Summary: A new study reveals how genes influence where and how Alzheimer’s-related tau protein spreads in the brain. By combining imaging, gene data, and advanced modeling, researchers uncovered four gene pathways that either amplify or resist tau buildup, depending on brain connectivity.
This challenges the traditional idea of tau spreading passively and highlights active, directional transport along neural networks. The findings offer a blueprint for identifying targets to slow or stop the disease’s progression.
Key Facts:
- Four Gene Pathways Identified: Genes can either promote or resist tau buildup, aligned or independent of brain connectivity.
- Active Tau Spread: Tau travels directionally along brain wiring, not by passive diffusion.
- New Targets for Intervention: Insights into genetic influences may help develop therapies to block tau’s progression.
Source: UCSF
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, PhD, 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; and 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, PhD, a UCSF post-doctoral 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.”
This research built on another recent UCSF study in mice, published May 21 in Alzheimer’s & Dementia, which 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, PhD, a post-doctoral 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.”
Additional authors: Farras Abdelnour, Benjamin Sipes, Daren Ma, Pedro D. Maia, PhD.
Funding: The research was partially supported by NIH grants R01NS092802, RF1AG062196, and R01AG072753 awarded to Ashish Raj.
About this genetics, Alzheimer’s disease, and brain mapping research news
Author: Melinda Krigel
Source: UCSF
Contact: Melinda Krigel – UCSF
Image: The image is credited to Neuroscience News
Original Research: Open access.
“Selective vulnerability and resilience to Alzheimer’s disease tauopathy as a function of genes and the connectome” by Ashish Raj et al. Brain
Abstract
Selective vulnerability and resilience to Alzheimer’s disease tauopathy as a function of genes and the connectome
Brain regions in Alzheimer’s disease exhibit distinct vulnerability to its hallmark pathology with the entorhinal cortex and hippocampus succumbing early to tau tangles while others like the primary sensory cortices remain resilient.
The quest to understand how local/regional genetic factors, pathogenesis and network-mediated pathology spread, together govern this selective vulnerability (SV) or resilience (SR) is ongoing. Although many Alzheimer’s risk genes are known from gene association and transgenic studies, it is still unclear whether and how their baseline expression confers SV/SR to pathology.
Prior analyses have yielded conflicting results, pointing to a disconnect between the location of genetic risk factors and downstream tau pathology. The spatial distribution of vulnerability doesn’t always align with genetic factors, suggesting a role for non-cell-autonomous mechanisms like transneuronal tau transmission.
We hypothesize that a full accounting of the role of genes in mediating SV/SR would require modelling of network-based vulnerability, whereby tau misfolds, aggregates and propagates along fibre projections.
We employed an extended network diffusion model (eNDM) and fitted it on tau PET data from 196 patients from the Alzheimer’s Disease Neuroimaging Initiative. The fitted eNDM then becomes a reference from which to assess the role of innate genetic factors.
Using the residual (observed − model-predicted) tau as a novel target outcome, we obtained its association with 100 Alzheimer’s risk genes, whose baseline spatial transcriptional profiles were obtained from the Allen Human Brain Atlas.
Our eNDM was successful in capturing tau pathology distribution in patients. After regressing out the model, we found that while many risk genes have spatial expression patterns that correlate with regional tau, many others showed a stronger association with residual tau. This suggests that direct vulnerability aligned with the network, as well as network-independent vulnerability, are conferred by risk genes.
We report four classes of risk genes: network-aligned SV (SV-NA), network-independent SV (SV-NI), network-aligned SR (SR-NA) and network-independent SR (SR-NI), each with a distinct spatial signature and associated vulnerability to tau. Remarkably, using gene ontology analysis, we found that the identified gene classes have distinct and sometimes surprising functional enrichment patterns.
Network-aligned genes broadly participate in cell death, stress response and metabolic processing; network-independent genes in amyloid-β processing and immune response. These previously unreported segregated roles point to multiple distinct pathways by which risk genes confer vulnerability or resilience in Alzheimer’s disease.
Our findings offer new insights into vulnerability signatures in Alzheimer’s disease and may prove helpful in identifying potential intervention targets.
