proportion of these isoforms was found to be especially high within several specific glutamatergic neuron subtypes. In-depth characterization of the predicted structural and biochemical properties of -Syn-115 using an in silico modeling approach revealed a greater aggregative affinity compared with canonical -Syn-140, suggesting the potential for increased cytosolic -Syn-115 abundance to induce aggregation between heterogeneous -Syn isoforms, potentially driving fibril formation and disease progression. Together, our findings provide new insights into the molecular mechanisms underlying -Syn involvement in multiple synucleinopathies and have translational implications for the development of new precision medicine strategies to combat these diseases, indicating the potential for treatments targeting both specific transcript and protein isoforms, as well as disease-driving cell subtypes.

neuroscience↗

bioRxiv2024

Comparative mapping of single-cell transcriptomic landscapes in neurodegenerative diseases

INTRODUCTIONAlzheimers disease (AD), Dementia with Lewy bodies (DLB), and Parkinsons disease (PD) represent a spectrum of neurodegenerative disorders (NDDs). Here, we performed the first direct comparison of their transcriptomic landscapes. METHODSWe profiled the whole transcriptomes of NDD cortical tissue by snRNA-seq. We used computational analyses to identify common and distinct differentially expressed genes (DEGs), biological pathways, vulnerable and disease-driver cell subtypes, and alteration in cell-to-cell interactions. RESULTSThe same vulnerable inhibitory neuron subtype was depleted in both AD and DLB. Potentially disease-driving neuronal cell subtypes were present in both PD and DLB. Cell-cell communication was predicted to be increased in AD but decreased in DLB and PD. DEGs were most commonly shared across NDDs within inhibitory neuron subtypes. Overall, we observed the greatest transcriptomic divergence between AD and PD, while DLB exhibited an intermediate transcriptomic signature. DISCUSSIONThese results help explain the clinicopathological spectrum of this group of NDDs and provide unique insights into the shared and distinct molecular mechanisms underlying the pathogenesis of NDDs.

neuroscience↗

bioRxiv2024

Microglia States are Susceptible to Senescence and Cholesterol Dysregulation in Alzheimer's Disease

Cellular senescence is a major contributor to aging-related degenerative diseases, including Alzheimers disease (AD) but much less is known on the key cell types and pathways driving mechanisms of senescence in the brain. We hypothesized that dysregulated cholesterol metabolism is central to cellular senescence in AD. We analyzed whole transcriptomic data and utilized single-cell RNA seq integration techniques to unveil the convoluted cell-type-specific and sub-cell-type-state-specific senescence pathologies in AD using both ROSMAP and Sea-AD datasets. We identified that microglia are central components to AD associated senescence phenotypes in ROSMAP snRNA-seq data (982,384 nuclei from postmortem prefrontal cortex of 239 AD and 188 non-AD) among non-neuron cell types. We identified that homeostatic, inflammatory, phagocytic, lipid processing and neuronal surveillance microglia states were associated with AD associated senescence in ROSMAP (152,459 microglia nuclei from six regions of brain tissue of 138 early AD, 79 late AD and 226 control subject) and in Sea-AD (82,486 microglia nuclei of 42 dementia, 42 no dementia and 5 reference subjects) via integrative analysis, which preserves the meaningful biological information of microglia cell states across the datasets. We assessed top senescence associated bioprocesses including mitochondrial, apoptosis, oxidative stress, ER stress, endosomes, and lysosomes systems. Specifically, we found that senescent microglia have altered cholesterol related bioprocesses and dysregulated cholesterol. We discovered three gene co-expression modules, which represent the specific cholesterol related senescence transcriptomic signatures in postmortem brains. To validate these findings, the activation of specific cholesterol associated senescence transcriptomic signatures was assessed using integrative analysis of snRNA-seq data from iMGs (microglia induced from iPSCs) exposed to myelin, Abeta, and synaptosomes (56,454 microglia across two replicates of untreated and four treated groups). In vivo cholesterol associated senescence transcriptomic signatures were preserved and altered after treatment with AD pathological substrates in iMGs. This study provides the first evidence that dysregulation of cholesterol metabolism in microglia is a major driver of senescence pathologies in AD. Targeting cholesterol pathways in senescent microglia is an attractive strategy to slow down AD progression.

neuroscience↗

bioRxiv2023

Integrative single-nucleus multi-omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in Alzheimers disease brains

BackgroundThe genetic underpinnings of late-onset Alzheimers disease (LOAD) are yet to be fully elucidated. Although numerous LOAD-associated loci have been discovered, the causal variants and their target genes remain largely unknown. Since the brain is composed of heterogenous cell subtypes, it is imperative to study the brain on a cell subtype specific level to explore the biological processes underlying LOAD. MethodsHere, we present the largest parallel single-nucleus (sn) multi-omics study to simultaneously profile gene expression (snRNA-seq) and chromatin accessibility (snATAC-seq) to date, using nuclei from 12 normal and 12 LOAD brains. We identified cell subtype clusters based on gene expression and chromatin accessibility profiles and characterized cell subtype-specific LOAD-associated differentially expressed genes (DEGs), differentially accessible peaks (DAPs) and cis co-accessibility networks (CCANs). ResultsIntegrative analysis defined disease-relevant CCANs in multiple cell subtypes and discovered LOAD-associated cell subtype specific candidate cis regulatory elements (cCREs), their candidate target genes, and trans-interacting transcription factors (TFs), some of which were LOAD-DEG, for example, ELK1 in excitatory neurons (Exc1) and KLF13 and JUN, found in multiple cell subtypes. Finally, we focused on a subset of cell subtype-specific CCANs that overlap known LOAD-GWAS regions and catalogued putative functional SNPs changing the affinities of TF motifs within LOAD-cCREs linked to LOAD-DEGs including, APOE and MYO1E in a specific subtype of microglia and BIN1 in a subpopulation of oligodendrocytes. ConclusionsTo our knowledge, this study represents the most comprehensive systematic interrogation to date of regulatory networks and the impact of genetic variants on gene dysregulation in LOAD at a cell subtype resolution. Our findings revealed crosstalk between epigenetic, genomic, and transcriptomic determinates of LOAD pathogenesis and define catalogues of candidate genes, cCREs, and variants involved in LOAD genetic etiology and the cell subtypes in which they act to exert their pathogenic effects. Overall, these results suggest that cell subtype-specific cis-trans interactions between regulatory elements and TFs, and the genes dysregulated by these networks contribute to the development of LOAD.

neuroscience↗