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[Preprint]. 2024 Dec 13:2024.12.09.627436. [Version 1] doi: 10.1101/2024.12.09.627436

Data-driven discovery of cell-type-directed network-correcting combination therapy for Alzheimer’s disease

Yaqiao Li, Carlota Pereda Serras, Jessica Blumenfeld, Min Xie, Yanxia Hao, Elise Deng, You Young Chun, Julia Holtzman, Alice An, Seo Yeon Yoon, Xinyu Tang, Antara Rao, Sarah Woldemariam, Alice Tang, Alex Zhang, Jeffrey Simms, Iris Lo, Tomiko Oskotsky, Michael J Keiser, Yadong Huang, Marina Sirota
PMCID: PMC11661161  PMID: 39713353

Abstract

Alzheimer’s disease (AD) is a multifactorial neurodegenerative disorder characterized by heterogeneous molecular changes across diverse cell types, posing significant challenges for treatment development. To address this, we introduced a cell-type-specific, multi-target drug discovery strategy grounded in human data and real-world evidence. This approach integrates single-cell transcriptomics, drug perturbation databases, and clinical records. Using this framework, letrozole and irinotecan were identified as a potential combination therapy, each targeting AD-related gene expression changes in neurons and glial cells, respectively. In an AD mouse model, this combination therapy significantly improved memory function and reduced AD-related pathologies compared to vehicle and single-drug treatments. Single-nuclei transcriptomic analysis confirmed that the therapy reversed disease-associated gene networks in a cell-type-specific manner. These results highlight the promise of cell-type-directed combination therapies in addressing multifactorial diseases like AD and lay the groundwork for precision medicine tailored to patient-specific transcriptomic and clinical profiles.

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