AI maps gene control networks driving Alzheimer's disease

Researchers create detailed maps of gene control in Alzheimer's

A team from the University of California, Irvine has created the most comprehensive maps to date of how genes directly control one another in brain cells affected by Alzheimer's disease. The research, published in Alzheimer's & Dementia: The Journal of the Alzheimer's Association, moves beyond identifying linked genes to reveal the causal relationships driving the disease.

The scientists developed a machine learning platform called SIGNET to build these maps. This tool was designed to uncover true cause-and-effect relationships between genes, which traditional correlation-based methods cannot reliably accomplish.

How SIGNET works to find cause and effect

The team analyzed single-cell molecular data from brain samples donated by 272 participants in long-term aging studies. SIGNET integrates single-cell RNA sequencing with whole-genome sequencing data to detect causal relationships across the entire genome.

"Most gene-mapping tools can show which genes move together, but they can't tell which genes are actually driving the changes," said co-corresponding author Dabao Zhang, a professor of epidemiology and biostatistics. The platform constructed causal gene regulatory networks for six major brain cell types.

Major genetic rewiring found in key neurons

The most significant gene disruptions were found in excitatory neurons, which send activating signals in the brain. The research revealed nearly 6,000 cause-and-effect interactions, showing extensive genetic rewiring as Alzheimer's progresses.

The study also identified hundreds of "hub genes" that function as central regulators influencing many other genes. These hub genes could become valuable targets for earlier diagnosis and future therapies.

• Found nearly 6,000 causal interactions in excitatory neurons
• Identified hundreds of central "hub genes"
• Uncovered new regulatory roles for well-known genes like APP

New targets for Alzheimer's treatments emerge

The maps highlight newly identified genes that could become promising targets for future treatments. The research also uncovered new regulatory roles for well-known Alzheimer's-related genes.

For example, the APP gene was shown to strongly control other genes in inhibitory neurons. The team validated their findings using an independent set of human brain samples, strengthening confidence that the observed relationships reflect genuine biological mechanisms.

"Our work provides cell type-specific maps of gene regulation in the Alzheimer's brain, shifting the field from observing correlations to uncovering the causal mechanisms," said co-corresponding author Min Zhang, a professor of epidemiology and biostatistics.

Potential applications beyond Alzheimer's

The SIGNET platform may be applied to the study of other complex diseases. Researchers suggest it could help unravel genetic networks in conditions including cancer, autoimmune disorders, and mental health conditions.

Funding support for the study came in part from the National Institute on Aging and the National Cancer Institute. Alzheimer's disease is the leading cause of dementia and is expected to affect nearly 14 million Americans by 2060.