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Home»News»A ‘Google Maps’ for tau movement sheds light on why some brain regions resist Alzheimer’s
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A ‘Google Maps’ for tau movement sheds light on why some brain regions resist Alzheimer’s

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A 'Google Maps' for tau movement sheds light on why some brain regions resist Alzheimer's
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Workflow of selective vulnerability and resilience analysis. Structural tractography data from diffusion tensor imaging (DTI) analysis and regional tau PET MRI data (observed tau) are entered into the extended network diffusion model (eNDM) to calculate predicted tau. Linear regression analysis between the observed (PET MRI) tau and eNDM-predicted tau provides residual tau levels. Baseline regional gene expression data obtained from the Allen Human Brain Atlas (AHBA) are correlated with regional observed and residual tau levels to identify genes in the selective vulnerability and selective resilience (SV and SR) groups. This is followed by gene ontology analysis (GO) on the gene sets identified above. Credit: Brain (2025). DOI: 10.1093/brain/awaf179

It’s been recognized for some time that Alzheimer’s disease affects brain regions differently and that tau—a protein known to misbehave—plays an important role in the disease. Normally, tau helps stabilize neurons, but in Alzheimer’s disease, it begins to misfold and tangle inside neurons. It spreads across the brain forming toxic clumps that impair neuronal function and ultimately lead to cell death.

Brain areas like the entorhinal cortex and hippocampus succumb early to tau tangles, while other areas, like the primary sensory cortices, remain resilient to the disease. In the quest to better understand this selective vulnerability (SV) or resilience (SR) to Alzheimer’s disease, researchers have looked to gene association and transgenic studies to identify Alzheimer’s risk genes. But past research has not shown a clear link between the location of genetic risk factors and associated tau pathology.

Now, a new study by UC San Francisco researchers has made a leap toward answering that question—by combining brain imaging, genetics, and advanced mathematical modeling into a powerful new lens. The study, published July 9 in Brain, shows multiple distinct pathways by which risk genes confer vulnerability or resilience in Alzheimer’s disease.

The study introduced a model of disease spread called the extended Network Diffusion Model (eNDM). The researchers applied this model on brain scans from 196 individuals at various stages of Alzheimer’s. They subtracted what the model predicted from what they saw in the scans. The leftovers, called “residual tau,” pointed to areas where something else besides brain connections influence the buildup of tau—in this case, genes.

Using brain gene expression maps from the Allen Human Brain Atlas, the researchers tested the degree to which Alzheimer’s risk genes explain the patterns of both actual and residual tau. This allowed them to tease apart genetic effects that act with or independently of the brain’s wiring.

“We think of our model as Google Maps for tau,” said senior study author Ashish Raj, Ph.D., UCSF professor of Radiology and Biomedical Imaging. “It predicts where the protein will likely go next, using real-world brain connection data from healthy people.”

This upends traditional view of how tau moves in the brain

The study team uncovered four distinct gene types based on how much and in what manner they were predictive of tau:

  • Network-Aligned Vulnerability (SV-NA), which are genes that boost tau spread along the brain’s wiring
  • Network-Independent Vulnerability (SV-NI), which are genes that promote tau buildup in ways unrelated to connectivity
  • Network-Aligned Resilience (SR-NA), which are genes that help protect regions that are otherwise tau hotspots
  • Network-Independent Resilience (SR-NI), which are genes that offer protection outside of the network’s usual path—like hidden shields in unlikely spots

“Vulnerability-aligned genes dealt with stress, metabolism, and cell death; resilience-related ones were involved in immune response and the cleanup of amyloid-beta—another Alzheimer’s culprit,” said study first author Chaitali Anand, Ph.D., a UCSF postdoctoral researcher.

“In essence, the genes that make parts of the brain more or less likely to be affected by Alzheimer’s are working through different jobs—some controlling how tau moves, others dealing with internal defenses or cleanup systems.”

Brain regions show varied Alzheimer's resistance, genetic analysis confirms
Tau exhibits a network-level directional preference. Credit: Alzheimer’s & Dementia (2025). DOI: 10.1002/alz.70092

This research built on another recent UCSF study in mice, published May 21 in Alzheimer’s & Dementia, that demonstrated that tau does not travel randomly or diffuse passively; instead, it follows the brain’s wiring pathways with a distinct directional preference.

Using a system of differential equations called the Network Diffusion Model (NDM), the research team was able to show the dynamics of tau spread between connected brain regions, challenging the traditional view that tau spreads simply by diffusing through extracellular space or leaking from dying neurons.

“Our research showed that tau propagates trans-synaptically, traveling along axonal projections driven by active transport processes rather than passive diffusion, and exploiting active neural pathways in the preferred retrograde direction,” said Justin Torok, Ph.D., a postdoctoral researcher working in the Raj lab.

In the current study, network-based analyses complemented the existing approaches for validating and identifying gene-based determinants of selective vulnerability and resilience. Genes that respond independently of the network having different biological functions than those genes that respond in concert with the network.

“This study offers a hopeful map forward: one that blends biology and brain maps into a smarter strategy for understanding and eventually stopping Alzheimer’s disease,” said Raj. “Our findings offer new insights into vulnerability signatures in Alzheimer’s disease and may prove helpful in identifying potential intervention targets.”

More information:
Chaitali Anand et al, Selective vulnerability and resilience to Alzheimer’s disease tauopathy as a function of genes and the connectome, Brain (2025). DOI: 10.1093/brain/awaf179

Justin Torok et al, Directionality bias underpins divergent spatiotemporal progression of Alzheimer‐related tauopathy in mouse models, Alzheimer’s & Dementia (2025). DOI: 10.1002/alz.70092

Provided by
University of California, San Francisco


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A ‘Google Maps’ for tau movement sheds light on why some brain regions resist Alzheimer’s (2025, July 9)
retrieved 9 July 2025
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