The idea that tau pathology creeps through the brain via neural circuitry may have gained its strongest support yet from a study published January 17 in Nature Communications. Drawing on longitudinal tau PET imaging data from ADNI and BIOFINDER cohorts, researchers led by Michael Ewers of Ludwig-Maximilians-University in Munich reported that in people with amyloid plaque deposition, tau tangles crop up sequentially in functionally connected regions, as opposed to regions that are merely nearby. A combination of baseline tau-PET and functional connectivity predicted where, and to what extent, tau would accumulate next. The data support the idea that tau pathology spreads via neuronal circuitry, as opposed to simply drifting into neighboring areas.
- Tau tangles accumulate at similar rates in connected regions of the brain.
- Spatial proximity alone does not predict pattern of tau spread.
- Baseline tau and connectivity together do.
That tau tangles overtake the brain in a stereotypical pattern in AD was shown by neuropathology nearly 30 years ago (Braak and Braak, 1991). The advent of tau tracers has allowed scientists to track tangles in living people, and shown that Aβ deposition instigates the spread of neurofibrillary tangles from medial temporal lobe out into the neocortex (Feb 2018 news; May 2019 news; Jun 2019 news). Cross-sectional studies, including a recent one from Ewers and colleagues, have found that the timing and extent of tau accumulation appears highly correlated among regions that are functionally connected, i.e., that fire in sync with each other (Hoenig et al., 2018; Franzmeier et al., 2019; Vogel et al., 2019).
However, cross-sectional data cannot completely decipher longitudinal processes. First author Nicolai Franzmeier and colleagues analyzed serial data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and Swedish BIOFINDER cohorts. ADNI participants included 28 people without evidence of Aβ deposition, and 53 people with amyloid who were either cognitively normal or had mild cognitive impairment. The BIOFINDER set included 16 people without amyloid and 41 with amyloid, who spanned the AD spectrum from unimpaired to dementia. For both cohorts, participants had a baseline tau-PET scan and at least one additional scan about a year later.
The researchers first measured by how much tangles accumulated in each of 400 brain regions. As seen in previous studies, people without amyloid deposition had little to no evidence of tau tangles at baseline or follow-up, while those with amyloid not only had more tangles at baseline, but also had still more tau pathology at follow-up. Those with MCI or AD had more deposition than those who were cognitively normal.
How did patterns of tau accumulation in people with amyloid relate to functional connectivity? ADNI participants had resting-state functional MRI scans around baseline, which the researchers used to chart connectivity between 400 brain regions. BIOFINDER did not use fMRI, so the researchers used fMRI data compiled from 500 different people in the Human Connectome Project to create a connectivity template. Across 400 brain regions in both cohorts, the researchers found a strong positive association between functional connectivity and increase in tangles. In other words, the more closely two regions fired together, the more likely they were to have accumulated similar amounts of tau between baseline and follow-up.
Aβ Sparks Tau. In ADNI (left) and BIOFINDER (right) cohorts, tau PET shows tangle growth between baseline and follow-up (colored areas) only in people who have amyloid deposition. [Courtesy of Franzmeier et al., Nature Communications, 2020]
This link between functional connectivity and tangle burden held true regardless of the absolute amount of tau in a given region, though the link was strongest where tau-PET signals were highest. The association was consistent across all seven canonical brain networks, for example the default mode network, dorsal attention network, and frontoparietal control network. It held up even when the scientists controlled for how close together two regions were to each other, suggesting that synaptic connections, rather than proximity in the same neighborhood, dictated tau accumulation.
Franzmeier and colleagues next asked to what extent functional connectivity and/or spatial proximity predict patterns of tau spreading from one area to the next. Weaving baseline tau and functional connectivity into computational models, they were able to foretell changes in tau-PET seen one year later. Spatial proximity was not a strong predictor of tangles, but it did improve models of tau spread based on functional connectivity. Essentially, the findings suggested that tau spreads fastest between functionally connected regions that are also close to each other.
“No matter where tau pathology occurs, the functional connectivity of that region to another one seems to be the best predictor of where tau occurs next,” said Ewers.
The data are consistent with the long-held hypothesis that hyperphosphorylated, misfolded tau spreads between neurons via synaptic connections, corrupting healthy tau along the way (Jun 2009 news; Jun 2016 news). However, both Franzmeier and Ewers emphasized that the data are also consistent with the idea that interconnected regions become sequentially vulnerable to tau pathology.
David Jones of the Mayo Clinic in Rochester, Minnesota, agreed. “This and related studies are unable to differentiate purely reductionist mechanisms, such as transneuronal spreading, from complex systems models that include cascading network failures,” he wrote. “These two model classes would produce similar patterns in neuroimaging data, but would have vastly different mechanism and therapeutic implications across the disease spectrum.”
Tau propagation is likely a multifactorial process that depends on both transneuronal propagation and regional vulnerability, said Sylvia Villeneuve of McGill University in Montreal. Future studies that consider gene-expression differences between brain regions might illuminate the role of regional vulnerability, she said. For example, one study reported that regions prone to neurodegenerative disease tend to express genes that promote protein aggregation, while another implicated a combination of functional connectivity and gene expression in the spread of α-synuclein pathology in PD (Aug 2016 news; Zheng et al., 2019).
Villeneuve added that incorporating structural measures of connectivity—i.e., diffusion tensor imaging that traces white-matter connections—could also clarify what drives tau’s travel patterns. Ewers and Franzmeier agreed, noting that the two types of connectivity measures complement each other. While DTI exposes direct physical connections, resting-state functional MRI reveals both direct and indirect connections between regions. For example, two regions that fire together might be connected via one or two intermediate regions. Whether tau tangles accumulate more synchronously between directly versus indirectly connected regions could be explored by incorporating both imaging measures, they said.
Alexander Drzezga of the University Hospital of Cologne in Germany wondered how the known erosion of neural networks in AD might factor into the findings. Patterns of functional connectivity are known to change with disease progression. In particular, as tau accumulates, circuitry tends to crumble. “It is unclear whether the pattern of propagation in patients with affected network function is still determined by patterns of ‘previous (healthy)’ or by ‘current (diseased)’ pathways of high connectivity,” Drzezga wrote to Alzforum. In short, the causal relationship between network dysfunction and tau tangles needs more investigation (see full comment below).
The researchers believe longitudinal tau PET imaging is suitable to gauge treatment effects in clinical trials for therapies targeting tau. Using a functional connectivity template similar to the one devised for the BIOFINDER cohort, along with a patient’s baseline tau-PET scan, clinicians could predict where tau is most likely to accumulate next. In a follow-up tau-PET scan, they could assess how well a given treatment stopped tau in its tracks.—Jessica Shugart
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- Franzmeier N, Neitzel J, Rubinski A, Smith R, Strandberg O, Ossenkoppele R, Hansson O, Ewers M, Alzheimer’s Disease Neuroimaging Initiative (ADNI). Functional brain architecture is associated with the rate of tau accumulation in Alzheimer's disease. Nat Commun. 2020 Jan 17;11(1):347. PubMed.