Transcriptional Network Dysregulation in Alzheimer’s Disease Revealed by Individual-Specific Gene Regulatory Models

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Abstract

Alzheimer’s disease (AD) is a multifactorial neurodegenerative disorder marked by progressive cognitive decline, yet its transcriptional regulatory architecture remains poorly understood. Here, we model sample-specific gene regulatory networks (GRNs) from dorsolateral prefrontal cortex transcriptomes of 87 individuals with AD and 67 non-cognitively impaired (NCI) controls using PANDA and LIONESS algorithms. This personalized network approach captures individual-level transcriptional regulation, revealing 22 key transcription factor–gene interactions that distinguish AD from NCI with 96% accuracy.

Network topology analyses uncovered significant structural differences in regulatory connectivity and modular organization between AD and controls. Notably, ZNF225, ZNF849, and ZNF548 emerged as AD-specific regulatory hubs. The key transcription factor–gene interactions were enriched in pathways related to ADs molecular presentation, including synaptic signaling, mitochondrial function, proteostasis, and neuroinflammation.

Our findings highlight pervasive transcriptional network dysregulation in AD and underscore the value of personalized GRN modeling in uncovering regulatory mechanisms not apparent from differential gene expression alone. This systems-level approach reveals potential biomarkers and therapeutic targets, offering new insights into the molecular basis of AD and informing precision aging research.

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