
==== Front
bioRxiv
BIORXIV
bioRxiv
2692-8205
Cold Spring Harbor Laboratory

10.1101/2024.09.06.611761
preprint
1
Article
Single-nucleus multi-omics identifies shared and distinct pathways in Pick’s and Alzheimer’s disease
Shi Zechuan http://orcid.org/0000-0002-2844-5816

Das Sudeshna
Morabito Samuel
Miyoshi Emily
Stocksdale Jennifer
Emerson Nora
Srinivasan Shushrruth Sai
Shahin Arshi
Rahimzadeh Negin
Cao Zhenkun
Silva Justine
Castaneda Andres Alonso
Head Elizabeth
Thompson Leslie
Swarup Vivek http://orcid.org/0000-0003-3762-2746

08 9 2024
2024.09.06.611761https://creativecommons.org/licenses/by-nc-nd/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
http://biorxiv.org/lookup/doi/10.1101/2024.09.06.611761
nihpp-2024.09.06.611761.pdf
The study of neurodegenerative diseases, particularly tauopathies like Pick’s disease (PiD) and Alzheimer’s disease (AD), offers insights into the underlying regulatory mechanisms. By investigating epigenomic variations in these conditions, we identified critical regulatory changes driving disease progression, revealing potential therapeutic targets. Our comparative analyses uncovered disease-enriched non-coding regions and genome-wide transcription factor (TF) binding differences, linking them to target genes. Notably, we identified a distal human-gained enhancer (HGE) associated with E3 ubiquitin ligase (UBE3A), highlighting disease-specific regulatory alterations. Additionally, fine-mapping of AD risk genes uncovered loci enriched in microglial enhancers and accessible in other cell types. Shared and distinct TF binding patterns were observed in neurons and glial cells across PiD and AD. We validated our findings using CRISPR to excise a predicted enhancer region in UBE3A and developed an interactive database ( http://swaruplab.bio.uci.edu/scROAD ) to visualize predicted single-cell TF occupancy and regulatory networks.
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pmc
