AI-built maps reveal causal gene regulation across Alzheimer’s brain cell types

Researchers led by Min Zhang and Dabao Zhang of the University of California, Irvine's Joe C. Wen School of Population & Public Health have created the most detailed maps to date showing how genes causally regulate one another across different types of brain cells affected by Alzheimer's disease.

Using their newly developed machine learning framework, SIGNET, which reveals cause-and-effect relationships rather than simple genetic correlations, they uncovered key biological pathways that may drive memory loss and brain degeneration.

The study, published in Alzheimer’s & Dementia, also identifies new genes that could serve as targets for future treatments.

Alzheimer’s disease, the leading cause of dementia, is projected to affect nearly 14 million Americans by 2060. Scientists have already found many genes linked to the disease, such as APOE and APP, but they still don’t fully understand how these genes disrupt healthy brain function.

“Different types of brain cells play d

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