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Single-nucleus multi-omics identifies shared and distinct pathways in Pick's and Alzheimer's disease.

41223260
PMC12609060
Science advances
Nov. 14, 2025
Mathematical, Computational and Systems Biology Program, University of California, Irvine, Irvine, CA 92697, USA.
Gene Regulatory Networks, Microglia, Enhancer Elements, Genetic, Cell Nucleus, Gene Expression Regulation, Transcription Factors, Ubiquitin-Protein Ligases, Single-Cell Analysis, Neurons, Alzheimer Disease, Transcriptome, Humans, Multiomics
U19 AG068054, RF1 AG071683, P01 NS084974, T32 AG000096, U54 AG054349, F31 AG076308, R35 NS116872
Head E, Swarup V, Cao Z, Morabito S, Miyoshi E, Shi Z, Rahimzadeh N, Silva J, Das S, Srinivasan SS, Emerson N, Thompson L, Stocksdale J, Shahin A, Castaneda AA
Shi Z, Das S, Morabito S, Stocksdale J, Miyoshi E, Srinivasan SS, Emerson N, Shahin A, Rahimzadeh N, Cao Z, Silva J, Castaneda AA, Head E, Thompson L, Swarup V. Single-nucleus multi-omics identifies shared and distinct pathways in Pick's and Alzheimer's disease. Science advances. 2025 Nov 14.

Abstract

The study of transcriptomic and epigenomic variations in neurodegenerative diseases, particularly tauopathies like Pick's disease (PiD) and Alzheimer's disease (AD), offers insights into their underlying regulatory mechanisms. Here, we identified critical regulatory changes driving disease progression, revealing potential therapeutic targets. Our comparative analyses uncovered disease-enriched noncoding 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, scROAD, to visualize predicted single-cell TF occupancy and regulatory networks.