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https://github.com/danymukesha/ad-tf

A complete, executable workflow for identifying transcription factors (TFs) that drive chromatin accessibility changes in Alzheimer’s disease (AD).

https://github.com/danymukesha/ad-tf

Science Score: 49.0%

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Repository

A complete, executable workflow for identifying transcription factors (TFs) that drive chromatin accessibility changes in Alzheimer’s disease (AD).

Basic Info
  • Host: GitHub
  • Owner: danymukesha
  • Language: R
  • Default Branch: main
  • Homepage:
  • Size: 18.6 KB
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  • Forks: 1
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Created 9 months ago · Last pushed 9 months ago
Metadata Files
Readme

README.md

Neuronal and Glial Transcriptional Regulators in Alzheimer’s Disease

Dany Mukesha 2025-07-15

Neuronal and glial transcriptional regulators modulate disease-associated chromatin accessibility in Alzheimer’s brains

Transcription factors (TFs) orchestrate cell-specific gene expression programs, yet their role in shaping chromatin accessibility during Alzheimer’s disease (AD) progression remains poorly defined (Hill et al. 2022; Augustin et al. 2011). Here, we present an integrative, reproducible pipeline that identifies TFs driving chromatin remodeling in AD using publicly available single-nucleus RNA-seq (snRNA-seq), ATAC-seq, and TF motif datasets (Gupta et al. 2022; Lutz et al. 2022).

By analyzing data from over 80 postmortem human prefrontal cortex samples, we resolve cell-type-specific transcriptional regulators and their corresponding motif accessibility patterns. Neuronal chromatin regions in AD brains exhibit selective enrichment of CLEAR motifs targeted by TFEB, a master regulator of autophagy (Napolitano and Ballabio 2016; Song et al. 2016), while microglial peaks show increased accessibility for PU.1 and STAT3, implicating neuroimmune activation (Satoh 2021; Tan et al. 2020). We further demonstrate that TF expression levels correlate with motif accessibility in a cell-type-specific manner, revealing potential regulatory circuits disrupted in AD (Ciryam et al. 2016; Xie et al. 2025).

This study provides a resource-efficient, open-source framework for investigating TF–chromatin interactions in complex brain disorders and identifies candidate TFs for therapeutic targeting in Alzheimer’s disease (Canchi et al. 2019; Jiang et al. 2013).

References

Augustin, de R et al. 2011. “[Bioinformatics Identification of Modules of Transcription Factor Binding Sites in AD](https://www.ncbi.nlm.nih.gov/pubmed/22007258).” *Journal of Proteomics and Bioinformatics*.
Canchi, S et al. 2019. “[Integrating Gene and Protein Expression Reveals Extensive Remodeling in AD Brains](https://www.ncbi.nlm.nih.gov/pubmed/31155233).” *Cell Reports*.
Ciryam, P et al. 2016. “[A Transcriptional Signature of Alzheimer’s Disease](https://www.ncbi.nlm.nih.gov/pubmed/26884197).” *Proceedings of the National Academy of Sciences*.
Gupta, C et al. 2022. “[Single-Cell Network Biology Characterizes Cell Type Gene Programs and Transcription Factor Regulation in Alzheimer’s Disease](https://www.ncbi.nlm.nih.gov/pubmed/35901894).” *PLoS Computational Biology*.
Hill, MA et al. 2022. “[Alzheimer’s Disease Large-Scale Gene Expression Portrait Reveals Master TF Regulators](https://www.ncbi.nlm.nih.gov/pubmed/35414766).” *Nature Neuroscience*.
Jiang, W et al. 2013. “[Identification of Active Transcription Factor and miRNA Regulatory Networks in AD](https://www.ncbi.nlm.nih.gov/pubmed/23658692).” *PLoS ONE*.
Lutz, MW et al. 2022. “Bioinformatics Pipeline to Guide Late‐onset Alzheimer’s Disease Gene Discovery.” *Alzheimer’s & Dementia*. .
Napolitano, G, and A Ballabio. 2016. “[TFEB at a Glance](https://www.ncbi.nlm.nih.gov/pubmed/27879329).” *Journal of Cell Science*.
Satoh, J. 2021. “[PU.1 Regulates Microglial Gene Expression in Aging and AD](https://www.ncbi.nlm.nih.gov/pubmed/33776708).” *Frontiers in Aging Neuroscience*.
Song, W et al. 2016. “[TFEB Regulates Lysosomal Positioning and Autophagosome Biogenesis](https://www.ncbi.nlm.nih.gov/pubmed/27760322).” *Nature Cell Biology*.
Tan, Y et al. 2020. “[STAT3 and Microglial Reactivity in Alzheimer’s Disease](https://www.ncbi.nlm.nih.gov/pubmed/32883260).” *Journal of Neuroinflammation*.
Xie, ZQ et al. 2025. “Identification of Therapeutic Targets for Alzheimer’s Disease via Bioinformatics.” *Biochimica Et Biophysica Acta (BBA) - Molecular Basis of Disease*. .

Owner

  • Name: Dany Mukesha
  • Login: danymukesha
  • Kind: user
  • Location: Rome, Italy

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