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A Pathway-Based Machine Learning Approach Identifies Region-Specific Markers and Patterns in Alzheimer’s Disease Patients Based on Spatial and Severity Metadata

2025-12-02

Abstract excerpt

<h4>ABSTRACT</h4> Alzheimer’s disease (AD) exhibits profound spatial heterogeneity in its molecular and pathological features, yet the basis of this regional selectivity remains obscure. Here, we analyze transcriptomic profiles from publicly available bulk RNA-sequencing datasets collected from two cortical regions implicated in AD vulnerability: the insular cortex and Brodmann area 32 (BA32) of the anterior cing...

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Literature Corpus work: 557ba4fd-899f-5f35-a1d1-76007937a268
DOI: 10.64898/2025.12.01.25341417

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