First-of-Its-Kind Map of Alzheimer's Reveals Hidden Gene Activity
NEWS | 17 February 2026
A new Alzheimer's study has produced a first-of-its-kind genetic map, which could provide vital insights into the cause-and-effect sequences of gene activity that may be driving the disease in the brain. This blueprint shows not only snapshots of gene activity in specific brain cells, but also connections between genes showing potential paths of chain reactions. The research team, from the University of California, Irvine (UC Irvine) and Purdue University in the US, used their map to identify 'hub genes' that act as major junctions for gene activity, and which could be targeted by future Alzheimer's treatments. "Different types of brain cells play distinct roles in Alzheimer's disease, but how they interact at the molecular level has remained unclear," says UC Irvine epidemiologist Min Zhang. "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 that actively drive disease progression." The researchers deployed a newly developed machine learning system called SIGNET – Statistical Inference on Gene Regulatory Networks, to give it its full name – to look in detail at brain tissue from 272 people who had died with Alzheimer's disease. Six main brain cell types were studied: excitatory neurons, inhibitory neurons, astrocytes, microglia, oligodendrocytes, and oligodendrocyte progenitor cells. The team used their software to focus on genes previously linked to Alzheimer's, and to see which other genes they might be influencing. As SIGNET can analyze both single-cell RNA sequencing and whole genome sequencing data, it means that both specific gene activity per brain cell type, and the bigger picture of the genetic starting point for these cells, can be compared and contrasted. "Most gene-mapping tools can show which genes move together, but they can't tell which genes are actually driving the changes," says epidemiologist Dabao Zhang, from UC Irvine. "Some methods also make unrealistic assumptions, such as ignoring feedback loops between genes." "Our approach takes advantage of information encoded in DNA to enable the identification of true cause-and-effect relationships between genes in the brain." The data showed that excitatory neurons (vital for brain signaling) had the most disruption in their genetic wiring in association with Alzheimer's. Almost 6,000 cause-and-effect interactions were identified within these cells. What's more, the genetic map data was later validated against a small number of additional human brains with Alzheimer's, which showed evidence of similar chain reactions. These previously hidden communications give scientists a much more detailed look at how Alzheimer's changes the expression of genes in the brain. That, in turn, opens up more opportunities to understand how the disease progresses and approaches that could stop or reverse it. Identifying both the master controller hub genes and the widespread disruption in excitatory neurons – essential to memory and cognition, which are severely impacted by Alzheimer's – means that we have new and more specific targets for drugs to combat Alzheimer's. Any treatments from this research are still a long way off, but because Alzheimer's is such a complex disease with so many overlapping contributors and consequences, any indications for where future research can focus are going to be helpful. As thorough as the study is, it doesn't conclusively prove that these gene changes are causing Alzheimer's. The next steps are to introduce comparisons with brain tissue unaffected by Alzheimer's, to try to tease out which shifts in brain wiring are due to the disease and which aren't. Related: Cancer May Emit Signals That Protect The Brain Against Alzheimer's "Moving forward, we will dive deeper into the current results to investigate networks involved in Alzheimer's disease-specific pathologies across different cell types," write the researchers in their published paper. "This comparison will allow us to distinguish the regulatory changes involved in neurodegeneration from normal cell activities during aging." The research has been published in Alzheimer's & Dementia.
Author: David Nield.
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