Selective Neuronal Vulnerability in Alzheimer's Disease: A Modern Holy Grail

Cross-disorder and disease-specific pathways in dementia revealed by single-cell genomics

The development of successful therapeutics for dementias requires an understanding of their shared and distinct molecular features in the human brain. We performed single-nuclear RNA-seq and ATAC-seq in Alzheimer's disease (AD), frontotemporal dementia (FTD), and progressive supranuclear palsy (PSP), analyzing 41 participants and ∼1 million cells (RNA + ATAC) from three brain regions varying in vulnerability and pathological burden. We identify 32 shared, disease-associated cell types and 14 that are disease specific. Disease-specific cell states represent glial-immune mechanisms and selective neuronal vulnerability impacting layer 5 intratelencephalic neurons in AD, layer 2/3 intratelencephalic neurons in FTD, and layer 5/6 near-projection neurons in PSP. We identify disease-associated gene regulatory networks and cells impacted by causal genetic risk, which differ by disorder. These data illustrate the heterogeneous spectrum of glial and neuronal compositional and gene expression alterations in different dementias and identify therapeutic targets by revealing shared and disease-specific cell states.

Neuropathogenesis-on-chips for neurodegenerative diseases

Developing diagnostics and treatments for neurodegenerative diseases (NDs) is challenging due to multifactorial pathogenesis that progresses gradually. Advanced in vitro systems that recapitulate patient-like pathophysiology are emerging as alternatives to conventional animal-based models. In this review, we explore the interconnected pathogenic features of different types of ND, discuss the general strategy to modelling NDs using a microfluidic chip, and introduce the organoid-on-a-chip as the next advanced relevant model. Lastly, we overview how these models are being applied in academic and industrial drug development. The integration of microfluidic chips, stem cells, and biotechnological devices promises to provide valuable insights for biomedical research and developing diagnostic and therapeutic solutions for NDs.

Disease-specific selective vulnerability and neuroimmune pathways in dementia revealed by single cell genomics

The development of successful therapeutics for dementias requires an understanding of their shared and distinct molecular features in the human brain. We performed single-nuclear RNAseq and ATACseq in Alzheimer disease (AD), Frontotemporal degeneration (FTD), and Progressive Supranuclear Palsy (PSP), analyzing 40 participants, yielding over 1.4M cells from three brain regions ranging in vulnerability and pathological burden. We identify 35 shared disease-associated cell types and 14 that are disease-specific, replicating those previously identified in AD. Disease - specific cell states represent molecular features of disease-specific glial-immune mechanisms and neuronal vulnerability in each disorder, layer 4/5 intra-telencephalic neurons in AD, layer 2/3 intra-telencephalic neurons in FTD, and layer 5/6 near-projection neurons in PSP. We infer intrinsic disease-associated gene regulatory networks, which we empirically validate by chromatin footprinting. We find that causal genetic risk acts in specific neuronal and glial cells that differ across disorders, primarily non-neuronal cells in AD and specific neuronal subtypes in FTD and PSP. These data illustrate the heterogeneous spectrum of glial and neuronal composition and gene expression alterations in different dementias and identify new therapeutic targets by revealing shared and disease-specific cell states.

Spatiotemporal Expression of RNA-Seq Identified Proteins at the Electrode Interface

Implantation of electrodes in the brain can be used to record from or stimulate neural tissues to treat neurological disease and injury. However, the tissue response to implanted devices can limit their functional longevity. Recent RNA-seq datasets identify hundreds of genes associated with gliosis, neuronal function, myelination, and cellular metabolism that are spatiotemporally expressed in neural tissues following the insertion of microelectrodes. To validate mRNA as a predictor of protein expression, this study evaluates a sub-set of RNA-seq identified proteins (RSIP) at 24-hours, 1-week, and 6-weeks post-implantation using quantitative immunofluorescence methods. This study found that expression of RSIPs associated with glial activation (Glial fibrillary acidic protein (GFAP), Polypyrmidine tract binding protein-1 (Ptbp1)), neuronal structure (Neurofilament heavy chain (Nefh), Proteolipid protein-1 (Plp1), Myelin Basic Protein (MBP)), and iron metabolism (Transferrin (TF), Ferritin heavy chain-1 (Fth1)) reinforce transcriptional data. This study also provides additional context to the cellular distribution of RSIPs using a MATLAB-based approach to quantify immunofluorescence intensity within specific cell types. Ptbp1, TF, and Fth1 were found to be spatiotemporally distributed within neurons, astrocytes, microglia, and oligodendrocytes at the device interface relative to distal and contralateral tissues. The altered distribution of RSIPs relative to distal tissue is largely localized within 100µm of the device injury, which approaches the functional recording range of implanted electrodes. This study provides evidence that RNA-sequencing can be used to predict protein-level changes in cortical tissues and that RSIPs can be further investigated to identify new biomarkers of the tissue response that influence signal quality. STATEMENT OF SIGNIFICANCE: : Microelectrode arrays implanted into the brain are useful tools that can be used to study neuroscience and to treat pathological conditions in a clinical setting. The tissue response to these devices, however, can severely limit their functional longevity. Transcriptomics has deepened the understandings of the tissue response by revealing numerous genes which are differentially expressed following device insertion. This manuscript provides validation for the use of transcriptomics to characterize the tissue response by evaluating a subset of known differentially expressed genes at the protein level around implanted electrodes over time. In additional to validating mRNA-to-protein relationships at the device interface, this study has identified emerging trends in the spatiotemporal distribution of proteins involved with glial activation, neuronal remodeling, and essential iron binding proteins around implanted silicon devices. This study additionally provides a new MATLAB based methodology to quantify protein distribution within discrete cell types at the device interface which may be used as biomarkers for further study or therapeutic intervention in the future.