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Measuring tau accumulation and progression

The ability of PET to map regional changes in tau pathology over time provides important insights into factors influencing tau accumulation and the rate and spatial distribution of its spread. Rik Ossenkoppele (Amsterdam University Medical Center, The Netherlands) considered the clinical implications of recent findings during a presentation at AAIC2020.

Longitudinal PET studies suggest tau accumulates at a rate of around 3-10% per year in people with cognitive impairment and Alzheimer’s dementia, compared with an annual rate of 0-3% in healthy elderly controls.1,2

Although study findings are not entirely consistent, it appears that the presence of amyloid pathology encourages tau progression.3 In people who are amyloid-beta (Aβ) positive, younger age is associated with higher tau PET levels at baseline and faster accumulation with time.4

 

Amyloid, age, gender and genetics play a part

Tau drives local neurodegeneration and tau-PET predicts progression in the individual patient5

Along with Aβ pathology and age, factors related to sex, genetics and connectivity also influence tau accumulation.

Women have higher tau PET levels at baseline and accumulate tau faster – but, intriguingly, they are more resistant to its effects: with the same extent of tau pathology, brain structures are better preserved in women than in men.6 Whether this is due to hormonal or other genetic influences remains to be established.

More broadly, the effects of genetics are complex. In cognitively unimpaired people, the APOE ɛ4 allele predicts increased tau in the medial temporal lobe, but in cognitively impaired people, APOE ɛ4 non carriers show greater tau load in the parietal cortex. The single nucleotide polymorphism rs744373 in the bridging integrator-1 gene (BIN1) is associated with worse memory, which seems to be mediated by increased global tau levels.7

BIN1 has been linked to increased tau pathology

 

Connectivity a key to spread

Tau may spread through functional connections, causing network-based neurodegeneration. Ossenkoppele and colleagues recently found a striking overlap between patterns of spread in AD patients and fMRI functional connectivity maps in healthy adults.

One potential clinical application of these findings is the prediction of neurodegeneration, since there is good spatial overlap between tau present in a baseline PET and brain atrophy that becomes evident with longitudinal MRI.5 Baseline tau accounted for 43% of the variance in amount of brain atrophy while baseline amyloid explained only 3%.

A second clinical application is in establishing the likely pattern of tau spread in individual patients since both Alzheimer's Disease Neuroimaging Initiative and BioFINDER data show that tau accumulates most quickly in regions closely connected to a tau epicenter. 

In another presentation during the session on tau pathology, Gabor Kovacs (University of Toronto, Canada) agreed that hierarchical involvement of brain regions is seen in tau proteinopathies. But the exact mechanism whereby tau spreads from cell to cell in the human brain remains to be clarified.

Our correspondent’s highlights from the symposium are meant as a fair representation of the scientific content presented. The views and opinions expressed on this page do not necessarily reflect those of Lundbeck.

References

1. Harrison TM et al. Ann Neurol 2019;85:229-40 

2. Jack CR et al. Brain 2018;141:1517–28

3. Pontecorvo MJ et al. Brain 2019;142:1723-35

4. Schöll M et al. Brain 2017;140:2286-94

5. La Joie R et al. Sci Transl Med 2020 Jan 1;12(524):eaau5732

6. Ossenkoppele R et al. JAMA Neurology 2020;77:632-42

7. Franzheimer N et al. Nat Commun 2019;10:1766

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